T:\\n ...\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6396938","0.63250375","0.61931926","0.6181083","0.60503036","0.6019446","0.597","0.5902527","0.58856195","0.5864737","0.58281857","0.57671076","0.57660705","0.5757237","0.573097","0.57248074","0.57248074","0.57069016","0.56881464","0.5687392","0.5686203","0.5686203","0.56861","0.5662305","0.56605315","0.56482303","0.5648025","0.5629078","0.5623478","0.56232226","0.5619148","0.5614399","0.5608755","0.5599784","0.55849445","0.5563676","0.5558614","0.5555767","0.5551515","0.5548764","0.55038255","0.549362","0.5491354","0.5482948","0.54776186","0.5473473","0.5468946","0.545529","0.5452817","0.5451986","0.54487294","0.5441447","0.5436852","0.5433126","0.5430025","0.54085827","0.539921","0.53919","0.5380436","0.5379964","0.53755283","0.53739923","0.5370586","0.53694826","0.5362696","0.53600734","0.5353865","0.5339322","0.5334842","0.53347206","0.5326459","0.5322827","0.53107816","0.52961123","0.52942014","0.5285641","0.5268396","0.52671856","0.52471626","0.5241321","0.5238018","0.5233206","0.5229059","0.5226925","0.52234495","0.52188057","0.5214753","0.5212405","0.5204148","0.519946","0.5197421","0.5195538","0.51950705","0.51859856","0.51852304","0.5181673","0.5174132","0.51738936","0.5171282","0.51671034"],"string":"[\n \"0.6396938\",\n \"0.63250375\",\n \"0.61931926\",\n \"0.6181083\",\n \"0.60503036\",\n \"0.6019446\",\n \"0.597\",\n \"0.5902527\",\n \"0.58856195\",\n \"0.5864737\",\n \"0.58281857\",\n \"0.57671076\",\n \"0.57660705\",\n \"0.5757237\",\n \"0.573097\",\n \"0.57248074\",\n \"0.57248074\",\n \"0.57069016\",\n \"0.56881464\",\n \"0.5687392\",\n \"0.5686203\",\n \"0.5686203\",\n \"0.56861\",\n \"0.5662305\",\n \"0.56605315\",\n \"0.56482303\",\n \"0.5648025\",\n \"0.5629078\",\n \"0.5623478\",\n \"0.56232226\",\n \"0.5619148\",\n \"0.5614399\",\n \"0.5608755\",\n \"0.5599784\",\n \"0.55849445\",\n \"0.5563676\",\n \"0.5558614\",\n \"0.5555767\",\n \"0.5551515\",\n \"0.5548764\",\n \"0.55038255\",\n \"0.549362\",\n \"0.5491354\",\n \"0.5482948\",\n \"0.54776186\",\n \"0.5473473\",\n \"0.5468946\",\n \"0.545529\",\n \"0.5452817\",\n \"0.5451986\",\n \"0.54487294\",\n \"0.5441447\",\n \"0.5436852\",\n \"0.5433126\",\n \"0.5430025\",\n \"0.54085827\",\n \"0.539921\",\n \"0.53919\",\n \"0.5380436\",\n \"0.5379964\",\n \"0.53755283\",\n \"0.53739923\",\n \"0.5370586\",\n \"0.53694826\",\n \"0.5362696\",\n \"0.53600734\",\n \"0.5353865\",\n \"0.5339322\",\n \"0.5334842\",\n \"0.53347206\",\n \"0.5326459\",\n \"0.5322827\",\n \"0.53107816\",\n \"0.52961123\",\n \"0.52942014\",\n \"0.5285641\",\n \"0.5268396\",\n \"0.52671856\",\n \"0.52471626\",\n \"0.5241321\",\n \"0.5238018\",\n \"0.5233206\",\n \"0.5229059\",\n \"0.5226925\",\n \"0.52234495\",\n \"0.52188057\",\n \"0.5214753\",\n \"0.5212405\",\n \"0.5204148\",\n \"0.519946\",\n \"0.5197421\",\n \"0.5195538\",\n \"0.51950705\",\n \"0.51859856\",\n \"0.51852304\",\n \"0.5181673\",\n \"0.5174132\",\n \"0.51738936\",\n \"0.5171282\",\n \"0.51671034\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5674374"},"document_rank":{"kind":"string","value":"23"}}},{"rowIdx":92977,"cells":{"query":{"kind":"string","value":"Try to find nfo file in movie directory and search in nfo IMDB idetifier"},"document":{"kind":"string","value":"def IMDB_idenifier_search(self):\n\tdir_list = os.listdir(self.MovieDir)\n\tdir_count = 0\n\tfor x in dir_list:\n\t if x.split(\".\")[-1].lower()==\"nfo\":\n\t\tprint \"find NFO in %i list\" % dir_count\n\t\tbreak\n\t dir_count=dir_count+1\n\ttry:\t\n\t nfo_file = open(self.MovieDir+\"/\"+dir_list[dir_count],\"r\")\n\t buffor = nfo_file.read()\n\t nfo_file.close\n\t #IMDB line in nfo: iMDB: http://www.imdb.com/title/tt1219289/\t \n\t char_count = 0\n\t while (char_count+len(\"http://www.imdb.com/title/\")) < len(buffor):\n\t\tif buffor[char_count:(char_count+len(\"http://www.imdb.com/title/\"))] == \"http://www.imdb.com/title/\":\n\t\t #print \"%s\" % str(char_count+len(\"http://www.imdb.com/title/\"))\n\t\t self.dd11 = IMDB_begining = char_count+len(\"http://www.imdb.com/title/\")\n\t\t break\n\t\tchar_count=char_count+1\n\t char_count=IMDB_begining+1 \n\t while char_count < len(buffor):\n\t\tif buffor[char_count:(char_count+1)] == \"/\":\n\t\t #print \"%s\" % str(char_count)\n\t\t self.dd22 = IMDB_ending = char_count\n\t\t break\n\t\tchar_count=char_count+1\n\t return buffor[IMDB_begining:IMDB_ending]\t\n\t#tutaj trzeba sprawdzienia IMDB numeru jesli jest oka to zwraca informacje jesli jest nie oka to zwraca blad\n\texcept:\t \n\t print \"blad IMBN\"\n\t return False"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def MovieScan():\r\n for root, dirnames, filenames in os.walk(dlPath):\r\n for extend in movtypes:\r\n for filename in fnmatch.filter(filenames, extend):\r\n matches.append(os.path.join(root, filename))\r\n print(os.path.join(root, filename))\r\n shutil.move(os.path.join(root, filename), os.path.join(moviePath, filename))\r\n print color.GREEN + 'File succesfully moved!' + color.ENDC\r\n print 'Finished Scanning For Movies'","def findMayaFiles(directory):\n\n pass","def _findVideoFile(self, videofile):\n for vf in self.vflist:\n if vf.startswith(videofile + '.'):\n videosource = os.path.join(self.vfdir, vf)\n return videosource","def test_afni_nifti():\n im = ndar.Image('test_data/06025B_mprage.nii.gz')\n assert os.path.exists('%s.BRIK' % im.afni)\n assert os.path.exists('%s.HEAD' % im.afni)","def provoke_and_handle_FileNotFoundError():\n try:\n with open(\"NEIN.mp3\") as f:\n print(\"well\")\n except FileNotFoundError as fnfe:\n print(f\"Sorry! {fnfe}\")","def find_movie(imdb_file, title_regex):\n\n process = subprocess.run([\n \"grep\",\n \"-i\", # Case insensitive\n f'movie\\t[^\\t]*{title_regex}', # Only match movies\n imdb_file\n ], stdout=subprocess.PIPE)\n hits = [dict(zip(COLUMNS, hit.decode(\"utf-8\").split(\"\\t\")))\n for hit in process.stdout.split(b\"\\n\")[:-1]]\n # Try to filter out irrelevant hits, e.g. that don't yet exist or are porn\n legitimate_hits = [hit for hit in hits\n if hit[\"startYear\"] != \"\\\\N\" and\n hit[\"isAdult\"] == \"0\"]\n return legitimate_hits","def TvScan():\r\n for root, dirnames, filenames in os.walk(dlPath):\r\n for key, location in tvshows.iteritems():\r\n for filename in fnmatch.filter(filenames, key):\r\n matches.append(os.path.join(root, filename))\r\n print(os.path.join(root, filename))\r\n shutil.move(os.path.join(root, filename), os.path.join(location, filename))\r\n print color.GREEN + 'File succesfully moved!' + color.ENDC\r\n # Send the file through another filter in case of lower case filenames \r\n for filename in fnmatch.filter(filenames, key.lower()):\r\n matches.append(os.path.join(root, filename))\r\n print(os.path.join(root, filename))\r\n shutil.move(os.path.join(root, filename), os.path.join(location, filename))\r\n print color.GREEN + 'File succesfully moved!' + color.ENDC\r\n print 'Finished Scanning For TV Shows'","def imdb_load():\n for root, dirs, filenames in os.walk(os.path.dirname(__file__) + \"/imdb\"):\n for file_name in filenames:\n if file_name.find(\".json\") > 0:\n Movie.imdb_load_file(os.path.dirname(__file__) + \"/imdb/\" + file_name)\n return Movie.__movies","def MusicScan():\r\n for root, dirnames, filenames in os.walk(dlPath):\r\n for extend in mustypes:\r\n for filename in fnmatch.filter(filenames, extend):\r\n matches.append(os.path.join(root, filename))\r\n print(os.path.join(root, filename))\r\n shutil.move(os.path.join(root, filename), os.path.join(musicPath, filename))\r\n print color.GREEN + 'File succesfully moved!' + color.ENDC\r\n print 'Finished Scanning For Music'","def lookup_ifproc_file(obsnum, path='/data_lmt/ifproc/', debug=False):\n paths = [path]\n\n if 'ifproc' not in path:\n paths += ['/data_lmt/ifproc/']\n if 'lmtttpm' not in path:\n paths += ['/data_lmt/lmttpm/']\n if 'tel' not in path:\n paths += ['/data_lmt/tel/']\n\n if debug:\n print(paths)\n\n for path in paths:\n filenames = glob.glob(os.path.join(path, '*_%06d_*.nc' % obsnum))\n if len(filenames) > 0:\n if debug:\n print('found %s' % (filenames[0]))\n return filenames[0]\n return ''\n #filename = ''\n #for file in os.listdir(path):\n # if fnmatch.fnmatch(file,'*_%06d_*.nc'%(obsnum)):\n # print('found %s'%(file))\n # filename = path+file\n #if filename == '':\n #print('lookup_ifproc_file: no file for obsnum ', obsnum)\n #if 'lmttpm' not in path:\n # print('look in lmttpm')\n # return lookup_ifproc_file(obsnum,path='/data_lmt/lmttpm/')\n #return(filename)","def searchImage(text):\n creds = None\n # The file token.json stores the user's access and refresh tokens, and is\n # created automatically when the authorization flow completes for the first\n # time.\n if os.path.exists('token.json'):\n creds = Credentials.from_authorized_user_file('token.json', SCOPES)\n # If there are no (valid) credentials available, let the user log in.\n if not creds or not creds.valid:\n if creds and creds.expired and creds.refresh_token:\n creds.refresh(Request())\n else:\n flow = InstalledAppFlow.from_client_secrets_file(\n 'credentials.json', SCOPES)\n creds = flow.run_local_server(port=0)\n # Save the credentials for the next run\n with open('token.json', 'w') as token:\n token.write(creds.to_json())\n\n service = build('drive', 'v3', credentials=creds)\n\n results_length = 0\n results_message = []\n nextPageToken = \"first\"\n flex_dict = {\n \"type\": \"carousel\",\n \"contents\": []\n }\n\n with open(\"episode_info.json\", 'r', encoding=\"utf-8\") as f:\n episode_info = json.load(f)\n\n # imageFolder: https://drive.google.com/drive/u/0/folders/1CH7i08P4NK0WkhASe4_qs92fsL2Mz0tM\n\n while nextPageToken != []:\n if nextPageToken == \"first\":\n results = service.files().list(q=\"'1CH7i08P4NK0WkhASe4_qs92fsL2Mz0tM' in parents and fullText contains '{}'\".format(text), pageSize=1000,\n fields=\"nextPageToken, files(id, name)\").execute()\n else:\n results = service.files().list(q=\"'1CH7i08P4NK0WkhASe4_qs92fsL2Mz0tM' in parents and fullText contains '{}'\".format(text), pageSize=1000, pageToken=nextPageToken,\n fields=\"nextPageToken, files(id, name)\").execute()\n items = results.get('files', [])\n nextPageToken = results.get('nextPageToken', [])\n print(len(items))\n for item in items:\n img_url = \"https://lh3.googleusercontent.com/d/{}=w1080\".format(\n item['id'])\n # print(u'{0} ({1})'.format(item['name'], img_url))\n\n positino_left_brackets = item['name'].find(\"【\")\n position_right_brackets = item['name'].find(\"】\")\n position_dot = item['name'].find(\".jpg\")\n img_episode = item['name'][positino_left_brackets +\n 1:position_right_brackets]\n img_title = item['name'][position_right_brackets+1:position_dot]\n if img_title.find(text) != -1:\n results_length += 1\n if len(flex_dict[\"contents\"]) < 12:\n try:\n esfio = episode_info[img_episode][\"Every Spongebob Frame In Order\"]\n chn_episode_title = episode_info[img_episode][\"中文集數名稱\"]\n eng_episode_title = episode_info[img_episode][\"英文集數名稱\"]\n except:\n pass\n\n new_bubble_flex_message = {}\n\n with open(\"bubble_flex_message.json\", \"r\", encoding='utf-8') as f:\n new_bubble_flex_message = json.load(f)\n\n new_bubble_flex_message[\"hero\"][\"url\"] = img_url\n new_bubble_flex_message[\"body\"][\"contents\"][0][\"contents\"][0][\"text\"] = img_title\n new_bubble_flex_message[\"body\"][\"contents\"][1][\"contents\"][0][\"contents\"][1][\"text\"] = img_episode\n new_bubble_flex_message[\"body\"][\"contents\"][1][\"contents\"][1][\"contents\"][1][\"text\"] = esfio\n new_bubble_flex_message[\"body\"][\"contents\"][1][\"contents\"][2][\"contents\"][1][\"text\"] = chn_episode_title\n new_bubble_flex_message[\"body\"][\"contents\"][1][\"contents\"][3][\"contents\"][1][\"text\"] = eng_episode_title\n new_bubble_flex_message[\"footer\"][\"contents\"][0][\"action\"][\"data\"] = \"傳\" + img_url\n new_bubble_flex_message[\"footer\"][\"contents\"][1][\"action\"][\"uri\"] = img_url\n\n flex_dict[\"contents\"].append(new_bubble_flex_message)\n if len(flex_dict[\"contents\"]) == 12:\n if len(results_message) < 5:\n results_message.append(FlexSendMessage(\n alt_text=\"搜尋結果\",\n contents=flex_dict)\n )\n if len(results_message) == 5:\n print(\"len(results_message)1: \", len(results_message))\n return {\"length\": results_length, \"top5_url_list\": results_message}\n flex_dict[\"contents\"] = []\n if nextPageToken == []:\n if len(flex_dict[\"contents\"]) != 0:\n if len(results_message) < 5:\n results_message.append(FlexSendMessage(\n alt_text=\"搜尋結果\",\n contents=flex_dict)\n )\n print(\"len(results_message)2: \", len(results_message))\n return {\"length\": results_length, \"top5_url_list\": results_message}\n\n print(\"len(results_message)3: \", len(results_message))\n return {\"length\": results_length, \"top5_url_list\": results_message}","def process(self):\n try:\n existing_movie = os.listdir(self.movie_root_path)\n except:\n os.makedirs(self.movie_root_path)\n existing_movie = os.listdir(self.movie_root_path)\n\n if not [movie for movie in existing_movie if self.title.lower() in movie.lower()]:\n if self.has_video_extension:\n self.move_media()\n else:\n self.extract_media()\n else:\n Logger.log('[-] %s already exists. Skipping...' % self.title)","def identify_file(self, file):","def test_afni_minc():\n im = ndar.Image('test_data/a.mnc')\n assert os.path.exists('%s.BRIK' % im.afni)\n assert os.path.exists('%s.HEAD' % im.afni)","def find_file(lines, MF=1):\n v = [l[slices['MF']] for l in lines]\n n = len(v)\n cmpstr = '%2s' % MF # search string\n i0 = v.index(cmpstr) # first occurrence\n i1 = n - v[::-1].index(cmpstr) # last occurrence\n return lines[i0: i1]","def extract_file_observable_info(filename):\n # all possible observables\n all_obs = [\"He4_E\", \"He4_rptp\", \"H3_E\", \"fT12\"]\n obs_found = []\n\n # search for these in the filename\n for obs in all_obs:\n match = search(obs, filename)\n if match:\n obs_found.append(obs)\n if not obs_found:\n print(\"No matches were found in this file name\")\n return None\n return obs_found","def download_episode(self, filmid):\n self.logger.debug('download_episode')\n if not self._test_download_path(self.settings.getDownloadPathEpisode()):\n return\n film = self.database.retrieve_film_info(filmid)\n if film is None:\n return\n\n (filmurl, extension,) = self._get_film_url_and_extension(film)\n\n # detect season and episode\n (season, episode, fninfo,) = self._season_and_episode_detect(film)\n\n # determine names\n showname = mvutils.cleanup_filename(film.show)[:64]\n namestem = mvutils.cleanup_filename(film.title)[:80]\n if not namestem:\n namestem = u'Episode-{}'.format(film.filmid)\n if not showname:\n showname = namestem\n\n # review name\n if self.settings.getReviewName():\n (namestem, confirmed) = self.notifier.get_entered_text(namestem, 30986)\n namestem = mvutils.cleanup_filename(namestem)\n if len(namestem) < 1 or confirmed is False:\n return\n\n # prepare download directory and determine sequence number\n pathname = self.settings.getDownloadPathEpisode() + showname + '/'\n sequence = 1\n if xbmcvfs.exists(pathname):\n (_, epfiles,) = xbmcvfs.listdir(pathname)\n for epfile in epfiles:\n match = re.search(r'^.* - \\(([0-9]*)\\)\\.[^/]*$', epfile)\n if match and match.groups():\n if sequence <= int(match.group(1)):\n sequence = int(match.group(1)) + 1\n else:\n xbmcvfs.mkdir(pathname)\n\n filename = showname + ' - ' + fninfo + \\\n namestem + (u' - (%04d)' % sequence)\n # download the stuff\n if self._download_files(film, filmurl, pathname, filename, extension):\n self._make_series_nfo_files(\n film, filmurl, pathname, filename, season, episode, sequence)","def video_files():\n p = parse_cmdline(get_parser=get_parser_files)\n log.setup_main_handler(\n mods=(\"fogtools\", \"typhon\", \"fogpy\", \"sattools\", \"fcitools\", \"satpy\",\n \"pyresample\"),\n level=logging.INFO)\n vis.show_video_abi_glm(\n files=p.files,\n img_out=p.filename_pattern_image,\n vid_out=p.filename_pattern_video,\n out_dir=p.outdir)\n print(\"Files written to:\", p.outdir)","def writeCDNAresults(self, target, target_folder, outf, contigf):\n if self.params['assembler'] == 'newbler':\n contigf = os.path.join(self.params['working_dir'], target_folder, \"assembly\", \"assembly\", \"454AllContigs.fna\")\n isotigsf = os.path.join(self.params['working_dir'], target_folder, \"assembly\", \"assembly\", \"454IsotigsLayout.txt\")\n readstatusf = os.path.join(self.params['working_dir'], target_folder, \"assembly\", \"assembly\", \"454ReadStatus.txt\")\n else:\n logger.info(\"WARNING writeCDNAresults called when assembler was not Newbler\")\n return None\n if not (os.path.exists(contigf) and os.path.exists(isotigsf) and os.path.exists(readstatusf)):\n logger.info(\"CDNA WARNING MISSING FILE!! %s %s\" % (target, self.params['sample']))\n logger.info(contigf, os.path.exists(contigf))\n logger.info(isotigsf, os.path.exists(isotigsf))\n logger.info(readstatusf, os.path.exists(readstatusf))\n return None\n #Storage data structures:\n isogroups = {} # A dict of isogroups which each contain an in-order list of contigs\n readcounts = Counter() # A dict of all contigs, these contain read counts (from ReadStatus)\n contig_orientation = {}\n contig_to_isogroup = {}\n contig_idx = SeqIO.index(contigf, \"fasta\")\n # Parse isotigsf:\n igroup = \"\"\n #print self.params['sample'], target, \"Parsing isotigsf: %s\" % isotigsf\n for l in open(isotigsf, 'r'):\n #Handle lines with only a '\\n'\n if l == '\\n':\n pass\n #Handle lines for isogroup:\n elif l[0:9] == '>isogroup':\n igroup = l.strip().split()[0].strip(\">\")\n #Handle lines containing all contigs:\n elif l.strip().split()[0] == 'Contig':\n l2 = l.strip().split()\n contigs = map(lambda x: \"contig\" + x, l2[2:-1])\n isogroups[igroup] = contigs\n for contig in contigs:\n if contig not in contig_orientation:\n contig_orientation[contig] = '+'\n contig_to_isogroup[contig] = igroup\n else:\n raise exceptions.FatalError('Contig %s in %s more than once' % (contig, contigf))\n #Handle lines containing contig orientation info:\n elif l[0:6] == 'isotig':\n l2 = l[l.find(\" \") + 1: l.rfind(\" \") - 1]\n l3 = [l2[i:i+6] for i in range(0, len(l2), 6)]\n for i in range(len(l3)):\n if l3[i][0] == '<':\n # contig is in reverse orientation\n contig = isogroups[igroup][i]\n contig_orientation[contig] = '-'\n #print self.params['sample'], target, \"Parsed isotigsf, contigs:\", len(isogroups), \"contig_to_isogroup\", len(contig_to_isogroup), \"contig_orientation\", len(contig_orientation)\n #Now parse readstatus:\n inf = open(readstatusf, 'r')\n inf.readline() # discard first line\n for l in inf:\n l2 = l.strip().split('\\t')\n #Determine if this read was assembled\n if len(l2) == 8:\n contig = l2[2]\n # Note that there are some built in limits to the number of contigs that can be in an isogroup:\n # http://contig.wordpress.com/2010/08/31/running-newbler-de-novo-transcriptome-assembly-i/\n # These won't appear in the IsotigsLayout.txt, but ARE in the ReadStatus.txt file.\n if contig in contig_to_isogroup:\n readcounts[contig_to_isogroup[contig]] += 1\n else:\n readcounts['ExceedsThreshold'] += 1\n #print self.params['sample'], target, \"Parse read status\"\n\n #Finally, output all of this information appropriately:\n countsf = open(os.path.join(self.params['finished_dir'], \"isogroup_read_counts.tsv\"), 'a')\n sample = self.params['sample']\n #First write out readcounts: sample \\t target \\t isogroup \\t readcount\n for isogroup in readcounts:\n countsf.write('\\t'.join([sample, target, isogroup, str(readcounts[isogroup])]) + '\\n')\n countsf.close()\n #print self.params['sample'], target, \"Wrote readcounts\"\n\n #Next write the contigs in proper order and orientation:\n ncontigs = 0\n nisogroups = 0\n for isogroup in isogroups:\n nisogroups += 1\n for contig in isogroups[isogroup]:\n ncontigs += 1\n seqrec = contig_idx[contig]\n #print self.params['sample'], target, seqrec\n if contig_orientation[contig] == '-':\n seqrec.seq = seqrec.seq.reverse_complement()\n #print self.params['sample'], target, seqrec\n seqrec.name = seqrec.id = sample + \"_:_\" + target + \"_:_\" + isogroup + \"|\" + contig\n #print self.params['sample'], target, seqrec\n SeqIO.write(seqrec, outf, \"fasta\")\n ## TODO: add support for the ExceedsThreshold contigs\n logger.info(\"Sample: %s target: %s iteration: %s Finished writing %s contigs, %s isogroups \" % (self.params['sample'],\n target, self.params['iteration'], ncontigs, nisogroups))","def extract_nac_pet(dicom_folder):\n from glob import glob\n import os\n import shutil\n import re\n from nipype.interfaces.dcm2nii import Dcm2nii\n\n def atoi(text):\n return int(text) if text.isdigit() else text\n\n def natural_keys(text):\n return [atoi(c) for c in re.split('(\\d+)', text)]\n\n files = glob(os.path.join(os.path.abspath(dicom_folder), '*'))\n sorted_files = sorted(files, key=natural_keys)\n nac_pet_files = sorted_files[-127:]\n for f in nac_pet_files:\n shutil.copy(f, os.getcwd())\n dcm2nii = Dcm2nii()\n dcm2nii.inputs.source_dir = os.getcwd()\n nii_outputs = dcm2nii.run().outputs.converted_files\n print (nii_outputs)\n return nii_outputs[0]","def get_movie_info_from_folder(folder):\n if not os.path.exists(folder):\n raise ValueError(\"folder does not exists\")\n for file in os.listdir(folder):\n filename = os.path.join(folder, file)\n if os.path.isfile(filename):\n e = ET.parse(filename).getroot()\n for result in e[1]:\n attributes = dict()\n for bindings in result:\n attributes[bindings.attrib['name']] = bindings[0].text\n if len(attributes['title']) > 0:\n yield Movie(**attributes)","def check_for_3dm(folder):\n find=False;\n if not os.path.exists(folder): return;\n \n walk=os.walk(folder);\n for dirpath, dirnames, filenames in walk:\n for file in filenames:\n ext=file.split(\".\")[-1];\n if ext.upper()==\"3DM\":\n find = True;\n return find;\n \n return find","def _discover_in_dir(self, dir_path: str) -> Optional[str]:\n for this_file in os.listdir(dir_path):\n if this_file.endswith('.esvi'):\n return os.path.join(dir_path, this_file)\n\n return None","def search_string(command):\n try:\n my_file.search_string(command[1])\n except FileNotFoundError:\n print('No file has been read yet')","def main(\n):\n music_home = \"/home/banana/music\"\n for inode in list_dir(music_home):\n if basename(inode) in [\n \"annotate\",\n \"metadata\",\n \"sped-up\",\n \"tracklists\",\n ] or isfile(inode):\n continue\n convert(inode)","def _find_tif_file(self):\n name = self.results_file.name[:-12] + \".tif\"\n try:\n tif_file = next(self.results_file.parent.glob(name))\n return tif_file\n except StopIteration:\n print(f\"Tif not found for {name}\")\n return None","def get_files_match(matches, dname, Lshow, Ldir=False):\n matched_files=[]\n ### two for-loop is converted\n for fname in os.listdir(dname):\n #print(f\"{fname}\")\n for match in matches:\n if re.search(match, fname):\n ### if it is dir skip\n if os.path.isdir(fname) and not Ldir:\n continue\n if Lshow:\n print(f\"detect {fname}\") # in {match} {matches}\")\n matched_files.append(fname)\n return matched_files","def search(self, id):\n\n db = self.connection(\"imdb\")\n\n try:\n cur = db.cursor()\n sql = \"SELECT * FROM film WHERE id = %s;\"\n cur.execute(sql, (id,))\n return cur.fetchall()\n except:\n print(\"Cannot find the film!\")\n\n db.close()","def load_enron():\n connection=apsw.Connection(\"enron.db\")\n cursor=connection.cursor()\n\n \n cursor.execute(\"CREATE VIRTUAL TABLE corpus USING fts4(rowid, title, body);\")\n\n\n enrondir = \"/Users/jonas/Downloads/enron_mail_20110402/maildir\"\n\n pi = 0\n \n for dirpath, dirnames, filenames in os.walk(enrondir):\n for filename in filenames:\n try:\n subject, body = enron.parse_file(os.path.join(dirpath, filename))\n \n cursor.execute(\"insert into corpus values(?,?,?)\", (pi, subject, body))\n except:\n pass\n \n if pi % 100 == 0:\n print pi\n pi += 1","def detect(self, fstring, fname=None):\n return True","def test_find_processed_file(self):\n\n this_file_name = tornado_io.find_processed_file(\n directory_name=TORNADO_DIRECTORY_NAME, year=YEAR,\n raise_error_if_missing=False)\n\n self.assertTrue(this_file_name == TORNADO_FILE_NAME)","def __searchFiles(self):\n self.ui.showFindFilesDialog(self.textForFind())","def download_movie(self, filmid):\n self.logger.debug('download_movie')\n if not self._test_download_path(self.settings.getDownloadPathMovie()):\n return\n film = self.database.retrieve_film_info(filmid)\n if film is None:\n return\n (filmurl, extension,) = self._get_film_url_and_extension(film)\n # try to create a good name for the downloaded file\n namestem = mvutils.cleanup_filename(film.title)[:80]\n if not namestem:\n # try to take the show name instead...\n namestem = mvutils.cleanup_filename(film.show)[:64]\n if not namestem:\n namestem = u'Film'\n namestem = namestem + '-{}'.format(film.filmid)\n elif self.settings.getMovieNameWithShow():\n showname = mvutils.cleanup_filename(film.show)[:64]\n if showname:\n namestem = showname + ' - ' + namestem\n # review name\n if self.settings.getReviewName():\n (namestem, confirmed) = self.notifier.get_entered_text(namestem, 30986)\n namestem = mvutils.cleanup_filename(namestem)\n if len(namestem) < 1 or confirmed is False:\n return\n # determine destination path and film filename\n if self.settings.getUseMovieFolder():\n pathname = self.settings.getDownloadPathMovie() + namestem + '/'\n filename = namestem\n else:\n pathname = self.settings.getDownloadPathMovie()\n filename = namestem\n # check for duplicate\n # keep\n if self.settings.getFileExistsAction() == 1 and xbmcvfs.exists(pathname + filename + extension):\n return\n # prompt\n if self.settings.getFileExistsAction() == 0:\n while xbmcvfs.exists(pathname + filename + extension):\n (filename, confirmed) = self.notifier.get_entered_text(filename, 30987)\n filename = mvutils.cleanup_filename(filename)\n if len(filename) < 1 or confirmed is False:\n return\n\n # download the stuff\n if self._download_files(film, filmurl, pathname, filename, extension):\n self._make_movie_nfo_file(film, filmurl, pathname, filename)\n else:\n self.logger.debug('download_movie ERROR')","def is_hmmer_hmmsearch_file(f):\n #HMMER output doesn't have a specific file extension\n with open(f) as hmmer_file:\n try:\n return hmmer_file.next().startswith(\"% hmmsearch\")\n except StopIteration:\n return False","def findByFileName(fileName, get_movie_name_only = False):\r\n MovieName = 'MovieName'\r\n queryresult = None\r\n\r\n movienamequery = IOpenSubtitlesProvider.FormatQuery(\r\n {'query' : fileName})\r\n try:\r\n #send the query\r\n queryresult = IOpenSubtitlesProvider.GetServer().SearchSubtitles(\r\n IOpenSubtitlesProvider.GetToken(), \r\n [movienamequery])\r\n queryresult = queryresult['data']\r\n except Exception as eX:\r\n WriteDebug(eX)\r\n\r\n if queryresult:\r\n is_episode = queryresult[0]['MovieKind'] == 'episode'\r\n if get_movie_name_only: \r\n if is_episode:\r\n res = queryresult[0][MovieName]\r\n queryresult = Utils.getregexresults('\"(.*?)\"', res)[0]\r\n else:\r\n queryresult = queryresult[0][MovieName]\r\n else: queryresult = queryresult\r\n else:\r\n queryresult = None\r\n\r\n return queryresult","def find_calib_file(self, runnum=0) :\n cfile = find_calib_file_in_list_for_run(self.list_of_sorted_calib_files(), runnum)\n #cfile.print_member_data()\n if cfile is None : return ''\n else : return os.path.join(self.path, cfile.get_basename())","def fsearch(self,pattern,msg=None, killon=None ):\n import re\n current=0\n cpat=re.compile(pattern)\n\n for num,line in enumerate(self.f):\n if killon:\n kill = re.search(killon,line)\n if kill:\n # the kill phrase was found first, so die. \n return False\n current=re.search(cpat,line)\n if current:\n if msg:\n print msg\n break\n if not current:\n# print 'ERROR: Requested pattern ('+pattern+') not found in file: <'+self.f.name+ '>. Check file for correct structure. Exiting...'\n return False\n\n return line","async def movievotes(self, ctx: discord.ext.commands.Context, *args):\n print(\"-------------------------\")\n message_channel: discord.abc.Messageable = ctx.message.channel\n if len(args) == 1:\n print(\"Starting search\")\n api_key = self.botVariables.get_mashape_metacritic_key()\n search_term = (re.sub(r'([^\\s\\w]|_)+', '', args[0])).lower()\n request_search_link = \"https://api-marcalencc-metacritic-v1.p.mashape.com/search/\" + str(\n urllib.parse.quote(search_term)) + \"/movie?limit=20&offset=1\"\n # search all the films with the term given\n async with aiohttp.ClientSession() as session:\n # the website use get\n async with session.get(request_search_link, headers={'X-Mashape-Key': str(api_key),\n 'Accept': 'application/json'}) as resp:\n request_result = await resp.json()\n if len(request_result[0]['SearchItems']) > 0: # there is at least one film\n films_found = []\n max_prob = 0.0\n # decide the best film using string similarity\n for entry in request_result[0]['SearchItems']:\n entry_string = (re.sub(r'([^\\s\\w]|_)+', '', entry['Title'])).lower()\n film_similarity = BotMethods.similar(search_term, entry_string, None)\n if film_similarity > 0.7: # consider it only if it's > 0.7 (range is 0.0-1.0)\n films_found.append(\n self.FilmInfo(entry['Id'], entry['Title'], film_similarity)) # store that film in the array\n if film_similarity > max_prob: # search for max prob\n max_prob = film_similarity\n if film_similarity >= 1.0: # i have found the perfect string\n print(\"Perfect name found, search cycle stopped\")\n break # stop the for\n if len(films_found) > 0: # i have found at least one possible film\n film_web_id = \"\"\n for film in films_found: # search the film with the max name similarity in the array\n if film.similar == max_prob:\n print(\"Film Chosen: \" + film.film_name + \" - Film web id:\" + str(\n film.film_id) + \" - Sim.:\" + str(\n max_prob))\n film_web_id = film.film_id # get the film web id\n break\n # make request to get all necessary film informations\n request_search_link = \"https://api-marcalencc-metacritic-v1.p.mashape.com\" + str(film_web_id)\n async with aiohttp.ClientSession() as session:\n async with session.get(request_search_link, headers={'X-Mashape-Key': str(api_key),\n 'Accept': 'application/json'}) as resp: # the website use get\n request_result = await resp.json()\n if 'message' in request_result:\n await message_channel.send(\"*An error occurred downloading the data...*\")\n return\n # prepare the embed message\n embed = discord.Embed(title=str(request_result[0]['Title']),\n colour=discord.Colour(0xffcc00),\n url=\"http://www.metacritic.com\" + str(film_web_id),\n description=\"Metacritic votes about \" + str(\n request_result[0]['Title']) + \" by \" + str(\n request_result[0]['Director']) + \", released on \" + str(\n request_result[0]['ReleaseDate']),\n timestamp=datetime.utcfromtimestamp(time.time())\n )\n if 'ImageUrl' in request_result[0]:\n embed.set_thumbnail(url=str(request_result[0]['ImageUrl']))\n else:\n print(\"No ImageUrl found, no thumbnail set\")\n embed.set_author(name=ctx.message.author.name, url=\"\", icon_url=ctx.message.author.avatar_url)\n embed.set_footer(text=self.botVariables.get_description(),\n icon_url=self.botVariables.get_bot_icon())\n if len(request_result[0]['Rating']) > 0:\n # --- read users votes ---\n user_votes = \"Rating: \" + str(request_result[0]['Rating']['UserRating']) + \" (\" + str(\n request_result[0]['Rating']['UserReviewCount']) + \" votes)\"\n # --- read critic votes ---\n critic_votes = \"Rating: \" + str(request_result[0]['Rating']['CriticRating']) + \" (\" + str(\n request_result[0]['Rating']['CriticReviewCount']) + \" votes)\"\n # --- create fields ---\n embed.add_field(name=\"Critic Rating\", value=critic_votes)\n embed.add_field(name=\"User Rating\", value=user_votes)\n else:\n embed.add_field(name=\"No votes found...\",\n value=\"Looks like there are no votes for this film...\")\n # --- sending the message ---\n print(\"Sending film embed message\")\n await message_channel.send(embed=embed)\n else:\n print(\"No films found\")\n await message_channel.send(\"*No films found, check the name...*\")\n else:\n print(\"No films found\")\n await message_channel.send(\"*No films found, check the name...*\")\n else:\n await message_channel.send(\n \"**Usage:** \" + self.command_prefix + \"movievotes <film Title>, for more see \" + self.command_prefix + \"help movievotes\")\n print(\"-------------------------\")","def LoadMetadata(filename):\r\n## print filename\r\n globbed=glob.glob(os.path.join(os.path.dirname(filename),'*.zvi'))\r\n if globbed:\r\n return LoadZVIMetaData(globbed[0])\r\n globbed=glob.glob(os.path.join(os.path.dirname(filename),'*.xml'))\r\n if globbed:\r\n return LoadAxioVisionXMLMetaData(globbed[0])\r\n globbed=glob.glob(os.path.join(os.path.dirname(filename),'metadata.txt'))\r\n if globbed:\r\n return LoadMMMetaData(globbed[0])\r\n return None\r\n #no further valid options, crash horribly\r","def open(self):\n file = askopenfilename(\n initialdir=self.initial_directory,\n filetypes=(\n (\"Audio Video Interleave\", \"*.avi\"),\n (\"Matroska\", \"*.mkv\"),(\"MPEG-4 AVC\",\"*.mp4\"),\n )\n )\n if isinstance(file, tuple):\n return\n if os.path.isfile(file):\n self.play_film(file)","def find_FEfiles(self):\n \n\t\t# take each item in the list of files to eve.\n for i in self.files_to_find:\n filename1 = i[0] \n file1_dye = i[1]\n filename2 = i[2]\n file2_dye = i[3]\n out_file_prefix=i[4]\n\n # set filename as none to help identify when no match has been found below\n file1_filename = None\n file2_filename = None\n\n # search for a FE file which matches the filename pattern\n for afile in os.listdir(self.chosenfolder):\n # file 1\n if fnmatch.fnmatch(afile, filename1):\n file1_filename = afile\n \n # file 2\n if fnmatch.fnmatch(afile, filename2):\n file2_filename = afile\n \n # if both files have been identified add this to a new list\n if file1_filename and file2_filename:\n self.list_of_files.append((file1_filename, file1_dye, file2_filename, file2_dye,out_file_prefix))\n\t\t\t# if either file could not be identified report this.\n else:\n raise ValueError(\"no match for \" + filename1 + \" and \" + filename2)","def test_findfile_outdir(self):\n from ..io.meta import findfile\n outdir = '/blat/foo/bar'\n x = findfile('fibermap', night='20150101', expid=123, outdir=outdir)\n self.assertEqual(x, os.path.join(outdir, os.path.basename(x)))","def search_file(filename, term):\n try:\n filepath = root + filename\n with open(filepath) as file:\n return term in file.read().splitlines()\n except FileNotFoundError:\n with open(filepath,\"w+\") as file:\n return (search_file(filename, term))","def find(pattern):\n files = config.index.files(path_glob=\"*%s*\" % pattern)\n print_files(files)","def filesearch(word=\"\"):\n logger.info('Starting filesearch')\n file = []\n for f in glob.glob(\"*\"):\n if word[0] == \".\":\n if f.endswith(word):\n file.append(f)\n\n elif word in f:\n file.append(f)\n #return file\n logger.debug(file)\n return file","def find(location, path):\n\n index = AnnoyIndex(64, metric='hamming')\n index.load('live/phash_index.ann')\n\n # get the requested image\n if location == 'url':\n MAX_DOWNLOAD = 15 * 1024 * 1024\n response = requests.get(path, stream=True)\n size = 0\n content = bytearray()\n for chunk in response.iter_content(1024):\n size += len(chunk)\n content += chunk\n if size > MAX_DOWNLOAD:\n raise ValueError\n img = Image.open(BytesIO(content))\n else:\n img = Image.open(path)\n\n # get the image's phash\n phash = imagehash.phash(img)\n phash_arr = phash.hash.flatten()\n\n # find the closest mateches\n results = index.get_nns_by_vector(phash_arr, 16, include_distances=True)\n\n conn = sqlite3.connect('live/twitter_scraper.db')\n c = conn.cursor()\n\n basenames = []\n tweet_ids = []\n\n # look up the location of the match and its tweet info\n first = True\n for idx, score in map(list, zip(*results)):\n if not first and score > 8:\n break\n first = False\n\n print('score: {}'.format(score))\n c.execute('SELECT path, filename FROM annoy WHERE idx=(?)', (idx,))\n dirname, basename = c.fetchone()\n fullpath = os.path.join(dirname, basename)\n c.execute('SELECT id FROM info WHERE filename=(?) AND path=(?)', (basename, dirname))\n tweet_id = c.fetchone()\n print(tweet_id)\n tweet_id = tweet_id[0]\n\n print('local path: {}'.format(fullpath))\n print('direct link: https://pbs.twimg.com/media/{}'.format(basename))\n print('source tweet: https://www.twitter.com/statuses/{}'.format(tweet_id))\n print()\n\n basenames.append(basename)\n tweet_ids.append(tweet_id)\n\n conn.close()\n return basenames, tweet_ids","def extract_vob(in_vob, guid):\n\t#Detect interlacing.\n\tmediainfo_command = \"mediainfo --Inform='Video;%ScanType%,%ScanOrder%' \" + in_vob\n\tprint(mediainfo_command)\n\tprocess = subprocess.Popen(mediainfo_command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n\t(cout, cerr) = process.communicate()\n\texit_code = process.wait()\n\tif exit_code != 0:\n\t\traise Exception(\"Calling Mediainfo on {in_vob} failed with exit code {exit_code}.\".format(in_vob=in_vob, exit_code=exit_code))\n\tmediainfo_parts = cout.decode(\"utf-8\").split(\",\")\n\tis_interlaced = mediainfo_parts[0] == \"Interlaced\"\n\tfield_order = mediainfo_parts[1].lower().strip()\n\tprint(\"Interlace detection:\", is_interlaced, field_order, \"(\", mediainfo_parts, \")\")\n\n\tffmpeg_command = [\"ffmpeg\", \"-i\", in_vob]\n\tprint(ffmpeg_command)\n\tprocess = subprocess.Popen(ffmpeg_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n\t(cout, cerr) = process.communicate()\n\tprocess.wait() #Ignore the exit code. It always fails.\n\tvobinfo = cerr.decode(\"utf-8\")\n\ttracks = []\n\tfor match in re.finditer(r\" Stream #0:(\\d+)\\[0x[0-9a-f]+\\]: (\\w+): ([^\\n]+)\", vobinfo):\n\t\ttrack_nr = match.group(1)\n\t\ttrack_type = match.group(2)\n\t\ttrack_codec = match.group(3)\n\t\tnew_track = track.Track()\n\t\tnew_track.from_vob(track_nr, track_type, track_codec, is_interlaced, field_order)\n\t\tnew_track.file_name = guid + \"-T\" + str(new_track.track_nr) + \".\" + new_track.codec\n\t\tif new_track.type != \"unknown\":\n\t\t\ttracks.append(new_track)\n\n\t#Generate the parameters to pass to ffmpeg.\n\ttrack_params = [\"-i\", in_vob]\n\tfor track_metadata in tracks:\n\t\ttrack_params.append(\"-map\")\n\t\ttrack_params.append(\"0:\" + str(track_metadata.track_nr))\n\t\ttrack_params.append(\"-c\")\n\t\ttrack_params.append(\"copy\")\n\t\ttrack_params.append(track_metadata.file_name)\n\n\t#Extract all tracks.\n\tprint(\"---- Extracting tracks...\")\n\tffmpeg(*track_params)\n\n\treturn tracks","def watch_movie():\r\n if os.path.isfile('files/final_movie.mp4'): # if the file exists\r\n with open('files/final_movie.mp4', 'rb') as f:\r\n video_data = f.read()\r\n st.video(video_data)\r\n else: # if the file doesn't exist, let the user know\r\n st.header(\"You haven't created a movie yet!\")","def find_obsid_src(obsid, obs):\n if obs['readmode'] == 'CONTINUOUS':\n return None\n\n if obs['obs_mode'] == 'SECONDARY':\n return None\n\n if ((obs['instrume'] == 'ACIS') & (obs['detector'] == 'HRC-S')):\n return None\n\n xray_data = XRAY_DATA\n if not os.path.exists(xray_data):\n os.makedirs(xray_data)\n obsdir = os.path.join(xray_data, 'obs%05d' % obsid)\n if not os.path.exists(obsdir):\n os.makedirs(obsdir)\n\n no_source = os.path.join(obsdir, \"has_no_source\")\n if os.path.exists(no_source):\n return None\n\n srcfiles = glob(os.path.join(obsdir, '*src2*'))\n src_json = '{}/evtinfo.json'.format(obsdir)\n if len(srcfiles) and os.path.exists(src_json) and not REDO :\n src = get_source(obs['obsid'], obs['obi'], obsdir)\n return src\n\n # Fetch X-ray events\n tempdir = tempfile.mkdtemp(dir='/export/jeanconn/tempdir/')\n det = 'acis'\n if (obs['instrume'] == 'HRC'):\n det = 'hrc'\n bash('echo \"cd %s\\n obsid=%d\\n get %s2{evt2}\\n\" | arc5gl -stdin' % (tempdir, obs['obsid'], det))\n event_files = glob(\"%s/*evt2*gz\" % tempdir)\n if not len(event_files):\n return None\n if len(event_files) > 1:\n return None\n bash('gunzip %s' % event_files[0])\n event_files = glob(\"%s/*evt2*\" % tempdir)\n # Read processing keywords from the evt2 file\n f = fits.open(event_files[0])\n if 'ASOLFILE' not in f[1].header:\n return None\n proc_info = {'ASCDSVER': f[1].header['ASCDSVER'],\n 'CALDBVER': f[1].header['CALDBVER'],\n 'REVISION': f[1].header['REVISION'],\n 'ASOLFILE': f[1].header['ASOLFILE'],\n 'OBS_ID': f[1].header['OBS_ID']}\n # Get the X/Y for this detector from the header\n for i in range(1, 30):\n if 'TTYPE{}'.format(i) in f[1].header:\n if f[1].header['TTYPE{}'.format(i)] == 'x':\n proc_info['x_center'] = f[1].header['TCRPX{}'.format(i)]\n proc_info['y_center'] = f[1].header['TCRPX{}'.format(i + 1)]\n if f[1].header['TTYPE{}'.format(i)] == 'detx':\n proc_info['detx_center'] = f[1].header['TCRPX{}'.format(i)]\n proc_info['dety_center'] = f[1].header['TCRPX{}'.format(i + 1)]\n if ((proc_info['detx_center'] != proc_info['x_center'])\n or (proc_info['dety_center'] != proc_info['y_center'])):\n raise ValueError\n f.close()\n # Save processing keywords out to a file\n ph = open(src_json, 'w')\n ph.write(json.dumps(proc_info, indent=4, sort_keys=True))\n ph.close()\n # Setup to run celldetect\n pfiles = ';'.join([tempdir, ciao_env['PFILES'].split(';')[-1]])\n outlines1, stat = tcsh_shell(\"env PFILES={} punlearn celldetect\".format(pfiles), env=ciao_env)\n cmd = ('{} celldetect eenergy=0.9 infile=\"{}\" outfile=\"{}/{}_src2.fits\"'.format(\n 'env LD_LIBRARY_PATH=\"\" PFILES=\"{}\"'.format(pfiles), event_files[0], obsdir, obs['obsid']))\n # Run celldetect\n outlines2, stat = tcsh_shell(cmd, env=ciao_env)\n srcfiles = glob(os.path.join(obsdir, \"*src2*\"))\n if len(srcfiles):\n src = get_source(obs['obsid'], obs['obi'], obsdir)\n if src is not None:\n os.unlink(event_files[0])\n else:\n bash(\"touch {}\".format(no_source))\n print \"no sources in {}\".format(event_files[0])\n return src\n else:\n print(\"No src2 file was made\")\n return None","def find_file(path):\n return NotImplemented","def download(pattern):\n query = pattern.lower()\n videolist = getvideolist()\n filename = []\n for video in videolist:\n for value in video.values():\n if query in str(value).lower():\n filename.append(video[\"file\"])\n if filename:\n for name in filename:\n downloadvideo(name)\n else:\n safeprint(\"No video matching the given query was found.\")","def get_matches(self, file_map) -> dict:\r\n get_file_dict = {}\r\n match_dict = {\r\n 'GIF': re.findall(b'(?s)(\\x47\\x49\\x46\\x38\\x39\\x61.{80})', file_map),\r\n 'RTF': re.findall(b'(?s)(.{20}\\x35\\x30\\x34\\x65\\x34\\x37\\x30.{80}|.{20}\\x66\\x66\\x64\\x38\\x66\\x66.{80}|'\r\n b'.{20}\\x66\\x66\\x64\\x38\\x66\\x66\\x65\\x30\\x30\\x30\\x31\\x30.{80})', file_map),\r\n }\r\n if self.jpgsos:\r\n match_dict['JPG_SOS'] = jpg_sos(file_map)\r\n elif self.sof2sos:\r\n match_dict['JPG_SOF2SOS'] = jpg_sof2sos(file_map)\r\n elif self.jump:\r\n match_dict['JPG_JUMP'] = jpg_jump(file_map)\r\n else:\r\n match_dict['JPG'] = re.findall(b'(?s)(\\xff\\xd8\\xff\\xe0\\x00\\x10.{80})', file_map)\r\n match_dict['JPG2'] = re.findall(b'(?s)(\\xff\\xd8\\xff.{80})', file_map)\r\n if self.idat:\r\n match_dict['PNG_IDAT'] = idat(file_map)\r\n else:\r\n match_dict['PNG'] = re.findall(b'(?s)(\\x89\\x50\\x4e\\x47.{82})', file_map)\r\n m = re.match(br'^(?P<magic_beans>\\x49\\x49\\x2a\\x00[^\\x00\\x00]{2}.{80})',file_map,re.S)\r\n if m:\r\n match_dict['TIF'] = [m.group('magic_beans')]\r\n for file_type, regex_match in match_dict.items():\r\n if len(regex_match) > 0:\r\n get_file_dict[file_type] = regex_match\r\n return get_file_dict","def test_afni_afni():\n im = ndar.Image('test_data/NDAR_INVZU049GXV_image03_1326225820791.zip')\n assert im.afni == im.path(im.files['AFNI'][0])","def find_dsym_file(project, image_uuid):\n image_uuid = image_uuid.lower()\n try:\n return ProjectDSymFile.objects.filter(\n uuid=image_uuid,\n project=project\n ).select_related('file', 'file__blob').get()\n except ProjectDSymFile.DoesNotExist:\n pass\n try:\n return GlobalDSymFile.objects.filter(\n uuid=image_uuid\n ).select_related('file', 'file__blob').get()\n except GlobalDSymFile.DoesNotExist:\n return None","def findAudioFile(self,kinfilename):\r\n progress = QtGui.QProgressDialog(\"Searching for Audio File...\",QtCore.QString(), 0,0,parent = self)\r\n progress.setMinimumDuration(250)\r\n\r\n (filename, _) = os.path.splitext(os.path.basename(kinfilename))\r\n pattern = filename.split('_BPC')[0] + '.wav'\r\n fullpath = os.path.dirname(kinfilename)\r\n toSearch = []\r\n audiofilename = None\r\n for i in self.find(fullpath,'/'):\r\n toSearch.append(fullpath[:i])\r\n toSearch.reverse()\r\n toSearch.append(fullpath)\r\n for loc in toSearch:\r\n for filenames in os.walk(loc):\r\n for filename in filenames:\r\n if pattern in filename:\r\n desiredFile = filename\r\n for files in desiredFile:\r\n if pattern == files:\r\n audiofilename = os.path.join(filenames[0],files)\r\n progress.destroy()\r\n return audiofilename\r\n if audiofilename is None:\r\n progress.destroy()\r\n return audiofilename","def findframe(startdir,camera,grating,filename):\n grating = re.sub(\"\\/\",\"_\",grating)\n gdir = camera + grating\n if os.path.isfile(os.path.join(startdir,filename)):\n return(startdir)\n else:\n # now the grating directory\n if os.path.isfile(os.path.join(startdir,gdir,filename)):\n return(os.path.join(startdir,gdir))\n poswavedirs = glob.glob(os.path.join(startdir,gdir) + '/w*')\n wavedirs = []\n\n for pwd in poswavedirs:\n if re.search(\"w\\d+\",pwd):\n wavedirs.append(pwd) \n\n\n for wd in wavedirs:\n # alright, now we search the subdirs\n if os.path.isfile(os.path.join(wd,filename)):\n return(wd)\n\n return(None)","def readPlayerImageFiles(self):\n currentPath = os.path.dirname(os.path.abspath(__file__))\n listOfFileNames=[]\n for i in os.listdir(currentPath):\n if re.match(\"player\\_\\d+\",i): #i.endswith(\".gif\")\n listOfFileNames.append(currentPath+'/'+i)\n return listOfFileNames","def __searchOpenFiles(self):\n self.ui.showFindFilesDialog(self.textForFind(), openFiles=True)","def get_tanimoto_from_isomif_file(pdb1, pdb2, i1, i2):\n filename = pdb1 + 'h_' + str(i1) + '_match' + pdb2 + 'h_' + str(i2) + '.isomif'\n with open(str(HIVE / 'match' / filename), 'rb', 0) as file, \\\n mmap.mmap(file.fileno(), 0, access=mmap.ACCESS_READ) as s:\n if s.find(b'TANIM') != -1:\n pos = s.find(b'TANIM')\n tanim = float(s[pos+6 : pos+12].decode('utf-8'))\n else:\n return -1\n return tanim","def main():\n base_dir = '/home/sjimenez/imagenes_prueba'\n out_dir = '/home/sjimenez/easy_analysis'\n for _, _, files in os.walk(base_dir, topdown=False):\n for f in files:\n print('--------- {} ---------'.format(f))\n act_dir = osp.join(base_dir, f)\n act_im = cv2.imread(act_dir)\n if act_im is not None:\n get_image_stats(act_im, out_dir, f)\n else:\n print('Not able to open the image')","def _run_lyrics_nogui(self):\n self.read_files()\n\n # find lyrics\n self._log_print(msg_GREEN=\"Searching for lyrics\")\n\n self.save_lyrics()\n\n if not self.write_tags():\n self._log_print(msg_WHITE=\"Cannot write tags because there are no \"\n \"coresponding files\")\n else:\n self._log_print(msg_GREEN=\"Done\")","def find_files(directory, extension, magictext):\n global files_logged\n global found_text\n dir_path = os.path.abspath(directory)\n dir_files = os.listdir(dir_path)\n for file in dir_files:\n if file.endswith(extension) and file not in files_logged:\n logger.info('New file found: {}'.format(file))\n files_logged.append(file)\n if file.endswith(extension):\n file_path = os.path.join(dir_path, file)\n if find_string_in_files(file_path, magictext):\n break\n for file in files_logged:\n if file not in dir_files:\n logger.info('File deleted: {}'.format(file))\n files_logged.remove(file)\n found_text[file] = 0","def demo():\n logging.basicConfig(level=logging.INFO, format=\"%(message)s\")\n fcm = FMQLCacher(\"Caches\")\n fcm.setVista(\"CGVISTA\", \"http://vista.caregraf.org/fmqlEP\")\n \"\"\"\n for i, scheme in enumerate(fcm.describeSchemaTypes()):\n if \"count\" in scheme:\n print \"%d: %s (%s)\" % (i, scheme[\"number\"], scheme[\"count\"])\n else:\n print \"%d: %s\" % (i, scheme[\"number\"])\n \"\"\"\n for entry in fcm.describeFileEntries(\"9_6\", cstop=\"1000\"):\n print entry[\"uri\"][\"label\"]","def _search_path_to_file(self, directory, binary_name):\n for root, dirs, files in os.walk(directory):\n if binary_name in files:\n return os.path.join(root, binary_name)\n raise micp_kernel.NoExecutableError","def file_name_search():\n directory = \"/Users/andrewpowers/Documents/server/fastq_pass\"\n\n for file in os.listdir(directory):\n output_file = re.sub('fastq', 'fasta', file)\n os.system(bash_command.format(directory+\"/\"+file, output_file))\n print('File {} converted to fasta.'.format(file))\n print('Conversion Done.')","def findReferenceImage(modelfile):\n\n try:\n\n dirname = op.dirname(modelfile)\n prefixes = [getFIRSTPrefix(modelfile)]\n except ValueError:\n return None\n\n if prefixes[0].endswith('_first'):\n prefixes.append(prefixes[0][:-6])\n\n for p in prefixes:\n try:\n return fslimage.addExt(op.join(dirname, p), mustExist=True)\n except fslimage.PathError:\n continue\n\n return None","def find_metadata_file(diagnostics_dir, file_pattern, verbose=False):\n if not diagnostics_dir:\n return None\n metadata_dir = os.path.dirname(diagnostics_dir) + '/metadata'\n if not os.path.isdir(metadata_dir):\n if verbose:\n print(\"Unable to find metadata dir at\", metadata_dir)\n return None\n metafiles = sorted(glob.glob(metadata_dir+'/'+file_pattern))\n if len(metafiles) == 0:\n if verbose:\n print(\"Unable to find metdata file wiht pattern {} in {}\".format(file_pattern, metadata_dir))\n return None\n metadata_file = metafiles[0]\n return metadata_file","def find_flames(filename):\r\n image = SimpleImage(filename)\r\n # TODO: your code here\r\n return image","def iOFTPMatch(filename):\n ret = libxml2mod.xmlIOFTPMatch(filename)\n return ret","def getFilmTitles(checkFolder):\n\n files = [str(x) for x in Path(checkFolder).rglob(\"*\")]\n libFilmFiles = list(map(os.path.basename,files)) # Remove the path\n libFilmTitles = [os.path.splitext(x)[0] for x in libFilmFiles]\n return libFilmTitles","def extract_meta_data(video_file_name, output_file=meta.txt, *args, **kwargs):","def findFileLinearly(filename):\n #construct message\n id = generateUniqueID()\n msg = query(generateUniqueID(), GLOBALS.TTL, filename)\n\n #connect to neighbor\n neighbor = connectToSuperPeer(GLOBALS.NEIGHBOR_IP, GLOBALS.NEIGHBOR_PORT)\n if neighbor == -1: return -1\n if GLOBALS.DEBUG_MODE: print(\"[info] Linear lib: connected to neighbor\")\n\n #send query\n sendMessage(neighbor, msg)\n\n #wait for query responces\n while True:\n responce = receiveMessage(neighbor)\n if responce == -1: break # connection closed\n elif responce == 0: break\t# connection shutdown\n yield responce\n neighbor.close()","def _findfile(self,path,label):\n files=[];filenames=os.listdir(path)\n for name in filenames:\n if os.path.splitext(name)[0]==str(label):\n files.append(name)\n return files","def find_filter_phot(path = defaults._default_data_dir_path, snname = False,\n prefix = 'SN', file_type = '.dat',\n verbose = False):\n # regex = re.compile(\"^SN.*.dat\")\n\n errors.StringWarning(path)\n if not utils.check_dir_path(path):\n # return False\n raise errors.PathError\n\n\n try:\n if snname:\n match_string = \"^\" + str(snname) + \".*\" + '.dat'\n else:\n match_string = \"^\" + str(prefix) + \".*\" + '.dat'\n except:\n raise TypeError\n\n regex = re.compile(match_string)\n\n ls = os.listdir(path)\n\n phot_list = [os.path.join(path, match.group(0)) for file_name in ls for match in [regex.search(file_name)] if match]\n\n if os.path.join(path, snname + file_type) in phot_list:\n phot_list.remove(os.path.join(path,snname + file_type))\n warnings.warn(\"Found \" + os.path.join(path,snname + file_type) + \" - you could just read that in.\")\n\n if verbose:\n print(\"searching for\", match_string)\n print(\"Found: \")\n print(ls)\n print(\"Matched:\")\n print(phot_list)\n if len(phot_list) is 0:\n warnings.warn(\"No matches found.\")\n return phot_list","def test_find_anglerfish_results(self):\n anglerfish_dir = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2/anglerfish_output'\n run_dir = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2'\n run = MinIONqc(run_dir, None, None)\n found_file = run._find_anglerfish_results()\n expected_file = os.path.join(anglerfish_dir, 'anglerfish_2020_09_23_141922', 'anglerfish_stats.txt')\n self.assertEqual(expected_file, found_file)","def lookForDB():\n done = False\n msg = \"\"\n i = 0\n while not done:\n dbfilnam = \"SpeciesDB{}.txt\".format(i+1)\n path = os.path.join(progpath, dbfilnam)\n if os.path.exists(path):\n with open(path) as f:\n lines = f.read().splitlines()\n if len(lines):\n title = \"\"\n for l, lin in enumerate(lines):\n if l == 0:\n DBnames.append(lines[0].strip(\"# \"))\n i += 1\n else:\n lin = lin.strip(\"# \")\n if lin == \"\" or lin.startswith(\"List of species\"):\n DBtitles.append(title)\n break\n else:\n title += \"{}<br>\".format(lin)\n else:\n msg = \"No data in the file {}\".format(dbfilnam)\n done = True\n else:\n done = True\n if i == 0:\n msg = \"No database were found !\"\n if msg == \"\":\n return True\n QtWidgets.QMessageBox.critical(None, appName, msg)\n return False","def crawl_by_title(movie_name, verbose, year=None, parent_pbar=None):\n def _print(msg):\n if verbose:\n if parent_pbar is not None:\n parent_pbar.set_description(msg)\n parent_pbar.refresh()\n sys.stdout.flush()\n tqdm()\n else:\n print(msg)\n\n os.makedirs(_IMDB_DIR_PATH, exist_ok=True)\n file_name = _parse_name_for_file_name(movie_name) + '.json'\n file_path = os.path.join(_IMDB_DIR_PATH, file_name)\n if os.path.isfile(file_path):\n _print('{} already processed'.format(movie_name))\n return _result.EXIST\n\n # _print(\"Extracting a profile for {} from IMDB...\".format(movie_name))\n try:\n props = crawl_movie_profile(movie_name, year)\n # _print(\"Profile extracted succesfully\")\n # _print(\"Saving profile for {} to disk...\".format(movie_name))\n with open(file_path, 'w+') as json_file:\n # json.dump(props, json_file, cls=_RottenJsonEncoder, indent=2)\n json.dump(props, json_file, indent=2)\n _print(\"Done saving a profile for {}.\".format(movie_name))\n return _result.SUCCESS\n except Exception as exc:\n _print(\"Extracting a profile for {} failed\".format(movie_name))\n # traceback.print_exc()\n return _result.FAILURE\n # print(\"Extracting a profile for {} failed with:\".format(movie_name))\n # raise exc","def list_images_in_dataset(f):\n # list ms images\n # the '-not \\( -path *_files -prune \\)' is to avoid entering in the dzi\n # folders, which contains tens of thousands jpeg files and make the process\n # very slow\n p = subprocess.Popen(\"find %s -not \\( -path *_files -prune \\) -type f -name \\\"*_MS_*.JP2.TIF\\\"\" % f, shell=True, stdout=subprocess.PIPE)\n ms_files = p.stdout.read().splitlines()\n p = subprocess.Popen(\"find %s -not \\( -path *_files -prune \\) -type f -name \\\"*_P_*.JP2.TIF\\\"\" % f, shell=True, stdout=subprocess.PIPE)\n pan_files = p.stdout.read().splitlines()\n if not ms_files:\n print(\"no MS images in dataset %s\" % f, file=sys.stderr)\n return pan_files\n else:\n out = []\n for ms in ms_files:\n try:\n date_ms = re.split('_', os.path.basename(ms))[3]\n except IndexError:\n print(\"non standard filename in dataset %s\" % f, file=sys.stderr)\n return pan_files\n # search for the pan file with the same date\n matching_pan = None\n for pan in pan_files:\n if re.split('_', os.path.basename(pan))[3] == date_ms:\n matching_pan = pan\n break\n if matching_pan is None:\n print(\"no matching panchro image found for %s\" % ms, file=sys.stderr)\n else:\n out.append((matching_pan, ms))\n return out","def is_video(mine=None, file=None):\n if file:\n mine = get_file_mine(file)\n print(mine)\n\n if mine:\n return mine.find('video') != -1\n\n return False","def identify_dvd(job):\n # Added from pull 366\n \"\"\" Manipulates the DVD title and calls OMDB to try and \t\n lookup the title \"\"\"\n\n # Safe way of dealing with log files if the users need to post it online\n # cleanlog = makecleanlogfile(job)\n # logging.debug(\"#### --- job ----\" + str(cleanlog))\n\n # Added from #338\n # Some older DVDs aren't actually labelled\n if not job.label or job.label == \"\":\n job.label = \"not identified\"\n\n dvd_info_xml = False\n dvd_release_date = \"\"\n\n # TODO: remove this because its pointless keeping when it can never work\n try:\n crc64 = pydvdid.compute(str(job.mountpoint))\n fallback_title = \"{0}_{1}\".format(str(job.label), str(crc64))\n dvd_title = str(fallback_title)\n except pydvdid.exceptions.PydvdidException as e:\n logging.error(\"Pydvdid failed with the error: \" + str(e))\n dvd_title = fallback_title = str(job.label)\n crc64 = \"\"\n\n logging.info(\"DVD CRC64 hash is: \" + str(crc64))\n job.crc_id = str(crc64)\n\n # Dead needs removing\n urlstring = \"http://metaservices.windowsmedia.com/pas_dvd_B/template/GetMDRDVDByCRC.xml?CRC={0}\".format(str(crc64))\n logging.debug(urlstring)\n\n dvd_title = job.label\n logging.debug(\"dvd_title_label= \" + str(dvd_title))\n # strip all non-numeric chars and use that for year\n year = re.sub(\"[^0-9]\", \"\", str(job.year))\n # next line is not really needed, but we dont want to leave an x somewhere\n dvd_title = job.label.replace(\"16x9\", \"\")\n # Rip out any not alpha chars replace with\n dvd_title = re.sub(\"[^a-zA-Z ]\", \" \", dvd_title)\n logging.debug(\"dvd_title ^a-z= \" + str(dvd_title))\n # rip out any SKU's at the end of the line\n dvd_title = re.sub(\"SKU$\", \" \", dvd_title)\n logging.debug(\"dvd_title SKU$= \" + str(dvd_title))\n\n # try to contact omdb\n try:\n dvd_info_xml = callwebservice(job, job.config.OMDB_API_KEY, dvd_title, year)\n logging.debug(\"DVD_INFO_XML: \" + str(dvd_info_xml))\n except OSError as e:\n # we couldnt reach omdb\n logging.error(\"Failed to reach OMDB\")\n return False\n\n job.year = year\n job.title = dvd_title\n db.session.commit()\n return True","def get_files_search(query, video=False):\n\n creds = authenticate()\n service = build('drive', 'v3', credentials=creds)\n\n folder_ids, folder_names = get_folder_ids(ROOT_PHOTO_FOLDER_ID)\n files = []\n found_files = []\n gd_query = \"'{}' in parents and trashed = false and (mimeType = 'image/jpeg' or mimeType = 'image/png' or mimeType = 'image/svg+xml')\"\n\n if video:\n gd_query = \"'{}' in parents and trashed = false and mimeType = 'video/mp4'\"\n\n for id in folder_ids:\n page_token = None\n response = service.files().list(q=gd_query.format(id),\n pageSize=10,\n spaces=\"drive\",\n fields='nextPageToken, files(id, name, webViewLink, description)',\n pageToken=page_token,\n\n ).execute()\n files.extend(response[\"files\"]) # simply add to the current list of files found in other folders\n\n for file in files:\n if (\n file[\"name\"].rfind(query) != -1 or \n \"description\" in file and file[\"description\"].rfind(query) != -1\n ):\n found_files.append(file)\n\n return found_files","def lookup(collated_file,query_file):\r\n x=open(query_file,\"r\")\r\n query=[]\r\n for i in x:\r\n i=i.replace(\"\\n\",\"\")\r\n query.append(i)\r\n y=open(collated_file,\"r\")\r\n collection=[]\r\n for i in y :\r\n i=i.replace(\"\\n\",\"\")\r\n i=i.split(\":\")\r\n collection.append(i)\r\n answer=[]\r\n for i in range(len(query)):\r\n answer.append(BinarySearch(collection,0,len(collection)-1,query[i]))\r\n y = open(\"song_ids.txt\", \"w\")\r\n for i in range(len(answer)):\r\n y.write(str(answer[i]) + \"\\n\")","def read_mastcam_dir(self, filepath, suffix, unit, feature, extension = '.IMG', lblext='.LBL_label', eye='LR', margin=6):\n \n if eye == 'L':\n eyez = 'ML'\n elif eye == 'R':\n eyez = 'MR'\n elif eye == 'LR':\n eyez = ''\n pass\n else:\n raise ValueError('Eye name %s is not valid! Use L, R, or LR.' % eye)\n \n # GET ALL FILES WITH GIVEN EXTENSION IN FILEPATH\n files = sorted(glob.glob(str(filepath) + \"*\" + eyez + \"*\" + str(suffix) + \"*\" + str(extension)))\n fileprefixes = sorted(list(set([f.split('/')[-1][0:12] for f in files])))\n print(fileprefixes)\n \n print(\"found %d files among %d sequences with eye %s and extension %s in %s:\" % (len(files), len(fileprefixes), eye, extension, filepath))\n assert len(files) > 0\n \n numfiles = len(fileprefixes)\n seen = 0\n percent = 0.0\n printed = [False for foo in range(1000)]\n \n fullimages = {}\n segmentation = {}\n\n data = []\n self.labels = []\n \n for fileprefix in fileprefixes:\n print(\" \" + fileprefix)\n \n thissequence = sorted(glob.glob(str(filepath) + fileprefix + \"*\" + str(suffix) + \"*\" + str(extension)))\n asdfghjkl = 0\n \n parser = Parser()\n seqfiltstr = \"\"\n dimlist = []\n for w in thissequence:\n labels = parser.parse(open_pds(w.replace(extension, lblext))) \n filt = labels['INSTRUMENT_STATE_PARMS']['FILTER_NAME'][9]\n seqfiltstr += filt\n h = int(labels['IMAGE']['LINES'])\n w = int(labels['IMAGE']['LINE_SAMPLES'])\n dimlist.append([h, w])\n #print(\" %s %s %s\" % (filt, h, w))\n\n print(\"Filter name:\", labels['INSTRUMENT_STATE_PARMS']['FILTER_NAME'])\n \n #print(seqfiltstr)\n # print(dimlist)\n seqstocombine = []\n \n # Handle cases which appear to be several series of observations\n if len(seqfiltstr) % 7 == 0:\n for i in range(len(seqfiltstr) // 7):\n subseq = thissequence[7*i:7*i+7]\n subseqfilt = seqfiltstr[7*i:7*i+7]\n if subseqfilt == '0123456':\n cont = False\n for j in range(7*i, 7*i+7):\n if dimlist[7*i] != dimlist[j]:\n print(\"SIZE ERROR\")\n cont = True\n if cont:\n continue\n \n seqstocombine.append(subseq)\n \n else:\n if seqfiltstr == '00112233445566':\n seq1 = [thissequence[2*i] for i in range(len(thissequence) // 2)]\n seq2 = [thissequence[2*i+1] for i in range(len(thissequence) // 2)]\n \n seqstocombine.append(seq1)\n seqstocombine.append(seq2)\n \n break\n else:\n print(\"Length multiple of 7 but bad sequence\")\n\n # Non-7 number of observations\n else:\n for i in range(len(seqfiltstr)):\n subseq = thissequence[i:i+7]\n subseqfilt = seqfiltstr[i:i+7]\n if subseqfilt == '0123456':\n cont = False\n for j in range(i, i+7):\n if dimlist[i] != dimlist[j]:\n print(\"SIZE ERROR\")\n cont = True\n if cont: continue\n \n seqstocombine.append(subseq)\n \n # No actual multispectral images exist, so use all RGB (sol 388)\n if len(seqstocombine) == 0 and 'sol388' in self.archive:\n seqstocombine = [[f] for f in thissequence]\n \n # Now, download each sequence with this prefix\n for subseq in seqstocombine:\n qwertyuiop = 0\n bigimage = None\n \n err = False\n # Get each image within sequence\n for filename in subseq:\n namestem = filename.split('.')[0].split('/')[-1]\n\n try:\n (image, lbls) = self.load_image(namestem, filepath, ext=extension, lblext=lblext)\n except ValueError as e:\n #print(\"An error happened while processing %s\" % filename)\n err = True\n break\n\n (h, w, b) = image.shape\n \n if b == 3:\n self.rgbdict[fileprefix + str(asdfghjkl)] = namestem\n fullimages[fileprefix + str(asdfghjkl)] = image\n #print(\"Stored %s to rgbdict\" % (fileprefix + str(asdfghjkl)))\n \n if bigimage == None and 'sol388' not in filepath:\n bigimage = np.zeros([h, w, 9], dtype='uint8')\n elif bigimage == None:\n bigimage = np.zeros([h, w, b], dtype='uint8')\n \n bigimage[:,:,qwertyuiop:qwertyuiop+b] = image\n\n qwertyuiop += b\n \n\n # Reorder images based on camera so filters are ordered\n if eye in ['L', 'R']:\n bi = np.zeros([h, w, 9], dtype='uint8')\n if eye == 'L':\n bi[:, :, 0] = bigimage[:, :, 0]\n bi[:, :, 1] = bigimage[:, :, 1]\n bi[:, :, 2] = bigimage[:, :, 2]\n bi[:, :, 3] = bigimage[:, :, 4]\n bi[:, :, 4] = bigimage[:, :, 3]\n bi[:, :, 5] = bigimage[:, :, 6]\n bi[:, :, 6] = bigimage[:, :, 5]\n bi[:, :, 7] = bigimage[:, :, 7]\n bi[:, :, 8] = bigimage[:, :, 8]\n elif eye == 'R':\n bi[:, :, 0] = bigimage[:, :, 2]\n bi[:, :, 1] = bigimage[:, :, 1]\n bi[:, :, 2] = bigimage[:, :, 0]\n bi[:, :, 3] = bigimage[:, :, 4]\n bi[:, :, 4] = bigimage[:, :, 3]\n bi[:, :, 5] = bigimage[:, :, 5]\n bi[:, :, 6] = bigimage[:, :, 6]\n bi[:, :, 7] = bigimage[:, :, 7]\n bi[:, :, 8] = bigimage[:, :, 8]\n bigimage = bi\n\n if err:\n print(\" ...didn't load sequence. There was an error.\")\n continue\n \n print(\" ...loaded one sequence:\", (fileprefix + str(asdfghjkl)))\n \n if 'sol388' not in self.archive:\n name = fileprefix + str(asdfghjkl) + '_' + unit + '_' + feature\n else:\n name = namestem + '_' + unit + '_' + feature\n\n \n (segments, segmentlabels) = self.segment_image(bigimage, unit=unit)\n segmentation[fileprefix + str(asdfghjkl)] = segments[0][1]\n\n for i in range(len(segments)):\n data += [[float(x) for x in self.process_image(segments[i], name + segmentlabels[i], feature=feature)]]\n \n asdfghjkl += 1\n \n ###########################################\n \n seen += 1\n \n # output read-in progress\n if percent < 100:\n if (round((seen / float(numfiles)) * 100, 1) >= percent) and (printed[int(percent * 10)] == False):\n #print(\"...%3.1f%%...\" % percent)\n printed[int(percent * 10)] == True\n percent = round(((seen / float(numfiles)) * 100), 1) + 1\n print(\"...100%...\")\n print(\"Transposing data...\")\n data = np.array(data).T\n self.xvals.sort()\n \n # Output the pickle\n print(\"Writing pickle to \" + self.archive + \" ...\")\n outf = open(self.archive, 'w')\n pickle.dump((data, fullimages, segmentation, self.labels, self.xlabel, self.ylabel, self.xvals, self.rgbdict, self.lblext, self.initdata, self.initfilename), outf)\n outf.close()\n print(\"Wrote pickle to \" + self.archive)","def recursively_find_file(folder, file_name):\n # TODO: print a hint when not founding file_name","def find_file_match(folder, end):\n if not os.path.exists(folder):\n return None\n if not os.path.isdir(folder):\n return None\n\n dir_list = os.listdir(folder)\n subdirs = []\n\n # First try to find the file. Save any sub folders for later\n for entry in dir_list:\n # Skip over hidden files\n if entry[0] == '.':\n continue\n\n # Check the name to see if it's a file and if it first the descrioption\n test_path = os.path.join(folder, entry)\n if os.path.isfile(test_path):\n if test_path.endswith(end):\n return test_path\n else:\n subdirs.append(entry)\n\n # Loop through sub folders\n subdirs_len = len(subdirs)\n if subdirs_len > 0:\n for one_dir in subdirs:\n found = find_file_match(os.path.join(folder, one_dir), end)\n if not found is None:\n return found\n\n return None","def match_filename(filename: str) -> Optional[dict]:\n r = re.match(string=filename, pattern=NPS_PATTERN, flags=re.I)\n if r:\n return r.groupdict()\n else:\n return None","def main(video_folder, database_location):\n \n # Validate parameters\n if not path.isdir(video_folder):\n print 'Invalid video directory path: {}'.format(video_folder)\n return\n \n if not path.exists(database_location):\n print 'Invalid database location: {}'.format(database_location)\n return\n \n # Connect to database\n conn = sqlite3.connect(database_location)\n cursor = conn.cursor()\n\n # Get data\n video_files = listdir(video_folder)\n video_ids = [f.split('.')[0] for f in video_files if f.endswith('.avi')]\n \n # Stats\n true_positives = 0 # Category 1 classified as category 1\n false_positives = 0 # Categories 2 or 3 classified as category 1\n true_negatives = 0 # Categories 2 or 3 classified as categories 2 or 3\n false_negatives = 0 # Category 1 classified as categories 2 or 3\n\n for video_id in video_ids:\n \n # Make sure both a .avi and .wav file are available for this id\n video_location = path.join(video_folder, '{}.avi'.format(video_id))\n audio_location = path.join(video_folder, '{}.wav'.format(video_id))\n \n if not path.exists(video_location) or not path.exists(audio_location):\n continue\n \n # Process video\n print 'Processing `{}`...'.format(video_id) \n category_classifier = process_video.process(\n video_location,\n audio_location,\n database_location\n )\n\n # Get actual label\n metadata = video_id.split('-')\n db_video_id = ''.join(metadata[:-2])\n db_start_time_ms = metadata[-2]\n\n query = '''\n SELECT category FROM classifications\n WHERE video_id = ?\n AND start_time_ms = ?\n '''\n cursor.execute(query, (db_video_id, db_start_time_ms))\n result = cursor.fetchone()\n \n # (Skip if the video isn't labeled)\n if result is None:\n print 'No label - skipped'\n continue\n \n category_actual = result[0]\n\n # Mark as TP, FP, TN, or FN\n if category_classifier == 1:\n if category_actual == 1:\n true_positives += 1\n mark = 'TP'\n else:\n false_positives += 1\n mark = 'FP'\n else:\n if category_actual == 1:\n false_negatives += 1\n mark = 'FN'\n else:\n true_negatives += 1\n mark = 'TN'\n \n print 'Classified as category {} ({})'.format(\n category_classifier,\n mark\n )\n \n print\n\n print\n\n print 'RESULTS:'\n print\n print 'True Positives (TP) =', true_positives\n print 'False Positives (FP) =', false_positives\n print 'True Negatives (TN) =', true_negatives\n print 'False Negatives (FN) =', false_negatives\n\n print\n print 'Recall [TP / (TP + FN)] =', float(true_positives) / (true_positives + false_negatives)\n print 'Precision [TP / (TP + FP)] =', float(true_positives) / (true_positives + false_positives)","def test_word_found_in_file(self):\n\n # create indexer object\n indexer = indexing_module.IndexModule()\n\n # index the location (storage/data/test/empty_directory)\n indexer.index(_path_prefix + 'word_not_found')\n\n # search for few words and check that the result is empty\n result = indexer.search(\"unit\")\n self.assertTrue(result != [])\n\n result = indexer.search(\"index\")\n self.assertTrue(result != [])\n print(result)","def find_video_of_file(\n self, video_dir: Union[str, os.PathLike], filename: str\n ) -> Union[str, os.PathLike]:\n try:\n all_files_in_video_folder = [\n f for f in next(os.walk(video_dir))[2] if not f[0] == \".\"\n ]\n except StopIteration:\n raise NoFilesFoundError(msg=f\"No files found in the {video_dir} directory\")\n all_files_in_video_folder = [\n os.path.join(video_dir, x) for x in all_files_in_video_folder\n ]\n return_path = None\n for file_path in all_files_in_video_folder:\n _, video_filename, ext = get_fn_ext(file_path)\n if (video_filename == filename) and (\n (ext.lower() == \".mp4\") or (ext.lower() == \".avi\")\n ):\n return_path = file_path\n\n if return_path is None:\n NoFileFoundWarning(\n f\"SimBA could not find a video file representing {filename} in the project video directory\"\n )\n return return_path","def movies_filename(self):\n pass","def search(pattern):\n query = pattern.lower()\n videolist = getvideolist()\n results = []\n for video in videolist:\n for value in video.values():\n if query in str(value).lower():\n results.append(Colors.YELLOW + video[\"file\"] + Colors.END + \" - \" + video[\"source\"] + \" - \" +\n video[\"title\"])\n if results:\n for result in results:\n safeprint(result)\n else:\n safeprint(\"No video matching the given query was found.\")","def find(self, file, version):\n matches = []\n for root, dirnames, filenames in os.walk(self.full_doc_path(version)):\n for filename in fnmatch.filter(filenames, file):\n matches.append(os.path.join(root, filename))\n return matches","def test_IMDB_Search_TC_002_search_for_a_movie(self):\n # to load a given URL in browser window\n self.driver.get(self.base_url) \n # to enter search term, we need to locate the search textbox\n searchTextBox=self.driver.find_element_by_id(\"suggestion-search\")\n # to clear any text in the search textbox\n searchTextBox.clear()\n # to enter the search term in the search textbox via send_keys() function\n searchTextBox.send_keys(self.search_term)\n # to search for the entered search term\n searchTextBox.send_keys(Keys.RETURN)\n # to see movie title element\n searchMovieBox = self.driver.find_element_by_link_text(\"Silicon Valley\")\n # to verify if the search results page loaded\n self.assertIn(\"Find - IMDb\",self.driver.title)\n # to verify if the search results page contains any results or no results were found.\n self.assertNotIn(\"No results found.\",self.driver.page_source)","def files_of(mage_id):\n\tcursor.execute('select tag.id, tag.name from tag, tagging as is_file_tagging, tagging where tag.id = tagging.child_id and tag.id = is_file_tagging.child_id and is_file_tagging.parent_id = ? and tagging.parent_id = ?', (settings['file'],mage_id))\n\treturn cursor.fetchall()","def isVideoFolder():","def _find_named_files(self):\n for name, description in self.named_files.iteritems():\n name = name.format(job_name=self.job_name)\n f_path = '{}/{}'.format(self.rism3d_folder, name)\n if os.path.isfile(f_path):\n self.file_path_dic[description] = f_path\n else:\n self._not_found_error(f_path)","def scanForAssays(self):\n if not self.isDataDir():\n self.setDataDir(os.getcwdu())\n files = os.listdir(self.__datadir)\n print(files)\n for f in files:\n if f.endswith('.tif'):\n print('An TIFF image here! (%s)') % f","def get_mentions(fname):\n capture = re.compile('NPRI in ?.* ?(news|print)', re.I)\n with open(fname) as fp:\n for line in fp:\n line = line.strip()\n if capture.search(line):\n yield get_info(line)","def detect_netease_music_name(file_path, dist_path, KEEP_SOURCE=True):\n headers = {\n \"User-Agent\": \"Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:61.0) Gecko/20100101 Firefox/61.0\"\n }\n url_base = \"http://music.163.com/api/song/detail/?id={}&ids=[{}]\"\n\n if not os.path.exists(dist_path):\n os.mkdir(dist_path)\n\n for file_name in os.listdir(file_path):\n if not file_name.endswith(\".mp3\"):\n continue\n if not len(file_name.split(\"-\")) == 3:\n print(\n \">>>> File %s not in format <song id>-<bite rate>-<random number>.mp3\"\n % (file_name)\n )\n continue\n\n try:\n song_id = file_name.split(\"-\")[0]\n url_target = url_base.format(song_id, song_id)\n resp = requests.get(url_target, headers=headers)\n rr = json.loads(resp.text)\n\n tt = eyed3.load(os.path.join(file_path, file_name))\n tt.tag.title = rr[\"songs\"][0][\"name\"].replace(\"\\xa0\", \" \")\n tt.tag.artist = rr[\"songs\"][0][\"artists\"][0][\"name\"]\n tt.tag.album = rr[\"songs\"][0][\"album\"][\"name\"]\n tt.tag.album_artist = rr[\"songs\"][0][\"album\"][\"artists\"][0][\"name\"]\n print(\n \"song_id = %s, tt.tag title = %s, artist = %s, album = %s, album_artist = %s\"\n % (\n song_id,\n tt.tag.title,\n tt.tag.artist,\n tt.tag.album,\n tt.tag.album_artist,\n )\n )\n tt.tag.save()\n except UnicodeEncodeError as e:\n print(\n \">>>> UnicodeEncodeError, try again later: file_name = %s, error = %s\"\n % (file_name, str(e))\n )\n continue\n except:\n print(\">>>> Some other error happens: file_name = %s\" % (file_name))\n continue\n\n dist_name = (\n os.path.join(\n dist_path,\n \"%s - %s\"\n % (tt.tag.artist.replace(\"/\", \" \"), tt.tag.title.replace(\"/\", \" \")),\n )\n + \".mp3\"\n )\n \n if KEEP_SOURCE == True:\n shutil.copyfile(os.path.join(file_path, file_name), dist_name)\n else:\n os.rename(os.path.join(file_path, file_name), dist_name)","def get_movie_data(files: list) -> list:\n pass"],"string":"[\n \"def MovieScan():\\r\\n for root, dirnames, filenames in os.walk(dlPath):\\r\\n for extend in movtypes:\\r\\n for filename in fnmatch.filter(filenames, extend):\\r\\n matches.append(os.path.join(root, filename))\\r\\n print(os.path.join(root, filename))\\r\\n shutil.move(os.path.join(root, filename), os.path.join(moviePath, filename))\\r\\n print color.GREEN + 'File succesfully moved!' + color.ENDC\\r\\n print 'Finished Scanning For Movies'\",\n \"def findMayaFiles(directory):\\n\\n pass\",\n \"def _findVideoFile(self, videofile):\\n for vf in self.vflist:\\n if vf.startswith(videofile + '.'):\\n videosource = os.path.join(self.vfdir, vf)\\n return videosource\",\n \"def test_afni_nifti():\\n im = ndar.Image('test_data/06025B_mprage.nii.gz')\\n assert os.path.exists('%s.BRIK' % im.afni)\\n assert os.path.exists('%s.HEAD' % im.afni)\",\n \"def provoke_and_handle_FileNotFoundError():\\n try:\\n with open(\\\"NEIN.mp3\\\") as f:\\n print(\\\"well\\\")\\n except FileNotFoundError as fnfe:\\n print(f\\\"Sorry! {fnfe}\\\")\",\n \"def find_movie(imdb_file, title_regex):\\n\\n process = subprocess.run([\\n \\\"grep\\\",\\n \\\"-i\\\", # Case insensitive\\n f'movie\\\\t[^\\\\t]*{title_regex}', # Only match movies\\n imdb_file\\n ], stdout=subprocess.PIPE)\\n hits = [dict(zip(COLUMNS, hit.decode(\\\"utf-8\\\").split(\\\"\\\\t\\\")))\\n for hit in process.stdout.split(b\\\"\\\\n\\\")[:-1]]\\n # Try to filter out irrelevant hits, e.g. that don't yet exist or are porn\\n legitimate_hits = [hit for hit in hits\\n if hit[\\\"startYear\\\"] != \\\"\\\\\\\\N\\\" and\\n hit[\\\"isAdult\\\"] == \\\"0\\\"]\\n return legitimate_hits\",\n \"def TvScan():\\r\\n for root, dirnames, filenames in os.walk(dlPath):\\r\\n for key, location in tvshows.iteritems():\\r\\n for filename in fnmatch.filter(filenames, key):\\r\\n matches.append(os.path.join(root, filename))\\r\\n print(os.path.join(root, filename))\\r\\n shutil.move(os.path.join(root, filename), os.path.join(location, filename))\\r\\n print color.GREEN + 'File succesfully moved!' + color.ENDC\\r\\n # Send the file through another filter in case of lower case filenames \\r\\n for filename in fnmatch.filter(filenames, key.lower()):\\r\\n matches.append(os.path.join(root, filename))\\r\\n print(os.path.join(root, filename))\\r\\n shutil.move(os.path.join(root, filename), os.path.join(location, filename))\\r\\n print color.GREEN + 'File succesfully moved!' + color.ENDC\\r\\n print 'Finished Scanning For TV Shows'\",\n \"def imdb_load():\\n for root, dirs, filenames in os.walk(os.path.dirname(__file__) + \\\"/imdb\\\"):\\n for file_name in filenames:\\n if file_name.find(\\\".json\\\") > 0:\\n Movie.imdb_load_file(os.path.dirname(__file__) + \\\"/imdb/\\\" + file_name)\\n return Movie.__movies\",\n \"def MusicScan():\\r\\n for root, dirnames, filenames in os.walk(dlPath):\\r\\n for extend in mustypes:\\r\\n for filename in fnmatch.filter(filenames, extend):\\r\\n matches.append(os.path.join(root, filename))\\r\\n print(os.path.join(root, filename))\\r\\n shutil.move(os.path.join(root, filename), os.path.join(musicPath, filename))\\r\\n print color.GREEN + 'File succesfully moved!' + color.ENDC\\r\\n print 'Finished Scanning For Music'\",\n \"def lookup_ifproc_file(obsnum, path='/data_lmt/ifproc/', debug=False):\\n paths = [path]\\n\\n if 'ifproc' not in path:\\n paths += ['/data_lmt/ifproc/']\\n if 'lmtttpm' not in path:\\n paths += ['/data_lmt/lmttpm/']\\n if 'tel' not in path:\\n paths += ['/data_lmt/tel/']\\n\\n if debug:\\n print(paths)\\n\\n for path in paths:\\n filenames = glob.glob(os.path.join(path, '*_%06d_*.nc' % obsnum))\\n if len(filenames) > 0:\\n if debug:\\n print('found %s' % (filenames[0]))\\n return filenames[0]\\n return ''\\n #filename = ''\\n #for file in os.listdir(path):\\n # if fnmatch.fnmatch(file,'*_%06d_*.nc'%(obsnum)):\\n # print('found %s'%(file))\\n # filename = path+file\\n #if filename == '':\\n #print('lookup_ifproc_file: no file for obsnum ', obsnum)\\n #if 'lmttpm' not in path:\\n # print('look in lmttpm')\\n # return lookup_ifproc_file(obsnum,path='/data_lmt/lmttpm/')\\n #return(filename)\",\n \"def searchImage(text):\\n creds = None\\n # The file token.json stores the user's access and refresh tokens, and is\\n # created automatically when the authorization flow completes for the first\\n # time.\\n if os.path.exists('token.json'):\\n creds = Credentials.from_authorized_user_file('token.json', SCOPES)\\n # If there are no (valid) credentials available, let the user log in.\\n if not creds or not creds.valid:\\n if creds and creds.expired and creds.refresh_token:\\n creds.refresh(Request())\\n else:\\n flow = InstalledAppFlow.from_client_secrets_file(\\n 'credentials.json', SCOPES)\\n creds = flow.run_local_server(port=0)\\n # Save the credentials for the next run\\n with open('token.json', 'w') as token:\\n token.write(creds.to_json())\\n\\n service = build('drive', 'v3', credentials=creds)\\n\\n results_length = 0\\n results_message = []\\n nextPageToken = \\\"first\\\"\\n flex_dict = {\\n \\\"type\\\": \\\"carousel\\\",\\n \\\"contents\\\": []\\n }\\n\\n with open(\\\"episode_info.json\\\", 'r', encoding=\\\"utf-8\\\") as f:\\n episode_info = json.load(f)\\n\\n # imageFolder: https://drive.google.com/drive/u/0/folders/1CH7i08P4NK0WkhASe4_qs92fsL2Mz0tM\\n\\n while nextPageToken != []:\\n if nextPageToken == \\\"first\\\":\\n results = service.files().list(q=\\\"'1CH7i08P4NK0WkhASe4_qs92fsL2Mz0tM' in parents and fullText contains '{}'\\\".format(text), pageSize=1000,\\n fields=\\\"nextPageToken, files(id, name)\\\").execute()\\n else:\\n results = service.files().list(q=\\\"'1CH7i08P4NK0WkhASe4_qs92fsL2Mz0tM' in parents and fullText contains '{}'\\\".format(text), pageSize=1000, pageToken=nextPageToken,\\n fields=\\\"nextPageToken, files(id, name)\\\").execute()\\n items = results.get('files', [])\\n nextPageToken = results.get('nextPageToken', [])\\n print(len(items))\\n for item in items:\\n img_url = \\\"https://lh3.googleusercontent.com/d/{}=w1080\\\".format(\\n item['id'])\\n # print(u'{0} ({1})'.format(item['name'], img_url))\\n\\n positino_left_brackets = item['name'].find(\\\"【\\\")\\n position_right_brackets = item['name'].find(\\\"】\\\")\\n position_dot = item['name'].find(\\\".jpg\\\")\\n img_episode = item['name'][positino_left_brackets +\\n 1:position_right_brackets]\\n img_title = item['name'][position_right_brackets+1:position_dot]\\n if img_title.find(text) != -1:\\n results_length += 1\\n if len(flex_dict[\\\"contents\\\"]) < 12:\\n try:\\n esfio = episode_info[img_episode][\\\"Every Spongebob Frame In Order\\\"]\\n chn_episode_title = episode_info[img_episode][\\\"中文集數名稱\\\"]\\n eng_episode_title = episode_info[img_episode][\\\"英文集數名稱\\\"]\\n except:\\n pass\\n\\n new_bubble_flex_message = {}\\n\\n with open(\\\"bubble_flex_message.json\\\", \\\"r\\\", encoding='utf-8') as f:\\n new_bubble_flex_message = json.load(f)\\n\\n new_bubble_flex_message[\\\"hero\\\"][\\\"url\\\"] = img_url\\n new_bubble_flex_message[\\\"body\\\"][\\\"contents\\\"][0][\\\"contents\\\"][0][\\\"text\\\"] = img_title\\n new_bubble_flex_message[\\\"body\\\"][\\\"contents\\\"][1][\\\"contents\\\"][0][\\\"contents\\\"][1][\\\"text\\\"] = img_episode\\n new_bubble_flex_message[\\\"body\\\"][\\\"contents\\\"][1][\\\"contents\\\"][1][\\\"contents\\\"][1][\\\"text\\\"] = esfio\\n new_bubble_flex_message[\\\"body\\\"][\\\"contents\\\"][1][\\\"contents\\\"][2][\\\"contents\\\"][1][\\\"text\\\"] = chn_episode_title\\n new_bubble_flex_message[\\\"body\\\"][\\\"contents\\\"][1][\\\"contents\\\"][3][\\\"contents\\\"][1][\\\"text\\\"] = eng_episode_title\\n new_bubble_flex_message[\\\"footer\\\"][\\\"contents\\\"][0][\\\"action\\\"][\\\"data\\\"] = \\\"傳\\\" + img_url\\n new_bubble_flex_message[\\\"footer\\\"][\\\"contents\\\"][1][\\\"action\\\"][\\\"uri\\\"] = img_url\\n\\n flex_dict[\\\"contents\\\"].append(new_bubble_flex_message)\\n if len(flex_dict[\\\"contents\\\"]) == 12:\\n if len(results_message) < 5:\\n results_message.append(FlexSendMessage(\\n alt_text=\\\"搜尋結果\\\",\\n contents=flex_dict)\\n )\\n if len(results_message) == 5:\\n print(\\\"len(results_message)1: \\\", len(results_message))\\n return {\\\"length\\\": results_length, \\\"top5_url_list\\\": results_message}\\n flex_dict[\\\"contents\\\"] = []\\n if nextPageToken == []:\\n if len(flex_dict[\\\"contents\\\"]) != 0:\\n if len(results_message) < 5:\\n results_message.append(FlexSendMessage(\\n alt_text=\\\"搜尋結果\\\",\\n contents=flex_dict)\\n )\\n print(\\\"len(results_message)2: \\\", len(results_message))\\n return {\\\"length\\\": results_length, \\\"top5_url_list\\\": results_message}\\n\\n print(\\\"len(results_message)3: \\\", len(results_message))\\n return {\\\"length\\\": results_length, \\\"top5_url_list\\\": results_message}\",\n \"def process(self):\\n try:\\n existing_movie = os.listdir(self.movie_root_path)\\n except:\\n os.makedirs(self.movie_root_path)\\n existing_movie = os.listdir(self.movie_root_path)\\n\\n if not [movie for movie in existing_movie if self.title.lower() in movie.lower()]:\\n if self.has_video_extension:\\n self.move_media()\\n else:\\n self.extract_media()\\n else:\\n Logger.log('[-] %s already exists. Skipping...' % self.title)\",\n \"def identify_file(self, file):\",\n \"def test_afni_minc():\\n im = ndar.Image('test_data/a.mnc')\\n assert os.path.exists('%s.BRIK' % im.afni)\\n assert os.path.exists('%s.HEAD' % im.afni)\",\n \"def find_file(lines, MF=1):\\n v = [l[slices['MF']] for l in lines]\\n n = len(v)\\n cmpstr = '%2s' % MF # search string\\n i0 = v.index(cmpstr) # first occurrence\\n i1 = n - v[::-1].index(cmpstr) # last occurrence\\n return lines[i0: i1]\",\n \"def extract_file_observable_info(filename):\\n # all possible observables\\n all_obs = [\\\"He4_E\\\", \\\"He4_rptp\\\", \\\"H3_E\\\", \\\"fT12\\\"]\\n obs_found = []\\n\\n # search for these in the filename\\n for obs in all_obs:\\n match = search(obs, filename)\\n if match:\\n obs_found.append(obs)\\n if not obs_found:\\n print(\\\"No matches were found in this file name\\\")\\n return None\\n return obs_found\",\n \"def download_episode(self, filmid):\\n self.logger.debug('download_episode')\\n if not self._test_download_path(self.settings.getDownloadPathEpisode()):\\n return\\n film = self.database.retrieve_film_info(filmid)\\n if film is None:\\n return\\n\\n (filmurl, extension,) = self._get_film_url_and_extension(film)\\n\\n # detect season and episode\\n (season, episode, fninfo,) = self._season_and_episode_detect(film)\\n\\n # determine names\\n showname = mvutils.cleanup_filename(film.show)[:64]\\n namestem = mvutils.cleanup_filename(film.title)[:80]\\n if not namestem:\\n namestem = u'Episode-{}'.format(film.filmid)\\n if not showname:\\n showname = namestem\\n\\n # review name\\n if self.settings.getReviewName():\\n (namestem, confirmed) = self.notifier.get_entered_text(namestem, 30986)\\n namestem = mvutils.cleanup_filename(namestem)\\n if len(namestem) < 1 or confirmed is False:\\n return\\n\\n # prepare download directory and determine sequence number\\n pathname = self.settings.getDownloadPathEpisode() + showname + '/'\\n sequence = 1\\n if xbmcvfs.exists(pathname):\\n (_, epfiles,) = xbmcvfs.listdir(pathname)\\n for epfile in epfiles:\\n match = re.search(r'^.* - \\\\(([0-9]*)\\\\)\\\\.[^/]*$', epfile)\\n if match and match.groups():\\n if sequence <= int(match.group(1)):\\n sequence = int(match.group(1)) + 1\\n else:\\n xbmcvfs.mkdir(pathname)\\n\\n filename = showname + ' - ' + fninfo + \\\\\\n namestem + (u' - (%04d)' % sequence)\\n # download the stuff\\n if self._download_files(film, filmurl, pathname, filename, extension):\\n self._make_series_nfo_files(\\n film, filmurl, pathname, filename, season, episode, sequence)\",\n \"def video_files():\\n p = parse_cmdline(get_parser=get_parser_files)\\n log.setup_main_handler(\\n mods=(\\\"fogtools\\\", \\\"typhon\\\", \\\"fogpy\\\", \\\"sattools\\\", \\\"fcitools\\\", \\\"satpy\\\",\\n \\\"pyresample\\\"),\\n level=logging.INFO)\\n vis.show_video_abi_glm(\\n files=p.files,\\n img_out=p.filename_pattern_image,\\n vid_out=p.filename_pattern_video,\\n out_dir=p.outdir)\\n print(\\\"Files written to:\\\", p.outdir)\",\n \"def writeCDNAresults(self, target, target_folder, outf, contigf):\\n if self.params['assembler'] == 'newbler':\\n contigf = os.path.join(self.params['working_dir'], target_folder, \\\"assembly\\\", \\\"assembly\\\", \\\"454AllContigs.fna\\\")\\n isotigsf = os.path.join(self.params['working_dir'], target_folder, \\\"assembly\\\", \\\"assembly\\\", \\\"454IsotigsLayout.txt\\\")\\n readstatusf = os.path.join(self.params['working_dir'], target_folder, \\\"assembly\\\", \\\"assembly\\\", \\\"454ReadStatus.txt\\\")\\n else:\\n logger.info(\\\"WARNING writeCDNAresults called when assembler was not Newbler\\\")\\n return None\\n if not (os.path.exists(contigf) and os.path.exists(isotigsf) and os.path.exists(readstatusf)):\\n logger.info(\\\"CDNA WARNING MISSING FILE!! %s %s\\\" % (target, self.params['sample']))\\n logger.info(contigf, os.path.exists(contigf))\\n logger.info(isotigsf, os.path.exists(isotigsf))\\n logger.info(readstatusf, os.path.exists(readstatusf))\\n return None\\n #Storage data structures:\\n isogroups = {} # A dict of isogroups which each contain an in-order list of contigs\\n readcounts = Counter() # A dict of all contigs, these contain read counts (from ReadStatus)\\n contig_orientation = {}\\n contig_to_isogroup = {}\\n contig_idx = SeqIO.index(contigf, \\\"fasta\\\")\\n # Parse isotigsf:\\n igroup = \\\"\\\"\\n #print self.params['sample'], target, \\\"Parsing isotigsf: %s\\\" % isotigsf\\n for l in open(isotigsf, 'r'):\\n #Handle lines with only a '\\\\n'\\n if l == '\\\\n':\\n pass\\n #Handle lines for isogroup:\\n elif l[0:9] == '>isogroup':\\n igroup = l.strip().split()[0].strip(\\\">\\\")\\n #Handle lines containing all contigs:\\n elif l.strip().split()[0] == 'Contig':\\n l2 = l.strip().split()\\n contigs = map(lambda x: \\\"contig\\\" + x, l2[2:-1])\\n isogroups[igroup] = contigs\\n for contig in contigs:\\n if contig not in contig_orientation:\\n contig_orientation[contig] = '+'\\n contig_to_isogroup[contig] = igroup\\n else:\\n raise exceptions.FatalError('Contig %s in %s more than once' % (contig, contigf))\\n #Handle lines containing contig orientation info:\\n elif l[0:6] == 'isotig':\\n l2 = l[l.find(\\\" \\\") + 1: l.rfind(\\\" \\\") - 1]\\n l3 = [l2[i:i+6] for i in range(0, len(l2), 6)]\\n for i in range(len(l3)):\\n if l3[i][0] == '<':\\n # contig is in reverse orientation\\n contig = isogroups[igroup][i]\\n contig_orientation[contig] = '-'\\n #print self.params['sample'], target, \\\"Parsed isotigsf, contigs:\\\", len(isogroups), \\\"contig_to_isogroup\\\", len(contig_to_isogroup), \\\"contig_orientation\\\", len(contig_orientation)\\n #Now parse readstatus:\\n inf = open(readstatusf, 'r')\\n inf.readline() # discard first line\\n for l in inf:\\n l2 = l.strip().split('\\\\t')\\n #Determine if this read was assembled\\n if len(l2) == 8:\\n contig = l2[2]\\n # Note that there are some built in limits to the number of contigs that can be in an isogroup:\\n # http://contig.wordpress.com/2010/08/31/running-newbler-de-novo-transcriptome-assembly-i/\\n # These won't appear in the IsotigsLayout.txt, but ARE in the ReadStatus.txt file.\\n if contig in contig_to_isogroup:\\n readcounts[contig_to_isogroup[contig]] += 1\\n else:\\n readcounts['ExceedsThreshold'] += 1\\n #print self.params['sample'], target, \\\"Parse read status\\\"\\n\\n #Finally, output all of this information appropriately:\\n countsf = open(os.path.join(self.params['finished_dir'], \\\"isogroup_read_counts.tsv\\\"), 'a')\\n sample = self.params['sample']\\n #First write out readcounts: sample \\\\t target \\\\t isogroup \\\\t readcount\\n for isogroup in readcounts:\\n countsf.write('\\\\t'.join([sample, target, isogroup, str(readcounts[isogroup])]) + '\\\\n')\\n countsf.close()\\n #print self.params['sample'], target, \\\"Wrote readcounts\\\"\\n\\n #Next write the contigs in proper order and orientation:\\n ncontigs = 0\\n nisogroups = 0\\n for isogroup in isogroups:\\n nisogroups += 1\\n for contig in isogroups[isogroup]:\\n ncontigs += 1\\n seqrec = contig_idx[contig]\\n #print self.params['sample'], target, seqrec\\n if contig_orientation[contig] == '-':\\n seqrec.seq = seqrec.seq.reverse_complement()\\n #print self.params['sample'], target, seqrec\\n seqrec.name = seqrec.id = sample + \\\"_:_\\\" + target + \\\"_:_\\\" + isogroup + \\\"|\\\" + contig\\n #print self.params['sample'], target, seqrec\\n SeqIO.write(seqrec, outf, \\\"fasta\\\")\\n ## TODO: add support for the ExceedsThreshold contigs\\n logger.info(\\\"Sample: %s target: %s iteration: %s Finished writing %s contigs, %s isogroups \\\" % (self.params['sample'],\\n target, self.params['iteration'], ncontigs, nisogroups))\",\n \"def extract_nac_pet(dicom_folder):\\n from glob import glob\\n import os\\n import shutil\\n import re\\n from nipype.interfaces.dcm2nii import Dcm2nii\\n\\n def atoi(text):\\n return int(text) if text.isdigit() else text\\n\\n def natural_keys(text):\\n return [atoi(c) for c in re.split('(\\\\d+)', text)]\\n\\n files = glob(os.path.join(os.path.abspath(dicom_folder), '*'))\\n sorted_files = sorted(files, key=natural_keys)\\n nac_pet_files = sorted_files[-127:]\\n for f in nac_pet_files:\\n shutil.copy(f, os.getcwd())\\n dcm2nii = Dcm2nii()\\n dcm2nii.inputs.source_dir = os.getcwd()\\n nii_outputs = dcm2nii.run().outputs.converted_files\\n print (nii_outputs)\\n return nii_outputs[0]\",\n \"def get_movie_info_from_folder(folder):\\n if not os.path.exists(folder):\\n raise ValueError(\\\"folder does not exists\\\")\\n for file in os.listdir(folder):\\n filename = os.path.join(folder, file)\\n if os.path.isfile(filename):\\n e = ET.parse(filename).getroot()\\n for result in e[1]:\\n attributes = dict()\\n for bindings in result:\\n attributes[bindings.attrib['name']] = bindings[0].text\\n if len(attributes['title']) > 0:\\n yield Movie(**attributes)\",\n \"def check_for_3dm(folder):\\n find=False;\\n if not os.path.exists(folder): return;\\n \\n walk=os.walk(folder);\\n for dirpath, dirnames, filenames in walk:\\n for file in filenames:\\n ext=file.split(\\\".\\\")[-1];\\n if ext.upper()==\\\"3DM\\\":\\n find = True;\\n return find;\\n \\n return find\",\n \"def _discover_in_dir(self, dir_path: str) -> Optional[str]:\\n for this_file in os.listdir(dir_path):\\n if this_file.endswith('.esvi'):\\n return os.path.join(dir_path, this_file)\\n\\n return None\",\n \"def search_string(command):\\n try:\\n my_file.search_string(command[1])\\n except FileNotFoundError:\\n print('No file has been read yet')\",\n \"def main(\\n):\\n music_home = \\\"/home/banana/music\\\"\\n for inode in list_dir(music_home):\\n if basename(inode) in [\\n \\\"annotate\\\",\\n \\\"metadata\\\",\\n \\\"sped-up\\\",\\n \\\"tracklists\\\",\\n ] or isfile(inode):\\n continue\\n convert(inode)\",\n \"def _find_tif_file(self):\\n name = self.results_file.name[:-12] + \\\".tif\\\"\\n try:\\n tif_file = next(self.results_file.parent.glob(name))\\n return tif_file\\n except StopIteration:\\n print(f\\\"Tif not found for {name}\\\")\\n return None\",\n \"def get_files_match(matches, dname, Lshow, Ldir=False):\\n matched_files=[]\\n ### two for-loop is converted\\n for fname in os.listdir(dname):\\n #print(f\\\"{fname}\\\")\\n for match in matches:\\n if re.search(match, fname):\\n ### if it is dir skip\\n if os.path.isdir(fname) and not Ldir:\\n continue\\n if Lshow:\\n print(f\\\"detect {fname}\\\") # in {match} {matches}\\\")\\n matched_files.append(fname)\\n return matched_files\",\n \"def search(self, id):\\n\\n db = self.connection(\\\"imdb\\\")\\n\\n try:\\n cur = db.cursor()\\n sql = \\\"SELECT * FROM film WHERE id = %s;\\\"\\n cur.execute(sql, (id,))\\n return cur.fetchall()\\n except:\\n print(\\\"Cannot find the film!\\\")\\n\\n db.close()\",\n \"def load_enron():\\n connection=apsw.Connection(\\\"enron.db\\\")\\n cursor=connection.cursor()\\n\\n \\n cursor.execute(\\\"CREATE VIRTUAL TABLE corpus USING fts4(rowid, title, body);\\\")\\n\\n\\n enrondir = \\\"/Users/jonas/Downloads/enron_mail_20110402/maildir\\\"\\n\\n pi = 0\\n \\n for dirpath, dirnames, filenames in os.walk(enrondir):\\n for filename in filenames:\\n try:\\n subject, body = enron.parse_file(os.path.join(dirpath, filename))\\n \\n cursor.execute(\\\"insert into corpus values(?,?,?)\\\", (pi, subject, body))\\n except:\\n pass\\n \\n if pi % 100 == 0:\\n print pi\\n pi += 1\",\n \"def detect(self, fstring, fname=None):\\n return True\",\n \"def test_find_processed_file(self):\\n\\n this_file_name = tornado_io.find_processed_file(\\n directory_name=TORNADO_DIRECTORY_NAME, year=YEAR,\\n raise_error_if_missing=False)\\n\\n self.assertTrue(this_file_name == TORNADO_FILE_NAME)\",\n \"def __searchFiles(self):\\n self.ui.showFindFilesDialog(self.textForFind())\",\n \"def download_movie(self, filmid):\\n self.logger.debug('download_movie')\\n if not self._test_download_path(self.settings.getDownloadPathMovie()):\\n return\\n film = self.database.retrieve_film_info(filmid)\\n if film is None:\\n return\\n (filmurl, extension,) = self._get_film_url_and_extension(film)\\n # try to create a good name for the downloaded file\\n namestem = mvutils.cleanup_filename(film.title)[:80]\\n if not namestem:\\n # try to take the show name instead...\\n namestem = mvutils.cleanup_filename(film.show)[:64]\\n if not namestem:\\n namestem = u'Film'\\n namestem = namestem + '-{}'.format(film.filmid)\\n elif self.settings.getMovieNameWithShow():\\n showname = mvutils.cleanup_filename(film.show)[:64]\\n if showname:\\n namestem = showname + ' - ' + namestem\\n # review name\\n if self.settings.getReviewName():\\n (namestem, confirmed) = self.notifier.get_entered_text(namestem, 30986)\\n namestem = mvutils.cleanup_filename(namestem)\\n if len(namestem) < 1 or confirmed is False:\\n return\\n # determine destination path and film filename\\n if self.settings.getUseMovieFolder():\\n pathname = self.settings.getDownloadPathMovie() + namestem + '/'\\n filename = namestem\\n else:\\n pathname = self.settings.getDownloadPathMovie()\\n filename = namestem\\n # check for duplicate\\n # keep\\n if self.settings.getFileExistsAction() == 1 and xbmcvfs.exists(pathname + filename + extension):\\n return\\n # prompt\\n if self.settings.getFileExistsAction() == 0:\\n while xbmcvfs.exists(pathname + filename + extension):\\n (filename, confirmed) = self.notifier.get_entered_text(filename, 30987)\\n filename = mvutils.cleanup_filename(filename)\\n if len(filename) < 1 or confirmed is False:\\n return\\n\\n # download the stuff\\n if self._download_files(film, filmurl, pathname, filename, extension):\\n self._make_movie_nfo_file(film, filmurl, pathname, filename)\\n else:\\n self.logger.debug('download_movie ERROR')\",\n \"def is_hmmer_hmmsearch_file(f):\\n #HMMER output doesn't have a specific file extension\\n with open(f) as hmmer_file:\\n try:\\n return hmmer_file.next().startswith(\\\"% hmmsearch\\\")\\n except StopIteration:\\n return False\",\n \"def findByFileName(fileName, get_movie_name_only = False):\\r\\n MovieName = 'MovieName'\\r\\n queryresult = None\\r\\n\\r\\n movienamequery = IOpenSubtitlesProvider.FormatQuery(\\r\\n {'query' : fileName})\\r\\n try:\\r\\n #send the query\\r\\n queryresult = IOpenSubtitlesProvider.GetServer().SearchSubtitles(\\r\\n IOpenSubtitlesProvider.GetToken(), \\r\\n [movienamequery])\\r\\n queryresult = queryresult['data']\\r\\n except Exception as eX:\\r\\n WriteDebug(eX)\\r\\n\\r\\n if queryresult:\\r\\n is_episode = queryresult[0]['MovieKind'] == 'episode'\\r\\n if get_movie_name_only: \\r\\n if is_episode:\\r\\n res = queryresult[0][MovieName]\\r\\n queryresult = Utils.getregexresults('\\\"(.*?)\\\"', res)[0]\\r\\n else:\\r\\n queryresult = queryresult[0][MovieName]\\r\\n else: queryresult = queryresult\\r\\n else:\\r\\n queryresult = None\\r\\n\\r\\n return queryresult\",\n \"def find_calib_file(self, runnum=0) :\\n cfile = find_calib_file_in_list_for_run(self.list_of_sorted_calib_files(), runnum)\\n #cfile.print_member_data()\\n if cfile is None : return ''\\n else : return os.path.join(self.path, cfile.get_basename())\",\n \"def fsearch(self,pattern,msg=None, killon=None ):\\n import re\\n current=0\\n cpat=re.compile(pattern)\\n\\n for num,line in enumerate(self.f):\\n if killon:\\n kill = re.search(killon,line)\\n if kill:\\n # the kill phrase was found first, so die. \\n return False\\n current=re.search(cpat,line)\\n if current:\\n if msg:\\n print msg\\n break\\n if not current:\\n# print 'ERROR: Requested pattern ('+pattern+') not found in file: <'+self.f.name+ '>. Check file for correct structure. Exiting...'\\n return False\\n\\n return line\",\n \"async def movievotes(self, ctx: discord.ext.commands.Context, *args):\\n print(\\\"-------------------------\\\")\\n message_channel: discord.abc.Messageable = ctx.message.channel\\n if len(args) == 1:\\n print(\\\"Starting search\\\")\\n api_key = self.botVariables.get_mashape_metacritic_key()\\n search_term = (re.sub(r'([^\\\\s\\\\w]|_)+', '', args[0])).lower()\\n request_search_link = \\\"https://api-marcalencc-metacritic-v1.p.mashape.com/search/\\\" + str(\\n urllib.parse.quote(search_term)) + \\\"/movie?limit=20&offset=1\\\"\\n # search all the films with the term given\\n async with aiohttp.ClientSession() as session:\\n # the website use get\\n async with session.get(request_search_link, headers={'X-Mashape-Key': str(api_key),\\n 'Accept': 'application/json'}) as resp:\\n request_result = await resp.json()\\n if len(request_result[0]['SearchItems']) > 0: # there is at least one film\\n films_found = []\\n max_prob = 0.0\\n # decide the best film using string similarity\\n for entry in request_result[0]['SearchItems']:\\n entry_string = (re.sub(r'([^\\\\s\\\\w]|_)+', '', entry['Title'])).lower()\\n film_similarity = BotMethods.similar(search_term, entry_string, None)\\n if film_similarity > 0.7: # consider it only if it's > 0.7 (range is 0.0-1.0)\\n films_found.append(\\n self.FilmInfo(entry['Id'], entry['Title'], film_similarity)) # store that film in the array\\n if film_similarity > max_prob: # search for max prob\\n max_prob = film_similarity\\n if film_similarity >= 1.0: # i have found the perfect string\\n print(\\\"Perfect name found, search cycle stopped\\\")\\n break # stop the for\\n if len(films_found) > 0: # i have found at least one possible film\\n film_web_id = \\\"\\\"\\n for film in films_found: # search the film with the max name similarity in the array\\n if film.similar == max_prob:\\n print(\\\"Film Chosen: \\\" + film.film_name + \\\" - Film web id:\\\" + str(\\n film.film_id) + \\\" - Sim.:\\\" + str(\\n max_prob))\\n film_web_id = film.film_id # get the film web id\\n break\\n # make request to get all necessary film informations\\n request_search_link = \\\"https://api-marcalencc-metacritic-v1.p.mashape.com\\\" + str(film_web_id)\\n async with aiohttp.ClientSession() as session:\\n async with session.get(request_search_link, headers={'X-Mashape-Key': str(api_key),\\n 'Accept': 'application/json'}) as resp: # the website use get\\n request_result = await resp.json()\\n if 'message' in request_result:\\n await message_channel.send(\\\"*An error occurred downloading the data...*\\\")\\n return\\n # prepare the embed message\\n embed = discord.Embed(title=str(request_result[0]['Title']),\\n colour=discord.Colour(0xffcc00),\\n url=\\\"http://www.metacritic.com\\\" + str(film_web_id),\\n description=\\\"Metacritic votes about \\\" + str(\\n request_result[0]['Title']) + \\\" by \\\" + str(\\n request_result[0]['Director']) + \\\", released on \\\" + str(\\n request_result[0]['ReleaseDate']),\\n timestamp=datetime.utcfromtimestamp(time.time())\\n )\\n if 'ImageUrl' in request_result[0]:\\n embed.set_thumbnail(url=str(request_result[0]['ImageUrl']))\\n else:\\n print(\\\"No ImageUrl found, no thumbnail set\\\")\\n embed.set_author(name=ctx.message.author.name, url=\\\"\\\", icon_url=ctx.message.author.avatar_url)\\n embed.set_footer(text=self.botVariables.get_description(),\\n icon_url=self.botVariables.get_bot_icon())\\n if len(request_result[0]['Rating']) > 0:\\n # --- read users votes ---\\n user_votes = \\\"Rating: \\\" + str(request_result[0]['Rating']['UserRating']) + \\\" (\\\" + str(\\n request_result[0]['Rating']['UserReviewCount']) + \\\" votes)\\\"\\n # --- read critic votes ---\\n critic_votes = \\\"Rating: \\\" + str(request_result[0]['Rating']['CriticRating']) + \\\" (\\\" + str(\\n request_result[0]['Rating']['CriticReviewCount']) + \\\" votes)\\\"\\n # --- create fields ---\\n embed.add_field(name=\\\"Critic Rating\\\", value=critic_votes)\\n embed.add_field(name=\\\"User Rating\\\", value=user_votes)\\n else:\\n embed.add_field(name=\\\"No votes found...\\\",\\n value=\\\"Looks like there are no votes for this film...\\\")\\n # --- sending the message ---\\n print(\\\"Sending film embed message\\\")\\n await message_channel.send(embed=embed)\\n else:\\n print(\\\"No films found\\\")\\n await message_channel.send(\\\"*No films found, check the name...*\\\")\\n else:\\n print(\\\"No films found\\\")\\n await message_channel.send(\\\"*No films found, check the name...*\\\")\\n else:\\n await message_channel.send(\\n \\\"**Usage:** \\\" + self.command_prefix + \\\"movievotes <film Title>, for more see \\\" + self.command_prefix + \\\"help movievotes\\\")\\n print(\\\"-------------------------\\\")\",\n \"def LoadMetadata(filename):\\r\\n## print filename\\r\\n globbed=glob.glob(os.path.join(os.path.dirname(filename),'*.zvi'))\\r\\n if globbed:\\r\\n return LoadZVIMetaData(globbed[0])\\r\\n globbed=glob.glob(os.path.join(os.path.dirname(filename),'*.xml'))\\r\\n if globbed:\\r\\n return LoadAxioVisionXMLMetaData(globbed[0])\\r\\n globbed=glob.glob(os.path.join(os.path.dirname(filename),'metadata.txt'))\\r\\n if globbed:\\r\\n return LoadMMMetaData(globbed[0])\\r\\n return None\\r\\n #no further valid options, crash horribly\\r\",\n \"def open(self):\\n file = askopenfilename(\\n initialdir=self.initial_directory,\\n filetypes=(\\n (\\\"Audio Video Interleave\\\", \\\"*.avi\\\"),\\n (\\\"Matroska\\\", \\\"*.mkv\\\"),(\\\"MPEG-4 AVC\\\",\\\"*.mp4\\\"),\\n )\\n )\\n if isinstance(file, tuple):\\n return\\n if os.path.isfile(file):\\n self.play_film(file)\",\n \"def find_FEfiles(self):\\n \\n\\t\\t# take each item in the list of files to eve.\\n for i in self.files_to_find:\\n filename1 = i[0] \\n file1_dye = i[1]\\n filename2 = i[2]\\n file2_dye = i[3]\\n out_file_prefix=i[4]\\n\\n # set filename as none to help identify when no match has been found below\\n file1_filename = None\\n file2_filename = None\\n\\n # search for a FE file which matches the filename pattern\\n for afile in os.listdir(self.chosenfolder):\\n # file 1\\n if fnmatch.fnmatch(afile, filename1):\\n file1_filename = afile\\n \\n # file 2\\n if fnmatch.fnmatch(afile, filename2):\\n file2_filename = afile\\n \\n # if both files have been identified add this to a new list\\n if file1_filename and file2_filename:\\n self.list_of_files.append((file1_filename, file1_dye, file2_filename, file2_dye,out_file_prefix))\\n\\t\\t\\t# if either file could not be identified report this.\\n else:\\n raise ValueError(\\\"no match for \\\" + filename1 + \\\" and \\\" + filename2)\",\n \"def test_findfile_outdir(self):\\n from ..io.meta import findfile\\n outdir = '/blat/foo/bar'\\n x = findfile('fibermap', night='20150101', expid=123, outdir=outdir)\\n self.assertEqual(x, os.path.join(outdir, os.path.basename(x)))\",\n \"def search_file(filename, term):\\n try:\\n filepath = root + filename\\n with open(filepath) as file:\\n return term in file.read().splitlines()\\n except FileNotFoundError:\\n with open(filepath,\\\"w+\\\") as file:\\n return (search_file(filename, term))\",\n \"def find(pattern):\\n files = config.index.files(path_glob=\\\"*%s*\\\" % pattern)\\n print_files(files)\",\n \"def filesearch(word=\\\"\\\"):\\n logger.info('Starting filesearch')\\n file = []\\n for f in glob.glob(\\\"*\\\"):\\n if word[0] == \\\".\\\":\\n if f.endswith(word):\\n file.append(f)\\n\\n elif word in f:\\n file.append(f)\\n #return file\\n logger.debug(file)\\n return file\",\n \"def find(location, path):\\n\\n index = AnnoyIndex(64, metric='hamming')\\n index.load('live/phash_index.ann')\\n\\n # get the requested image\\n if location == 'url':\\n MAX_DOWNLOAD = 15 * 1024 * 1024\\n response = requests.get(path, stream=True)\\n size = 0\\n content = bytearray()\\n for chunk in response.iter_content(1024):\\n size += len(chunk)\\n content += chunk\\n if size > MAX_DOWNLOAD:\\n raise ValueError\\n img = Image.open(BytesIO(content))\\n else:\\n img = Image.open(path)\\n\\n # get the image's phash\\n phash = imagehash.phash(img)\\n phash_arr = phash.hash.flatten()\\n\\n # find the closest mateches\\n results = index.get_nns_by_vector(phash_arr, 16, include_distances=True)\\n\\n conn = sqlite3.connect('live/twitter_scraper.db')\\n c = conn.cursor()\\n\\n basenames = []\\n tweet_ids = []\\n\\n # look up the location of the match and its tweet info\\n first = True\\n for idx, score in map(list, zip(*results)):\\n if not first and score > 8:\\n break\\n first = False\\n\\n print('score: {}'.format(score))\\n c.execute('SELECT path, filename FROM annoy WHERE idx=(?)', (idx,))\\n dirname, basename = c.fetchone()\\n fullpath = os.path.join(dirname, basename)\\n c.execute('SELECT id FROM info WHERE filename=(?) AND path=(?)', (basename, dirname))\\n tweet_id = c.fetchone()\\n print(tweet_id)\\n tweet_id = tweet_id[0]\\n\\n print('local path: {}'.format(fullpath))\\n print('direct link: https://pbs.twimg.com/media/{}'.format(basename))\\n print('source tweet: https://www.twitter.com/statuses/{}'.format(tweet_id))\\n print()\\n\\n basenames.append(basename)\\n tweet_ids.append(tweet_id)\\n\\n conn.close()\\n return basenames, tweet_ids\",\n \"def extract_vob(in_vob, guid):\\n\\t#Detect interlacing.\\n\\tmediainfo_command = \\\"mediainfo --Inform='Video;%ScanType%,%ScanOrder%' \\\" + in_vob\\n\\tprint(mediainfo_command)\\n\\tprocess = subprocess.Popen(mediainfo_command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\\n\\t(cout, cerr) = process.communicate()\\n\\texit_code = process.wait()\\n\\tif exit_code != 0:\\n\\t\\traise Exception(\\\"Calling Mediainfo on {in_vob} failed with exit code {exit_code}.\\\".format(in_vob=in_vob, exit_code=exit_code))\\n\\tmediainfo_parts = cout.decode(\\\"utf-8\\\").split(\\\",\\\")\\n\\tis_interlaced = mediainfo_parts[0] == \\\"Interlaced\\\"\\n\\tfield_order = mediainfo_parts[1].lower().strip()\\n\\tprint(\\\"Interlace detection:\\\", is_interlaced, field_order, \\\"(\\\", mediainfo_parts, \\\")\\\")\\n\\n\\tffmpeg_command = [\\\"ffmpeg\\\", \\\"-i\\\", in_vob]\\n\\tprint(ffmpeg_command)\\n\\tprocess = subprocess.Popen(ffmpeg_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\\n\\t(cout, cerr) = process.communicate()\\n\\tprocess.wait() #Ignore the exit code. It always fails.\\n\\tvobinfo = cerr.decode(\\\"utf-8\\\")\\n\\ttracks = []\\n\\tfor match in re.finditer(r\\\" Stream #0:(\\\\d+)\\\\[0x[0-9a-f]+\\\\]: (\\\\w+): ([^\\\\n]+)\\\", vobinfo):\\n\\t\\ttrack_nr = match.group(1)\\n\\t\\ttrack_type = match.group(2)\\n\\t\\ttrack_codec = match.group(3)\\n\\t\\tnew_track = track.Track()\\n\\t\\tnew_track.from_vob(track_nr, track_type, track_codec, is_interlaced, field_order)\\n\\t\\tnew_track.file_name = guid + \\\"-T\\\" + str(new_track.track_nr) + \\\".\\\" + new_track.codec\\n\\t\\tif new_track.type != \\\"unknown\\\":\\n\\t\\t\\ttracks.append(new_track)\\n\\n\\t#Generate the parameters to pass to ffmpeg.\\n\\ttrack_params = [\\\"-i\\\", in_vob]\\n\\tfor track_metadata in tracks:\\n\\t\\ttrack_params.append(\\\"-map\\\")\\n\\t\\ttrack_params.append(\\\"0:\\\" + str(track_metadata.track_nr))\\n\\t\\ttrack_params.append(\\\"-c\\\")\\n\\t\\ttrack_params.append(\\\"copy\\\")\\n\\t\\ttrack_params.append(track_metadata.file_name)\\n\\n\\t#Extract all tracks.\\n\\tprint(\\\"---- Extracting tracks...\\\")\\n\\tffmpeg(*track_params)\\n\\n\\treturn tracks\",\n \"def watch_movie():\\r\\n if os.path.isfile('files/final_movie.mp4'): # if the file exists\\r\\n with open('files/final_movie.mp4', 'rb') as f:\\r\\n video_data = f.read()\\r\\n st.video(video_data)\\r\\n else: # if the file doesn't exist, let the user know\\r\\n st.header(\\\"You haven't created a movie yet!\\\")\",\n \"def find_obsid_src(obsid, obs):\\n if obs['readmode'] == 'CONTINUOUS':\\n return None\\n\\n if obs['obs_mode'] == 'SECONDARY':\\n return None\\n\\n if ((obs['instrume'] == 'ACIS') & (obs['detector'] == 'HRC-S')):\\n return None\\n\\n xray_data = XRAY_DATA\\n if not os.path.exists(xray_data):\\n os.makedirs(xray_data)\\n obsdir = os.path.join(xray_data, 'obs%05d' % obsid)\\n if not os.path.exists(obsdir):\\n os.makedirs(obsdir)\\n\\n no_source = os.path.join(obsdir, \\\"has_no_source\\\")\\n if os.path.exists(no_source):\\n return None\\n\\n srcfiles = glob(os.path.join(obsdir, '*src2*'))\\n src_json = '{}/evtinfo.json'.format(obsdir)\\n if len(srcfiles) and os.path.exists(src_json) and not REDO :\\n src = get_source(obs['obsid'], obs['obi'], obsdir)\\n return src\\n\\n # Fetch X-ray events\\n tempdir = tempfile.mkdtemp(dir='/export/jeanconn/tempdir/')\\n det = 'acis'\\n if (obs['instrume'] == 'HRC'):\\n det = 'hrc'\\n bash('echo \\\"cd %s\\\\n obsid=%d\\\\n get %s2{evt2}\\\\n\\\" | arc5gl -stdin' % (tempdir, obs['obsid'], det))\\n event_files = glob(\\\"%s/*evt2*gz\\\" % tempdir)\\n if not len(event_files):\\n return None\\n if len(event_files) > 1:\\n return None\\n bash('gunzip %s' % event_files[0])\\n event_files = glob(\\\"%s/*evt2*\\\" % tempdir)\\n # Read processing keywords from the evt2 file\\n f = fits.open(event_files[0])\\n if 'ASOLFILE' not in f[1].header:\\n return None\\n proc_info = {'ASCDSVER': f[1].header['ASCDSVER'],\\n 'CALDBVER': f[1].header['CALDBVER'],\\n 'REVISION': f[1].header['REVISION'],\\n 'ASOLFILE': f[1].header['ASOLFILE'],\\n 'OBS_ID': f[1].header['OBS_ID']}\\n # Get the X/Y for this detector from the header\\n for i in range(1, 30):\\n if 'TTYPE{}'.format(i) in f[1].header:\\n if f[1].header['TTYPE{}'.format(i)] == 'x':\\n proc_info['x_center'] = f[1].header['TCRPX{}'.format(i)]\\n proc_info['y_center'] = f[1].header['TCRPX{}'.format(i + 1)]\\n if f[1].header['TTYPE{}'.format(i)] == 'detx':\\n proc_info['detx_center'] = f[1].header['TCRPX{}'.format(i)]\\n proc_info['dety_center'] = f[1].header['TCRPX{}'.format(i + 1)]\\n if ((proc_info['detx_center'] != proc_info['x_center'])\\n or (proc_info['dety_center'] != proc_info['y_center'])):\\n raise ValueError\\n f.close()\\n # Save processing keywords out to a file\\n ph = open(src_json, 'w')\\n ph.write(json.dumps(proc_info, indent=4, sort_keys=True))\\n ph.close()\\n # Setup to run celldetect\\n pfiles = ';'.join([tempdir, ciao_env['PFILES'].split(';')[-1]])\\n outlines1, stat = tcsh_shell(\\\"env PFILES={} punlearn celldetect\\\".format(pfiles), env=ciao_env)\\n cmd = ('{} celldetect eenergy=0.9 infile=\\\"{}\\\" outfile=\\\"{}/{}_src2.fits\\\"'.format(\\n 'env LD_LIBRARY_PATH=\\\"\\\" PFILES=\\\"{}\\\"'.format(pfiles), event_files[0], obsdir, obs['obsid']))\\n # Run celldetect\\n outlines2, stat = tcsh_shell(cmd, env=ciao_env)\\n srcfiles = glob(os.path.join(obsdir, \\\"*src2*\\\"))\\n if len(srcfiles):\\n src = get_source(obs['obsid'], obs['obi'], obsdir)\\n if src is not None:\\n os.unlink(event_files[0])\\n else:\\n bash(\\\"touch {}\\\".format(no_source))\\n print \\\"no sources in {}\\\".format(event_files[0])\\n return src\\n else:\\n print(\\\"No src2 file was made\\\")\\n return None\",\n \"def find_file(path):\\n return NotImplemented\",\n \"def download(pattern):\\n query = pattern.lower()\\n videolist = getvideolist()\\n filename = []\\n for video in videolist:\\n for value in video.values():\\n if query in str(value).lower():\\n filename.append(video[\\\"file\\\"])\\n if filename:\\n for name in filename:\\n downloadvideo(name)\\n else:\\n safeprint(\\\"No video matching the given query was found.\\\")\",\n \"def get_matches(self, file_map) -> dict:\\r\\n get_file_dict = {}\\r\\n match_dict = {\\r\\n 'GIF': re.findall(b'(?s)(\\\\x47\\\\x49\\\\x46\\\\x38\\\\x39\\\\x61.{80})', file_map),\\r\\n 'RTF': re.findall(b'(?s)(.{20}\\\\x35\\\\x30\\\\x34\\\\x65\\\\x34\\\\x37\\\\x30.{80}|.{20}\\\\x66\\\\x66\\\\x64\\\\x38\\\\x66\\\\x66.{80}|'\\r\\n b'.{20}\\\\x66\\\\x66\\\\x64\\\\x38\\\\x66\\\\x66\\\\x65\\\\x30\\\\x30\\\\x30\\\\x31\\\\x30.{80})', file_map),\\r\\n }\\r\\n if self.jpgsos:\\r\\n match_dict['JPG_SOS'] = jpg_sos(file_map)\\r\\n elif self.sof2sos:\\r\\n match_dict['JPG_SOF2SOS'] = jpg_sof2sos(file_map)\\r\\n elif self.jump:\\r\\n match_dict['JPG_JUMP'] = jpg_jump(file_map)\\r\\n else:\\r\\n match_dict['JPG'] = re.findall(b'(?s)(\\\\xff\\\\xd8\\\\xff\\\\xe0\\\\x00\\\\x10.{80})', file_map)\\r\\n match_dict['JPG2'] = re.findall(b'(?s)(\\\\xff\\\\xd8\\\\xff.{80})', file_map)\\r\\n if self.idat:\\r\\n match_dict['PNG_IDAT'] = idat(file_map)\\r\\n else:\\r\\n match_dict['PNG'] = re.findall(b'(?s)(\\\\x89\\\\x50\\\\x4e\\\\x47.{82})', file_map)\\r\\n m = re.match(br'^(?P<magic_beans>\\\\x49\\\\x49\\\\x2a\\\\x00[^\\\\x00\\\\x00]{2}.{80})',file_map,re.S)\\r\\n if m:\\r\\n match_dict['TIF'] = [m.group('magic_beans')]\\r\\n for file_type, regex_match in match_dict.items():\\r\\n if len(regex_match) > 0:\\r\\n get_file_dict[file_type] = regex_match\\r\\n return get_file_dict\",\n \"def test_afni_afni():\\n im = ndar.Image('test_data/NDAR_INVZU049GXV_image03_1326225820791.zip')\\n assert im.afni == im.path(im.files['AFNI'][0])\",\n \"def find_dsym_file(project, image_uuid):\\n image_uuid = image_uuid.lower()\\n try:\\n return ProjectDSymFile.objects.filter(\\n uuid=image_uuid,\\n project=project\\n ).select_related('file', 'file__blob').get()\\n except ProjectDSymFile.DoesNotExist:\\n pass\\n try:\\n return GlobalDSymFile.objects.filter(\\n uuid=image_uuid\\n ).select_related('file', 'file__blob').get()\\n except GlobalDSymFile.DoesNotExist:\\n return None\",\n \"def findAudioFile(self,kinfilename):\\r\\n progress = QtGui.QProgressDialog(\\\"Searching for Audio File...\\\",QtCore.QString(), 0,0,parent = self)\\r\\n progress.setMinimumDuration(250)\\r\\n\\r\\n (filename, _) = os.path.splitext(os.path.basename(kinfilename))\\r\\n pattern = filename.split('_BPC')[0] + '.wav'\\r\\n fullpath = os.path.dirname(kinfilename)\\r\\n toSearch = []\\r\\n audiofilename = None\\r\\n for i in self.find(fullpath,'/'):\\r\\n toSearch.append(fullpath[:i])\\r\\n toSearch.reverse()\\r\\n toSearch.append(fullpath)\\r\\n for loc in toSearch:\\r\\n for filenames in os.walk(loc):\\r\\n for filename in filenames:\\r\\n if pattern in filename:\\r\\n desiredFile = filename\\r\\n for files in desiredFile:\\r\\n if pattern == files:\\r\\n audiofilename = os.path.join(filenames[0],files)\\r\\n progress.destroy()\\r\\n return audiofilename\\r\\n if audiofilename is None:\\r\\n progress.destroy()\\r\\n return audiofilename\",\n \"def findframe(startdir,camera,grating,filename):\\n grating = re.sub(\\\"\\\\/\\\",\\\"_\\\",grating)\\n gdir = camera + grating\\n if os.path.isfile(os.path.join(startdir,filename)):\\n return(startdir)\\n else:\\n # now the grating directory\\n if os.path.isfile(os.path.join(startdir,gdir,filename)):\\n return(os.path.join(startdir,gdir))\\n poswavedirs = glob.glob(os.path.join(startdir,gdir) + '/w*')\\n wavedirs = []\\n\\n for pwd in poswavedirs:\\n if re.search(\\\"w\\\\d+\\\",pwd):\\n wavedirs.append(pwd) \\n\\n\\n for wd in wavedirs:\\n # alright, now we search the subdirs\\n if os.path.isfile(os.path.join(wd,filename)):\\n return(wd)\\n\\n return(None)\",\n \"def readPlayerImageFiles(self):\\n currentPath = os.path.dirname(os.path.abspath(__file__))\\n listOfFileNames=[]\\n for i in os.listdir(currentPath):\\n if re.match(\\\"player\\\\_\\\\d+\\\",i): #i.endswith(\\\".gif\\\")\\n listOfFileNames.append(currentPath+'/'+i)\\n return listOfFileNames\",\n \"def __searchOpenFiles(self):\\n self.ui.showFindFilesDialog(self.textForFind(), openFiles=True)\",\n \"def get_tanimoto_from_isomif_file(pdb1, pdb2, i1, i2):\\n filename = pdb1 + 'h_' + str(i1) + '_match' + pdb2 + 'h_' + str(i2) + '.isomif'\\n with open(str(HIVE / 'match' / filename), 'rb', 0) as file, \\\\\\n mmap.mmap(file.fileno(), 0, access=mmap.ACCESS_READ) as s:\\n if s.find(b'TANIM') != -1:\\n pos = s.find(b'TANIM')\\n tanim = float(s[pos+6 : pos+12].decode('utf-8'))\\n else:\\n return -1\\n return tanim\",\n \"def main():\\n base_dir = '/home/sjimenez/imagenes_prueba'\\n out_dir = '/home/sjimenez/easy_analysis'\\n for _, _, files in os.walk(base_dir, topdown=False):\\n for f in files:\\n print('--------- {} ---------'.format(f))\\n act_dir = osp.join(base_dir, f)\\n act_im = cv2.imread(act_dir)\\n if act_im is not None:\\n get_image_stats(act_im, out_dir, f)\\n else:\\n print('Not able to open the image')\",\n \"def _run_lyrics_nogui(self):\\n self.read_files()\\n\\n # find lyrics\\n self._log_print(msg_GREEN=\\\"Searching for lyrics\\\")\\n\\n self.save_lyrics()\\n\\n if not self.write_tags():\\n self._log_print(msg_WHITE=\\\"Cannot write tags because there are no \\\"\\n \\\"coresponding files\\\")\\n else:\\n self._log_print(msg_GREEN=\\\"Done\\\")\",\n \"def find_files(directory, extension, magictext):\\n global files_logged\\n global found_text\\n dir_path = os.path.abspath(directory)\\n dir_files = os.listdir(dir_path)\\n for file in dir_files:\\n if file.endswith(extension) and file not in files_logged:\\n logger.info('New file found: {}'.format(file))\\n files_logged.append(file)\\n if file.endswith(extension):\\n file_path = os.path.join(dir_path, file)\\n if find_string_in_files(file_path, magictext):\\n break\\n for file in files_logged:\\n if file not in dir_files:\\n logger.info('File deleted: {}'.format(file))\\n files_logged.remove(file)\\n found_text[file] = 0\",\n \"def demo():\\n logging.basicConfig(level=logging.INFO, format=\\\"%(message)s\\\")\\n fcm = FMQLCacher(\\\"Caches\\\")\\n fcm.setVista(\\\"CGVISTA\\\", \\\"http://vista.caregraf.org/fmqlEP\\\")\\n \\\"\\\"\\\"\\n for i, scheme in enumerate(fcm.describeSchemaTypes()):\\n if \\\"count\\\" in scheme:\\n print \\\"%d: %s (%s)\\\" % (i, scheme[\\\"number\\\"], scheme[\\\"count\\\"])\\n else:\\n print \\\"%d: %s\\\" % (i, scheme[\\\"number\\\"])\\n \\\"\\\"\\\"\\n for entry in fcm.describeFileEntries(\\\"9_6\\\", cstop=\\\"1000\\\"):\\n print entry[\\\"uri\\\"][\\\"label\\\"]\",\n \"def _search_path_to_file(self, directory, binary_name):\\n for root, dirs, files in os.walk(directory):\\n if binary_name in files:\\n return os.path.join(root, binary_name)\\n raise micp_kernel.NoExecutableError\",\n \"def file_name_search():\\n directory = \\\"/Users/andrewpowers/Documents/server/fastq_pass\\\"\\n\\n for file in os.listdir(directory):\\n output_file = re.sub('fastq', 'fasta', file)\\n os.system(bash_command.format(directory+\\\"/\\\"+file, output_file))\\n print('File {} converted to fasta.'.format(file))\\n print('Conversion Done.')\",\n \"def findReferenceImage(modelfile):\\n\\n try:\\n\\n dirname = op.dirname(modelfile)\\n prefixes = [getFIRSTPrefix(modelfile)]\\n except ValueError:\\n return None\\n\\n if prefixes[0].endswith('_first'):\\n prefixes.append(prefixes[0][:-6])\\n\\n for p in prefixes:\\n try:\\n return fslimage.addExt(op.join(dirname, p), mustExist=True)\\n except fslimage.PathError:\\n continue\\n\\n return None\",\n \"def find_metadata_file(diagnostics_dir, file_pattern, verbose=False):\\n if not diagnostics_dir:\\n return None\\n metadata_dir = os.path.dirname(diagnostics_dir) + '/metadata'\\n if not os.path.isdir(metadata_dir):\\n if verbose:\\n print(\\\"Unable to find metadata dir at\\\", metadata_dir)\\n return None\\n metafiles = sorted(glob.glob(metadata_dir+'/'+file_pattern))\\n if len(metafiles) == 0:\\n if verbose:\\n print(\\\"Unable to find metdata file wiht pattern {} in {}\\\".format(file_pattern, metadata_dir))\\n return None\\n metadata_file = metafiles[0]\\n return metadata_file\",\n \"def find_flames(filename):\\r\\n image = SimpleImage(filename)\\r\\n # TODO: your code here\\r\\n return image\",\n \"def iOFTPMatch(filename):\\n ret = libxml2mod.xmlIOFTPMatch(filename)\\n return ret\",\n \"def getFilmTitles(checkFolder):\\n\\n files = [str(x) for x in Path(checkFolder).rglob(\\\"*\\\")]\\n libFilmFiles = list(map(os.path.basename,files)) # Remove the path\\n libFilmTitles = [os.path.splitext(x)[0] for x in libFilmFiles]\\n return libFilmTitles\",\n \"def extract_meta_data(video_file_name, output_file=meta.txt, *args, **kwargs):\",\n \"def findFileLinearly(filename):\\n #construct message\\n id = generateUniqueID()\\n msg = query(generateUniqueID(), GLOBALS.TTL, filename)\\n\\n #connect to neighbor\\n neighbor = connectToSuperPeer(GLOBALS.NEIGHBOR_IP, GLOBALS.NEIGHBOR_PORT)\\n if neighbor == -1: return -1\\n if GLOBALS.DEBUG_MODE: print(\\\"[info] Linear lib: connected to neighbor\\\")\\n\\n #send query\\n sendMessage(neighbor, msg)\\n\\n #wait for query responces\\n while True:\\n responce = receiveMessage(neighbor)\\n if responce == -1: break # connection closed\\n elif responce == 0: break\\t# connection shutdown\\n yield responce\\n neighbor.close()\",\n \"def _findfile(self,path,label):\\n files=[];filenames=os.listdir(path)\\n for name in filenames:\\n if os.path.splitext(name)[0]==str(label):\\n files.append(name)\\n return files\",\n \"def find_filter_phot(path = defaults._default_data_dir_path, snname = False,\\n prefix = 'SN', file_type = '.dat',\\n verbose = False):\\n # regex = re.compile(\\\"^SN.*.dat\\\")\\n\\n errors.StringWarning(path)\\n if not utils.check_dir_path(path):\\n # return False\\n raise errors.PathError\\n\\n\\n try:\\n if snname:\\n match_string = \\\"^\\\" + str(snname) + \\\".*\\\" + '.dat'\\n else:\\n match_string = \\\"^\\\" + str(prefix) + \\\".*\\\" + '.dat'\\n except:\\n raise TypeError\\n\\n regex = re.compile(match_string)\\n\\n ls = os.listdir(path)\\n\\n phot_list = [os.path.join(path, match.group(0)) for file_name in ls for match in [regex.search(file_name)] if match]\\n\\n if os.path.join(path, snname + file_type) in phot_list:\\n phot_list.remove(os.path.join(path,snname + file_type))\\n warnings.warn(\\\"Found \\\" + os.path.join(path,snname + file_type) + \\\" - you could just read that in.\\\")\\n\\n if verbose:\\n print(\\\"searching for\\\", match_string)\\n print(\\\"Found: \\\")\\n print(ls)\\n print(\\\"Matched:\\\")\\n print(phot_list)\\n if len(phot_list) is 0:\\n warnings.warn(\\\"No matches found.\\\")\\n return phot_list\",\n \"def test_find_anglerfish_results(self):\\n anglerfish_dir = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2/anglerfish_output'\\n run_dir = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2'\\n run = MinIONqc(run_dir, None, None)\\n found_file = run._find_anglerfish_results()\\n expected_file = os.path.join(anglerfish_dir, 'anglerfish_2020_09_23_141922', 'anglerfish_stats.txt')\\n self.assertEqual(expected_file, found_file)\",\n \"def lookForDB():\\n done = False\\n msg = \\\"\\\"\\n i = 0\\n while not done:\\n dbfilnam = \\\"SpeciesDB{}.txt\\\".format(i+1)\\n path = os.path.join(progpath, dbfilnam)\\n if os.path.exists(path):\\n with open(path) as f:\\n lines = f.read().splitlines()\\n if len(lines):\\n title = \\\"\\\"\\n for l, lin in enumerate(lines):\\n if l == 0:\\n DBnames.append(lines[0].strip(\\\"# \\\"))\\n i += 1\\n else:\\n lin = lin.strip(\\\"# \\\")\\n if lin == \\\"\\\" or lin.startswith(\\\"List of species\\\"):\\n DBtitles.append(title)\\n break\\n else:\\n title += \\\"{}<br>\\\".format(lin)\\n else:\\n msg = \\\"No data in the file {}\\\".format(dbfilnam)\\n done = True\\n else:\\n done = True\\n if i == 0:\\n msg = \\\"No database were found !\\\"\\n if msg == \\\"\\\":\\n return True\\n QtWidgets.QMessageBox.critical(None, appName, msg)\\n return False\",\n \"def crawl_by_title(movie_name, verbose, year=None, parent_pbar=None):\\n def _print(msg):\\n if verbose:\\n if parent_pbar is not None:\\n parent_pbar.set_description(msg)\\n parent_pbar.refresh()\\n sys.stdout.flush()\\n tqdm()\\n else:\\n print(msg)\\n\\n os.makedirs(_IMDB_DIR_PATH, exist_ok=True)\\n file_name = _parse_name_for_file_name(movie_name) + '.json'\\n file_path = os.path.join(_IMDB_DIR_PATH, file_name)\\n if os.path.isfile(file_path):\\n _print('{} already processed'.format(movie_name))\\n return _result.EXIST\\n\\n # _print(\\\"Extracting a profile for {} from IMDB...\\\".format(movie_name))\\n try:\\n props = crawl_movie_profile(movie_name, year)\\n # _print(\\\"Profile extracted succesfully\\\")\\n # _print(\\\"Saving profile for {} to disk...\\\".format(movie_name))\\n with open(file_path, 'w+') as json_file:\\n # json.dump(props, json_file, cls=_RottenJsonEncoder, indent=2)\\n json.dump(props, json_file, indent=2)\\n _print(\\\"Done saving a profile for {}.\\\".format(movie_name))\\n return _result.SUCCESS\\n except Exception as exc:\\n _print(\\\"Extracting a profile for {} failed\\\".format(movie_name))\\n # traceback.print_exc()\\n return _result.FAILURE\\n # print(\\\"Extracting a profile for {} failed with:\\\".format(movie_name))\\n # raise exc\",\n \"def list_images_in_dataset(f):\\n # list ms images\\n # the '-not \\\\( -path *_files -prune \\\\)' is to avoid entering in the dzi\\n # folders, which contains tens of thousands jpeg files and make the process\\n # very slow\\n p = subprocess.Popen(\\\"find %s -not \\\\( -path *_files -prune \\\\) -type f -name \\\\\\\"*_MS_*.JP2.TIF\\\\\\\"\\\" % f, shell=True, stdout=subprocess.PIPE)\\n ms_files = p.stdout.read().splitlines()\\n p = subprocess.Popen(\\\"find %s -not \\\\( -path *_files -prune \\\\) -type f -name \\\\\\\"*_P_*.JP2.TIF\\\\\\\"\\\" % f, shell=True, stdout=subprocess.PIPE)\\n pan_files = p.stdout.read().splitlines()\\n if not ms_files:\\n print(\\\"no MS images in dataset %s\\\" % f, file=sys.stderr)\\n return pan_files\\n else:\\n out = []\\n for ms in ms_files:\\n try:\\n date_ms = re.split('_', os.path.basename(ms))[3]\\n except IndexError:\\n print(\\\"non standard filename in dataset %s\\\" % f, file=sys.stderr)\\n return pan_files\\n # search for the pan file with the same date\\n matching_pan = None\\n for pan in pan_files:\\n if re.split('_', os.path.basename(pan))[3] == date_ms:\\n matching_pan = pan\\n break\\n if matching_pan is None:\\n print(\\\"no matching panchro image found for %s\\\" % ms, file=sys.stderr)\\n else:\\n out.append((matching_pan, ms))\\n return out\",\n \"def is_video(mine=None, file=None):\\n if file:\\n mine = get_file_mine(file)\\n print(mine)\\n\\n if mine:\\n return mine.find('video') != -1\\n\\n return False\",\n \"def identify_dvd(job):\\n # Added from pull 366\\n \\\"\\\"\\\" Manipulates the DVD title and calls OMDB to try and \\t\\n lookup the title \\\"\\\"\\\"\\n\\n # Safe way of dealing with log files if the users need to post it online\\n # cleanlog = makecleanlogfile(job)\\n # logging.debug(\\\"#### --- job ----\\\" + str(cleanlog))\\n\\n # Added from #338\\n # Some older DVDs aren't actually labelled\\n if not job.label or job.label == \\\"\\\":\\n job.label = \\\"not identified\\\"\\n\\n dvd_info_xml = False\\n dvd_release_date = \\\"\\\"\\n\\n # TODO: remove this because its pointless keeping when it can never work\\n try:\\n crc64 = pydvdid.compute(str(job.mountpoint))\\n fallback_title = \\\"{0}_{1}\\\".format(str(job.label), str(crc64))\\n dvd_title = str(fallback_title)\\n except pydvdid.exceptions.PydvdidException as e:\\n logging.error(\\\"Pydvdid failed with the error: \\\" + str(e))\\n dvd_title = fallback_title = str(job.label)\\n crc64 = \\\"\\\"\\n\\n logging.info(\\\"DVD CRC64 hash is: \\\" + str(crc64))\\n job.crc_id = str(crc64)\\n\\n # Dead needs removing\\n urlstring = \\\"http://metaservices.windowsmedia.com/pas_dvd_B/template/GetMDRDVDByCRC.xml?CRC={0}\\\".format(str(crc64))\\n logging.debug(urlstring)\\n\\n dvd_title = job.label\\n logging.debug(\\\"dvd_title_label= \\\" + str(dvd_title))\\n # strip all non-numeric chars and use that for year\\n year = re.sub(\\\"[^0-9]\\\", \\\"\\\", str(job.year))\\n # next line is not really needed, but we dont want to leave an x somewhere\\n dvd_title = job.label.replace(\\\"16x9\\\", \\\"\\\")\\n # Rip out any not alpha chars replace with\\n dvd_title = re.sub(\\\"[^a-zA-Z ]\\\", \\\" \\\", dvd_title)\\n logging.debug(\\\"dvd_title ^a-z= \\\" + str(dvd_title))\\n # rip out any SKU's at the end of the line\\n dvd_title = re.sub(\\\"SKU$\\\", \\\" \\\", dvd_title)\\n logging.debug(\\\"dvd_title SKU$= \\\" + str(dvd_title))\\n\\n # try to contact omdb\\n try:\\n dvd_info_xml = callwebservice(job, job.config.OMDB_API_KEY, dvd_title, year)\\n logging.debug(\\\"DVD_INFO_XML: \\\" + str(dvd_info_xml))\\n except OSError as e:\\n # we couldnt reach omdb\\n logging.error(\\\"Failed to reach OMDB\\\")\\n return False\\n\\n job.year = year\\n job.title = dvd_title\\n db.session.commit()\\n return True\",\n \"def get_files_search(query, video=False):\\n\\n creds = authenticate()\\n service = build('drive', 'v3', credentials=creds)\\n\\n folder_ids, folder_names = get_folder_ids(ROOT_PHOTO_FOLDER_ID)\\n files = []\\n found_files = []\\n gd_query = \\\"'{}' in parents and trashed = false and (mimeType = 'image/jpeg' or mimeType = 'image/png' or mimeType = 'image/svg+xml')\\\"\\n\\n if video:\\n gd_query = \\\"'{}' in parents and trashed = false and mimeType = 'video/mp4'\\\"\\n\\n for id in folder_ids:\\n page_token = None\\n response = service.files().list(q=gd_query.format(id),\\n pageSize=10,\\n spaces=\\\"drive\\\",\\n fields='nextPageToken, files(id, name, webViewLink, description)',\\n pageToken=page_token,\\n\\n ).execute()\\n files.extend(response[\\\"files\\\"]) # simply add to the current list of files found in other folders\\n\\n for file in files:\\n if (\\n file[\\\"name\\\"].rfind(query) != -1 or \\n \\\"description\\\" in file and file[\\\"description\\\"].rfind(query) != -1\\n ):\\n found_files.append(file)\\n\\n return found_files\",\n \"def lookup(collated_file,query_file):\\r\\n x=open(query_file,\\\"r\\\")\\r\\n query=[]\\r\\n for i in x:\\r\\n i=i.replace(\\\"\\\\n\\\",\\\"\\\")\\r\\n query.append(i)\\r\\n y=open(collated_file,\\\"r\\\")\\r\\n collection=[]\\r\\n for i in y :\\r\\n i=i.replace(\\\"\\\\n\\\",\\\"\\\")\\r\\n i=i.split(\\\":\\\")\\r\\n collection.append(i)\\r\\n answer=[]\\r\\n for i in range(len(query)):\\r\\n answer.append(BinarySearch(collection,0,len(collection)-1,query[i]))\\r\\n y = open(\\\"song_ids.txt\\\", \\\"w\\\")\\r\\n for i in range(len(answer)):\\r\\n y.write(str(answer[i]) + \\\"\\\\n\\\")\",\n \"def read_mastcam_dir(self, filepath, suffix, unit, feature, extension = '.IMG', lblext='.LBL_label', eye='LR', margin=6):\\n \\n if eye == 'L':\\n eyez = 'ML'\\n elif eye == 'R':\\n eyez = 'MR'\\n elif eye == 'LR':\\n eyez = ''\\n pass\\n else:\\n raise ValueError('Eye name %s is not valid! Use L, R, or LR.' % eye)\\n \\n # GET ALL FILES WITH GIVEN EXTENSION IN FILEPATH\\n files = sorted(glob.glob(str(filepath) + \\\"*\\\" + eyez + \\\"*\\\" + str(suffix) + \\\"*\\\" + str(extension)))\\n fileprefixes = sorted(list(set([f.split('/')[-1][0:12] for f in files])))\\n print(fileprefixes)\\n \\n print(\\\"found %d files among %d sequences with eye %s and extension %s in %s:\\\" % (len(files), len(fileprefixes), eye, extension, filepath))\\n assert len(files) > 0\\n \\n numfiles = len(fileprefixes)\\n seen = 0\\n percent = 0.0\\n printed = [False for foo in range(1000)]\\n \\n fullimages = {}\\n segmentation = {}\\n\\n data = []\\n self.labels = []\\n \\n for fileprefix in fileprefixes:\\n print(\\\" \\\" + fileprefix)\\n \\n thissequence = sorted(glob.glob(str(filepath) + fileprefix + \\\"*\\\" + str(suffix) + \\\"*\\\" + str(extension)))\\n asdfghjkl = 0\\n \\n parser = Parser()\\n seqfiltstr = \\\"\\\"\\n dimlist = []\\n for w in thissequence:\\n labels = parser.parse(open_pds(w.replace(extension, lblext))) \\n filt = labels['INSTRUMENT_STATE_PARMS']['FILTER_NAME'][9]\\n seqfiltstr += filt\\n h = int(labels['IMAGE']['LINES'])\\n w = int(labels['IMAGE']['LINE_SAMPLES'])\\n dimlist.append([h, w])\\n #print(\\\" %s %s %s\\\" % (filt, h, w))\\n\\n print(\\\"Filter name:\\\", labels['INSTRUMENT_STATE_PARMS']['FILTER_NAME'])\\n \\n #print(seqfiltstr)\\n # print(dimlist)\\n seqstocombine = []\\n \\n # Handle cases which appear to be several series of observations\\n if len(seqfiltstr) % 7 == 0:\\n for i in range(len(seqfiltstr) // 7):\\n subseq = thissequence[7*i:7*i+7]\\n subseqfilt = seqfiltstr[7*i:7*i+7]\\n if subseqfilt == '0123456':\\n cont = False\\n for j in range(7*i, 7*i+7):\\n if dimlist[7*i] != dimlist[j]:\\n print(\\\"SIZE ERROR\\\")\\n cont = True\\n if cont:\\n continue\\n \\n seqstocombine.append(subseq)\\n \\n else:\\n if seqfiltstr == '00112233445566':\\n seq1 = [thissequence[2*i] for i in range(len(thissequence) // 2)]\\n seq2 = [thissequence[2*i+1] for i in range(len(thissequence) // 2)]\\n \\n seqstocombine.append(seq1)\\n seqstocombine.append(seq2)\\n \\n break\\n else:\\n print(\\\"Length multiple of 7 but bad sequence\\\")\\n\\n # Non-7 number of observations\\n else:\\n for i in range(len(seqfiltstr)):\\n subseq = thissequence[i:i+7]\\n subseqfilt = seqfiltstr[i:i+7]\\n if subseqfilt == '0123456':\\n cont = False\\n for j in range(i, i+7):\\n if dimlist[i] != dimlist[j]:\\n print(\\\"SIZE ERROR\\\")\\n cont = True\\n if cont: continue\\n \\n seqstocombine.append(subseq)\\n \\n # No actual multispectral images exist, so use all RGB (sol 388)\\n if len(seqstocombine) == 0 and 'sol388' in self.archive:\\n seqstocombine = [[f] for f in thissequence]\\n \\n # Now, download each sequence with this prefix\\n for subseq in seqstocombine:\\n qwertyuiop = 0\\n bigimage = None\\n \\n err = False\\n # Get each image within sequence\\n for filename in subseq:\\n namestem = filename.split('.')[0].split('/')[-1]\\n\\n try:\\n (image, lbls) = self.load_image(namestem, filepath, ext=extension, lblext=lblext)\\n except ValueError as e:\\n #print(\\\"An error happened while processing %s\\\" % filename)\\n err = True\\n break\\n\\n (h, w, b) = image.shape\\n \\n if b == 3:\\n self.rgbdict[fileprefix + str(asdfghjkl)] = namestem\\n fullimages[fileprefix + str(asdfghjkl)] = image\\n #print(\\\"Stored %s to rgbdict\\\" % (fileprefix + str(asdfghjkl)))\\n \\n if bigimage == None and 'sol388' not in filepath:\\n bigimage = np.zeros([h, w, 9], dtype='uint8')\\n elif bigimage == None:\\n bigimage = np.zeros([h, w, b], dtype='uint8')\\n \\n bigimage[:,:,qwertyuiop:qwertyuiop+b] = image\\n\\n qwertyuiop += b\\n \\n\\n # Reorder images based on camera so filters are ordered\\n if eye in ['L', 'R']:\\n bi = np.zeros([h, w, 9], dtype='uint8')\\n if eye == 'L':\\n bi[:, :, 0] = bigimage[:, :, 0]\\n bi[:, :, 1] = bigimage[:, :, 1]\\n bi[:, :, 2] = bigimage[:, :, 2]\\n bi[:, :, 3] = bigimage[:, :, 4]\\n bi[:, :, 4] = bigimage[:, :, 3]\\n bi[:, :, 5] = bigimage[:, :, 6]\\n bi[:, :, 6] = bigimage[:, :, 5]\\n bi[:, :, 7] = bigimage[:, :, 7]\\n bi[:, :, 8] = bigimage[:, :, 8]\\n elif eye == 'R':\\n bi[:, :, 0] = bigimage[:, :, 2]\\n bi[:, :, 1] = bigimage[:, :, 1]\\n bi[:, :, 2] = bigimage[:, :, 0]\\n bi[:, :, 3] = bigimage[:, :, 4]\\n bi[:, :, 4] = bigimage[:, :, 3]\\n bi[:, :, 5] = bigimage[:, :, 5]\\n bi[:, :, 6] = bigimage[:, :, 6]\\n bi[:, :, 7] = bigimage[:, :, 7]\\n bi[:, :, 8] = bigimage[:, :, 8]\\n bigimage = bi\\n\\n if err:\\n print(\\\" ...didn't load sequence. There was an error.\\\")\\n continue\\n \\n print(\\\" ...loaded one sequence:\\\", (fileprefix + str(asdfghjkl)))\\n \\n if 'sol388' not in self.archive:\\n name = fileprefix + str(asdfghjkl) + '_' + unit + '_' + feature\\n else:\\n name = namestem + '_' + unit + '_' + feature\\n\\n \\n (segments, segmentlabels) = self.segment_image(bigimage, unit=unit)\\n segmentation[fileprefix + str(asdfghjkl)] = segments[0][1]\\n\\n for i in range(len(segments)):\\n data += [[float(x) for x in self.process_image(segments[i], name + segmentlabels[i], feature=feature)]]\\n \\n asdfghjkl += 1\\n \\n ###########################################\\n \\n seen += 1\\n \\n # output read-in progress\\n if percent < 100:\\n if (round((seen / float(numfiles)) * 100, 1) >= percent) and (printed[int(percent * 10)] == False):\\n #print(\\\"...%3.1f%%...\\\" % percent)\\n printed[int(percent * 10)] == True\\n percent = round(((seen / float(numfiles)) * 100), 1) + 1\\n print(\\\"...100%...\\\")\\n print(\\\"Transposing data...\\\")\\n data = np.array(data).T\\n self.xvals.sort()\\n \\n # Output the pickle\\n print(\\\"Writing pickle to \\\" + self.archive + \\\" ...\\\")\\n outf = open(self.archive, 'w')\\n pickle.dump((data, fullimages, segmentation, self.labels, self.xlabel, self.ylabel, self.xvals, self.rgbdict, self.lblext, self.initdata, self.initfilename), outf)\\n outf.close()\\n print(\\\"Wrote pickle to \\\" + self.archive)\",\n \"def recursively_find_file(folder, file_name):\\n # TODO: print a hint when not founding file_name\",\n \"def find_file_match(folder, end):\\n if not os.path.exists(folder):\\n return None\\n if not os.path.isdir(folder):\\n return None\\n\\n dir_list = os.listdir(folder)\\n subdirs = []\\n\\n # First try to find the file. Save any sub folders for later\\n for entry in dir_list:\\n # Skip over hidden files\\n if entry[0] == '.':\\n continue\\n\\n # Check the name to see if it's a file and if it first the descrioption\\n test_path = os.path.join(folder, entry)\\n if os.path.isfile(test_path):\\n if test_path.endswith(end):\\n return test_path\\n else:\\n subdirs.append(entry)\\n\\n # Loop through sub folders\\n subdirs_len = len(subdirs)\\n if subdirs_len > 0:\\n for one_dir in subdirs:\\n found = find_file_match(os.path.join(folder, one_dir), end)\\n if not found is None:\\n return found\\n\\n return None\",\n \"def match_filename(filename: str) -> Optional[dict]:\\n r = re.match(string=filename, pattern=NPS_PATTERN, flags=re.I)\\n if r:\\n return r.groupdict()\\n else:\\n return None\",\n \"def main(video_folder, database_location):\\n \\n # Validate parameters\\n if not path.isdir(video_folder):\\n print 'Invalid video directory path: {}'.format(video_folder)\\n return\\n \\n if not path.exists(database_location):\\n print 'Invalid database location: {}'.format(database_location)\\n return\\n \\n # Connect to database\\n conn = sqlite3.connect(database_location)\\n cursor = conn.cursor()\\n\\n # Get data\\n video_files = listdir(video_folder)\\n video_ids = [f.split('.')[0] for f in video_files if f.endswith('.avi')]\\n \\n # Stats\\n true_positives = 0 # Category 1 classified as category 1\\n false_positives = 0 # Categories 2 or 3 classified as category 1\\n true_negatives = 0 # Categories 2 or 3 classified as categories 2 or 3\\n false_negatives = 0 # Category 1 classified as categories 2 or 3\\n\\n for video_id in video_ids:\\n \\n # Make sure both a .avi and .wav file are available for this id\\n video_location = path.join(video_folder, '{}.avi'.format(video_id))\\n audio_location = path.join(video_folder, '{}.wav'.format(video_id))\\n \\n if not path.exists(video_location) or not path.exists(audio_location):\\n continue\\n \\n # Process video\\n print 'Processing `{}`...'.format(video_id) \\n category_classifier = process_video.process(\\n video_location,\\n audio_location,\\n database_location\\n )\\n\\n # Get actual label\\n metadata = video_id.split('-')\\n db_video_id = ''.join(metadata[:-2])\\n db_start_time_ms = metadata[-2]\\n\\n query = '''\\n SELECT category FROM classifications\\n WHERE video_id = ?\\n AND start_time_ms = ?\\n '''\\n cursor.execute(query, (db_video_id, db_start_time_ms))\\n result = cursor.fetchone()\\n \\n # (Skip if the video isn't labeled)\\n if result is None:\\n print 'No label - skipped'\\n continue\\n \\n category_actual = result[0]\\n\\n # Mark as TP, FP, TN, or FN\\n if category_classifier == 1:\\n if category_actual == 1:\\n true_positives += 1\\n mark = 'TP'\\n else:\\n false_positives += 1\\n mark = 'FP'\\n else:\\n if category_actual == 1:\\n false_negatives += 1\\n mark = 'FN'\\n else:\\n true_negatives += 1\\n mark = 'TN'\\n \\n print 'Classified as category {} ({})'.format(\\n category_classifier,\\n mark\\n )\\n \\n print\\n\\n print\\n\\n print 'RESULTS:'\\n print\\n print 'True Positives (TP) =', true_positives\\n print 'False Positives (FP) =', false_positives\\n print 'True Negatives (TN) =', true_negatives\\n print 'False Negatives (FN) =', false_negatives\\n\\n print\\n print 'Recall [TP / (TP + FN)] =', float(true_positives) / (true_positives + false_negatives)\\n print 'Precision [TP / (TP + FP)] =', float(true_positives) / (true_positives + false_positives)\",\n \"def test_word_found_in_file(self):\\n\\n # create indexer object\\n indexer = indexing_module.IndexModule()\\n\\n # index the location (storage/data/test/empty_directory)\\n indexer.index(_path_prefix + 'word_not_found')\\n\\n # search for few words and check that the result is empty\\n result = indexer.search(\\\"unit\\\")\\n self.assertTrue(result != [])\\n\\n result = indexer.search(\\\"index\\\")\\n self.assertTrue(result != [])\\n print(result)\",\n \"def find_video_of_file(\\n self, video_dir: Union[str, os.PathLike], filename: str\\n ) -> Union[str, os.PathLike]:\\n try:\\n all_files_in_video_folder = [\\n f for f in next(os.walk(video_dir))[2] if not f[0] == \\\".\\\"\\n ]\\n except StopIteration:\\n raise NoFilesFoundError(msg=f\\\"No files found in the {video_dir} directory\\\")\\n all_files_in_video_folder = [\\n os.path.join(video_dir, x) for x in all_files_in_video_folder\\n ]\\n return_path = None\\n for file_path in all_files_in_video_folder:\\n _, video_filename, ext = get_fn_ext(file_path)\\n if (video_filename == filename) and (\\n (ext.lower() == \\\".mp4\\\") or (ext.lower() == \\\".avi\\\")\\n ):\\n return_path = file_path\\n\\n if return_path is None:\\n NoFileFoundWarning(\\n f\\\"SimBA could not find a video file representing {filename} in the project video directory\\\"\\n )\\n return return_path\",\n \"def movies_filename(self):\\n pass\",\n \"def search(pattern):\\n query = pattern.lower()\\n videolist = getvideolist()\\n results = []\\n for video in videolist:\\n for value in video.values():\\n if query in str(value).lower():\\n results.append(Colors.YELLOW + video[\\\"file\\\"] + Colors.END + \\\" - \\\" + video[\\\"source\\\"] + \\\" - \\\" +\\n video[\\\"title\\\"])\\n if results:\\n for result in results:\\n safeprint(result)\\n else:\\n safeprint(\\\"No video matching the given query was found.\\\")\",\n \"def find(self, file, version):\\n matches = []\\n for root, dirnames, filenames in os.walk(self.full_doc_path(version)):\\n for filename in fnmatch.filter(filenames, file):\\n matches.append(os.path.join(root, filename))\\n return matches\",\n \"def test_IMDB_Search_TC_002_search_for_a_movie(self):\\n # to load a given URL in browser window\\n self.driver.get(self.base_url) \\n # to enter search term, we need to locate the search textbox\\n searchTextBox=self.driver.find_element_by_id(\\\"suggestion-search\\\")\\n # to clear any text in the search textbox\\n searchTextBox.clear()\\n # to enter the search term in the search textbox via send_keys() function\\n searchTextBox.send_keys(self.search_term)\\n # to search for the entered search term\\n searchTextBox.send_keys(Keys.RETURN)\\n # to see movie title element\\n searchMovieBox = self.driver.find_element_by_link_text(\\\"Silicon Valley\\\")\\n # to verify if the search results page loaded\\n self.assertIn(\\\"Find - IMDb\\\",self.driver.title)\\n # to verify if the search results page contains any results or no results were found.\\n self.assertNotIn(\\\"No results found.\\\",self.driver.page_source)\",\n \"def files_of(mage_id):\\n\\tcursor.execute('select tag.id, tag.name from tag, tagging as is_file_tagging, tagging where tag.id = tagging.child_id and tag.id = is_file_tagging.child_id and is_file_tagging.parent_id = ? and tagging.parent_id = ?', (settings['file'],mage_id))\\n\\treturn cursor.fetchall()\",\n \"def isVideoFolder():\",\n \"def _find_named_files(self):\\n for name, description in self.named_files.iteritems():\\n name = name.format(job_name=self.job_name)\\n f_path = '{}/{}'.format(self.rism3d_folder, name)\\n if os.path.isfile(f_path):\\n self.file_path_dic[description] = f_path\\n else:\\n self._not_found_error(f_path)\",\n \"def scanForAssays(self):\\n if not self.isDataDir():\\n self.setDataDir(os.getcwdu())\\n files = os.listdir(self.__datadir)\\n print(files)\\n for f in files:\\n if f.endswith('.tif'):\\n print('An TIFF image here! (%s)') % f\",\n \"def get_mentions(fname):\\n capture = re.compile('NPRI in ?.* ?(news|print)', re.I)\\n with open(fname) as fp:\\n for line in fp:\\n line = line.strip()\\n if capture.search(line):\\n yield get_info(line)\",\n \"def detect_netease_music_name(file_path, dist_path, KEEP_SOURCE=True):\\n headers = {\\n \\\"User-Agent\\\": \\\"Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:61.0) Gecko/20100101 Firefox/61.0\\\"\\n }\\n url_base = \\\"http://music.163.com/api/song/detail/?id={}&ids=[{}]\\\"\\n\\n if not os.path.exists(dist_path):\\n os.mkdir(dist_path)\\n\\n for file_name in os.listdir(file_path):\\n if not file_name.endswith(\\\".mp3\\\"):\\n continue\\n if not len(file_name.split(\\\"-\\\")) == 3:\\n print(\\n \\\">>>> File %s not in format <song id>-<bite rate>-<random number>.mp3\\\"\\n % (file_name)\\n )\\n continue\\n\\n try:\\n song_id = file_name.split(\\\"-\\\")[0]\\n url_target = url_base.format(song_id, song_id)\\n resp = requests.get(url_target, headers=headers)\\n rr = json.loads(resp.text)\\n\\n tt = eyed3.load(os.path.join(file_path, file_name))\\n tt.tag.title = rr[\\\"songs\\\"][0][\\\"name\\\"].replace(\\\"\\\\xa0\\\", \\\" \\\")\\n tt.tag.artist = rr[\\\"songs\\\"][0][\\\"artists\\\"][0][\\\"name\\\"]\\n tt.tag.album = rr[\\\"songs\\\"][0][\\\"album\\\"][\\\"name\\\"]\\n tt.tag.album_artist = rr[\\\"songs\\\"][0][\\\"album\\\"][\\\"artists\\\"][0][\\\"name\\\"]\\n print(\\n \\\"song_id = %s, tt.tag title = %s, artist = %s, album = %s, album_artist = %s\\\"\\n % (\\n song_id,\\n tt.tag.title,\\n tt.tag.artist,\\n tt.tag.album,\\n tt.tag.album_artist,\\n )\\n )\\n tt.tag.save()\\n except UnicodeEncodeError as e:\\n print(\\n \\\">>>> UnicodeEncodeError, try again later: file_name = %s, error = %s\\\"\\n % (file_name, str(e))\\n )\\n continue\\n except:\\n print(\\\">>>> Some other error happens: file_name = %s\\\" % (file_name))\\n continue\\n\\n dist_name = (\\n os.path.join(\\n dist_path,\\n \\\"%s - %s\\\"\\n % (tt.tag.artist.replace(\\\"/\\\", \\\" \\\"), tt.tag.title.replace(\\\"/\\\", \\\" \\\")),\\n )\\n + \\\".mp3\\\"\\n )\\n \\n if KEEP_SOURCE == True:\\n shutil.copyfile(os.path.join(file_path, file_name), dist_name)\\n else:\\n os.rename(os.path.join(file_path, file_name), dist_name)\",\n \"def get_movie_data(files: list) -> list:\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5898576","0.58694935","0.5622307","0.5614593","0.55535376","0.5487656","0.5487184","0.5405422","0.5401638","0.51820374","0.511373","0.5113248","0.510091","0.5017189","0.5016573","0.5016369","0.5010073","0.5002005","0.50001943","0.49860036","0.49847925","0.49709547","0.4970679","0.495316","0.49496913","0.49380678","0.49361154","0.4930789","0.4921521","0.49175277","0.4910977","0.4907848","0.48938137","0.4891469","0.4890466","0.48841736","0.4881867","0.4876369","0.4874948","0.4866477","0.4866445","0.48575813","0.48537102","0.4851211","0.48465112","0.48452064","0.4838598","0.4838516","0.48336667","0.4831662","0.4826296","0.48260084","0.48216856","0.4817146","0.48135757","0.48033366","0.48013684","0.47928363","0.47856244","0.47855893","0.47794884","0.47783092","0.47583026","0.47213355","0.47007483","0.46794686","0.46735442","0.467117","0.46677026","0.4653675","0.46532777","0.46455312","0.46429595","0.463718","0.46365905","0.46322098","0.46298805","0.4629065","0.46279785","0.46276122","0.4620724","0.4619541","0.46177873","0.46165636","0.4614816","0.46121424","0.46039426","0.46010274","0.4596408","0.45903715","0.45903146","0.45890582","0.45843333","0.45774853","0.45758066","0.45753592","0.4573643","0.45706737","0.45684618","0.45683956"],"string":"[\n \"0.5898576\",\n \"0.58694935\",\n \"0.5622307\",\n \"0.5614593\",\n \"0.55535376\",\n \"0.5487656\",\n \"0.5487184\",\n \"0.5405422\",\n \"0.5401638\",\n \"0.51820374\",\n \"0.511373\",\n \"0.5113248\",\n \"0.510091\",\n \"0.5017189\",\n \"0.5016573\",\n \"0.5016369\",\n \"0.5010073\",\n \"0.5002005\",\n \"0.50001943\",\n \"0.49860036\",\n \"0.49847925\",\n \"0.49709547\",\n \"0.4970679\",\n \"0.495316\",\n \"0.49496913\",\n \"0.49380678\",\n \"0.49361154\",\n \"0.4930789\",\n \"0.4921521\",\n \"0.49175277\",\n \"0.4910977\",\n \"0.4907848\",\n \"0.48938137\",\n \"0.4891469\",\n \"0.4890466\",\n \"0.48841736\",\n \"0.4881867\",\n \"0.4876369\",\n \"0.4874948\",\n \"0.4866477\",\n \"0.4866445\",\n \"0.48575813\",\n \"0.48537102\",\n \"0.4851211\",\n \"0.48465112\",\n \"0.48452064\",\n \"0.4838598\",\n \"0.4838516\",\n \"0.48336667\",\n \"0.4831662\",\n \"0.4826296\",\n \"0.48260084\",\n \"0.48216856\",\n \"0.4817146\",\n \"0.48135757\",\n \"0.48033366\",\n \"0.48013684\",\n \"0.47928363\",\n \"0.47856244\",\n \"0.47855893\",\n \"0.47794884\",\n \"0.47783092\",\n \"0.47583026\",\n \"0.47213355\",\n \"0.47007483\",\n \"0.46794686\",\n \"0.46735442\",\n \"0.467117\",\n \"0.46677026\",\n \"0.4653675\",\n \"0.46532777\",\n \"0.46455312\",\n \"0.46429595\",\n \"0.463718\",\n \"0.46365905\",\n \"0.46322098\",\n \"0.46298805\",\n \"0.4629065\",\n \"0.46279785\",\n \"0.46276122\",\n \"0.4620724\",\n \"0.4619541\",\n \"0.46177873\",\n \"0.46165636\",\n \"0.4614816\",\n \"0.46121424\",\n \"0.46039426\",\n \"0.46010274\",\n \"0.4596408\",\n \"0.45903715\",\n \"0.45903146\",\n \"0.45890582\",\n \"0.45843333\",\n \"0.45774853\",\n \"0.45758066\",\n \"0.45753592\",\n \"0.4573643\",\n \"0.45706737\",\n \"0.45684618\",\n \"0.45683956\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.77056664"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":92978,"cells":{"query":{"kind":"string","value":"Function connect with server and downloades avaliable subtitle list or avaliable subtitle zip file"},"document":{"kind":"string","value":"def __connect_with_server(self,get_operatoin,server_reuest_type):\n\twhat_is_downloaded = server_reuest_type\n\tself.XML_String = None\n\tself.zip_string = None\n\ttry:\n\t conn = httplib.HTTPConnection(self.NAPISY24_url)\n\t conn.request(\"GET\", get_operatoin)\n\t r1 = conn.getresponse()\n\t print r1.status, r1.reason\n\t if what_is_downloaded == \"downloada_subtitle_list_by_film_name\" or what_is_downloaded == \"downloada_subtitle_list_by_IMDB\":\n\t\tself.XML_String = r1.read()\n\t elif what_is_downloaded == \"download_subtilte_zip\":\t\t\n\t\tself.zip_string = r1.read()\n\t return r1.status#, r1.reason\n\texcept (IOError, OSError), e:\n\t print >> sys.stderr, \"Napisy24.pl server connection error.\"\n\t time.sleep(0.5)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def download(self):\n if not os.path.isdir(self.save_path):\n try:\n os.mkdir(self.save_path)\n except IOError:\n print(\"Can't create subfolder. \"\n \"Check that you have write access for \"\n \"{}\".format(self.save_path))\n\n sub_zip_file = request.urlopen(self.download_link)\n sub_gzip = gzip.GzipFile(fileobj=StringIO(sub_zip_file.read()))\n subtitle_content = sub_gzip.read()\n try:\n with open(self.full_path, 'wb') as subtitle_output:\n subtitle_output.write(subtitle_content)\n print(\"Downloaded subtitle...\")\n except IOError:\n print(\"Couldn't save subtitle, permissions issue?\")","def download_subtitle_zip(self, dict_entry_to_download):\n\trequest_subtitle_list = \"http://napisy24.pl/download/%s/\" % str(self.return_xml_dict_entry_value(dict_entry_to_download,'id'))\n\trepeat = 3\n\twhile repeat > 0: \n repeat = repeat - 1\n\t #request_subtitle_list = \"/libs/webapi.php?title=%s\" % self.MovieName\n\t r1_status = self.__connect_with_server(request_subtitle_list, \"download_subtilte_zip\") \n if r1_status != 302:\n print \"Fetching subtitle failed, HTTP code: %s\" % (str(r1_status))\n time.sleep(0.5)\n continue\n else:\n repeat = 0\n \n if self.zip_string == None:\n print \"Subtitle NOT DOWNLOADED\"\n repeat = 0\n continue\n\n if self.zip_string is None or self.zip_string == \"\":\n print \"Subtitle NOT DOWNLOADED\"\n continue\n \n if self.zip_string[0:2] == 'PK':\n\t print \"Success to download subtitle zip.\"\n return True\n else:\n\t print \"Reild to download subtitle zip.\"\n return False","def download_data(self, format = 'srt'):\n \n def to_ascii(data):\n \"\"\"\n Remove non-ascii characters\n \"\"\"\n return ''.join([x for x in data if ord(x) < 128])\n \n url = self.config.subtitles['url'] % (self.media_resource_id)\n \n print url\n resp, content = httplib2.Http(\".cache\").request(url, \"GET\")\n \n subtitles = json.loads(content)['subtitles']\n \n final_data = ''\n if format == 'srt':\n final_data += self.to_srt(subtitles)\n else:\n final_data += subtitles\n \n return to_ascii(final_data)","def download(self, language, filename, filetype):\n if language not in self.languages.keys():\n print \"Theres's no subtitle in this language\"\n sys.exit()\n url = \"http://www.youtube.com/api/timedtext?v={0}&lang={1}\".format(self.video_id, language)\n self.subtitle = urllib2.urlopen(url)\n if filetype == \"srt\":\n self.writeSRTFile(filename)\n else:\n self.writeXMLFile(filename)","def download_subtitle(search, results, filename, min_match=0,\n force=0, debug=0):\n s = Subseek()\n subtitleurl = False\n for result in s.order_match(search, results):\n match_text = s.clean_text(s.clean_html(result['text']),False,\n s.detect_encoding(s.clean_html(result['text']))\n ) + \" \" + s.clean_text(s.clean_html(result['description']),False,\n s.detect_encoding(s.clean_html(result['description'])))\n subtitleurl = result['link']\n rating_weight = s.text_weight(search, match_text)\n max_weight = s.text_weight(search)\n rating_match = rating_weight/max_weight*100\n if debug == 1:\n print \"Subtitle File URL: \" + subtitleurl\n print \" Text To Search: \" + search\n print \" Text To Match: \" + match_text\n print \" Text Match (%): \" + str(round(rating_match,2)) + \"%\"\n # check minimal match to use\n if rating_match >= min_match:\n downloaded = s.download(subtitleurl, filename + '.tmp')\n if downloaded == False:\n if debug == 1:\n print \"Error: connection or file creation failed\"\n subtitleurl = False\n else:\n if debug == 1:\n print \"File downloaded\"\n # unrar, unzip or get srt file\n typefile = s.get_sub_file_from_file(filename + '.tmp',\n search, force)\n if typefile == False:\n if debug == 1:\n print \"Subtitle file not found\"\n subtitleurl = False\n else:\n if debug == 1:\n print \"Subtitle file found in \" + typefile\n subtitleurl = True\n break\n else:\n if debug == 1:\n print \"Error: match less than \" + str(round(min_match,2))+ \"%\"\n subtitleurl = False\n break\n\n return subtitleurl","def play_video(path):\r\n #logger.info(\"######: {}, log: {}########\".format('rk8', path))\r\n #original=https://api.hotstar.com/h/v1/play?contentId=1000238814\r\n #path=\"https://api.hotstar.com/h/v2/play/in/contents/1000238814\"\r\n # Create a playable item with a path to play.\r\n data = make_request(path)\r\n #logger.info(\"######: {}, log: {}########\".format('rk3', path))\r\n if not data:\r\n return\r\n\r\n def get_subtitle(url):\r\n #\r\n # https://hses.akamaized.net/videos/hotstarint/hostages/1260003409/1558430241469/\r\n # 265b9dab22d4e9a033e6df6f89639f17/master.m3u8?hdnea=st=1560107863~exp=1560111463~acl=\r\n # /*~hmac=2f6fb393159ed5fa1b12bbf12e954eb377cfa0fc852d4ff5eb24446233237620\r\n #\r\n # https://hses.akamaized.net/videos/hotstarint/hostages/1260003409/1558430241469/\r\n # 5d0f83c3ccbf4501cf952bdfc8c0d785/subtitle/lang_en/sub-0.vtt\r\n #\r\n _url = urlparse(url)\r\n values = _url._asdict()\r\n values['query'] = ''\r\n values['path'] = '{}/subtitle/lang_en/sub-0.vtt'.format(\"/\".join(values['path'].split('/')[:-1]))\r\n\r\n subtitle_url = ParseResult(**values).geturl()\r\n # subtitle_file = kodiutils.download_url_content_to_temp(subtitle_url, '{}-{}.srt'.format(\r\n # Zee5Plugin.safe_string(item['title']),\r\n # subtitle_lang,\r\n # ))\r\n\r\n return subtitle_url\r\n\r\n #logger.info(\"######: {}, log: {}########\".format('rk6', data))\r\n #item = data['body']['results']['item']\r\n item=data['body']['results']['playBackSets'][0]\r\n path = item['playbackUrl']\r\n licenseURL = item.get('licenseUrl')\r\n subtitle = get_subtitle(path)\r\n\r\n logger.info('Playing video URL: {}, licenseURL: {}, subtitle: {}'.format(path, licenseURL, subtitle))\r\n\r\n play_item = xbmcgui.ListItem(path=path)\r\n if licenseURL:\r\n play_item.setProperty('inputstreamaddon', 'inputstream.adaptive')\r\n play_item.setProperty('inputstream.adaptive.manifest_type', 'hls')\r\n play_item.setMimeType('application/dash+xml')\r\n play_item.setContentLookup(False)\r\n\r\n play_item.setSubtitles([get_subtitle(path)])\r\n\r\n # Pass the item to the Kodi player.\r\n xbmcplugin.setResolvedUrl(_handle, True, listitem=play_item)","def download(self, filename = None, format = 'srt', append = False):\n \n data = self.download_data(format)\n \n if filename != None:\n extension = '' if filename.lower().endswith('.srt') else '.srt'\n \n sys.stdout.write('Saving subtitle...\\n')\n \n out_dir = self.config.subtitles['out']\n if os.path.isfile(out_dir):\n raise OSError('Video output directory is not a directory, but is a file')\n elif not os.path.isdir(out_dir):\n os.mkdir(out_dir)\n \n mod = 'a' if append else 'w'\n f = open(out_dir + os.path.sep + filename + extension, mod)\n f.write(data)\n f.close()\n \n return data","def main():\n parser = argparse.ArgumentParser()\n parser.add_argument('source_path', help=\"Path to the video or audio file to subtitle\",\n nargs='?')\n parser.add_argument('-C', '--concurrency', help=\"Number of concurrent API requests to make\",\n type=int, default=DEFAULT_CONCURRENCY)\n parser.add_argument('-o', '--output',\n help=\"Output path for subtitles (by default, subtitles are saved in \\\n the same directory and name as the source path)\")\n parser.add_argument('-F', '--format', help=\"Destination subtitle format\",\n default=DEFAULT_SUBTITLE_FORMAT)\n parser.add_argument('-S', '--src-language', help=\"Language spoken in source file\",\n default=DEFAULT_SRC_LANGUAGE)\n parser.add_argument('-D', '--dst-language', help=\"Desired language for the subtitles\",\n default=DEFAULT_DST_LANGUAGE)\n parser.add_argument('-K', '--api-key',\n help=\"The Google Translate API key to be used. \\\n (Required for subtitle translation)\")\n parser.add_argument('--list-formats', help=\"List all available subtitle formats\",\n action='store_true')\n parser.add_argument('--list-languages', help=\"List all available source/destination languages\",\n action='store_true')\n\n parser.add_argument('--min_height', help=\"minimum height from 0 - 100%\", type=float, default=93)\n\n parser.add_argument('--max_height', help=\"maximum height from 0 - 100%\", type=float, default=99)\n\n parser.add_argument('--l_v', help=\"Light sensitive\", type=float, default=210)\n\n parser.add_argument('--debug', help=\"Allows to show cropped image on the desktop\", action='store_true', default=True)\n\n parser.add_argument('--cloud', help=\"Use google cloud compute to extract text\", action='store_true', default=False)\n\n parser.add_argument('--disable_time', help=\"Parse time function\", action='store_true')\n\n parser.add_argument('--all', help=\"Render all files\", action='store_true')\n\n args = parser.parse_args()\n\n if args.list_formats:\n print(\"List of formats:\")\n for subtitle_format in FORMATTERS:\n print(\"{format}\".format(format=subtitle_format))\n return 0\n\n if args.list_languages:\n print(\"List of all languages:\")\n for code, language in sorted(LANGUAGE_CODES.items()):\n print(\"{code}\\t{language}\".format(code=code, language=language))\n return 0\n\n if not validate(args):\n return 1\n\n try:\n if args.all:\n for file in os.listdir():\n # *.avi *.flv *.mkv *.mpg *.mp4 *.webm\n if file.endswith('.avi') or file.endswith('.flv') or file.endswith('.mkv') or file.endswith('.mpg') or file.endswith('.mp4') or file.endswith(\".webm\"):\n st = time.time()\n subtitle_file_path = generate_subtitles(\n source_path=file,\n dst_language=args.dst_language,\n output=args.output,\n debug=args.debug,\n cloud=args.cloud,\n disable_time=args.disable_time,\n min_height=args.min_height,\n max_height=args.max_height,\n l_v=args.l_v,\n )\n print(\"Subtitles file created at {} time consumer: {}\".format(subtitle_file_path, time.time() - st))\n else:\n st = time.time()\n subtitle_file_path = generate_subtitles(\n source_path=args.source_path,\n dst_language=args.dst_language,\n output=args.output,\n debug=args.debug,\n cloud=args.cloud,\n disable_time=args.disable_time,\n min_height=args.min_height,\n max_height=args.max_height,\n l_v=args.l_v,\n )\n print(\"Subtitles file created at {} time consumer: {}\".format(subtitle_file_path, time.time() - st))\n except KeyboardInterrupt:\n return 1\n\n return 0","def podcast_download(self):\r\n warnings.filterwarnings(\"ignore\", category=UnicodeWarning)\r\n now = datetime.datetime.now()\r\n\r\n for podcast_file in self.podcast_list:\r\n published, name, link, title = podcast_file\r\n if self.podcast_list != []:\r\n line_file = (published + ';' + title + ';' + name + ';' + link).encode(\"utf-8\") \r\n if line_file in open(self.download_log).read():\r\n pass\r\n else:\r\n title = unicodedata.normalize('NFKD', title).encode('ascii', 'ignore')\r\n download_folder = os.path.join('downloads', title)\r\n if not os.path.exists(download_folder): \r\n os.makedirs(download_folder)\r\n try:\r\n published = str(parser.parse(published))[:10]\r\n except IOError as error:\r\n print 'Error' + (error) + ': File - ' + str(title)\r\n download_folder = os.path.join(download_folder, published)\r\n if not os.path.exists(download_folder): \r\n os.makedirs(download_folder)\r\n namefile_unicode = link[link.rfind('/')+1:]\r\n namefile_str = unicodedata.normalize('NFKD', \r\n namefile_unicode).encode('ascii', 'ignore')\r\n namefile_str = namefile_str.decode('utf-8', 'ignore').encode(\"utf-8\")\r\n if '.mp3' in namefile_str:\r\n len_name = namefile_str.index('.mp3')\r\n elif '.MP3' in namefile_str:\r\n len_name = namefile_str.index('.MP3')\r\n namefile_str = namefile_str[:len_name + 4]\r\n fileoutput = os.path.join(download_folder, namefile_str)\r\n name = unicodedata.normalize('NFKD', name).encode('ascii', 'ignore')\r\n print str(published) + '; ' + name\r\n ## downlink\r\n download_file(link, fileoutput) \r\n ## tagging\r\n mp3_tagging(fileoutput, podcast_file)\r\n ## write log\r\n write_file(self.download_log, line_file)\r\n end = datetime.datetime.now()\r\n print '\\r' + 'Download Time = ' + str(end-now) + '\\r'\r\n return None","def get_subtitleinfo(fileFullName):\n sys.stdout.write(\"Requesting subtitle info...\\n\")\n\n #接口获取字幕信息\n response = requests.post(\n \"https://www.shooter.cn/api/subapi.php\",\n verify=False,\n params= {\n 'filehash': ComputeFileHash(fileFullName),\n 'pathinfo': os.path.realpath(fileFullName),\n 'format': 'json',\n 'lang': \"Chn\",\n },\n )\n #未找到字幕处理\n if response.text == u'\\xff':\n sys.stderr.write(\"Subtitle not found.\\n\")\n sys.exit(1)\n return response","def link_subtitles_to_files(self):\n target_filenames = self.get_target_filenames()\n subtitle_filenames = []\n\n zip_filenames = self.subtitle_zip_files_dir.glob('*.zip')\n for zip_fn in zip_filenames:\n subtitle_filenames.extend(self.unzip_subtitles(zip_fn))\n\n subtitle_metadata = self.cache_file_metadata(subtitle_filenames)\n target_metadata = self.cache_file_metadata(target_filenames)\n\n for target_file_metadata_summary in target_metadata:\n try:\n source_filename = f'{subtitle_metadata[target_file_metadata_summary][\"fn\"]}.srt'\n target_filename = f'{target_metadata[target_file_metadata_summary][\"fn\"]}.srt'\n source_filepath = pathlib.PurePath(self.temp_storage_dir, source_filename)\n target_filepath = pathlib.PurePath(self.target_dir, target_filename)\n shutil.move(source_filepath, target_filepath)\n print(f'Subtitle for \\'{target_file_metadata_summary}\\' successfully linked.')\n except KeyError:\n logging.warning(f'Subtitle for \\'{target_file_metadata_summary}\\' not found!')\n\n self.clean_temp_storage_dir(subtitle_filenames)","def download_subtitles(video_ids):\n print(f\"[downloading subs] {video_ids}\")\n ydl_opts = {\n 'skip_download': True,\n 'writeautomaticsub': True,\n 'outtmpl': 'subtitles/%(id)s',\n 'subtitleslangs': ['en']\n }\n for video_id in video_ids:\n filename = f\"subtitles/{video_id}.en.vtt\"\n # Don't download if these subtitles are already downloaded\n # or if we know there are no subtitles on the video\n if video_id in cached_no_subtitles:\n continue\n if not os.path.isfile(filename):\n print(f\"[downloading subtitle] {video_id}\")\n with youtube_dl.YoutubeDL(ydl_opts) as ydl:\n # assume downloaded subtitle is correct\n ydl.download([video_id])\n # Delay to be nice to the server\n time.sleep(2)\n try:\n with open(filename) as f:\n yield video_id, f.read()\n except IOError:\n with open(CACHED_NO_SUBTITLES_FILE, \"a\") as f:\n f.write(video_id + '\\n')\n cached_no_subtitles.add(video_id)\n yield video_id, None","def downloadDfxpTranscript(self, SubsLink):\n try:\n subRequestObject = requests.get(SubsLink)\n # print(subRequestObject.text)\n subRequestObject.encoding = 'utf-8'\n\n subsFileHandler = open(self.title + \".dfxp\", \"w\")\n print(\"Creating ~ '%s.dfxp' ...\" % (self.title))\n subsFileHandler.write(subRequestObject.text)\n subsFileHandler.close()\n return 1\n\n except:\n return 0\n\n pass","def download_subtitle(self, film, ttmname, srtname, filename):\n self.logger.debug('download_subtitle')\n ret = False\n if film.url_sub:\n progress = KodiProgressDialog()\n progress.create(30978, filename + u'.ttml')\n # pylint: disable=broad-except\n try:\n progress.update(0)\n mvutils.url_retrieve_vfs(\n film.url_sub, ttmname, progress.url_retrieve_hook)\n try:\n ttml2srtConverter = ttml2srt()\n ttml2srtConverter.do(xbmcvfs.File(ttmname, 'r'),\n xbmcvfs.File(srtname, 'w'))\n ret = True\n except Exception as err:\n self.logger.error('Failed to convert to srt: {}', err)\n progress.close()\n except Exception as err:\n progress.close()\n self.logger.error(\n 'Failure downloading {}: {}', film.url_sub, err)\n return ret","def transcribeAll(service, url, fileName):\n if(service == \"omny.fm\"):\n url = url.replace(\".mp3\",\"\") + \".mp3\"\n subprocess.Popen(\"wget -c -O ./podcasts/\" + fileName + \".mp3 \" + url + \" && sleep 40 && ffmpeg -i ./podcasts/\"\n + fileName + \".mp3 -acodec pcm_s16le -ac 1 -ar 8000 ./podcasts/\" + fileName + \".wav && sleep 10 && rm ./podcasts/\" \n + fileName + \".mp3 && nohup ./online2-wav-nnet3-latgen-faster --online=false --do-endpointing=false \"\n + \"--frame-subsampling-factor=3 --config=online.conf --max-mem=2000000000 --max-active=7000 --beam=15.0 --lattice-beam=6.0 \"\n + \"--acoustic-scale=1.0 --word-symbol-table=words.txt final.mdl HCLG.fst 'ark:echo utterance-id\" + fileName \n + \" utterance-id\" + fileName + \"|' 'scp:echo utterance-id\" + fileName + \" ./podcasts/\" + fileName + \".wav|' 'ark:/dev/null' &\", shell=True)","def test_get_subtitles(self):\n\n (subtitles, start, end) = self.sp.get_subtitles(INDEX)\n self.assertEqual(subtitles, INDEX_SUBTITLES, 'Check get_subtitles.')","def download_data():\n\n if not os.path.exists(zipfile_path):\n print(f'Downloading {config.download_url} to {zipfile_path}')\n urlretrieve(config.download_url, zipfile_path)\n print(f'Successfully downloaded {zipfile_path}')\n\n zip_ref = ZipFile(zipfile_path, 'r')\n zip_ref.extractall(config.raw_data_dir)\n zip_ref.close()\n\n os.rename(f\"{config.raw_data_dir}/cornell movie-dialogs corpus\", extracted_dir)","def download(self, filename, info_dict, subtitle=False):\n nooverwrites_and_exists = (\n not self.params.get('overwrites', True)\n and os.path.exists(encodeFilename(filename))\n )\n\n if not hasattr(filename, 'write'):\n continuedl_and_exists = (\n self.params.get('continuedl', True)\n and os.path.isfile(encodeFilename(filename))\n and not self.params.get('nopart', False)\n )\n\n # Check file already present\n if filename != '-' and (nooverwrites_and_exists or continuedl_and_exists):\n self.report_file_already_downloaded(filename)\n self._hook_progress({\n 'filename': filename,\n 'status': 'finished',\n 'total_bytes': os.path.getsize(encodeFilename(filename)),\n }, info_dict)\n self._finish_multiline_status()\n return True, False\n\n if subtitle:\n sleep_interval = self.params.get('sleep_interval_subtitles') or 0\n else:\n min_sleep_interval = self.params.get('sleep_interval') or 0\n sleep_interval = random.uniform(\n min_sleep_interval, self.params.get('max_sleep_interval') or min_sleep_interval)\n if sleep_interval > 0:\n self.to_screen(f'[download] Sleeping {sleep_interval:.2f} seconds ...')\n time.sleep(sleep_interval)\n\n ret = self.real_download(filename, info_dict)\n self._finish_multiline_status()\n return ret, True","def main():\n\n # Parse arguments\n parser = OptionParser()\n parser.add_option('-n', '--subscription_key', dest='subscription_key',\n help='subscription_key for authentication')\n parser.add_option('-t', '--text', dest='text',\n help='text to synthesize')\n parser.add_option('-l', '--language', dest='language',\n help='language')\n parser.add_option('-g', '--gender', dest='gender',\n help='gender')\n parser.add_option('-d', '--directory', dest='directory',\n help='directory to store the file')\n (options, args) = parser.parse_args()\n subscription_key = options.subscription_key\n text = options.text\n language = options.language\n gender = options.gender\n directory = options.directory\n\n # Perform sanity checks on options\n validate_options(subscription_key, text)\n\n if not directory:\n directory = default_directory\n\n if not language:\n language = default_language\n\n if not gender:\n gender = default_gender\n\n # format = 'riff-16khz-16bit-mono-pcm'\n format = 'riff-8khz-8bit-mono-mulaw'\n\n # lang = 'en-AU'\n # gender = 'Female'\n tts_msspeak = MSSpeak(subscription_key, '/tmp/')\n tts_msspeak.set_cache(False)\n output_filename = tts_msspeak.speak(text, language, gender, format)\n\n print 'Recorded TTS to %s%s' % (directory, output_filename)","def download_text_command():\n # 1. Get input scan id from Demisto\n scanid = demisto.args().get('scanid')\n # 2. Get the forensic webpage text from SlashNext API\n response = download_text(scanid=scanid)\n if response.get('errorNo') != 0:\n return\n # 3. Parse and format the response\n text_base64 = response.get('textData').get('textBase64')\n text_data = base64.b64decode(text_base64)\n\n text_file = fileResult('slashnext_{}.txt'.format(scanid), text_data, entryTypes['file'])\n\n demisto.results({\n 'Type': entryTypes['file'],\n 'ContentsFormat': formats['text'],\n 'Contents': 'Forensics: Webpage Rendered Text for URL Scan ID = {}'.format(scanid),\n 'File': text_file.get('File'),\n 'FileID': text_file.get('FileID')\n })","def demonstrate():\n\n api = authenticate()\n\n # Demonstrate upload feature.\n # Create a list of one or more file paths of the mp3s you would like \n # to upload\n filepaths = []\n filepaths.append('./song1.mp3')\n\n # Upload an mp3 to your library. upload() returns a tuple of information\n # about the success or failure of uploads\n print(\"Beginning upload...\\n\")\n uploaded = api.upload(filepaths) \n\n # Print all successfully uploaded songs\n if len(uploaded[0]) > 0:\n print(\"Successfully uploaded:\")\n i = 1\n for key in uploaded[0]:\n print(\"%d. %s\" % (i, key))\n i += 1\n\n # Print all unsuccessfully uploaded songs and a description of why\n # songs weren't uploaded\n if len(uploaded[2]) == 0:\n print(\"\\nAll songs successfully uploaded.\")\n else:\n print(\"Not all songs were successfully uploaded:\")\n i = 1\n for key in uploaded[2]:\n print(\"%d. %s not uploaded: %s\" % (i, key, uploaded[2][key]))\n i += 1\n\n\n # Demonstrate download feature\n # Get information about songs previously uploaded that are available\n # to be downloaded\n uploaded_songs = api.get_uploaded_songs()\n\n if len(uploaded_songs) == 0:\n print(\"There are no songs currently available for download\")\n else:\n # Print songs that are available for download and store their ids\n # so we can download them\n song_ids = []\n print(\"\\nThe following songs are available for download\")\n for i in range(len(uploaded_songs)):\n song_ids.append(uploaded_songs[i]['id'])\n print(\"%d. %s\" % (i+1, uploaded_songs[i]['title']))\n\n # Download uploaded songs from your library\n print(\"\\nBeginning download...\")\n for i in range(len(song_ids)):\n filename, audio = api.download_song(song_ids[i])\n\n # Write song to disk\n with open(filename, 'wb') as f:\n f.write(audio)\n\n print(\"%d. Written to ./%s\" % (i + 1, filename))\n print(\"\\nDownload complete.\")\n\n # It's good practice to logout when finished\n api.logout()","def get_subtitles(self, title):\n return library.subtitles.get_subtitle_url(title)","def best_subtitle_url(search, full_search, path_file_name,\n min_match=0, force=0, deep=0, debug=0):\n # first search in subtitle search engines\n links = subtitle_search_engines_links(search, deep, debug)\n subtitle_url = download_best_subtitle(links,\n full_search,\n path_file_name,\n min_match, force, debug)\n # if not found use the external search engines\n if not subtitle_url:\n links = external_search_engines_links(search, deep, debug)\n subtitle_url = download_best_subtitle(links,\n full_search,\n path_file_name,\n min_match, force, debug)\n\n return subtitle_url","def unzip_subtitles(self, zip_filepath):\n with ZipFile(zip_filepath, 'r') as zip_obj:\n filenames = zip_obj.namelist()\n\n subtitle_filenames = [fn for fn in filenames if fn.endswith('.srt')]\n for fn in subtitle_filenames:\n zip_obj.extract(fn, self.temp_storage_dir)\n\n return subtitle_filenames","def download_video(url, fn):\n start_time = time.time()\n\n # Sorry: This is terrible code, but I'm kind of throwing it\n # together as I discover more about it.\n print ' Downloading {0} to {1}'.format(url, fn)\n\n resp = requests.get(url)\n if resp.status_code != 200:\n print ' GAH! MY EYES! {0} kicked up {1}'.format(url, resp.status_code)\n return\n\n rss_url_m = re.search(r'\"(/rss/flash/\\d+)\"', resp.content)\n rss_url = 'http://blip.tv' + rss_url_m.group(0).strip('\"')\n resp = requests.get(rss_url)\n\n rss_content = resp.content\n\n for ending in POSSIBLE_ENDINGS:\n regex = r'\"http://blip.tv[^\"]+?' + ending + '\"'\n\n download_m = re.search(regex, rss_content)\n if not download_m:\n print ' No {0} url found'.format(ending)\n continue\n\n download_url = download_m.group(0).strip('\"')\n print ' Attempting to download {0}'.format(download_url)\n\n try:\n resp = requests.get(download_url, stream=True)\n print ' Downloading {0}'.format(download_url)\n if resp.status_code == 200:\n total_length = int(resp.headers['content-length'])\n\n if os.path.exists(fn + ending) and file_size(fn + ending) == total_length:\n print ' Already downloaded.'\n return\n\n with open(fn + ending, 'w') as fp:\n total_downloaded = 0\n\n tic_chunk = total_downloaded\n tic = time.time()\n for chunk in resp.iter_content(chunk_size=1024):\n if chunk:\n fp.write(chunk)\n fp.flush()\n tic_chunk += len(chunk)\n total_downloaded += len(chunk)\n\n if time.time() - tic > 1:\n with TERM.location(x=0):\n line = ' {0} {1}kbps'.format(\n format_downloaded(total_downloaded, total_length),\n int(tic_chunk / (time.time() - tic) / 1000))\n sys.stdout.write(line + TERM.clear_eol)\n sys.stdout.flush()\n tic_chunk = 0\n tic = time.time()\n print ''\n\n print ' Done! {0} {1}mb {2}'.format(\n fn + ending,\n int(total_length / 1000000.0),\n format_duration(time.time() - start_time))\n return\n\n else:\n print ' HTTP{0}! GAH! SPUTTER!'.format(resp.status_code)\n\n except requests.exceptions.ConnectionError as exc:\n print ' CONNECTIONERROR! GAH! SPUTTER! {0}'.format(exc)\n\n print ' SO MANY FAILURES!'\n raise NoDownloadMeNoLikeyException()","def download():\r\n\tglobal server\r\n\tfolder = str(get_folder())\r\n\tfilename = str(get_filename())\r\n\tprint(folder)\r\n\r\n\t# on crée le chemin absolue\r\n\tpath = \"partage/\"+folder +\"/\"+filename\r\n\tprint(path)\r\n\tdata = [\"download\", path]\r\n\t#on dump la liste\r\n\tdata = pickle.dumps(data)\r\n\tserver.send(data)\r\n\r\n\tcontent = server.recv(2**30) # Reception du conenue du fichier\r\n\r\n\tif content == b\"unknown\":\r\n\t\tprint(\"Fichier inéxistant\")\r\n\telse:\r\n\t\twith open(filename, \"wb\") as f: # Creation d'un fichier similaire\r\n\t\t\tprint(content)\r\n\t\t\tf.write(content)\r\n\t\t\tf.close()","def download_song(song):\n ydl.download([song])\n print(\"Finished downloading and converting: \" + song)","def download_transcripts(request):\r\n locator = request.GET.get('locator')\r\n if not locator:\r\n log.debug('GET data without \"locator\" property.')\r\n raise Http404\r\n\r\n try:\r\n item = _get_item(request, request.GET)\r\n except (InvalidKeyError, ItemNotFoundError):\r\n log.debug(\"Can't find item by locator.\")\r\n raise Http404\r\n\r\n subs_id = request.GET.get('subs_id')\r\n if not subs_id:\r\n log.debug('GET data without \"subs_id\" property.')\r\n raise Http404\r\n\r\n if item.category != 'video':\r\n log.debug('transcripts are supported only for video\" modules.')\r\n raise Http404\r\n\r\n filename = 'subs_{0}.srt.sjson'.format(subs_id)\r\n content_location = StaticContent.compute_location(item.location.course_key, filename)\r\n try:\r\n sjson_transcripts = contentstore().find(content_location)\r\n log.debug(\"Downloading subs for %s id\", subs_id)\r\n str_subs = generate_srt_from_sjson(json.loads(sjson_transcripts.data), speed=1.0)\r\n if not str_subs:\r\n log.debug('generate_srt_from_sjson produces no subtitles')\r\n raise Http404\r\n response = HttpResponse(str_subs, content_type='application/x-subrip')\r\n response['Content-Disposition'] = 'attachment; filename=\"{0}.srt\"'.format(subs_id)\r\n return response\r\n except NotFoundError:\r\n log.debug(\"Can't find content in storage for %s subs\", subs_id)\r\n raise Http404","def download_data():\n url = 'https://www.dropbox.com/s/8oehplrobcgi9cq/imdb.tgz?dl=1'\n urllib.request.urlretrieve(url, 'imdb.tgz')\n tar = tarfile.open(\"imdb.tgz\")\n tar.extractall()\n tar.close()","def download_best_subtitle(links, full_search, path_file_name,\n min_match=0, force=0, debug=0):\n s = Subseek()\n if not links or len(links) == 0:\n return False\n else:\n results = []\n for link in links:\n if debug == 1:\n print \"Searching in \" + link['link']\n for provider in SUBTITLE_PROVIDERS:\n results_aux = s.get_subtitles_links(link['link'],\n provider)\n if results_aux is False or len(results_aux) == 0:\n if debug == 1:\n print \"No subtitles with '%s'\" % provider['name']\n else:\n if debug == 1:\n print \"%s subtitles with '%s'\" % (len(results_aux),\n provider['name'])\n results = results + results_aux\n # download the best subtitle of the entire list\n return download_subtitle(full_search,\n results,\n path_file_name,\n min_match,\n force,\n debug)","def main():\n port = 8080\n ipaddr = my_ip.lookup()\n player = sonos.Player()\n\n music_dir = \"mp3s\"\n # Move to the mp3 directory to serve files from it.\n try:\n os.chdir(music_dir)\n except OSError, ex:\n print \"Couldn't chdir to %s directory: %s\" % (music_dir, ex)\n sys.exit(1)\n\n webserver = localwebserver.HttpServer(port)\n webserver.start()\n\n uri = \"http://%s:%s/\" % (ipaddr, port)\n\n print \"Serving MP3s at %s.\" % uri\n\n sniffer = Sniffer(uri, player)\n sniffer.run_forever()","def cli(date, path, mission):\n download.main(path, mission, date)","def download_youtube_subs(youtube_subs, item, settings):\r\n i18n = item.runtime.service(item, \"i18n\")\r\n _ = i18n.ugettext\r\n\r\n highest_speed = highest_speed_subs = None\r\n missed_speeds = []\r\n # Iterate from lowest to highest speed and try to do download transcripts\r\n # from the Youtube service.\r\n for speed, youtube_id in sorted(youtube_subs.iteritems()):\r\n if not youtube_id:\r\n continue\r\n try:\r\n subs = get_transcripts_from_youtube(youtube_id, settings, i18n)\r\n if not subs: # if empty subs are returned\r\n raise GetTranscriptsFromYouTubeException\r\n except GetTranscriptsFromYouTubeException:\r\n missed_speeds.append(speed)\r\n continue\r\n\r\n save_subs_to_store(subs, youtube_id, item)\r\n\r\n log.info(\r\n \"Transcripts for YouTube id %s (speed %s)\"\r\n \"are downloaded and saved.\", youtube_id, speed\r\n )\r\n\r\n highest_speed = speed\r\n highest_speed_subs = subs\r\n\r\n if not highest_speed:\r\n raise GetTranscriptsFromYouTubeException(_(\"Can't find any transcripts on the Youtube service.\"))\r\n\r\n # When we exit from the previous loop, `highest_speed` and `highest_speed_subs`\r\n # are the transcripts data for the highest speed available on the\r\n # Youtube service. We use the highest speed as main speed for the\r\n # generation other transcripts, cause during calculation timestamps\r\n # for lower speeds we just use multiplication instead of division.\r\n for speed in missed_speeds: # Generate transcripts for missed speeds.\r\n save_subs_to_store(\r\n generate_subs(speed, highest_speed, highest_speed_subs),\r\n youtube_subs[speed],\r\n item\r\n )\r\n\r\n log.info(\r\n \"Transcripts for YouTube id %s (speed %s)\"\r\n \"are generated from YouTube id %s (speed %s) and saved\",\r\n youtube_subs[speed], speed,\r\n youtube_subs[highest_speed],\r\n highest_speed\r\n )","def download_data():\n url = 'https://www.dropbox.com/s/xk4glpk61q3qrg2/imdb.tgz?dl=1'\n urllib.request.urlretrieve(url, 'imdb.tgz')\n tar = tarfile.open(\"imdb.tgz\")\n tar.extractall()\n tar.close()","def edx_get_subtitle(url, headers):\n \"\"\" or None if no subtitles are available \"\"\"\n try:\n jsonString = get_page_contents(url, headers)\n jsonObject = json.loads(jsonString)\n return edx_json2srt(jsonObject)\n except URLError as e:\n print('[warning] edX subtitles (error:%s)' % e.reason)\n return None\n except ValueError as e:\n print('[warning] edX subtitles (error:%s)' % e.message)\n return None","def read_subtitles(self):\n\n # Group 1: index, Group 2: Start Time, Group 3: End Time, Group 4: Text\n\n patterns = [\n r\"(\\d+)\\n(\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d) --> (\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d)\\n((?:.+\\n)*.+)\",\n r\"(\\d+)\\r\\n(\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d) --> (\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d)\\r\\n((?:.+\\r\\n)*.+)\",\n # Reports pattern\n r\"(\\d+)\\r(\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d) --> (\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d)\\n((?:.+\\r)*.+)\"\n ]\n\n for pattern in patterns:\n re_subs = re.findall(pattern, self.subtitles, re.M | re.I)\n if(len(re_subs) > 1):\n self.re_subs = re_subs\n return\n\n raise Exception(\n f're_subs length is {len(re_subs)}. Maybe the regex pattern is falty?')","def play_movie_with_subs(self, filmid):\n self.logger.debug('play_movie_with_subs')\n start = time.time()\n #\n film = self.database.retrieve_film_info(filmid)\n if film is None:\n self.logger.error(\"no film for download \" + self.plugin.language(30991))\n self.notifier.show_error(30990, self.plugin.language(30991))\n return\n ttmname = os.path.join(self.settings.getDatapath(), 'subtitle.ttml')\n srtname = os.path.join(self.settings.getDatapath(), 'subtitle.srt')\n subs = []\n if self.download_subtitle(film, ttmname, srtname, 'subtitle'):\n subs.append(srtname)\n # (_, listitem) = FilmUI(self.plugin).get_list_item(None, film)\n (_, listitem) = FilmlistUi(self.plugin)._generateListItem(film)\n self.logger.debug('SUBTITLE FOUND {} from url {}' , subs, film.url_sub)\n if listitem:\n if subs:\n listitem.setSubtitles(subs)\n self.plugin.set_resolved_url(True, listitem)\n self.logger.debug('play_movie_with_subs processed: {} sec', time.time() - start)","def download(connection, priv_key, server_pub_key):\r\n\r\n # Get the filename from the user\r\n file_name = input('What file would you like to download from the server?: ')\r\n\r\n # Tell the server to prepare to download a file\r\n connection.sendall(rsa.encrypt(b'DOWNLOAD', server_pub_key))\r\n\r\n # Send the file name to the server\r\n connection.sendall(rsa.encrypt(file_name.encode(), server_pub_key))\r\n\r\n # Attempt to download the file\r\n try:\r\n shared.download_file(connection, priv_key, file_name)\r\n\r\n # If the server can't find the file that is asked for\r\n except ValueError:\r\n print(''.join(['\\nThe file does not exist']), file=sys.stderr)","def __init__(self, subtitle_zip_files_dir, target_dir, temp_storage_dir):\n self._video_formats = ('avi', 'mp4', 'mov', 'mkv', 'mk3d', 'webm', \\\n 'ts', 'mts', 'm2ts', 'ps', 'vob', 'evo', 'mpeg', 'mpg', \\\n 'm1v', 'm2p', 'm2v', 'm4v', 'movhd', 'movx', 'qt', \\\n 'mxf', 'ogg', 'ogm', 'ogv', 'rm', 'rmvb', 'flv', 'swf', \\\n 'asf', 'wm', 'wmv', 'wmx', 'divx', 'x264', 'xvid')\n\n self.subtitle_zip_files_dir = pathlib.Path(subtitle_zip_files_dir)\n self.target_dir = pathlib.Path(target_dir)\n self.temp_storage_dir = pathlib.Path(temp_storage_dir)","def dowload_vt():\n print get_date_time_now() + \" ==> Download VT Samples started!\"\n print get_date_time_now() + \" ==> Nothing downloaded\"","def start(self):\n if not path.exists(self.dir):\n mkdir(self.dir)\n\n try:\n yt = YouTube(self.link)\n ys = yt.streams\n if self.aud == True:\n ysf = ys.get_audio_only()\n elif self.aud == False:\n ysf = ys.get_by_resolution(resolution=self.res)\n ysf.download(self.dir)\n except AttributeError:\n raise Exception(f\"Resolution [{self.res}] is not available for this video\")\n except excep.RegexMatchError:\n raise Exception(\"Invalid link!\")\n except excep.VideoPrivate:\n raise Exception(\"This video is private! Try with a public one\")\n except excep.PytubeError:\n raise Exception(\"Error occured!\")\n except excep.VideoPrivate:\n raise Exception(\"This video is private! Try with a public one\")\n except excep.VideoUnavailable:\n raise Exception(\"This video is unvailable!\")\n except excep.ExtractError:\n raise Exception(\"Error in extractiong the video!\")\n except Exception:\n raise Exception(\"Error occured. Make sure of your connection ;)\")","def download(dltype, num):\n # This function needs refactoring!\n # pylint: disable=R0912\n # pylint: disable=R0914\n if g.browse_mode == \"ytpl\" and dltype in (\"da\", \"dv\"):\n plid = g.ytpls[int(num) - 1][\"link\"]\n down_plist(dltype, plid)\n return\n\n elif g.browse_mode == \"ytpl\":\n g.message = \"Use da or dv to specify audio / video playlist download\"\n g.message = c.y + g.message + c.w\n g.content = generate_songlist_display()\n return\n\n elif g.browse_mode != \"normal\":\n g.message = \"Download must refer to a specific video item\"\n g.message = c.y + g.message + c.w\n g.content = generate_songlist_display()\n return\n\n writestatus(\"Fetching video info...\")\n song = (g.model.songs[int(num) - 1])\n best = dltype.startswith(\"dv\") or dltype.startswith(\"da\")\n\n if not best:\n\n try:\n # user prompt for download stream\n url, ext, url_au, ext_au = prompt_dl(song)\n\n except KeyboardInterrupt:\n g.message = c.r + \"Download aborted!\" + c.w\n g.content = generate_songlist_display()\n return\n\n if not url or ext_au == \"abort\":\n # abort on invalid stream selection\n g.content = generate_songlist_display()\n g.message = \"%sNo download selected / invalid input%s\" % (c.y, c.w)\n return\n\n else:\n # download user selected stream(s)\n filename = _make_fname(song, ext)\n args = (song, filename, url)\n\n if url_au and ext_au:\n # downloading video and audio stream for muxing\n audio = False\n filename_au = _make_fname(song, ext_au)\n args_au = (song, filename_au, url_au)\n\n else:\n audio = ext in (\"m4a\", \"ogg\")\n\n kwargs = dict(audio=audio)\n\n elif best:\n # set updownload without prompt\n url_au = None\n av = \"audio\" if dltype.startswith(\"da\") else \"video\"\n audio = av == \"audio\"\n filename = _make_fname(song, None, av=av)\n args = (song, filename)\n kwargs = dict(url=None, audio=audio)\n\n try:\n # perform download(s)\n dl_filenames = [args[1]]\n f = _download(*args, **kwargs)\n if f:\n g.message = \"Saved to \" + c.g + f + c.w\n\n if url_au:\n dl_filenames += [args_au[1]]\n _download(*args_au, allow_transcode=False, **kwargs)\n\n except KeyboardInterrupt:\n g.message = c.r + \"Download halted!\" + c.w\n\n try:\n for downloaded in dl_filenames:\n os.remove(downloaded)\n\n except IOError:\n pass\n\n if url_au:\n # multiplex\n mux_cmd = \"APP -i VIDEO -i AUDIO -c copy OUTPUT\".split()\n mux_cmd = \"%s -i %s -i %s -c copy %s\"\n mux_cmd = [g.muxapp, \"-i\", args[1], \"-i\", args_au[1], \"-c\",\n \"copy\", args[1][:-3] + \"mp4\"]\n\n try:\n subprocess.call(mux_cmd)\n g.message = \"Saved to :\" + c.g + mux_cmd[7] + c.w\n os.remove(args[1])\n os.remove(args_au[1])\n\n except KeyboardInterrupt:\n g.message = \"Audio/Video multiplex aborted!\"\n\n g.content = generate_songlist_display()","async def download_video(v_url):\n reply = await v_url.get_reply_message()\n if v_url.pattern_match.group(2) != \"\":\n url = v_url.pattern_match.group(2)\n elif reply is not None:\n url = reply.message\n url = re.findall(r\"\\bhttps?://.*\\.\\S+\", reply.message)[0]\n else:\n return\n type = (\n v_url.pattern_match.group(1).lower()\n if v_url.pattern_match.group(1) is not None\n else \"a\"\n )\n await v_url.edit(\"`Preparing to download...`\")\n out_folder = Config.TMP_DOWNLOAD_DIRECTORY + \"youtubedl/\"\n Config.TMP_DOWNLOAD_DIRECTORY + \"/thumb_image.jpg\"\n if not os.path.isdir(out_folder):\n os.makedirs(out_folder)\n if type == \"a\":\n opts = {\n \"format\": \"bestaudio\",\n \"addmetadata\": True,\n \"noplaylist\": False,\n \"key\": \"FFmpegMetadata\",\n \"writethumbnail\": True,\n \"embedthumbnail\": True,\n \"prefer_ffmpeg\": True,\n \"geo_bypass\": True,\n \"nocheckcertificate\": True,\n \"postprocessors\": [\n {\n \"key\": \"FFmpegExtractAudio\",\n \"preferredcodec\": \"mp3\",\n \"preferredquality\": \"320\",\n }\n ],\n \"outtmpl\": out_folder + \"%(title)s.%(ext)s\",\n \"quiet\": True,\n \"logtostderr\": False,\n }\n video = False\n song = True\n\n elif type == \"v\":\n opts = {\n \"format\": \"best\",\n \"addmetadata\": True,\n \"noplaylist\": False,\n \"getthumbnail\": True,\n \"embedthumbnail\": True,\n \"xattrs\": True,\n \"writethumbnail\": True,\n \"key\": \"FFmpegMetadata\",\n \"prefer_ffmpeg\": True,\n \"geo_bypass\": True,\n \"nocheckcertificate\": True,\n \"postprocessors\": [\n {\"key\": \"FFmpegVideoConvertor\", \"preferedformat\": \"mp4\"},\n ],\n \"outtmpl\": out_folder + \"%(title)s.%(ext)s\",\n \"logtostderr\": False,\n \"quiet\": True,\n }\n song = False\n video = True\n\n try:\n await v_url.edit(\"`Fetching playlist data, please wait..`\")\n with YoutubeDL(opts) as ytdl:\n ytdl.extract_info(url)\n # print(ytdl_data['thumbnail'])\n filename = sorted(get_lst_of_files(out_folder, []))\n except DownloadError as DE:\n await v_url.edit(f\"`{str(DE)}`\")\n return\n except ContentTooShortError:\n await v_url.edit(\"`The download content was too short.`\")\n return\n except GeoRestrictedError:\n await v_url.edit(\n \"`Video is not available from your geographic location due to geographic restrictions imposed by a website.`\"\n )\n return\n except MaxDownloadsReached:\n await v_url.edit(\"`Max-downloads limit has been reached.`\")\n return\n except PostProcessingError:\n await v_url.edit(\"`There was an error during post processing.`\")\n return\n except UnavailableVideoError:\n await v_url.edit(\"`Media is not available in the requested format.`\")\n return\n except XAttrMetadataError as XAME:\n await v_url.edit(f\"`{XAME.code}: {XAME.msg}\\n{XAME.reason}`\")\n return\n except ExtractorError:\n await v_url.edit(\"`There was an error during info extraction.`\")\n return\n except Exception as e:\n await v_url.edit(f\"{str(type(e)): {str(e)}}\")\n return\n c_time = time.time()\n await v_url.edit(\"`YouTube Playlist Downloading Processing Now.\\nPlease Wait!`\")\n if song:\n for single_file in filename:\n if os.path.exists(single_file):\n caption_rts = os.path.basename(single_file)\n force_document = True\n supports_streaming = False\n document_attributes = []\n if single_file.endswith((\".mp4\", \".mp3\", \".flac\", \".webm\")):\n metadata = extractMetadata(createParser(single_file))\n duration = 0\n width = 0\n height = 180\n if metadata.has(\"duration\"):\n duration = metadata.get(\"duration\").seconds\n document_attributes = [\n DocumentAttributeVideo(\n duration=duration,\n w=width,\n h=height,\n round_message=False,\n supports_streaming=True,\n )\n ]\n try:\n ytdl_data_name_audio = os.path.basename(single_file)\n thumb = (\n out_folder\n + ytdl_data_name_audio[: (len(ytdl_data_name_audio) - 4)]\n + \".jpg\"\n )\n print(ytdl_data_name_audio)\n file_path = single_file\n song_size = file_size(file_path)\n await v_url.client.send_file(\n v_url.chat_id,\n single_file,\n caption=f\"`{ytdl_data_name_audio}`\"\n + \"\\n\"\n + f\"Size👉 {song_size}\",\n force_document=force_document,\n supports_streaming=supports_streaming,\n allow_cache=False,\n thumb=thumb,\n reply_to=v_url.message.id,\n attributes=document_attributes,\n progress_callback=lambda d, t: asyncio.get_event_loop().create_task(\n progress(\n d,\n t,\n v_url,\n c_time,\n \"Uploading..\",\n f\"{ytdl_data_name_audio}\",\n )\n ),\n )\n # os.remove(thumb)\n except Exception as e:\n await v_url.client.send_message(\n v_url.chat_id,\n \"{} caused `{}`\".format(caption_rts, str(e)),\n )\n continue\n os.remove(single_file)\n await asyncio.sleep(DELETE_TIMEOUT)\n # await v_url.delete()\n shutil.rmtree(out_folder)\n if video:\n for single_file in filename:\n if os.path.exists(single_file):\n caption_rts = os.path.basename(single_file)\n force_document = False\n supports_streaming = True\n document_attributes = []\n if single_file.endswith((\".mp4\", \".mp3\", \".flac\", \".webm\")):\n metadata = extractMetadata(createParser(single_file))\n duration = 0\n width = 0\n height = 0\n if metadata.has(\"duration\"):\n duration = metadata.get(\"duration\").seconds\n document_attributes = [\n DocumentAttributeVideo(\n duration=duration,\n w=width,\n h=height,\n round_message=False,\n supports_streaming=True,\n )\n ]\n # print(ytdl_data)\n # for file in os.listdir(\"./DOWNLOADS/youtubedl/\"):\n # if file.endswith(\".jpg\"):\n # thumb = \"./DOWNLOADS/youtubedl/\" + file\n # print(os.path.join(\"./DOWNLOADS/youtubedl/\", file))\n # image_link = ytdl_data['thumbnail']\n # downloaded_image = wget.download(image_link,out_folder)\n # thumb = ytdl_data_name_video + \".jpg\"\n file_path = single_file\n video_size = file_size(file_path)\n try:\n ytdl_data_name_video = os.path.basename(single_file)\n thumb = (\n out_folder\n + ytdl_data_name_video[: (len(ytdl_data_name_video) - 4)]\n + \".jpg\"\n )\n await v_url.client.send_file(\n v_url.chat_id,\n single_file,\n caption=f\"`{ytdl_data_name_video}`\"\n + \"\\n\"\n + f\"Size👉 {video_size}\",\n force_document=force_document,\n supports_streaming=supports_streaming,\n thumb=thumb,\n allow_cache=False,\n reply_to=v_url.message.id,\n attributes=document_attributes,\n progress_callback=lambda d, t: asyncio.get_event_loop().create_task(\n progress(\n d,\n t,\n v_url,\n c_time,\n \"Uploading..\",\n f\"{ytdl_data_name_video}\",\n )\n ),\n )\n # os.remove(thumb)\n except Exception as e:\n await v_url.client.send_message(\n v_url.chat_id,\n \"{} caused `{}`\".format(caption_rts, str(e)),\n )\n continue\n os.remove(single_file)\n await asyncio.sleep(DELETE_TIMEOUT)\n # await v_url.delete()\n shutil.rmtree(out_folder)","def do_downloads(filename1=\"og\", filename2=\"lyrical\", video_id=DEFALT_VIDEO_ID):\n original_video_url = youtube_id_to_url(video_id)\n download_from_url(original_video_url, filename1)\n lyrics_video_url = get_lyrics_url(original_video_url)\n download_from_url(lyrics_video_url, filename2)\n\n return filename1, filename2","def download_cdn_videos(filenames,sub_urls,handout_urls,video_urls, target_dir):\n \"\"\" using a simple file downloader \"\"\"\n for i, v in enumerate(video_urls):\n filename_prefix = str(i+1).zfill(2) + '-'\n #original_filename = v.rsplit('/', 1)[1]\n video_filename = filename_prefix + filenames[i] + '.mp4'\n sub_filename = filename_prefix + filenames[i] + '.srt'\n handout_filename = filename_prefix + filenames[i] + '.srt'\n video_path = os.path.join(target_dir, video_filename)\n sub_path = os.path.join(target_dir, sub_filename)\n handout_path = os.path.join(target_dir, handout_filename)\n #print('[debug] GET %s' % v)\n print('[download] Destination: %s' % video_path)\n v = quote(v,safe=\":/\")\n if len(v) != YOUTUBE_VIDEO_ID_LENGTH:\n req = Request(v) \n try:\n video = urlopen(v)\n fileSize = int(video.headers['content-length'])\n finish = False\n existSize = 0\n if os.path.exists(video_path):\n output = open(video_path,\"ab\")\n existSize = os.path.getsize(video_path)\n #If the file exists, then only download the remainder\n if existSize < fileSize:\n #print(\"[debug] bytes range is: %s-%s\" % (existSize,fileSize))\n req.headers[\"Range\"]= \"bytes=%s-%s\" % (existSize,fileSize)\n video = urlopen(req)\n else:\n finish = True\n else:\n output = open(video_path,\"wb\")\n if finish == False:\n file_size_dl = existSize\n block_sz = 262144\n while True:\n buffer = video.read(block_sz)\n if not buffer:\n break\n \n file_size_dl += len(buffer)\n output.write(buffer)\n status = r\"%10d [%3.2f%%]\" % (file_size_dl, file_size_dl * 100. / fileSize)\n status = status + chr(8)*(len(status)+1)\n sys.stdout.write(status)\n sys.stdout.flush()\n \n output.close()\n\n except URLError as e:\n print(\"[warning]error: %r when downloading %s\" % (e.reason,v) )\n\n else:\n download_youtube_video(v,video_path)\n \n if sub_urls[i] != \"\":\n #print('[debug] GET %s' % BASE_URL+sub_urls[i])\n if not os.path.exists(sub_path):\n subs_string = edx_get_subtitle(sub_urls[i], headers)\n if subs_string:\n print('[info] Writing edX subtitles: %s' % sub_path)\n open(os.path.join(os.getcwd(), sub_path),\n 'wb+').write(subs_string.encode('utf-8'))\n\n if handout_urls[i] != \"\":\n #print('[debug] GET %s' % BASE_URL+sub_urls[i])\n if not os.path.exists(handout_path):\n handout_content = urlopen(BASE_URL+handout_urls[i]).read()\n if handout_content:\n print('[info] Writing handout: %s' % handout_path)\n open(os.path.join(os.getcwd(), handout_path),\n 'wb+').write(handout_content)\n #srtfile = urlopen(BASE_URL+sub_urls[i])\n #output = open(srt_path,'wb')\n #output.write(srtfile.read())\n #output.close()","def main():\n\tif not len(sys.argv) in (3, 4):\n\t\tprint \"usage: nowplaying \\\"Interpreter\\\" \\\"Title\\\" [\\\"link\\\"]\"\n\t\tsys.exit(1)\n\tinterpreter = sys.argv[1]\n\ttitle = sys.argv[2]\n\tif len(sys.argv) == 4:\n\t\tlink = sys.argv[3]\n\telse:\n\t\tlink = None\n\t\n\tclient = NowPlayingClient(APIKEY)\n\tret = client.sendTrack(interpreter, title, link)\n\tif ret == \"Done.\\n\":\n\t\tsys.exit(0)\n\telse:\n\t\t# some debugging\n\t\tprint \"ERROR!\\nServer response below:\\n\\n--BEGIN SERVER RESPONSE--\"\n\t\tprint ret\n\t\tprint \"--END SERVER RESPONSE--\"\n\t\tsys.exit(1)","async def download_audio(event):\n url = event.pattern_match.group(1)\n rmsg = await event.get_reply_message()\n if not url and rmsg:\n myString = rmsg.text\n url = re.search(\"(?P<url>https?://[^\\s]+)\", myString).group(\"url\")\n if not url:\n return await edit_or_reply(event, \"`What I am Supposed to find? Give link`\")\n codevent = await edit_or_reply(event, \"`Preparing to download...`\")\n reply_to_id = await reply_id(event)\n ytdl_data = await ytdl_down(codevent, audio_opts, url)\n if ytdl_data is None:\n return\n await codevent.edit(\n f\"`Preparing to upload song:`\\\n \\n**{ytdl_data['title']}**\\\n \\nby *{ytdl_data['uploader']}*\"\n )\n f = pathlib.Path(f\"{ytdl_data['title']}.mp3\".replace(\"|\", \"_\"))\n codthumb = pathlib.Path(f\"{ytdl_data['title']}.mp3.jpg\".replace(\"|\", \"_\"))\n if not os.path.exists(codthumb):\n codthumb = pathlib.Path(f\"{ytdl_data['title']}.mp3.webp\".replace(\"|\", \"_\"))\n if not os.path.exists(codthumb):\n codthumb = None\n c_time = time.time()\n ul = io.open(f, \"rb\")\n uploaded = await event.client.fast_upload_file(\n file=ul,\n progress_callback=lambda d, t: asyncio.get_event_loop().create_task(\n progress(d, t, codevent, c_time, \"upload\", file_name=f)\n ),\n )\n ul.close()\n attributes, mime_type = await fix_attributes(f, ytdl_data, supports_streaming=True)\n media = types.InputMediaUploadedDocument(\n file=uploaded,\n mime_type=mime_type,\n attributes=attributes,\n thumb=await event.client.upload_file(codthumb) if codthumb else None,\n )\n await event.client.send_file(\n event.chat_id,\n file=media,\n reply_to=reply_to_id,\n caption=ytdl_data[\"title\"],\n supports_streaming=True,\n force_document=False,\n )\n os.remove(f)\n if codthumb:\n os.remove(codthumb)\n await codevent.delete()","def do_GET(s):\n s.send_response(200)\n s.send_header(\"Content-type\", \"text/html;charset=utf-8\")\n s.send_header(\"Accept-Charset\", \"utf-8\")\n s.end_headers()\n s.wfile.write(\"<html><head><title>Oll.tv - live stream links</title>\" \\\n \"<style type='text/css'>\"\n \"#content { \\n\"\n \" width: 900px; \\n\" \\\n \" display: inline;\" \\\n \"}\\n\" \\\n \"div.item { \\n\" \\\n \" width: 12%; \\n\" \\\n \" min-width: 165px; \\n\" \\\n \" display: inline-block; \\n\" \\\n \" -webkit-box-shadow: 3px -1px 20px -1px rgba(0,0,0,0.6); \\n\" \\\n \" -moz-box-shadow: 3px -1px 20px -1px rgba(0,0,0,0.6); \\n\" \\\n \" box-shadow: 3px -1px 20px -1px rgba(0,0,0,0.6); \\n\" \\\n \" margin: 15px; \\n\" \\\n \" text-align: center; \\n\" \\\n \" padding: 10px; \\n\" \\\n \" padding-bottom: 10px; \\n\" \\\n \" vertical-align: top; \\n\" \\\n \"} \\n\" \\\n \"</style>\" \\\n \"</head>\")\n s.wfile.write(\"<body><p><a href='/index/'>Oll.tv</a> - Get channel stream links</p><div id='content'>\")\n myid = 0\n try:\n path_list = s.path.split('/')\n if len(path_list[2]) != 0:\n myid = path_list[2]\n except IndexError:\n pass\n\n if path_list[1] == 'channel':\n channel_data = dorequest('GetTVChannel', {'item_id': myid, 'afterDays': 7})\n s.wfile.write(\"<h2>%s</h2><img src='%s' border=0><br/>\" % (\n channel_data[u'name'].encode('utf8', 'ignore'),\n channel_data[u'poster'].encode('utf8', 'ignore')\n ))\n # s.wfile.write(\"<a href='/item/%s'>Get Online Link</a><ul>\" % (channel_data[u'item_id']))\n channel_link_data = dorequest('media', {'id': channel_data[u'item_id']})\n if len(channel_link_data) > 0:\n s.wfile.write(\"Your live stream link here:<br/><input type='text' size='140' value='%s'/><ul>\" % (\n channel_link_data[u'media_url'].encode('utf-8', 'ignore'),\n ))\n print pprint.pprint(channel_data[u'nextThree'])\n print pprint.pprint(channel_data[u'program'])\n for line in channel_data[u'nextThree']:\n s.wfile.write(\"<li><a href='/programm/%s'>%s</a> (%s / %s) - %s</li>\" % (\n line[u'programm_id'],\n line[u'name'].encode('utf8', 'ignore'),\n line[u'start'].encode('utf8', 'ignore'),\n line[u'stop'].encode('utf8', 'ignore'),\n ''))\n s.wfile.write(\"</ul><br/>History:<ul>\")\n for line in channel_data[u'program']:\n s.wfile.write(\"<li><a href='/programm/%s'>%s</a> (%s / %s) - %s</li>\" % (\n line[u'programm_id'],\n line[u'name'].encode('utf8', 'ignore'),\n line[u'start'].encode('utf8', 'ignore'),\n line[u'stop'].encode('utf8', 'ignore'),\n ''))\n elif path_list[1] == 'item':\n channel_data = dorequest('media', {'id': myid})\n if len(channel_data) > 0:\n s.wfile.write(\"<ul><li>%s</li><li>%s</li><li>%s</li></ul>\" % (\n channel_data[u'category_name'].encode('utf-8', 'ignore'),\n channel_data[u'title'].encode('utf-8', 'ignore'),\n channel_data[u'media_url'].encode('utf-8', 'ignore'),\n ))\n print pprint.pprint(channel_data)\n\n elif path_list[1] == 'index' or s.path == '/':\n channels = dorequest('getAllTVChannels')\n for line in channels:\n for item in line[u'items']:\n try:\n if item[u'is_free'] != 1:\n continue\n except KeyError:\n continue\n s.wfile.write(\"<div class='item'><a href='/channel/%s'><img src='%s' border=0/>\" \\\n % (item[u'id'],\n item[u'src']))\n\n s.wfile.write(\"<br/>%s (%s)</a><br/>%s</div>\" \\\n % (item[u'title'].encode('utf8', 'ignore'),\n item[u'genre'].encode('utf8', 'ignore'),\n item[u'descr'].encode('utf8', 'ignore')))\n # s.wfile.write(\"<p>You accessed path: %s</p>\" % s.path) # debug info\n s.wfile.write(\"</div></body></html>\")","def add_subtitles(media_id, req):\n\n media_hndl = media_map.get(media_id)\n if not media_hndl:\n raise FileNotFoundError('{} is not a registered media_id'.format(media_id))\n\n subfile = None\n if req.data:\n subfile = json.loads(req.data.decode('utf-8')).get('filename')\n if not subfile:\n raise AttributeError('No filename specified in the request')\n\n if not subfile:\n if not media_hndl.path:\n raise NotImplementedError(\n 'Subtitles are currently only supported for local media files')\n\n req = {\n 'type': 'request',\n 'action': 'media.subtitles.get_subtitles',\n 'args': {\n 'resource': media_hndl.path,\n }\n }\n\n try:\n subtitles = send_message(req).output or []\n except Exception as e:\n raise RuntimeError('Could not get subtitles: {}'.format(str(e)))\n\n if not subtitles:\n raise FileNotFoundError('No subtitles found for resource {}'.\n format(media_hndl.path))\n\n req = {\n 'type': 'request',\n 'action': 'media.subtitles.download',\n 'args': {\n 'link': subtitles[0].get('SubDownloadLink'),\n 'media_resource': media_hndl.path,\n 'convert_to_vtt': True,\n }\n }\n\n subfile = (send_message(req).output or {}).get('filename')\n\n media_hndl.set_subtitles(subfile)\n return {\n 'filename': subfile,\n 'url': get_remote_base_url() + '/media/subtitles/' + media_id + '.vtt',\n }","async def download_video(event):\n url = event.pattern_match.group(1)\n rmsg = await event.get_reply_message()\n if not url and rmsg:\n myString = rmsg.text\n url = re.search(\"(?P<url>https?://[^\\s]+)\", myString).group(\"url\")\n if not url:\n return await edit_or_reply(event, \"What I am Supposed to find? Give link\")\n codevent = await edit_or_reply(event, \"`Preparing to download...`\")\n reply_to_id = await reply_id(event)\n ytdl_data = await ytdl_down(codevent, video_opts, url)\n if ytdl_down is None:\n return\n f = pathlib.Path(f\"{ytdl_data['title']}.mp4\".replace(\"|\", \"_\"))\n codthumb = pathlib.Path(f\"{ytdl_data['title']}.jpg\".replace(\"|\", \"_\"))\n if not os.path.exists(codthumb):\n codthumb = pathlib.Path(f\"{ytdl_data['title']}.webp\".replace(\"|\", \"_\"))\n if not os.path.exists(codthumb):\n codthumb = None\n await codevent.edit(\n f\"`Preparing to upload video:`\\\n \\n**{ytdl_data['title']}**\\\n \\nby *{ytdl_data['uploader']}*\"\n )\n ul = io.open(f, \"rb\")\n c_time = time.time()\n attributes, mime_type = await fix_attributes(f, ytdl_data, supports_streaming=True)\n uploaded = await event.client.fast_upload_file(\n file=ul,\n progress_callback=lambda d, t: asyncio.get_event_loop().create_task(\n progress(d, t, codevent, c_time, \"upload\", file_name=f)\n ),\n )\n ul.close()\n media = types.InputMediaUploadedDocument(\n file=uploaded,\n mime_type=mime_type,\n attributes=attributes,\n thumb=await event.client.upload_file(codthumb) if codthumb else None,\n )\n await event.client.send_file(\n event.chat_id,\n file=media,\n reply_to=reply_to_id,\n caption=ytdl_data[\"title\"],\n )\n os.remove(f)\n if codthumb:\n os.remove(codthumb)\n await event.delete()","def main(url, localfile):\n ph.download_file(url, localfile)","def download_file(year: str, month: str, career: str, kind: str = \"ativo\") -> str:\n\n career = career.lower()\n downloaded_files = []\n existing_files = []\n res = \"\"\n for file_ in CGU_FILES[career][kind]:\n url = f\"{URL_CGU_DOWNLOADS}/{year}{month}_{file_}\"\n try:\n division = file_.split(\"_\")[-1] if career == \"civil\" else None\n if not file_exists(year, month, career, kind, division):\n print(f\"Downloading {url}\")\n sleep(10)\n req = requests.get(url, stream=True, timeout=90)\n req.raise_for_status()\n filename = (\n req.headers.get(\"Content-Disposition\")\n .split(\"=\")[-1]\n .replace('\"', \"\")\n )\n saved = save_file(filename, req.content)\n unzipped_file = unzip_salary_file(saved, year, month, career, kind)\n downloaded_files.append(unzipped_file)\n else:\n print(f\"Arquivo {url} já existe\")\n existing_files.append(file_)\n res = f\"Arquivos baixados: {', '.join(downloaded_files)} \\nArquivos existentes: {', '.join(existing_files)}\"\n except requests.exceptions.ConnectionError as err:\n res = f\"Erro de conexão: {err}\"\n # pylint: disable=line-too-long\n # Erro de conexão: HTTPConnectionPool(host='www.portaltransparencia.gov.br', port=80): Max retries\n # exceeded with url: /download-de-dados/servidores/202202_Reserva_Reformas_Militares (Caused by\n # NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f9cd019cd90>: Failed to establish\n # a new connection: [Errno -3] Temporary failure in name resolution')\n except requests.exceptions.HTTPError as err:\n res = f\"Arquivo inexistente: {url.split('/')[-1]}.zip - {err}\"\n # pylint: disable=line-too-long\n # Erro no download: 404 Client Error: Not Found for url:\n # https://www.portaltransparencia.gov.br/download-de-dados/servidores/202202_Reserva_Reformas_Militares\n\n print(res)\n return res","def get_sunpy_files(self):\n from sunpy.net import jsoc\n client = jsoc.JSOCClient() \n dfmt = '%Y-%m-%dT%H:%M:%S' #date format for JSOC\n\n #get a query response from JSOC\n response = client.query(jsoc.Time(self.start.strftime(dfmt),self.end.strftime(dfmt)),jsoc.Series(self.series),\n jsoc.Wavelength(self.wav),jsoc.Segment(self.segment),jsoc.Notify(self.email))\n\n res = client.get(response,path=self.odir,sleep=60,overwrite=self.overwrite,max_conn=self.max_con)\n res.wait(progress=True)","def download():\n raise NotImplementedError","def getSubtitleURL(self):\n\n # If it is a movie, we use this methodology -\n try:\n IndexingParameters = [\"subtitleUrls\", 0, \"url\"]\n TitleParamters = [\n \"catalogMetadata\", \"catalog\", \"title\", \"episodeNumber\"]\n subRequestObject = requests.get(self.subtitleURLContainer)\n\n parsedJsonObject = json.loads(str(subRequestObject.text))\n SubsURL = parsedJsonObject[IndexingParameters[0]][\n IndexingParameters[1]][IndexingParameters[2]]\n if self.title == \"Amazonsubtitles\":\n try:\n self.title = parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[2]] + \"_\" + str(\n parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[3]])\n except:\n pass\n\n return SubsURL\n\n except:\n pass\n pass","def extract_data():\n args = arguments()\n\n if args.list is not None:\n songs = utility.get_songs(args.list)\n logger.debug(str(songs))\n if len(songs) != 0:\n logger.info(\"Downloading songs in {}\".format(args.list))\n for song_name in songs:\n logger.debug(song_name)\n args.SONG_NAME = [song_name]\n main(args)\n else:\n logger.info(\"{}: is empty\".format(args.list))\n elif args.SONG_NAME and yt.is_playlist(args.SONG_NAME[0]):\n logger.info(\"Youtube playlist passed...extracting!\")\n songs, playlist_name = yt.get_playlist(\n args.SONG_NAME[0],\n args.proxy,\n args.pl_start,\n args.pl_end,\n args.pl_items\n )\n\n # Check if data is actually returned\n if songs is None:\n logger.error(\"Couldn't extract playlist data!\")\n\n logger.info(\"Playlist: {}\".format(playlist_name))\n logger.info(\"{} songs found\".format(len(songs)))\n\n # Iterate and work on the data.\n url_base = \"https://www.youtube.com/watch?v=\"\n for song in songs:\n args.url = url_base + song[\"url\"]\n\n # Try to pass the title as well, if it's not there\n # that will be handled by ytmdl\n try:\n args.SONG_NAME = [stringutils.remove_yt_words(song[\"title\"])]\n except KeyError:\n pass\n\n main(args)\n else:\n main(args)","def extract_subtitle_track(path_to_mkv):\n handler = SubtitleHandler()\n with open(path_to_mkv, \"rb\") as fp:\n mkvparse.mkvparse(fp, handler)\n\n return handler.subs","def get_subtitle_print(subs: List[Track]) -> List[str]:\n data = []\n if not subs:\n data.append(\"--\")\n for sub in subs:\n line_items = []\n\n # following sub.title tree checks and supports three different language and title scenarios\n # The second scenario is the recommended option to choose if you are open to choosing any\n # The third scenario should be used if you have nothing unique to state about the track\n # | Language | Track Title | Output |\n # | ------------ | ----------------------------- | --------------------------------------------- |\n # | es / Spanish | Spanish (Latin American, SDH) | - Spanish (Latin American, SDH), SubRip (SRT) |\n # | es / Spanish | Latin American (SDH) | - Spanish, Latin American (SDH), SubRip (SRT) |\n # | es / Spanish | None | - Spanish, SubRip (SRT) |\n language = pycountry.languages.get(alpha_2=sub.language).name\n if sub.title:\n if language.lower() in sub.title.lower():\n line_items.append(sub.title)\n else:\n line_items.append(f\"{language}, {sub.title}\")\n else:\n line_items.append(language)\n\n line_items.append(sub.format.replace(\"UTF-8\", \"SubRip (SRT)\"))\n\n line = \"- \" + \", \".join(line_items)\n data += [\n (\" \" + x if i > 0 else x)\n for i, x in enumerate(textwrap.wrap(line, 64))\n ]\n return data","def do_GET(s):\n s.send_response(200)\n s.send_header(\"Content-type\", \"text/html\")\n s.end_headers()\n s.wfile.write(\"<html><head><title>Simple nc cli2dlna UI</title></head>\")\n s.wfile.write(\"<body><form action=/play method=GET><input type=text id=ytu name=ytu><input type=submit value=Play></form>\")\n s.wfile.write(\"Enter youtube URL to play\")\n if len(s.path) > 10 and s.path[0:10] == '/play?ytu=':\n url = unquote(s.path[10:])\n if match(ytl_re, url):\n s.wfile.write(\"<br>Accepted URL: %s\" % url)\n call([\n \"/storage/.kodi/addons/service.system.docker/bin/docker\",\n \"run\",\n \"--rm\",\n \"--name\",\n \"cli2dlna\",\n \"-v\",\n \"/storage/.cache/cli2dlna/renderer.cache:/renderer.cache\",\n \"mitroko/cli2dlna\",\n \"-yv\",\n url\n ])\n s.wfile.write(\"</body></html>\")","def download_data():\r\n print('Downloading cifar-10 data...')\r\n request.urlretrieve(dataurl)\r\n print('Done')\r\n print('Please unzip files. command is:')\r\n print('gzip -d cifar-10-python.tar.gz')\r\n print('tar -xf cifar-10-python.tar')\r\n exit()","def downloadSong(self, song, outputFolder=\"\", outputFunction=None, writeJSON=True):\n\n \"\"\"\n -x: Extract audio\n --audio-format: sets the audio format from ogg to mp3\n --audio-quality: 0 is best\n --write-info-json: Writes the DASH information for the downloaded video to the filename with .info.json appended\n \"\"\"\n audioOptions = self.audioOptions.copy() # Generate a shallow copy of our object's options\n if writeJSON:\n audioOptions[\"--write-info-json\"] = True\n audioOptions.update(settings[\"youtubeSettings\"])\n\n self.youtubeLock.acquire() # Wait the requisite amount of time\n log.debug(\"Downloading Song '{}'\".format(song))\n obj = subprocess.Popen(\n [settings[\"youtube_dl\"]] + # Executable\n self.flattenDict(audioOptions) + #Turn the dict items into a list where key is before value. Bools are special. If false, not added, otherwise only key\n [\"-o\", os.path.join(outputFolder, settings[\"formatString\"])] + #Output format and folder\n [\"--\", song], #Then add song as input\n **settings[\"pipeOptions\"], #Add in subprocess options\n stdout=subprocess.PIPE #Also this for now\n )\n \n outputText = \"\"\n for line in obj.stdout:\n outputText += line\n match = re.match(r\"\\[download\\]\\s+([\\d.]+)% of \\S+ at\\s+([\\d.]+\\S+)\", line) #Matches the download update lines\n if match:\n percent, downloadRate = match.group(1, 2)\n if callable(outputFunction):\n outputFunction(song, float(percent), downloadRate) #Update this if we have items\n return obj.wait(), outputText # Wait for process to complete and get return code. Also return the whole output printed to stdout","def download():\n try:\n cli.run(\n [URL, '--output', TEMP_DIR],\n )\n except SystemExit:\n return None","def main():\n # the url for african daily and global daily\n african_dialy_url = \"https://data.chc.ucsb.edu/products/CHIRPS-2.0/africa_daily/tifs/p25/\"\n global_daily_url = \"https://data.chc.ucsb.edu/products/CHIRPS-2.0/global_daily/tifs/p25/\"\n\n\n each_year_list = GetRasterYears(url=african_dialy_url)\n new_path = makenewdir(each_year_list)\n years_new_list = fecthrasterurl(url=african_dialy_url)\n downloadwithwget(each_year_list, years_new_list, new_path)","def main(file_url, file_path):\n\n # extract file from the link\n\n if not os.path.exists(file_path):\n os.makedirs(file_path, exist_ok=True)\n \n r = requests.get(str(file_url))\n\n #unzip the zip file\n z = zipfile.ZipFile(io.BytesIO(r.content))\n z.extractall(path = file_path)","def parse_message(message, selector):\n\n msg = message.decode('utf-8')\n print(colored(\"Telnet pide \" + msg, 'magenta'))\n\n # Mandó list?\n clist = re.match(r'list', msg)\n if clist:\n return armar_lista()\n\n # Mandó offer?\n else:\n offer = re.match(r'offer (.*)\\r', msg)\n if offer:\n filename = offer[1] \n\n file_path = os.getcwd() + \"/files/\" + filename\n\n if os.path.exists(file_path):\n sizefile = int(os.path.getsize(file_path))\n\n # Calcula el md5\n with open(file_path, \"rb\") as f:\n file_hash = hashlib.md5()\n chunk = f.read(8192)\n while chunk:\n file_hash.update(chunk)\n chunk = f.read(8192)\n\n file_hash = file_hash.hexdigest()\n\n aux_file = AppFile(filename, sizefile, file_hash)\n\n # Guardamos el archivo en nuestro diccionario de seguimiento local\n local_files[file_hash] = aux_file\n\n # Lo borramos del de los disponibles remotos\n if remote_files.get(file_hash):\n del remote_files[file_hash]\n\n # Una vez actualizada la lista de archivos locales, mandamos a actualizar los anuncios\n announce_forever.set_announcements()\n\n return 'ARCHIVO AGREGADO'\n\n else:\n return 'ARCHIVO NO ENCONTRADO'\n\n\n # Mandó get?\n else:\n get = re.match(r'get (\\d*)\\r\\n', msg)\n if get:\n file_id = int(get[1])\n msg = f'INICIANDO DESCARGA DEL ARCHIVO {file_id}'\n print(msg)\n request_download(file_id, selector)\n return msg\n\n return 'COMANDO INCORRECTO!'","def download (url):\n path, url = url\n r = requests.get (url, stream = True)\n content = r.text\n #print (content)\n with open (path + '.txt', 'w') as f:\n f.write (content)","def news_cli():\n get_news_cli()","def download_files(self):","def download_and_extract(down_dir=download_dir, url=tuda_url):\n\n wget.download(url, down_dir) \n tar_filepath = os.path.join(down_dir, \"german-speechdata-package-v2.tar.gz\")\n #with tarfile.open(tar_filepath, \"r\") as tar:\n # tar.extractall(down_dir)","def main():\n show_banner()\n args = parse_args(sys.argv[1:])\n urls = get_urls(args.inputfiles)\n if args.only_urls:\n print(\"URL\")\n else:\n print('{:70.70} {}'.format(\"URL\", \"Response\"))\n\n loop = asyncio.get_event_loop()\n loop.run_until_complete(download(urls,\n args.concurrency,\n args.only_success,\n args.outputfile,\n args.only_urls))","def do_downloads_by_server(self, arg):\n args = arg.split()\n if len(args) != 0:\n common.error('`downloads_by_server` doesn\\'t'\n 'expect any arguments.')\n else:\n servers = self.central_server.download_service.get_servers()\n requests = self.central_server.client_service.get_requests()\n\n if not servers.is_empty():\n print(\"%i server(s):\" % len(\n servers.servers))\n print('')\n for server in servers.servers:\n print('server:')\n print(str(server))\n print('downloads:')\n server_requests = requests.get_requests_from_server(server)\n if server_requests:\n print(tabulate(\n [request.to_row() for request\n in server_requests],\n headers=['Movie', 'Client'],\n tablefmt=\"psql\"))\n print('')\n else:\n print('No downloads\\n')\n else:\n print('There\\'s no available servers')","def retrieve_files_over_ftp(self, host, port, subpath):\n write_path = os.path.join(os.getcwd(), PathConstants.MEDIA_FOLDER)\n if not os.path.isdir(write_path):\n os.mkdir(write_path)\n client = RemuFTPClient(host, port, subpath, write_path, self)\n client.connect()","def start(self):\n tokyo_time = datetime.datetime.now(tz=TOKYO_TZ)\n\n # TODO: Does this work on Windows now?\n env = os.environ.copy()\n\n # remove proxy information\n for key in ('http_proxy', 'https_proxy', 'HTTP_PROXY', 'HTTPS_PROXY'):\n env.pop(key, None)\n\n self.update_streaming_url()\n\n # TODO: rework this whole process to include lhls, and make it configurable\n # and less braindead\n if not self._protocol:\n self._protocol = 'rtmp'\n if not self._ffmpeg_container:\n self._ffmpeg_container = 'mp4'\n extra_args = []\n # Fall back to HLS if no RTMP stream available\n # Better to do this here or in update_streaming_url?\n # There's a possible race condition here, if some external thread modifies either of these\n if not self._rtmp_url and self._protocol == 'rtmp':\n download_logger.warn('Using HLS downloader for {}'.format(self._room.handle))\n self._protocol = 'hls'\n\n # extra_args = []\n # force using TS container with HLS\n # this is causing more problems than it solves\n # if self.protocol in ('hls', 'lhls'):\n # self._ffmpeg_container = 'ts'\n\n # 2020-01-10: those problems were preferrable to completely unwatchable streams\n if self.protocol in ('hls', 'lhls'):\n extra_args = [\"-copyts\"]\n if self._ffmpeg_container == 'mp4':\n extra_args.extend([\"-bsf:a\", \"aac_adtstoasc\"])\n\n # I don't think this is needed?\n # if self._ffmpeg_container == 'ts':\n # extra_args.extend(['-bsf:v', 'h264_mp4toannexb'])\n # elif self._ffmpeg_container != 'mp4':\n # # TODO: support additional container formats, e.g. FLV\n # self._ffmpeg_container = 'mp4'\n temp, dest, out = format_name(self._rootdir,\n strftime(tokyo_time, FULL_DATE_FMT),\n self._room, ext=self._ffmpeg_container)\n\n with self._lock:\n self.tempdir, self.destdir, self.outfile = temp, dest, out\n\n if self._logging is True:\n log_file = os.path.normpath('{}/logs/{}.log'.format(self.destdir, self.outfile))\n env.update({'FFREPORT': 'file={}:level=40'.format(log_file)})\n # level=48 is debug mode, with lots and lots of extra information\n # maybe too much\n normed_outpath = os.path.normpath('{}/{}'.format(self.tempdir, self.outfile))\n\n self._process = subprocess.Popen([\n self._ffmpeg_path,\n # '-nostdin',\n # '-nostats', # will this omit any useful information?\n '-loglevel', '40', # 40+ required for wait() to check output\n '-copytb', '1',\n '-i', self.stream_url,\n '-c', 'copy',\n *extra_args,\n normed_outpath\n ],\n stdin=subprocess.DEVNULL,\n stderr=subprocess.PIPE, # ffmpeg sends all output to stderr\n universal_newlines=True,\n bufsize=1,\n env=env)","def get_server_list():\n\n if file_downloaded(output_file):\n server_list = load_server_list_json()\n printer('Server list loaded from JSON')\n\n #server_list = load_server_list_json()\n #printer('Server list loaded from JSON')\n\n else:\n # Connect to RS\n rsconn = object\n rsconn = connect()\n\n # Store the JSON response from list_servers\n printer(\"Fetching server list from Rackspace...\")\n\n server_list = rsconn.list_servers(detailed = DETAILED)\n save_server_list_json(server_list)\n\n printer('Server list loaded via API call')\n\n return server_list","def youtube_download_by_id(id, title=None, output_dir='.', merge=True, info_only=False):\n \n raw_video_info = get_content('http://www.youtube.com/get_video_info?video_id=%s' % id)\n video_info = parse.parse_qs(raw_video_info)\n \n if video_info['status'] == ['ok'] and ('use_cipher_signature' not in video_info or video_info['use_cipher_signature'] == ['False']):\n title = parse.unquote_plus(video_info['title'][0])\n stream_list = parse.parse_qs(raw_video_info)['url_encoded_fmt_stream_map'][0].split(',')\n \n else:\n # Parse video page when video_info is not usable.\n video_page = get_content('http://www.youtube.com/watch?v=%s' % id)\n ytplayer_config = json.loads(match1(video_page, r'ytplayer.config\\s*=\\s*([^\\n]+);'))\n \n title = ytplayer_config['args']['title']\n stream_list = ytplayer_config['args']['url_encoded_fmt_stream_map'].split(',')\n \n streams = {\n parse.parse_qs(stream)['itag'][0] : parse.parse_qs(stream)\n for stream in stream_list\n }\n \n for codec in yt_codecs:\n itag = str(codec['itag'])\n if itag in streams:\n download_stream = streams[itag]\n break\n \n url = download_stream['url'][0]\n if 'sig' in download_stream:\n sig = download_stream['sig'][0]\n else:\n sig = decrypt_signature(download_stream['s'][0])\n url = '%s&signature=%s' % (url, sig)\n \n type, ext, size = url_info(url)\n \n print_info(site_info, title, type, size)\n if not info_only:\n download_urls([url], title, ext, size, output_dir, merge = merge)","def __init__(self, subtitles_file, subtitles_language: str, audio_language: str):\n\n subtitles_binary = subtitles_file.read()\n encoding = detect_encoding(subtitles_binary)['encoding']\n self.subtitles = subtitles_binary.decode(encoding)\n self.encoding = encoding\n logger.debug(f'Subtitles Encoding: {encoding}')\n logger.debug(f'Subtitles[:100]: {[self.subtitles[:1000]]}')\n self.read_subtitles()\n self.audio_language = audio_language\n\n # Detect subtitles language\n if(subtitles_language == 'ad'): # ad = Auto Detect\n detected_language = detect_language(self.subtitles)\n logger.debug(f\"Subtitles language detected as {detected_language}\")\n\n # True if the detected language in google's supported languages\n language_items = any(map(\n lambda lang: lang['language'] == detected_language, Constants.GOOGLE_LANGUAGES))\n if(language_items is False):\n raise Exception(\n f'Detected language {detected_language} is not supported.')\n self.subtitles_language = detected_language\n\n else:\n self.subtitles_language = subtitles_language\n\n self.translator = CustomTranslator(self.subtitles_language, audio_language)","def start(update, context):\n update.message.reply_text(\n 'Hello! Use /convert to convert streaming music urls into other services.')","def download_songs(playlist_url):\n command_string = 'youtube-dl -x --audio-format wav --postprocessor-args \"-ar 44100 -ac 1\" --output \"Songs/%(' \\\n 'title)s_%(id)s.%(ext)s\" ' + \\\n playlist_url\n args = shlex.split(command_string)\n subprocess.call(args)","def start_torrent_download(filename):\n return tadapt.start_download(filename)","def extractRawSubtitleList(subtitleFullPath, srtEncodingConfidenceThreshold = 0.8, defaultEncoding=\"utf-8\"):\n\n getSubOk = False\n rawSubtitleListOrErrMsg = \"Unknown Error\"\n\n with open(subtitleFullPath, 'rb') as subtitleFp:\n fileContentStr = subtitleFp.read()\n detectedResult = chardet.detect(fileContentStr)\n # logging.debug(\"detectedResult=%s\", detectedResult)\n fileEncoding = defaultEncoding\n if detectedResult[\"confidence\"] >= srtEncodingConfidenceThreshold:\n fileEncoding = detectedResult[\"encoding\"] # 'UTF-8-SIG'\n # logging.debug(\"fileEncoding=%s\", fileEncoding)\n\n try:\n rawSubtitleList = pysrt.open(subtitleFullPath, encoding=fileEncoding)\n rawSubtitleListOrErrMsg = rawSubtitleList\n getSubOk = True\n except Exception as openSrtException:\n rawSubtitleListOrErrMsg = str(openSrtException)\n # logging.debug(\"Error %s of pysrt.open %s\", rawSubtitleListOrErrMsg, subtitleFullPath)\n\n return getSubOk, rawSubtitleListOrErrMsg","def main() -> None:\n run_time = datetime.datetime.now()\n datetime_string = run_time.strftime(\"%Y%m%d_%H%M%S\")\n\n parser = argparse.ArgumentParser(\n description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter\n )\n parser.add_argument(\n \"-l\",\n \"--logfolder\",\n type=str,\n default=\"ia_downloader_logs\",\n help=(\n \"Folder to write logs to (if not specified, folder 'ia_downloader_logs' will be used in\"\n \" same directory as this script)\"\n ),\n )\n\n subparsers = parser.add_subparsers(\n help=(\n \"Either 'download' files associated with an Internet Archive identifier, or 'verify' a\"\n \" previously-completed download was successful and files match expected MD5 hash values\"\n ),\n dest=\"command\",\n required=True,\n )\n\n download_parser = subparsers.add_parser(\"download\")\n download_parser.add_argument(\n \"identifiers\",\n type=str,\n nargs=\"+\",\n help=(\n \"One or more (space separated) Archive.org identifiers (e.g.\"\n \" 'gov.archives.arc.1155023'). If specifying a collection (and you wish to download all\"\n \" items within the collection), use the prefix 'collection:' (e.g. 'collection:nasa')\"\n ),\n )\n download_parser.add_argument(\"output_folder\", type=str, help=\"Folder to download files to\")\n download_parser.add_argument(\n \"-t\",\n \"--threads\",\n type=check_argument_int_greater_than_one,\n default=5,\n help=(\n \"Number of download threads (i.e. how many downloads to perform simultaneously)\"\n \" (default is 5)\"\n ),\n )\n download_parser.add_argument(\n \"-v\",\n \"--verify\",\n default=False,\n action=\"store_true\",\n help=\"Perform an MD5 hash check on each file as downloads complete\",\n )\n download_parser.add_argument(\n \"-r\",\n \"--resume\",\n default=False,\n action=\"store_true\",\n help=(\n \"Attempt to resume downloads using already-downloaded data if a connection error occurs\"\n ),\n )\n download_parser.add_argument(\n \"-s\",\n \"--split\",\n type=check_argument_int_greater_than_one,\n default=1,\n help=(\n \"To increase per-file download speeds, split files above 10MB into provided number of\"\n \" chunks, and reconstruct on completion\"\n ),\n )\n download_parser.add_argument(\n \"-f\",\n \"--filefilters\",\n type=str,\n nargs=\"+\",\n help=(\n \"One or more (space separated) file name filters; only files that contain any of the\"\n \" provided filter strings (case insensitive) will be downloaded. If multiple filters\"\n \" are provided, the search will be an 'OR' (i.e. only one of the provided strings needs\"\n \" to hit)\"\n ),\n )\n download_parser.add_argument(\n \"-c\",\n \"--credentials\",\n type=str,\n nargs=2,\n help=(\n \"Email address and password (as separate strings) for Internet Archive account\"\n \" (required for download of some Internet Archive items)\"\n ),\n )\n download_parser.add_argument(\n \"--hashfile\",\n type=str,\n help=(\n \"Output path to write file containing hash metadata to (if not specified, file will\"\n \" be created in the output folder)\"\n ),\n )\n download_parser.add_argument(\n \"--cacherefresh\",\n default=False,\n action=\"store_true\",\n help=\"Flag to update any cached Internet Archive metadata from previous script executions\",\n )\n\n verify_parser = subparsers.add_parser(\"verify\")\n verify_parser.add_argument(\n \"data_folders\",\n type=str,\n nargs=\"+\",\n help=\"Path to folder containing previously downloaded data\",\n )\n verify_parser.add_argument(\n \"-i\",\n \"--identifiers\",\n type=str,\n nargs=\"+\",\n help=(\n \"One or more (space separated) Archive.org identifiers (e.g.\"\n \" 'gov.archives.arc.1155023') - to be used if only certain item(s) in the target\"\n \" folder(s) are to be verified\"\n ),\n )\n verify_parser.add_argument(\n \"--hashfile\",\n type=str,\n help=(\n \"Path to file containing hash metadata from previous download using this script (if not\"\n \" specified, cached data from previous script execution will be used)\"\n ),\n )\n verify_parser.add_argument(\n \"-f\",\n \"--filefilters\",\n type=str,\n nargs=\"+\",\n help=(\n \"One or more (space separated) file name filters; only files that contain any of the\"\n \" provided filter strings (case insensitive) will be verified. If multiple filters\"\n \" are provided, the search will be an 'OR' (i.e. only one of the provided strings needs\"\n \" to hit)\"\n ),\n )\n verify_parser.add_argument(\n \"--nopaths\",\n default=False,\n action=\"store_true\",\n help=(\n \"If files are no longer in the same relative paths, perform lookup based only on\"\n \" whether MD5 hashes are present in the data set (rather than also checking where those\"\n \" files are stored)\"\n ),\n )\n\n args = parser.parse_args()\n\n # Set up logging\n log_subfolders = [\"logs\", \"cache\"]\n for log_subfolder in log_subfolders:\n pathlib.Path(os.path.join(args.logfolder, log_subfolder)).mkdir(parents=True, exist_ok=True)\n log, counter_handler = prepare_logging(\n datetime_string,\n os.path.join(args.logfolder, log_subfolders[0]),\n \"ia_downloader\",\n dict(vars(args)),\n )\n log.info(\n \"Internet Archive is a non-profit organisation that is experiencing unprecedented service\"\n \" demand. Please consider making a donation: https://archive.org/donate\"\n )\n log.info(\"Logs will be stored in folder '{}'\".format(args.logfolder))\n\n try:\n if args.command == \"download\":\n if args.credentials is not None:\n try:\n internetarchive.configure(args.credentials[0], args.credentials[1])\n except internetarchive.exceptions.AuthenticationError:\n log.error(\n \"Authentication error raised for supplied email address and password -\"\n \" check these were entered correctly (if the password has spaces, it must\"\n \" be wrapped in quotation marks)\"\n )\n return\n if args.hashfile is not None:\n log.info(\n \"Internet Archive metadata will be written to hash file at '{}'\".format(\n args.hashfile\n )\n )\n if args.threads > 5 or args.split > 5:\n log.info(\n \"Reducing download threads to 5, to optimise script performance and reduce\"\n \" Internet Archive server load\"\n )\n args.threads = min(args.threads, 5)\n args.split = min(args.split, 5)\n if args.split > 1:\n if args.threads > 1:\n log.info(\n \"While using file splitting, only one file will be downloaded at a time so\"\n \" as to not overwhelm Internet Archive servers\"\n )\n args.threads = 1\n hashfile_file_handler = None\n if args.hashfile:\n hashfile_file_handler = open(args.hashfile, \"w\")\n\n for identifier in args.identifiers:\n download(\n identifier=identifier,\n output_folder=args.output_folder,\n hash_file=hashfile_file_handler,\n thread_count=args.threads,\n resume_flag=args.resume,\n verify_flag=args.verify,\n split_count=args.split,\n file_filters=args.filefilters,\n cache_parent_folder=os.path.join(args.logfolder, log_subfolders[1]),\n cache_refresh=args.cacherefresh,\n )\n\n if args.hashfile:\n hashfile_file_handler.close()\n\n elif args.command == \"verify\":\n verify(\n hash_file=args.hashfile,\n data_folders=args.data_folders,\n no_paths_flag=args.nopaths,\n hash_flag=True,\n cache_parent_folder=os.path.join(args.logfolder, log_subfolders[1]),\n identifiers=args.identifiers,\n file_filters=args.filefilters,\n )\n\n if counter_handler.count[\"WARNING\"] > 0 or counter_handler.count[\"ERROR\"] > 0:\n log.warning(\n \"Script complete; {} warnings/errors occurred requiring review (see log entries\"\n \" above, replicated in folder '{}')\".format(\n counter_handler.count[\"WARNING\"] + counter_handler.count[\"ERROR\"],\n args.logfolder,\n )\n )\n else:\n log.info(\"Script complete; no errors reported\")\n\n except KeyboardInterrupt:\n log.warning(\n \"KeyboardInterrupt received, quitting immediately (any in-progress downloads or\"\n \" verifications have been terminated)\"\n )\n except Exception:\n log.exception(\"Exception occurred:\")","def handle_file_retrieval(self, msg):\n Logger.info(\"Slave: Retrieving files\")\n params = msg.get_field(MessageKeys.params_key)\n host = msg.get_field(MessageKeys.sender_key)\n port = params[MessageKeys.ftp_port_key]\n subpath = params[MessageKeys.ftp_subpath_key]\n self.presentation.set_files(params[MessageKeys.presentation_content_key])\n self.presentation.reset()\n self.layout.init_presentation()\n self.retrieve_files_over_ftp(host, port, subpath)\n self.presentation_ended = False\n return self.create_response(msg.get_command())","def main():\n pass\n # service = getServiceInstant()\n # # insertFile(service, 'dynamip.conf')\n # file_id = getFileIdFromName(service, 'dynamip.conf')\n # metadata = updateFile(service, file_id, 'dynamip.conf')\n # print(metadata)\n # file = open('metadata_of_updated_dynamip_file', 'w')\n # json.dump(metadata, file)\n # file.write(file)\n # results = service.files().list(maxResults=10).execute()\n # items = results.get('items', [])\n # if not items:\n # print('No files found.')\n # else:\n # print('Files:')\n # for item in items:\n # try:\n # print('{0} ({1})'.format(item['title'], item['id']))\n # except Exception, e:\n # print(e)","def extract_url_download(update: Update, context: CallbackContext) -> None:\r\n received_text = update.message.text\r\n yt_urls = get_link_text(received_text)\r\n yt_urls_msg = update.message.reply_text(pretty_url_string(yt_urls), disable_web_page_preview=True)\r\n if len(yt_urls) > 0:\r\n for url in yt_urls:\r\n if 'list=' in url:\r\n print(\"dshgshj\")\r\n\t\t\t\t# download_playlist_url(update, context, url)\r\n else:\r\n download_url(update, context, url)\r\n context.bot.delete_message(message_id=yt_urls_msg.message_id, chat_id=yt_urls_msg.chat_id)","def get_cmd_string(res, DVDFab_path, src_iso_path, client_dest_path): \n dest_path = change_fuhao(res[6])\n Dest = get_value(res[6], \"/DEST\")\n Mode = get_value(res[4], \"/MODE\")\n Src = get_value(src_iso_path, \"/SRC\")\n Audio = get_value(res[9], \"/AUDIO\")\n Audio_type = get_value(res[10], \"/AUDIOTYPE\")\n Change_play_order = get_value(res[11], \"/CHANGEPLAYORDER\")\n Copy_IFO = get_value(res[12], \"/COPYIFO\")\n Display_forced_sub = get_value(res[13], \"/DISPLAYFORCEDSUB\")\n Jump_menu = get_value(res[14], \"/JUMPMENU\")\n Jump_main = get_value(res[15], \"/JUMPMAIN\")\n Out_disc = get_value(res[16], \"/OUTDISC\")\n Path_player = get_value(res[17], \"/PATHPLAYER\")\n Preserve_menu_disc2 = get_value(res[18], \"/PRESERVEMENUDISC2\")\n Profile = get_value(res[19], \"/PROFILE\")\n Remove_DTS = get_value(res[20], \"/REMOVEDTS\")\n Remove_HD_audio = get_value(res[21], \"/REMOVEHDAUDIO\")\n Remove_menu = get_value(res[22], \"/REMOVEMENU\")\n Remove_PGC = get_value(res[23], \"/REMOVEPGC\")\n Rewind = get_value(res[24], \"/REWIND\")\n Subtitle = get_value(res[25], \"/SUBTITLE\")\n Title = get_value(res[26], \"/TITLE\")\n Volume = get_value(res[27], \"/VOLUME\")\n BD3DT = get_value(res[44], \"/BD3DCONVERTTYPE\")\n COMPRESSTOAC3 = get_value(res[45], \"/COMPRESSTOAC3\")\n Close = ' /CLOSE' \n Createminiso = ' /CREATEMINISO' if os.name == 'nt' else ''\n cmd_string = Mode + Src + Dest + Audio + Audio_type + Change_play_order + Copy_IFO + Display_forced_sub + Jump_menu + Jump_main\\\n + Out_disc + Path_player + Preserve_menu_disc2 + Profile + Remove_DTS + Remove_HD_audio + Remove_menu + Remove_PGC\\\n + Rewind + Subtitle + Title + Volume + BD3DT + COMPRESSTOAC3 + Close + Createminiso\n DVDFab_path_cmd_string = '\"' + DVDFab_path + '\"' + cmd_string \n initlog('the cmd_string: %s' % DVDFab_path_cmd_string)\n return DVDFab_path_cmd_string, dest_path","def download_sra_files(remote_location, local_location = '', max_recursion = 3, verbose = False):\n\n downloaded_files = list();\n\n def printv(*args):\n if(verbose):\n print(*args);\n sys.stdout.flush();\n\n printv(\"Reading folder: \", remote_location);\n\n req = urllib2.Request(remote_location);\n\n response = urllib2.urlopen(req);\n\n the_page = response.read();\n\n entries = the_page.split('\\r\\n');\n\n #Identify sub folders\n folders = list();\n for entry in entries:\n if(len(entry) == 0):\n continue;\n\n spl_entry = entry.split();\n if(spl_entry[0][0] == 'd'): #if directory flag\n folders.append(spl_entry[-1]);\n\n\n for folder in folders:\n dl_files = download_sra_files(remote_location + '/' + folder, local_location, max_recursion - 1, verbose);\n downloaded_files.extend(dl_files);\n\n #Identify SRA files\n files = list();\n for entry in entries:\n if(len(entry) == 0):\n continue;\n\n spl_entry = entry.split();\n if(spl_entry[0][0] == '-' and #Not a directory\n spl_entry[-1].lower().endswith('.sra')): #Has extension '.sra'\n\n files.append(spl_entry[-1]);\n\n if(len(files) > 0):\n printv(\"Identified sra files: \");\n for file_name in files:\n printv(\" \", file_name);\n\n abs_local_location = os.path.abspath(local_location);\n\n if(not os.path.isdir(abs_local_location)):\n os.makedirs(abs_local_location);\n\n for file_name in files:\n\n printv(\"Downloading \", file_name);\n\n file_str = remote_location + '/' + file_name;\n\n req = urllib2.Request(file_str);\n response = urllib2.urlopen(req);\n\n dest_file_name = abs_local_location + os.sep + file_name;\n dest_file = open(dest_file_name, 'wb');\n shutil.copyfileobj(response, dest_file)\n dest_file.close();\n downloaded_files.append(dest_file_name);\n\n return downloaded_files;","async def _(event):\n if event.fwd_from:\n return\n\n strings = {\n \"name\": \"DeezLoad\",\n \"arl_token_cfg_doc\": \"ARL Token for Deezer\",\n \"invalid_arl_token\": \"please set the required variables for this module\",\n \"wrong_cmd_syntax\": \"bruh, now i think how far should we go. please terminate my Session 🥺\",\n \"server_error\": \"We're experiencing technical difficulties.\",\n \"processing\": \"`Downloading...`\",\n }\n\n ARL_TOKEN = Config.DEEZER_ARL_TOKEN\n\n if ARL_TOKEN is None:\n await event.edit(strings[\"invalid_arl_token\"])\n return\n\n try:\n loader = deezloader.Login(ARL_TOKEN)\n except Exception as er:\n await event.edit(str(er))\n return\n\n temp_dl_path = os.path.join(Config.TMP_DOWNLOAD_DIRECTORY, str(time.time()))\n if not os.path.exists(temp_dl_path):\n os.makedirs(temp_dl_path)\n\n required_link = event.pattern_match.group(1)\n required_qty = event.pattern_match.group(2)\n\n await event.edit(strings[\"processing\"])\n\n if \"spotify\" in required_link:\n if \"track\" in required_link:\n required_track = loader.download_trackspo(\n required_link,\n output=temp_dl_path,\n quality=required_qty,\n recursive_quality=True,\n recursive_download=True,\n not_interface=True,\n )\n await event.edit(\"`Uploading...`\")\n await upload_track(required_track, event)\n shutil.rmtree(temp_dl_path)\n await event.delete()\n\n elif \"album\" in required_link:\n reqd_albums = loader.download_albumspo(\n required_link,\n output=temp_dl_path,\n quality=required_qty,\n recursive_quality=True,\n recursive_download=True,\n not_interface=True,\n zips=False,\n )\n for required_track in reqd_albums:\n await upload_track(required_track, event)\n shutil.rmtree(temp_dl_path)\n await event.delete()\n\n elif \"deezer\" in required_link:\n if \"track\" in required_link:\n required_track = loader.download_trackdee(\n required_link,\n output=temp_dl_path,\n quality=required_qty,\n recursive_quality=True,\n recursive_download=True,\n not_interface=True,\n )\n await event.edit(\"Uploading...\")\n await upload_track(required_track, event)\n shutil.rmtree(temp_dl_path)\n await event.delete()\n\n elif \"album\" in required_link:\n reqd_albums = loader.download_albumdee(\n required_link,\n output=temp_dl_path,\n quality=required_qty,\n recursive_quality=True,\n recursive_download=True,\n not_interface=True,\n zips=False,\n )\n for required_track in reqd_albums:\n await upload_track(required_track, event)\n shutil.rmtree(temp_dl_path)\n await event.delete()\n\n else:\n await event.edit(strings[\"wrong_cmd_syntax\"])","def do_download(ftp):\n # Active (PORT), Passive (PASV), ExtActive (EPRT), or ExtPassive (EPSV)?\n output, sock, transfer_type = get_transfer_output_and_socket(ftp)\n print_debug(output + \"\\n\")\n\n # What file to download?\n path = raw_input(\"What file do you want to download?\\n> \")\n while not path:\n path = raw_input(\"What file do you want to download?\\n> \")\n try:\n msg_rec, data_rec = ftp.retr_cmd(sock, path, transfer_type)\n print_debug(str(msg_rec))\n except Exception as e:\n print(\"An error has occurred: \" + str(e) + \"\\nPlease try again.\")\n return main_menu(ftp)\n\n # Download file.\n if data_rec:\n print_debug(str(data_rec))\n try:\n write_to_local(path, data_rec)\n except Exception as e:\n print(\"An error has occurred: \" + str(e) + \"\\nPlease try again.\")\n return main_menu(ftp)\n main_menu(ftp)","def download_data():\n url = 'https://www.dropbox.com/s/h9ubx22ftdkyvd5/ml-latest-small.zip?dl=1'\n urllib.request.urlretrieve(url, 'ml-latest-small.zip')\n zfile = zipfile.ZipFile('ml-latest-small.zip')\n zfile.extractall()\n zfile.close()","def download(self, *path, **kwargs):\n extract = kwargs.get(\"extract\", True)\n callback = kwargs.get(\"callback\", None)\n info = self.serverfiles.info(*path)\n\n extract = extract and \"compression\" in info\n target = self.localpath(*path)\n self.serverfiles.download(*path,\n target=target + \".tmp\" if extract else target,\n callback=callback)\n\n _save_file_info(target + '.info', info)\n\n if extract:\n if info.get(\"compression\") in [\"tar.gz\", \"tar.bz2\"]:\n f = tarfile.open(target + \".tmp\")\n try:\n os.mkdir(target)\n except OSError:\n pass\n f.extractall(target)\n elif info.get(\"compression\") == \"gz\":\n f = gzip.open(target + \".tmp\")\n shutil.copyfileobj(f, open(target, \"wb\"))\n elif info.get(\"compression\") == \"bz2\":\n f = bz2.BZ2File(target + \".tmp\", \"r\")\n shutil.copyfileobj(f, open(target, \"wb\"))\n f.close()\n os.remove(target + \".tmp\")","def fetch_files():\n props = util.get_properties()\n # get atmosfn\n atmosfn = \"%s/rwis.txt\" % (INCOMING, )\n try:\n ftp = ftplib.FTP('165.206.203.34')\n except TimeoutError as _exp:\n print(\"process_rwis FTP Server Timeout\")\n sys.exit()\n ftp.login('rwis', props['rwis_ftp_password'])\n ftp.retrbinary('RETR ExpApAirData.txt', open(atmosfn, 'wb').write)\n # Insert into LDM\n pqstr = \"plot ac %s rwis.txt raw/rwis/%sat.txt txt\" % (GTS, GTS)\n subprocess.call((\"/home/ldm/bin/pqinsert -i -p '%s' %s \"\n \"\") % (pqstr, atmosfn), shell=True)\n\n # get sfcfn\n sfcfn = \"%s/rwis_sf.txt\" % (INCOMING, )\n ftp.retrbinary('RETR ExpSfData.txt', open(sfcfn, 'wb').write)\n ftp.close()\n # Insert into LDM\n pqstr = \"plot ac %s rwis_sf.txt raw/rwis/%ssf.txt txt\" % (GTS, GTS)\n subprocess.call((\"/home/ldm/bin/pqinsert -i -p '%s' %s \"\n \"\") % (pqstr, sfcfn), shell=True)\n\n return atmosfn, sfcfn","def download_file():\r\n global title_dict\r\n title=ResultsListbox.get(ResultsListbox.curselection())\r\n link=title_dict[title]\r\n file_dl=urllib.URLopener()\r\n file_dl.retrieve(link,str(title)+\".pdf\")","def __init__(self, subtitle=None):\n self.subtitle = subtitle\n if not self.subtitle:\n self.parse_subtitles()","def load_mytransit_archived_feeds(timestamp=datetime.datetime(2017, 1, 1, 12, 0)):\n import requests\n\n ts = timestamp\n uri = \"http://data.mytransit.nyc.s3.amazonaws.com/subway_time/{0}/{0}-{1}/subway_time_{2}.tar.xz\".format(\n ts.year, str(ts.month).rjust(2, '0'), str(ts.year) + str(ts.month).rjust(2, '0') + str(ts.day).rjust(2, '0')\n )\n # filename_date_format = str(datetime.datetime.strftime(datetime.datetime(2016, 1, 1), \"%Y%m%dT%H%MZ\"))\n\n # The tar module does not seem to support reading virtual files via io.BytesIO, we have to go to disc.\n temp_filename = \"temp.tar.xz\"\n with open(temp_filename, \"wb\") as f:\n f.write(requests.get(uri).content)\n\n archive = tarfile.open(temp_filename, 'r')\n messages = [archive.extractfile(f) for f in archive.getmembers()]\n os.remove(temp_filename)\n\n return messages","def track_04():\n sonos.play_uri('http://stream.sunshine-live.de/live/mp3-192', title='Sunshine Live', force_radio=True)\n return \"Ok\"","def download_archive(self):\n\n def time_convert(structure):\n \"\"\"\n :param structure: tuple representation of time\n :return: GitHub archive time\n \"\"\"\n \n \n join_number_to_zero = lambda number: (\"\" if number > 9 else \"0\") + str(number)\n\n return \"%s-%s-%s-%s\" % (\n structure.tm_year, join_number_to_zero(structure.tm_mon), join_number_to_zero(structure.tm_mday),\n structure.tm_hour)\n\n current_time = self.get_time()\n self.logger.debug(__name__ + \": \" + \"current time: \" + str(gmtime(current_time)))\n\n difference = -25200\n #timezone difference in seconds between GMT and west coast of USA\n\n downloading_time = int(timegm(self.config[\"last_connection_time\"])) + 3600\n self.logger.debug(__name__ + \": \" + \"downloading time: \" + str(gmtime(downloading_time)))\n\n if downloading_time > current_time - 7200:\n self.logger.info(__name__ + \": \" + \"unable to download file (time limiting).\")\n return\n\n downloading_time += difference\n\n json_file_name = self.download_file(time_convert(gmtime(downloading_time)))\n\n self.config[\"last_connection_time\"] = gmtime(downloading_time - difference)\n self.logger.debug(__name__ + \": \" + \"last_connection_time: \" + str(self.config[\"last_connection_time\"]))\n\n return json_file_name","def download(self):\r\n \r\n # RAR Files names\r\n if self.debug==0:\r\n rar_files_name = [\"K001.rar\",\"K002.rar\",\"K003.rar\",\"K004.rar\",\"K005.rar\",\"K006.rar\",\r\n \"KA01.rar\", \"KA03.rar\", \"KA04.rar\", \"KA05.rar\", \"KA06.rar\", \"KA07.rar\", \r\n \"KA08.rar\", \"KA09.rar\", \"KA15.rar\", \"KA16.rar\", \"KA22.rar\", \"KA30.rar\", \r\n \"KB23.rar\", \"KB24.rar\", \"KB27.rar\", \r\n \"KI01.rar\", \"KI03.rar\", \"KI04.rar\", \"KI05.rar\", \"KI07.rar\", \"KI08.rar\", \r\n \"KI14.rar\", \"KI16.rar\", \"KI17.rar\", \"KI18.rar\", \"KI21.rar\"]\r\n else:\r\n rar_files_name = [\"K002.rar\", \"KA01.rar\", \"KI01.rar\"]\r\n\r\n url = self.url\r\n \r\n dirname = self.rawfilesdir\r\n dir_rar = \"rar_files\"\r\n if not os.path.isdir(dirname):\r\n os.mkdir(dirname)\r\n if not os.path.isdir(os.path.join(dirname, dir_rar)):\r\n os.mkdir(os.path.join(dirname, dir_rar))\r\n \r\n\r\n print(\"Downloading RAR files:\")\r\n for i in rar_files_name:\r\n file_name = i\r\n if not os.path.exists(os.path.join(dirname, dir_rar, file_name)):\r\n urllib.request.urlretrieve(url+file_name, os.path.join(dirname, dir_rar, file_name))\r\n print(file_name)\r\n \r\n print(\"Extracting files:\")\r\n for i in rar_files_name:\r\n if not os.path.exists(os.path.join(dirname, i[:4])):\r\n file_name = os.path.join(dirname, dir_rar, i)\r\n Archive(file_name).extractall(dirname) \r\n print(i)\r\n\r\n if self.debug==0:\r\n files_path = self.files\r\n else:\r\n files_path = files_debug(self.rawfilesdir)\r\n\r\n print(files_path)\r\n self.files = files_path","def retrieve_tla(extension, username=None, password=None, pagelimit=999999):\n\n if extension != 'eaf':\n print(\"currently, only eaf downloads are supported for TLA\")\n return\n TLA_LIMIT = 5000 #there are currently 35k ELAN files in TLA\n #base_url = \"\"\"https://archive.mpi.nl/tla/islandora/search/*%3A*?f[0]=cmd.Format%3A\"%s\"&f[1]=-cmd.Country%3A\"Netherlands\"&f[2]=-cmd.Country%3A\"Belgium\"&f[3]=-cmd.Country%3A\"Germany\"&limit=%i\"\"\"%(mimetype, TLA_LIMIT)\n #https://archive.mpi.nl/tla/islandora/search/%2A%3A%2A?page=2&f%5B0%5D=cmd.Format%3A%22text/x-eaf%2Bxml%22&islandora_solr_search_navigation=0&sort=fgs_label_s%20asc&limit=500\n login_url = \"https://archive.mpi.nl/tla/user/login\"\n if username and password:\n pass\n else:\n username = input(\"Enter user name for TLA: \\n\")\n password = getpass(\n \"Your password will only be used for this login session and not be stored anywhere.\\n Enter password for TLA: \\n\"\n )\n with requests.Session() as s:\n #login\n print(\"retrieving collections\")\n s = requests.Session()\n un_name = \"name\"\n pw_name = \"pass\"\n values = {\n un_name: username.strip(),\n pw_name: password,\n \"op\": \"Log+in\",\n \"form_id\": \"user_login\",\n }\n s.post(login_url, data=values)\n session_id = s.cookies.get_dict().get(\"SESSd8112b76bc7d4802dc104c36df341519\")\n print(session_id)\n #get pages quantity\n collection_urls = []\n tla_mime = \"text/x-eaf%2Bxml\"\n country_restrictors = \"f%5B1%5D=-cmd.Country%3A%22Netherlands%22&f%5B2%5D=-cmd.Country%3A%22Belgium%22&f%5B3%5D=-cmd.Country%3A%22Germany%22&\"\n resultpages = [\"https://archive.mpi.nl/tla/islandora/search/%%2A%%3A%%2A?page=%i&f%%5B0%%5D=cmd.Format%%3A%%22%s%%22&%slimit=%i\"%(i, tla_mime, country_restrictors, TLA_LIMIT) for i in range(5)]\n #retrieve collections from resultpages\n for resultpage in resultpages[:pagelimit]:\n print(resultpage)\n #base_request = s.get(resultpage)\n #base_html = base_request.text\n #base_root = fromstring(base_html)\n base_root = url2root(s, resultpage)\n collection_links = base_root.findall('.//dd[@class=\"solr-value cmd-title\"]/a')\n new_collection_urls = [\n \"https://archive.mpi.nl/%s\" % a.attrib[\"href\"] for a in collection_links\n ]\n print(len(new_collection_urls), \"new urls\")\n collection_urls += new_collection_urls\n collection_length = len(collection_urls)\n print(len(collection_urls), \"collections\")\n OFFSET = 0\n #OFFSET = 3390\n #retrieve file links from collections\n for i, c_url in enumerate(collection_urls[OFFSET:]):\n #print(\"collection \", c_url)\n collection_id = c_url.split(\"%3A\")[-1]\n print(collection_id, \"%i(+%i)/%i\"%(i+1, OFFSET, collection_length))\n #c_request = s.get(c_url)\n #c_html = c_request.text\n #c_root = fromstring(c_html)\n c_root = url2root(s, c_url)\n file_links = c_root.findall('.//a[@class=\"flat-compound-caption-link\"]')\n file_tuples = [\n (a.attrib[\"href\"],\n a.text,\n a.getparent().getparent().find('div[@class=\"flat-compound-buttons\"]/div[@class=\"permission-labels\"]').find('span').text)\n for a in file_links\n if a.text is not None\n and a.text.endswith(extension)\n ]\n #download files\n for file_tuple in file_tuples:\n # print(\" f: \", file_tuple)\n f_url, filename, access = file_tuple\n tla_eaf_id = f_url.split('/')[-1]\n local_basename = '.'.join((tla_eaf_id, extension))\n if access.strip() == 'Restricted':\n print(' %s: no access' % f_url)\n else:\n download_url = \"https://archive.mpi.nl/%s/datastream/OBJ/download\" % f_url\n filepath = os.path.join('tla', collection_id, local_basename)\n print(\" downloading %s as %s:\" % (download_url, filepath))\n os.makedirs(os.path.dirname(filepath), exist_ok=True)\n save_file(s, filepath, download_url, {\"SESSd8112b76bc7d4802dc104c36df341519\": session_id})","def connect(self):\n self.conn = self.protocol(self.url.host, 'anonymous', '', timeout=self.timeout)\n self.conn.voidcmd('TYPE I')\n self.conn.cwd(self.url.path)\n self.conn.voidcmd('PASV')\n file_size = self.conn.size(self.url.filename)\n return TaskHeadData(self.url.host, 200, file_size) # set the code 200 for compatibility with HTTP","def dascasi_download():\n p = argparse.ArgumentParser(description=\"download DASC all-sky camera data\")\n p.add_argument(\"site\", choices=[\"EAA\", \"FYU\", \"KAK\", \"PKR\", \"TOO\", \"VEE\"])\n p.add_argument(\n \"startend\", help=\"start/end times UTC e.g. 2012-11-03T06:23 2012-11-03T07\", nargs=2\n )\n p.add_argument(\"odir\", help=\"directory to write downloaded FITS to\")\n p.add_argument(\"-w\", \"--wavelen\", help=\"request specific wavelength(s)\", nargs=\"+\")\n p.add_argument(\"-host\", default=\"ftp://optics.gi.alaska.edu\")\n p = p.parse_args()\n\n # host = \"ftp://mirrors.arsc.edu/AMISR/PKR/DASC/RAW/\"\n download(p.startend, p.site, p.odir, p.host, p.wavelen)"],"string":"[\n \"def download(self):\\n if not os.path.isdir(self.save_path):\\n try:\\n os.mkdir(self.save_path)\\n except IOError:\\n print(\\\"Can't create subfolder. \\\"\\n \\\"Check that you have write access for \\\"\\n \\\"{}\\\".format(self.save_path))\\n\\n sub_zip_file = request.urlopen(self.download_link)\\n sub_gzip = gzip.GzipFile(fileobj=StringIO(sub_zip_file.read()))\\n subtitle_content = sub_gzip.read()\\n try:\\n with open(self.full_path, 'wb') as subtitle_output:\\n subtitle_output.write(subtitle_content)\\n print(\\\"Downloaded subtitle...\\\")\\n except IOError:\\n print(\\\"Couldn't save subtitle, permissions issue?\\\")\",\n \"def download_subtitle_zip(self, dict_entry_to_download):\\n\\trequest_subtitle_list = \\\"http://napisy24.pl/download/%s/\\\" % str(self.return_xml_dict_entry_value(dict_entry_to_download,'id'))\\n\\trepeat = 3\\n\\twhile repeat > 0: \\n repeat = repeat - 1\\n\\t #request_subtitle_list = \\\"/libs/webapi.php?title=%s\\\" % self.MovieName\\n\\t r1_status = self.__connect_with_server(request_subtitle_list, \\\"download_subtilte_zip\\\") \\n if r1_status != 302:\\n print \\\"Fetching subtitle failed, HTTP code: %s\\\" % (str(r1_status))\\n time.sleep(0.5)\\n continue\\n else:\\n repeat = 0\\n \\n if self.zip_string == None:\\n print \\\"Subtitle NOT DOWNLOADED\\\"\\n repeat = 0\\n continue\\n\\n if self.zip_string is None or self.zip_string == \\\"\\\":\\n print \\\"Subtitle NOT DOWNLOADED\\\"\\n continue\\n \\n if self.zip_string[0:2] == 'PK':\\n\\t print \\\"Success to download subtitle zip.\\\"\\n return True\\n else:\\n\\t print \\\"Reild to download subtitle zip.\\\"\\n return False\",\n \"def download_data(self, format = 'srt'):\\n \\n def to_ascii(data):\\n \\\"\\\"\\\"\\n Remove non-ascii characters\\n \\\"\\\"\\\"\\n return ''.join([x for x in data if ord(x) < 128])\\n \\n url = self.config.subtitles['url'] % (self.media_resource_id)\\n \\n print url\\n resp, content = httplib2.Http(\\\".cache\\\").request(url, \\\"GET\\\")\\n \\n subtitles = json.loads(content)['subtitles']\\n \\n final_data = ''\\n if format == 'srt':\\n final_data += self.to_srt(subtitles)\\n else:\\n final_data += subtitles\\n \\n return to_ascii(final_data)\",\n \"def download(self, language, filename, filetype):\\n if language not in self.languages.keys():\\n print \\\"Theres's no subtitle in this language\\\"\\n sys.exit()\\n url = \\\"http://www.youtube.com/api/timedtext?v={0}&lang={1}\\\".format(self.video_id, language)\\n self.subtitle = urllib2.urlopen(url)\\n if filetype == \\\"srt\\\":\\n self.writeSRTFile(filename)\\n else:\\n self.writeXMLFile(filename)\",\n \"def download_subtitle(search, results, filename, min_match=0,\\n force=0, debug=0):\\n s = Subseek()\\n subtitleurl = False\\n for result in s.order_match(search, results):\\n match_text = s.clean_text(s.clean_html(result['text']),False,\\n s.detect_encoding(s.clean_html(result['text']))\\n ) + \\\" \\\" + s.clean_text(s.clean_html(result['description']),False,\\n s.detect_encoding(s.clean_html(result['description'])))\\n subtitleurl = result['link']\\n rating_weight = s.text_weight(search, match_text)\\n max_weight = s.text_weight(search)\\n rating_match = rating_weight/max_weight*100\\n if debug == 1:\\n print \\\"Subtitle File URL: \\\" + subtitleurl\\n print \\\" Text To Search: \\\" + search\\n print \\\" Text To Match: \\\" + match_text\\n print \\\" Text Match (%): \\\" + str(round(rating_match,2)) + \\\"%\\\"\\n # check minimal match to use\\n if rating_match >= min_match:\\n downloaded = s.download(subtitleurl, filename + '.tmp')\\n if downloaded == False:\\n if debug == 1:\\n print \\\"Error: connection or file creation failed\\\"\\n subtitleurl = False\\n else:\\n if debug == 1:\\n print \\\"File downloaded\\\"\\n # unrar, unzip or get srt file\\n typefile = s.get_sub_file_from_file(filename + '.tmp',\\n search, force)\\n if typefile == False:\\n if debug == 1:\\n print \\\"Subtitle file not found\\\"\\n subtitleurl = False\\n else:\\n if debug == 1:\\n print \\\"Subtitle file found in \\\" + typefile\\n subtitleurl = True\\n break\\n else:\\n if debug == 1:\\n print \\\"Error: match less than \\\" + str(round(min_match,2))+ \\\"%\\\"\\n subtitleurl = False\\n break\\n\\n return subtitleurl\",\n \"def play_video(path):\\r\\n #logger.info(\\\"######: {}, log: {}########\\\".format('rk8', path))\\r\\n #original=https://api.hotstar.com/h/v1/play?contentId=1000238814\\r\\n #path=\\\"https://api.hotstar.com/h/v2/play/in/contents/1000238814\\\"\\r\\n # Create a playable item with a path to play.\\r\\n data = make_request(path)\\r\\n #logger.info(\\\"######: {}, log: {}########\\\".format('rk3', path))\\r\\n if not data:\\r\\n return\\r\\n\\r\\n def get_subtitle(url):\\r\\n #\\r\\n # https://hses.akamaized.net/videos/hotstarint/hostages/1260003409/1558430241469/\\r\\n # 265b9dab22d4e9a033e6df6f89639f17/master.m3u8?hdnea=st=1560107863~exp=1560111463~acl=\\r\\n # /*~hmac=2f6fb393159ed5fa1b12bbf12e954eb377cfa0fc852d4ff5eb24446233237620\\r\\n #\\r\\n # https://hses.akamaized.net/videos/hotstarint/hostages/1260003409/1558430241469/\\r\\n # 5d0f83c3ccbf4501cf952bdfc8c0d785/subtitle/lang_en/sub-0.vtt\\r\\n #\\r\\n _url = urlparse(url)\\r\\n values = _url._asdict()\\r\\n values['query'] = ''\\r\\n values['path'] = '{}/subtitle/lang_en/sub-0.vtt'.format(\\\"/\\\".join(values['path'].split('/')[:-1]))\\r\\n\\r\\n subtitle_url = ParseResult(**values).geturl()\\r\\n # subtitle_file = kodiutils.download_url_content_to_temp(subtitle_url, '{}-{}.srt'.format(\\r\\n # Zee5Plugin.safe_string(item['title']),\\r\\n # subtitle_lang,\\r\\n # ))\\r\\n\\r\\n return subtitle_url\\r\\n\\r\\n #logger.info(\\\"######: {}, log: {}########\\\".format('rk6', data))\\r\\n #item = data['body']['results']['item']\\r\\n item=data['body']['results']['playBackSets'][0]\\r\\n path = item['playbackUrl']\\r\\n licenseURL = item.get('licenseUrl')\\r\\n subtitle = get_subtitle(path)\\r\\n\\r\\n logger.info('Playing video URL: {}, licenseURL: {}, subtitle: {}'.format(path, licenseURL, subtitle))\\r\\n\\r\\n play_item = xbmcgui.ListItem(path=path)\\r\\n if licenseURL:\\r\\n play_item.setProperty('inputstreamaddon', 'inputstream.adaptive')\\r\\n play_item.setProperty('inputstream.adaptive.manifest_type', 'hls')\\r\\n play_item.setMimeType('application/dash+xml')\\r\\n play_item.setContentLookup(False)\\r\\n\\r\\n play_item.setSubtitles([get_subtitle(path)])\\r\\n\\r\\n # Pass the item to the Kodi player.\\r\\n xbmcplugin.setResolvedUrl(_handle, True, listitem=play_item)\",\n \"def download(self, filename = None, format = 'srt', append = False):\\n \\n data = self.download_data(format)\\n \\n if filename != None:\\n extension = '' if filename.lower().endswith('.srt') else '.srt'\\n \\n sys.stdout.write('Saving subtitle...\\\\n')\\n \\n out_dir = self.config.subtitles['out']\\n if os.path.isfile(out_dir):\\n raise OSError('Video output directory is not a directory, but is a file')\\n elif not os.path.isdir(out_dir):\\n os.mkdir(out_dir)\\n \\n mod = 'a' if append else 'w'\\n f = open(out_dir + os.path.sep + filename + extension, mod)\\n f.write(data)\\n f.close()\\n \\n return data\",\n \"def main():\\n parser = argparse.ArgumentParser()\\n parser.add_argument('source_path', help=\\\"Path to the video or audio file to subtitle\\\",\\n nargs='?')\\n parser.add_argument('-C', '--concurrency', help=\\\"Number of concurrent API requests to make\\\",\\n type=int, default=DEFAULT_CONCURRENCY)\\n parser.add_argument('-o', '--output',\\n help=\\\"Output path for subtitles (by default, subtitles are saved in \\\\\\n the same directory and name as the source path)\\\")\\n parser.add_argument('-F', '--format', help=\\\"Destination subtitle format\\\",\\n default=DEFAULT_SUBTITLE_FORMAT)\\n parser.add_argument('-S', '--src-language', help=\\\"Language spoken in source file\\\",\\n default=DEFAULT_SRC_LANGUAGE)\\n parser.add_argument('-D', '--dst-language', help=\\\"Desired language for the subtitles\\\",\\n default=DEFAULT_DST_LANGUAGE)\\n parser.add_argument('-K', '--api-key',\\n help=\\\"The Google Translate API key to be used. \\\\\\n (Required for subtitle translation)\\\")\\n parser.add_argument('--list-formats', help=\\\"List all available subtitle formats\\\",\\n action='store_true')\\n parser.add_argument('--list-languages', help=\\\"List all available source/destination languages\\\",\\n action='store_true')\\n\\n parser.add_argument('--min_height', help=\\\"minimum height from 0 - 100%\\\", type=float, default=93)\\n\\n parser.add_argument('--max_height', help=\\\"maximum height from 0 - 100%\\\", type=float, default=99)\\n\\n parser.add_argument('--l_v', help=\\\"Light sensitive\\\", type=float, default=210)\\n\\n parser.add_argument('--debug', help=\\\"Allows to show cropped image on the desktop\\\", action='store_true', default=True)\\n\\n parser.add_argument('--cloud', help=\\\"Use google cloud compute to extract text\\\", action='store_true', default=False)\\n\\n parser.add_argument('--disable_time', help=\\\"Parse time function\\\", action='store_true')\\n\\n parser.add_argument('--all', help=\\\"Render all files\\\", action='store_true')\\n\\n args = parser.parse_args()\\n\\n if args.list_formats:\\n print(\\\"List of formats:\\\")\\n for subtitle_format in FORMATTERS:\\n print(\\\"{format}\\\".format(format=subtitle_format))\\n return 0\\n\\n if args.list_languages:\\n print(\\\"List of all languages:\\\")\\n for code, language in sorted(LANGUAGE_CODES.items()):\\n print(\\\"{code}\\\\t{language}\\\".format(code=code, language=language))\\n return 0\\n\\n if not validate(args):\\n return 1\\n\\n try:\\n if args.all:\\n for file in os.listdir():\\n # *.avi *.flv *.mkv *.mpg *.mp4 *.webm\\n if file.endswith('.avi') or file.endswith('.flv') or file.endswith('.mkv') or file.endswith('.mpg') or file.endswith('.mp4') or file.endswith(\\\".webm\\\"):\\n st = time.time()\\n subtitle_file_path = generate_subtitles(\\n source_path=file,\\n dst_language=args.dst_language,\\n output=args.output,\\n debug=args.debug,\\n cloud=args.cloud,\\n disable_time=args.disable_time,\\n min_height=args.min_height,\\n max_height=args.max_height,\\n l_v=args.l_v,\\n )\\n print(\\\"Subtitles file created at {} time consumer: {}\\\".format(subtitle_file_path, time.time() - st))\\n else:\\n st = time.time()\\n subtitle_file_path = generate_subtitles(\\n source_path=args.source_path,\\n dst_language=args.dst_language,\\n output=args.output,\\n debug=args.debug,\\n cloud=args.cloud,\\n disable_time=args.disable_time,\\n min_height=args.min_height,\\n max_height=args.max_height,\\n l_v=args.l_v,\\n )\\n print(\\\"Subtitles file created at {} time consumer: {}\\\".format(subtitle_file_path, time.time() - st))\\n except KeyboardInterrupt:\\n return 1\\n\\n return 0\",\n \"def podcast_download(self):\\r\\n warnings.filterwarnings(\\\"ignore\\\", category=UnicodeWarning)\\r\\n now = datetime.datetime.now()\\r\\n\\r\\n for podcast_file in self.podcast_list:\\r\\n published, name, link, title = podcast_file\\r\\n if self.podcast_list != []:\\r\\n line_file = (published + ';' + title + ';' + name + ';' + link).encode(\\\"utf-8\\\") \\r\\n if line_file in open(self.download_log).read():\\r\\n pass\\r\\n else:\\r\\n title = unicodedata.normalize('NFKD', title).encode('ascii', 'ignore')\\r\\n download_folder = os.path.join('downloads', title)\\r\\n if not os.path.exists(download_folder): \\r\\n os.makedirs(download_folder)\\r\\n try:\\r\\n published = str(parser.parse(published))[:10]\\r\\n except IOError as error:\\r\\n print 'Error' + (error) + ': File - ' + str(title)\\r\\n download_folder = os.path.join(download_folder, published)\\r\\n if not os.path.exists(download_folder): \\r\\n os.makedirs(download_folder)\\r\\n namefile_unicode = link[link.rfind('/')+1:]\\r\\n namefile_str = unicodedata.normalize('NFKD', \\r\\n namefile_unicode).encode('ascii', 'ignore')\\r\\n namefile_str = namefile_str.decode('utf-8', 'ignore').encode(\\\"utf-8\\\")\\r\\n if '.mp3' in namefile_str:\\r\\n len_name = namefile_str.index('.mp3')\\r\\n elif '.MP3' in namefile_str:\\r\\n len_name = namefile_str.index('.MP3')\\r\\n namefile_str = namefile_str[:len_name + 4]\\r\\n fileoutput = os.path.join(download_folder, namefile_str)\\r\\n name = unicodedata.normalize('NFKD', name).encode('ascii', 'ignore')\\r\\n print str(published) + '; ' + name\\r\\n ## downlink\\r\\n download_file(link, fileoutput) \\r\\n ## tagging\\r\\n mp3_tagging(fileoutput, podcast_file)\\r\\n ## write log\\r\\n write_file(self.download_log, line_file)\\r\\n end = datetime.datetime.now()\\r\\n print '\\\\r' + 'Download Time = ' + str(end-now) + '\\\\r'\\r\\n return None\",\n \"def get_subtitleinfo(fileFullName):\\n sys.stdout.write(\\\"Requesting subtitle info...\\\\n\\\")\\n\\n #接口获取字幕信息\\n response = requests.post(\\n \\\"https://www.shooter.cn/api/subapi.php\\\",\\n verify=False,\\n params= {\\n 'filehash': ComputeFileHash(fileFullName),\\n 'pathinfo': os.path.realpath(fileFullName),\\n 'format': 'json',\\n 'lang': \\\"Chn\\\",\\n },\\n )\\n #未找到字幕处理\\n if response.text == u'\\\\xff':\\n sys.stderr.write(\\\"Subtitle not found.\\\\n\\\")\\n sys.exit(1)\\n return response\",\n \"def link_subtitles_to_files(self):\\n target_filenames = self.get_target_filenames()\\n subtitle_filenames = []\\n\\n zip_filenames = self.subtitle_zip_files_dir.glob('*.zip')\\n for zip_fn in zip_filenames:\\n subtitle_filenames.extend(self.unzip_subtitles(zip_fn))\\n\\n subtitle_metadata = self.cache_file_metadata(subtitle_filenames)\\n target_metadata = self.cache_file_metadata(target_filenames)\\n\\n for target_file_metadata_summary in target_metadata:\\n try:\\n source_filename = f'{subtitle_metadata[target_file_metadata_summary][\\\"fn\\\"]}.srt'\\n target_filename = f'{target_metadata[target_file_metadata_summary][\\\"fn\\\"]}.srt'\\n source_filepath = pathlib.PurePath(self.temp_storage_dir, source_filename)\\n target_filepath = pathlib.PurePath(self.target_dir, target_filename)\\n shutil.move(source_filepath, target_filepath)\\n print(f'Subtitle for \\\\'{target_file_metadata_summary}\\\\' successfully linked.')\\n except KeyError:\\n logging.warning(f'Subtitle for \\\\'{target_file_metadata_summary}\\\\' not found!')\\n\\n self.clean_temp_storage_dir(subtitle_filenames)\",\n \"def download_subtitles(video_ids):\\n print(f\\\"[downloading subs] {video_ids}\\\")\\n ydl_opts = {\\n 'skip_download': True,\\n 'writeautomaticsub': True,\\n 'outtmpl': 'subtitles/%(id)s',\\n 'subtitleslangs': ['en']\\n }\\n for video_id in video_ids:\\n filename = f\\\"subtitles/{video_id}.en.vtt\\\"\\n # Don't download if these subtitles are already downloaded\\n # or if we know there are no subtitles on the video\\n if video_id in cached_no_subtitles:\\n continue\\n if not os.path.isfile(filename):\\n print(f\\\"[downloading subtitle] {video_id}\\\")\\n with youtube_dl.YoutubeDL(ydl_opts) as ydl:\\n # assume downloaded subtitle is correct\\n ydl.download([video_id])\\n # Delay to be nice to the server\\n time.sleep(2)\\n try:\\n with open(filename) as f:\\n yield video_id, f.read()\\n except IOError:\\n with open(CACHED_NO_SUBTITLES_FILE, \\\"a\\\") as f:\\n f.write(video_id + '\\\\n')\\n cached_no_subtitles.add(video_id)\\n yield video_id, None\",\n \"def downloadDfxpTranscript(self, SubsLink):\\n try:\\n subRequestObject = requests.get(SubsLink)\\n # print(subRequestObject.text)\\n subRequestObject.encoding = 'utf-8'\\n\\n subsFileHandler = open(self.title + \\\".dfxp\\\", \\\"w\\\")\\n print(\\\"Creating ~ '%s.dfxp' ...\\\" % (self.title))\\n subsFileHandler.write(subRequestObject.text)\\n subsFileHandler.close()\\n return 1\\n\\n except:\\n return 0\\n\\n pass\",\n \"def download_subtitle(self, film, ttmname, srtname, filename):\\n self.logger.debug('download_subtitle')\\n ret = False\\n if film.url_sub:\\n progress = KodiProgressDialog()\\n progress.create(30978, filename + u'.ttml')\\n # pylint: disable=broad-except\\n try:\\n progress.update(0)\\n mvutils.url_retrieve_vfs(\\n film.url_sub, ttmname, progress.url_retrieve_hook)\\n try:\\n ttml2srtConverter = ttml2srt()\\n ttml2srtConverter.do(xbmcvfs.File(ttmname, 'r'),\\n xbmcvfs.File(srtname, 'w'))\\n ret = True\\n except Exception as err:\\n self.logger.error('Failed to convert to srt: {}', err)\\n progress.close()\\n except Exception as err:\\n progress.close()\\n self.logger.error(\\n 'Failure downloading {}: {}', film.url_sub, err)\\n return ret\",\n \"def transcribeAll(service, url, fileName):\\n if(service == \\\"omny.fm\\\"):\\n url = url.replace(\\\".mp3\\\",\\\"\\\") + \\\".mp3\\\"\\n subprocess.Popen(\\\"wget -c -O ./podcasts/\\\" + fileName + \\\".mp3 \\\" + url + \\\" && sleep 40 && ffmpeg -i ./podcasts/\\\"\\n + fileName + \\\".mp3 -acodec pcm_s16le -ac 1 -ar 8000 ./podcasts/\\\" + fileName + \\\".wav && sleep 10 && rm ./podcasts/\\\" \\n + fileName + \\\".mp3 && nohup ./online2-wav-nnet3-latgen-faster --online=false --do-endpointing=false \\\"\\n + \\\"--frame-subsampling-factor=3 --config=online.conf --max-mem=2000000000 --max-active=7000 --beam=15.0 --lattice-beam=6.0 \\\"\\n + \\\"--acoustic-scale=1.0 --word-symbol-table=words.txt final.mdl HCLG.fst 'ark:echo utterance-id\\\" + fileName \\n + \\\" utterance-id\\\" + fileName + \\\"|' 'scp:echo utterance-id\\\" + fileName + \\\" ./podcasts/\\\" + fileName + \\\".wav|' 'ark:/dev/null' &\\\", shell=True)\",\n \"def test_get_subtitles(self):\\n\\n (subtitles, start, end) = self.sp.get_subtitles(INDEX)\\n self.assertEqual(subtitles, INDEX_SUBTITLES, 'Check get_subtitles.')\",\n \"def download_data():\\n\\n if not os.path.exists(zipfile_path):\\n print(f'Downloading {config.download_url} to {zipfile_path}')\\n urlretrieve(config.download_url, zipfile_path)\\n print(f'Successfully downloaded {zipfile_path}')\\n\\n zip_ref = ZipFile(zipfile_path, 'r')\\n zip_ref.extractall(config.raw_data_dir)\\n zip_ref.close()\\n\\n os.rename(f\\\"{config.raw_data_dir}/cornell movie-dialogs corpus\\\", extracted_dir)\",\n \"def download(self, filename, info_dict, subtitle=False):\\n nooverwrites_and_exists = (\\n not self.params.get('overwrites', True)\\n and os.path.exists(encodeFilename(filename))\\n )\\n\\n if not hasattr(filename, 'write'):\\n continuedl_and_exists = (\\n self.params.get('continuedl', True)\\n and os.path.isfile(encodeFilename(filename))\\n and not self.params.get('nopart', False)\\n )\\n\\n # Check file already present\\n if filename != '-' and (nooverwrites_and_exists or continuedl_and_exists):\\n self.report_file_already_downloaded(filename)\\n self._hook_progress({\\n 'filename': filename,\\n 'status': 'finished',\\n 'total_bytes': os.path.getsize(encodeFilename(filename)),\\n }, info_dict)\\n self._finish_multiline_status()\\n return True, False\\n\\n if subtitle:\\n sleep_interval = self.params.get('sleep_interval_subtitles') or 0\\n else:\\n min_sleep_interval = self.params.get('sleep_interval') or 0\\n sleep_interval = random.uniform(\\n min_sleep_interval, self.params.get('max_sleep_interval') or min_sleep_interval)\\n if sleep_interval > 0:\\n self.to_screen(f'[download] Sleeping {sleep_interval:.2f} seconds ...')\\n time.sleep(sleep_interval)\\n\\n ret = self.real_download(filename, info_dict)\\n self._finish_multiline_status()\\n return ret, True\",\n \"def main():\\n\\n # Parse arguments\\n parser = OptionParser()\\n parser.add_option('-n', '--subscription_key', dest='subscription_key',\\n help='subscription_key for authentication')\\n parser.add_option('-t', '--text', dest='text',\\n help='text to synthesize')\\n parser.add_option('-l', '--language', dest='language',\\n help='language')\\n parser.add_option('-g', '--gender', dest='gender',\\n help='gender')\\n parser.add_option('-d', '--directory', dest='directory',\\n help='directory to store the file')\\n (options, args) = parser.parse_args()\\n subscription_key = options.subscription_key\\n text = options.text\\n language = options.language\\n gender = options.gender\\n directory = options.directory\\n\\n # Perform sanity checks on options\\n validate_options(subscription_key, text)\\n\\n if not directory:\\n directory = default_directory\\n\\n if not language:\\n language = default_language\\n\\n if not gender:\\n gender = default_gender\\n\\n # format = 'riff-16khz-16bit-mono-pcm'\\n format = 'riff-8khz-8bit-mono-mulaw'\\n\\n # lang = 'en-AU'\\n # gender = 'Female'\\n tts_msspeak = MSSpeak(subscription_key, '/tmp/')\\n tts_msspeak.set_cache(False)\\n output_filename = tts_msspeak.speak(text, language, gender, format)\\n\\n print 'Recorded TTS to %s%s' % (directory, output_filename)\",\n \"def download_text_command():\\n # 1. Get input scan id from Demisto\\n scanid = demisto.args().get('scanid')\\n # 2. Get the forensic webpage text from SlashNext API\\n response = download_text(scanid=scanid)\\n if response.get('errorNo') != 0:\\n return\\n # 3. Parse and format the response\\n text_base64 = response.get('textData').get('textBase64')\\n text_data = base64.b64decode(text_base64)\\n\\n text_file = fileResult('slashnext_{}.txt'.format(scanid), text_data, entryTypes['file'])\\n\\n demisto.results({\\n 'Type': entryTypes['file'],\\n 'ContentsFormat': formats['text'],\\n 'Contents': 'Forensics: Webpage Rendered Text for URL Scan ID = {}'.format(scanid),\\n 'File': text_file.get('File'),\\n 'FileID': text_file.get('FileID')\\n })\",\n \"def demonstrate():\\n\\n api = authenticate()\\n\\n # Demonstrate upload feature.\\n # Create a list of one or more file paths of the mp3s you would like \\n # to upload\\n filepaths = []\\n filepaths.append('./song1.mp3')\\n\\n # Upload an mp3 to your library. upload() returns a tuple of information\\n # about the success or failure of uploads\\n print(\\\"Beginning upload...\\\\n\\\")\\n uploaded = api.upload(filepaths) \\n\\n # Print all successfully uploaded songs\\n if len(uploaded[0]) > 0:\\n print(\\\"Successfully uploaded:\\\")\\n i = 1\\n for key in uploaded[0]:\\n print(\\\"%d. %s\\\" % (i, key))\\n i += 1\\n\\n # Print all unsuccessfully uploaded songs and a description of why\\n # songs weren't uploaded\\n if len(uploaded[2]) == 0:\\n print(\\\"\\\\nAll songs successfully uploaded.\\\")\\n else:\\n print(\\\"Not all songs were successfully uploaded:\\\")\\n i = 1\\n for key in uploaded[2]:\\n print(\\\"%d. %s not uploaded: %s\\\" % (i, key, uploaded[2][key]))\\n i += 1\\n\\n\\n # Demonstrate download feature\\n # Get information about songs previously uploaded that are available\\n # to be downloaded\\n uploaded_songs = api.get_uploaded_songs()\\n\\n if len(uploaded_songs) == 0:\\n print(\\\"There are no songs currently available for download\\\")\\n else:\\n # Print songs that are available for download and store their ids\\n # so we can download them\\n song_ids = []\\n print(\\\"\\\\nThe following songs are available for download\\\")\\n for i in range(len(uploaded_songs)):\\n song_ids.append(uploaded_songs[i]['id'])\\n print(\\\"%d. %s\\\" % (i+1, uploaded_songs[i]['title']))\\n\\n # Download uploaded songs from your library\\n print(\\\"\\\\nBeginning download...\\\")\\n for i in range(len(song_ids)):\\n filename, audio = api.download_song(song_ids[i])\\n\\n # Write song to disk\\n with open(filename, 'wb') as f:\\n f.write(audio)\\n\\n print(\\\"%d. Written to ./%s\\\" % (i + 1, filename))\\n print(\\\"\\\\nDownload complete.\\\")\\n\\n # It's good practice to logout when finished\\n api.logout()\",\n \"def get_subtitles(self, title):\\n return library.subtitles.get_subtitle_url(title)\",\n \"def best_subtitle_url(search, full_search, path_file_name,\\n min_match=0, force=0, deep=0, debug=0):\\n # first search in subtitle search engines\\n links = subtitle_search_engines_links(search, deep, debug)\\n subtitle_url = download_best_subtitle(links,\\n full_search,\\n path_file_name,\\n min_match, force, debug)\\n # if not found use the external search engines\\n if not subtitle_url:\\n links = external_search_engines_links(search, deep, debug)\\n subtitle_url = download_best_subtitle(links,\\n full_search,\\n path_file_name,\\n min_match, force, debug)\\n\\n return subtitle_url\",\n \"def unzip_subtitles(self, zip_filepath):\\n with ZipFile(zip_filepath, 'r') as zip_obj:\\n filenames = zip_obj.namelist()\\n\\n subtitle_filenames = [fn for fn in filenames if fn.endswith('.srt')]\\n for fn in subtitle_filenames:\\n zip_obj.extract(fn, self.temp_storage_dir)\\n\\n return subtitle_filenames\",\n \"def download_video(url, fn):\\n start_time = time.time()\\n\\n # Sorry: This is terrible code, but I'm kind of throwing it\\n # together as I discover more about it.\\n print ' Downloading {0} to {1}'.format(url, fn)\\n\\n resp = requests.get(url)\\n if resp.status_code != 200:\\n print ' GAH! MY EYES! {0} kicked up {1}'.format(url, resp.status_code)\\n return\\n\\n rss_url_m = re.search(r'\\\"(/rss/flash/\\\\d+)\\\"', resp.content)\\n rss_url = 'http://blip.tv' + rss_url_m.group(0).strip('\\\"')\\n resp = requests.get(rss_url)\\n\\n rss_content = resp.content\\n\\n for ending in POSSIBLE_ENDINGS:\\n regex = r'\\\"http://blip.tv[^\\\"]+?' + ending + '\\\"'\\n\\n download_m = re.search(regex, rss_content)\\n if not download_m:\\n print ' No {0} url found'.format(ending)\\n continue\\n\\n download_url = download_m.group(0).strip('\\\"')\\n print ' Attempting to download {0}'.format(download_url)\\n\\n try:\\n resp = requests.get(download_url, stream=True)\\n print ' Downloading {0}'.format(download_url)\\n if resp.status_code == 200:\\n total_length = int(resp.headers['content-length'])\\n\\n if os.path.exists(fn + ending) and file_size(fn + ending) == total_length:\\n print ' Already downloaded.'\\n return\\n\\n with open(fn + ending, 'w') as fp:\\n total_downloaded = 0\\n\\n tic_chunk = total_downloaded\\n tic = time.time()\\n for chunk in resp.iter_content(chunk_size=1024):\\n if chunk:\\n fp.write(chunk)\\n fp.flush()\\n tic_chunk += len(chunk)\\n total_downloaded += len(chunk)\\n\\n if time.time() - tic > 1:\\n with TERM.location(x=0):\\n line = ' {0} {1}kbps'.format(\\n format_downloaded(total_downloaded, total_length),\\n int(tic_chunk / (time.time() - tic) / 1000))\\n sys.stdout.write(line + TERM.clear_eol)\\n sys.stdout.flush()\\n tic_chunk = 0\\n tic = time.time()\\n print ''\\n\\n print ' Done! {0} {1}mb {2}'.format(\\n fn + ending,\\n int(total_length / 1000000.0),\\n format_duration(time.time() - start_time))\\n return\\n\\n else:\\n print ' HTTP{0}! GAH! SPUTTER!'.format(resp.status_code)\\n\\n except requests.exceptions.ConnectionError as exc:\\n print ' CONNECTIONERROR! GAH! SPUTTER! {0}'.format(exc)\\n\\n print ' SO MANY FAILURES!'\\n raise NoDownloadMeNoLikeyException()\",\n \"def download():\\r\\n\\tglobal server\\r\\n\\tfolder = str(get_folder())\\r\\n\\tfilename = str(get_filename())\\r\\n\\tprint(folder)\\r\\n\\r\\n\\t# on crée le chemin absolue\\r\\n\\tpath = \\\"partage/\\\"+folder +\\\"/\\\"+filename\\r\\n\\tprint(path)\\r\\n\\tdata = [\\\"download\\\", path]\\r\\n\\t#on dump la liste\\r\\n\\tdata = pickle.dumps(data)\\r\\n\\tserver.send(data)\\r\\n\\r\\n\\tcontent = server.recv(2**30) # Reception du conenue du fichier\\r\\n\\r\\n\\tif content == b\\\"unknown\\\":\\r\\n\\t\\tprint(\\\"Fichier inéxistant\\\")\\r\\n\\telse:\\r\\n\\t\\twith open(filename, \\\"wb\\\") as f: # Creation d'un fichier similaire\\r\\n\\t\\t\\tprint(content)\\r\\n\\t\\t\\tf.write(content)\\r\\n\\t\\t\\tf.close()\",\n \"def download_song(song):\\n ydl.download([song])\\n print(\\\"Finished downloading and converting: \\\" + song)\",\n \"def download_transcripts(request):\\r\\n locator = request.GET.get('locator')\\r\\n if not locator:\\r\\n log.debug('GET data without \\\"locator\\\" property.')\\r\\n raise Http404\\r\\n\\r\\n try:\\r\\n item = _get_item(request, request.GET)\\r\\n except (InvalidKeyError, ItemNotFoundError):\\r\\n log.debug(\\\"Can't find item by locator.\\\")\\r\\n raise Http404\\r\\n\\r\\n subs_id = request.GET.get('subs_id')\\r\\n if not subs_id:\\r\\n log.debug('GET data without \\\"subs_id\\\" property.')\\r\\n raise Http404\\r\\n\\r\\n if item.category != 'video':\\r\\n log.debug('transcripts are supported only for video\\\" modules.')\\r\\n raise Http404\\r\\n\\r\\n filename = 'subs_{0}.srt.sjson'.format(subs_id)\\r\\n content_location = StaticContent.compute_location(item.location.course_key, filename)\\r\\n try:\\r\\n sjson_transcripts = contentstore().find(content_location)\\r\\n log.debug(\\\"Downloading subs for %s id\\\", subs_id)\\r\\n str_subs = generate_srt_from_sjson(json.loads(sjson_transcripts.data), speed=1.0)\\r\\n if not str_subs:\\r\\n log.debug('generate_srt_from_sjson produces no subtitles')\\r\\n raise Http404\\r\\n response = HttpResponse(str_subs, content_type='application/x-subrip')\\r\\n response['Content-Disposition'] = 'attachment; filename=\\\"{0}.srt\\\"'.format(subs_id)\\r\\n return response\\r\\n except NotFoundError:\\r\\n log.debug(\\\"Can't find content in storage for %s subs\\\", subs_id)\\r\\n raise Http404\",\n \"def download_data():\\n url = 'https://www.dropbox.com/s/8oehplrobcgi9cq/imdb.tgz?dl=1'\\n urllib.request.urlretrieve(url, 'imdb.tgz')\\n tar = tarfile.open(\\\"imdb.tgz\\\")\\n tar.extractall()\\n tar.close()\",\n \"def download_best_subtitle(links, full_search, path_file_name,\\n min_match=0, force=0, debug=0):\\n s = Subseek()\\n if not links or len(links) == 0:\\n return False\\n else:\\n results = []\\n for link in links:\\n if debug == 1:\\n print \\\"Searching in \\\" + link['link']\\n for provider in SUBTITLE_PROVIDERS:\\n results_aux = s.get_subtitles_links(link['link'],\\n provider)\\n if results_aux is False or len(results_aux) == 0:\\n if debug == 1:\\n print \\\"No subtitles with '%s'\\\" % provider['name']\\n else:\\n if debug == 1:\\n print \\\"%s subtitles with '%s'\\\" % (len(results_aux),\\n provider['name'])\\n results = results + results_aux\\n # download the best subtitle of the entire list\\n return download_subtitle(full_search,\\n results,\\n path_file_name,\\n min_match,\\n force,\\n debug)\",\n \"def main():\\n port = 8080\\n ipaddr = my_ip.lookup()\\n player = sonos.Player()\\n\\n music_dir = \\\"mp3s\\\"\\n # Move to the mp3 directory to serve files from it.\\n try:\\n os.chdir(music_dir)\\n except OSError, ex:\\n print \\\"Couldn't chdir to %s directory: %s\\\" % (music_dir, ex)\\n sys.exit(1)\\n\\n webserver = localwebserver.HttpServer(port)\\n webserver.start()\\n\\n uri = \\\"http://%s:%s/\\\" % (ipaddr, port)\\n\\n print \\\"Serving MP3s at %s.\\\" % uri\\n\\n sniffer = Sniffer(uri, player)\\n sniffer.run_forever()\",\n \"def cli(date, path, mission):\\n download.main(path, mission, date)\",\n \"def download_youtube_subs(youtube_subs, item, settings):\\r\\n i18n = item.runtime.service(item, \\\"i18n\\\")\\r\\n _ = i18n.ugettext\\r\\n\\r\\n highest_speed = highest_speed_subs = None\\r\\n missed_speeds = []\\r\\n # Iterate from lowest to highest speed and try to do download transcripts\\r\\n # from the Youtube service.\\r\\n for speed, youtube_id in sorted(youtube_subs.iteritems()):\\r\\n if not youtube_id:\\r\\n continue\\r\\n try:\\r\\n subs = get_transcripts_from_youtube(youtube_id, settings, i18n)\\r\\n if not subs: # if empty subs are returned\\r\\n raise GetTranscriptsFromYouTubeException\\r\\n except GetTranscriptsFromYouTubeException:\\r\\n missed_speeds.append(speed)\\r\\n continue\\r\\n\\r\\n save_subs_to_store(subs, youtube_id, item)\\r\\n\\r\\n log.info(\\r\\n \\\"Transcripts for YouTube id %s (speed %s)\\\"\\r\\n \\\"are downloaded and saved.\\\", youtube_id, speed\\r\\n )\\r\\n\\r\\n highest_speed = speed\\r\\n highest_speed_subs = subs\\r\\n\\r\\n if not highest_speed:\\r\\n raise GetTranscriptsFromYouTubeException(_(\\\"Can't find any transcripts on the Youtube service.\\\"))\\r\\n\\r\\n # When we exit from the previous loop, `highest_speed` and `highest_speed_subs`\\r\\n # are the transcripts data for the highest speed available on the\\r\\n # Youtube service. We use the highest speed as main speed for the\\r\\n # generation other transcripts, cause during calculation timestamps\\r\\n # for lower speeds we just use multiplication instead of division.\\r\\n for speed in missed_speeds: # Generate transcripts for missed speeds.\\r\\n save_subs_to_store(\\r\\n generate_subs(speed, highest_speed, highest_speed_subs),\\r\\n youtube_subs[speed],\\r\\n item\\r\\n )\\r\\n\\r\\n log.info(\\r\\n \\\"Transcripts for YouTube id %s (speed %s)\\\"\\r\\n \\\"are generated from YouTube id %s (speed %s) and saved\\\",\\r\\n youtube_subs[speed], speed,\\r\\n youtube_subs[highest_speed],\\r\\n highest_speed\\r\\n )\",\n \"def download_data():\\n url = 'https://www.dropbox.com/s/xk4glpk61q3qrg2/imdb.tgz?dl=1'\\n urllib.request.urlretrieve(url, 'imdb.tgz')\\n tar = tarfile.open(\\\"imdb.tgz\\\")\\n tar.extractall()\\n tar.close()\",\n \"def edx_get_subtitle(url, headers):\\n \\\"\\\"\\\" or None if no subtitles are available \\\"\\\"\\\"\\n try:\\n jsonString = get_page_contents(url, headers)\\n jsonObject = json.loads(jsonString)\\n return edx_json2srt(jsonObject)\\n except URLError as e:\\n print('[warning] edX subtitles (error:%s)' % e.reason)\\n return None\\n except ValueError as e:\\n print('[warning] edX subtitles (error:%s)' % e.message)\\n return None\",\n \"def read_subtitles(self):\\n\\n # Group 1: index, Group 2: Start Time, Group 3: End Time, Group 4: Text\\n\\n patterns = [\\n r\\\"(\\\\d+)\\\\n(\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d) --> (\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d)\\\\n((?:.+\\\\n)*.+)\\\",\\n r\\\"(\\\\d+)\\\\r\\\\n(\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d) --> (\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d)\\\\r\\\\n((?:.+\\\\r\\\\n)*.+)\\\",\\n # Reports pattern\\n r\\\"(\\\\d+)\\\\r(\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d) --> (\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d)\\\\n((?:.+\\\\r)*.+)\\\"\\n ]\\n\\n for pattern in patterns:\\n re_subs = re.findall(pattern, self.subtitles, re.M | re.I)\\n if(len(re_subs) > 1):\\n self.re_subs = re_subs\\n return\\n\\n raise Exception(\\n f're_subs length is {len(re_subs)}. Maybe the regex pattern is falty?')\",\n \"def play_movie_with_subs(self, filmid):\\n self.logger.debug('play_movie_with_subs')\\n start = time.time()\\n #\\n film = self.database.retrieve_film_info(filmid)\\n if film is None:\\n self.logger.error(\\\"no film for download \\\" + self.plugin.language(30991))\\n self.notifier.show_error(30990, self.plugin.language(30991))\\n return\\n ttmname = os.path.join(self.settings.getDatapath(), 'subtitle.ttml')\\n srtname = os.path.join(self.settings.getDatapath(), 'subtitle.srt')\\n subs = []\\n if self.download_subtitle(film, ttmname, srtname, 'subtitle'):\\n subs.append(srtname)\\n # (_, listitem) = FilmUI(self.plugin).get_list_item(None, film)\\n (_, listitem) = FilmlistUi(self.plugin)._generateListItem(film)\\n self.logger.debug('SUBTITLE FOUND {} from url {}' , subs, film.url_sub)\\n if listitem:\\n if subs:\\n listitem.setSubtitles(subs)\\n self.plugin.set_resolved_url(True, listitem)\\n self.logger.debug('play_movie_with_subs processed: {} sec', time.time() - start)\",\n \"def download(connection, priv_key, server_pub_key):\\r\\n\\r\\n # Get the filename from the user\\r\\n file_name = input('What file would you like to download from the server?: ')\\r\\n\\r\\n # Tell the server to prepare to download a file\\r\\n connection.sendall(rsa.encrypt(b'DOWNLOAD', server_pub_key))\\r\\n\\r\\n # Send the file name to the server\\r\\n connection.sendall(rsa.encrypt(file_name.encode(), server_pub_key))\\r\\n\\r\\n # Attempt to download the file\\r\\n try:\\r\\n shared.download_file(connection, priv_key, file_name)\\r\\n\\r\\n # If the server can't find the file that is asked for\\r\\n except ValueError:\\r\\n print(''.join(['\\\\nThe file does not exist']), file=sys.stderr)\",\n \"def __init__(self, subtitle_zip_files_dir, target_dir, temp_storage_dir):\\n self._video_formats = ('avi', 'mp4', 'mov', 'mkv', 'mk3d', 'webm', \\\\\\n 'ts', 'mts', 'm2ts', 'ps', 'vob', 'evo', 'mpeg', 'mpg', \\\\\\n 'm1v', 'm2p', 'm2v', 'm4v', 'movhd', 'movx', 'qt', \\\\\\n 'mxf', 'ogg', 'ogm', 'ogv', 'rm', 'rmvb', 'flv', 'swf', \\\\\\n 'asf', 'wm', 'wmv', 'wmx', 'divx', 'x264', 'xvid')\\n\\n self.subtitle_zip_files_dir = pathlib.Path(subtitle_zip_files_dir)\\n self.target_dir = pathlib.Path(target_dir)\\n self.temp_storage_dir = pathlib.Path(temp_storage_dir)\",\n \"def dowload_vt():\\n print get_date_time_now() + \\\" ==> Download VT Samples started!\\\"\\n print get_date_time_now() + \\\" ==> Nothing downloaded\\\"\",\n \"def start(self):\\n if not path.exists(self.dir):\\n mkdir(self.dir)\\n\\n try:\\n yt = YouTube(self.link)\\n ys = yt.streams\\n if self.aud == True:\\n ysf = ys.get_audio_only()\\n elif self.aud == False:\\n ysf = ys.get_by_resolution(resolution=self.res)\\n ysf.download(self.dir)\\n except AttributeError:\\n raise Exception(f\\\"Resolution [{self.res}] is not available for this video\\\")\\n except excep.RegexMatchError:\\n raise Exception(\\\"Invalid link!\\\")\\n except excep.VideoPrivate:\\n raise Exception(\\\"This video is private! Try with a public one\\\")\\n except excep.PytubeError:\\n raise Exception(\\\"Error occured!\\\")\\n except excep.VideoPrivate:\\n raise Exception(\\\"This video is private! Try with a public one\\\")\\n except excep.VideoUnavailable:\\n raise Exception(\\\"This video is unvailable!\\\")\\n except excep.ExtractError:\\n raise Exception(\\\"Error in extractiong the video!\\\")\\n except Exception:\\n raise Exception(\\\"Error occured. Make sure of your connection ;)\\\")\",\n \"def download(dltype, num):\\n # This function needs refactoring!\\n # pylint: disable=R0912\\n # pylint: disable=R0914\\n if g.browse_mode == \\\"ytpl\\\" and dltype in (\\\"da\\\", \\\"dv\\\"):\\n plid = g.ytpls[int(num) - 1][\\\"link\\\"]\\n down_plist(dltype, plid)\\n return\\n\\n elif g.browse_mode == \\\"ytpl\\\":\\n g.message = \\\"Use da or dv to specify audio / video playlist download\\\"\\n g.message = c.y + g.message + c.w\\n g.content = generate_songlist_display()\\n return\\n\\n elif g.browse_mode != \\\"normal\\\":\\n g.message = \\\"Download must refer to a specific video item\\\"\\n g.message = c.y + g.message + c.w\\n g.content = generate_songlist_display()\\n return\\n\\n writestatus(\\\"Fetching video info...\\\")\\n song = (g.model.songs[int(num) - 1])\\n best = dltype.startswith(\\\"dv\\\") or dltype.startswith(\\\"da\\\")\\n\\n if not best:\\n\\n try:\\n # user prompt for download stream\\n url, ext, url_au, ext_au = prompt_dl(song)\\n\\n except KeyboardInterrupt:\\n g.message = c.r + \\\"Download aborted!\\\" + c.w\\n g.content = generate_songlist_display()\\n return\\n\\n if not url or ext_au == \\\"abort\\\":\\n # abort on invalid stream selection\\n g.content = generate_songlist_display()\\n g.message = \\\"%sNo download selected / invalid input%s\\\" % (c.y, c.w)\\n return\\n\\n else:\\n # download user selected stream(s)\\n filename = _make_fname(song, ext)\\n args = (song, filename, url)\\n\\n if url_au and ext_au:\\n # downloading video and audio stream for muxing\\n audio = False\\n filename_au = _make_fname(song, ext_au)\\n args_au = (song, filename_au, url_au)\\n\\n else:\\n audio = ext in (\\\"m4a\\\", \\\"ogg\\\")\\n\\n kwargs = dict(audio=audio)\\n\\n elif best:\\n # set updownload without prompt\\n url_au = None\\n av = \\\"audio\\\" if dltype.startswith(\\\"da\\\") else \\\"video\\\"\\n audio = av == \\\"audio\\\"\\n filename = _make_fname(song, None, av=av)\\n args = (song, filename)\\n kwargs = dict(url=None, audio=audio)\\n\\n try:\\n # perform download(s)\\n dl_filenames = [args[1]]\\n f = _download(*args, **kwargs)\\n if f:\\n g.message = \\\"Saved to \\\" + c.g + f + c.w\\n\\n if url_au:\\n dl_filenames += [args_au[1]]\\n _download(*args_au, allow_transcode=False, **kwargs)\\n\\n except KeyboardInterrupt:\\n g.message = c.r + \\\"Download halted!\\\" + c.w\\n\\n try:\\n for downloaded in dl_filenames:\\n os.remove(downloaded)\\n\\n except IOError:\\n pass\\n\\n if url_au:\\n # multiplex\\n mux_cmd = \\\"APP -i VIDEO -i AUDIO -c copy OUTPUT\\\".split()\\n mux_cmd = \\\"%s -i %s -i %s -c copy %s\\\"\\n mux_cmd = [g.muxapp, \\\"-i\\\", args[1], \\\"-i\\\", args_au[1], \\\"-c\\\",\\n \\\"copy\\\", args[1][:-3] + \\\"mp4\\\"]\\n\\n try:\\n subprocess.call(mux_cmd)\\n g.message = \\\"Saved to :\\\" + c.g + mux_cmd[7] + c.w\\n os.remove(args[1])\\n os.remove(args_au[1])\\n\\n except KeyboardInterrupt:\\n g.message = \\\"Audio/Video multiplex aborted!\\\"\\n\\n g.content = generate_songlist_display()\",\n \"async def download_video(v_url):\\n reply = await v_url.get_reply_message()\\n if v_url.pattern_match.group(2) != \\\"\\\":\\n url = v_url.pattern_match.group(2)\\n elif reply is not None:\\n url = reply.message\\n url = re.findall(r\\\"\\\\bhttps?://.*\\\\.\\\\S+\\\", reply.message)[0]\\n else:\\n return\\n type = (\\n v_url.pattern_match.group(1).lower()\\n if v_url.pattern_match.group(1) is not None\\n else \\\"a\\\"\\n )\\n await v_url.edit(\\\"`Preparing to download...`\\\")\\n out_folder = Config.TMP_DOWNLOAD_DIRECTORY + \\\"youtubedl/\\\"\\n Config.TMP_DOWNLOAD_DIRECTORY + \\\"/thumb_image.jpg\\\"\\n if not os.path.isdir(out_folder):\\n os.makedirs(out_folder)\\n if type == \\\"a\\\":\\n opts = {\\n \\\"format\\\": \\\"bestaudio\\\",\\n \\\"addmetadata\\\": True,\\n \\\"noplaylist\\\": False,\\n \\\"key\\\": \\\"FFmpegMetadata\\\",\\n \\\"writethumbnail\\\": True,\\n \\\"embedthumbnail\\\": True,\\n \\\"prefer_ffmpeg\\\": True,\\n \\\"geo_bypass\\\": True,\\n \\\"nocheckcertificate\\\": True,\\n \\\"postprocessors\\\": [\\n {\\n \\\"key\\\": \\\"FFmpegExtractAudio\\\",\\n \\\"preferredcodec\\\": \\\"mp3\\\",\\n \\\"preferredquality\\\": \\\"320\\\",\\n }\\n ],\\n \\\"outtmpl\\\": out_folder + \\\"%(title)s.%(ext)s\\\",\\n \\\"quiet\\\": True,\\n \\\"logtostderr\\\": False,\\n }\\n video = False\\n song = True\\n\\n elif type == \\\"v\\\":\\n opts = {\\n \\\"format\\\": \\\"best\\\",\\n \\\"addmetadata\\\": True,\\n \\\"noplaylist\\\": False,\\n \\\"getthumbnail\\\": True,\\n \\\"embedthumbnail\\\": True,\\n \\\"xattrs\\\": True,\\n \\\"writethumbnail\\\": True,\\n \\\"key\\\": \\\"FFmpegMetadata\\\",\\n \\\"prefer_ffmpeg\\\": True,\\n \\\"geo_bypass\\\": True,\\n \\\"nocheckcertificate\\\": True,\\n \\\"postprocessors\\\": [\\n {\\\"key\\\": \\\"FFmpegVideoConvertor\\\", \\\"preferedformat\\\": \\\"mp4\\\"},\\n ],\\n \\\"outtmpl\\\": out_folder + \\\"%(title)s.%(ext)s\\\",\\n \\\"logtostderr\\\": False,\\n \\\"quiet\\\": True,\\n }\\n song = False\\n video = True\\n\\n try:\\n await v_url.edit(\\\"`Fetching playlist data, please wait..`\\\")\\n with YoutubeDL(opts) as ytdl:\\n ytdl.extract_info(url)\\n # print(ytdl_data['thumbnail'])\\n filename = sorted(get_lst_of_files(out_folder, []))\\n except DownloadError as DE:\\n await v_url.edit(f\\\"`{str(DE)}`\\\")\\n return\\n except ContentTooShortError:\\n await v_url.edit(\\\"`The download content was too short.`\\\")\\n return\\n except GeoRestrictedError:\\n await v_url.edit(\\n \\\"`Video is not available from your geographic location due to geographic restrictions imposed by a website.`\\\"\\n )\\n return\\n except MaxDownloadsReached:\\n await v_url.edit(\\\"`Max-downloads limit has been reached.`\\\")\\n return\\n except PostProcessingError:\\n await v_url.edit(\\\"`There was an error during post processing.`\\\")\\n return\\n except UnavailableVideoError:\\n await v_url.edit(\\\"`Media is not available in the requested format.`\\\")\\n return\\n except XAttrMetadataError as XAME:\\n await v_url.edit(f\\\"`{XAME.code}: {XAME.msg}\\\\n{XAME.reason}`\\\")\\n return\\n except ExtractorError:\\n await v_url.edit(\\\"`There was an error during info extraction.`\\\")\\n return\\n except Exception as e:\\n await v_url.edit(f\\\"{str(type(e)): {str(e)}}\\\")\\n return\\n c_time = time.time()\\n await v_url.edit(\\\"`YouTube Playlist Downloading Processing Now.\\\\nPlease Wait!`\\\")\\n if song:\\n for single_file in filename:\\n if os.path.exists(single_file):\\n caption_rts = os.path.basename(single_file)\\n force_document = True\\n supports_streaming = False\\n document_attributes = []\\n if single_file.endswith((\\\".mp4\\\", \\\".mp3\\\", \\\".flac\\\", \\\".webm\\\")):\\n metadata = extractMetadata(createParser(single_file))\\n duration = 0\\n width = 0\\n height = 180\\n if metadata.has(\\\"duration\\\"):\\n duration = metadata.get(\\\"duration\\\").seconds\\n document_attributes = [\\n DocumentAttributeVideo(\\n duration=duration,\\n w=width,\\n h=height,\\n round_message=False,\\n supports_streaming=True,\\n )\\n ]\\n try:\\n ytdl_data_name_audio = os.path.basename(single_file)\\n thumb = (\\n out_folder\\n + ytdl_data_name_audio[: (len(ytdl_data_name_audio) - 4)]\\n + \\\".jpg\\\"\\n )\\n print(ytdl_data_name_audio)\\n file_path = single_file\\n song_size = file_size(file_path)\\n await v_url.client.send_file(\\n v_url.chat_id,\\n single_file,\\n caption=f\\\"`{ytdl_data_name_audio}`\\\"\\n + \\\"\\\\n\\\"\\n + f\\\"Size👉 {song_size}\\\",\\n force_document=force_document,\\n supports_streaming=supports_streaming,\\n allow_cache=False,\\n thumb=thumb,\\n reply_to=v_url.message.id,\\n attributes=document_attributes,\\n progress_callback=lambda d, t: asyncio.get_event_loop().create_task(\\n progress(\\n d,\\n t,\\n v_url,\\n c_time,\\n \\\"Uploading..\\\",\\n f\\\"{ytdl_data_name_audio}\\\",\\n )\\n ),\\n )\\n # os.remove(thumb)\\n except Exception as e:\\n await v_url.client.send_message(\\n v_url.chat_id,\\n \\\"{} caused `{}`\\\".format(caption_rts, str(e)),\\n )\\n continue\\n os.remove(single_file)\\n await asyncio.sleep(DELETE_TIMEOUT)\\n # await v_url.delete()\\n shutil.rmtree(out_folder)\\n if video:\\n for single_file in filename:\\n if os.path.exists(single_file):\\n caption_rts = os.path.basename(single_file)\\n force_document = False\\n supports_streaming = True\\n document_attributes = []\\n if single_file.endswith((\\\".mp4\\\", \\\".mp3\\\", \\\".flac\\\", \\\".webm\\\")):\\n metadata = extractMetadata(createParser(single_file))\\n duration = 0\\n width = 0\\n height = 0\\n if metadata.has(\\\"duration\\\"):\\n duration = metadata.get(\\\"duration\\\").seconds\\n document_attributes = [\\n DocumentAttributeVideo(\\n duration=duration,\\n w=width,\\n h=height,\\n round_message=False,\\n supports_streaming=True,\\n )\\n ]\\n # print(ytdl_data)\\n # for file in os.listdir(\\\"./DOWNLOADS/youtubedl/\\\"):\\n # if file.endswith(\\\".jpg\\\"):\\n # thumb = \\\"./DOWNLOADS/youtubedl/\\\" + file\\n # print(os.path.join(\\\"./DOWNLOADS/youtubedl/\\\", file))\\n # image_link = ytdl_data['thumbnail']\\n # downloaded_image = wget.download(image_link,out_folder)\\n # thumb = ytdl_data_name_video + \\\".jpg\\\"\\n file_path = single_file\\n video_size = file_size(file_path)\\n try:\\n ytdl_data_name_video = os.path.basename(single_file)\\n thumb = (\\n out_folder\\n + ytdl_data_name_video[: (len(ytdl_data_name_video) - 4)]\\n + \\\".jpg\\\"\\n )\\n await v_url.client.send_file(\\n v_url.chat_id,\\n single_file,\\n caption=f\\\"`{ytdl_data_name_video}`\\\"\\n + \\\"\\\\n\\\"\\n + f\\\"Size👉 {video_size}\\\",\\n force_document=force_document,\\n supports_streaming=supports_streaming,\\n thumb=thumb,\\n allow_cache=False,\\n reply_to=v_url.message.id,\\n attributes=document_attributes,\\n progress_callback=lambda d, t: asyncio.get_event_loop().create_task(\\n progress(\\n d,\\n t,\\n v_url,\\n c_time,\\n \\\"Uploading..\\\",\\n f\\\"{ytdl_data_name_video}\\\",\\n )\\n ),\\n )\\n # os.remove(thumb)\\n except Exception as e:\\n await v_url.client.send_message(\\n v_url.chat_id,\\n \\\"{} caused `{}`\\\".format(caption_rts, str(e)),\\n )\\n continue\\n os.remove(single_file)\\n await asyncio.sleep(DELETE_TIMEOUT)\\n # await v_url.delete()\\n shutil.rmtree(out_folder)\",\n \"def do_downloads(filename1=\\\"og\\\", filename2=\\\"lyrical\\\", video_id=DEFALT_VIDEO_ID):\\n original_video_url = youtube_id_to_url(video_id)\\n download_from_url(original_video_url, filename1)\\n lyrics_video_url = get_lyrics_url(original_video_url)\\n download_from_url(lyrics_video_url, filename2)\\n\\n return filename1, filename2\",\n \"def download_cdn_videos(filenames,sub_urls,handout_urls,video_urls, target_dir):\\n \\\"\\\"\\\" using a simple file downloader \\\"\\\"\\\"\\n for i, v in enumerate(video_urls):\\n filename_prefix = str(i+1).zfill(2) + '-'\\n #original_filename = v.rsplit('/', 1)[1]\\n video_filename = filename_prefix + filenames[i] + '.mp4'\\n sub_filename = filename_prefix + filenames[i] + '.srt'\\n handout_filename = filename_prefix + filenames[i] + '.srt'\\n video_path = os.path.join(target_dir, video_filename)\\n sub_path = os.path.join(target_dir, sub_filename)\\n handout_path = os.path.join(target_dir, handout_filename)\\n #print('[debug] GET %s' % v)\\n print('[download] Destination: %s' % video_path)\\n v = quote(v,safe=\\\":/\\\")\\n if len(v) != YOUTUBE_VIDEO_ID_LENGTH:\\n req = Request(v) \\n try:\\n video = urlopen(v)\\n fileSize = int(video.headers['content-length'])\\n finish = False\\n existSize = 0\\n if os.path.exists(video_path):\\n output = open(video_path,\\\"ab\\\")\\n existSize = os.path.getsize(video_path)\\n #If the file exists, then only download the remainder\\n if existSize < fileSize:\\n #print(\\\"[debug] bytes range is: %s-%s\\\" % (existSize,fileSize))\\n req.headers[\\\"Range\\\"]= \\\"bytes=%s-%s\\\" % (existSize,fileSize)\\n video = urlopen(req)\\n else:\\n finish = True\\n else:\\n output = open(video_path,\\\"wb\\\")\\n if finish == False:\\n file_size_dl = existSize\\n block_sz = 262144\\n while True:\\n buffer = video.read(block_sz)\\n if not buffer:\\n break\\n \\n file_size_dl += len(buffer)\\n output.write(buffer)\\n status = r\\\"%10d [%3.2f%%]\\\" % (file_size_dl, file_size_dl * 100. / fileSize)\\n status = status + chr(8)*(len(status)+1)\\n sys.stdout.write(status)\\n sys.stdout.flush()\\n \\n output.close()\\n\\n except URLError as e:\\n print(\\\"[warning]error: %r when downloading %s\\\" % (e.reason,v) )\\n\\n else:\\n download_youtube_video(v,video_path)\\n \\n if sub_urls[i] != \\\"\\\":\\n #print('[debug] GET %s' % BASE_URL+sub_urls[i])\\n if not os.path.exists(sub_path):\\n subs_string = edx_get_subtitle(sub_urls[i], headers)\\n if subs_string:\\n print('[info] Writing edX subtitles: %s' % sub_path)\\n open(os.path.join(os.getcwd(), sub_path),\\n 'wb+').write(subs_string.encode('utf-8'))\\n\\n if handout_urls[i] != \\\"\\\":\\n #print('[debug] GET %s' % BASE_URL+sub_urls[i])\\n if not os.path.exists(handout_path):\\n handout_content = urlopen(BASE_URL+handout_urls[i]).read()\\n if handout_content:\\n print('[info] Writing handout: %s' % handout_path)\\n open(os.path.join(os.getcwd(), handout_path),\\n 'wb+').write(handout_content)\\n #srtfile = urlopen(BASE_URL+sub_urls[i])\\n #output = open(srt_path,'wb')\\n #output.write(srtfile.read())\\n #output.close()\",\n \"def main():\\n\\tif not len(sys.argv) in (3, 4):\\n\\t\\tprint \\\"usage: nowplaying \\\\\\\"Interpreter\\\\\\\" \\\\\\\"Title\\\\\\\" [\\\\\\\"link\\\\\\\"]\\\"\\n\\t\\tsys.exit(1)\\n\\tinterpreter = sys.argv[1]\\n\\ttitle = sys.argv[2]\\n\\tif len(sys.argv) == 4:\\n\\t\\tlink = sys.argv[3]\\n\\telse:\\n\\t\\tlink = None\\n\\t\\n\\tclient = NowPlayingClient(APIKEY)\\n\\tret = client.sendTrack(interpreter, title, link)\\n\\tif ret == \\\"Done.\\\\n\\\":\\n\\t\\tsys.exit(0)\\n\\telse:\\n\\t\\t# some debugging\\n\\t\\tprint \\\"ERROR!\\\\nServer response below:\\\\n\\\\n--BEGIN SERVER RESPONSE--\\\"\\n\\t\\tprint ret\\n\\t\\tprint \\\"--END SERVER RESPONSE--\\\"\\n\\t\\tsys.exit(1)\",\n \"async def download_audio(event):\\n url = event.pattern_match.group(1)\\n rmsg = await event.get_reply_message()\\n if not url and rmsg:\\n myString = rmsg.text\\n url = re.search(\\\"(?P<url>https?://[^\\\\s]+)\\\", myString).group(\\\"url\\\")\\n if not url:\\n return await edit_or_reply(event, \\\"`What I am Supposed to find? Give link`\\\")\\n codevent = await edit_or_reply(event, \\\"`Preparing to download...`\\\")\\n reply_to_id = await reply_id(event)\\n ytdl_data = await ytdl_down(codevent, audio_opts, url)\\n if ytdl_data is None:\\n return\\n await codevent.edit(\\n f\\\"`Preparing to upload song:`\\\\\\n \\\\n**{ytdl_data['title']}**\\\\\\n \\\\nby *{ytdl_data['uploader']}*\\\"\\n )\\n f = pathlib.Path(f\\\"{ytdl_data['title']}.mp3\\\".replace(\\\"|\\\", \\\"_\\\"))\\n codthumb = pathlib.Path(f\\\"{ytdl_data['title']}.mp3.jpg\\\".replace(\\\"|\\\", \\\"_\\\"))\\n if not os.path.exists(codthumb):\\n codthumb = pathlib.Path(f\\\"{ytdl_data['title']}.mp3.webp\\\".replace(\\\"|\\\", \\\"_\\\"))\\n if not os.path.exists(codthumb):\\n codthumb = None\\n c_time = time.time()\\n ul = io.open(f, \\\"rb\\\")\\n uploaded = await event.client.fast_upload_file(\\n file=ul,\\n progress_callback=lambda d, t: asyncio.get_event_loop().create_task(\\n progress(d, t, codevent, c_time, \\\"upload\\\", file_name=f)\\n ),\\n )\\n ul.close()\\n attributes, mime_type = await fix_attributes(f, ytdl_data, supports_streaming=True)\\n media = types.InputMediaUploadedDocument(\\n file=uploaded,\\n mime_type=mime_type,\\n attributes=attributes,\\n thumb=await event.client.upload_file(codthumb) if codthumb else None,\\n )\\n await event.client.send_file(\\n event.chat_id,\\n file=media,\\n reply_to=reply_to_id,\\n caption=ytdl_data[\\\"title\\\"],\\n supports_streaming=True,\\n force_document=False,\\n )\\n os.remove(f)\\n if codthumb:\\n os.remove(codthumb)\\n await codevent.delete()\",\n \"def do_GET(s):\\n s.send_response(200)\\n s.send_header(\\\"Content-type\\\", \\\"text/html;charset=utf-8\\\")\\n s.send_header(\\\"Accept-Charset\\\", \\\"utf-8\\\")\\n s.end_headers()\\n s.wfile.write(\\\"<html><head><title>Oll.tv - live stream links</title>\\\" \\\\\\n \\\"<style type='text/css'>\\\"\\n \\\"#content { \\\\n\\\"\\n \\\" width: 900px; \\\\n\\\" \\\\\\n \\\" display: inline;\\\" \\\\\\n \\\"}\\\\n\\\" \\\\\\n \\\"div.item { \\\\n\\\" \\\\\\n \\\" width: 12%; \\\\n\\\" \\\\\\n \\\" min-width: 165px; \\\\n\\\" \\\\\\n \\\" display: inline-block; \\\\n\\\" \\\\\\n \\\" -webkit-box-shadow: 3px -1px 20px -1px rgba(0,0,0,0.6); \\\\n\\\" \\\\\\n \\\" -moz-box-shadow: 3px -1px 20px -1px rgba(0,0,0,0.6); \\\\n\\\" \\\\\\n \\\" box-shadow: 3px -1px 20px -1px rgba(0,0,0,0.6); \\\\n\\\" \\\\\\n \\\" margin: 15px; \\\\n\\\" \\\\\\n \\\" text-align: center; \\\\n\\\" \\\\\\n \\\" padding: 10px; \\\\n\\\" \\\\\\n \\\" padding-bottom: 10px; \\\\n\\\" \\\\\\n \\\" vertical-align: top; \\\\n\\\" \\\\\\n \\\"} \\\\n\\\" \\\\\\n \\\"</style>\\\" \\\\\\n \\\"</head>\\\")\\n s.wfile.write(\\\"<body><p><a href='/index/'>Oll.tv</a> - Get channel stream links</p><div id='content'>\\\")\\n myid = 0\\n try:\\n path_list = s.path.split('/')\\n if len(path_list[2]) != 0:\\n myid = path_list[2]\\n except IndexError:\\n pass\\n\\n if path_list[1] == 'channel':\\n channel_data = dorequest('GetTVChannel', {'item_id': myid, 'afterDays': 7})\\n s.wfile.write(\\\"<h2>%s</h2><img src='%s' border=0><br/>\\\" % (\\n channel_data[u'name'].encode('utf8', 'ignore'),\\n channel_data[u'poster'].encode('utf8', 'ignore')\\n ))\\n # s.wfile.write(\\\"<a href='/item/%s'>Get Online Link</a><ul>\\\" % (channel_data[u'item_id']))\\n channel_link_data = dorequest('media', {'id': channel_data[u'item_id']})\\n if len(channel_link_data) > 0:\\n s.wfile.write(\\\"Your live stream link here:<br/><input type='text' size='140' value='%s'/><ul>\\\" % (\\n channel_link_data[u'media_url'].encode('utf-8', 'ignore'),\\n ))\\n print pprint.pprint(channel_data[u'nextThree'])\\n print pprint.pprint(channel_data[u'program'])\\n for line in channel_data[u'nextThree']:\\n s.wfile.write(\\\"<li><a href='/programm/%s'>%s</a> (%s / %s) - %s</li>\\\" % (\\n line[u'programm_id'],\\n line[u'name'].encode('utf8', 'ignore'),\\n line[u'start'].encode('utf8', 'ignore'),\\n line[u'stop'].encode('utf8', 'ignore'),\\n ''))\\n s.wfile.write(\\\"</ul><br/>History:<ul>\\\")\\n for line in channel_data[u'program']:\\n s.wfile.write(\\\"<li><a href='/programm/%s'>%s</a> (%s / %s) - %s</li>\\\" % (\\n line[u'programm_id'],\\n line[u'name'].encode('utf8', 'ignore'),\\n line[u'start'].encode('utf8', 'ignore'),\\n line[u'stop'].encode('utf8', 'ignore'),\\n ''))\\n elif path_list[1] == 'item':\\n channel_data = dorequest('media', {'id': myid})\\n if len(channel_data) > 0:\\n s.wfile.write(\\\"<ul><li>%s</li><li>%s</li><li>%s</li></ul>\\\" % (\\n channel_data[u'category_name'].encode('utf-8', 'ignore'),\\n channel_data[u'title'].encode('utf-8', 'ignore'),\\n channel_data[u'media_url'].encode('utf-8', 'ignore'),\\n ))\\n print pprint.pprint(channel_data)\\n\\n elif path_list[1] == 'index' or s.path == '/':\\n channels = dorequest('getAllTVChannels')\\n for line in channels:\\n for item in line[u'items']:\\n try:\\n if item[u'is_free'] != 1:\\n continue\\n except KeyError:\\n continue\\n s.wfile.write(\\\"<div class='item'><a href='/channel/%s'><img src='%s' border=0/>\\\" \\\\\\n % (item[u'id'],\\n item[u'src']))\\n\\n s.wfile.write(\\\"<br/>%s (%s)</a><br/>%s</div>\\\" \\\\\\n % (item[u'title'].encode('utf8', 'ignore'),\\n item[u'genre'].encode('utf8', 'ignore'),\\n item[u'descr'].encode('utf8', 'ignore')))\\n # s.wfile.write(\\\"<p>You accessed path: %s</p>\\\" % s.path) # debug info\\n s.wfile.write(\\\"</div></body></html>\\\")\",\n \"def add_subtitles(media_id, req):\\n\\n media_hndl = media_map.get(media_id)\\n if not media_hndl:\\n raise FileNotFoundError('{} is not a registered media_id'.format(media_id))\\n\\n subfile = None\\n if req.data:\\n subfile = json.loads(req.data.decode('utf-8')).get('filename')\\n if not subfile:\\n raise AttributeError('No filename specified in the request')\\n\\n if not subfile:\\n if not media_hndl.path:\\n raise NotImplementedError(\\n 'Subtitles are currently only supported for local media files')\\n\\n req = {\\n 'type': 'request',\\n 'action': 'media.subtitles.get_subtitles',\\n 'args': {\\n 'resource': media_hndl.path,\\n }\\n }\\n\\n try:\\n subtitles = send_message(req).output or []\\n except Exception as e:\\n raise RuntimeError('Could not get subtitles: {}'.format(str(e)))\\n\\n if not subtitles:\\n raise FileNotFoundError('No subtitles found for resource {}'.\\n format(media_hndl.path))\\n\\n req = {\\n 'type': 'request',\\n 'action': 'media.subtitles.download',\\n 'args': {\\n 'link': subtitles[0].get('SubDownloadLink'),\\n 'media_resource': media_hndl.path,\\n 'convert_to_vtt': True,\\n }\\n }\\n\\n subfile = (send_message(req).output or {}).get('filename')\\n\\n media_hndl.set_subtitles(subfile)\\n return {\\n 'filename': subfile,\\n 'url': get_remote_base_url() + '/media/subtitles/' + media_id + '.vtt',\\n }\",\n \"async def download_video(event):\\n url = event.pattern_match.group(1)\\n rmsg = await event.get_reply_message()\\n if not url and rmsg:\\n myString = rmsg.text\\n url = re.search(\\\"(?P<url>https?://[^\\\\s]+)\\\", myString).group(\\\"url\\\")\\n if not url:\\n return await edit_or_reply(event, \\\"What I am Supposed to find? Give link\\\")\\n codevent = await edit_or_reply(event, \\\"`Preparing to download...`\\\")\\n reply_to_id = await reply_id(event)\\n ytdl_data = await ytdl_down(codevent, video_opts, url)\\n if ytdl_down is None:\\n return\\n f = pathlib.Path(f\\\"{ytdl_data['title']}.mp4\\\".replace(\\\"|\\\", \\\"_\\\"))\\n codthumb = pathlib.Path(f\\\"{ytdl_data['title']}.jpg\\\".replace(\\\"|\\\", \\\"_\\\"))\\n if not os.path.exists(codthumb):\\n codthumb = pathlib.Path(f\\\"{ytdl_data['title']}.webp\\\".replace(\\\"|\\\", \\\"_\\\"))\\n if not os.path.exists(codthumb):\\n codthumb = None\\n await codevent.edit(\\n f\\\"`Preparing to upload video:`\\\\\\n \\\\n**{ytdl_data['title']}**\\\\\\n \\\\nby *{ytdl_data['uploader']}*\\\"\\n )\\n ul = io.open(f, \\\"rb\\\")\\n c_time = time.time()\\n attributes, mime_type = await fix_attributes(f, ytdl_data, supports_streaming=True)\\n uploaded = await event.client.fast_upload_file(\\n file=ul,\\n progress_callback=lambda d, t: asyncio.get_event_loop().create_task(\\n progress(d, t, codevent, c_time, \\\"upload\\\", file_name=f)\\n ),\\n )\\n ul.close()\\n media = types.InputMediaUploadedDocument(\\n file=uploaded,\\n mime_type=mime_type,\\n attributes=attributes,\\n thumb=await event.client.upload_file(codthumb) if codthumb else None,\\n )\\n await event.client.send_file(\\n event.chat_id,\\n file=media,\\n reply_to=reply_to_id,\\n caption=ytdl_data[\\\"title\\\"],\\n )\\n os.remove(f)\\n if codthumb:\\n os.remove(codthumb)\\n await event.delete()\",\n \"def main(url, localfile):\\n ph.download_file(url, localfile)\",\n \"def download_file(year: str, month: str, career: str, kind: str = \\\"ativo\\\") -> str:\\n\\n career = career.lower()\\n downloaded_files = []\\n existing_files = []\\n res = \\\"\\\"\\n for file_ in CGU_FILES[career][kind]:\\n url = f\\\"{URL_CGU_DOWNLOADS}/{year}{month}_{file_}\\\"\\n try:\\n division = file_.split(\\\"_\\\")[-1] if career == \\\"civil\\\" else None\\n if not file_exists(year, month, career, kind, division):\\n print(f\\\"Downloading {url}\\\")\\n sleep(10)\\n req = requests.get(url, stream=True, timeout=90)\\n req.raise_for_status()\\n filename = (\\n req.headers.get(\\\"Content-Disposition\\\")\\n .split(\\\"=\\\")[-1]\\n .replace('\\\"', \\\"\\\")\\n )\\n saved = save_file(filename, req.content)\\n unzipped_file = unzip_salary_file(saved, year, month, career, kind)\\n downloaded_files.append(unzipped_file)\\n else:\\n print(f\\\"Arquivo {url} já existe\\\")\\n existing_files.append(file_)\\n res = f\\\"Arquivos baixados: {', '.join(downloaded_files)} \\\\nArquivos existentes: {', '.join(existing_files)}\\\"\\n except requests.exceptions.ConnectionError as err:\\n res = f\\\"Erro de conexão: {err}\\\"\\n # pylint: disable=line-too-long\\n # Erro de conexão: HTTPConnectionPool(host='www.portaltransparencia.gov.br', port=80): Max retries\\n # exceeded with url: /download-de-dados/servidores/202202_Reserva_Reformas_Militares (Caused by\\n # NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f9cd019cd90>: Failed to establish\\n # a new connection: [Errno -3] Temporary failure in name resolution')\\n except requests.exceptions.HTTPError as err:\\n res = f\\\"Arquivo inexistente: {url.split('/')[-1]}.zip - {err}\\\"\\n # pylint: disable=line-too-long\\n # Erro no download: 404 Client Error: Not Found for url:\\n # https://www.portaltransparencia.gov.br/download-de-dados/servidores/202202_Reserva_Reformas_Militares\\n\\n print(res)\\n return res\",\n \"def get_sunpy_files(self):\\n from sunpy.net import jsoc\\n client = jsoc.JSOCClient() \\n dfmt = '%Y-%m-%dT%H:%M:%S' #date format for JSOC\\n\\n #get a query response from JSOC\\n response = client.query(jsoc.Time(self.start.strftime(dfmt),self.end.strftime(dfmt)),jsoc.Series(self.series),\\n jsoc.Wavelength(self.wav),jsoc.Segment(self.segment),jsoc.Notify(self.email))\\n\\n res = client.get(response,path=self.odir,sleep=60,overwrite=self.overwrite,max_conn=self.max_con)\\n res.wait(progress=True)\",\n \"def download():\\n raise NotImplementedError\",\n \"def getSubtitleURL(self):\\n\\n # If it is a movie, we use this methodology -\\n try:\\n IndexingParameters = [\\\"subtitleUrls\\\", 0, \\\"url\\\"]\\n TitleParamters = [\\n \\\"catalogMetadata\\\", \\\"catalog\\\", \\\"title\\\", \\\"episodeNumber\\\"]\\n subRequestObject = requests.get(self.subtitleURLContainer)\\n\\n parsedJsonObject = json.loads(str(subRequestObject.text))\\n SubsURL = parsedJsonObject[IndexingParameters[0]][\\n IndexingParameters[1]][IndexingParameters[2]]\\n if self.title == \\\"Amazonsubtitles\\\":\\n try:\\n self.title = parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[2]] + \\\"_\\\" + str(\\n parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[3]])\\n except:\\n pass\\n\\n return SubsURL\\n\\n except:\\n pass\\n pass\",\n \"def extract_data():\\n args = arguments()\\n\\n if args.list is not None:\\n songs = utility.get_songs(args.list)\\n logger.debug(str(songs))\\n if len(songs) != 0:\\n logger.info(\\\"Downloading songs in {}\\\".format(args.list))\\n for song_name in songs:\\n logger.debug(song_name)\\n args.SONG_NAME = [song_name]\\n main(args)\\n else:\\n logger.info(\\\"{}: is empty\\\".format(args.list))\\n elif args.SONG_NAME and yt.is_playlist(args.SONG_NAME[0]):\\n logger.info(\\\"Youtube playlist passed...extracting!\\\")\\n songs, playlist_name = yt.get_playlist(\\n args.SONG_NAME[0],\\n args.proxy,\\n args.pl_start,\\n args.pl_end,\\n args.pl_items\\n )\\n\\n # Check if data is actually returned\\n if songs is None:\\n logger.error(\\\"Couldn't extract playlist data!\\\")\\n\\n logger.info(\\\"Playlist: {}\\\".format(playlist_name))\\n logger.info(\\\"{} songs found\\\".format(len(songs)))\\n\\n # Iterate and work on the data.\\n url_base = \\\"https://www.youtube.com/watch?v=\\\"\\n for song in songs:\\n args.url = url_base + song[\\\"url\\\"]\\n\\n # Try to pass the title as well, if it's not there\\n # that will be handled by ytmdl\\n try:\\n args.SONG_NAME = [stringutils.remove_yt_words(song[\\\"title\\\"])]\\n except KeyError:\\n pass\\n\\n main(args)\\n else:\\n main(args)\",\n \"def extract_subtitle_track(path_to_mkv):\\n handler = SubtitleHandler()\\n with open(path_to_mkv, \\\"rb\\\") as fp:\\n mkvparse.mkvparse(fp, handler)\\n\\n return handler.subs\",\n \"def get_subtitle_print(subs: List[Track]) -> List[str]:\\n data = []\\n if not subs:\\n data.append(\\\"--\\\")\\n for sub in subs:\\n line_items = []\\n\\n # following sub.title tree checks and supports three different language and title scenarios\\n # The second scenario is the recommended option to choose if you are open to choosing any\\n # The third scenario should be used if you have nothing unique to state about the track\\n # | Language | Track Title | Output |\\n # | ------------ | ----------------------------- | --------------------------------------------- |\\n # | es / Spanish | Spanish (Latin American, SDH) | - Spanish (Latin American, SDH), SubRip (SRT) |\\n # | es / Spanish | Latin American (SDH) | - Spanish, Latin American (SDH), SubRip (SRT) |\\n # | es / Spanish | None | - Spanish, SubRip (SRT) |\\n language = pycountry.languages.get(alpha_2=sub.language).name\\n if sub.title:\\n if language.lower() in sub.title.lower():\\n line_items.append(sub.title)\\n else:\\n line_items.append(f\\\"{language}, {sub.title}\\\")\\n else:\\n line_items.append(language)\\n\\n line_items.append(sub.format.replace(\\\"UTF-8\\\", \\\"SubRip (SRT)\\\"))\\n\\n line = \\\"- \\\" + \\\", \\\".join(line_items)\\n data += [\\n (\\\" \\\" + x if i > 0 else x)\\n for i, x in enumerate(textwrap.wrap(line, 64))\\n ]\\n return data\",\n \"def do_GET(s):\\n s.send_response(200)\\n s.send_header(\\\"Content-type\\\", \\\"text/html\\\")\\n s.end_headers()\\n s.wfile.write(\\\"<html><head><title>Simple nc cli2dlna UI</title></head>\\\")\\n s.wfile.write(\\\"<body><form action=/play method=GET><input type=text id=ytu name=ytu><input type=submit value=Play></form>\\\")\\n s.wfile.write(\\\"Enter youtube URL to play\\\")\\n if len(s.path) > 10 and s.path[0:10] == '/play?ytu=':\\n url = unquote(s.path[10:])\\n if match(ytl_re, url):\\n s.wfile.write(\\\"<br>Accepted URL: %s\\\" % url)\\n call([\\n \\\"/storage/.kodi/addons/service.system.docker/bin/docker\\\",\\n \\\"run\\\",\\n \\\"--rm\\\",\\n \\\"--name\\\",\\n \\\"cli2dlna\\\",\\n \\\"-v\\\",\\n \\\"/storage/.cache/cli2dlna/renderer.cache:/renderer.cache\\\",\\n \\\"mitroko/cli2dlna\\\",\\n \\\"-yv\\\",\\n url\\n ])\\n s.wfile.write(\\\"</body></html>\\\")\",\n \"def download_data():\\r\\n print('Downloading cifar-10 data...')\\r\\n request.urlretrieve(dataurl)\\r\\n print('Done')\\r\\n print('Please unzip files. command is:')\\r\\n print('gzip -d cifar-10-python.tar.gz')\\r\\n print('tar -xf cifar-10-python.tar')\\r\\n exit()\",\n \"def downloadSong(self, song, outputFolder=\\\"\\\", outputFunction=None, writeJSON=True):\\n\\n \\\"\\\"\\\"\\n -x: Extract audio\\n --audio-format: sets the audio format from ogg to mp3\\n --audio-quality: 0 is best\\n --write-info-json: Writes the DASH information for the downloaded video to the filename with .info.json appended\\n \\\"\\\"\\\"\\n audioOptions = self.audioOptions.copy() # Generate a shallow copy of our object's options\\n if writeJSON:\\n audioOptions[\\\"--write-info-json\\\"] = True\\n audioOptions.update(settings[\\\"youtubeSettings\\\"])\\n\\n self.youtubeLock.acquire() # Wait the requisite amount of time\\n log.debug(\\\"Downloading Song '{}'\\\".format(song))\\n obj = subprocess.Popen(\\n [settings[\\\"youtube_dl\\\"]] + # Executable\\n self.flattenDict(audioOptions) + #Turn the dict items into a list where key is before value. Bools are special. If false, not added, otherwise only key\\n [\\\"-o\\\", os.path.join(outputFolder, settings[\\\"formatString\\\"])] + #Output format and folder\\n [\\\"--\\\", song], #Then add song as input\\n **settings[\\\"pipeOptions\\\"], #Add in subprocess options\\n stdout=subprocess.PIPE #Also this for now\\n )\\n \\n outputText = \\\"\\\"\\n for line in obj.stdout:\\n outputText += line\\n match = re.match(r\\\"\\\\[download\\\\]\\\\s+([\\\\d.]+)% of \\\\S+ at\\\\s+([\\\\d.]+\\\\S+)\\\", line) #Matches the download update lines\\n if match:\\n percent, downloadRate = match.group(1, 2)\\n if callable(outputFunction):\\n outputFunction(song, float(percent), downloadRate) #Update this if we have items\\n return obj.wait(), outputText # Wait for process to complete and get return code. Also return the whole output printed to stdout\",\n \"def download():\\n try:\\n cli.run(\\n [URL, '--output', TEMP_DIR],\\n )\\n except SystemExit:\\n return None\",\n \"def main():\\n # the url for african daily and global daily\\n african_dialy_url = \\\"https://data.chc.ucsb.edu/products/CHIRPS-2.0/africa_daily/tifs/p25/\\\"\\n global_daily_url = \\\"https://data.chc.ucsb.edu/products/CHIRPS-2.0/global_daily/tifs/p25/\\\"\\n\\n\\n each_year_list = GetRasterYears(url=african_dialy_url)\\n new_path = makenewdir(each_year_list)\\n years_new_list = fecthrasterurl(url=african_dialy_url)\\n downloadwithwget(each_year_list, years_new_list, new_path)\",\n \"def main(file_url, file_path):\\n\\n # extract file from the link\\n\\n if not os.path.exists(file_path):\\n os.makedirs(file_path, exist_ok=True)\\n \\n r = requests.get(str(file_url))\\n\\n #unzip the zip file\\n z = zipfile.ZipFile(io.BytesIO(r.content))\\n z.extractall(path = file_path)\",\n \"def parse_message(message, selector):\\n\\n msg = message.decode('utf-8')\\n print(colored(\\\"Telnet pide \\\" + msg, 'magenta'))\\n\\n # Mandó list?\\n clist = re.match(r'list', msg)\\n if clist:\\n return armar_lista()\\n\\n # Mandó offer?\\n else:\\n offer = re.match(r'offer (.*)\\\\r', msg)\\n if offer:\\n filename = offer[1] \\n\\n file_path = os.getcwd() + \\\"/files/\\\" + filename\\n\\n if os.path.exists(file_path):\\n sizefile = int(os.path.getsize(file_path))\\n\\n # Calcula el md5\\n with open(file_path, \\\"rb\\\") as f:\\n file_hash = hashlib.md5()\\n chunk = f.read(8192)\\n while chunk:\\n file_hash.update(chunk)\\n chunk = f.read(8192)\\n\\n file_hash = file_hash.hexdigest()\\n\\n aux_file = AppFile(filename, sizefile, file_hash)\\n\\n # Guardamos el archivo en nuestro diccionario de seguimiento local\\n local_files[file_hash] = aux_file\\n\\n # Lo borramos del de los disponibles remotos\\n if remote_files.get(file_hash):\\n del remote_files[file_hash]\\n\\n # Una vez actualizada la lista de archivos locales, mandamos a actualizar los anuncios\\n announce_forever.set_announcements()\\n\\n return 'ARCHIVO AGREGADO'\\n\\n else:\\n return 'ARCHIVO NO ENCONTRADO'\\n\\n\\n # Mandó get?\\n else:\\n get = re.match(r'get (\\\\d*)\\\\r\\\\n', msg)\\n if get:\\n file_id = int(get[1])\\n msg = f'INICIANDO DESCARGA DEL ARCHIVO {file_id}'\\n print(msg)\\n request_download(file_id, selector)\\n return msg\\n\\n return 'COMANDO INCORRECTO!'\",\n \"def download (url):\\n path, url = url\\n r = requests.get (url, stream = True)\\n content = r.text\\n #print (content)\\n with open (path + '.txt', 'w') as f:\\n f.write (content)\",\n \"def news_cli():\\n get_news_cli()\",\n \"def download_files(self):\",\n \"def download_and_extract(down_dir=download_dir, url=tuda_url):\\n\\n wget.download(url, down_dir) \\n tar_filepath = os.path.join(down_dir, \\\"german-speechdata-package-v2.tar.gz\\\")\\n #with tarfile.open(tar_filepath, \\\"r\\\") as tar:\\n # tar.extractall(down_dir)\",\n \"def main():\\n show_banner()\\n args = parse_args(sys.argv[1:])\\n urls = get_urls(args.inputfiles)\\n if args.only_urls:\\n print(\\\"URL\\\")\\n else:\\n print('{:70.70} {}'.format(\\\"URL\\\", \\\"Response\\\"))\\n\\n loop = asyncio.get_event_loop()\\n loop.run_until_complete(download(urls,\\n args.concurrency,\\n args.only_success,\\n args.outputfile,\\n args.only_urls))\",\n \"def do_downloads_by_server(self, arg):\\n args = arg.split()\\n if len(args) != 0:\\n common.error('`downloads_by_server` doesn\\\\'t'\\n 'expect any arguments.')\\n else:\\n servers = self.central_server.download_service.get_servers()\\n requests = self.central_server.client_service.get_requests()\\n\\n if not servers.is_empty():\\n print(\\\"%i server(s):\\\" % len(\\n servers.servers))\\n print('')\\n for server in servers.servers:\\n print('server:')\\n print(str(server))\\n print('downloads:')\\n server_requests = requests.get_requests_from_server(server)\\n if server_requests:\\n print(tabulate(\\n [request.to_row() for request\\n in server_requests],\\n headers=['Movie', 'Client'],\\n tablefmt=\\\"psql\\\"))\\n print('')\\n else:\\n print('No downloads\\\\n')\\n else:\\n print('There\\\\'s no available servers')\",\n \"def retrieve_files_over_ftp(self, host, port, subpath):\\n write_path = os.path.join(os.getcwd(), PathConstants.MEDIA_FOLDER)\\n if not os.path.isdir(write_path):\\n os.mkdir(write_path)\\n client = RemuFTPClient(host, port, subpath, write_path, self)\\n client.connect()\",\n \"def start(self):\\n tokyo_time = datetime.datetime.now(tz=TOKYO_TZ)\\n\\n # TODO: Does this work on Windows now?\\n env = os.environ.copy()\\n\\n # remove proxy information\\n for key in ('http_proxy', 'https_proxy', 'HTTP_PROXY', 'HTTPS_PROXY'):\\n env.pop(key, None)\\n\\n self.update_streaming_url()\\n\\n # TODO: rework this whole process to include lhls, and make it configurable\\n # and less braindead\\n if not self._protocol:\\n self._protocol = 'rtmp'\\n if not self._ffmpeg_container:\\n self._ffmpeg_container = 'mp4'\\n extra_args = []\\n # Fall back to HLS if no RTMP stream available\\n # Better to do this here or in update_streaming_url?\\n # There's a possible race condition here, if some external thread modifies either of these\\n if not self._rtmp_url and self._protocol == 'rtmp':\\n download_logger.warn('Using HLS downloader for {}'.format(self._room.handle))\\n self._protocol = 'hls'\\n\\n # extra_args = []\\n # force using TS container with HLS\\n # this is causing more problems than it solves\\n # if self.protocol in ('hls', 'lhls'):\\n # self._ffmpeg_container = 'ts'\\n\\n # 2020-01-10: those problems were preferrable to completely unwatchable streams\\n if self.protocol in ('hls', 'lhls'):\\n extra_args = [\\\"-copyts\\\"]\\n if self._ffmpeg_container == 'mp4':\\n extra_args.extend([\\\"-bsf:a\\\", \\\"aac_adtstoasc\\\"])\\n\\n # I don't think this is needed?\\n # if self._ffmpeg_container == 'ts':\\n # extra_args.extend(['-bsf:v', 'h264_mp4toannexb'])\\n # elif self._ffmpeg_container != 'mp4':\\n # # TODO: support additional container formats, e.g. FLV\\n # self._ffmpeg_container = 'mp4'\\n temp, dest, out = format_name(self._rootdir,\\n strftime(tokyo_time, FULL_DATE_FMT),\\n self._room, ext=self._ffmpeg_container)\\n\\n with self._lock:\\n self.tempdir, self.destdir, self.outfile = temp, dest, out\\n\\n if self._logging is True:\\n log_file = os.path.normpath('{}/logs/{}.log'.format(self.destdir, self.outfile))\\n env.update({'FFREPORT': 'file={}:level=40'.format(log_file)})\\n # level=48 is debug mode, with lots and lots of extra information\\n # maybe too much\\n normed_outpath = os.path.normpath('{}/{}'.format(self.tempdir, self.outfile))\\n\\n self._process = subprocess.Popen([\\n self._ffmpeg_path,\\n # '-nostdin',\\n # '-nostats', # will this omit any useful information?\\n '-loglevel', '40', # 40+ required for wait() to check output\\n '-copytb', '1',\\n '-i', self.stream_url,\\n '-c', 'copy',\\n *extra_args,\\n normed_outpath\\n ],\\n stdin=subprocess.DEVNULL,\\n stderr=subprocess.PIPE, # ffmpeg sends all output to stderr\\n universal_newlines=True,\\n bufsize=1,\\n env=env)\",\n \"def get_server_list():\\n\\n if file_downloaded(output_file):\\n server_list = load_server_list_json()\\n printer('Server list loaded from JSON')\\n\\n #server_list = load_server_list_json()\\n #printer('Server list loaded from JSON')\\n\\n else:\\n # Connect to RS\\n rsconn = object\\n rsconn = connect()\\n\\n # Store the JSON response from list_servers\\n printer(\\\"Fetching server list from Rackspace...\\\")\\n\\n server_list = rsconn.list_servers(detailed = DETAILED)\\n save_server_list_json(server_list)\\n\\n printer('Server list loaded via API call')\\n\\n return server_list\",\n \"def youtube_download_by_id(id, title=None, output_dir='.', merge=True, info_only=False):\\n \\n raw_video_info = get_content('http://www.youtube.com/get_video_info?video_id=%s' % id)\\n video_info = parse.parse_qs(raw_video_info)\\n \\n if video_info['status'] == ['ok'] and ('use_cipher_signature' not in video_info or video_info['use_cipher_signature'] == ['False']):\\n title = parse.unquote_plus(video_info['title'][0])\\n stream_list = parse.parse_qs(raw_video_info)['url_encoded_fmt_stream_map'][0].split(',')\\n \\n else:\\n # Parse video page when video_info is not usable.\\n video_page = get_content('http://www.youtube.com/watch?v=%s' % id)\\n ytplayer_config = json.loads(match1(video_page, r'ytplayer.config\\\\s*=\\\\s*([^\\\\n]+);'))\\n \\n title = ytplayer_config['args']['title']\\n stream_list = ytplayer_config['args']['url_encoded_fmt_stream_map'].split(',')\\n \\n streams = {\\n parse.parse_qs(stream)['itag'][0] : parse.parse_qs(stream)\\n for stream in stream_list\\n }\\n \\n for codec in yt_codecs:\\n itag = str(codec['itag'])\\n if itag in streams:\\n download_stream = streams[itag]\\n break\\n \\n url = download_stream['url'][0]\\n if 'sig' in download_stream:\\n sig = download_stream['sig'][0]\\n else:\\n sig = decrypt_signature(download_stream['s'][0])\\n url = '%s&signature=%s' % (url, sig)\\n \\n type, ext, size = url_info(url)\\n \\n print_info(site_info, title, type, size)\\n if not info_only:\\n download_urls([url], title, ext, size, output_dir, merge = merge)\",\n \"def __init__(self, subtitles_file, subtitles_language: str, audio_language: str):\\n\\n subtitles_binary = subtitles_file.read()\\n encoding = detect_encoding(subtitles_binary)['encoding']\\n self.subtitles = subtitles_binary.decode(encoding)\\n self.encoding = encoding\\n logger.debug(f'Subtitles Encoding: {encoding}')\\n logger.debug(f'Subtitles[:100]: {[self.subtitles[:1000]]}')\\n self.read_subtitles()\\n self.audio_language = audio_language\\n\\n # Detect subtitles language\\n if(subtitles_language == 'ad'): # ad = Auto Detect\\n detected_language = detect_language(self.subtitles)\\n logger.debug(f\\\"Subtitles language detected as {detected_language}\\\")\\n\\n # True if the detected language in google's supported languages\\n language_items = any(map(\\n lambda lang: lang['language'] == detected_language, Constants.GOOGLE_LANGUAGES))\\n if(language_items is False):\\n raise Exception(\\n f'Detected language {detected_language} is not supported.')\\n self.subtitles_language = detected_language\\n\\n else:\\n self.subtitles_language = subtitles_language\\n\\n self.translator = CustomTranslator(self.subtitles_language, audio_language)\",\n \"def start(update, context):\\n update.message.reply_text(\\n 'Hello! Use /convert to convert streaming music urls into other services.')\",\n \"def download_songs(playlist_url):\\n command_string = 'youtube-dl -x --audio-format wav --postprocessor-args \\\"-ar 44100 -ac 1\\\" --output \\\"Songs/%(' \\\\\\n 'title)s_%(id)s.%(ext)s\\\" ' + \\\\\\n playlist_url\\n args = shlex.split(command_string)\\n subprocess.call(args)\",\n \"def start_torrent_download(filename):\\n return tadapt.start_download(filename)\",\n \"def extractRawSubtitleList(subtitleFullPath, srtEncodingConfidenceThreshold = 0.8, defaultEncoding=\\\"utf-8\\\"):\\n\\n getSubOk = False\\n rawSubtitleListOrErrMsg = \\\"Unknown Error\\\"\\n\\n with open(subtitleFullPath, 'rb') as subtitleFp:\\n fileContentStr = subtitleFp.read()\\n detectedResult = chardet.detect(fileContentStr)\\n # logging.debug(\\\"detectedResult=%s\\\", detectedResult)\\n fileEncoding = defaultEncoding\\n if detectedResult[\\\"confidence\\\"] >= srtEncodingConfidenceThreshold:\\n fileEncoding = detectedResult[\\\"encoding\\\"] # 'UTF-8-SIG'\\n # logging.debug(\\\"fileEncoding=%s\\\", fileEncoding)\\n\\n try:\\n rawSubtitleList = pysrt.open(subtitleFullPath, encoding=fileEncoding)\\n rawSubtitleListOrErrMsg = rawSubtitleList\\n getSubOk = True\\n except Exception as openSrtException:\\n rawSubtitleListOrErrMsg = str(openSrtException)\\n # logging.debug(\\\"Error %s of pysrt.open %s\\\", rawSubtitleListOrErrMsg, subtitleFullPath)\\n\\n return getSubOk, rawSubtitleListOrErrMsg\",\n \"def main() -> None:\\n run_time = datetime.datetime.now()\\n datetime_string = run_time.strftime(\\\"%Y%m%d_%H%M%S\\\")\\n\\n parser = argparse.ArgumentParser(\\n description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter\\n )\\n parser.add_argument(\\n \\\"-l\\\",\\n \\\"--logfolder\\\",\\n type=str,\\n default=\\\"ia_downloader_logs\\\",\\n help=(\\n \\\"Folder to write logs to (if not specified, folder 'ia_downloader_logs' will be used in\\\"\\n \\\" same directory as this script)\\\"\\n ),\\n )\\n\\n subparsers = parser.add_subparsers(\\n help=(\\n \\\"Either 'download' files associated with an Internet Archive identifier, or 'verify' a\\\"\\n \\\" previously-completed download was successful and files match expected MD5 hash values\\\"\\n ),\\n dest=\\\"command\\\",\\n required=True,\\n )\\n\\n download_parser = subparsers.add_parser(\\\"download\\\")\\n download_parser.add_argument(\\n \\\"identifiers\\\",\\n type=str,\\n nargs=\\\"+\\\",\\n help=(\\n \\\"One or more (space separated) Archive.org identifiers (e.g.\\\"\\n \\\" 'gov.archives.arc.1155023'). If specifying a collection (and you wish to download all\\\"\\n \\\" items within the collection), use the prefix 'collection:' (e.g. 'collection:nasa')\\\"\\n ),\\n )\\n download_parser.add_argument(\\\"output_folder\\\", type=str, help=\\\"Folder to download files to\\\")\\n download_parser.add_argument(\\n \\\"-t\\\",\\n \\\"--threads\\\",\\n type=check_argument_int_greater_than_one,\\n default=5,\\n help=(\\n \\\"Number of download threads (i.e. how many downloads to perform simultaneously)\\\"\\n \\\" (default is 5)\\\"\\n ),\\n )\\n download_parser.add_argument(\\n \\\"-v\\\",\\n \\\"--verify\\\",\\n default=False,\\n action=\\\"store_true\\\",\\n help=\\\"Perform an MD5 hash check on each file as downloads complete\\\",\\n )\\n download_parser.add_argument(\\n \\\"-r\\\",\\n \\\"--resume\\\",\\n default=False,\\n action=\\\"store_true\\\",\\n help=(\\n \\\"Attempt to resume downloads using already-downloaded data if a connection error occurs\\\"\\n ),\\n )\\n download_parser.add_argument(\\n \\\"-s\\\",\\n \\\"--split\\\",\\n type=check_argument_int_greater_than_one,\\n default=1,\\n help=(\\n \\\"To increase per-file download speeds, split files above 10MB into provided number of\\\"\\n \\\" chunks, and reconstruct on completion\\\"\\n ),\\n )\\n download_parser.add_argument(\\n \\\"-f\\\",\\n \\\"--filefilters\\\",\\n type=str,\\n nargs=\\\"+\\\",\\n help=(\\n \\\"One or more (space separated) file name filters; only files that contain any of the\\\"\\n \\\" provided filter strings (case insensitive) will be downloaded. If multiple filters\\\"\\n \\\" are provided, the search will be an 'OR' (i.e. only one of the provided strings needs\\\"\\n \\\" to hit)\\\"\\n ),\\n )\\n download_parser.add_argument(\\n \\\"-c\\\",\\n \\\"--credentials\\\",\\n type=str,\\n nargs=2,\\n help=(\\n \\\"Email address and password (as separate strings) for Internet Archive account\\\"\\n \\\" (required for download of some Internet Archive items)\\\"\\n ),\\n )\\n download_parser.add_argument(\\n \\\"--hashfile\\\",\\n type=str,\\n help=(\\n \\\"Output path to write file containing hash metadata to (if not specified, file will\\\"\\n \\\" be created in the output folder)\\\"\\n ),\\n )\\n download_parser.add_argument(\\n \\\"--cacherefresh\\\",\\n default=False,\\n action=\\\"store_true\\\",\\n help=\\\"Flag to update any cached Internet Archive metadata from previous script executions\\\",\\n )\\n\\n verify_parser = subparsers.add_parser(\\\"verify\\\")\\n verify_parser.add_argument(\\n \\\"data_folders\\\",\\n type=str,\\n nargs=\\\"+\\\",\\n help=\\\"Path to folder containing previously downloaded data\\\",\\n )\\n verify_parser.add_argument(\\n \\\"-i\\\",\\n \\\"--identifiers\\\",\\n type=str,\\n nargs=\\\"+\\\",\\n help=(\\n \\\"One or more (space separated) Archive.org identifiers (e.g.\\\"\\n \\\" 'gov.archives.arc.1155023') - to be used if only certain item(s) in the target\\\"\\n \\\" folder(s) are to be verified\\\"\\n ),\\n )\\n verify_parser.add_argument(\\n \\\"--hashfile\\\",\\n type=str,\\n help=(\\n \\\"Path to file containing hash metadata from previous download using this script (if not\\\"\\n \\\" specified, cached data from previous script execution will be used)\\\"\\n ),\\n )\\n verify_parser.add_argument(\\n \\\"-f\\\",\\n \\\"--filefilters\\\",\\n type=str,\\n nargs=\\\"+\\\",\\n help=(\\n \\\"One or more (space separated) file name filters; only files that contain any of the\\\"\\n \\\" provided filter strings (case insensitive) will be verified. If multiple filters\\\"\\n \\\" are provided, the search will be an 'OR' (i.e. only one of the provided strings needs\\\"\\n \\\" to hit)\\\"\\n ),\\n )\\n verify_parser.add_argument(\\n \\\"--nopaths\\\",\\n default=False,\\n action=\\\"store_true\\\",\\n help=(\\n \\\"If files are no longer in the same relative paths, perform lookup based only on\\\"\\n \\\" whether MD5 hashes are present in the data set (rather than also checking where those\\\"\\n \\\" files are stored)\\\"\\n ),\\n )\\n\\n args = parser.parse_args()\\n\\n # Set up logging\\n log_subfolders = [\\\"logs\\\", \\\"cache\\\"]\\n for log_subfolder in log_subfolders:\\n pathlib.Path(os.path.join(args.logfolder, log_subfolder)).mkdir(parents=True, exist_ok=True)\\n log, counter_handler = prepare_logging(\\n datetime_string,\\n os.path.join(args.logfolder, log_subfolders[0]),\\n \\\"ia_downloader\\\",\\n dict(vars(args)),\\n )\\n log.info(\\n \\\"Internet Archive is a non-profit organisation that is experiencing unprecedented service\\\"\\n \\\" demand. Please consider making a donation: https://archive.org/donate\\\"\\n )\\n log.info(\\\"Logs will be stored in folder '{}'\\\".format(args.logfolder))\\n\\n try:\\n if args.command == \\\"download\\\":\\n if args.credentials is not None:\\n try:\\n internetarchive.configure(args.credentials[0], args.credentials[1])\\n except internetarchive.exceptions.AuthenticationError:\\n log.error(\\n \\\"Authentication error raised for supplied email address and password -\\\"\\n \\\" check these were entered correctly (if the password has spaces, it must\\\"\\n \\\" be wrapped in quotation marks)\\\"\\n )\\n return\\n if args.hashfile is not None:\\n log.info(\\n \\\"Internet Archive metadata will be written to hash file at '{}'\\\".format(\\n args.hashfile\\n )\\n )\\n if args.threads > 5 or args.split > 5:\\n log.info(\\n \\\"Reducing download threads to 5, to optimise script performance and reduce\\\"\\n \\\" Internet Archive server load\\\"\\n )\\n args.threads = min(args.threads, 5)\\n args.split = min(args.split, 5)\\n if args.split > 1:\\n if args.threads > 1:\\n log.info(\\n \\\"While using file splitting, only one file will be downloaded at a time so\\\"\\n \\\" as to not overwhelm Internet Archive servers\\\"\\n )\\n args.threads = 1\\n hashfile_file_handler = None\\n if args.hashfile:\\n hashfile_file_handler = open(args.hashfile, \\\"w\\\")\\n\\n for identifier in args.identifiers:\\n download(\\n identifier=identifier,\\n output_folder=args.output_folder,\\n hash_file=hashfile_file_handler,\\n thread_count=args.threads,\\n resume_flag=args.resume,\\n verify_flag=args.verify,\\n split_count=args.split,\\n file_filters=args.filefilters,\\n cache_parent_folder=os.path.join(args.logfolder, log_subfolders[1]),\\n cache_refresh=args.cacherefresh,\\n )\\n\\n if args.hashfile:\\n hashfile_file_handler.close()\\n\\n elif args.command == \\\"verify\\\":\\n verify(\\n hash_file=args.hashfile,\\n data_folders=args.data_folders,\\n no_paths_flag=args.nopaths,\\n hash_flag=True,\\n cache_parent_folder=os.path.join(args.logfolder, log_subfolders[1]),\\n identifiers=args.identifiers,\\n file_filters=args.filefilters,\\n )\\n\\n if counter_handler.count[\\\"WARNING\\\"] > 0 or counter_handler.count[\\\"ERROR\\\"] > 0:\\n log.warning(\\n \\\"Script complete; {} warnings/errors occurred requiring review (see log entries\\\"\\n \\\" above, replicated in folder '{}')\\\".format(\\n counter_handler.count[\\\"WARNING\\\"] + counter_handler.count[\\\"ERROR\\\"],\\n args.logfolder,\\n )\\n )\\n else:\\n log.info(\\\"Script complete; no errors reported\\\")\\n\\n except KeyboardInterrupt:\\n log.warning(\\n \\\"KeyboardInterrupt received, quitting immediately (any in-progress downloads or\\\"\\n \\\" verifications have been terminated)\\\"\\n )\\n except Exception:\\n log.exception(\\\"Exception occurred:\\\")\",\n \"def handle_file_retrieval(self, msg):\\n Logger.info(\\\"Slave: Retrieving files\\\")\\n params = msg.get_field(MessageKeys.params_key)\\n host = msg.get_field(MessageKeys.sender_key)\\n port = params[MessageKeys.ftp_port_key]\\n subpath = params[MessageKeys.ftp_subpath_key]\\n self.presentation.set_files(params[MessageKeys.presentation_content_key])\\n self.presentation.reset()\\n self.layout.init_presentation()\\n self.retrieve_files_over_ftp(host, port, subpath)\\n self.presentation_ended = False\\n return self.create_response(msg.get_command())\",\n \"def main():\\n pass\\n # service = getServiceInstant()\\n # # insertFile(service, 'dynamip.conf')\\n # file_id = getFileIdFromName(service, 'dynamip.conf')\\n # metadata = updateFile(service, file_id, 'dynamip.conf')\\n # print(metadata)\\n # file = open('metadata_of_updated_dynamip_file', 'w')\\n # json.dump(metadata, file)\\n # file.write(file)\\n # results = service.files().list(maxResults=10).execute()\\n # items = results.get('items', [])\\n # if not items:\\n # print('No files found.')\\n # else:\\n # print('Files:')\\n # for item in items:\\n # try:\\n # print('{0} ({1})'.format(item['title'], item['id']))\\n # except Exception, e:\\n # print(e)\",\n \"def extract_url_download(update: Update, context: CallbackContext) -> None:\\r\\n received_text = update.message.text\\r\\n yt_urls = get_link_text(received_text)\\r\\n yt_urls_msg = update.message.reply_text(pretty_url_string(yt_urls), disable_web_page_preview=True)\\r\\n if len(yt_urls) > 0:\\r\\n for url in yt_urls:\\r\\n if 'list=' in url:\\r\\n print(\\\"dshgshj\\\")\\r\\n\\t\\t\\t\\t# download_playlist_url(update, context, url)\\r\\n else:\\r\\n download_url(update, context, url)\\r\\n context.bot.delete_message(message_id=yt_urls_msg.message_id, chat_id=yt_urls_msg.chat_id)\",\n \"def get_cmd_string(res, DVDFab_path, src_iso_path, client_dest_path): \\n dest_path = change_fuhao(res[6])\\n Dest = get_value(res[6], \\\"/DEST\\\")\\n Mode = get_value(res[4], \\\"/MODE\\\")\\n Src = get_value(src_iso_path, \\\"/SRC\\\")\\n Audio = get_value(res[9], \\\"/AUDIO\\\")\\n Audio_type = get_value(res[10], \\\"/AUDIOTYPE\\\")\\n Change_play_order = get_value(res[11], \\\"/CHANGEPLAYORDER\\\")\\n Copy_IFO = get_value(res[12], \\\"/COPYIFO\\\")\\n Display_forced_sub = get_value(res[13], \\\"/DISPLAYFORCEDSUB\\\")\\n Jump_menu = get_value(res[14], \\\"/JUMPMENU\\\")\\n Jump_main = get_value(res[15], \\\"/JUMPMAIN\\\")\\n Out_disc = get_value(res[16], \\\"/OUTDISC\\\")\\n Path_player = get_value(res[17], \\\"/PATHPLAYER\\\")\\n Preserve_menu_disc2 = get_value(res[18], \\\"/PRESERVEMENUDISC2\\\")\\n Profile = get_value(res[19], \\\"/PROFILE\\\")\\n Remove_DTS = get_value(res[20], \\\"/REMOVEDTS\\\")\\n Remove_HD_audio = get_value(res[21], \\\"/REMOVEHDAUDIO\\\")\\n Remove_menu = get_value(res[22], \\\"/REMOVEMENU\\\")\\n Remove_PGC = get_value(res[23], \\\"/REMOVEPGC\\\")\\n Rewind = get_value(res[24], \\\"/REWIND\\\")\\n Subtitle = get_value(res[25], \\\"/SUBTITLE\\\")\\n Title = get_value(res[26], \\\"/TITLE\\\")\\n Volume = get_value(res[27], \\\"/VOLUME\\\")\\n BD3DT = get_value(res[44], \\\"/BD3DCONVERTTYPE\\\")\\n COMPRESSTOAC3 = get_value(res[45], \\\"/COMPRESSTOAC3\\\")\\n Close = ' /CLOSE' \\n Createminiso = ' /CREATEMINISO' if os.name == 'nt' else ''\\n cmd_string = Mode + Src + Dest + Audio + Audio_type + Change_play_order + Copy_IFO + Display_forced_sub + Jump_menu + Jump_main\\\\\\n + Out_disc + Path_player + Preserve_menu_disc2 + Profile + Remove_DTS + Remove_HD_audio + Remove_menu + Remove_PGC\\\\\\n + Rewind + Subtitle + Title + Volume + BD3DT + COMPRESSTOAC3 + Close + Createminiso\\n DVDFab_path_cmd_string = '\\\"' + DVDFab_path + '\\\"' + cmd_string \\n initlog('the cmd_string: %s' % DVDFab_path_cmd_string)\\n return DVDFab_path_cmd_string, dest_path\",\n \"def download_sra_files(remote_location, local_location = '', max_recursion = 3, verbose = False):\\n\\n downloaded_files = list();\\n\\n def printv(*args):\\n if(verbose):\\n print(*args);\\n sys.stdout.flush();\\n\\n printv(\\\"Reading folder: \\\", remote_location);\\n\\n req = urllib2.Request(remote_location);\\n\\n response = urllib2.urlopen(req);\\n\\n the_page = response.read();\\n\\n entries = the_page.split('\\\\r\\\\n');\\n\\n #Identify sub folders\\n folders = list();\\n for entry in entries:\\n if(len(entry) == 0):\\n continue;\\n\\n spl_entry = entry.split();\\n if(spl_entry[0][0] == 'd'): #if directory flag\\n folders.append(spl_entry[-1]);\\n\\n\\n for folder in folders:\\n dl_files = download_sra_files(remote_location + '/' + folder, local_location, max_recursion - 1, verbose);\\n downloaded_files.extend(dl_files);\\n\\n #Identify SRA files\\n files = list();\\n for entry in entries:\\n if(len(entry) == 0):\\n continue;\\n\\n spl_entry = entry.split();\\n if(spl_entry[0][0] == '-' and #Not a directory\\n spl_entry[-1].lower().endswith('.sra')): #Has extension '.sra'\\n\\n files.append(spl_entry[-1]);\\n\\n if(len(files) > 0):\\n printv(\\\"Identified sra files: \\\");\\n for file_name in files:\\n printv(\\\" \\\", file_name);\\n\\n abs_local_location = os.path.abspath(local_location);\\n\\n if(not os.path.isdir(abs_local_location)):\\n os.makedirs(abs_local_location);\\n\\n for file_name in files:\\n\\n printv(\\\"Downloading \\\", file_name);\\n\\n file_str = remote_location + '/' + file_name;\\n\\n req = urllib2.Request(file_str);\\n response = urllib2.urlopen(req);\\n\\n dest_file_name = abs_local_location + os.sep + file_name;\\n dest_file = open(dest_file_name, 'wb');\\n shutil.copyfileobj(response, dest_file)\\n dest_file.close();\\n downloaded_files.append(dest_file_name);\\n\\n return downloaded_files;\",\n \"async def _(event):\\n if event.fwd_from:\\n return\\n\\n strings = {\\n \\\"name\\\": \\\"DeezLoad\\\",\\n \\\"arl_token_cfg_doc\\\": \\\"ARL Token for Deezer\\\",\\n \\\"invalid_arl_token\\\": \\\"please set the required variables for this module\\\",\\n \\\"wrong_cmd_syntax\\\": \\\"bruh, now i think how far should we go. please terminate my Session 🥺\\\",\\n \\\"server_error\\\": \\\"We're experiencing technical difficulties.\\\",\\n \\\"processing\\\": \\\"`Downloading...`\\\",\\n }\\n\\n ARL_TOKEN = Config.DEEZER_ARL_TOKEN\\n\\n if ARL_TOKEN is None:\\n await event.edit(strings[\\\"invalid_arl_token\\\"])\\n return\\n\\n try:\\n loader = deezloader.Login(ARL_TOKEN)\\n except Exception as er:\\n await event.edit(str(er))\\n return\\n\\n temp_dl_path = os.path.join(Config.TMP_DOWNLOAD_DIRECTORY, str(time.time()))\\n if not os.path.exists(temp_dl_path):\\n os.makedirs(temp_dl_path)\\n\\n required_link = event.pattern_match.group(1)\\n required_qty = event.pattern_match.group(2)\\n\\n await event.edit(strings[\\\"processing\\\"])\\n\\n if \\\"spotify\\\" in required_link:\\n if \\\"track\\\" in required_link:\\n required_track = loader.download_trackspo(\\n required_link,\\n output=temp_dl_path,\\n quality=required_qty,\\n recursive_quality=True,\\n recursive_download=True,\\n not_interface=True,\\n )\\n await event.edit(\\\"`Uploading...`\\\")\\n await upload_track(required_track, event)\\n shutil.rmtree(temp_dl_path)\\n await event.delete()\\n\\n elif \\\"album\\\" in required_link:\\n reqd_albums = loader.download_albumspo(\\n required_link,\\n output=temp_dl_path,\\n quality=required_qty,\\n recursive_quality=True,\\n recursive_download=True,\\n not_interface=True,\\n zips=False,\\n )\\n for required_track in reqd_albums:\\n await upload_track(required_track, event)\\n shutil.rmtree(temp_dl_path)\\n await event.delete()\\n\\n elif \\\"deezer\\\" in required_link:\\n if \\\"track\\\" in required_link:\\n required_track = loader.download_trackdee(\\n required_link,\\n output=temp_dl_path,\\n quality=required_qty,\\n recursive_quality=True,\\n recursive_download=True,\\n not_interface=True,\\n )\\n await event.edit(\\\"Uploading...\\\")\\n await upload_track(required_track, event)\\n shutil.rmtree(temp_dl_path)\\n await event.delete()\\n\\n elif \\\"album\\\" in required_link:\\n reqd_albums = loader.download_albumdee(\\n required_link,\\n output=temp_dl_path,\\n quality=required_qty,\\n recursive_quality=True,\\n recursive_download=True,\\n not_interface=True,\\n zips=False,\\n )\\n for required_track in reqd_albums:\\n await upload_track(required_track, event)\\n shutil.rmtree(temp_dl_path)\\n await event.delete()\\n\\n else:\\n await event.edit(strings[\\\"wrong_cmd_syntax\\\"])\",\n \"def do_download(ftp):\\n # Active (PORT), Passive (PASV), ExtActive (EPRT), or ExtPassive (EPSV)?\\n output, sock, transfer_type = get_transfer_output_and_socket(ftp)\\n print_debug(output + \\\"\\\\n\\\")\\n\\n # What file to download?\\n path = raw_input(\\\"What file do you want to download?\\\\n> \\\")\\n while not path:\\n path = raw_input(\\\"What file do you want to download?\\\\n> \\\")\\n try:\\n msg_rec, data_rec = ftp.retr_cmd(sock, path, transfer_type)\\n print_debug(str(msg_rec))\\n except Exception as e:\\n print(\\\"An error has occurred: \\\" + str(e) + \\\"\\\\nPlease try again.\\\")\\n return main_menu(ftp)\\n\\n # Download file.\\n if data_rec:\\n print_debug(str(data_rec))\\n try:\\n write_to_local(path, data_rec)\\n except Exception as e:\\n print(\\\"An error has occurred: \\\" + str(e) + \\\"\\\\nPlease try again.\\\")\\n return main_menu(ftp)\\n main_menu(ftp)\",\n \"def download_data():\\n url = 'https://www.dropbox.com/s/h9ubx22ftdkyvd5/ml-latest-small.zip?dl=1'\\n urllib.request.urlretrieve(url, 'ml-latest-small.zip')\\n zfile = zipfile.ZipFile('ml-latest-small.zip')\\n zfile.extractall()\\n zfile.close()\",\n \"def download(self, *path, **kwargs):\\n extract = kwargs.get(\\\"extract\\\", True)\\n callback = kwargs.get(\\\"callback\\\", None)\\n info = self.serverfiles.info(*path)\\n\\n extract = extract and \\\"compression\\\" in info\\n target = self.localpath(*path)\\n self.serverfiles.download(*path,\\n target=target + \\\".tmp\\\" if extract else target,\\n callback=callback)\\n\\n _save_file_info(target + '.info', info)\\n\\n if extract:\\n if info.get(\\\"compression\\\") in [\\\"tar.gz\\\", \\\"tar.bz2\\\"]:\\n f = tarfile.open(target + \\\".tmp\\\")\\n try:\\n os.mkdir(target)\\n except OSError:\\n pass\\n f.extractall(target)\\n elif info.get(\\\"compression\\\") == \\\"gz\\\":\\n f = gzip.open(target + \\\".tmp\\\")\\n shutil.copyfileobj(f, open(target, \\\"wb\\\"))\\n elif info.get(\\\"compression\\\") == \\\"bz2\\\":\\n f = bz2.BZ2File(target + \\\".tmp\\\", \\\"r\\\")\\n shutil.copyfileobj(f, open(target, \\\"wb\\\"))\\n f.close()\\n os.remove(target + \\\".tmp\\\")\",\n \"def fetch_files():\\n props = util.get_properties()\\n # get atmosfn\\n atmosfn = \\\"%s/rwis.txt\\\" % (INCOMING, )\\n try:\\n ftp = ftplib.FTP('165.206.203.34')\\n except TimeoutError as _exp:\\n print(\\\"process_rwis FTP Server Timeout\\\")\\n sys.exit()\\n ftp.login('rwis', props['rwis_ftp_password'])\\n ftp.retrbinary('RETR ExpApAirData.txt', open(atmosfn, 'wb').write)\\n # Insert into LDM\\n pqstr = \\\"plot ac %s rwis.txt raw/rwis/%sat.txt txt\\\" % (GTS, GTS)\\n subprocess.call((\\\"/home/ldm/bin/pqinsert -i -p '%s' %s \\\"\\n \\\"\\\") % (pqstr, atmosfn), shell=True)\\n\\n # get sfcfn\\n sfcfn = \\\"%s/rwis_sf.txt\\\" % (INCOMING, )\\n ftp.retrbinary('RETR ExpSfData.txt', open(sfcfn, 'wb').write)\\n ftp.close()\\n # Insert into LDM\\n pqstr = \\\"plot ac %s rwis_sf.txt raw/rwis/%ssf.txt txt\\\" % (GTS, GTS)\\n subprocess.call((\\\"/home/ldm/bin/pqinsert -i -p '%s' %s \\\"\\n \\\"\\\") % (pqstr, sfcfn), shell=True)\\n\\n return atmosfn, sfcfn\",\n \"def download_file():\\r\\n global title_dict\\r\\n title=ResultsListbox.get(ResultsListbox.curselection())\\r\\n link=title_dict[title]\\r\\n file_dl=urllib.URLopener()\\r\\n file_dl.retrieve(link,str(title)+\\\".pdf\\\")\",\n \"def __init__(self, subtitle=None):\\n self.subtitle = subtitle\\n if not self.subtitle:\\n self.parse_subtitles()\",\n \"def load_mytransit_archived_feeds(timestamp=datetime.datetime(2017, 1, 1, 12, 0)):\\n import requests\\n\\n ts = timestamp\\n uri = \\\"http://data.mytransit.nyc.s3.amazonaws.com/subway_time/{0}/{0}-{1}/subway_time_{2}.tar.xz\\\".format(\\n ts.year, str(ts.month).rjust(2, '0'), str(ts.year) + str(ts.month).rjust(2, '0') + str(ts.day).rjust(2, '0')\\n )\\n # filename_date_format = str(datetime.datetime.strftime(datetime.datetime(2016, 1, 1), \\\"%Y%m%dT%H%MZ\\\"))\\n\\n # The tar module does not seem to support reading virtual files via io.BytesIO, we have to go to disc.\\n temp_filename = \\\"temp.tar.xz\\\"\\n with open(temp_filename, \\\"wb\\\") as f:\\n f.write(requests.get(uri).content)\\n\\n archive = tarfile.open(temp_filename, 'r')\\n messages = [archive.extractfile(f) for f in archive.getmembers()]\\n os.remove(temp_filename)\\n\\n return messages\",\n \"def track_04():\\n sonos.play_uri('http://stream.sunshine-live.de/live/mp3-192', title='Sunshine Live', force_radio=True)\\n return \\\"Ok\\\"\",\n \"def download_archive(self):\\n\\n def time_convert(structure):\\n \\\"\\\"\\\"\\n :param structure: tuple representation of time\\n :return: GitHub archive time\\n \\\"\\\"\\\"\\n \\n \\n join_number_to_zero = lambda number: (\\\"\\\" if number > 9 else \\\"0\\\") + str(number)\\n\\n return \\\"%s-%s-%s-%s\\\" % (\\n structure.tm_year, join_number_to_zero(structure.tm_mon), join_number_to_zero(structure.tm_mday),\\n structure.tm_hour)\\n\\n current_time = self.get_time()\\n self.logger.debug(__name__ + \\\": \\\" + \\\"current time: \\\" + str(gmtime(current_time)))\\n\\n difference = -25200\\n #timezone difference in seconds between GMT and west coast of USA\\n\\n downloading_time = int(timegm(self.config[\\\"last_connection_time\\\"])) + 3600\\n self.logger.debug(__name__ + \\\": \\\" + \\\"downloading time: \\\" + str(gmtime(downloading_time)))\\n\\n if downloading_time > current_time - 7200:\\n self.logger.info(__name__ + \\\": \\\" + \\\"unable to download file (time limiting).\\\")\\n return\\n\\n downloading_time += difference\\n\\n json_file_name = self.download_file(time_convert(gmtime(downloading_time)))\\n\\n self.config[\\\"last_connection_time\\\"] = gmtime(downloading_time - difference)\\n self.logger.debug(__name__ + \\\": \\\" + \\\"last_connection_time: \\\" + str(self.config[\\\"last_connection_time\\\"]))\\n\\n return json_file_name\",\n \"def download(self):\\r\\n \\r\\n # RAR Files names\\r\\n if self.debug==0:\\r\\n rar_files_name = [\\\"K001.rar\\\",\\\"K002.rar\\\",\\\"K003.rar\\\",\\\"K004.rar\\\",\\\"K005.rar\\\",\\\"K006.rar\\\",\\r\\n \\\"KA01.rar\\\", \\\"KA03.rar\\\", \\\"KA04.rar\\\", \\\"KA05.rar\\\", \\\"KA06.rar\\\", \\\"KA07.rar\\\", \\r\\n \\\"KA08.rar\\\", \\\"KA09.rar\\\", \\\"KA15.rar\\\", \\\"KA16.rar\\\", \\\"KA22.rar\\\", \\\"KA30.rar\\\", \\r\\n \\\"KB23.rar\\\", \\\"KB24.rar\\\", \\\"KB27.rar\\\", \\r\\n \\\"KI01.rar\\\", \\\"KI03.rar\\\", \\\"KI04.rar\\\", \\\"KI05.rar\\\", \\\"KI07.rar\\\", \\\"KI08.rar\\\", \\r\\n \\\"KI14.rar\\\", \\\"KI16.rar\\\", \\\"KI17.rar\\\", \\\"KI18.rar\\\", \\\"KI21.rar\\\"]\\r\\n else:\\r\\n rar_files_name = [\\\"K002.rar\\\", \\\"KA01.rar\\\", \\\"KI01.rar\\\"]\\r\\n\\r\\n url = self.url\\r\\n \\r\\n dirname = self.rawfilesdir\\r\\n dir_rar = \\\"rar_files\\\"\\r\\n if not os.path.isdir(dirname):\\r\\n os.mkdir(dirname)\\r\\n if not os.path.isdir(os.path.join(dirname, dir_rar)):\\r\\n os.mkdir(os.path.join(dirname, dir_rar))\\r\\n \\r\\n\\r\\n print(\\\"Downloading RAR files:\\\")\\r\\n for i in rar_files_name:\\r\\n file_name = i\\r\\n if not os.path.exists(os.path.join(dirname, dir_rar, file_name)):\\r\\n urllib.request.urlretrieve(url+file_name, os.path.join(dirname, dir_rar, file_name))\\r\\n print(file_name)\\r\\n \\r\\n print(\\\"Extracting files:\\\")\\r\\n for i in rar_files_name:\\r\\n if not os.path.exists(os.path.join(dirname, i[:4])):\\r\\n file_name = os.path.join(dirname, dir_rar, i)\\r\\n Archive(file_name).extractall(dirname) \\r\\n print(i)\\r\\n\\r\\n if self.debug==0:\\r\\n files_path = self.files\\r\\n else:\\r\\n files_path = files_debug(self.rawfilesdir)\\r\\n\\r\\n print(files_path)\\r\\n self.files = files_path\",\n \"def retrieve_tla(extension, username=None, password=None, pagelimit=999999):\\n\\n if extension != 'eaf':\\n print(\\\"currently, only eaf downloads are supported for TLA\\\")\\n return\\n TLA_LIMIT = 5000 #there are currently 35k ELAN files in TLA\\n #base_url = \\\"\\\"\\\"https://archive.mpi.nl/tla/islandora/search/*%3A*?f[0]=cmd.Format%3A\\\"%s\\\"&f[1]=-cmd.Country%3A\\\"Netherlands\\\"&f[2]=-cmd.Country%3A\\\"Belgium\\\"&f[3]=-cmd.Country%3A\\\"Germany\\\"&limit=%i\\\"\\\"\\\"%(mimetype, TLA_LIMIT)\\n #https://archive.mpi.nl/tla/islandora/search/%2A%3A%2A?page=2&f%5B0%5D=cmd.Format%3A%22text/x-eaf%2Bxml%22&islandora_solr_search_navigation=0&sort=fgs_label_s%20asc&limit=500\\n login_url = \\\"https://archive.mpi.nl/tla/user/login\\\"\\n if username and password:\\n pass\\n else:\\n username = input(\\\"Enter user name for TLA: \\\\n\\\")\\n password = getpass(\\n \\\"Your password will only be used for this login session and not be stored anywhere.\\\\n Enter password for TLA: \\\\n\\\"\\n )\\n with requests.Session() as s:\\n #login\\n print(\\\"retrieving collections\\\")\\n s = requests.Session()\\n un_name = \\\"name\\\"\\n pw_name = \\\"pass\\\"\\n values = {\\n un_name: username.strip(),\\n pw_name: password,\\n \\\"op\\\": \\\"Log+in\\\",\\n \\\"form_id\\\": \\\"user_login\\\",\\n }\\n s.post(login_url, data=values)\\n session_id = s.cookies.get_dict().get(\\\"SESSd8112b76bc7d4802dc104c36df341519\\\")\\n print(session_id)\\n #get pages quantity\\n collection_urls = []\\n tla_mime = \\\"text/x-eaf%2Bxml\\\"\\n country_restrictors = \\\"f%5B1%5D=-cmd.Country%3A%22Netherlands%22&f%5B2%5D=-cmd.Country%3A%22Belgium%22&f%5B3%5D=-cmd.Country%3A%22Germany%22&\\\"\\n resultpages = [\\\"https://archive.mpi.nl/tla/islandora/search/%%2A%%3A%%2A?page=%i&f%%5B0%%5D=cmd.Format%%3A%%22%s%%22&%slimit=%i\\\"%(i, tla_mime, country_restrictors, TLA_LIMIT) for i in range(5)]\\n #retrieve collections from resultpages\\n for resultpage in resultpages[:pagelimit]:\\n print(resultpage)\\n #base_request = s.get(resultpage)\\n #base_html = base_request.text\\n #base_root = fromstring(base_html)\\n base_root = url2root(s, resultpage)\\n collection_links = base_root.findall('.//dd[@class=\\\"solr-value cmd-title\\\"]/a')\\n new_collection_urls = [\\n \\\"https://archive.mpi.nl/%s\\\" % a.attrib[\\\"href\\\"] for a in collection_links\\n ]\\n print(len(new_collection_urls), \\\"new urls\\\")\\n collection_urls += new_collection_urls\\n collection_length = len(collection_urls)\\n print(len(collection_urls), \\\"collections\\\")\\n OFFSET = 0\\n #OFFSET = 3390\\n #retrieve file links from collections\\n for i, c_url in enumerate(collection_urls[OFFSET:]):\\n #print(\\\"collection \\\", c_url)\\n collection_id = c_url.split(\\\"%3A\\\")[-1]\\n print(collection_id, \\\"%i(+%i)/%i\\\"%(i+1, OFFSET, collection_length))\\n #c_request = s.get(c_url)\\n #c_html = c_request.text\\n #c_root = fromstring(c_html)\\n c_root = url2root(s, c_url)\\n file_links = c_root.findall('.//a[@class=\\\"flat-compound-caption-link\\\"]')\\n file_tuples = [\\n (a.attrib[\\\"href\\\"],\\n a.text,\\n a.getparent().getparent().find('div[@class=\\\"flat-compound-buttons\\\"]/div[@class=\\\"permission-labels\\\"]').find('span').text)\\n for a in file_links\\n if a.text is not None\\n and a.text.endswith(extension)\\n ]\\n #download files\\n for file_tuple in file_tuples:\\n # print(\\\" f: \\\", file_tuple)\\n f_url, filename, access = file_tuple\\n tla_eaf_id = f_url.split('/')[-1]\\n local_basename = '.'.join((tla_eaf_id, extension))\\n if access.strip() == 'Restricted':\\n print(' %s: no access' % f_url)\\n else:\\n download_url = \\\"https://archive.mpi.nl/%s/datastream/OBJ/download\\\" % f_url\\n filepath = os.path.join('tla', collection_id, local_basename)\\n print(\\\" downloading %s as %s:\\\" % (download_url, filepath))\\n os.makedirs(os.path.dirname(filepath), exist_ok=True)\\n save_file(s, filepath, download_url, {\\\"SESSd8112b76bc7d4802dc104c36df341519\\\": session_id})\",\n \"def connect(self):\\n self.conn = self.protocol(self.url.host, 'anonymous', '', timeout=self.timeout)\\n self.conn.voidcmd('TYPE I')\\n self.conn.cwd(self.url.path)\\n self.conn.voidcmd('PASV')\\n file_size = self.conn.size(self.url.filename)\\n return TaskHeadData(self.url.host, 200, file_size) # set the code 200 for compatibility with HTTP\",\n \"def dascasi_download():\\n p = argparse.ArgumentParser(description=\\\"download DASC all-sky camera data\\\")\\n p.add_argument(\\\"site\\\", choices=[\\\"EAA\\\", \\\"FYU\\\", \\\"KAK\\\", \\\"PKR\\\", \\\"TOO\\\", \\\"VEE\\\"])\\n p.add_argument(\\n \\\"startend\\\", help=\\\"start/end times UTC e.g. 2012-11-03T06:23 2012-11-03T07\\\", nargs=2\\n )\\n p.add_argument(\\\"odir\\\", help=\\\"directory to write downloaded FITS to\\\")\\n p.add_argument(\\\"-w\\\", \\\"--wavelen\\\", help=\\\"request specific wavelength(s)\\\", nargs=\\\"+\\\")\\n p.add_argument(\\\"-host\\\", default=\\\"ftp://optics.gi.alaska.edu\\\")\\n p = p.parse_args()\\n\\n # host = \\\"ftp://mirrors.arsc.edu/AMISR/PKR/DASC/RAW/\\\"\\n download(p.startend, p.site, p.odir, p.host, p.wavelen)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6728568","0.6727653","0.63100266","0.60740006","0.5940395","0.5809924","0.5798153","0.56826454","0.5632426","0.560139","0.55641836","0.5529447","0.53975224","0.5332132","0.5298177","0.5249126","0.520643","0.5179963","0.51734734","0.51577014","0.5155442","0.51006067","0.5069311","0.50593686","0.50466186","0.5038289","0.502039","0.50190693","0.50184596","0.501773","0.501743","0.50038755","0.50017476","0.49909922","0.49885088","0.49853498","0.49756926","0.4967387","0.49654606","0.49466094","0.49359575","0.493419","0.49278715","0.49220318","0.48757362","0.48679575","0.48473328","0.48451403","0.48444918","0.48435795","0.48337632","0.48183417","0.48088136","0.48054802","0.48013884","0.4795224","0.4794421","0.4790557","0.47812724","0.47787714","0.47774017","0.47768024","0.4775967","0.477546","0.47689202","0.47575232","0.47572172","0.47517276","0.4749333","0.4740446","0.47315624","0.4692781","0.46881944","0.4679196","0.4679163","0.46790582","0.46709973","0.4668023","0.46650684","0.46619081","0.4661506","0.46584854","0.46579358","0.46540466","0.4641902","0.4639148","0.463568","0.46343824","0.4628731","0.46280822","0.46224082","0.46132463","0.4612247","0.46099508","0.4603214","0.46021903","0.460076","0.45970413","0.45958304","0.45936006"],"string":"[\n \"0.6728568\",\n \"0.6727653\",\n \"0.63100266\",\n \"0.60740006\",\n \"0.5940395\",\n \"0.5809924\",\n \"0.5798153\",\n \"0.56826454\",\n \"0.5632426\",\n \"0.560139\",\n \"0.55641836\",\n \"0.5529447\",\n \"0.53975224\",\n \"0.5332132\",\n \"0.5298177\",\n \"0.5249126\",\n \"0.520643\",\n \"0.5179963\",\n \"0.51734734\",\n \"0.51577014\",\n \"0.5155442\",\n \"0.51006067\",\n \"0.5069311\",\n \"0.50593686\",\n \"0.50466186\",\n \"0.5038289\",\n \"0.502039\",\n \"0.50190693\",\n \"0.50184596\",\n \"0.501773\",\n \"0.501743\",\n \"0.50038755\",\n \"0.50017476\",\n \"0.49909922\",\n \"0.49885088\",\n \"0.49853498\",\n \"0.49756926\",\n \"0.4967387\",\n \"0.49654606\",\n \"0.49466094\",\n \"0.49359575\",\n \"0.493419\",\n \"0.49278715\",\n \"0.49220318\",\n \"0.48757362\",\n \"0.48679575\",\n \"0.48473328\",\n \"0.48451403\",\n \"0.48444918\",\n \"0.48435795\",\n \"0.48337632\",\n \"0.48183417\",\n \"0.48088136\",\n \"0.48054802\",\n \"0.48013884\",\n \"0.4795224\",\n \"0.4794421\",\n \"0.4790557\",\n \"0.47812724\",\n \"0.47787714\",\n \"0.47774017\",\n \"0.47768024\",\n \"0.4775967\",\n \"0.477546\",\n \"0.47689202\",\n \"0.47575232\",\n \"0.47572172\",\n \"0.47517276\",\n \"0.4749333\",\n \"0.4740446\",\n \"0.47315624\",\n \"0.4692781\",\n \"0.46881944\",\n \"0.4679196\",\n \"0.4679163\",\n \"0.46790582\",\n \"0.46709973\",\n \"0.4668023\",\n \"0.46650684\",\n \"0.46619081\",\n \"0.4661506\",\n \"0.46584854\",\n \"0.46579358\",\n \"0.46540466\",\n \"0.4641902\",\n \"0.4639148\",\n \"0.463568\",\n \"0.46343824\",\n \"0.4628731\",\n \"0.46280822\",\n \"0.46224082\",\n \"0.46132463\",\n \"0.4612247\",\n \"0.46099508\",\n \"0.4603214\",\n \"0.46021903\",\n \"0.460076\",\n \"0.45970413\",\n \"0.45958304\",\n \"0.45936006\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.62584805"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":92979,"cells":{"query":{"kind":"string","value":"Downloaded XML string isn't compatybil with XML standard in which minidom is written."},"document":{"kind":"string","value":"def Correct_MultiRoot_XML(self):\n if self.XML_String[0] == \"\\n\":\n self.XML_String=self.XML_String[1:]\n SECONDLINE_CHAR = 0\n for x in self.XML_String:\n SECONDLINE_CHAR = SECONDLINE_CHAR+1\n if x ==\"\\n\":\n break\n self.XML_String = self.XML_String[0:SECONDLINE_CHAR] + \"<lista>\"+ self.XML_String[(SECONDLINE_CHAR+1):]+\"</lista>\"\n\tself.XML_String = re.sub(\"&\", \"and\", self.XML_String)\n\tself.XML_String = self.XML_String.decode(\"CP1252\").encode(\"UTF-8\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_with_no_encoding(self):\n xml = (\n u'<?xml version=\"1.0\"?>'\n u'<DocRoot>'\n u'<Elem1>默认جذ</Elem1>'\n u'<Elem2/>'\n u'</DocRoot>'\n )\n io_string = six.StringIO()\n self.builder.dom_element.write_doc(io_string, encoding=None)\n # NOTE Exact test, no encoding of comparison XML doc string\n self.assertEqual(xml, io_string.getvalue())","def get_xml(self):\n with io.StringIO() as string:\n string.write(ET.tostring(self.root, encoding=\"unicode\"))\n return string.getvalue()","def xml_string(self):\r\n if self._xml_string is not None:\r\n return self._xml_string\r\n\r\n return etree.tostring(self._xml_node)","def xml_string(self):\n if self._xml_string is not None:\n return self._xml_string\n\n return etree.tostring(self._xml_node)","def prettify(elem):\n #print(\"prettify function: rough_string:\")\n rough_string = ET.tostring(elem, 'utf-8')\n \n #print(rough_string)\n #print(type(rough_string)) #bytes\n new_rough_string = rough_string.replace(b'\\n', b'')\n new_rough_string = rough_string.replace(b'\\t', b'')\n #print(new_rough_string)\n '''\n testStr = str(rough_string)\n print(type(testStr)) #str\n testBytes = testStr.encode('utf-8')\n print(type(testBytes))\n print(testBytes)\n fakeparse = minidom.parseString(testBytes)\n testStr = testStr.replace('\\n', '')\n lessRoughString = testStr.encode('utf-8')\n print(type(lessRoughString)) #bytes\n '''\n reparsed = minidom.parseString(new_rough_string)\n #print(type(reparsed))\n return reparsed.toprettyxml(indent='\\t', newl='')","def make_request_xml(self):\n #print (self.url)\n try:\n with closing(get(self.url, stream=True)) as resp: #returns b`xml`\n if self.is_good_enough_xml(resp):\n return resp.content\n else:\n return None\n except RequestException as e:\n print('Error during requests to {0} : {1}'.format(url, str(e)))\n return None","def exportXml ( w, xml ):\n assert str ( type ( xml ) ) == \"<type 'str'>\"\n rawText = xml\n pattern = re.compile (r'[^\\S ]+')\n text = re.sub ( pattern, \"\", rawText )\n reparsed = MD.parseString ( text )\n w.write ( reparsed.toprettyxml ( indent = \"\\t\", encoding = \"UTF-8\" ) )","def test_write_defaults(self):\n xml = (\n u'<?xml version=\"1.0\" encoding=\"utf-8\"?>'\n u'<DocRoot>'\n u'<Elem1>默认جذ</Elem1>'\n u'<Elem2/>'\n u'</DocRoot>'\n )\n io_string = six.StringIO()\n self.builder.write_doc(io_string)\n if six.PY2:\n self.assertEqual(xml.encode('utf-8'), io_string.getvalue())\n else:\n self.assertEqual(xml, io_string.getvalue())","def toString(doc):\n return doc.toxml()","def saveXml(self, buf: java.lang.StringBuilder) -> None:\n ...","def _readXMLfragment(self) -> str:\n\t\tself._check()\n\t\tself._raven.reset_output_buffer()\n\t\tself._raven.reset_input_buffer()\n\t\tfirst_char = self._raven.read()\n\t\twhile (first_char == 0 or first_char == b' '):\n\t\t\tfirst_char = self._raven.read()\n\t\tif (first_char != b'<'):\n\t\t\tself._clear()\n\t\t\traise InvalidFormat('INVALID CHAR: {}'.format(first_char))\n\t\tstart_tag = first_char\n\t\tresult = ''\n\t\twhile (start_tag[-1] != 62):\n\t\t\tchar = self._raven.read()\n\t\t\tif len(char) == 0:\n\t\t\t\traise Exception('No data')\n\t\t\tstart_tag += char\n\t\tstart_tag = start_tag.decode('ascii').strip('\\x00')\n\t# Debugging\n\t#\tprint(start_tag)\n\t\tif \"/\" in start_tag:\n\t\t\traise InvalidFormat('\"/\" detected in XML starting tag')\n\t\tresult = start_tag\n\t\tend_tag = start_tag[0] + '/' + start_tag[1:] \n\t\tend_tag_len = len(end_tag)\n\t\twhile (result[-end_tag_len:] != end_tag):\n\t\t\tchar = self._raven.read()\n\t\t\tif len(char) == 0:\n\t\t\t\traise Exception('No data')\n\t\t\tresult += char.decode('ascii')\n\t\ttry:\n\t\t\treturn ET.fromstring(result)\n\t\texcept:\n\t\t\traise InvalidFormat","def downloadXML(url): \n request=NSURLRequest.requestWithURL_(NSURL.URLWithString_(url))\n (data, response, error)= NSURLConnection.sendSynchronousRequest_returningResponse_error_(request)\n return data","def xml(string, token=[WORD, POS, CHUNK, PNP, REL, ANCHOR, LEMMA]):\n return Text(string, token).xml","def xml(self):\n return lxml.etree.fromstring(self.content, _XML_PARSER)","def write(self):\n temp_string = minidom.parseString(ET.tostring(self.root)).toprettyxml(encoding=\"UTF-8\")\n with open(self.xml_file, 'w') as f:\n f.write(temp_string)\n # f = open(self.xml_file, \"w\")\n # f.write(temp_string)\n # f.close()","def _load(self, source):\n\n sock = toolbox.openAnything(source)\n xmldoc = minidom.parse(sock).documentElement\n sock.close()\n return xmldoc","def strtoxml(s):\n return s.replace('&','&').replace('\"', '"').replace('<','<').replace('>','>')","def xml(self):\n rough_string = ElementTree.tostring(self.dom, \"utf-8\")\n reparsed = minidom.parseString(rough_string)\n return reparsed.toprettyxml(indent=\" \")","def beautify_xml(XML):\n # convert XML file to modifiable string to beautify it\n text_string = ET.tostring(XML, encoding='UTF-8', method='xml')\n \n # insert line breaks before end of file tag\n file_string = text_string.replace('</aardvark>', '\\n\\n</aardvark>')\n \n # insert double new line before comments to create\n # blocks for each command\n file_string = file_string.replace('<!', '\\n\\n<!')\n \n # insert new line between each set of XML tags\n file_string = file_string.replace('><', '>\\n\\t<')\n \n # remove header\n # file_string = file_string.replace('<?xml version=\\'1.0\\' encoding=\\'utf8\\'?>\\n', '') \n \n return file_string","def getxml(url, **kwargs):\n xml = fetch_resource(url, **kwargs)\n return etree.fromstring(xml)","def __str__(self):\n result = xml.dom.minidom.parseString(\n xml.etree.ElementTree.tostring(\n self.ToXMLElement(), encoding='utf-8')).toprettyxml(indent=' ')\n\n return result","def to_xml(self, enc='utf-8'):\n return b\"\"\"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<!DOCTYPE GIFTI SYSTEM \"http://www.nitrc.org/frs/download.php/115/gifti.dtd\">\n\"\"\" + xml.XmlSerializable.to_xml(self, enc)","def stringToXML(self, unparsedXML):\n xmlRoot = ET.fromstring(unparsedXML)\n self.xmlRoot = xmlRoot\n return xmlRoot","def parse_string(s):\n return XmlWrapper(minidom.parseString(s))","def saveToXml(self) -> org.jdom.Element:\n ...","def _clean_xml(raw: str) -> str:\n a = raw.encode(\"ascii\", \"ignore\").decode(\"ascii\")\n no_encoding = _strip_encoding(a)\n no_ns = _strip_namespace(no_encoding)\n return no_ns","def example_xml43(example_xml_file41):\n return etree.fromstring(example_xml_file43.encode('utf-8'))","def test_parse_xml():\r\n\r\n url = 'http://firds.esma.europa.eu/firds/DLTINS_20210117_01of01.zip'\r\n\r\n assert url == parse_xml()","def new_xml(self, root_name):\n\n self.tree = ET.ElementTree(ET.fromstring('<?xml version=\"1.0\" encoding=\"UTF-8\"?><%s></%s>'%(\n root_name, root_name)))\n return self.tree.getroot()","def get_xml(self):\n return etree.tostring(self.get_etree())","def parsexml(self):\n raise NotImplementedError","def get_xml_string(stream_pointer):\n # This function avoid stream_pointer.seek() for the vast majority\n # of cases (when xml is formatted correctly) just because i don't\n # like using 'seek' (never know when you're getting non-rewindable \n # streams\n c = stream_pointer.read(1)\n count = 0\n while c != '<' and c != '':\n count = count + 1\n c = stream_pointer.read(1)\n if c == '':\n stream_pointer.seek(0)\n logging.error(\"Poorly formatted schema - no '<' found\", \\\n extra={'xml':stream_pointer.read()})\n return\n xml_string = \"<\" + stream_pointer.read()\n if count > 0:\n stream_pointer.seek(0)\n logging.error(\"Poorly formatted schema\", \\\n extra={'xml':stream_pointer.read()}) \n return xml_string","def xml(self):\n raise NotImplementedError('This api does not return xml')","def read(self, return_string=False):\r\n # Get result data from debugger engine and verify length of response\r\n data = self.read_data()\r\n\r\n # Show debug output\r\n debug('[Response data] %s' % data)\r\n\r\n # Return data string\r\n if return_string:\r\n return data\r\n\r\n # Remove special character quoting\r\n data = self.unescape(data)\r\n\r\n # Replace invalid XML characters\r\n data = ILLEGAL_XML_RE.sub('?', data)\r\n\r\n # Create XML document object\r\n document = ET.fromstring(data)\r\n return document","def example_xml41(example_xml_file41):\n return etree.fromstring(example_xml_file41.encode('utf-8'))","def example_xml42(example_xml_file41):\n return etree.fromstring(example_xml_file42.encode('utf-8'))","def xml_decode(string):\n string = string.replace(\"&\", \"&\")\n string = string.replace(\"<\", \"<\")\n string = string.replace(\">\", \">\")\n string = string.replace(\""\",\"\\\"\")\n string = string.replace(\"/\", SLASH)\n return string","def parse_xml_str(self, data):\n try:\n dom = parseString(data)\n process_includes(dom)\n except ExpatError, x:\n raise EzXMLError(\"Failed to parse: %s\" % x)\n return self.walkdom(dom.documentElement)","def test_xml_direct(self): \n response = client.result(True, 'xml', 'unittest', test_data = self.test_data)\n root = ET.fromstring(response)\n first_name = root[0][0][0].text\n self.assertEqual(first_name,'John', 'Should print John')\n nationality = '<nationality>' in response\n self.assertFalse(nationality, 'Nationality should not be present')","def toxml(self) :\n\t\treturn self.doc.toxml()","def ConvertFromXML (given_xml_string) :\r\n stream_thing = cStringIO.StringIO(given_xml_string)\r\n return ReadFromXMLStream(stream_thing)","def ler_arquivo_xml(self, diretorio):\r\n with open(diretorio, 'r') as fxml:\r\n\t strfx = fxml.readlines()\r\n\t string = \"\".join(strfx).replace(\"&\",\" e \")\r\n return string","def example_xml40(example_xml_file40):\n return etree.fromstring(example_xml_file40.encode('utf-8'))","def load_xml(pmid, sleep=None):\n link = \"https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&retmode=xml&id=%s\" % str(pmid) + \"&api_key=\" + API_KEY\n print(link)\n page = requests.get(link)\n tree = html.fromstring(page.content)\n if sleep is not None:\n time.sleep(sleep)\n return tree","def xml(self):\n return self._xml","def xml(self):\n return self._xml","def content_api_xml(url, request):\n headers = {'content-type': 'application/xml'}\n content = 'xml string'\n return response(status_code=200,\n content=content,\n headers=headers,\n request=request)","def serialize(self):\n return self.xmlnode.serialize(encoding=\"utf-8\")","def parse_xml():\r\n\r\n fileXml = read_file('feed.xml')\r\n\r\n doc = fileXml['response']['result']['doc'][0]\r\n\r\n for string in doc['str']:\r\n if string['@name'] == \"download_link\":\r\n downloadLink = string['#text']\r\n else:\r\n logging.error('Download link not found')\r\n\r\n return downloadLink","def load_xml(pmid, sleep=None):\r\n link = \"https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&retmode=xml&id=%s\" % str(pmid) \r\n page = requests.get(link) \r\n tree = html.fromstring(page.content)\r\n if sleep is not None:\r\n time.sleep(sleep)\r\n return tree","def xml(self):\n return parse_xml(self, tab=\"\\t\", id=self.id or \"\")","def cleanXML(aString):\n\treturn re.sub(\"\\s+\", \" \", _xmlJunkPat.sub('', aString)).strip(\n\t\t).replace(\" />\", \"/>\").replace(\" >\", \">\")","def xmldoc(self, doctype):\n # we hack in the DOCTYPE using the parser\n docstr = \"\"\"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n <!DOCTYPE %s SYSTEM \"file:///usr/share/emane/dtd/%s.dtd\">\n <%s/>\"\"\" % (doctype, doctype, doctype)\n # normally this would be: doc = Document()\n return parseString(docstr)","def xml_pretty(xml_string):\n return xml_string # xml.dom.minidom.parseString(xml_string).toprettyxml()","def docType():\n return (u'<?xml version=\"1.0\" encoding=\"UTF-8\"?>\\n'\n u'<!DOCTYPE html PUBLIC \"-//W3C//DTD XHTML 1.0 '\n u'Transitional//EN\" '\n u'\"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd\">\\n')","def _parse_xml(self, response):\n if response.startswith('\\n'):\n response = response[1:]\n tree = etree.fromstring(response)\n return tree","def test_incomplete_xml_no_timestamp(self):\n self.__opener.contents = '<Report><Doc><Summary/></Doc></Report>'\n self.assertEqual(datetime.datetime.min, self.__uft.datetime('url'))","def str_to_v2_str(xml_str):\n if str_is_v2(xml_str):\n return xml_str\n etree_obj = str_to_etree(xml_str)\n etree_replace_namespace(etree_obj, v2_0.Namespace)\n return etree_to_str(etree_obj)","def test_fixed_xml_tag(self):\r\n\r\n # create a error tag with valid xml contents\r\n root = etree.Element('error')\r\n good_xml = '''<sequential display_name=\"fixed\"><video url=\"hi\"/></sequential>'''\r\n root.text = good_xml\r\n\r\n xml_str_in = etree.tostring(root)\r\n\r\n # load it\r\n system = self.get_system()\r\n descriptor = system.process_xml(xml_str_in)\r\n\r\n # export it\r\n node = etree.Element('unknown')\r\n descriptor.add_xml_to_node(node)\r\n\r\n # Now make sure the exported xml is a sequential\r\n self.assertEqual(node.tag, 'sequential')","def read(self) -> str:\n\t\treturn self._readXMLfragment()","def unpack_xml(text) -> ET.ElementTree:\n etree: ET.ElementTree = ET.parse(io.StringIO(text))\n _check_for_errors(etree)\n return etree","def xml(self):\n raise NotImplementedError('must be implemented by all subclasses')","def test_raw_feed(self):\n self.assertEqual(self.feed.feed.raw[:6].decode('utf-8'), \"<?xml \")","def get_str_from_xml_tag( xml_object , tag ):\n # get it\n results = xml_object.getElementsByTagName( tag )\n \n # convert to string\n L = len( tag )\n results = [i.toxml()[L + 2:-(L + 3)].strip() for i in results]\n \n return results","def MakeTextXMLReady(text):\n dec_text = DecodeNonASCIIText(text)[0]\n items = []\n for char in dec_text:\n try:\n char = char.encode('ascii')\n except UnicodeEncodeError:\n # We have a non-ASCII character of type unicode. Convert it into an\n # XML-ready format.\n try:\n str(char)\n char.encode('utf-8')\n except UnicodeEncodeError:\n char = '%s;' % hex(ord(char)).replace('0x', '&#x')\n items.append(char)\n return ''.join(items)","def getXmlTree(url):\n return lxml.etree.parse(url)","def getxml(self, pmcid):\n import requests\n r = requests.get(\n (self.xmlurl).format(pmcid=pmcid))\n return r.content","def toXMLString(self):\n return _libsbml.XMLNode_toXMLString(self)","def test_default_indent_and_newline(self):\n self.builder.dom_element.write_doc(self.iobytes, indent=True)\n self.assertEqual(\n u'<?xml version=\"1.0\" encoding=\"utf-8\"?>\\n'\n u'<DocRoot>\\n'\n u' <Elem1>默认جذ</Elem1>\\n'\n u' <Elem2/>\\n'\n u'</DocRoot>\\n'.encode('utf-8'),\n self.iobytes.getvalue())","def test_something(self):\n self.assertEqual(\n b\"\"\"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\\n<Foo>bar</Foo>\"\"\",\n self.successResultOf(to_xml(tags.Foo(\"bar\"))),\n )","def xml_to_text(xml_string, node_name='text'):\n # import xml.etree.ElementTree as ET\n root = ET.fromstring(xml_string)\n return_string = u\"\"\n for node in root.iter(node_name):\n if node.text is None:\n pass\n else:\n return_string = u\"\".join([return_string, unicode(node.text)])\n return return_string","def str_to_v1_str(xml_str):\n if str_is_v1(xml_str):\n return xml_str\n etree_obj = str_to_etree(xml_str)\n strip_v2_elements(etree_obj)\n etree_replace_namespace(etree_obj, v1_0.Namespace)\n return etree_to_str(etree_obj)","def xml(self, request):\n raise Exception(\"Not Implemented\")","def getIdentifierMetaXML(base_url, identifier):\n\n\tquery_url = base_url + \"/meta/\" + urllib.quote_plus(identifier)\n\tprint(\"\\t\\t%s\" % query_url)\n\n\ttry:\n\t\trequest = urllib2.urlopen(query_url)\n\t\tresponse = request.read()\n\t\tresponse_xml = ET.fromstring(response)\n\texcept:\n\t\tprint \"\\t\\tFailed request: %s\" % query_url\n\t\tresponse_xml = None\n\n\treturn response_xml","def saving_file(xml):\r\n\r\n xml_string = etree.tostring(xml)\r\n parsed = minidom.parseString(xml_string)\r\n with open(self.app_path + \"\\\\temp_\\\\\" + file_name + \".xml\", \"w\") as file:\r\n file.write(parsed.toprettyxml(indent=\" \"))","def to_string(root: ElementTree.Element) -> str:\n return ElementTree.tostring(root, encoding=\"unicode\", method=\"xml\").replace(\n \"\\n\", \"\\r\\n\"\n )","def __str__(self):\n if self.hocr is None:\n return ''\n body = self.hocr.find(\".//%sbody\"%(self.xmlns))\n if body:\n return self._get_element_text(body).encode('utf-8') # XML gives unicode\n else:\n return ''","def get_xml(codetoget):\n\txmlfilename = ''\n\ttry:\n\t\tTrainingComponentDetailsRequest= client.factory.create('TrainingComponentDetailsRequest')\n\t\tTrainingComponentDetailsRequest.Code=codetoget\n\t\tTrainingComponentInformationRequested=client.factory.create('TrainingComponentInformationRequested')\n\t\tTrainingComponentInformationRequested.ShowReleases=True\n\t\tTrainingComponentInformationRequested.ShowUnitGrid=True\n\t\tTrainingComponentInformationRequested.ShowFiles=True\n\t\tTrainingComponentInformationRequested.ShowComponents=True\n\t\tTrainingComponentDetailsRequest.InformationRequest=TrainingComponentInformationRequested\n\t\ttry:\n\t\t\tresult= client.service.GetDetails(TrainingComponentDetailsRequest)\n\t\t\t#print result\n\t\t\tfor unit in result.Releases[0]:\n\t\t\t\ttry:\n\t\t\t\t\tfor fyle in unit.Files.ReleaseFile:\n\t\t\t\t\t\t#print fyle.RelativePath\n\t\t\t\t\t\tfname = fyle.RelativePath.strip()\n\t\t\t\t\t\tfname = fname.lower()\n\t\t\t\t\t\t#sys.stderr.write(\"\\nfile: (%s)\" % (fname)) \n\t\t\t\t\t\tif fname[-4:]==\".xml\":\n\t\t\t\t\t\t\tstrFile=fyle.RelativePath\n\t\t\t\t\t\t\txmlfilename = strFile\n\t\t\t\t\t\t\tif os.path.exists(os.path.join(xmlfolder, strFile))==False:\n\t\t\t\t\t\t\t\tsys.stderr.write('downloading ' + strFile + '\\n')\n\t\t\t\t\t\t\t\turllib.urlretrieve(xmlbaseurl + urllib.quote(strFile), os.path.join(xmlfolder, strFile))\n\t\t\t\t\t\t\t\tshutil.copyfile(os.path.join(xmlfolder, strFile), os.path.join('newfiles', strFile))\n\t\t\t\t\t\t\t\treturn xmlfilename\n\t\t\t\t\t\t\telse: # file already there\n\t\t\t\t\t\t\t\treturn xmlfilename\n\t\t\t\t\t\t# if you didn't find an xml file just return an empty string\n\t\t\t\t\treturn ''\n\t\t\t\texcept:\n\t\t\t\t\treturn ''\n\t\texcept:\n\t\t\treturn ''\n\texcept WebFault, e:\n\t\tsys.stderr.write(\"soap request failed: \" + e)\n\t\treturn \"\"","def normalize_xml(xml):\n if not xml:\n return u''\n if isinstance(xml, unicode):\n xml = xml.encode('utf-8')\n xml = xml.replace('\\r\\n', '\\n')\n return xml","def tostring(self):\n header, body = None, None\n\n if self._header:\n header = b'<?xml version=\"1.0\" encoding=\"utf-8\"?>'\n\n if self._main() is not None:\n body = ET.tostring(self._main(), 'utf-8')\n\n return (header if header else b'') + (body if body else b'')","def restoreFromXml(self, root: org.jdom.Element) -> None:\n ...","def ParseXMLFile(file):\n\n\tstring = \"\";\n\n\t# reads in the dom structure\n\tdom = parse(file);\t\n\n\t# generate touples\n\tfor node in dom.getElementsByTagName('string'): \n\t\tstring = node.firstChild.nodeValue;\n\t\n\tprint (\"XML File: \", file);\n\tprint (\"String: \", string);\n\n\treturn string;","def convertXMLNodeToString(*args):\n return _libsbml.XMLNode_convertXMLNodeToString(*args)","def doc(self):\n\n if not hasattr(self, \"_doc\"):\n self.loader.cdr_cursor.execute(self.SELECT_XML, self.id)\n xml = self.loader.cdr_cursor.fetchone().xml\n self._doc = etree.fromstring(xml.encode(\"utf-8\"))\n return self._doc","def get_dom(self, text):\n from xml.dom import minidom\n \n dom = minidom.parseString(text)\n \n return dom","def test_01_FindXml(self):","def restoreXML(self, parser: ghidra.xml.XmlPullParser) -> None:\n ...","def xml_to_string(xml, encode_base64=True):\n xml_string = etree.tostring(xml, xml_declaration=True, encoding='utf-8', pretty_print=True)\n if encode_base64:\n return base64.standard_b64encode(xml_string)\n return xml_string","def _make_string(self, filename):\n\n if not os.path.isfile(filename):\n str = \"ERROR: Could not find specified XML file %s.\" % filename\n PRINT.info(str)\n raise OSError(str)\n\n return open(filename).read()","def read_xml(self):\n pass","def parse_string(self, xml_url):\n if len(xml_url) == 0:\n raise BadURL(\"An empty string is not a valid URL.\")\n try:\n dom = parseString(xml_url).firstChild\n self.parse_element(dom)\n dom.unlink()\n dom = None\n except ExpatError:\n self.url = xml_url\n return","def cleanXMLfromSpecialChars(self,line):\n return str(line).replace(\"&\", \"&\").replace(\"\\\"\",\""\").replace(\"<\",\"<\").replace(\">\",\">\").replace(\"'\",\"'\")","def parseXML(self, xml):\n return BeautifulSoup(xml, \"xml\")","def encode(self):\n\n return lxml.etree.tostring(self.get_content(),\n pretty_print = True,\n encoding = self.encoding,\n xml_declaration = True)","def test_incomplete_xml(self):\n self.__opener.contents = '<Report></Report>>'\n self.assertEqual(-1, self.__uft.failed_tests('url'))","def checkMissionXML(self):\n # -- It is not included for simplifity --#\n self.mission_xml_as_expected = 'Unknown'","def readString(self, st):\n if not isinstance(st, str):\n raise ValueError(\"String must be of type string, not %s\" % type(st))\n return etree.fromstring(st)","def XmlNamespace(self) -> str:","def getIdentifierObjectXML(base_url, identifier):\n\n\tquery_url = base_url + \"/object/\" + urllib.quote_plus(identifier)\n\tprint(\"\\t\\t%s\" % query_url)\n\n\ttry:\n\t\trequest = urllib2.urlopen(query_url)\n\t\tresponse = request.read()\n\t\tresponse_xml = ET.fromstring(response)\n\texcept:\n\t\tprint \"\\t\\tFailed request: %s\" % query_url\n\n\t\tresponse_xml = None\n\n\treturn response_xml","def test_write_string():\n buf = make_buffer()\n writer = XmlWriter(buf)\n writer.write_element('value', 'myvalue')\n writer.flush()\n assert_equals(decode_buffer(buf), '<value>myvalue</value>')","def xml(self):\n xml = []\n xml.append('<?xml version=\"1.0\" encoding=\"%s\"?>' % XML_ENCODING.get(self.encoding, self.encoding))\n xml.append(\"<%s>\" % XML_TEXT)\n xml.extend([sentence.xml for sentence in self])\n xml.append(\"</%s>\" % XML_TEXT)\n return \"\\n\".join(xml)"],"string":"[\n \"def test_with_no_encoding(self):\\n xml = (\\n u'<?xml version=\\\"1.0\\\"?>'\\n u'<DocRoot>'\\n u'<Elem1>默认جذ</Elem1>'\\n u'<Elem2/>'\\n u'</DocRoot>'\\n )\\n io_string = six.StringIO()\\n self.builder.dom_element.write_doc(io_string, encoding=None)\\n # NOTE Exact test, no encoding of comparison XML doc string\\n self.assertEqual(xml, io_string.getvalue())\",\n \"def get_xml(self):\\n with io.StringIO() as string:\\n string.write(ET.tostring(self.root, encoding=\\\"unicode\\\"))\\n return string.getvalue()\",\n \"def xml_string(self):\\r\\n if self._xml_string is not None:\\r\\n return self._xml_string\\r\\n\\r\\n return etree.tostring(self._xml_node)\",\n \"def xml_string(self):\\n if self._xml_string is not None:\\n return self._xml_string\\n\\n return etree.tostring(self._xml_node)\",\n \"def prettify(elem):\\n #print(\\\"prettify function: rough_string:\\\")\\n rough_string = ET.tostring(elem, 'utf-8')\\n \\n #print(rough_string)\\n #print(type(rough_string)) #bytes\\n new_rough_string = rough_string.replace(b'\\\\n', b'')\\n new_rough_string = rough_string.replace(b'\\\\t', b'')\\n #print(new_rough_string)\\n '''\\n testStr = str(rough_string)\\n print(type(testStr)) #str\\n testBytes = testStr.encode('utf-8')\\n print(type(testBytes))\\n print(testBytes)\\n fakeparse = minidom.parseString(testBytes)\\n testStr = testStr.replace('\\\\n', '')\\n lessRoughString = testStr.encode('utf-8')\\n print(type(lessRoughString)) #bytes\\n '''\\n reparsed = minidom.parseString(new_rough_string)\\n #print(type(reparsed))\\n return reparsed.toprettyxml(indent='\\\\t', newl='')\",\n \"def make_request_xml(self):\\n #print (self.url)\\n try:\\n with closing(get(self.url, stream=True)) as resp: #returns b`xml`\\n if self.is_good_enough_xml(resp):\\n return resp.content\\n else:\\n return None\\n except RequestException as e:\\n print('Error during requests to {0} : {1}'.format(url, str(e)))\\n return None\",\n \"def exportXml ( w, xml ):\\n assert str ( type ( xml ) ) == \\\"<type 'str'>\\\"\\n rawText = xml\\n pattern = re.compile (r'[^\\\\S ]+')\\n text = re.sub ( pattern, \\\"\\\", rawText )\\n reparsed = MD.parseString ( text )\\n w.write ( reparsed.toprettyxml ( indent = \\\"\\\\t\\\", encoding = \\\"UTF-8\\\" ) )\",\n \"def test_write_defaults(self):\\n xml = (\\n u'<?xml version=\\\"1.0\\\" encoding=\\\"utf-8\\\"?>'\\n u'<DocRoot>'\\n u'<Elem1>默认جذ</Elem1>'\\n u'<Elem2/>'\\n u'</DocRoot>'\\n )\\n io_string = six.StringIO()\\n self.builder.write_doc(io_string)\\n if six.PY2:\\n self.assertEqual(xml.encode('utf-8'), io_string.getvalue())\\n else:\\n self.assertEqual(xml, io_string.getvalue())\",\n \"def toString(doc):\\n return doc.toxml()\",\n \"def saveXml(self, buf: java.lang.StringBuilder) -> None:\\n ...\",\n \"def _readXMLfragment(self) -> str:\\n\\t\\tself._check()\\n\\t\\tself._raven.reset_output_buffer()\\n\\t\\tself._raven.reset_input_buffer()\\n\\t\\tfirst_char = self._raven.read()\\n\\t\\twhile (first_char == 0 or first_char == b' '):\\n\\t\\t\\tfirst_char = self._raven.read()\\n\\t\\tif (first_char != b'<'):\\n\\t\\t\\tself._clear()\\n\\t\\t\\traise InvalidFormat('INVALID CHAR: {}'.format(first_char))\\n\\t\\tstart_tag = first_char\\n\\t\\tresult = ''\\n\\t\\twhile (start_tag[-1] != 62):\\n\\t\\t\\tchar = self._raven.read()\\n\\t\\t\\tif len(char) == 0:\\n\\t\\t\\t\\traise Exception('No data')\\n\\t\\t\\tstart_tag += char\\n\\t\\tstart_tag = start_tag.decode('ascii').strip('\\\\x00')\\n\\t# Debugging\\n\\t#\\tprint(start_tag)\\n\\t\\tif \\\"/\\\" in start_tag:\\n\\t\\t\\traise InvalidFormat('\\\"/\\\" detected in XML starting tag')\\n\\t\\tresult = start_tag\\n\\t\\tend_tag = start_tag[0] + '/' + start_tag[1:] \\n\\t\\tend_tag_len = len(end_tag)\\n\\t\\twhile (result[-end_tag_len:] != end_tag):\\n\\t\\t\\tchar = self._raven.read()\\n\\t\\t\\tif len(char) == 0:\\n\\t\\t\\t\\traise Exception('No data')\\n\\t\\t\\tresult += char.decode('ascii')\\n\\t\\ttry:\\n\\t\\t\\treturn ET.fromstring(result)\\n\\t\\texcept:\\n\\t\\t\\traise InvalidFormat\",\n \"def downloadXML(url): \\n request=NSURLRequest.requestWithURL_(NSURL.URLWithString_(url))\\n (data, response, error)= NSURLConnection.sendSynchronousRequest_returningResponse_error_(request)\\n return data\",\n \"def xml(string, token=[WORD, POS, CHUNK, PNP, REL, ANCHOR, LEMMA]):\\n return Text(string, token).xml\",\n \"def xml(self):\\n return lxml.etree.fromstring(self.content, _XML_PARSER)\",\n \"def write(self):\\n temp_string = minidom.parseString(ET.tostring(self.root)).toprettyxml(encoding=\\\"UTF-8\\\")\\n with open(self.xml_file, 'w') as f:\\n f.write(temp_string)\\n # f = open(self.xml_file, \\\"w\\\")\\n # f.write(temp_string)\\n # f.close()\",\n \"def _load(self, source):\\n\\n sock = toolbox.openAnything(source)\\n xmldoc = minidom.parse(sock).documentElement\\n sock.close()\\n return xmldoc\",\n \"def strtoxml(s):\\n return s.replace('&','&').replace('\\\"', '"').replace('<','<').replace('>','>')\",\n \"def xml(self):\\n rough_string = ElementTree.tostring(self.dom, \\\"utf-8\\\")\\n reparsed = minidom.parseString(rough_string)\\n return reparsed.toprettyxml(indent=\\\" \\\")\",\n \"def beautify_xml(XML):\\n # convert XML file to modifiable string to beautify it\\n text_string = ET.tostring(XML, encoding='UTF-8', method='xml')\\n \\n # insert line breaks before end of file tag\\n file_string = text_string.replace('</aardvark>', '\\\\n\\\\n</aardvark>')\\n \\n # insert double new line before comments to create\\n # blocks for each command\\n file_string = file_string.replace('<!', '\\\\n\\\\n<!')\\n \\n # insert new line between each set of XML tags\\n file_string = file_string.replace('><', '>\\\\n\\\\t<')\\n \\n # remove header\\n # file_string = file_string.replace('<?xml version=\\\\'1.0\\\\' encoding=\\\\'utf8\\\\'?>\\\\n', '') \\n \\n return file_string\",\n \"def getxml(url, **kwargs):\\n xml = fetch_resource(url, **kwargs)\\n return etree.fromstring(xml)\",\n \"def __str__(self):\\n result = xml.dom.minidom.parseString(\\n xml.etree.ElementTree.tostring(\\n self.ToXMLElement(), encoding='utf-8')).toprettyxml(indent=' ')\\n\\n return result\",\n \"def to_xml(self, enc='utf-8'):\\n return b\\\"\\\"\\\"<?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?>\\n<!DOCTYPE GIFTI SYSTEM \\\"http://www.nitrc.org/frs/download.php/115/gifti.dtd\\\">\\n\\\"\\\"\\\" + xml.XmlSerializable.to_xml(self, enc)\",\n \"def stringToXML(self, unparsedXML):\\n xmlRoot = ET.fromstring(unparsedXML)\\n self.xmlRoot = xmlRoot\\n return xmlRoot\",\n \"def parse_string(s):\\n return XmlWrapper(minidom.parseString(s))\",\n \"def saveToXml(self) -> org.jdom.Element:\\n ...\",\n \"def _clean_xml(raw: str) -> str:\\n a = raw.encode(\\\"ascii\\\", \\\"ignore\\\").decode(\\\"ascii\\\")\\n no_encoding = _strip_encoding(a)\\n no_ns = _strip_namespace(no_encoding)\\n return no_ns\",\n \"def example_xml43(example_xml_file41):\\n return etree.fromstring(example_xml_file43.encode('utf-8'))\",\n \"def test_parse_xml():\\r\\n\\r\\n url = 'http://firds.esma.europa.eu/firds/DLTINS_20210117_01of01.zip'\\r\\n\\r\\n assert url == parse_xml()\",\n \"def new_xml(self, root_name):\\n\\n self.tree = ET.ElementTree(ET.fromstring('<?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?><%s></%s>'%(\\n root_name, root_name)))\\n return self.tree.getroot()\",\n \"def get_xml(self):\\n return etree.tostring(self.get_etree())\",\n \"def parsexml(self):\\n raise NotImplementedError\",\n \"def get_xml_string(stream_pointer):\\n # This function avoid stream_pointer.seek() for the vast majority\\n # of cases (when xml is formatted correctly) just because i don't\\n # like using 'seek' (never know when you're getting non-rewindable \\n # streams\\n c = stream_pointer.read(1)\\n count = 0\\n while c != '<' and c != '':\\n count = count + 1\\n c = stream_pointer.read(1)\\n if c == '':\\n stream_pointer.seek(0)\\n logging.error(\\\"Poorly formatted schema - no '<' found\\\", \\\\\\n extra={'xml':stream_pointer.read()})\\n return\\n xml_string = \\\"<\\\" + stream_pointer.read()\\n if count > 0:\\n stream_pointer.seek(0)\\n logging.error(\\\"Poorly formatted schema\\\", \\\\\\n extra={'xml':stream_pointer.read()}) \\n return xml_string\",\n \"def xml(self):\\n raise NotImplementedError('This api does not return xml')\",\n \"def read(self, return_string=False):\\r\\n # Get result data from debugger engine and verify length of response\\r\\n data = self.read_data()\\r\\n\\r\\n # Show debug output\\r\\n debug('[Response data] %s' % data)\\r\\n\\r\\n # Return data string\\r\\n if return_string:\\r\\n return data\\r\\n\\r\\n # Remove special character quoting\\r\\n data = self.unescape(data)\\r\\n\\r\\n # Replace invalid XML characters\\r\\n data = ILLEGAL_XML_RE.sub('?', data)\\r\\n\\r\\n # Create XML document object\\r\\n document = ET.fromstring(data)\\r\\n return document\",\n \"def example_xml41(example_xml_file41):\\n return etree.fromstring(example_xml_file41.encode('utf-8'))\",\n \"def example_xml42(example_xml_file41):\\n return etree.fromstring(example_xml_file42.encode('utf-8'))\",\n \"def xml_decode(string):\\n string = string.replace(\\\"&\\\", \\\"&\\\")\\n string = string.replace(\\\"<\\\", \\\"<\\\")\\n string = string.replace(\\\">\\\", \\\">\\\")\\n string = string.replace(\\\""\\\",\\\"\\\\\\\"\\\")\\n string = string.replace(\\\"/\\\", SLASH)\\n return string\",\n \"def parse_xml_str(self, data):\\n try:\\n dom = parseString(data)\\n process_includes(dom)\\n except ExpatError, x:\\n raise EzXMLError(\\\"Failed to parse: %s\\\" % x)\\n return self.walkdom(dom.documentElement)\",\n \"def test_xml_direct(self): \\n response = client.result(True, 'xml', 'unittest', test_data = self.test_data)\\n root = ET.fromstring(response)\\n first_name = root[0][0][0].text\\n self.assertEqual(first_name,'John', 'Should print John')\\n nationality = '<nationality>' in response\\n self.assertFalse(nationality, 'Nationality should not be present')\",\n \"def toxml(self) :\\n\\t\\treturn self.doc.toxml()\",\n \"def ConvertFromXML (given_xml_string) :\\r\\n stream_thing = cStringIO.StringIO(given_xml_string)\\r\\n return ReadFromXMLStream(stream_thing)\",\n \"def ler_arquivo_xml(self, diretorio):\\r\\n with open(diretorio, 'r') as fxml:\\r\\n\\t strfx = fxml.readlines()\\r\\n\\t string = \\\"\\\".join(strfx).replace(\\\"&\\\",\\\" e \\\")\\r\\n return string\",\n \"def example_xml40(example_xml_file40):\\n return etree.fromstring(example_xml_file40.encode('utf-8'))\",\n \"def load_xml(pmid, sleep=None):\\n link = \\\"https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&retmode=xml&id=%s\\\" % str(pmid) + \\\"&api_key=\\\" + API_KEY\\n print(link)\\n page = requests.get(link)\\n tree = html.fromstring(page.content)\\n if sleep is not None:\\n time.sleep(sleep)\\n return tree\",\n \"def xml(self):\\n return self._xml\",\n \"def xml(self):\\n return self._xml\",\n \"def content_api_xml(url, request):\\n headers = {'content-type': 'application/xml'}\\n content = 'xml string'\\n return response(status_code=200,\\n content=content,\\n headers=headers,\\n request=request)\",\n \"def serialize(self):\\n return self.xmlnode.serialize(encoding=\\\"utf-8\\\")\",\n \"def parse_xml():\\r\\n\\r\\n fileXml = read_file('feed.xml')\\r\\n\\r\\n doc = fileXml['response']['result']['doc'][0]\\r\\n\\r\\n for string in doc['str']:\\r\\n if string['@name'] == \\\"download_link\\\":\\r\\n downloadLink = string['#text']\\r\\n else:\\r\\n logging.error('Download link not found')\\r\\n\\r\\n return downloadLink\",\n \"def load_xml(pmid, sleep=None):\\r\\n link = \\\"https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&retmode=xml&id=%s\\\" % str(pmid) \\r\\n page = requests.get(link) \\r\\n tree = html.fromstring(page.content)\\r\\n if sleep is not None:\\r\\n time.sleep(sleep)\\r\\n return tree\",\n \"def xml(self):\\n return parse_xml(self, tab=\\\"\\\\t\\\", id=self.id or \\\"\\\")\",\n \"def cleanXML(aString):\\n\\treturn re.sub(\\\"\\\\s+\\\", \\\" \\\", _xmlJunkPat.sub('', aString)).strip(\\n\\t\\t).replace(\\\" />\\\", \\\"/>\\\").replace(\\\" >\\\", \\\">\\\")\",\n \"def xmldoc(self, doctype):\\n # we hack in the DOCTYPE using the parser\\n docstr = \\\"\\\"\\\"<?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?>\\n <!DOCTYPE %s SYSTEM \\\"file:///usr/share/emane/dtd/%s.dtd\\\">\\n <%s/>\\\"\\\"\\\" % (doctype, doctype, doctype)\\n # normally this would be: doc = Document()\\n return parseString(docstr)\",\n \"def xml_pretty(xml_string):\\n return xml_string # xml.dom.minidom.parseString(xml_string).toprettyxml()\",\n \"def docType():\\n return (u'<?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?>\\\\n'\\n u'<!DOCTYPE html PUBLIC \\\"-//W3C//DTD XHTML 1.0 '\\n u'Transitional//EN\\\" '\\n u'\\\"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd\\\">\\\\n')\",\n \"def _parse_xml(self, response):\\n if response.startswith('\\\\n'):\\n response = response[1:]\\n tree = etree.fromstring(response)\\n return tree\",\n \"def test_incomplete_xml_no_timestamp(self):\\n self.__opener.contents = '<Report><Doc><Summary/></Doc></Report>'\\n self.assertEqual(datetime.datetime.min, self.__uft.datetime('url'))\",\n \"def str_to_v2_str(xml_str):\\n if str_is_v2(xml_str):\\n return xml_str\\n etree_obj = str_to_etree(xml_str)\\n etree_replace_namespace(etree_obj, v2_0.Namespace)\\n return etree_to_str(etree_obj)\",\n \"def test_fixed_xml_tag(self):\\r\\n\\r\\n # create a error tag with valid xml contents\\r\\n root = etree.Element('error')\\r\\n good_xml = '''<sequential display_name=\\\"fixed\\\"><video url=\\\"hi\\\"/></sequential>'''\\r\\n root.text = good_xml\\r\\n\\r\\n xml_str_in = etree.tostring(root)\\r\\n\\r\\n # load it\\r\\n system = self.get_system()\\r\\n descriptor = system.process_xml(xml_str_in)\\r\\n\\r\\n # export it\\r\\n node = etree.Element('unknown')\\r\\n descriptor.add_xml_to_node(node)\\r\\n\\r\\n # Now make sure the exported xml is a sequential\\r\\n self.assertEqual(node.tag, 'sequential')\",\n \"def read(self) -> str:\\n\\t\\treturn self._readXMLfragment()\",\n \"def unpack_xml(text) -> ET.ElementTree:\\n etree: ET.ElementTree = ET.parse(io.StringIO(text))\\n _check_for_errors(etree)\\n return etree\",\n \"def xml(self):\\n raise NotImplementedError('must be implemented by all subclasses')\",\n \"def test_raw_feed(self):\\n self.assertEqual(self.feed.feed.raw[:6].decode('utf-8'), \\\"<?xml \\\")\",\n \"def get_str_from_xml_tag( xml_object , tag ):\\n # get it\\n results = xml_object.getElementsByTagName( tag )\\n \\n # convert to string\\n L = len( tag )\\n results = [i.toxml()[L + 2:-(L + 3)].strip() for i in results]\\n \\n return results\",\n \"def MakeTextXMLReady(text):\\n dec_text = DecodeNonASCIIText(text)[0]\\n items = []\\n for char in dec_text:\\n try:\\n char = char.encode('ascii')\\n except UnicodeEncodeError:\\n # We have a non-ASCII character of type unicode. Convert it into an\\n # XML-ready format.\\n try:\\n str(char)\\n char.encode('utf-8')\\n except UnicodeEncodeError:\\n char = '%s;' % hex(ord(char)).replace('0x', '&#x')\\n items.append(char)\\n return ''.join(items)\",\n \"def getXmlTree(url):\\n return lxml.etree.parse(url)\",\n \"def getxml(self, pmcid):\\n import requests\\n r = requests.get(\\n (self.xmlurl).format(pmcid=pmcid))\\n return r.content\",\n \"def toXMLString(self):\\n return _libsbml.XMLNode_toXMLString(self)\",\n \"def test_default_indent_and_newline(self):\\n self.builder.dom_element.write_doc(self.iobytes, indent=True)\\n self.assertEqual(\\n u'<?xml version=\\\"1.0\\\" encoding=\\\"utf-8\\\"?>\\\\n'\\n u'<DocRoot>\\\\n'\\n u' <Elem1>默认جذ</Elem1>\\\\n'\\n u' <Elem2/>\\\\n'\\n u'</DocRoot>\\\\n'.encode('utf-8'),\\n self.iobytes.getvalue())\",\n \"def test_something(self):\\n self.assertEqual(\\n b\\\"\\\"\\\"<?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?>\\\\n<Foo>bar</Foo>\\\"\\\"\\\",\\n self.successResultOf(to_xml(tags.Foo(\\\"bar\\\"))),\\n )\",\n \"def xml_to_text(xml_string, node_name='text'):\\n # import xml.etree.ElementTree as ET\\n root = ET.fromstring(xml_string)\\n return_string = u\\\"\\\"\\n for node in root.iter(node_name):\\n if node.text is None:\\n pass\\n else:\\n return_string = u\\\"\\\".join([return_string, unicode(node.text)])\\n return return_string\",\n \"def str_to_v1_str(xml_str):\\n if str_is_v1(xml_str):\\n return xml_str\\n etree_obj = str_to_etree(xml_str)\\n strip_v2_elements(etree_obj)\\n etree_replace_namespace(etree_obj, v1_0.Namespace)\\n return etree_to_str(etree_obj)\",\n \"def xml(self, request):\\n raise Exception(\\\"Not Implemented\\\")\",\n \"def getIdentifierMetaXML(base_url, identifier):\\n\\n\\tquery_url = base_url + \\\"/meta/\\\" + urllib.quote_plus(identifier)\\n\\tprint(\\\"\\\\t\\\\t%s\\\" % query_url)\\n\\n\\ttry:\\n\\t\\trequest = urllib2.urlopen(query_url)\\n\\t\\tresponse = request.read()\\n\\t\\tresponse_xml = ET.fromstring(response)\\n\\texcept:\\n\\t\\tprint \\\"\\\\t\\\\tFailed request: %s\\\" % query_url\\n\\t\\tresponse_xml = None\\n\\n\\treturn response_xml\",\n \"def saving_file(xml):\\r\\n\\r\\n xml_string = etree.tostring(xml)\\r\\n parsed = minidom.parseString(xml_string)\\r\\n with open(self.app_path + \\\"\\\\\\\\temp_\\\\\\\\\\\" + file_name + \\\".xml\\\", \\\"w\\\") as file:\\r\\n file.write(parsed.toprettyxml(indent=\\\" \\\"))\",\n \"def to_string(root: ElementTree.Element) -> str:\\n return ElementTree.tostring(root, encoding=\\\"unicode\\\", method=\\\"xml\\\").replace(\\n \\\"\\\\n\\\", \\\"\\\\r\\\\n\\\"\\n )\",\n \"def __str__(self):\\n if self.hocr is None:\\n return ''\\n body = self.hocr.find(\\\".//%sbody\\\"%(self.xmlns))\\n if body:\\n return self._get_element_text(body).encode('utf-8') # XML gives unicode\\n else:\\n return ''\",\n \"def get_xml(codetoget):\\n\\txmlfilename = ''\\n\\ttry:\\n\\t\\tTrainingComponentDetailsRequest= client.factory.create('TrainingComponentDetailsRequest')\\n\\t\\tTrainingComponentDetailsRequest.Code=codetoget\\n\\t\\tTrainingComponentInformationRequested=client.factory.create('TrainingComponentInformationRequested')\\n\\t\\tTrainingComponentInformationRequested.ShowReleases=True\\n\\t\\tTrainingComponentInformationRequested.ShowUnitGrid=True\\n\\t\\tTrainingComponentInformationRequested.ShowFiles=True\\n\\t\\tTrainingComponentInformationRequested.ShowComponents=True\\n\\t\\tTrainingComponentDetailsRequest.InformationRequest=TrainingComponentInformationRequested\\n\\t\\ttry:\\n\\t\\t\\tresult= client.service.GetDetails(TrainingComponentDetailsRequest)\\n\\t\\t\\t#print result\\n\\t\\t\\tfor unit in result.Releases[0]:\\n\\t\\t\\t\\ttry:\\n\\t\\t\\t\\t\\tfor fyle in unit.Files.ReleaseFile:\\n\\t\\t\\t\\t\\t\\t#print fyle.RelativePath\\n\\t\\t\\t\\t\\t\\tfname = fyle.RelativePath.strip()\\n\\t\\t\\t\\t\\t\\tfname = fname.lower()\\n\\t\\t\\t\\t\\t\\t#sys.stderr.write(\\\"\\\\nfile: (%s)\\\" % (fname)) \\n\\t\\t\\t\\t\\t\\tif fname[-4:]==\\\".xml\\\":\\n\\t\\t\\t\\t\\t\\t\\tstrFile=fyle.RelativePath\\n\\t\\t\\t\\t\\t\\t\\txmlfilename = strFile\\n\\t\\t\\t\\t\\t\\t\\tif os.path.exists(os.path.join(xmlfolder, strFile))==False:\\n\\t\\t\\t\\t\\t\\t\\t\\tsys.stderr.write('downloading ' + strFile + '\\\\n')\\n\\t\\t\\t\\t\\t\\t\\t\\turllib.urlretrieve(xmlbaseurl + urllib.quote(strFile), os.path.join(xmlfolder, strFile))\\n\\t\\t\\t\\t\\t\\t\\t\\tshutil.copyfile(os.path.join(xmlfolder, strFile), os.path.join('newfiles', strFile))\\n\\t\\t\\t\\t\\t\\t\\t\\treturn xmlfilename\\n\\t\\t\\t\\t\\t\\t\\telse: # file already there\\n\\t\\t\\t\\t\\t\\t\\t\\treturn xmlfilename\\n\\t\\t\\t\\t\\t\\t# if you didn't find an xml file just return an empty string\\n\\t\\t\\t\\t\\treturn ''\\n\\t\\t\\t\\texcept:\\n\\t\\t\\t\\t\\treturn ''\\n\\t\\texcept:\\n\\t\\t\\treturn ''\\n\\texcept WebFault, e:\\n\\t\\tsys.stderr.write(\\\"soap request failed: \\\" + e)\\n\\t\\treturn \\\"\\\"\",\n \"def normalize_xml(xml):\\n if not xml:\\n return u''\\n if isinstance(xml, unicode):\\n xml = xml.encode('utf-8')\\n xml = xml.replace('\\\\r\\\\n', '\\\\n')\\n return xml\",\n \"def tostring(self):\\n header, body = None, None\\n\\n if self._header:\\n header = b'<?xml version=\\\"1.0\\\" encoding=\\\"utf-8\\\"?>'\\n\\n if self._main() is not None:\\n body = ET.tostring(self._main(), 'utf-8')\\n\\n return (header if header else b'') + (body if body else b'')\",\n \"def restoreFromXml(self, root: org.jdom.Element) -> None:\\n ...\",\n \"def ParseXMLFile(file):\\n\\n\\tstring = \\\"\\\";\\n\\n\\t# reads in the dom structure\\n\\tdom = parse(file);\\t\\n\\n\\t# generate touples\\n\\tfor node in dom.getElementsByTagName('string'): \\n\\t\\tstring = node.firstChild.nodeValue;\\n\\t\\n\\tprint (\\\"XML File: \\\", file);\\n\\tprint (\\\"String: \\\", string);\\n\\n\\treturn string;\",\n \"def convertXMLNodeToString(*args):\\n return _libsbml.XMLNode_convertXMLNodeToString(*args)\",\n \"def doc(self):\\n\\n if not hasattr(self, \\\"_doc\\\"):\\n self.loader.cdr_cursor.execute(self.SELECT_XML, self.id)\\n xml = self.loader.cdr_cursor.fetchone().xml\\n self._doc = etree.fromstring(xml.encode(\\\"utf-8\\\"))\\n return self._doc\",\n \"def get_dom(self, text):\\n from xml.dom import minidom\\n \\n dom = minidom.parseString(text)\\n \\n return dom\",\n \"def test_01_FindXml(self):\",\n \"def restoreXML(self, parser: ghidra.xml.XmlPullParser) -> None:\\n ...\",\n \"def xml_to_string(xml, encode_base64=True):\\n xml_string = etree.tostring(xml, xml_declaration=True, encoding='utf-8', pretty_print=True)\\n if encode_base64:\\n return base64.standard_b64encode(xml_string)\\n return xml_string\",\n \"def _make_string(self, filename):\\n\\n if not os.path.isfile(filename):\\n str = \\\"ERROR: Could not find specified XML file %s.\\\" % filename\\n PRINT.info(str)\\n raise OSError(str)\\n\\n return open(filename).read()\",\n \"def read_xml(self):\\n pass\",\n \"def parse_string(self, xml_url):\\n if len(xml_url) == 0:\\n raise BadURL(\\\"An empty string is not a valid URL.\\\")\\n try:\\n dom = parseString(xml_url).firstChild\\n self.parse_element(dom)\\n dom.unlink()\\n dom = None\\n except ExpatError:\\n self.url = xml_url\\n return\",\n \"def cleanXMLfromSpecialChars(self,line):\\n return str(line).replace(\\\"&\\\", \\\"&\\\").replace(\\\"\\\\\\\"\\\",\\\""\\\").replace(\\\"<\\\",\\\"<\\\").replace(\\\">\\\",\\\">\\\").replace(\\\"'\\\",\\\"'\\\")\",\n \"def parseXML(self, xml):\\n return BeautifulSoup(xml, \\\"xml\\\")\",\n \"def encode(self):\\n\\n return lxml.etree.tostring(self.get_content(),\\n pretty_print = True,\\n encoding = self.encoding,\\n xml_declaration = True)\",\n \"def test_incomplete_xml(self):\\n self.__opener.contents = '<Report></Report>>'\\n self.assertEqual(-1, self.__uft.failed_tests('url'))\",\n \"def checkMissionXML(self):\\n # -- It is not included for simplifity --#\\n self.mission_xml_as_expected = 'Unknown'\",\n \"def readString(self, st):\\n if not isinstance(st, str):\\n raise ValueError(\\\"String must be of type string, not %s\\\" % type(st))\\n return etree.fromstring(st)\",\n \"def XmlNamespace(self) -> str:\",\n \"def getIdentifierObjectXML(base_url, identifier):\\n\\n\\tquery_url = base_url + \\\"/object/\\\" + urllib.quote_plus(identifier)\\n\\tprint(\\\"\\\\t\\\\t%s\\\" % query_url)\\n\\n\\ttry:\\n\\t\\trequest = urllib2.urlopen(query_url)\\n\\t\\tresponse = request.read()\\n\\t\\tresponse_xml = ET.fromstring(response)\\n\\texcept:\\n\\t\\tprint \\\"\\\\t\\\\tFailed request: %s\\\" % query_url\\n\\n\\t\\tresponse_xml = None\\n\\n\\treturn response_xml\",\n \"def test_write_string():\\n buf = make_buffer()\\n writer = XmlWriter(buf)\\n writer.write_element('value', 'myvalue')\\n writer.flush()\\n assert_equals(decode_buffer(buf), '<value>myvalue</value>')\",\n \"def xml(self):\\n xml = []\\n xml.append('<?xml version=\\\"1.0\\\" encoding=\\\"%s\\\"?>' % XML_ENCODING.get(self.encoding, self.encoding))\\n xml.append(\\\"<%s>\\\" % XML_TEXT)\\n xml.extend([sentence.xml for sentence in self])\\n xml.append(\\\"</%s>\\\" % XML_TEXT)\\n return \\\"\\\\n\\\".join(xml)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6344099","0.6286215","0.6196129","0.6091438","0.60381323","0.6027413","0.60088193","0.59996015","0.589542","0.58318496","0.5826632","0.58164376","0.57975066","0.57491887","0.5740025","0.57227606","0.5715181","0.5678621","0.5669144","0.56683767","0.5633037","0.5613422","0.55988675","0.5597629","0.5589473","0.5547889","0.55406135","0.5517547","0.5497076","0.5490076","0.5482787","0.54583186","0.545725","0.5452038","0.544431","0.5427777","0.54229194","0.54150224","0.5406048","0.538814","0.5358682","0.53560174","0.5353759","0.53527045","0.53415567","0.53415567","0.53412116","0.5334339","0.5325414","0.5301355","0.5301332","0.5301299","0.5296742","0.52956885","0.52944905","0.52919763","0.5288149","0.52712333","0.52649003","0.52617586","0.52614254","0.52555513","0.52535087","0.52341306","0.5228354","0.52050734","0.52006066","0.51952004","0.51921284","0.51913905","0.5178123","0.51770866","0.5172857","0.51707155","0.5162624","0.51557505","0.51536345","0.51495737","0.5139021","0.5137924","0.51319355","0.5124743","0.51077783","0.5105308","0.51044977","0.51035357","0.5096939","0.50920403","0.50843287","0.5080814","0.5079117","0.50769407","0.5074451","0.5068624","0.50679374","0.5059473","0.5053129","0.50505024","0.5046999","0.50439805","0.50379443"],"string":"[\n \"0.6344099\",\n \"0.6286215\",\n \"0.6196129\",\n \"0.6091438\",\n \"0.60381323\",\n \"0.6027413\",\n \"0.60088193\",\n \"0.59996015\",\n \"0.589542\",\n \"0.58318496\",\n \"0.5826632\",\n \"0.58164376\",\n \"0.57975066\",\n \"0.57491887\",\n \"0.5740025\",\n \"0.57227606\",\n \"0.5715181\",\n \"0.5678621\",\n \"0.5669144\",\n \"0.56683767\",\n \"0.5633037\",\n \"0.5613422\",\n \"0.55988675\",\n \"0.5597629\",\n \"0.5589473\",\n \"0.5547889\",\n \"0.55406135\",\n \"0.5517547\",\n \"0.5497076\",\n \"0.5490076\",\n \"0.5482787\",\n \"0.54583186\",\n \"0.545725\",\n \"0.5452038\",\n \"0.544431\",\n \"0.5427777\",\n \"0.54229194\",\n \"0.54150224\",\n \"0.5406048\",\n \"0.538814\",\n \"0.5358682\",\n \"0.53560174\",\n \"0.5353759\",\n \"0.53527045\",\n \"0.53415567\",\n \"0.53415567\",\n \"0.53412116\",\n \"0.5334339\",\n \"0.5325414\",\n \"0.5301355\",\n \"0.5301332\",\n \"0.5301299\",\n \"0.5296742\",\n \"0.52956885\",\n \"0.52944905\",\n \"0.52919763\",\n \"0.5288149\",\n \"0.52712333\",\n \"0.52649003\",\n \"0.52617586\",\n \"0.52614254\",\n \"0.52555513\",\n \"0.52535087\",\n \"0.52341306\",\n \"0.5228354\",\n \"0.52050734\",\n \"0.52006066\",\n \"0.51952004\",\n \"0.51921284\",\n \"0.51913905\",\n \"0.5178123\",\n \"0.51770866\",\n \"0.5172857\",\n \"0.51707155\",\n \"0.5162624\",\n \"0.51557505\",\n \"0.51536345\",\n \"0.51495737\",\n \"0.5139021\",\n \"0.5137924\",\n \"0.51319355\",\n \"0.5124743\",\n \"0.51077783\",\n \"0.5105308\",\n \"0.51044977\",\n \"0.51035357\",\n \"0.5096939\",\n \"0.50920403\",\n \"0.50843287\",\n \"0.5080814\",\n \"0.5079117\",\n \"0.50769407\",\n \"0.5074451\",\n \"0.5068624\",\n \"0.50679374\",\n \"0.5059473\",\n \"0.5053129\",\n \"0.50505024\",\n \"0.5046999\",\n \"0.50439805\",\n \"0.50379443\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":92980,"cells":{"query":{"kind":"string","value":"Function returns subtitle dictionary which is computed from correct xml string."},"document":{"kind":"string","value":"def return_xml_dict(self):\n\ttry:\n\t self.Correct_MultiRoot_XML()\n\t self.subtitle_dict = sorted(self.xmltodict(self.XML_String)['subtitle'],key=itemgetter('imdb','cd'))\n\t #self.subtitle_dict = self.xmltodict(self.XML_String)['subtitle']\n\t print \"XML subtitle list downloaded and converted to dict\"\n\t return True\n\texcept:\n\t print \"XML subtitle list not downloaded or converterd.\"\n\t return False"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _from_origin_to_dict(self):\n try:\n for elem in self._xml_tree.getchildren():\n if elem.tag == \"info\":\n for subelem in elem.xpath(\"//Metadata/General/Metas/Titulo\"):\n self._translated_dict[\"root\"][\"title\"] = subelem.text\n return self\n\n except Exception as e:\n logger.error(\"XML Parse Error. %s\" % repr(e))","def parse_text(self, text: str) -> SectionDict:","def get_subtitles(self, index: int):\n\n match = self.re_subs[index - 1]\n start = convert_subs_time(match[1])\n end = convert_subs_time(match[2])\n subtitles = match[3]\n subtitles = clean_text(subtitles)\n\n return (subtitles, start, end)","def stat_subtitle(self, release_name, movie_dir):\n ret = {}\n for root_dir, child_folders, file_names in os.walk(movie_dir):\n for file_name in file_names:\n if not file_name.startswith(release_name):\n continue\n\n subtitle_info = get_subtitle_info(file_name)\n if not subtitle_info:\n continue\n\n if 'lang' not in subtitle_info:\n continue\n\n lang = subtitle_info['lang']\n if lang not in ret:\n ret[lang] = []\n\n ret[lang].append(file_name)\n\n # Sort result\n for lang in ret:\n ret[lang] = sorted(ret[lang])\n\n return ret","def parse_info(s:str) -> dict:\n d = {}\n d[\"SVTYPE\"] = re.search(r'(?<=SVTYPE=)\\w+',s).group(0)\n d[\"SUPPORT\"] = re.search(r'(?<=SUPPORT=)\\d+',s).group(0)\n if d[\"SVTYPE\"] in [\"BND\"]:\n return d\n d[\"END\"] = re.search(r'(?<=END=)\\d+',s).group(0)\n if d[\"SVTYPE\"] in [\"INV\"]:\n return d\n d[\"SVLEN\"] = re.search(r'(?<=SVLEN=)(.*?)(?=;)',s).group(0)\n d[\"READS\"] = re.search(r'(?<=READS=)(.*?)(?=$)',s).group(0).split(\",\")\n if d[\"SVTYPE\"] == \"INS\":\n d[\"SEQS\"] = re.search(r'(?<=SEQS=)(.*?)(?=;)',s).group(0).split(\",\")\n return d","def extract(self, json_str, sub_number):\n topic_dict = json.loads(json_str)\n # print(topic_dict)\n\n if ('children' not in topic_dict):\n raise RuntimeError('topic tree json data has no children.')\n\n sub_topic_title = topic_dict['standalone_title']\n\n # 1. sub: subject (math, physic)\n # 2. nb_main: main topic number (addition/subtraction, fraction, ...)\n # 3. nb_sub: sub topic number\n # 4. nb_video: video title number\n # 5. sub_topic_title:\n # 6. video_title:\n # 7. d1: text translation duration time\n # 8. d2: voice over, edit duration time\n # 9. d3: subtitle duration time\n # 10. d4: total duration time\n # 11. s1: start date\n # 12. s2: end date\n # 13. s3: elapsed date\n # 14. status:\n # 15. finished bool\n # 16. update bool\n # 17. new at 2017 bool\n # 18. video_url:\n # 19. id:\n\n video_idx=1\n retstr = ''\n for i in topic_dict['children']:\n if (i['kind'] == 'Video'):\n line_str = ' , {_nb_main}, {_nb_sub}, {_nb_video}, {_sub_topic_title}, {_video_title}, {_d1}, {_d2}, {_d3}, {_d4}, {_s1}, {_s2}, {_s3}, {_status}, , , , {_video_url}, {_id}\\n'.\\\n format(\n _nb_main=1,\n _nb_sub=sub_number,\n _nb_video=video_idx,\n _sub_topic_title=sub_topic_title,\n _video_title=i['title'],\n _d1='00:00:00', _d2='00:00:00',\n _d3='00:00:00', _d4='00:00:00',\n _s1='2017-05-01', _s2='2017-05-01', _s3=0,\n _status='not_started',\n _video_url=i['url'],\n _id=i['internal_id'])\n video_idx += 1\n retstr += line_str\n else:\n verbose_mes = '# Skip kind [{kind}]: {title}'.format(\n kind=i['kind'], title=i['title'])\n self.verbose_out(verbose_mes)\n\n return retstr","def to_xmp_string(self):\n \"\"\"\n ...\n <xmpDM:Tracks>\n <rdf:Bag>\n <rdf:li>\n <rdf:Description\n xmpDM:trackName=\"Speaker identification\">\n <xmpDM:markers>\n <rdf:Seq>\n <rdf:li\n xmpDM:startTime=\"310\"\n xmpDM:duration=\"140\"\n xmpDM:speaker=\"Speaker0\"\n />\n <rdf:li\n xmpDM:startTime=\"450\"\n xmpDM:duration=\"60\"\n xmpDM:speaker=\"Speaker0\"\n />\n </rdf:Seq>\n </xmpDM:markers>\n </rdf:Description>\n </rdf:li>\n </rdf:Bag>\n </xmpDM:Tracks>\n ...\n \"\"\"\n initial_tags = \"\"\"<?xml version=\"1.0\"?>\n<x:xmpmeta xmlns:x=\"adobe:ns:meta/\" x:xmptk=\"XMP Core 4.4.0\">\n <rdf:RDF xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n <rdf:Description xmlns:xmpDM=\"http://ns.adobe.com/xmp/1.0/DynamicMedia/\">\n <xmpDM:Tracks>\n <rdf:Bag>\n <rdf:li>\n <rdf:Description\n xmpDM:trackName=\"Speaker identification\">\n <xmpDM:markers>\n <rdf:Seq>\"\"\"\n inner_string = ''\n for seg in self.get_time_slices():\n inner_string += \"\"\"\n <rdf:li\n xmpDM:startTime=\"%seg\"\n xmpDM:duration=\"%seg\"\n xmpDM:speaker=\"%seg\"\n /> \"\"\" % (seg[0], seg[1], seg[-2])\n final_tags = \"\"\"\n </rdf:Seq>\n </xmpDM:markers>\n </rdf:Description>\n </rdf:li>\n </rdf:Bag>\n </xmpDM:Tracks>\n </rdf:Description>\n </rdf:RDF>\n</x:xmpmeta>\n\"\"\"\n #TODO: extract previous XMP information from the media and merge \n # with speaker information\n return initial_tags + inner_string + final_tags","def _parse_video_xml(cls, xml_data):\r\n xml = etree.fromstring(xml_data)\r\n field_data = {}\r\n\r\n # Convert between key types for certain attributes --\r\n # necessary for backwards compatibility.\r\n conversions = {\r\n # example: 'start_time': cls._example_convert_start_time\r\n }\r\n\r\n # Convert between key names for certain attributes --\r\n # necessary for backwards compatibility.\r\n compat_keys = {\r\n 'from': 'start_time',\r\n 'to': 'end_time'\r\n }\r\n sources = xml.findall('source')\r\n if sources:\r\n field_data['html5_sources'] = [ele.get('src') for ele in sources]\r\n\r\n track = xml.find('track')\r\n if track is not None:\r\n field_data['track'] = track.get('src')\r\n\r\n handout = xml.find('handout')\r\n if handout is not None:\r\n field_data['handout'] = handout.get('src')\r\n\r\n transcripts = xml.findall('transcript')\r\n if transcripts:\r\n field_data['transcripts'] = {tr.get('language'): tr.get('src') for tr in transcripts}\r\n\r\n for attr, value in xml.items():\r\n if attr in compat_keys:\r\n attr = compat_keys[attr]\r\n if attr in cls.metadata_to_strip + ('url_name', 'name'):\r\n continue\r\n if attr == 'youtube':\r\n speeds = cls._parse_youtube(value)\r\n for speed, youtube_id in speeds.items():\r\n # should have made these youtube_id_1_00 for\r\n # cleanliness, but hindsight doesn't need glasses\r\n normalized_speed = speed[:-1] if speed.endswith('0') else speed\r\n # If the user has specified html5 sources, make sure we don't use the default video\r\n if youtube_id != '' or 'html5_sources' in field_data:\r\n field_data['youtube_id_{0}'.format(normalized_speed.replace('.', '_'))] = youtube_id\r\n else:\r\n # Convert XML attrs into Python values.\r\n if attr in conversions:\r\n value = conversions[attr](value)\r\n else:\r\n # We export values with json.dumps (well, except for Strings, but\r\n # for about a month we did it for Strings also).\r\n value = deserialize_field(cls.fields[attr], value)\r\n field_data[attr] = value\r\n\r\n # For backwards compatibility: Add `source` if XML doesn't have `download_video`\r\n # attribute.\r\n if 'download_video' not in field_data and sources:\r\n field_data['source'] = field_data['html5_sources'][0]\r\n\r\n # For backwards compatibility: if XML doesn't have `download_track` attribute,\r\n # it means that it is an old format. So, if `track` has some value,\r\n # `download_track` needs to have value `True`.\r\n if 'download_track' not in field_data and track is not None:\r\n field_data['download_track'] = True\r\n\r\n return field_data","def extract_subtitle_track(path_to_mkv):\n handler = SubtitleHandler()\n with open(path_to_mkv, \"rb\") as fp:\n mkvparse.mkvparse(fp, handler)\n\n return handler.subs","def return_xml_dict_entry_value(self,dict_entry, dict_entry_position):\n\tvalue = self.subtitle_dict[dict_entry][dict_entry_position]\n\treturn value[0]","def get_subtitle_print(subs: List[Track]) -> List[str]:\n data = []\n if not subs:\n data.append(\"--\")\n for sub in subs:\n line_items = []\n\n # following sub.title tree checks and supports three different language and title scenarios\n # The second scenario is the recommended option to choose if you are open to choosing any\n # The third scenario should be used if you have nothing unique to state about the track\n # | Language | Track Title | Output |\n # | ------------ | ----------------------------- | --------------------------------------------- |\n # | es / Spanish | Spanish (Latin American, SDH) | - Spanish (Latin American, SDH), SubRip (SRT) |\n # | es / Spanish | Latin American (SDH) | - Spanish, Latin American (SDH), SubRip (SRT) |\n # | es / Spanish | None | - Spanish, SubRip (SRT) |\n language = pycountry.languages.get(alpha_2=sub.language).name\n if sub.title:\n if language.lower() in sub.title.lower():\n line_items.append(sub.title)\n else:\n line_items.append(f\"{language}, {sub.title}\")\n else:\n line_items.append(language)\n\n line_items.append(sub.format.replace(\"UTF-8\", \"SubRip (SRT)\"))\n\n line = \"- \" + \", \".join(line_items)\n data += [\n (\" \" + x if i > 0 else x)\n for i, x in enumerate(textwrap.wrap(line, 64))\n ]\n return data","def get_time_intervals(subtitle, regex=r\"\\S+\"):\n # module webvtt only gets the line-captions, not individual words, so it's time for some regex!\n # The time corresponding to a word is when that word *starts*\n # words = (match.group(\"word\") for match in WORD_REGEX.finditer(subtitle))\n time_words = [\n (m.group(\"time1\") or m.group(\"time2\"), m.group(\"word1\") or m.group(\"word2\"))\n for m in TIME_WORD_REGEX.finditer(subtitle)\n ]\n # Incorrect format, which would lead to trouble zipping\n if len(time_words) == 0:\n return []\n times, words = zip(*time_words)\n # Quickly search lines starting from the end\n final_time = next(match.group(\"time\") for line in reversed(subtitle.split(\"\\n\")) for match in [re.search(FINAL_TIME_REGEX, line)] if match)\n # timestamps[i] is the time the word starts at if i is the index of the start of a word\n timestamps = {}\n word_indices = {}\n # Build search_str while computing time_stamps by adding one word and one space at a time\n search_str = ''\n words = list(words)\n last_time = 0\n for j, (word, time) in enumerate(zip(words, times)):\n i = len(search_str)\n time = parse_time(time)\n timestamps[i] = time\n if time - last_time > 10:\n search_str += '[ … ] '\n last_time = time\n word_indices[i] = j\n search_str += word + ' '\n i = len(search_str)\n timestamps[i] = final_time\n word_indices[i] = len(words)\n # Trim off the final space\n # Inconsistent capitalization, so just lowercase\n search_str = search_str[:-1].lower()\n for match in re.finditer(regex, search_str):\n start, end = match.span()\n start_index = max(i for i in timestamps if i<=start)\n end_index = min(i for i in timestamps if i>end)\n yield Interval(\n timestamps[start_index],\n timestamps[end_index],\n word_indices[start_index],\n word_indices[end_index],\n match.group(0)\n )","def edx_get_subtitle(url, headers):\n \"\"\" or None if no subtitles are available \"\"\"\n try:\n jsonString = get_page_contents(url, headers)\n jsonObject = json.loads(jsonString)\n return edx_json2srt(jsonObject)\n except URLError as e:\n print('[warning] edX subtitles (error:%s)' % e.reason)\n return None\n except ValueError as e:\n print('[warning] edX subtitles (error:%s)' % e.message)\n return None","def parser(xml):\n if not xml:\n return {} # pragma: no cover\n\n data = {}\n\n match = RE_OWI.search(u(xml))\n if match:\n data['owi'] = match.group(1)\n match = RE_OCLC.search(u(xml))\n if match:\n data['oclc'] = match.group(1)\n\n match = RE_LCC.search(u(xml))\n if match:\n buf = match.group()\n match = RE_SFA.search(buf)\n if match:\n data['lcc'] = match.group(1)\n\n match = RE_DDC.search(u(xml))\n if match:\n buf = match.group()\n match = RE_SFA.search(buf)\n if match:\n data['ddc'] = match.group(1)\n\n fast = parser_headings(xml)\n if fast:\n data['fast'] = fast\n\n return data","def to_srt(self, subtitles):\n \n srt_data = ''\n subtitle_num = self.start_index\n for subtitle in subtitles:\n subtitle_num += 1\n \n offset = self.start_time\n \n start_time = self._ms_to_time(subtitle['start_time'] + offset)\n end_time = self._ms_to_time(subtitle['end_time'] + offset)\n \n content = subtitle['content'].replace('<br>', ' ')\n \n srt_data += str(subtitle_num) + '\\r\\n'\n srt_data += '%s --> %s' % (start_time, end_time) + '\\r\\n'\n srt_data += content + '\\r\\n'\n srt_data += '\\r\\n'\n \n self.end_index = subtitle_num\n \n return srt_data","def get_words_with_end_times(subtitle_file_path):\n\n with open(subtitle_file_path) as subtitle_file:\n\n # Remove first 4 lines (containing meta information)\n for j in range(0, 4):\n subtitle_file.readline()\n\n text = subtitle_file.read()\n\n # Check if the subtitle file supports individual word times\n if text.find(\"<c>\") == -1:\n print(\"Individual word times are not supported for file: \" + subtitle_file_path)\n return None, None\n\n chunks = text.split(\" \\n\\n\") # split into chunks for easier data processing\n\n words = list()\n word_end_times = list()\n\n for chunk in chunks:\n chunk_lines = chunk.split(\"\\n\")\n words_line = chunk_lines[2]\n\n words_in_chunk = []\n word_end_times_in_chunk = []\n\n first_word_end_index = words_line.find(\"<\")\n if first_word_end_index != -1:\n first_word = words_line[\n 0:first_word_end_index] # get the first word (can't be found using method below)\n\n words_in_chunk = re.findall(\"<c> [\\S]*</c>\", words_line) # get all words\n words_in_chunk = [w[4:-4] for w in words_in_chunk] # strip <c> and <c/>\n\n word_end_times_in_chunk = re.findall(\"<\\d\\d:\\d\\d:\\d\\d.\\d\\d\\d>\", words_line) # get all word end times\n word_end_times_in_chunk = [t[1:-1] for t in word_end_times_in_chunk] # strip < and >\n else:\n # Only one word\n first_word = words_line\n\n last_time = chunk_lines[4][17:29] # end time for the last word\n\n words_in_chunk.insert(0, first_word)\n word_end_times_in_chunk.append(last_time)\n\n words.extend(words_in_chunk)\n word_end_times.extend(word_end_times_in_chunk)\n\n # For the last chunk we have to get the word end time from somewhere else\n first_line_in_last_chunk = chunks[-1].split(\"\\n\")[0]\n last_time = first_line_in_last_chunk[17:29]\n word_end_times.pop()\n word_end_times.append(last_time)\n\n if len(words) != len(word_end_times):\n print(\"Warning: word count does not match times count\")\n\n return words, word_end_times","def parse_template(string):\n count = 0\n list1 = []\n for character in string:\n count = count + 1\n if character == \"{\":\n end = string.find(\"}\", count)\n s_strg = string[count:end]\n list1.append(s_strg)\n string = string.replace(s_strg, \"\", 1)\n count = count - len(s_strg)\n\n subs = tuple(list1)\n\n return(string, subs)\n print(subs)","def xml2dict( xml, sanitize=True, prefix=None):\n \n \n #Decode to avert parsing errors as some software dump large text\n #fields into the file that occasionally contain erronious chars\n xml=xml.decode('utf-8', errors='ignore')\n\n \n return etree2dict(etree.fromstring(xml), sanitize, prefix)","def dict(self):\n return xmltodict.parse(str(self))","def parse_string(xml):\n string = \"\"\n # Traverse all the <sentence> elements in the XML.\n dom = XML(xml)\n for sentence in dom(XML_SENTENCE):\n _anchors.clear() # Populated by calling _parse_tokens().\n _attachments.clear() # Populated by calling _parse_tokens().\n # Parse the language from <sentence language=\"\">.\n language = sentence.get(XML_LANGUAGE, \"en\")\n # Parse the token tag format from <sentence token=\"\">.\n # This information is returned in TokenString.tags,\n # so the format and order of the token tags is retained when exporting/importing as XML.\n format = sentence.get(XML_TOKEN, [WORD, POS, CHUNK, PNP, REL, ANCHOR, LEMMA])\n format = not isinstance(format, basestring) and format or format.replace(\" \",\"\").split(\",\")\n # Traverse all <chunk> and <chink> elements in the sentence.\n # Find the <word> elements inside and create tokens.\n tokens = []\n for chunk in sentence:\n tokens.extend(_parse_tokens(chunk, format))\n # Attach PNP's to their anchors.\n # Keys in _anchors have linked anchor chunks (each chunk is a list of tokens).\n # The keys correspond to the keys in _attachments, which have linked PNP chunks.\n if ANCHOR in format:\n A, P, a, i = _anchors, _attachments, 1, format.index(ANCHOR)\n for id in sorted(A.keys()):\n for token in A[id]:\n token[i] += \"-\"+\"-\".join([\"A\"+str(a+p) for p in range(len(P[id]))])\n token[i] = token[i].strip(\"O-\")\n for p, pnp in enumerate(P[id]):\n for token in pnp: \n token[i] += \"-\"+\"P\"+str(a+p)\n token[i] = token[i].strip(\"O-\")\n a += len(P[id])\n # Collapse the tokens to string.\n # Separate multiple sentences with a new line.\n tokens = [\"/\".join([tag for tag in token]) for token in tokens]\n tokens = \" \".join(tokens)\n string += tokens + \"\\n\"\n # Return a TokenString, which is a unicode string that transforms easily\n # into a plain str, a list of tokens, or a Sentence.\n try:\n if MBSP: from mbsp import TokenString\n return TokenString(string.strip(), tags=format, language=language)\n except:\n return TaggedString(string.strip(), tags=format, language=language)","def edx_get_subtitle(url, headers):\n try:\n json_object = get_page_contents_as_json(url, headers)\n return edx_json2srt(json_object)\n except URLError as e:\n _print('[warning] edX subtitles (error:%s)' % e.reason)\n return None\n except ValueError as e:\n _print('[warning] edX subtitles (error:%s)' % e.message)\n return None","def voc_xml_to_dict(xml_path):\n\n xml = etree.parse(xml_path)\n root = xml.getroot()\n image_name = root.find('filename').text\n labels = []\n boxes = []\n\n for obj in root.findall('object'):\n labels.append(obj.find('name').text)\n bbox = obj.find('bndbox')\n bounds = [\n float(bbox.find('xmin').text),\n float(bbox.find('ymin').text),\n float(bbox.find('xmax').text),\n float(bbox.find('ymax').text)\n ]\n boxes.append(bounds)\n\n return {\n 'image': image_name,\n 'labels': labels,\n 'boxes': boxes,\n }","def extract_context(xml):\r\n return eval(xml.text)","def generate_subs_from_source(speed_subs, subs_type, subs_filedata, item, language='en'):\r\n _ = item.runtime.service(item, \"i18n\").ugettext\r\n if subs_type.lower() != 'srt':\r\n raise TranscriptsGenerationException(_(\"We support only SubRip (*.srt) transcripts format.\"))\r\n try:\r\n srt_subs_obj = SubRipFile.from_string(subs_filedata)\r\n except Exception as ex:\r\n msg = _(\"Something wrong with SubRip transcripts file during parsing. Inner message is {error_message}\").format(\r\n error_message=ex.message\r\n )\r\n raise TranscriptsGenerationException(msg)\r\n if not srt_subs_obj:\r\n raise TranscriptsGenerationException(_(\"Something wrong with SubRip transcripts file during parsing.\"))\r\n\r\n sub_starts = []\r\n sub_ends = []\r\n sub_texts = []\r\n\r\n for sub in srt_subs_obj:\r\n sub_starts.append(sub.start.ordinal)\r\n sub_ends.append(sub.end.ordinal)\r\n sub_texts.append(sub.text.replace('\\n', ' '))\r\n\r\n subs = {\r\n 'start': sub_starts,\r\n 'end': sub_ends,\r\n 'text': sub_texts}\r\n\r\n for speed, subs_id in speed_subs.iteritems():\r\n save_subs_to_store(\r\n generate_subs(speed, 1, subs),\r\n subs_id,\r\n item,\r\n language\r\n )\r\n\r\n return subs","def test_parser_to_dict(self):\n xml = \"\"\"\\\n<foo>\n <bar>baz</bar>\n <quz>\n <wow>works!</wow>\n </quz>\n</foo>\n\"\"\"\n d = x.to_dict(xml, {})\n assert d.bar.text_ == u'baz'\n assert d.quz.wow.text_ == u'works!'","def loads(xtext):\n\n class XmlLoads(object):\n \"\"\"\n XMLLOADS implements 'YZXml.loads' functionality\n \"\"\"\n\n def __init__(self, xtext):\n self.index = 0\n self.xtext = xtext\n self.length = len(xtext)\n self.stack = []\n\n def loads(self):\n \"\"\"\n LOADS converts xml-string to object-string\n\n Returns\n -------\n - dict\n object-xml contains {'tag': str, 'attribs': dict, 'elements': list}\n \"\"\"\n\n self.ignore_whitespaces()\n\n if self.index >= self.length:\n return\n\n if self.xtext[self.index] == '<':\n self.index += 1\n\n if self.xtext[self.index] == '/':\n self.index += 1\n\n tag = self.read_until('>')\n self.index += 1\n\n elements = []\n while len(self.stack) > 0 and\\\n (isinstance(self.stack[-1], str) or self.stack[-1]['tag'] != tag):\n elements.append(self.stack.pop())\n\n assert len(self.stack) > 0\n\n self.stack[-1]['elements'].extend(reversed(elements))\n\n else:\n self.ignore_whitespaces()\n tag = self.read_until(' >')\n\n attribs = {}\n if self.xtext[self.index] != '>':\n attribs = self.read_attribs()\n\n self.index += 1\n self.stack.append({'tag': tag, 'attribs': attribs, 'elements': []})\n else:\n self.stack.append(self.read_until('<').strip())\n\n self.loads()\n\n\n def ignore_whitespaces(self):\n \"\"\"\n IGNORE_WHITESPACES reads whitespaces and advances self.index\n \"\"\"\n\n whitespaces = [' ', '\\t', '\\n', '\\r']\n while self.index < self.length and self.xtext[self.index] in whitespaces:\n self.index += 1\n\n def read_until(self, chars):\n \"\"\"\n READ_UNTIL reads charaters and advances self.index\n unitl reaches any character in 'cahrs'\n\n Parameters\n ----------\n - chars: str\n stoping characters\n \"\"\"\n\n start_index = self.index\n\n while self.index < self.length and self.xtext[self.index] not in chars:\n self.index += 1\n\n assert self.index < self.length\n\n return self.xtext[start_index:self.index]\n\n def read_attribs(self):\n \"\"\"\n READ_ATTRIBS reads attributes of an elements\n \"\"\"\n\n attribs = {}\n while self.index < self.length:\n self.ignore_whitespaces()\n if self.xtext[self.index] == '>':\n break\n name = self.read_until('=')\n self.index += 1\n self.read_until('\"')\n self.index += 1\n value = self.read_until('\"')\n self.index += 1\n\n attribs[name] = value\n\n return attribs\n\n xmlloads = XmlLoads(xtext)\n xmlloads.loads()\n return xmlloads.stack.pop()","def parse(self, xml_text):\n xml_doc = parse_doc(xml_text)\n data = findtext(xml_doc, \"Data\")\n if data is None:\n return\n\n cryptutil = CryptUtil(conf.get_openssl_cmd())\n p7m_file = os.path.join(conf.get_lib_dir(), P7M_FILE_NAME)\n p7m = (\"MIME-Version:1.0\\n\"\n \"Content-Disposition: attachment; filename=\\\"{0}\\\"\\n\"\n \"Content-Type: application/x-pkcs7-mime; name=\\\"{1}\\\"\\n\"\n \"Content-Transfer-Encoding: base64\\n\"\n \"\\n\"\n \"{2}\").format(p7m_file, p7m_file, data)\n\n self.client.save_cache(p7m_file, p7m)\n\n trans_prv_file = os.path.join(conf.get_lib_dir(),\n TRANSPORT_PRV_FILE_NAME)\n trans_cert_file = os.path.join(conf.get_lib_dir(),\n TRANSPORT_CERT_FILE_NAME)\n pem_file = os.path.join(conf.get_lib_dir(), PEM_FILE_NAME)\n # decrypt certificates\n cryptutil.decrypt_p7m(p7m_file, trans_prv_file, trans_cert_file,\n pem_file)\n\n # The parsing process use public key to match prv and crt.\n buf = []\n begin_crt = False\n begin_prv = False\n prvs = {}\n thumbprints = {}\n index = 0\n v1_cert_list = []\n with open(pem_file) as pem:\n for line in pem.readlines():\n buf.append(line)\n if re.match(r'[-]+BEGIN.*KEY[-]+', line):\n begin_prv = True\n elif re.match(r'[-]+BEGIN.*CERTIFICATE[-]+', line):\n begin_crt = True\n elif re.match(r'[-]+END.*KEY[-]+', line):\n tmp_file = self.write_to_tmp_file(index, 'prv', buf)\n pub = cryptutil.get_pubkey_from_prv(tmp_file)\n prvs[pub] = tmp_file\n buf = []\n index += 1\n begin_prv = False\n elif re.match(r'[-]+END.*CERTIFICATE[-]+', line):\n tmp_file = self.write_to_tmp_file(index, 'crt', buf)\n pub = cryptutil.get_pubkey_from_crt(tmp_file)\n thumbprint = cryptutil.get_thumbprint_from_crt(tmp_file)\n thumbprints[pub] = thumbprint\n # Rename crt with thumbprint as the file name\n crt = \"{0}.crt\".format(thumbprint)\n v1_cert_list.append({\n \"name\": None,\n \"thumbprint\": thumbprint\n })\n os.rename(tmp_file, os.path.join(conf.get_lib_dir(), crt))\n buf = []\n index += 1\n begin_crt = False\n\n # Rename prv key with thumbprint as the file name\n for pubkey in prvs:\n thumbprint = thumbprints[pubkey]\n if thumbprint:\n tmp_file = prvs[pubkey]\n prv = \"{0}.prv\".format(thumbprint)\n os.rename(tmp_file, os.path.join(conf.get_lib_dir(), prv))\n\n for v1_cert in v1_cert_list:\n cert = Cert()\n set_properties(\"certs\", cert, v1_cert)\n self.cert_list.certificates.append(cert)","def olive_parser(text: str) -> dict:\n soup = BeautifulSoup(text, \"lxml\")\n root = soup.find(\"xmd-entity\")\n page_no = root['page_no']\n identifier = root['id']\n language = root['language']\n title = soup.meta['name']\n entity_type = root['entity_type']\n issue_date = soup.meta['issue_date']\n\n out = {\n \"meta\": {\n \"language\": None,\n \"type\": {}\n },\n \"r\": [],\n \"stats\": {},\n \"legacy\": {\"continuation_from\": None, \"continuation_to\": None},\n }\n out[\"meta\"][\"title\"] = title\n out[\"meta\"][\"page_no\"] = [int(page_no)]\n out[\"meta\"][\"language\"] = normalize_language(language)\n out[\"meta\"][\"type\"][\"raw\"] = entity_type\n out[\"meta\"][\"issue_date\"] = issue_date\n\n new_region = {\n \"c\": [],\n \"p\": []\n }\n\n new_paragraph = {\n \"l\": []\n }\n\n new_line = {\n \"c\": [],\n \"t\": []\n }\n\n new_token = {\n \"c\": [],\n \"tx\": \"\"\n }\n\n for primitive in soup.find_all(\"primitive\"):\n\n # store coordinate of text areas (boxes) by page\n # 1) page number, 2) coordinate list\n region = copy.deepcopy(new_region)\n region[\"c\"] = [int(i) for i in primitive.get('box').split(\" \")]\n\n para = None\n line = None\n line_counter = 0\n\n for tag in primitive.find_all(recursive=False):\n\n if tag.name == \"l\":\n\n if para is None and line is None:\n para = copy.deepcopy(new_paragraph)\n line = copy.deepcopy(new_line)\n\n if line_counter > 0 and line is not None:\n line = normalize_line(line, out[\"meta\"][\"language\"])\n para[\"l\"].append(line)\n\n if tag.get(\"p\") in [\"S\", \"SA\"] and line_counter > 0:\n region[\"p\"].append(para)\n para = copy.deepcopy(new_paragraph)\n\n line = copy.deepcopy(new_line)\n line[\"c\"] = [\n int(i)\n for i in tag.get('box').split(\" \")\n ]\n line_counter += 1\n\n if tag.name in [\"w\", \"q\"]:\n\n # store coordinates of each token\n # 1) token, 2) page number, 3) coordinate list\n t = copy.deepcopy(new_token)\n t[\"c\"] = [int(i) for i in tag.get('box').split(\" \")]\n t[\"tx\"] = tag.string\n t[\"s\"] = int(tag.get('style_ref'))\n\n if tag.name == \"q\" and tag.get('qid') is not None:\n qid = tag.get('qid')\n normalized_form = soup.find('qw', qid=qid).text\n t[\"nf\"] = normalized_form\n t[\"qid\"] = qid\n\n # append the token to the line\n line[\"t\"].append(t)\n\n # append orphan lines\n if line is not None:\n line = normalize_line(line, out[\"meta\"][\"language\"])\n para[\"l\"].append(line)\n\n region[\"p\"].append(para)\n\n if para is not None:\n out[\"r\"].append(region)\n\n out[\"legacy\"][\"id\"] = identifier\n out[\"legacy\"][\"source\"] = soup.link['source']\n \"\"\"\n # I suspect this could be deleted\n out[\"legacy\"][\"word_count\"] = int(soup.meta['wordcnt'])\n out[\"legacy\"][\"chars_count\"] = int(soup.meta['total_chars_count'])\n suspicious_chars_count = int(soup.meta['suspicious_chars_count'])\n out[\"legacy\"][\"suspicious_chars_count\"] = int(suspicious_chars_count)\n \"\"\"\n out[\"legacy\"][\"first_id\"] = soup.link['first_id']\n out[\"legacy\"][\"last_id\"] = soup.link['last_id']\n out[\"legacy\"][\"next_id\"] = soup.link['next_id']\n out[\"legacy\"][\"prev_id\"] = soup.link['prev_id']\n\n if root.has_attr('continuation_from'):\n out[\"legacy\"][\"continuation_from\"] = root['continuation_from']\n\n if root.has_attr('continuation_to'):\n out[\"legacy\"][\"continuation_to\"] = root['continuation_to']\n\n return out","def read_speeches(filename):\n\n # Open a speech file\n speech_file = open(filename)\n\n # Create a new dictionary\n speech_dict = {}\n\n # Iterate over lines\n for line in speech_file:\n # Replace whitespace, including /n, at the end of a line with a single space\n line = line.rstrip() + ' '\n\n # Given that a title begins with #\n if line.startswith('#'):\n # Remove '# ' at the beginning and ': ' at the end, to be used as a title\n title = line[2:-2]\n # Assign the tile as a key in the dictionary\n speech_dict[title] = ''\n # A speech line does not begins with #\n else:\n # Not begins with [ either\n if line.startswith('[') is False:\n # Append the speech line to the already existing string of the corresponding title\n # The tile variable is kept from the previous loop(s)\n speech_dict[title] += line\n\n # Close the file\n speech_file.close()\n\n return speech_dict","def _process_data(self, wiki_xml):\r\n MEDIAWIKI_NS = 'http://www.mediawiki.org/xml/export-0.3/'\r\n sequences = []\r\n lw_url_re = re.compile(r'\\[(http://lesswrong\\.com/lw/[^ ]+) [^\\]]+\\]')\r\n\r\n for page in wiki_xml.getroot().iterfind('.//{%s}page' % MEDIAWIKI_NS): # TODO: Change to use iterparse\r\n # Get the titles\r\n title = page.findtext('{%s}title' % MEDIAWIKI_NS)\r\n\r\n # See if this page is a sequence page\r\n sequence_elem = page.xpath(\"mw:revision[1]/mw:text[contains(., '[[Category:Sequences]]')]\", namespaces={'mw': MEDIAWIKI_NS})\r\n\r\n if sequence_elem:\r\n sequence_elem = sequence_elem[0]\r\n articles = []\r\n\r\n # Find all the lesswrong urls\r\n for match in lw_url_re.finditer(sequence_elem.text):\r\n article_url = UrlParser(match.group(1))\r\n\r\n # Only store the path to the article\r\n article_path = article_url.path\r\n\r\n # Ensure path ends in slash\r\n if article_path[-1] != '/':\r\n article_path += '/'\r\n\r\n articles.append(article_path)\r\n\r\n sequences.append({\r\n 'title': title,\r\n 'articles': articles\r\n })\r\n return {'sequences': sequences}","def eficas_translation(ts_file, new_ts_file, lang):\n dicoCataToLabel={}\n dicoCataToTelemac={}\n header = '<?xml version=\"1.0\" encoding=\"utf-8\"?>'\n header +='<!DOCTYPE TS><TS version=\"1.1\" language=\"'+lang+'\">'\n header +='<context>\\n'\n header +=' <name>@deafult</name>\\n'\n\n end ='</context>\\n</TS>\\n'\n\n pattern_In=re.compile(r'^\\s*<source>(?P<ident>.*)</source>\\s*$')\n pattern_Out=re.compile(r'^\\s*<translation>(?P<traduit>.*)</translation>\\s*$')\n pattern_In2=re.compile(r'^\\s*<source2>(?P<ident>.*)</source2>\\s*$')\n pattern_Out2=re.compile(r'^\\s*<translation2>(?P<traduit>.*)</translation2>\\s*$')\n listeMaj=[]\n listeMaj.append(('for h','for H'))\n listeMaj.append(('pour h','pour H'))\n listeMaj.append(('for u','for U'))\n listeMaj.append(('pour u','pour U'))\n listeMaj.append(('of k','of K'))\n listeMaj.append(('de k','de K'))\n listeMaj.append(('of h','of H'))\n listeMaj.append(('de h','de H'))\n listeMaj.append(('u and v','U and V'))\n listeMaj.append(('u et v','U et V'))\n listeMaj.append(('on h','on H'))\n listeMaj.append(('sur h','sur H'))\n listeMaj.append(('supg','SUPG'))\n listeMaj.append(('k and epsilon','K and Epsilon'))\n listeMaj.append(('k-epsilon','K-Epsilon'))\n listeMaj.append(('gmres','GMRES'))\n listeMaj.append(('cgstab','CGSTAB'))\n listeMaj.append(('q(z)','Q(Z)'))\n listeMaj.append(('z(q)','Z(Q)'))\n listeMaj.append(('wgs84','WGS84'))\n listeMaj.append(('wgs84','UTM'))\n listeMaj.append(('n-scheme','N-Scheme'))\n listeMaj.append(('scheme n','Scheme N'))\n listeMaj.append(('psi-scheme','PSI-Scheme'))\n listeMaj.append((' psi',' PSI'))\n listeMaj.append(('f(t90)','F(T90)'))\n listeMaj.append(('(pa)','(Pa)'))\n listeMaj.append(('h clipping','H clipping'))\n listeMaj.append(('delwaq','DELWAQ'))\n listeMaj.append(('tomawac','TOMAWAC'))\n listeMaj.append(('chezy','CHEZY'))\n listeMaj.append(('hllc','HLLC'))\n listeMaj.append(('c-u','C-U'))\n listeMaj.append(('c,u,v','C,U,V'))\n listeMaj.append(('h,u,v','H,U,V'))\n listeMaj.append(('previmer','PREVIMER'))\n listeMaj.append(('fes20xx','FES20XX'))\n listeMaj.append(('legos-nea','LEGOS-NEA'))\n listeMaj.append(('tpxo','TPXO'))\n listeMaj.append((' x',' X'))\n listeMaj.append((' y',' Y'))\n listeMaj.append(('waf','WAF'))\n listeMaj.append(('(w/kg)','(W/kg)'))\n listeMaj.append(('(j/kg)','(W/kg)'))\n listeMaj.append(('zokagoa','Zokagoa'))\n listeMaj.append(('nikuradse','Nikuradse'))\n listeMaj.append(('froude','Froude'))\n listeMaj.append(('gauss','Gauss'))\n listeMaj.append(('seidel','Seidel'))\n listeMaj.append(('leo','Leo'))\n listeMaj.append(('postma','Postma'))\n listeMaj.append(('crout','Crout'))\n listeMaj.append(('okada','Okada'))\n listeMaj.append(('jmj','JMJ'))\n listeMaj.append(('haaland','HAALAND'))\n listeMaj.append(('grad(u)','grad(U)'))\n listeMaj.append(('variable z','variable Z'))\n listeMaj.append(('variable r','variable R'))\n listeMaj.append(('ascii','ASCII'))\n\n with open(ts_file, 'r') as f:\n for ligne in f.readlines():\n if pattern_In.match(ligne):\n m = pattern_In.match(ligne)\n ident = m.group('ident')\n if pattern_Out.match(ligne):\n m = pattern_Out.match(ligne)\n traduit = m.group('traduit')\n dicoCataToTelemac[ident] = traduit\n traduitMin = traduit.lower()\n for t in listeMaj :\n traduit = traduitMin.replace(t[0], t[1])\n traduitMin = traduit\n chaine = traduitMin[0].upper() + traduitMin[1:]\n dicoCataToLabel[ident] = chaine\n if pattern_In2.match(ligne):\n m = pattern_In2.match(ligne)\n ident = m.group('ident')\n if pattern_Out2.match(ligne):\n m = pattern_Out2.match(ligne)\n traduit = m.group('traduit')\n dicoCataToTelemac[ident] = traduit\n dicoCataToLabel[ident] = traduit\n\n with open(new_ts_file, 'w') as f:\n f.write(header)\n for k in dicoCataToTelemac :\n text = \" <message>\\n <source>\"\n text += k\n text += \"</source>\\n <translation>\"\n text += dicoCataToLabel[k]\n text += \"</translation>\\n </message>\\n\"\n f.write(text)\n f.write(end)","def read_subtitles(self):\n\n # Group 1: index, Group 2: Start Time, Group 3: End Time, Group 4: Text\n\n patterns = [\n r\"(\\d+)\\n(\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d) --> (\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d)\\n((?:.+\\n)*.+)\",\n r\"(\\d+)\\r\\n(\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d) --> (\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d)\\r\\n((?:.+\\r\\n)*.+)\",\n # Reports pattern\n r\"(\\d+)\\r(\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d) --> (\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d)\\n((?:.+\\r)*.+)\"\n ]\n\n for pattern in patterns:\n re_subs = re.findall(pattern, self.subtitles, re.M | re.I)\n if(len(re_subs) > 1):\n self.re_subs = re_subs\n return\n\n raise Exception(\n f're_subs length is {len(re_subs)}. Maybe the regex pattern is falty?')","def getSubtitleURL(self):\n\n # If it is a movie, we use this methodology -\n try:\n IndexingParameters = [\"subtitleUrls\", 0, \"url\"]\n TitleParamters = [\n \"catalogMetadata\", \"catalog\", \"title\", \"episodeNumber\"]\n subRequestObject = requests.get(self.subtitleURLContainer)\n\n parsedJsonObject = json.loads(str(subRequestObject.text))\n SubsURL = parsedJsonObject[IndexingParameters[0]][\n IndexingParameters[1]][IndexingParameters[2]]\n if self.title == \"Amazonsubtitles\":\n try:\n self.title = parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[2]] + \"_\" + str(\n parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[3]])\n except:\n pass\n\n return SubsURL\n\n except:\n pass\n pass","def elem_to_programme(elem):\n d = {'start': elem.get('start'),\n 'channel': elem.get('channel'),\n 'title': []}\n\n set_attrs(d, elem, ('stop', 'pdc-start', 'vps-start', 'showview',\n 'videoplus', 'clumpidx'))\n\n append_text(d, 'title', elem)\n append_text(d, 'sub-title', elem)\n append_text(d, 'desc', elem)\n\n crednode = elem.find('credits')\n if crednode is not None:\n creddict = {}\n # TODO: actor can have a 'role' attribute\n for credtype in ('director', 'actor', 'writer', 'adapter', 'producer',\n 'presenter', 'commentator', 'guest', 'composer',\n 'editor'):\n append_text(creddict, credtype, crednode, with_lang=False)\n d['credits'] = creddict\n\n set_text(d, 'date', elem, with_lang=False)\n append_text(d, 'category', elem)\n set_text(d, 'language', elem)\n set_text(d, 'orig-language', elem)\n\n lennode = elem.find('length')\n if lennode is not None:\n lend = {'units': lennode.get('units'),\n 'length': lennode.text}\n d['length'] = lend\n\n append_icons(d, elem)\n append_text(d, 'url', elem, with_lang=False)\n append_text(d, 'country', elem)\n\n for epnumnode in elem.findall('episode-num'):\n if not d.has_key('episode-num'):\n d['episode-num'] = []\n d['episode-num'].append((epnumnode.text,\n epnumnode.get('system', 'xmltv_ns')))\n\n vidnode = elem.find('video')\n if vidnode is not None:\n vidd = {}\n for name in ('present', 'colour'):\n set_boolean(vidd, name, vidnode)\n for videlem in ('aspect', 'quality'):\n venode = vidnode.find(videlem)\n if venode is not None:\n vidd[videlem] = venode.text\n d['video'] = vidd\n\n audnode = elem.find('audio')\n if audnode is not None:\n audd = {}\n set_boolean(audd, 'present', audnode)\n stereonode = audnode.find('stereo')\n if stereonode is not None:\n audd['stereo'] = stereonode.text\n d['audio'] = audd\n\n psnode = elem.find('previously-shown')\n if psnode is not None:\n psd = {}\n set_attrs(psd, psnode, ('start', 'channel'))\n d['previously-shown'] = psd\n\n set_text(d, 'premiere', elem)\n set_text(d, 'last-chance', elem)\n\n if elem.find('new') is not None:\n d['new'] = True\n\n for stnode in elem.findall('subtitles'):\n if not d.has_key('subtitles'):\n d['subtitles'] = []\n std = {}\n set_attrs(std, stnode, ('type',))\n set_text(std, 'language', stnode)\n d['subtitles'].append(std)\n\n for ratnode in elem.findall('rating'):\n if not d.has_key('rating'):\n d['rating'] = []\n ratd = {}\n set_attrs(ratd, ratnode, ('system',))\n set_text(ratd, 'value', ratnode, with_lang=False)\n append_icons(ratd, ratnode)\n d['rating'].append(ratd)\n\n for srnode in elem.findall('star-rating'):\n if not d.has_key('star-rating'):\n d['star-rating'] = []\n srd = {}\n set_attrs(srd, srnode, ('system',))\n set_text(srd, 'value', srnode, with_lang=False)\n append_icons(srd, srnode)\n d['star-rating'].append(srd)\n\n for revnode in elem.findall('review'):\n if not d.has_key('review'):\n d['review'] = []\n rd = {}\n set_attrs(rd, revnode, ('type', 'source', 'reviewer',))\n set_text(rd, 'value', revnode, with_lang=False)\n d['review'].append(rd)\n\n return d","def parse_title(self, pre):\n # Extract datapoints\n title_text = str(pre)\n title = {}\n\n identity_data = self.identity_regex.search(title_text)\n title['linc'] = int(identity_data.group(1).strip().replace(' ', ''))\n title['short_legal'] = identity_data.group(2).strip().replace(';', ' ')\n title['title_number'] = identity_data.group(3).strip()\n\n try:\n title['ats_reference'] = self.ats_regex.search(title_text).group(1).replace(';',' ')\n except AttributeError:\n title['ats_reference'] = ''\n\n title['municipality'] = self.municipality_regex.search(title_text).group(1).replace('\\r','')\n\n try:\n references = self.reference_regex.search(title_text).group(1).split(\"\\n\")\n references = [i.strip() for i in references]\n references = list(filter(None, references))\n title['reference_number'] = references\n except AttributeError:\n title['reference_number'] = ['']\n\n payday_raw = self.payday_regex.search(title_text).group(3).strip('</pre>').strip()\n title['registration'] = payday_raw[:11]\n title['date'] = reversed(payday_raw[15:25].split('/'))\n title['date'] = '-'.join(title['date'])\n title['document_type'] = payday_raw[27:46].strip()\n\n title['value'] = self._try_int(payday_raw[46:62].strip())\n title['consideration'] = self._try_int(payday_raw[62:80].strip())\n\n if \"CONDOMINIUM\" in title_text:\n title['condo'] = True\n else:\n title['condo'] = False\n\n title['title_text'] = title_text.strip('<pre>').strip('</pre>').strip()\n\n return title","def to_xml_dict(self):\n self._check_required_fields()\n\n root = odict[\n \"r:import\": odict[\n \"@xmlns:r\": \"http://resolver.nkp.cz/v3/\",\n \"r:monograph\": odict[\n \"r:titleInfo\": odict[\n \"r:title\": self.title,\n ],\n ],\n ]\n ]\n mono_root = root[\"r:import\"][\"r:monograph\"]\n\n # subtitle\n MonographComposer._assign_pattern(\n mono_root[\"r:titleInfo\"],\n \"r:subTitle\",\n self.subtitle\n )\n\n # handle ccnb, isbn, uuid\n self._add_identifier(mono_root, \"ccnb\")\n self._add_identifier(mono_root, \"isbn\")\n self._add_identifier(mono_root, \"other_id\", out=\"otherId\")\n\n # add form of the book\n MonographComposer._assign_pattern(\n mono_root,\n \"r:documentType\",\n self.document_type\n )\n\n mono_root[\"r:digitalBorn\"] = \"true\" if self.digital_born else \"false\"\n\n if self.author:\n mono_root[\"r:primaryOriginator\"] = odict[\n \"@type\": \"AUTHOR\",\n \"#text\": self.author\n ]\n\n if any([self.place, self.publisher, self.year]):\n publ = odict()\n\n MonographComposer._assign_pattern(\n publ,\n \"r:publisher\",\n self.publisher\n )\n MonographComposer._assign_pattern(publ, \"r:place\", self.place)\n MonographComposer._assign_pattern(publ, \"r:year\", self.year)\n\n mono_root[\"r:publication\"] = publ\n\n if self.format:\n format_dict = MonographComposer._create_path(\n root,\n odict,\n [\n \"r:import\",\n \"r:digitalDocument\",\n \"r:technicalMetadata\",\n \"r:format\",\n ]\n )\n\n format_dict[\"#text\"] = self.format\n\n return root","def convert(text: str) -> Iterator[Tuple[str, str]]:\n with gzip.open(resource_filename(\"nautc\", \"txt.gz\"), \"rt\") as txt:\n return (\n lambda idxs: map(\n lambda kv: (\n kv[0],\n \"\".join(\n map(\n lambda char: char in idxs\n and kv[1][idxs[char]]\n or char,\n text,\n )\n ),\n ),\n (\n lambda lines: map(\n lambda t, c: (t, c.split(\"||\")),\n lines[::2],\n lines[1::2],\n )\n )(txt.read().splitlines()),\n )\n )(\n dict(\n map(\n lambda kv: (kv[1], kv[0]),\n enumerate(ascii_letters + digits),\n )\n )\n )","def xml_to_dict(args):\n rdict = dict()\n args = re.sub(r'xmlns=\\\".+?\\\"', '', args)\n root = ET.fromstring(args)\n ifmtrunk = root.find('.//ifmtrunk')\n if ifmtrunk is not None:\n try:\n ifmtrunk_iter = ET.Element.iter(ifmtrunk)\n except AttributeError:\n ifmtrunk_iter = ifmtrunk.getiterator()\n\n for ele in ifmtrunk_iter:\n if ele.text is not None and len(ele.text.strip()) > 0:\n rdict[ele.tag] = ele.text\n return rdict","def getXmlDict(oxml):\n lines = oxml.split(\"\\n\")\n rrd_d = {}\n # <cf> AVERAGE </cf>\n # <pdp_per_row> 288 </pdp_per_row> <!-- 86400 seconds -->\n\n # parse xml file\n key = \"\"\n rows = [] \n for line in lines:\n if (reMatchCF(line)):\n cf = line.split()[1]\n key += cf\n if (reMatchPDP(line)):\n pdp = line.split()[1]\n key += pdp\n if (reMatchRow(line)):\n ele = line.split()\n time = ele[5]\n val = ele[8]\n rows.append([time,val,line])\n # end of rra is reached, store to dict and rest vals\n if (reMatchDBEnd(line) and key and rows):\n rrd_d[key] = rows\n key = \"\"\n rows = []\n return rrd_d","def generate_subs(speed, source_speed, source_subs):\r\n if speed == source_speed:\r\n return source_subs\r\n\r\n coefficient = 1.0 * speed / source_speed\r\n subs = {\r\n 'start': [\r\n int(round(timestamp * coefficient)) for\r\n timestamp in source_subs['start']\r\n ],\r\n 'end': [\r\n int(round(timestamp * coefficient)) for\r\n timestamp in source_subs['end']\r\n ],\r\n 'text': source_subs['text']}\r\n return subs","def parse_to_json(self, content):\n if content:\n stix_dict = STIXPackage.from_xml(etree.XML(content)).to_dict() # parse to dictionary\n return stix_dict\n else:\n return {}","def xml_to_dict(self):\n medicine_node = ['medicines', 'dose', 'unit', 'unit_price', 'goods_num', 'dose_that',\n 'remark', 'm_usage', 'goods_norms', 'goods_orgin', 'MedPerDos', 'MedPerDay']\n dict_data = {}\n n = 0\n xq_childs = 0\n for child in self.root.iter():\n # print(child.tag)\n # print(child.text)\n if child.tag not in medicine_node:\n if child.tag == 'xq':\n xq_childs = child.__len__() # __len__：返回元素大小，元素的大小为元素的子元素数量\n dict_data[child.tag] = child.text\n else:\n if n < xq_childs:\n dict_data[child.tag] = [child.text]\n n += 1\n else:\n dict_data[child.tag].append(child.text)\n return dict_data","def extract_staxml_info(staxml):\n instruments = defaultdict(dict)\n\n if isinstance(staxml, Inventory):\n inv = staxml\n else:\n if os.path.isfile(staxml):\n inv = safe_load_staxml(staxml)\n else:\n raise ValueError(\"Input staxml is neither obspy.Inventory or \"\n \"staxml file\")\n for nw in inv:\n nw_code = nw.code\n for sta in nw:\n sta_code = sta.code\n for chan in sta:\n chan_code = chan.code\n loc_code = chan.location_code\n key = \"%s.%s.%s.%s\" % (nw_code, sta_code, loc_code, chan_code)\n instruments[key][\"latitude\"] = chan.latitude\n instruments[key][\"longitude\"] = chan.longitude\n instruments[key][\"elevation\"] = chan.elevation\n instruments[key][\"depth\"] = chan.depth\n if chan.sensor.description is not None:\n sensor_type = chan.sensor.description\n elif chan.sensor.type is not None:\n sensor_type = chan.sensor.type\n else:\n sensor_type = \"None\"\n instruments[key][\"sensor\"] = sensor_type\n\n return instruments","def parse_m3u8_doc(self):\r\n lines = self.m3u8_doc.splitlines()\r\n lines = [line.strip() for line in lines if line.strip()]\r\n\r\n for i, line in enumerate(lines):\r\n\r\n if line.startswith('#EXT-X-VERSION'):\r\n self.playlist_version = line.split(':')[1]\r\n elif line.startswith('#EXT-X-PLAYLIST-TYPE'):\r\n self.playlist_type = line.split(':')[1]\r\n elif line.startswith('#EXT-X-MEDIA-SEQUENCE'):\r\n self.media_sequence = line.split(':')[1]\r\n elif line.startswith('#EXT-X-TARGETDURATION'):\r\n self.max_seg_duration = line.split(':')[1]\r\n\r\n elif line.startswith('#EXT-X-KEY'):\r\n key = Key()\r\n key.raw_line = line\r\n info = parse_m3u8_line(line)\r\n key.url = info.get('URI')\r\n key.method = info.get('METHOD')\r\n key.iv = info.get('IV')\r\n if key.method and key.url:\r\n if key.url.startswith('skd://'):\r\n # replace skd:// with https://\r\n key.url = key.url.replace('skd://', 'https://')\r\n\r\n key.url = urljoin(self.url, key.url)\r\n self.encrypted = True\r\n self.encryption_type = key.method\r\n self.current_key = key\r\n\r\n # stream #EXTINF tag must be followed by stream url\r\n elif line.startswith('#EXTINF'):\r\n try:\r\n self.seg_duration = float(line.split(':')[1].split(',')[0])\r\n self.total_duration += self.seg_duration\r\n except:\r\n pass\r\n\r\n next_line = lines[i + 1]\r\n seg = Segment()\r\n seg.url = next_line if not next_line.startswith('#') else None\r\n seg.duration = self.seg_duration\r\n seg.key = copy.copy(self.current_key)\r\n\r\n if seg.url:\r\n if seg.url.startswith('skd://'):\r\n # replace skd:// with https://\r\n seg.url = seg.url.replace('skd://', 'https://')\r\n\r\n seg.url = urljoin(self.url, seg.url)\r\n self.segments.append(seg)\r\n\r\n elif line.startswith('#EXT-X-ENDLIST'):\r\n # print('end of playlist')\r\n break\r\n\r\n # naming\r\n for i, seg in enumerate(self.segments):\r\n seg.name = os.path.join(self.d.temp_folder, f'{self.stream_type}_seg_{i + 1}.ts')\r\n\r\n if seg.key:\r\n seg.key.name = f'{seg.name}.key'","def get_media_info(xmlsent):\n media = {}\n media_element = xmlsent.findall(\".//{%s}media\" % NS)\n\n if media_element:\n media_element = media_element[0]\n media = {'start': media_element.attrib['start'],\n 'end': media_element.attrib['end'],\n 'unit': media_element.attrib['unit']\n }\n return media","def inf2dict(text):\n lines = text.strip().split('\\n')\n pairs, extra_lines = split_lines(lines)\n return parse_pairs(pairs, extra_lines)","def get_data(contents):\n\n header = {}\n copy = contents.split(\"\\n\")\n\n header_contents = dict(\n start_date=\"Start Date\",\n end_date=\" End Date\",\n subject=\" Subject\",\n experiment=\" Experiment\",\n group=\" Group\",\n box=\" Box\",\n start_time=\" Start Time\",\n end_time=\" End Time\",\n program=\" Program\",\n msn=\" MSN\",\n )\n\n for line in copy:\n for key in header_contents:\n heading = line.split(\":\")\n if heading[0] == header_contents[key]:\n if key == \"start_time\" or key == \"end_time\":\n header[key] = (\n heading[1].lstrip() + \":\" + heading[2] + \":\" + heading[3]\n )\n else:\n header[key] = heading[1].lstrip()\n\n data = {}\n copy = contents.split()\n\n uppercase = string.ascii_uppercase\n\n idx = []\n for i, val in enumerate(copy):\n if val[0] in uppercase and val[1] == \":\":\n idx.append(i)\n\n for i, j in zip(idx[:-1], idx[1:]):\n data[copy[i].lower()[0]] = [\n timestamp for timestamp in copy[i + 1 : j] if timestamp[-1] != \":\"\n ]\n\n return header, data","def get_translations(self) -> Dict[str, Dict[str, Tuple[str, Type]]]:\n\n return {\n 'material': {'elemental_proportion': ('elemental_proportions', dict)},\n }","def preprocess_text(text: str) -> Tuple[List[str], Dict]:\n raise NotImplementedError","def parse_book_record(root) -> dict:\n\n doc = {\n \"abstract\": \"\",\n \"pmid\": \"\",\n \"title\": \"\",\n \"authors\": [],\n \"pub_date\": \"\",\n \"journal_iso_title\": \"\",\n \"journal_title\": \"\",\n \"doi\": \"\",\n \"compounds\": [],\n \"mesh\": [],\n }\n\n doc[\"pmid\"] = root.xpath(\".//PMID/text()\")[0]\n\n doc[\"title\"] = next(iter(root.xpath(\".//BookTitle/text()\")))\n\n doc[\"authors\"] = []\n for author in root.xpath(\".//Author\"):\n last_name = next(iter(author.xpath(\"LastName/text()\")), \"\")\n first_name = next(iter(author.xpath(\"ForeName/text()\")), \"\")\n initials = next(iter(author.xpath(\"Initials/text()\")), \"\")\n if not first_name and initials:\n first_name = initials\n doc[\"authors\"].append(f\"{last_name}, {first_name}\")\n\n pub_year = next(iter(root.xpath(\".//Book/PubDate/Year/text()\")), None)\n pub_mon = next(iter(root.xpath(\".//Book/PubDate/Month/text()\")), \"Jan\")\n pub_day = next(iter(root.xpath(\".//Book/PubDate/Day/text()\")), \"01\")\n medline_date = next(\n iter(root.xpath(\".//Journal/JournalIssue/PubDate/MedlineDate/text()\")), None\n )\n\n pub_date = process_pub_date(pub_year, pub_mon, pub_day, medline_date)\n\n doc[\"pub_date\"] = pub_date\n\n for abstracttext in root.xpath(\".//Abstract/AbstractText\"):\n abstext = node_text(abstracttext)\n\n label = abstracttext.get(\"Label\", None)\n if label:\n doc[\"abstract\"] += f\"{label}: {abstext}\\n\"\n else:\n doc[\"abstract\"] += f\"{abstext}\\n\"\n\n doc[\"abstract\"] = doc[\"abstract\"].rstrip()\n\n return doc","def add_subtags(path, pxml_subtags):\n # print(\"CALLING... add_subtag\")\n root, tree = gen_tree(path)\n nmsps = root.nsmap['r']\n for k,v in pxml_subtags.items():\n subtag1 = tree.find(k)\n for i in v:\n if 'rId' not in i[1]:\n rId = f\"{{{nmsps}}}id\"\n subtext = etree.SubElement(subtag1, i[0])\n subtext.attrib['id'] = i[1]\n subtext.attrib[rId] = i[2]\n else:\n subtext = etree.SubElement(subtag1, i[0])\n subtext.attrib[rId] = i[1]\n tree.write(f'{output_path}/ppt/presentation.xml', pretty_print=True, xml_declaration=True, encoding='UTF-8', standalone=True)\n return","def subparse(block):\n\n verses = []\n context = None\n for char in block:\n\n if char == \"[\":\n if verses: verses[-1][\"quran\"] = verses[-1][\"quran\"].strip()\n verses.append({\"surah\": \"\", \"verse\": \"\", \"quran\": \"\"})\n context = \"surah\"\n elif char == \":\" and context == \"surah\":\n verses[-1][\"surah\"] = int(verses[-1][\"surah\"])\n context = \"verse\"\n elif char == \"]\":\n verses[-1][\"verse\"] = int(verses[-1][\"verse\"])\n context = \"quran\"\n else: verses[-1][context] += char\n\n verses[-1][\"quran\"] = verses[-1][\"quran\"].strip()\n return verses","def get_subtitle(annotation, sub_duration, video_clip, seen_annotations):\n if len(annotation[\"text\"]) == 0:\n return None\n\n annotation_txt = calculate_needed_subtitle_height(annotation, seen_annotations, video_clip)\n\n txt_clip = TextClip(annotation_txt, color=\"white\", fontsize=70, font='Sans Serif')\n txt_clip = txt_clip.set_position((\"center\", get_subtitle_offset(annotation, seen_annotations, video_clip)))\n txt_clip = txt_clip.set_start(float(annotation[\"time\"]) / 1000.0)\n txt_clip = txt_clip.set_duration(sub_duration)\n\n return txt_clip","def __init__(self, subtitle=None):\n self.subtitle = subtitle\n if not self.subtitle:\n self.parse_subtitles()","def xml_parse_prairie(xmlFileName,verbose=True):\n if verbose:\n print(\"parsing\",os.path.basename(xmlFileName))\n assert os.path.exists(xmlFileName), \"can't find \"+xmlFileName\n with open(xmlFileName) as f:\n xml=f.read()\n xml=xml.split(\">\")\n for i,line in enumerate(xml):\n xml[i]=line.strip()\n xml=\"\".join(xml)\n conf={}\n for key in ['opticalZoom','objectiveLens', # physical lens\n 'pixelsPerLine','linesPerFrame', # dimensions\n 'dwellTime','framePeriod','scanLinePeriod' # pixel timing\n 'laserPower', # laser settings\n 'pmtGain~1~','pmtGain~2~', # PMT settings\n 'INTENTIONAL_FAILURE', # just testing\n ]:\n val=xml_value_from_key(xml,key)\n if val is not None:\n conf[key.replace(\"~\",'')]=val\n times=[float(x.split('\"')[1]) for x in xml.split(\"absoluteTime=\")[1:]]\n conf[\"times\"]=np.array(times)\n if verbose and len(conf.keys()):\n print(\"XML parsing produced:\")\n for key in sorted(conf.keys()):\n if key is 'times':\n print(\" times=[%d points]\"%len(times))\n else:\n print(\" %s=%s\"%(key,conf[key]))\n return conf","def _build_transcript(self):\n\n # Create the transcript dictionary\n transcript_dict = dict()\n for splitted in self._get_transcript_entries(self._data_directory):\n transcript_dict[splitted[0]] = vocabulary.sentence_to_ids(splitted[1])\n\n return transcript_dict","def recursive_parse_xml_to_dict(xml):\n if not xml:\n return {xml.tag: xml.text}\n result = {}\n for child in xml:\n child_result = recursive_parse_xml_to_dict(child)\n if child.tag != 'object':\n result[child.tag] = child_result[child.tag]\n else:\n if child.tag not in result:\n result[child.tag] = []\n result[child.tag].append(child_result[child.tag])\n return {xml.tag: result}","def recursive_parse_xml_to_dict(xml):\n if not xml:\n return {xml.tag: xml.text}\n result = {}\n for child in xml:\n child_result = recursive_parse_xml_to_dict(child)\n if child.tag != 'object':\n result[child.tag] = child_result[child.tag]\n else:\n if child.tag not in result:\n result[child.tag] = []\n result[child.tag].append(child_result[child.tag])\n return {xml.tag: result}","def __build_dictionary(self):\n def recursive_generation(t):\n \"\"\"\n Nested helper function that recursively loops through an XML node to construct a dictionary.\n Solution from http://stackoverflow.com/a/10077069 (2013-01-19)\n \"\"\"\n d = {t.tag: {} if t.attrib else None}\n children = list(t)\n\n if children:\n dd = defaultdict(list)\n\n for dc in map(recursive_generation, children):\n for k, v in dc.iteritems():\n dd[k].append(v)\n\n d = {t.tag: {k:v[0] if len(v) == 1 else v for k, v in dd.iteritems()}}\n\n if t.attrib:\n d[t.tag].update(('@' + k, v) for k, v in t.attrib.iteritems())\n\n if t.text:\n text = t.text.strip()\n\n if children or t.attrib:\n if text:\n d[t.tag]['#text'] = text\n else:\n d[t.tag] = text\n\n return d\n \n string_repr = etree.tostring(self._config_file, pretty_print=True)\n element_tree = cElementTree.XML(string_repr)\n \n self._config_dict = recursive_generation(element_tree)\n self._config_dict = self._config_dict[self._config_dict.keys()[0]]","def parse_svn_info_xml(xml_string):\r\n d = {}\r\n tree = ET.fromstring(xml_string)\r\n entry = tree.find('.//entry')\r\n if entry:\r\n d['url'] = entry.find('url').text\r\n d['revision'] = int(entry.get('revision'))\r\n d['repos_url'] = tree.find('.//repository/root').text\r\n d['last_changed_rev'] = int(tree.find('.//commit').get('revision'))\r\n d['kind'] = entry.get('kind')\r\n return d","def parsexml0(xmltext, startingat=0, toplevel=1,\n # snarf in some globals\n entityReplacer=unEscapeContentList,\n #len=len, None=None\n #LENCDATAMARKER=LENCDATAMARKER, CDATAMARKER=CDATAMARKER\n ):\n #print \"parsexml0\", repr(xmltext[startingat: startingat+10])\n # DEFAULTS\n NameString = NONAME\n ContentList = AttDict = ExtraStuff = None\n if toplevel is not None:\n #if verbose: print \"at top level\"\n #if startingat!=0:\n # raise ValueError, \"have to start at 0 for top level!\"\n xmltext = xmltext.strip()\n cursor = startingat\n #look for interesting starting points\n firstbracket = xmltext.find(\"<\", cursor)\n afterbracket2char = xmltext[firstbracket+1:firstbracket+3]\n #print \"a\", repr(afterbracket2char)\n #firstampersand = xmltext.find(\"&\", cursor)\n #if firstampersand>0 and firstampersand<firstbracket:\n # raise ValueError, \"I don't handle ampersands yet!!!\"\n docontents = 1\n if firstbracket<0:\n # no tags\n #if verbose: print \"no tags\"\n if toplevel is not None:\n #D = {NAMEKEY: NONAME, CONTENTSKEY: [xmltext[cursor:]]}\n ContentList = [xmltext[cursor:]]\n if entityReplacer: ContentList = entityReplacer(ContentList)\n return (NameString, AttDict, ContentList, ExtraStuff), len(xmltext)\n else:\n raise ValueError(\"no tags at non-toplevel %s\" % repr(xmltext[cursor:cursor+20]))\n #D = {}\n L = []\n # look for start tag\n # NEED to force always outer level is unnamed!!!\n #if toplevel and firstbracket>0:\n #afterbracket2char = xmltext[firstbracket:firstbracket+2]\n if toplevel is not None:\n #print \"toplevel with no outer tag\"\n NameString = name = NONAME\n cursor = skip_prologue(xmltext, cursor)\n #break\n elif firstbracket<0:\n raise ValueError(\"non top level entry should be at start tag: %s\" % repr(xmltext[:10]))\n # special case: CDATA\n elif afterbracket2char==\"![\" and xmltext[firstbracket:firstbracket+9]==\"<![CDATA[\":\n #print \"in CDATA\", cursor\n # skip straight to the close marker\n startcdata = firstbracket+9\n endcdata = xmltext.find(CDATAENDMARKER, startcdata)\n if endcdata<0:\n raise ValueError(\"unclosed CDATA %s\" % repr(xmltext[cursor:cursor+20]))\n NameString = CDATAMARKER\n ContentList = [xmltext[startcdata: endcdata]]\n cursor = endcdata+len(CDATAENDMARKER)\n docontents = None\n # special case COMMENT\n elif afterbracket2char==\"!-\" and xmltext[firstbracket:firstbracket+4]==\"<!--\":\n #print \"in COMMENT\"\n endcommentdashes = xmltext.find(\"--\", firstbracket+4)\n if endcommentdashes<firstbracket:\n raise ValueError(\"unterminated comment %s\" % repr(xmltext[cursor:cursor+20]))\n endcomment = endcommentdashes+2\n if xmltext[endcomment]!=\">\":\n raise ValueError(\"invalid comment: contains double dashes %s\" % repr(xmltext[cursor:cursor+20]))\n return (None, endcomment+1) # shortcut exit\n else:\n # get the rest of the tag\n #if verbose: print \"parsing start tag\"\n # make sure the tag isn't in doublequote pairs\n closebracket = xmltext.find(\">\", firstbracket)\n noclose = closebracket<0\n startsearch = closebracket+1\n pastfirstbracket = firstbracket+1\n tagcontent = xmltext[pastfirstbracket:closebracket]\n # shortcut, no equal means nothing but name in the tag content\n if '=' not in tagcontent:\n if tagcontent[-1]==\"/\":\n # simple case\n #print \"simple case\", tagcontent\n tagcontent = tagcontent[:-1]\n docontents = None\n name = tagcontent.strip()\n NameString = name\n cursor = startsearch\n else:\n if '\"' in tagcontent:\n # check double quotes\n stop = None\n # not inside double quotes! (the split should have odd length)\n if noclose or len((tagcontent+\".\").split('\"'))% 2:\n stop=1\n while stop is None:\n closebracket = xmltext.find(\">\", startsearch)\n startsearch = closebracket+1\n noclose = closebracket<0\n tagcontent = xmltext[pastfirstbracket:closebracket]\n # not inside double quotes! (the split should have odd length)\n if noclose or len((tagcontent+\".\").split('\"'))% 2:\n stop=1\n if noclose:\n raise ValueError(\"unclosed start tag %s\" % repr(xmltext[firstbracket:firstbracket+20]))\n cursor = startsearch\n #cursor = closebracket+1\n # handle simple tag /> syntax\n if xmltext[closebracket-1]==\"/\":\n #if verbose: print \"it's a simple tag\"\n closebracket = closebracket-1\n tagcontent = tagcontent[:-1]\n docontents = None\n #tagcontent = xmltext[firstbracket+1:closebracket]\n tagcontent = tagcontent.strip()\n taglist = tagcontent.split(\"=\")\n #if not taglist:\n # raise ValueError, \"tag with no name %s\" % repr(xmltext[firstbracket:firstbracket+20])\n taglist0 = taglist[0]\n taglist0list = taglist0.split()\n #if len(taglist0list)>2:\n # raise ValueError, \"bad tag head %s\" % repr(taglist0)\n name = taglist0list[0]\n #print \"tag name is\", name\n NameString = name\n # now parse the attributes\n attributename = taglist0list[-1]\n # put a fake att name at end of last taglist entry for consistent parsing\n taglist[-1] = taglist[-1]+\" f\"\n AttDict = D = {}\n taglistindex = 1\n lasttaglistindex = len(taglist)\n #for attentry in taglist[1:]:\n while taglistindex<lasttaglistindex:\n #print \"looking for attribute named\", attributename\n attentry = taglist[taglistindex]\n taglistindex = taglistindex+1\n attentry = attentry.strip()\n if attentry[0]!='\"':\n raise ValueError(\"attribute value must start with double quotes\" + repr(attentry))\n while '\"' not in attentry[1:]:\n # must have an = inside the attribute value...\n if taglistindex>lasttaglistindex:\n raise ValueError(\"unclosed value \" + repr(attentry))\n nextattentry = taglist[taglistindex]\n taglistindex = taglistindex+1\n attentry = \"%s=%s\" % (attentry, nextattentry)\n attentry = attentry.strip() # only needed for while loop...\n attlist = attentry.split()\n nextattname = attlist[-1]\n attvalue = attentry[:-len(nextattname)]\n attvalue = attvalue.strip()\n try:\n first = attvalue[0]; last=attvalue[-1]\n except:\n raise ValueError(\"attvalue,attentry,attlist=\"+repr((attvalue, attentry,attlist)))\n if first==last=='\"' or first==last==\"'\":\n attvalue = attvalue[1:-1]\n #print attributename, \"=\", attvalue\n D[attributename] = attvalue\n attributename = nextattname\n # pass over other tags and content looking for end tag\n if docontents is not None:\n #print \"now looking for end tag\"\n ContentList = L\n while docontents is not None:\n nextopenbracket = xmltext.find(\"<\", cursor)\n if nextopenbracket<cursor:\n #if verbose: print \"no next open bracket found\"\n if name==NONAME:\n #print \"no more tags for noname\", repr(xmltext[cursor:cursor+10])\n docontents=None # done\n remainder = xmltext[cursor:]\n cursor = len(xmltext)\n if remainder:\n L.append(remainder)\n else:\n raise ValueError(\"no close bracket for %s found after %s\" % (name,repr(xmltext[cursor: cursor+20])))\n # is it a close bracket?\n elif xmltext[nextopenbracket+1]==\"/\":\n #print \"found close bracket\", repr(xmltext[nextopenbracket:nextopenbracket+20])\n nextclosebracket = xmltext.find(\">\", nextopenbracket)\n if nextclosebracket<nextopenbracket:\n raise ValueError(\"unclosed close tag %s\" % repr(xmltext[nextopenbracket: nextopenbracket+20]))\n closetagcontents = xmltext[nextopenbracket+2: nextclosebracket]\n closetaglist = closetagcontents.split()\n #if len(closetaglist)!=1:\n #print closetagcontents\n #raise ValueError, \"bad close tag format %s\" % repr(xmltext[nextopenbracket: nextopenbracket+20])\n # name should match\n closename = closetaglist[0]\n #if verbose: print \"closetag name is\", closename\n if name!=closename:\n prefix = xmltext[:cursor]\n endlinenum = len(prefix.split(\"\\n\"))\n prefix = xmltext[:startingat]\n linenum = len(prefix.split(\"\\n\"))\n raise ValueError(\"at lines %s...%s close tag name doesn't match %s...%s %s\" %(\n linenum, endlinenum, repr(name), repr(closename), repr(xmltext[cursor: cursor+100])))\n remainder = xmltext[cursor:nextopenbracket]\n if remainder:\n #if verbose: print \"remainder\", repr(remainder)\n L.append(remainder)\n cursor = nextclosebracket+1\n #print \"for\", name, \"found close tag\"\n docontents = None # done\n # otherwise we are looking at a new tag, recursively parse it...\n # first record any intervening content\n else:\n remainder = xmltext[cursor:nextopenbracket]\n if remainder:\n L.append(remainder)\n #if verbose:\n # #print \"skipping\", repr(remainder)\n # #print \"--- recursively parsing starting at\", xmltext[nextopenbracket:nextopenbracket+20]\n (parsetree, cursor) = parsexml0(xmltext, startingat=nextopenbracket, toplevel=None, entityReplacer=entityReplacer)\n if parsetree:\n L.append(parsetree)\n # maybe should check for trailing garbage?\n # toplevel:\n # remainder = xmltext[cursor:].strip()\n # if remainder:\n # raise ValueError, \"trailing garbage at top level %s\" % repr(remainder[:20])\n if ContentList:\n if entityReplacer: ContentList = entityReplacer(ContentList)\n t = (NameString, AttDict, ContentList, ExtraStuff)\n return (t, cursor)","def analysis_to_subword_dicts(ana):\n return map(pairs_to_dict, chunk_subwords(analysis_to_pairs(ana)))","def _parse_xml(self):\n self.properties = {}\n pages = self.root.findall('page')\n self.pages = {} \n\n for page_num, page in enumerate(pages): \n\n _, _ , width, height = page.attrib[\"bbox\"].split(\",\")\n width, height = float(width), float(height)\n \n page_object = {\"page\": page_num + 1 , \"width\": width, \"height\": height} \n lines = self.root.findall('page[@id=\\'{}\\']/textbox/textline'.format(page_num+1)) \n print(\"{} Number of Lines in Page {}\".format(len(lines), page_num))\n \n self.bbox = {'x1': [] , 'y1':[], 'x2':[], 'y2':[]}\n textlines = self.root.findall('page[@id=\\'{}\\']/textbox/textline'.format(page_num+1)) \n textlines = sorted(textlines, key= lambda x: -float(x.attrib['bbox'].split(',')[3]))\n \n \n line_objects = []\n for idx, item in enumerate(textlines):\n item_props = self._extract_textline_properties(item)\n bbox = item.attrib['bbox'].split(',')\n item_props[\"x0\"] = Decimal(bbox[0])\n item_props[\"x1\"] = Decimal(bbox[2])\n item_props[\"y0\"] = Decimal(bbox[1])\n item_props[\"y1\"] = Decimal(bbox[3])\n item_props[\"top\"] = Decimal(height - float(bbox[3]))\n item_props[\"bottom\"] = Decimal(height - float(bbox[1]))\n\n line_objects.append(item_props)\n page_object[\"lines\"] = line_objects\n \n \n others = [] \n# for key in [\"rect\", \"figure\", \"layout/textgroup\", \"curve\"]: \n for key in [\"curve\", \"rect\", \"figure\"]: \n other_objs = self.root.findall('page[@id=\\'{}\\']/{}'.format(page_num+1, key)) \n for idx, item in enumerate(other_objs):\n \n item_props = {\"type\": key}\n# print(key, ET.tostring(item))\n bbox = item.attrib['bbox'].split(',')\n item_props[\"x0\"] = Decimal(bbox[0])\n item_props[\"x1\"] = Decimal(bbox[2])\n item_props[\"y0\"] = Decimal(bbox[1])\n item_props[\"y1\"] = Decimal(bbox[3]) \n item_props[\"top\"] = Decimal(height - float(bbox[3]))\n item_props[\"bottom\"] = Decimal(height - float(bbox[1]))\n others.append(item_props)\n \n page_object[\"others\"] = others\n page = Page(page_object)\n page_object[\"para\"] = page.para\n page_object[\"plines\"] = page.lines\n page_object[\"bigbox\"] = page.bigbox\n page_object[\"components\"] = page.components\n\n self.pages[page_num+1] = page_object","def __title_context_dict(data):\n d = {}\n if isinstance(data, str):\n raw_data = __load_data(data)['data']\n else:\n raw_data = data['data']\n for i in range(len(raw_data)):\n title = raw_data[i]['title']\n paragraphs = raw_data[i]['paragraphs']\n text = []\n for j in range(len(paragraphs)):\n text.append(paragraphs[j]['context'])\n context = ' '.join(text)\n d[title] = context\n return d","def get_transcripts_from_youtube(youtube_id, settings, i18n):\r\n _ = i18n.ugettext\r\n\r\n utf8_parser = etree.XMLParser(encoding='utf-8')\r\n\r\n youtube_text_api = copy.deepcopy(settings.YOUTUBE['TEXT_API'])\r\n youtube_text_api['params']['v'] = youtube_id\r\n data = requests.get('http://' + youtube_text_api['url'], params=youtube_text_api['params'])\r\n\r\n if data.status_code != 200 or not data.text:\r\n msg = _(\"Can't receive transcripts from Youtube for {youtube_id}. Status code: {status_code}.\").format(\r\n youtube_id=youtube_id,\r\n status_code=data.status_code\r\n )\r\n raise GetTranscriptsFromYouTubeException(msg)\r\n\r\n sub_starts, sub_ends, sub_texts = [], [], []\r\n xmltree = etree.fromstring(data.content, parser=utf8_parser)\r\n for element in xmltree:\r\n if element.tag == \"text\":\r\n start = float(element.get(\"start\"))\r\n duration = float(element.get(\"dur\", 0)) # dur is not mandatory\r\n text = element.text\r\n end = start + duration\r\n\r\n if text:\r\n # Start and end should be ints representing the millisecond timestamp.\r\n sub_starts.append(int(start * 1000))\r\n sub_ends.append(int((end + 0.0001) * 1000))\r\n sub_texts.append(text.replace('\\n', ' '))\r\n\r\n return {'start': sub_starts, 'end': sub_ends, 'text': sub_texts}","def variable_dicts(self):\n \n def get_variable_text(rtf_file):\n \"Returns a list of variable_texts for each variable\"\n st='Pos. = '\n return rtf_file.split(st)[1:]\n \n def get_variable_name(variable_text):\n st='Variable = '\n b=variable_text.split(st)[1]\n return b[b.find(' ')+1:b.find('\\t')]\n \n def find_pos(rtf):\n a=rtf\n b=a\n return b[b.find(' ')+1:b.find('\\t')]\n \n def find_variable_label(rtf):\n try:\n a=rtf\n b=a.split('Variable label = ')[1]\n return b[b.find(' ')+1:b.find('\\\\par')]\n except IndexError:\n return None\n \n def find_variable_type(rtf):\n if not 'This variable is ' in rtf: return ''\n a=rtf\n b=a.split('This variable is ')[1]\n i1=b.find(' ')+1\n i2=i1+b[i1:].find('}')\n return b[i1:i2]\n \n def find_SPSS_measurement_level(rtf):\n if not 'the SPSS measurement level is ' in rtf: return ''\n a=rtf\n b=a.split('the SPSS measurement level is ')[1]\n i1=b.find(' ')+1\n i2=i1+b[i1:].find('\\\\par')\n return b[i1:i2]\n \n def find_SPSS_user_missing_values(rtf):\n if not 'SPSS user missing values = ' in rtf: return dict()\n a=rtf\n d=a.split('SPSS user missing values = ')\n if len(d)<2: return None\n e=d[1]\n i1=e.find(' ')+1\n i2=i1+e[i1:].find('\\\\par')\n f=e[i1:i2]\n g=f.split(' ')\n i=' '.join([g[0],g[2],g[4]])\n return i\n \n def find_value_labels(rtf):\n if not 'Value = ' in rtf: return dict()\n a=rtf\n d=a.split('Value = ')[1:]\n z={}\n for e in d:\n value=e[e.find(' ')+1:e.find('\\t')]\n value=float(value)\n f=e.split('Label = ')[1]\n label=f[f.find(' ')+1:f.find('\\\\par')]\n z[value]=label\n #print(z)\n return z\n \n variable_texts=get_variable_text(self.rtf)\n #pprint(variable_texts[0:2])\n \n result=[]\n for variable_text in variable_texts:\n d={'pos':find_pos(variable_text),\n 'variable':get_variable_name(variable_text),\n 'variable_label':find_variable_label(variable_text),\n 'variable_type':find_variable_type(variable_text),\n 'SPSS_measurement_level':find_SPSS_measurement_level(variable_text),\n 'SPSS_user_missing_values':find_SPSS_user_missing_values(variable_text),\n 'value_labels':find_value_labels(variable_text) \n }\n result.append(d)\n \n return result","def xml_parser(xml_string):\n def rec_parse(elements):\n \"\"\"recursively add nodes to the dictionary\"\"\"\n node = {\"name\": elements.tag, \"children\": []}\n for elem in elements:\n node[\"children\"].append(rec_parse(elem))\n if len(elements) > 0:\n rec_parse.max_depth += 1\n return node\n\n root = Et.fromstring(xml_string)\n rec_parse.max_depth = 0\n xml_dict = rec_parse(root)\n print(xml_dict, \", \", rec_parse.max_depth)\n\n return xml_dict, rec_parse.max_depth","async def parse(self, raw: str) -> dict:","def to_xml_dict(self):\n root = super(MultiMonoComposer, self).to_xml_dict()\n\n # same as mono, except that <r:monograph> is now <r:monographVolume>\n root[\"r:import\"] = MultiMonoComposer._swap_keys(\n root[\"r:import\"],\n \"r:monograph\",\n \"r:monographVolume\"\n )\n\n # same as mono, except that <r:title> is now <r:monographTitle>\n mono_volume = root[\"r:import\"][\"r:monographVolume\"]\n mono_volume[\"r:titleInfo\"] = MultiMonoComposer._swap_keys(\n mono_volume[\"r:titleInfo\"],\n \"r:title\",\n \"r:monographTitle\"\n )\n\n title_info = root[\"r:import\"][\"r:monographVolume\"][\"r:titleInfo\"]\n if self.volume_title:\n title_info[\"r:volumeTitle\"] = self.volume_title\n\n return root","def parse_string(self, data):\n from pyexpat import ExpatError\n\n from openff.toolkit.utils.exceptions import SMIRNOFFParseError\n\n # Parse XML file\n try:\n smirnoff_data = xmltodict.parse(data, attr_prefix=\"\")\n return smirnoff_data\n except ExpatError as e:\n raise SMIRNOFFParseError(str(e))","def _parse_subdefinitions(subdefinitions):\r\n parsed = {'definition': subdefinitions['difino']}\r\n parsed['examples'] = [\r\n {\r\n 'example': example['ekzemplo']\r\n } for example in subdefinitions['ekzemploj']]\r\n return parsed","def parse(file, time_i, title_i_start, title_i_end, final_time_end):\n file_iter = iter(file)\n tokens = next(file_iter).split()\n try:\n while True:\n time_start = tokens[time_i]\n if not time_string(time_start):\n print('error: could not interpret \\'{}\\' as time'\n ''.format(time_start))\n sys.exit(1)\n chapter_string = ' '.join(tokens[title_i_start:title_i_end])\n tokens = next(file_iter).split()\n yield {\n 'time_start': time_start,\n 'time_end': tokens[time_i],\n 'chapter_string': chapter_string\n }\n except StopIteration:\n yield {\n 'time_start': time_start,\n 'time_end': final_time_end,\n 'chapter_string': chapter_string\n }","def _decode_dictionary(data, sub=False):\n\n main_dict = {}\n\n if sub:\n # We are decoding a sub-dictionary, XML is assumed compliant\n tree = data\n else:\n fixed_data = XML_Fix(data)\n tree = ET.fromstring(fixed_data) \n\n for child in tree:\n for pair in child:\n if len(pair) == 2:\n key = _decode_value(pair[0].attrib['Value'])\n val = None\n if 'Type' in pair[1].attrib: \n collection_type = pair[1].attrib['Type']\n if collection_type == 'elsystem.collections.dictionary': # Handle sub-dictionary\n val = _decode_dictionary(data=pair[1], sub=True)\n elif collection_type == 'elsystem.collections.vector': # Handle sub-vector\n val = _decode_vector(data=pair[1], sub=True)\n else: # Handle normal pair\n val = _decode_value( pair[1].attrib['Value'] )\n main_dict[key] = val\n\n return main_dict","def gettext(xmltext):\n tree = ET.ElementTree(ET.fromstring(xmltext))\n root = tree.getroot()\n title = root.find('title')\n result = title.text\n for element in root.iterfind(\".//text/*\"):\n result = result + \" \" + element.text\n return result","def xml_to_otr(xml_file, destination, speakers=False):\n\n tree = etree.parse(xml_file)\n root = tree.getroot()\n\n # Check xml version and force encoding for compatibility purpose\n if(len(root.findall(\".//word[@value]\")) > 0):\n version = 'v2'\n encoding = 'utf-8'\n word_selector = 'value'\n spk_selector = 'speaker'\n gender_selector = 'gender'\n elif(len(root.findall(\".//word[@sel]\")) > 0):\n version = 'v1'\n encoding = 'iso-8859-1'\n word_selector = 'sel'\n spk_selector = 'locuteur'\n gender_selector = 'sexe'\n else:\n return []\n\n previous_speaker = None\n previous_gender = None\n speaker_turns = []\n speaker_sentences = []\n\n output = codecs.open(destination, 'w', encoding = 'utf-8') if destination else sys.stdout\n\n try:\n\n json_output = {}\n\n html = \"\";\n for i, sentence in enumerate(root):\n if(i != 0):\n html += \"</p>\";\n\n html += \"<p>\";\n\n speaker = sentence.attrib[spk_selector]\n words = []\n\n if speakers:\n # Speaker change\n if(speaker != previous_speaker):\n html += \"<p><strong>Locuteur {} :</strong> \".format(speaker);\n else:\n html += \"<p>\";\n else:\n html += \"<p>\";\n\n nb_words = len(sentence)\n for j, word in enumerate(sentence):\n value = word.attrib[word_selector]\n space_after = \" \"\n if(value.endswith(\"'\") or \\\n (j+1 < nb_words and sentence[j+1].attrib[word_selector].startswith('-'))):\n space_after=\"\"\n\n html += \"<span class=\\\"word\\\" data-start=\\\"{start}\\\">{value}{space}</span>\".format(start=word.attrib['start'], value=value, space=space_after)\n\n previous_speaker = speaker\n previous_gender = sentence.attrib[gender_selector]\n\n\n html += \"</p>\"\n #import pprint; pprint.pprint(html)\n\n json_output['text'] = html\n json_output['media_source'] = \"\"\n print(json.dumps(json_output), file=output)\n\n\n finally:\n if output is not sys.stdout:\n output.close()","def content_for_regtext(instruction_xml):\n label_parts, amdpar = label_amdpar_from(instruction_xml)\n xml = find_section(amdpar)\n\n def parse_regtext():\n sections = build_from_section(label_parts[0], xml)\n if sections:\n return sections[0]\n\n return xml, parse_regtext","def extract_subjects(subject_info_xml, primary_str):\n subject_info_pyxb = deserialize_subject_info(subject_info_xml)\n subject_info_tree = d1_common.cert.subject_info.gen_subject_info_tree(\n subject_info_pyxb, primary_str\n )\n return subject_info_tree.get_subject_set()","def _meta_dict(self, node):\n meta = {n: self._text(node, n) for n in ('source', 'date', 'key')}\n meta.update(self.infon_dict(node))\n return meta","def getSubfield(h, field, Lsubs):\n\td = {}\t\n\tfor k in Lsubs:\n\t\ttheElement = h.documentElement.getElementsByTagName(field)[0]\n\t\td[k] = str(theElement.getAttribute(k))\n\treturn d","def parseTitle(string):\n replacements={\n 'PT':'p_{T} [GeV]'\n ,'MET':'E_{T}^{miss} [GeV]'\n ,'HT':'H_{T} [GeV]'\n ,'HTG':'H_{T}^{gen} [GeV]'\n ,'MET':'E_{T}^{miss} [GeV]'\n ,'TREFF':'Trigger Effciency'\n }\n return reduce(lambda x, y: x.replace(y, replacements[y]), replacements,string)","def parseSkillDesc():\n\ttry:\n\t\thandle = app.OpenTextFile(app.GetLocalePath() + \"/skilldesc.txt\")\n\t\tcount = app.GetTextFileLineCount(handle)\n\texcept IOError:\n\t\tchat.AppendChat(1, \"Could not load \" + app.GetLocalePath() + \"/skilldesc.txt\")\n\t\treturn\n\t\n\tskill_map = {}\n\n\tfor i in range(count):\n\t\tline = app.GetTextFileLine(handle, i)\n\t\tif str(line).count(\"\\t\") >= 21:\n\t\t\tSkillData = str(line).split(\"\\t\")\n\t\t\tskill_map[int(SkillData[0])] = {\n\t\t\t\t\"class\":str(SkillData[1]).lower(),\n\t\t\t\t\"name\":str(SkillData[2]),\n\t\t\t\t\"icon\":str(SkillData[12]),\n\t\t\t\t}\n\t\n\tapp.CloseTextFile(handle)\n\t\n\treturn skill_map","def getTextUnits_old(filename):\n doc = Document(filename)\n units = list()\n \n unit_tracker = defaultdict(int)\n \n non_units = [\"name:\", \"date:\", \"date\", \"series\", \"transcriber\", \"thesis:\", \"currently:\", \"note\", \"comment\", \"grandparents:\", \"transcript:\", \"note:\"]\n\n ongoing_answer = \"\"\n\n \n\n # iterate over all paragraphs to get text units\n for para in doc.paragraphs:\n paragraph = para.text\n # ensure it is not an empty line\n if len(paragraph.strip())>0:\n # get first word\n formatted_para = paragraph.lstrip()\n unit_type = formatted_para.partition(' ')[0]\n # in case it is in the format of e.g 'George Salton:'\n \n # e.g AJ:, B.\n m = re.compile('[A-Z][A-Z]?[.|:|-]')\n type1 = m.match(unit_type)\n\n # e.g [WJ]\n n = re.compile('\\[[A-Z][A-Z]\\]')\n typer2= n.match(unit_type)\n\n # timestamp e.g 15:01:27\n o = re.compile('[0-9]?[0-9]:[0-9][0-9]:[0-9][0-9]')\n type3 = o.match(unit_type) \n \n \n \n\n\n # else parse them according to formatting guidelines\n if (\"Question:\" in unit_type or\n type1 or\n \"Answer:\" in unit_type or \n typer2 or\n type3):\n\n # check if there was an ongoing paragraph\n #units.append({'unit': paragraph})\n \n if ongoing_answer: \n units.append({'unit': ongoing_answer})\n\n # reset it\n ongoing_answer = \"\"\n ongoing_answer += paragraph\n \n # update tracker\n unit_tracker[unit_type] += 1\n\n elif (unit_type.endswith(':') and\n unit_type.lower() not in non_units and\n unit_type[:-1].isalpha()):\n \n \n units.append({'unit': paragraph})\n # update tracker\n unit_tracker[unit_type] += 1\n \n \n # backup method,in case it is in the format of e.g 'George Salton:'\n elif len(paragraph.split()) > 3:\n backup_type = paragraph.split()[1]\n backup_two = paragraph.split()[2]\n\n if ((':' in backup_type or backup_type.lower() not in non_units) or\n (':' in backup_two or backup_two.lower() not in non_units)): \n \n if ((paragraph.strip()[0].islower() and len(paragraph.strip()) > 5) or (paragraph.strip()[-1] in ['.','!','?'])) and len(units) >0:\n units[-1]['unit']=units[-1]['unit']+ ' '+paragraph\n # update tracker\n unit_tracker[unit_type] += 1\n else:\n units.append({'unit':paragraph})\n unit_tracker[unit_type] += 1\n # if it is none of these cases, maybe there is an ongoing answer\n \n elif (ongoing_answer and ongoing_answer != paragraph):\n \n if not any(non_unit in paragraph.lower() for non_unit in non_units):\n ongoing_answer += paragraph\n else:\n units.append({'unit':paragraph})\n\n if len(unit_tracker) < 2:\n return []\n \n return units","def _convert_tags_to_dict(text_list_tags):\n return OrderedDict([re.findall(r\"\"\"\\s*_(\\w+)\\s+(.+?)\\s*$\"\"\", row)[0] for row in text_list_tags])","def _parse_sub(self, parsetree, text, fpos=0):\r\n curr = 0\r\n for match in self._reSubstitution.finditer(text):\r\n start = match.start()\r\n if start > curr:\r\n parsetree.append((\"str\", self._reComment.sub('', text[curr:start])))\r\n\r\n if match.group(\"sub\") is not None:\r\n if not match.group(\"end\"):\r\n raise TemplateSyntaxError(\"Missing closing tag '%s' for '%s'.\" \r\n % (self._sub_end, match.group()), self._errpos(fpos+start))\r\n if len(match.group(\"sub\")) > 0:\r\n self._testexpr(match.group(\"sub\"), fpos+start)\r\n parsetree.append((\"sub\", match.group(\"sub\")))\r\n else:\r\n assert(match.group(\"escsub\") is not None)\r\n if not match.group(\"escend\"):\r\n raise TemplateSyntaxError(\"Missing closing tag '%s' for '%s'.\"\r\n % (self._subesc_end, match.group()), self._errpos(fpos+start))\r\n if len(match.group(\"escsub\")) > 0:\r\n self._testexpr(match.group(\"escsub\"), fpos+start)\r\n parsetree.append((\"esc\", self.escape, match.group(\"escsub\")))\r\n\r\n curr = match.end()\r\n\r\n if len(text) > curr:\r\n parsetree.append((\"str\", self._reComment.sub('', text[curr:])))","def test_parse_metadata_0(self):\n data = ET.parse(\"data/metadata_0.xml\")\n data_str = ET.tostring(data.getroot())\n\n dict = tesse_ros_bridge.utils.parse_metadata(data_str)\n self.assertEqual(dict['position'], [-5.692576, 2.499105, 10.63836])\n self.assertEqual(dict['quaternion'], [0, 0.5372996, 0, 0.8433914])\n self.assertEqual(dict['velocity'], [0, -0.0004944276, 0])\n self.assertEqual(dict['ang_vel'], [0, 0, 0])\n self.assertEqual(dict['acceleration'], [0, 0.001516496, 0])\n self.assertEqual(dict['ang_accel'], [0, 0, 0])\n self.assertEqual(dict['time'], 7.935)\n self.assertEqual(dict['collision_status'], False)","def getSubtitlesContainer(self):\n self.subtitleURLContainer = \"\"\n\n self.subtitleURLContainer += self.parametersDict['PreURL']\n\n for parameters in self.parametersDict:\n if parameters != \"PreURL\":\n self.subtitleURLContainer += \"&\"\n self.subtitleURLContainer += parameters\n self.subtitleURLContainer += \"=\"\n self.subtitleURLContainer += self.parametersDict[parameters]\n pass","def tracktorDeserialize(path, titles=None):\n tree = ET.parse(path)\n root = tree.getroot()\n tracks = {}\n for entry in root.find(\"COLLECTION\").iter(\"ENTRY\"):\n track = Track()\n track.name = entry.attrib[\"TITLE\"]\n track.path = entry.find(\"LOCATION\").attrib[\"FILE\"][:-4] #Removing .mp3\n cues = [cue for cue in entry.iter(\"CUE_V2\") if cue.attrib[\"NAME\"] != \"AutoGrid\"]\n track.features[\"Cues\"] = Signal([cue.attrib[\"NAME\"][:7] for cue in cues],\n times=[float(cue.attrib[\"START\"]) / 1000 for cue in cues],\n sparse=True)\n tracks[track.path] = track\n if titles:\n for t in titles:\n if t in tracks:\n yield tracks[t]\n else:\n print(t, \"not in collection\")\n dummytrack = Track()\n dummytrack.features[\"Cues\"] = Signal(times=[])\n yield dummytrack\n # return [tracks[t] if t in tracks else Track() for t in titles]\n else:\n return tracks.values()","def parse_data(self):\n\n msg = self.xml['dom'].childNodes[0]\n self.data = xml_to_dicts(msg, False)\n\n # Get some metadata together\n self.id = \"%s:%s\" % (self.data['src']['name']['#cdata'], self.data['src']['id']['#cdata'])\n self.temp = self.data['tmpr']['#cdata']\n self.watts = self.data['ch1']['watts']['#cdata']\n\n # Time - CurrentCost and local\n self.date = {}\n self.date['cc'] = [ int(self.data['date'][k]['#cdata']) for k in ('dsb','hr','min','sec') ]\n self.date['now'] = localtime()","def xml_to_json(xml_file, destination):\n\n tree = etree.parse(xml_file)\n root = tree.getroot()\n\n # Check xml version and force encoding for compatibility purpose\n if(len(root.findall(\".//word[@value]\")) > 0):\n version = 'v2'\n encoding = 'utf-8'\n word_selector = 'value'\n spk_selector = 'speaker'\n gender_selector = 'gender'\n elif(len(root.findall(\".//word[@sel]\")) > 0):\n version = 'v1'\n encoding = 'iso-8859-1'\n word_selector = 'sel'\n spk_selector = 'locuteur'\n gender_selector = 'sexe'\n else:\n return []\n\n previous_speaker = None\n previous_gender = None\n speaker_turns = []\n speaker_sentences = []\n\n output = codecs.open(destination, 'w', encoding = 'utf-8') if destination else sys.stdout\n\n try:\n\n for sentence in root:\n speaker = sentence.attrib[spk_selector]\n words = []\n\n # Speaker change\n if(previous_speaker is not None and speaker != previous_speaker):\n speaker_turns.append({\n \"id\":previous_speaker,\n \"gender\":previous_gender,\n # No speaker id score for now in xml\n \"score\": None,\n \"sentences\":speaker_sentences\n })\n speaker_sentences = []\n\n for word in sentence:\n json_word = {\n \"start\": word.attrib['start'],\n \"word\": word.attrib[word_selector],\n # No named entity support for now\n \"ne\": None\n }\n words.append(json_word)\n\n speaker_sentences.append(words)\n\n previous_speaker = speaker\n previous_gender = sentence.attrib[gender_selector]\n\n\n # Add the last sentence and last speaker turn\n speaker_turns.append({\n \"id\":previous_speaker,\n \"gender\":previous_gender,\n # No speaker id score for now in xml\n \"score\": None,\n \"sentences\":speaker_sentences\n })\n\n\n #import pprint; pprint.pprint(speaker_turns)\n\n json_output = {}\n json_output['speaker_turns'] = speaker_turns\n print(json.dumps(json_output), file=output)\n\n\n finally:\n if output is not sys.stdout:\n output.close()","def get_info_list(info_string, course):\n info_list = []\n split_on_newline = info_string.split(\"\\n\")\n for elem in split_on_newline:\n split = elem.split(\": \")\n for s in split:\n info_list.append(s)\n info_list = info_list[1:-1]\n info_tags = [\n 'session', 'school', 'credits', 'level', 'offered',\n 'visiting_students', 'erasmus_students',\n ]\n i = 0\n for info_tag in info_tags:\n course[info_tag] = new_dict(\n info_list[i] + ': ', info_list[i + 1])\n i += 2\n return course","def parseTSName(tsn):\n parsedName = [int(nc.split(\"=\")[1]) for nc in tsn.split(\".\")[0].split(\"/\")[-1].split(\"_\")]\n return {\"ti\": parsedName[0], \"intervalLen\": parsedName[1] - parsedName[0], \"sensor\": parsedName[2]}","def transform_string_to_dictionary(data_text: str) -> Dict[str, float]:\n # TODO: create an empty population dictionary\n # TODO: iterate through each line of the data set\n # TODO: extract the ordered pair on this line\n # the ordered pair has the format:\n # (Date, population count in thousands of persons)\n # TODO: extract the dat and store it as a string\n # TODO: convert the population count to a float and store it\n # TODO: add the new key-value pair to the dictionary where\n # the key is the date and the population is the value\n # TODO: return the population dictionary","def buildDictionaryFromXML(self, siteelement, elementstring):\n variablename = \"\"\n try:\n if len(siteelement.find(elementstring).findall(\"entry\")) > 0:\n variablename = {}\n for entry in siteelement.find(elementstring).findall(\"entry\"):\n variablename[entry.get(\"key\")] = entry.text\n else:\n return None\n except:\n return None\n return variablename","def __read_composite_template(self, text:str, start:int, end_marker:str) -> dict:\n\t\tbind = {}\n\t\tkey = None\n\t\tleft = start\n\t\ttry: right = text.rindex(end_marker)\n\t\texcept ValueError: right=len(text)\n\t\tsuffix = text[right+len(self.END_ASSY):]\n\t\tassert suffix=='' or suffix.isspace()\n\t\tfor match in re.finditer(r'<\\?(.*?)\\?>', text):\n\t\t\tbind[key] = text[left:match.start()].strip()\n\t\t\tkey = match.group(1).strip()\n\t\t\tleft = match.end()\n\t\tbind[key] = text[left:right].strip()\n\t\treturn bind","def scene_to_text(scenes):\n scene_text_dict = []\n scene_text_list = []\n for i, scene in enumerate(scenes):\n if len(scene['frame_data']) == 0:\n break\n scene_image = Image.fromarray(scene['frame_data'])\n str_text = pytesseract.image_to_string(scene_image)\n #list_text = list(filter(('').__ne__, re.split(\" |\\n|, ｜. |:|.\\n|\\x0c\", str_text)))\n list_text = list(filter(('').__ne__, re.split(\" |\\n\", str_text)))\n bag_of_word = collections.Counter(list_text)\n scene_text_dict.append(\n {'start': scene['start'], \n 'end': scene['end'], \n 'bag_of_word': dict(bag_of_word)\n })\n scene_text_list.append(list_text)\n return scene_text_dict, scene_text_list","def doc_title_table(title_file):\n with open(title_file , 'r') as f :\n lines = f.readlines()\n raw_text = \"\".join(l for l in lines)\n left_idx_num = [ m.end(0) for m in re.finditer(r\"<num>\",raw_text)]\n right_idx_num = [ m.start(0) for m in re.finditer(r\"</num>\",raw_text)]\n\n left_idx_title = [ m.end(0) for m in re.finditer(r\"<title>\",raw_text)]\n right_idx_title = [ m.start(0) for m in re.finditer(r\"</title>\",raw_text)]\n\n docs_title_dict = {}\n for i in range(len(left_idx_num)):\n docs_title_dict[raw_text[left_idx_num[i]+1:right_idx_num[i]-1]] = raw_text[left_idx_title[i]+1:right_idx_title[i]-1]\n return docs_title_dict","def setup_parser(self) -> Dict[str, Any]:\n\n\t# % year,doy, RH(m), Month, day, azimuth(deg),freq, satNu, LSP amp,pk2noise,UTC(hr) \n\t# 2021 9 4.888 1 9 225.3 1 2 9.51 3.23 10.08\n\t# 2021 9 5.018 1 9 181.3 1 15 7.79 2.84 15.67\n\t# 2021 9 5.123 1 9 185.4 1 16 6.27 3.01 0.68\n #----+----0----+----1----+----2----+----3----+----4----+----5----+----6----+----7\n return dict(\n skip_header=1,\n names=(\n \"year\",\n \"doy\",\n \"reflection_height\",\n \"month\",\n \"day\",\n \"azimuth\",\n \"frequency\",\n \"satellite\",\n \"amplitude\",\n \"peak2noise\",\n \"hour\",\n ),\n dtype=(\"f8\", \"f8\", \"f8\", \"f8\", \"f8\", \"f8\", \"f8\", \"f8\", \"f8\", \"f8\", \"f8\"),\n )","def agline2(line):\n \n vals = {}\n y = line.strip('\\n').split(',')\n y.extend(y[0].strip('.MTS').split('_'))\n \n #print(y)\n \n x = ['movie', 'moviecode', 'offset', 'well', 'agmin', 'agsec', 'agdur', \n 'agtype', 'agcomm', 'escmin', 'escsec', 'escdur', 'esctype', 'escbeh', \n 'esccomm', 'gen', 'date', 'assay', 'fps', 'flyid', 'side', 'moviepart']\n \n z = zip(x, y)\n\n for item in z:\n vals[item[0]] = item[1]\n\n return(vals)","def xml_children_as_dict(node):\n return dict((e.tag, e.text) for e in node)","def _parseXmlInter(self, xml_str):\n EOW = []\n phones = []\n explains = []\n\n root = ET.fromstring(xml_str)\n\n for explain_xml in root.iter(self.TAG_EXPLEIN):\n\n if len(explain_xml) > 0 and explain_xml[0].tag == self.TAG_POS: # 存在词性\n explain = explain_xml[0].text + explain_xml[0].tail\n\n else:\n if explain_xml.text == None:\n continue\n else:\n explain = explain_xml.text\n\n explains.append(explain)\n\n for phone_xml in root.iter(self.TAG_PHONE):\n if phone_xml.text == None:\n continue\n phones.append(phone_xml.text)\n\n EOW_xml = root.find(self.TAG_EOW)\n if EOW_xml != None:\n EOW = EOW_xml.text.split('|')\n\n return EOW, phones, explains"],"string":"[\n \"def _from_origin_to_dict(self):\\n try:\\n for elem in self._xml_tree.getchildren():\\n if elem.tag == \\\"info\\\":\\n for subelem in elem.xpath(\\\"//Metadata/General/Metas/Titulo\\\"):\\n self._translated_dict[\\\"root\\\"][\\\"title\\\"] = subelem.text\\n return self\\n\\n except Exception as e:\\n logger.error(\\\"XML Parse Error. %s\\\" % repr(e))\",\n \"def parse_text(self, text: str) -> SectionDict:\",\n \"def get_subtitles(self, index: int):\\n\\n match = self.re_subs[index - 1]\\n start = convert_subs_time(match[1])\\n end = convert_subs_time(match[2])\\n subtitles = match[3]\\n subtitles = clean_text(subtitles)\\n\\n return (subtitles, start, end)\",\n \"def stat_subtitle(self, release_name, movie_dir):\\n ret = {}\\n for root_dir, child_folders, file_names in os.walk(movie_dir):\\n for file_name in file_names:\\n if not file_name.startswith(release_name):\\n continue\\n\\n subtitle_info = get_subtitle_info(file_name)\\n if not subtitle_info:\\n continue\\n\\n if 'lang' not in subtitle_info:\\n continue\\n\\n lang = subtitle_info['lang']\\n if lang not in ret:\\n ret[lang] = []\\n\\n ret[lang].append(file_name)\\n\\n # Sort result\\n for lang in ret:\\n ret[lang] = sorted(ret[lang])\\n\\n return ret\",\n \"def parse_info(s:str) -> dict:\\n d = {}\\n d[\\\"SVTYPE\\\"] = re.search(r'(?<=SVTYPE=)\\\\w+',s).group(0)\\n d[\\\"SUPPORT\\\"] = re.search(r'(?<=SUPPORT=)\\\\d+',s).group(0)\\n if d[\\\"SVTYPE\\\"] in [\\\"BND\\\"]:\\n return d\\n d[\\\"END\\\"] = re.search(r'(?<=END=)\\\\d+',s).group(0)\\n if d[\\\"SVTYPE\\\"] in [\\\"INV\\\"]:\\n return d\\n d[\\\"SVLEN\\\"] = re.search(r'(?<=SVLEN=)(.*?)(?=;)',s).group(0)\\n d[\\\"READS\\\"] = re.search(r'(?<=READS=)(.*?)(?=$)',s).group(0).split(\\\",\\\")\\n if d[\\\"SVTYPE\\\"] == \\\"INS\\\":\\n d[\\\"SEQS\\\"] = re.search(r'(?<=SEQS=)(.*?)(?=;)',s).group(0).split(\\\",\\\")\\n return d\",\n \"def extract(self, json_str, sub_number):\\n topic_dict = json.loads(json_str)\\n # print(topic_dict)\\n\\n if ('children' not in topic_dict):\\n raise RuntimeError('topic tree json data has no children.')\\n\\n sub_topic_title = topic_dict['standalone_title']\\n\\n # 1. sub: subject (math, physic)\\n # 2. nb_main: main topic number (addition/subtraction, fraction, ...)\\n # 3. nb_sub: sub topic number\\n # 4. nb_video: video title number\\n # 5. sub_topic_title:\\n # 6. video_title:\\n # 7. d1: text translation duration time\\n # 8. d2: voice over, edit duration time\\n # 9. d3: subtitle duration time\\n # 10. d4: total duration time\\n # 11. s1: start date\\n # 12. s2: end date\\n # 13. s3: elapsed date\\n # 14. status:\\n # 15. finished bool\\n # 16. update bool\\n # 17. new at 2017 bool\\n # 18. video_url:\\n # 19. id:\\n\\n video_idx=1\\n retstr = ''\\n for i in topic_dict['children']:\\n if (i['kind'] == 'Video'):\\n line_str = ' , {_nb_main}, {_nb_sub}, {_nb_video}, {_sub_topic_title}, {_video_title}, {_d1}, {_d2}, {_d3}, {_d4}, {_s1}, {_s2}, {_s3}, {_status}, , , , {_video_url}, {_id}\\\\n'.\\\\\\n format(\\n _nb_main=1,\\n _nb_sub=sub_number,\\n _nb_video=video_idx,\\n _sub_topic_title=sub_topic_title,\\n _video_title=i['title'],\\n _d1='00:00:00', _d2='00:00:00',\\n _d3='00:00:00', _d4='00:00:00',\\n _s1='2017-05-01', _s2='2017-05-01', _s3=0,\\n _status='not_started',\\n _video_url=i['url'],\\n _id=i['internal_id'])\\n video_idx += 1\\n retstr += line_str\\n else:\\n verbose_mes = '# Skip kind [{kind}]: {title}'.format(\\n kind=i['kind'], title=i['title'])\\n self.verbose_out(verbose_mes)\\n\\n return retstr\",\n \"def to_xmp_string(self):\\n \\\"\\\"\\\"\\n ...\\n <xmpDM:Tracks>\\n <rdf:Bag>\\n <rdf:li>\\n <rdf:Description\\n xmpDM:trackName=\\\"Speaker identification\\\">\\n <xmpDM:markers>\\n <rdf:Seq>\\n <rdf:li\\n xmpDM:startTime=\\\"310\\\"\\n xmpDM:duration=\\\"140\\\"\\n xmpDM:speaker=\\\"Speaker0\\\"\\n />\\n <rdf:li\\n xmpDM:startTime=\\\"450\\\"\\n xmpDM:duration=\\\"60\\\"\\n xmpDM:speaker=\\\"Speaker0\\\"\\n />\\n </rdf:Seq>\\n </xmpDM:markers>\\n </rdf:Description>\\n </rdf:li>\\n </rdf:Bag>\\n </xmpDM:Tracks>\\n ...\\n \\\"\\\"\\\"\\n initial_tags = \\\"\\\"\\\"<?xml version=\\\"1.0\\\"?>\\n<x:xmpmeta xmlns:x=\\\"adobe:ns:meta/\\\" x:xmptk=\\\"XMP Core 4.4.0\\\">\\n <rdf:RDF xmlns:rdf=\\\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\\\">\\n <rdf:Description xmlns:xmpDM=\\\"http://ns.adobe.com/xmp/1.0/DynamicMedia/\\\">\\n <xmpDM:Tracks>\\n <rdf:Bag>\\n <rdf:li>\\n <rdf:Description\\n xmpDM:trackName=\\\"Speaker identification\\\">\\n <xmpDM:markers>\\n <rdf:Seq>\\\"\\\"\\\"\\n inner_string = ''\\n for seg in self.get_time_slices():\\n inner_string += \\\"\\\"\\\"\\n <rdf:li\\n xmpDM:startTime=\\\"%seg\\\"\\n xmpDM:duration=\\\"%seg\\\"\\n xmpDM:speaker=\\\"%seg\\\"\\n /> \\\"\\\"\\\" % (seg[0], seg[1], seg[-2])\\n final_tags = \\\"\\\"\\\"\\n </rdf:Seq>\\n </xmpDM:markers>\\n </rdf:Description>\\n </rdf:li>\\n </rdf:Bag>\\n </xmpDM:Tracks>\\n </rdf:Description>\\n </rdf:RDF>\\n</x:xmpmeta>\\n\\\"\\\"\\\"\\n #TODO: extract previous XMP information from the media and merge \\n # with speaker information\\n return initial_tags + inner_string + final_tags\",\n \"def _parse_video_xml(cls, xml_data):\\r\\n xml = etree.fromstring(xml_data)\\r\\n field_data = {}\\r\\n\\r\\n # Convert between key types for certain attributes --\\r\\n # necessary for backwards compatibility.\\r\\n conversions = {\\r\\n # example: 'start_time': cls._example_convert_start_time\\r\\n }\\r\\n\\r\\n # Convert between key names for certain attributes --\\r\\n # necessary for backwards compatibility.\\r\\n compat_keys = {\\r\\n 'from': 'start_time',\\r\\n 'to': 'end_time'\\r\\n }\\r\\n sources = xml.findall('source')\\r\\n if sources:\\r\\n field_data['html5_sources'] = [ele.get('src') for ele in sources]\\r\\n\\r\\n track = xml.find('track')\\r\\n if track is not None:\\r\\n field_data['track'] = track.get('src')\\r\\n\\r\\n handout = xml.find('handout')\\r\\n if handout is not None:\\r\\n field_data['handout'] = handout.get('src')\\r\\n\\r\\n transcripts = xml.findall('transcript')\\r\\n if transcripts:\\r\\n field_data['transcripts'] = {tr.get('language'): tr.get('src') for tr in transcripts}\\r\\n\\r\\n for attr, value in xml.items():\\r\\n if attr in compat_keys:\\r\\n attr = compat_keys[attr]\\r\\n if attr in cls.metadata_to_strip + ('url_name', 'name'):\\r\\n continue\\r\\n if attr == 'youtube':\\r\\n speeds = cls._parse_youtube(value)\\r\\n for speed, youtube_id in speeds.items():\\r\\n # should have made these youtube_id_1_00 for\\r\\n # cleanliness, but hindsight doesn't need glasses\\r\\n normalized_speed = speed[:-1] if speed.endswith('0') else speed\\r\\n # If the user has specified html5 sources, make sure we don't use the default video\\r\\n if youtube_id != '' or 'html5_sources' in field_data:\\r\\n field_data['youtube_id_{0}'.format(normalized_speed.replace('.', '_'))] = youtube_id\\r\\n else:\\r\\n # Convert XML attrs into Python values.\\r\\n if attr in conversions:\\r\\n value = conversions[attr](value)\\r\\n else:\\r\\n # We export values with json.dumps (well, except for Strings, but\\r\\n # for about a month we did it for Strings also).\\r\\n value = deserialize_field(cls.fields[attr], value)\\r\\n field_data[attr] = value\\r\\n\\r\\n # For backwards compatibility: Add `source` if XML doesn't have `download_video`\\r\\n # attribute.\\r\\n if 'download_video' not in field_data and sources:\\r\\n field_data['source'] = field_data['html5_sources'][0]\\r\\n\\r\\n # For backwards compatibility: if XML doesn't have `download_track` attribute,\\r\\n # it means that it is an old format. So, if `track` has some value,\\r\\n # `download_track` needs to have value `True`.\\r\\n if 'download_track' not in field_data and track is not None:\\r\\n field_data['download_track'] = True\\r\\n\\r\\n return field_data\",\n \"def extract_subtitle_track(path_to_mkv):\\n handler = SubtitleHandler()\\n with open(path_to_mkv, \\\"rb\\\") as fp:\\n mkvparse.mkvparse(fp, handler)\\n\\n return handler.subs\",\n \"def return_xml_dict_entry_value(self,dict_entry, dict_entry_position):\\n\\tvalue = self.subtitle_dict[dict_entry][dict_entry_position]\\n\\treturn value[0]\",\n \"def get_subtitle_print(subs: List[Track]) -> List[str]:\\n data = []\\n if not subs:\\n data.append(\\\"--\\\")\\n for sub in subs:\\n line_items = []\\n\\n # following sub.title tree checks and supports three different language and title scenarios\\n # The second scenario is the recommended option to choose if you are open to choosing any\\n # The third scenario should be used if you have nothing unique to state about the track\\n # | Language | Track Title | Output |\\n # | ------------ | ----------------------------- | --------------------------------------------- |\\n # | es / Spanish | Spanish (Latin American, SDH) | - Spanish (Latin American, SDH), SubRip (SRT) |\\n # | es / Spanish | Latin American (SDH) | - Spanish, Latin American (SDH), SubRip (SRT) |\\n # | es / Spanish | None | - Spanish, SubRip (SRT) |\\n language = pycountry.languages.get(alpha_2=sub.language).name\\n if sub.title:\\n if language.lower() in sub.title.lower():\\n line_items.append(sub.title)\\n else:\\n line_items.append(f\\\"{language}, {sub.title}\\\")\\n else:\\n line_items.append(language)\\n\\n line_items.append(sub.format.replace(\\\"UTF-8\\\", \\\"SubRip (SRT)\\\"))\\n\\n line = \\\"- \\\" + \\\", \\\".join(line_items)\\n data += [\\n (\\\" \\\" + x if i > 0 else x)\\n for i, x in enumerate(textwrap.wrap(line, 64))\\n ]\\n return data\",\n \"def get_time_intervals(subtitle, regex=r\\\"\\\\S+\\\"):\\n # module webvtt only gets the line-captions, not individual words, so it's time for some regex!\\n # The time corresponding to a word is when that word *starts*\\n # words = (match.group(\\\"word\\\") for match in WORD_REGEX.finditer(subtitle))\\n time_words = [\\n (m.group(\\\"time1\\\") or m.group(\\\"time2\\\"), m.group(\\\"word1\\\") or m.group(\\\"word2\\\"))\\n for m in TIME_WORD_REGEX.finditer(subtitle)\\n ]\\n # Incorrect format, which would lead to trouble zipping\\n if len(time_words) == 0:\\n return []\\n times, words = zip(*time_words)\\n # Quickly search lines starting from the end\\n final_time = next(match.group(\\\"time\\\") for line in reversed(subtitle.split(\\\"\\\\n\\\")) for match in [re.search(FINAL_TIME_REGEX, line)] if match)\\n # timestamps[i] is the time the word starts at if i is the index of the start of a word\\n timestamps = {}\\n word_indices = {}\\n # Build search_str while computing time_stamps by adding one word and one space at a time\\n search_str = ''\\n words = list(words)\\n last_time = 0\\n for j, (word, time) in enumerate(zip(words, times)):\\n i = len(search_str)\\n time = parse_time(time)\\n timestamps[i] = time\\n if time - last_time > 10:\\n search_str += '[ … ] '\\n last_time = time\\n word_indices[i] = j\\n search_str += word + ' '\\n i = len(search_str)\\n timestamps[i] = final_time\\n word_indices[i] = len(words)\\n # Trim off the final space\\n # Inconsistent capitalization, so just lowercase\\n search_str = search_str[:-1].lower()\\n for match in re.finditer(regex, search_str):\\n start, end = match.span()\\n start_index = max(i for i in timestamps if i<=start)\\n end_index = min(i for i in timestamps if i>end)\\n yield Interval(\\n timestamps[start_index],\\n timestamps[end_index],\\n word_indices[start_index],\\n word_indices[end_index],\\n match.group(0)\\n )\",\n \"def edx_get_subtitle(url, headers):\\n \\\"\\\"\\\" or None if no subtitles are available \\\"\\\"\\\"\\n try:\\n jsonString = get_page_contents(url, headers)\\n jsonObject = json.loads(jsonString)\\n return edx_json2srt(jsonObject)\\n except URLError as e:\\n print('[warning] edX subtitles (error:%s)' % e.reason)\\n return None\\n except ValueError as e:\\n print('[warning] edX subtitles (error:%s)' % e.message)\\n return None\",\n \"def parser(xml):\\n if not xml:\\n return {} # pragma: no cover\\n\\n data = {}\\n\\n match = RE_OWI.search(u(xml))\\n if match:\\n data['owi'] = match.group(1)\\n match = RE_OCLC.search(u(xml))\\n if match:\\n data['oclc'] = match.group(1)\\n\\n match = RE_LCC.search(u(xml))\\n if match:\\n buf = match.group()\\n match = RE_SFA.search(buf)\\n if match:\\n data['lcc'] = match.group(1)\\n\\n match = RE_DDC.search(u(xml))\\n if match:\\n buf = match.group()\\n match = RE_SFA.search(buf)\\n if match:\\n data['ddc'] = match.group(1)\\n\\n fast = parser_headings(xml)\\n if fast:\\n data['fast'] = fast\\n\\n return data\",\n \"def to_srt(self, subtitles):\\n \\n srt_data = ''\\n subtitle_num = self.start_index\\n for subtitle in subtitles:\\n subtitle_num += 1\\n \\n offset = self.start_time\\n \\n start_time = self._ms_to_time(subtitle['start_time'] + offset)\\n end_time = self._ms_to_time(subtitle['end_time'] + offset)\\n \\n content = subtitle['content'].replace('<br>', ' ')\\n \\n srt_data += str(subtitle_num) + '\\\\r\\\\n'\\n srt_data += '%s --> %s' % (start_time, end_time) + '\\\\r\\\\n'\\n srt_data += content + '\\\\r\\\\n'\\n srt_data += '\\\\r\\\\n'\\n \\n self.end_index = subtitle_num\\n \\n return srt_data\",\n \"def get_words_with_end_times(subtitle_file_path):\\n\\n with open(subtitle_file_path) as subtitle_file:\\n\\n # Remove first 4 lines (containing meta information)\\n for j in range(0, 4):\\n subtitle_file.readline()\\n\\n text = subtitle_file.read()\\n\\n # Check if the subtitle file supports individual word times\\n if text.find(\\\"<c>\\\") == -1:\\n print(\\\"Individual word times are not supported for file: \\\" + subtitle_file_path)\\n return None, None\\n\\n chunks = text.split(\\\" \\\\n\\\\n\\\") # split into chunks for easier data processing\\n\\n words = list()\\n word_end_times = list()\\n\\n for chunk in chunks:\\n chunk_lines = chunk.split(\\\"\\\\n\\\")\\n words_line = chunk_lines[2]\\n\\n words_in_chunk = []\\n word_end_times_in_chunk = []\\n\\n first_word_end_index = words_line.find(\\\"<\\\")\\n if first_word_end_index != -1:\\n first_word = words_line[\\n 0:first_word_end_index] # get the first word (can't be found using method below)\\n\\n words_in_chunk = re.findall(\\\"<c> [\\\\S]*</c>\\\", words_line) # get all words\\n words_in_chunk = [w[4:-4] for w in words_in_chunk] # strip <c> and <c/>\\n\\n word_end_times_in_chunk = re.findall(\\\"<\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d.\\\\d\\\\d\\\\d>\\\", words_line) # get all word end times\\n word_end_times_in_chunk = [t[1:-1] for t in word_end_times_in_chunk] # strip < and >\\n else:\\n # Only one word\\n first_word = words_line\\n\\n last_time = chunk_lines[4][17:29] # end time for the last word\\n\\n words_in_chunk.insert(0, first_word)\\n word_end_times_in_chunk.append(last_time)\\n\\n words.extend(words_in_chunk)\\n word_end_times.extend(word_end_times_in_chunk)\\n\\n # For the last chunk we have to get the word end time from somewhere else\\n first_line_in_last_chunk = chunks[-1].split(\\\"\\\\n\\\")[0]\\n last_time = first_line_in_last_chunk[17:29]\\n word_end_times.pop()\\n word_end_times.append(last_time)\\n\\n if len(words) != len(word_end_times):\\n print(\\\"Warning: word count does not match times count\\\")\\n\\n return words, word_end_times\",\n \"def parse_template(string):\\n count = 0\\n list1 = []\\n for character in string:\\n count = count + 1\\n if character == \\\"{\\\":\\n end = string.find(\\\"}\\\", count)\\n s_strg = string[count:end]\\n list1.append(s_strg)\\n string = string.replace(s_strg, \\\"\\\", 1)\\n count = count - len(s_strg)\\n\\n subs = tuple(list1)\\n\\n return(string, subs)\\n print(subs)\",\n \"def xml2dict( xml, sanitize=True, prefix=None):\\n \\n \\n #Decode to avert parsing errors as some software dump large text\\n #fields into the file that occasionally contain erronious chars\\n xml=xml.decode('utf-8', errors='ignore')\\n\\n \\n return etree2dict(etree.fromstring(xml), sanitize, prefix)\",\n \"def dict(self):\\n return xmltodict.parse(str(self))\",\n \"def parse_string(xml):\\n string = \\\"\\\"\\n # Traverse all the <sentence> elements in the XML.\\n dom = XML(xml)\\n for sentence in dom(XML_SENTENCE):\\n _anchors.clear() # Populated by calling _parse_tokens().\\n _attachments.clear() # Populated by calling _parse_tokens().\\n # Parse the language from <sentence language=\\\"\\\">.\\n language = sentence.get(XML_LANGUAGE, \\\"en\\\")\\n # Parse the token tag format from <sentence token=\\\"\\\">.\\n # This information is returned in TokenString.tags,\\n # so the format and order of the token tags is retained when exporting/importing as XML.\\n format = sentence.get(XML_TOKEN, [WORD, POS, CHUNK, PNP, REL, ANCHOR, LEMMA])\\n format = not isinstance(format, basestring) and format or format.replace(\\\" \\\",\\\"\\\").split(\\\",\\\")\\n # Traverse all <chunk> and <chink> elements in the sentence.\\n # Find the <word> elements inside and create tokens.\\n tokens = []\\n for chunk in sentence:\\n tokens.extend(_parse_tokens(chunk, format))\\n # Attach PNP's to their anchors.\\n # Keys in _anchors have linked anchor chunks (each chunk is a list of tokens).\\n # The keys correspond to the keys in _attachments, which have linked PNP chunks.\\n if ANCHOR in format:\\n A, P, a, i = _anchors, _attachments, 1, format.index(ANCHOR)\\n for id in sorted(A.keys()):\\n for token in A[id]:\\n token[i] += \\\"-\\\"+\\\"-\\\".join([\\\"A\\\"+str(a+p) for p in range(len(P[id]))])\\n token[i] = token[i].strip(\\\"O-\\\")\\n for p, pnp in enumerate(P[id]):\\n for token in pnp: \\n token[i] += \\\"-\\\"+\\\"P\\\"+str(a+p)\\n token[i] = token[i].strip(\\\"O-\\\")\\n a += len(P[id])\\n # Collapse the tokens to string.\\n # Separate multiple sentences with a new line.\\n tokens = [\\\"/\\\".join([tag for tag in token]) for token in tokens]\\n tokens = \\\" \\\".join(tokens)\\n string += tokens + \\\"\\\\n\\\"\\n # Return a TokenString, which is a unicode string that transforms easily\\n # into a plain str, a list of tokens, or a Sentence.\\n try:\\n if MBSP: from mbsp import TokenString\\n return TokenString(string.strip(), tags=format, language=language)\\n except:\\n return TaggedString(string.strip(), tags=format, language=language)\",\n \"def edx_get_subtitle(url, headers):\\n try:\\n json_object = get_page_contents_as_json(url, headers)\\n return edx_json2srt(json_object)\\n except URLError as e:\\n _print('[warning] edX subtitles (error:%s)' % e.reason)\\n return None\\n except ValueError as e:\\n _print('[warning] edX subtitles (error:%s)' % e.message)\\n return None\",\n \"def voc_xml_to_dict(xml_path):\\n\\n xml = etree.parse(xml_path)\\n root = xml.getroot()\\n image_name = root.find('filename').text\\n labels = []\\n boxes = []\\n\\n for obj in root.findall('object'):\\n labels.append(obj.find('name').text)\\n bbox = obj.find('bndbox')\\n bounds = [\\n float(bbox.find('xmin').text),\\n float(bbox.find('ymin').text),\\n float(bbox.find('xmax').text),\\n float(bbox.find('ymax').text)\\n ]\\n boxes.append(bounds)\\n\\n return {\\n 'image': image_name,\\n 'labels': labels,\\n 'boxes': boxes,\\n }\",\n \"def extract_context(xml):\\r\\n return eval(xml.text)\",\n \"def generate_subs_from_source(speed_subs, subs_type, subs_filedata, item, language='en'):\\r\\n _ = item.runtime.service(item, \\\"i18n\\\").ugettext\\r\\n if subs_type.lower() != 'srt':\\r\\n raise TranscriptsGenerationException(_(\\\"We support only SubRip (*.srt) transcripts format.\\\"))\\r\\n try:\\r\\n srt_subs_obj = SubRipFile.from_string(subs_filedata)\\r\\n except Exception as ex:\\r\\n msg = _(\\\"Something wrong with SubRip transcripts file during parsing. Inner message is {error_message}\\\").format(\\r\\n error_message=ex.message\\r\\n )\\r\\n raise TranscriptsGenerationException(msg)\\r\\n if not srt_subs_obj:\\r\\n raise TranscriptsGenerationException(_(\\\"Something wrong with SubRip transcripts file during parsing.\\\"))\\r\\n\\r\\n sub_starts = []\\r\\n sub_ends = []\\r\\n sub_texts = []\\r\\n\\r\\n for sub in srt_subs_obj:\\r\\n sub_starts.append(sub.start.ordinal)\\r\\n sub_ends.append(sub.end.ordinal)\\r\\n sub_texts.append(sub.text.replace('\\\\n', ' '))\\r\\n\\r\\n subs = {\\r\\n 'start': sub_starts,\\r\\n 'end': sub_ends,\\r\\n 'text': sub_texts}\\r\\n\\r\\n for speed, subs_id in speed_subs.iteritems():\\r\\n save_subs_to_store(\\r\\n generate_subs(speed, 1, subs),\\r\\n subs_id,\\r\\n item,\\r\\n language\\r\\n )\\r\\n\\r\\n return subs\",\n \"def test_parser_to_dict(self):\\n xml = \\\"\\\"\\\"\\\\\\n<foo>\\n <bar>baz</bar>\\n <quz>\\n <wow>works!</wow>\\n </quz>\\n</foo>\\n\\\"\\\"\\\"\\n d = x.to_dict(xml, {})\\n assert d.bar.text_ == u'baz'\\n assert d.quz.wow.text_ == u'works!'\",\n \"def loads(xtext):\\n\\n class XmlLoads(object):\\n \\\"\\\"\\\"\\n XMLLOADS implements 'YZXml.loads' functionality\\n \\\"\\\"\\\"\\n\\n def __init__(self, xtext):\\n self.index = 0\\n self.xtext = xtext\\n self.length = len(xtext)\\n self.stack = []\\n\\n def loads(self):\\n \\\"\\\"\\\"\\n LOADS converts xml-string to object-string\\n\\n Returns\\n -------\\n - dict\\n object-xml contains {'tag': str, 'attribs': dict, 'elements': list}\\n \\\"\\\"\\\"\\n\\n self.ignore_whitespaces()\\n\\n if self.index >= self.length:\\n return\\n\\n if self.xtext[self.index] == '<':\\n self.index += 1\\n\\n if self.xtext[self.index] == '/':\\n self.index += 1\\n\\n tag = self.read_until('>')\\n self.index += 1\\n\\n elements = []\\n while len(self.stack) > 0 and\\\\\\n (isinstance(self.stack[-1], str) or self.stack[-1]['tag'] != tag):\\n elements.append(self.stack.pop())\\n\\n assert len(self.stack) > 0\\n\\n self.stack[-1]['elements'].extend(reversed(elements))\\n\\n else:\\n self.ignore_whitespaces()\\n tag = self.read_until(' >')\\n\\n attribs = {}\\n if self.xtext[self.index] != '>':\\n attribs = self.read_attribs()\\n\\n self.index += 1\\n self.stack.append({'tag': tag, 'attribs': attribs, 'elements': []})\\n else:\\n self.stack.append(self.read_until('<').strip())\\n\\n self.loads()\\n\\n\\n def ignore_whitespaces(self):\\n \\\"\\\"\\\"\\n IGNORE_WHITESPACES reads whitespaces and advances self.index\\n \\\"\\\"\\\"\\n\\n whitespaces = [' ', '\\\\t', '\\\\n', '\\\\r']\\n while self.index < self.length and self.xtext[self.index] in whitespaces:\\n self.index += 1\\n\\n def read_until(self, chars):\\n \\\"\\\"\\\"\\n READ_UNTIL reads charaters and advances self.index\\n unitl reaches any character in 'cahrs'\\n\\n Parameters\\n ----------\\n - chars: str\\n stoping characters\\n \\\"\\\"\\\"\\n\\n start_index = self.index\\n\\n while self.index < self.length and self.xtext[self.index] not in chars:\\n self.index += 1\\n\\n assert self.index < self.length\\n\\n return self.xtext[start_index:self.index]\\n\\n def read_attribs(self):\\n \\\"\\\"\\\"\\n READ_ATTRIBS reads attributes of an elements\\n \\\"\\\"\\\"\\n\\n attribs = {}\\n while self.index < self.length:\\n self.ignore_whitespaces()\\n if self.xtext[self.index] == '>':\\n break\\n name = self.read_until('=')\\n self.index += 1\\n self.read_until('\\\"')\\n self.index += 1\\n value = self.read_until('\\\"')\\n self.index += 1\\n\\n attribs[name] = value\\n\\n return attribs\\n\\n xmlloads = XmlLoads(xtext)\\n xmlloads.loads()\\n return xmlloads.stack.pop()\",\n \"def parse(self, xml_text):\\n xml_doc = parse_doc(xml_text)\\n data = findtext(xml_doc, \\\"Data\\\")\\n if data is None:\\n return\\n\\n cryptutil = CryptUtil(conf.get_openssl_cmd())\\n p7m_file = os.path.join(conf.get_lib_dir(), P7M_FILE_NAME)\\n p7m = (\\\"MIME-Version:1.0\\\\n\\\"\\n \\\"Content-Disposition: attachment; filename=\\\\\\\"{0}\\\\\\\"\\\\n\\\"\\n \\\"Content-Type: application/x-pkcs7-mime; name=\\\\\\\"{1}\\\\\\\"\\\\n\\\"\\n \\\"Content-Transfer-Encoding: base64\\\\n\\\"\\n \\\"\\\\n\\\"\\n \\\"{2}\\\").format(p7m_file, p7m_file, data)\\n\\n self.client.save_cache(p7m_file, p7m)\\n\\n trans_prv_file = os.path.join(conf.get_lib_dir(),\\n TRANSPORT_PRV_FILE_NAME)\\n trans_cert_file = os.path.join(conf.get_lib_dir(),\\n TRANSPORT_CERT_FILE_NAME)\\n pem_file = os.path.join(conf.get_lib_dir(), PEM_FILE_NAME)\\n # decrypt certificates\\n cryptutil.decrypt_p7m(p7m_file, trans_prv_file, trans_cert_file,\\n pem_file)\\n\\n # The parsing process use public key to match prv and crt.\\n buf = []\\n begin_crt = False\\n begin_prv = False\\n prvs = {}\\n thumbprints = {}\\n index = 0\\n v1_cert_list = []\\n with open(pem_file) as pem:\\n for line in pem.readlines():\\n buf.append(line)\\n if re.match(r'[-]+BEGIN.*KEY[-]+', line):\\n begin_prv = True\\n elif re.match(r'[-]+BEGIN.*CERTIFICATE[-]+', line):\\n begin_crt = True\\n elif re.match(r'[-]+END.*KEY[-]+', line):\\n tmp_file = self.write_to_tmp_file(index, 'prv', buf)\\n pub = cryptutil.get_pubkey_from_prv(tmp_file)\\n prvs[pub] = tmp_file\\n buf = []\\n index += 1\\n begin_prv = False\\n elif re.match(r'[-]+END.*CERTIFICATE[-]+', line):\\n tmp_file = self.write_to_tmp_file(index, 'crt', buf)\\n pub = cryptutil.get_pubkey_from_crt(tmp_file)\\n thumbprint = cryptutil.get_thumbprint_from_crt(tmp_file)\\n thumbprints[pub] = thumbprint\\n # Rename crt with thumbprint as the file name\\n crt = \\\"{0}.crt\\\".format(thumbprint)\\n v1_cert_list.append({\\n \\\"name\\\": None,\\n \\\"thumbprint\\\": thumbprint\\n })\\n os.rename(tmp_file, os.path.join(conf.get_lib_dir(), crt))\\n buf = []\\n index += 1\\n begin_crt = False\\n\\n # Rename prv key with thumbprint as the file name\\n for pubkey in prvs:\\n thumbprint = thumbprints[pubkey]\\n if thumbprint:\\n tmp_file = prvs[pubkey]\\n prv = \\\"{0}.prv\\\".format(thumbprint)\\n os.rename(tmp_file, os.path.join(conf.get_lib_dir(), prv))\\n\\n for v1_cert in v1_cert_list:\\n cert = Cert()\\n set_properties(\\\"certs\\\", cert, v1_cert)\\n self.cert_list.certificates.append(cert)\",\n \"def olive_parser(text: str) -> dict:\\n soup = BeautifulSoup(text, \\\"lxml\\\")\\n root = soup.find(\\\"xmd-entity\\\")\\n page_no = root['page_no']\\n identifier = root['id']\\n language = root['language']\\n title = soup.meta['name']\\n entity_type = root['entity_type']\\n issue_date = soup.meta['issue_date']\\n\\n out = {\\n \\\"meta\\\": {\\n \\\"language\\\": None,\\n \\\"type\\\": {}\\n },\\n \\\"r\\\": [],\\n \\\"stats\\\": {},\\n \\\"legacy\\\": {\\\"continuation_from\\\": None, \\\"continuation_to\\\": None},\\n }\\n out[\\\"meta\\\"][\\\"title\\\"] = title\\n out[\\\"meta\\\"][\\\"page_no\\\"] = [int(page_no)]\\n out[\\\"meta\\\"][\\\"language\\\"] = normalize_language(language)\\n out[\\\"meta\\\"][\\\"type\\\"][\\\"raw\\\"] = entity_type\\n out[\\\"meta\\\"][\\\"issue_date\\\"] = issue_date\\n\\n new_region = {\\n \\\"c\\\": [],\\n \\\"p\\\": []\\n }\\n\\n new_paragraph = {\\n \\\"l\\\": []\\n }\\n\\n new_line = {\\n \\\"c\\\": [],\\n \\\"t\\\": []\\n }\\n\\n new_token = {\\n \\\"c\\\": [],\\n \\\"tx\\\": \\\"\\\"\\n }\\n\\n for primitive in soup.find_all(\\\"primitive\\\"):\\n\\n # store coordinate of text areas (boxes) by page\\n # 1) page number, 2) coordinate list\\n region = copy.deepcopy(new_region)\\n region[\\\"c\\\"] = [int(i) for i in primitive.get('box').split(\\\" \\\")]\\n\\n para = None\\n line = None\\n line_counter = 0\\n\\n for tag in primitive.find_all(recursive=False):\\n\\n if tag.name == \\\"l\\\":\\n\\n if para is None and line is None:\\n para = copy.deepcopy(new_paragraph)\\n line = copy.deepcopy(new_line)\\n\\n if line_counter > 0 and line is not None:\\n line = normalize_line(line, out[\\\"meta\\\"][\\\"language\\\"])\\n para[\\\"l\\\"].append(line)\\n\\n if tag.get(\\\"p\\\") in [\\\"S\\\", \\\"SA\\\"] and line_counter > 0:\\n region[\\\"p\\\"].append(para)\\n para = copy.deepcopy(new_paragraph)\\n\\n line = copy.deepcopy(new_line)\\n line[\\\"c\\\"] = [\\n int(i)\\n for i in tag.get('box').split(\\\" \\\")\\n ]\\n line_counter += 1\\n\\n if tag.name in [\\\"w\\\", \\\"q\\\"]:\\n\\n # store coordinates of each token\\n # 1) token, 2) page number, 3) coordinate list\\n t = copy.deepcopy(new_token)\\n t[\\\"c\\\"] = [int(i) for i in tag.get('box').split(\\\" \\\")]\\n t[\\\"tx\\\"] = tag.string\\n t[\\\"s\\\"] = int(tag.get('style_ref'))\\n\\n if tag.name == \\\"q\\\" and tag.get('qid') is not None:\\n qid = tag.get('qid')\\n normalized_form = soup.find('qw', qid=qid).text\\n t[\\\"nf\\\"] = normalized_form\\n t[\\\"qid\\\"] = qid\\n\\n # append the token to the line\\n line[\\\"t\\\"].append(t)\\n\\n # append orphan lines\\n if line is not None:\\n line = normalize_line(line, out[\\\"meta\\\"][\\\"language\\\"])\\n para[\\\"l\\\"].append(line)\\n\\n region[\\\"p\\\"].append(para)\\n\\n if para is not None:\\n out[\\\"r\\\"].append(region)\\n\\n out[\\\"legacy\\\"][\\\"id\\\"] = identifier\\n out[\\\"legacy\\\"][\\\"source\\\"] = soup.link['source']\\n \\\"\\\"\\\"\\n # I suspect this could be deleted\\n out[\\\"legacy\\\"][\\\"word_count\\\"] = int(soup.meta['wordcnt'])\\n out[\\\"legacy\\\"][\\\"chars_count\\\"] = int(soup.meta['total_chars_count'])\\n suspicious_chars_count = int(soup.meta['suspicious_chars_count'])\\n out[\\\"legacy\\\"][\\\"suspicious_chars_count\\\"] = int(suspicious_chars_count)\\n \\\"\\\"\\\"\\n out[\\\"legacy\\\"][\\\"first_id\\\"] = soup.link['first_id']\\n out[\\\"legacy\\\"][\\\"last_id\\\"] = soup.link['last_id']\\n out[\\\"legacy\\\"][\\\"next_id\\\"] = soup.link['next_id']\\n out[\\\"legacy\\\"][\\\"prev_id\\\"] = soup.link['prev_id']\\n\\n if root.has_attr('continuation_from'):\\n out[\\\"legacy\\\"][\\\"continuation_from\\\"] = root['continuation_from']\\n\\n if root.has_attr('continuation_to'):\\n out[\\\"legacy\\\"][\\\"continuation_to\\\"] = root['continuation_to']\\n\\n return out\",\n \"def read_speeches(filename):\\n\\n # Open a speech file\\n speech_file = open(filename)\\n\\n # Create a new dictionary\\n speech_dict = {}\\n\\n # Iterate over lines\\n for line in speech_file:\\n # Replace whitespace, including /n, at the end of a line with a single space\\n line = line.rstrip() + ' '\\n\\n # Given that a title begins with #\\n if line.startswith('#'):\\n # Remove '# ' at the beginning and ': ' at the end, to be used as a title\\n title = line[2:-2]\\n # Assign the tile as a key in the dictionary\\n speech_dict[title] = ''\\n # A speech line does not begins with #\\n else:\\n # Not begins with [ either\\n if line.startswith('[') is False:\\n # Append the speech line to the already existing string of the corresponding title\\n # The tile variable is kept from the previous loop(s)\\n speech_dict[title] += line\\n\\n # Close the file\\n speech_file.close()\\n\\n return speech_dict\",\n \"def _process_data(self, wiki_xml):\\r\\n MEDIAWIKI_NS = 'http://www.mediawiki.org/xml/export-0.3/'\\r\\n sequences = []\\r\\n lw_url_re = re.compile(r'\\\\[(http://lesswrong\\\\.com/lw/[^ ]+) [^\\\\]]+\\\\]')\\r\\n\\r\\n for page in wiki_xml.getroot().iterfind('.//{%s}page' % MEDIAWIKI_NS): # TODO: Change to use iterparse\\r\\n # Get the titles\\r\\n title = page.findtext('{%s}title' % MEDIAWIKI_NS)\\r\\n\\r\\n # See if this page is a sequence page\\r\\n sequence_elem = page.xpath(\\\"mw:revision[1]/mw:text[contains(., '[[Category:Sequences]]')]\\\", namespaces={'mw': MEDIAWIKI_NS})\\r\\n\\r\\n if sequence_elem:\\r\\n sequence_elem = sequence_elem[0]\\r\\n articles = []\\r\\n\\r\\n # Find all the lesswrong urls\\r\\n for match in lw_url_re.finditer(sequence_elem.text):\\r\\n article_url = UrlParser(match.group(1))\\r\\n\\r\\n # Only store the path to the article\\r\\n article_path = article_url.path\\r\\n\\r\\n # Ensure path ends in slash\\r\\n if article_path[-1] != '/':\\r\\n article_path += '/'\\r\\n\\r\\n articles.append(article_path)\\r\\n\\r\\n sequences.append({\\r\\n 'title': title,\\r\\n 'articles': articles\\r\\n })\\r\\n return {'sequences': sequences}\",\n \"def eficas_translation(ts_file, new_ts_file, lang):\\n dicoCataToLabel={}\\n dicoCataToTelemac={}\\n header = '<?xml version=\\\"1.0\\\" encoding=\\\"utf-8\\\"?>'\\n header +='<!DOCTYPE TS><TS version=\\\"1.1\\\" language=\\\"'+lang+'\\\">'\\n header +='<context>\\\\n'\\n header +=' <name>@deafult</name>\\\\n'\\n\\n end ='</context>\\\\n</TS>\\\\n'\\n\\n pattern_In=re.compile(r'^\\\\s*<source>(?P<ident>.*)</source>\\\\s*$')\\n pattern_Out=re.compile(r'^\\\\s*<translation>(?P<traduit>.*)</translation>\\\\s*$')\\n pattern_In2=re.compile(r'^\\\\s*<source2>(?P<ident>.*)</source2>\\\\s*$')\\n pattern_Out2=re.compile(r'^\\\\s*<translation2>(?P<traduit>.*)</translation2>\\\\s*$')\\n listeMaj=[]\\n listeMaj.append(('for h','for H'))\\n listeMaj.append(('pour h','pour H'))\\n listeMaj.append(('for u','for U'))\\n listeMaj.append(('pour u','pour U'))\\n listeMaj.append(('of k','of K'))\\n listeMaj.append(('de k','de K'))\\n listeMaj.append(('of h','of H'))\\n listeMaj.append(('de h','de H'))\\n listeMaj.append(('u and v','U and V'))\\n listeMaj.append(('u et v','U et V'))\\n listeMaj.append(('on h','on H'))\\n listeMaj.append(('sur h','sur H'))\\n listeMaj.append(('supg','SUPG'))\\n listeMaj.append(('k and epsilon','K and Epsilon'))\\n listeMaj.append(('k-epsilon','K-Epsilon'))\\n listeMaj.append(('gmres','GMRES'))\\n listeMaj.append(('cgstab','CGSTAB'))\\n listeMaj.append(('q(z)','Q(Z)'))\\n listeMaj.append(('z(q)','Z(Q)'))\\n listeMaj.append(('wgs84','WGS84'))\\n listeMaj.append(('wgs84','UTM'))\\n listeMaj.append(('n-scheme','N-Scheme'))\\n listeMaj.append(('scheme n','Scheme N'))\\n listeMaj.append(('psi-scheme','PSI-Scheme'))\\n listeMaj.append((' psi',' PSI'))\\n listeMaj.append(('f(t90)','F(T90)'))\\n listeMaj.append(('(pa)','(Pa)'))\\n listeMaj.append(('h clipping','H clipping'))\\n listeMaj.append(('delwaq','DELWAQ'))\\n listeMaj.append(('tomawac','TOMAWAC'))\\n listeMaj.append(('chezy','CHEZY'))\\n listeMaj.append(('hllc','HLLC'))\\n listeMaj.append(('c-u','C-U'))\\n listeMaj.append(('c,u,v','C,U,V'))\\n listeMaj.append(('h,u,v','H,U,V'))\\n listeMaj.append(('previmer','PREVIMER'))\\n listeMaj.append(('fes20xx','FES20XX'))\\n listeMaj.append(('legos-nea','LEGOS-NEA'))\\n listeMaj.append(('tpxo','TPXO'))\\n listeMaj.append((' x',' X'))\\n listeMaj.append((' y',' Y'))\\n listeMaj.append(('waf','WAF'))\\n listeMaj.append(('(w/kg)','(W/kg)'))\\n listeMaj.append(('(j/kg)','(W/kg)'))\\n listeMaj.append(('zokagoa','Zokagoa'))\\n listeMaj.append(('nikuradse','Nikuradse'))\\n listeMaj.append(('froude','Froude'))\\n listeMaj.append(('gauss','Gauss'))\\n listeMaj.append(('seidel','Seidel'))\\n listeMaj.append(('leo','Leo'))\\n listeMaj.append(('postma','Postma'))\\n listeMaj.append(('crout','Crout'))\\n listeMaj.append(('okada','Okada'))\\n listeMaj.append(('jmj','JMJ'))\\n listeMaj.append(('haaland','HAALAND'))\\n listeMaj.append(('grad(u)','grad(U)'))\\n listeMaj.append(('variable z','variable Z'))\\n listeMaj.append(('variable r','variable R'))\\n listeMaj.append(('ascii','ASCII'))\\n\\n with open(ts_file, 'r') as f:\\n for ligne in f.readlines():\\n if pattern_In.match(ligne):\\n m = pattern_In.match(ligne)\\n ident = m.group('ident')\\n if pattern_Out.match(ligne):\\n m = pattern_Out.match(ligne)\\n traduit = m.group('traduit')\\n dicoCataToTelemac[ident] = traduit\\n traduitMin = traduit.lower()\\n for t in listeMaj :\\n traduit = traduitMin.replace(t[0], t[1])\\n traduitMin = traduit\\n chaine = traduitMin[0].upper() + traduitMin[1:]\\n dicoCataToLabel[ident] = chaine\\n if pattern_In2.match(ligne):\\n m = pattern_In2.match(ligne)\\n ident = m.group('ident')\\n if pattern_Out2.match(ligne):\\n m = pattern_Out2.match(ligne)\\n traduit = m.group('traduit')\\n dicoCataToTelemac[ident] = traduit\\n dicoCataToLabel[ident] = traduit\\n\\n with open(new_ts_file, 'w') as f:\\n f.write(header)\\n for k in dicoCataToTelemac :\\n text = \\\" <message>\\\\n <source>\\\"\\n text += k\\n text += \\\"</source>\\\\n <translation>\\\"\\n text += dicoCataToLabel[k]\\n text += \\\"</translation>\\\\n </message>\\\\n\\\"\\n f.write(text)\\n f.write(end)\",\n \"def read_subtitles(self):\\n\\n # Group 1: index, Group 2: Start Time, Group 3: End Time, Group 4: Text\\n\\n patterns = [\\n r\\\"(\\\\d+)\\\\n(\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d) --> (\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d)\\\\n((?:.+\\\\n)*.+)\\\",\\n r\\\"(\\\\d+)\\\\r\\\\n(\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d) --> (\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d)\\\\r\\\\n((?:.+\\\\r\\\\n)*.+)\\\",\\n # Reports pattern\\n r\\\"(\\\\d+)\\\\r(\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d) --> (\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d)\\\\n((?:.+\\\\r)*.+)\\\"\\n ]\\n\\n for pattern in patterns:\\n re_subs = re.findall(pattern, self.subtitles, re.M | re.I)\\n if(len(re_subs) > 1):\\n self.re_subs = re_subs\\n return\\n\\n raise Exception(\\n f're_subs length is {len(re_subs)}. Maybe the regex pattern is falty?')\",\n \"def getSubtitleURL(self):\\n\\n # If it is a movie, we use this methodology -\\n try:\\n IndexingParameters = [\\\"subtitleUrls\\\", 0, \\\"url\\\"]\\n TitleParamters = [\\n \\\"catalogMetadata\\\", \\\"catalog\\\", \\\"title\\\", \\\"episodeNumber\\\"]\\n subRequestObject = requests.get(self.subtitleURLContainer)\\n\\n parsedJsonObject = json.loads(str(subRequestObject.text))\\n SubsURL = parsedJsonObject[IndexingParameters[0]][\\n IndexingParameters[1]][IndexingParameters[2]]\\n if self.title == \\\"Amazonsubtitles\\\":\\n try:\\n self.title = parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[2]] + \\\"_\\\" + str(\\n parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[3]])\\n except:\\n pass\\n\\n return SubsURL\\n\\n except:\\n pass\\n pass\",\n \"def elem_to_programme(elem):\\n d = {'start': elem.get('start'),\\n 'channel': elem.get('channel'),\\n 'title': []}\\n\\n set_attrs(d, elem, ('stop', 'pdc-start', 'vps-start', 'showview',\\n 'videoplus', 'clumpidx'))\\n\\n append_text(d, 'title', elem)\\n append_text(d, 'sub-title', elem)\\n append_text(d, 'desc', elem)\\n\\n crednode = elem.find('credits')\\n if crednode is not None:\\n creddict = {}\\n # TODO: actor can have a 'role' attribute\\n for credtype in ('director', 'actor', 'writer', 'adapter', 'producer',\\n 'presenter', 'commentator', 'guest', 'composer',\\n 'editor'):\\n append_text(creddict, credtype, crednode, with_lang=False)\\n d['credits'] = creddict\\n\\n set_text(d, 'date', elem, with_lang=False)\\n append_text(d, 'category', elem)\\n set_text(d, 'language', elem)\\n set_text(d, 'orig-language', elem)\\n\\n lennode = elem.find('length')\\n if lennode is not None:\\n lend = {'units': lennode.get('units'),\\n 'length': lennode.text}\\n d['length'] = lend\\n\\n append_icons(d, elem)\\n append_text(d, 'url', elem, with_lang=False)\\n append_text(d, 'country', elem)\\n\\n for epnumnode in elem.findall('episode-num'):\\n if not d.has_key('episode-num'):\\n d['episode-num'] = []\\n d['episode-num'].append((epnumnode.text,\\n epnumnode.get('system', 'xmltv_ns')))\\n\\n vidnode = elem.find('video')\\n if vidnode is not None:\\n vidd = {}\\n for name in ('present', 'colour'):\\n set_boolean(vidd, name, vidnode)\\n for videlem in ('aspect', 'quality'):\\n venode = vidnode.find(videlem)\\n if venode is not None:\\n vidd[videlem] = venode.text\\n d['video'] = vidd\\n\\n audnode = elem.find('audio')\\n if audnode is not None:\\n audd = {}\\n set_boolean(audd, 'present', audnode)\\n stereonode = audnode.find('stereo')\\n if stereonode is not None:\\n audd['stereo'] = stereonode.text\\n d['audio'] = audd\\n\\n psnode = elem.find('previously-shown')\\n if psnode is not None:\\n psd = {}\\n set_attrs(psd, psnode, ('start', 'channel'))\\n d['previously-shown'] = psd\\n\\n set_text(d, 'premiere', elem)\\n set_text(d, 'last-chance', elem)\\n\\n if elem.find('new') is not None:\\n d['new'] = True\\n\\n for stnode in elem.findall('subtitles'):\\n if not d.has_key('subtitles'):\\n d['subtitles'] = []\\n std = {}\\n set_attrs(std, stnode, ('type',))\\n set_text(std, 'language', stnode)\\n d['subtitles'].append(std)\\n\\n for ratnode in elem.findall('rating'):\\n if not d.has_key('rating'):\\n d['rating'] = []\\n ratd = {}\\n set_attrs(ratd, ratnode, ('system',))\\n set_text(ratd, 'value', ratnode, with_lang=False)\\n append_icons(ratd, ratnode)\\n d['rating'].append(ratd)\\n\\n for srnode in elem.findall('star-rating'):\\n if not d.has_key('star-rating'):\\n d['star-rating'] = []\\n srd = {}\\n set_attrs(srd, srnode, ('system',))\\n set_text(srd, 'value', srnode, with_lang=False)\\n append_icons(srd, srnode)\\n d['star-rating'].append(srd)\\n\\n for revnode in elem.findall('review'):\\n if not d.has_key('review'):\\n d['review'] = []\\n rd = {}\\n set_attrs(rd, revnode, ('type', 'source', 'reviewer',))\\n set_text(rd, 'value', revnode, with_lang=False)\\n d['review'].append(rd)\\n\\n return d\",\n \"def parse_title(self, pre):\\n # Extract datapoints\\n title_text = str(pre)\\n title = {}\\n\\n identity_data = self.identity_regex.search(title_text)\\n title['linc'] = int(identity_data.group(1).strip().replace(' ', ''))\\n title['short_legal'] = identity_data.group(2).strip().replace(';', ' ')\\n title['title_number'] = identity_data.group(3).strip()\\n\\n try:\\n title['ats_reference'] = self.ats_regex.search(title_text).group(1).replace(';',' ')\\n except AttributeError:\\n title['ats_reference'] = ''\\n\\n title['municipality'] = self.municipality_regex.search(title_text).group(1).replace('\\\\r','')\\n\\n try:\\n references = self.reference_regex.search(title_text).group(1).split(\\\"\\\\n\\\")\\n references = [i.strip() for i in references]\\n references = list(filter(None, references))\\n title['reference_number'] = references\\n except AttributeError:\\n title['reference_number'] = ['']\\n\\n payday_raw = self.payday_regex.search(title_text).group(3).strip('</pre>').strip()\\n title['registration'] = payday_raw[:11]\\n title['date'] = reversed(payday_raw[15:25].split('/'))\\n title['date'] = '-'.join(title['date'])\\n title['document_type'] = payday_raw[27:46].strip()\\n\\n title['value'] = self._try_int(payday_raw[46:62].strip())\\n title['consideration'] = self._try_int(payday_raw[62:80].strip())\\n\\n if \\\"CONDOMINIUM\\\" in title_text:\\n title['condo'] = True\\n else:\\n title['condo'] = False\\n\\n title['title_text'] = title_text.strip('<pre>').strip('</pre>').strip()\\n\\n return title\",\n \"def to_xml_dict(self):\\n self._check_required_fields()\\n\\n root = odict[\\n \\\"r:import\\\": odict[\\n \\\"@xmlns:r\\\": \\\"http://resolver.nkp.cz/v3/\\\",\\n \\\"r:monograph\\\": odict[\\n \\\"r:titleInfo\\\": odict[\\n \\\"r:title\\\": self.title,\\n ],\\n ],\\n ]\\n ]\\n mono_root = root[\\\"r:import\\\"][\\\"r:monograph\\\"]\\n\\n # subtitle\\n MonographComposer._assign_pattern(\\n mono_root[\\\"r:titleInfo\\\"],\\n \\\"r:subTitle\\\",\\n self.subtitle\\n )\\n\\n # handle ccnb, isbn, uuid\\n self._add_identifier(mono_root, \\\"ccnb\\\")\\n self._add_identifier(mono_root, \\\"isbn\\\")\\n self._add_identifier(mono_root, \\\"other_id\\\", out=\\\"otherId\\\")\\n\\n # add form of the book\\n MonographComposer._assign_pattern(\\n mono_root,\\n \\\"r:documentType\\\",\\n self.document_type\\n )\\n\\n mono_root[\\\"r:digitalBorn\\\"] = \\\"true\\\" if self.digital_born else \\\"false\\\"\\n\\n if self.author:\\n mono_root[\\\"r:primaryOriginator\\\"] = odict[\\n \\\"@type\\\": \\\"AUTHOR\\\",\\n \\\"#text\\\": self.author\\n ]\\n\\n if any([self.place, self.publisher, self.year]):\\n publ = odict()\\n\\n MonographComposer._assign_pattern(\\n publ,\\n \\\"r:publisher\\\",\\n self.publisher\\n )\\n MonographComposer._assign_pattern(publ, \\\"r:place\\\", self.place)\\n MonographComposer._assign_pattern(publ, \\\"r:year\\\", self.year)\\n\\n mono_root[\\\"r:publication\\\"] = publ\\n\\n if self.format:\\n format_dict = MonographComposer._create_path(\\n root,\\n odict,\\n [\\n \\\"r:import\\\",\\n \\\"r:digitalDocument\\\",\\n \\\"r:technicalMetadata\\\",\\n \\\"r:format\\\",\\n ]\\n )\\n\\n format_dict[\\\"#text\\\"] = self.format\\n\\n return root\",\n \"def convert(text: str) -> Iterator[Tuple[str, str]]:\\n with gzip.open(resource_filename(\\\"nautc\\\", \\\"txt.gz\\\"), \\\"rt\\\") as txt:\\n return (\\n lambda idxs: map(\\n lambda kv: (\\n kv[0],\\n \\\"\\\".join(\\n map(\\n lambda char: char in idxs\\n and kv[1][idxs[char]]\\n or char,\\n text,\\n )\\n ),\\n ),\\n (\\n lambda lines: map(\\n lambda t, c: (t, c.split(\\\"||\\\")),\\n lines[::2],\\n lines[1::2],\\n )\\n )(txt.read().splitlines()),\\n )\\n )(\\n dict(\\n map(\\n lambda kv: (kv[1], kv[0]),\\n enumerate(ascii_letters + digits),\\n )\\n )\\n )\",\n \"def xml_to_dict(args):\\n rdict = dict()\\n args = re.sub(r'xmlns=\\\\\\\".+?\\\\\\\"', '', args)\\n root = ET.fromstring(args)\\n ifmtrunk = root.find('.//ifmtrunk')\\n if ifmtrunk is not None:\\n try:\\n ifmtrunk_iter = ET.Element.iter(ifmtrunk)\\n except AttributeError:\\n ifmtrunk_iter = ifmtrunk.getiterator()\\n\\n for ele in ifmtrunk_iter:\\n if ele.text is not None and len(ele.text.strip()) > 0:\\n rdict[ele.tag] = ele.text\\n return rdict\",\n \"def getXmlDict(oxml):\\n lines = oxml.split(\\\"\\\\n\\\")\\n rrd_d = {}\\n # <cf> AVERAGE </cf>\\n # <pdp_per_row> 288 </pdp_per_row> <!-- 86400 seconds -->\\n\\n # parse xml file\\n key = \\\"\\\"\\n rows = [] \\n for line in lines:\\n if (reMatchCF(line)):\\n cf = line.split()[1]\\n key += cf\\n if (reMatchPDP(line)):\\n pdp = line.split()[1]\\n key += pdp\\n if (reMatchRow(line)):\\n ele = line.split()\\n time = ele[5]\\n val = ele[8]\\n rows.append([time,val,line])\\n # end of rra is reached, store to dict and rest vals\\n if (reMatchDBEnd(line) and key and rows):\\n rrd_d[key] = rows\\n key = \\\"\\\"\\n rows = []\\n return rrd_d\",\n \"def generate_subs(speed, source_speed, source_subs):\\r\\n if speed == source_speed:\\r\\n return source_subs\\r\\n\\r\\n coefficient = 1.0 * speed / source_speed\\r\\n subs = {\\r\\n 'start': [\\r\\n int(round(timestamp * coefficient)) for\\r\\n timestamp in source_subs['start']\\r\\n ],\\r\\n 'end': [\\r\\n int(round(timestamp * coefficient)) for\\r\\n timestamp in source_subs['end']\\r\\n ],\\r\\n 'text': source_subs['text']}\\r\\n return subs\",\n \"def parse_to_json(self, content):\\n if content:\\n stix_dict = STIXPackage.from_xml(etree.XML(content)).to_dict() # parse to dictionary\\n return stix_dict\\n else:\\n return {}\",\n \"def xml_to_dict(self):\\n medicine_node = ['medicines', 'dose', 'unit', 'unit_price', 'goods_num', 'dose_that',\\n 'remark', 'm_usage', 'goods_norms', 'goods_orgin', 'MedPerDos', 'MedPerDay']\\n dict_data = {}\\n n = 0\\n xq_childs = 0\\n for child in self.root.iter():\\n # print(child.tag)\\n # print(child.text)\\n if child.tag not in medicine_node:\\n if child.tag == 'xq':\\n xq_childs = child.__len__() # __len__：返回元素大小，元素的大小为元素的子元素数量\\n dict_data[child.tag] = child.text\\n else:\\n if n < xq_childs:\\n dict_data[child.tag] = [child.text]\\n n += 1\\n else:\\n dict_data[child.tag].append(child.text)\\n return dict_data\",\n \"def extract_staxml_info(staxml):\\n instruments = defaultdict(dict)\\n\\n if isinstance(staxml, Inventory):\\n inv = staxml\\n else:\\n if os.path.isfile(staxml):\\n inv = safe_load_staxml(staxml)\\n else:\\n raise ValueError(\\\"Input staxml is neither obspy.Inventory or \\\"\\n \\\"staxml file\\\")\\n for nw in inv:\\n nw_code = nw.code\\n for sta in nw:\\n sta_code = sta.code\\n for chan in sta:\\n chan_code = chan.code\\n loc_code = chan.location_code\\n key = \\\"%s.%s.%s.%s\\\" % (nw_code, sta_code, loc_code, chan_code)\\n instruments[key][\\\"latitude\\\"] = chan.latitude\\n instruments[key][\\\"longitude\\\"] = chan.longitude\\n instruments[key][\\\"elevation\\\"] = chan.elevation\\n instruments[key][\\\"depth\\\"] = chan.depth\\n if chan.sensor.description is not None:\\n sensor_type = chan.sensor.description\\n elif chan.sensor.type is not None:\\n sensor_type = chan.sensor.type\\n else:\\n sensor_type = \\\"None\\\"\\n instruments[key][\\\"sensor\\\"] = sensor_type\\n\\n return instruments\",\n \"def parse_m3u8_doc(self):\\r\\n lines = self.m3u8_doc.splitlines()\\r\\n lines = [line.strip() for line in lines if line.strip()]\\r\\n\\r\\n for i, line in enumerate(lines):\\r\\n\\r\\n if line.startswith('#EXT-X-VERSION'):\\r\\n self.playlist_version = line.split(':')[1]\\r\\n elif line.startswith('#EXT-X-PLAYLIST-TYPE'):\\r\\n self.playlist_type = line.split(':')[1]\\r\\n elif line.startswith('#EXT-X-MEDIA-SEQUENCE'):\\r\\n self.media_sequence = line.split(':')[1]\\r\\n elif line.startswith('#EXT-X-TARGETDURATION'):\\r\\n self.max_seg_duration = line.split(':')[1]\\r\\n\\r\\n elif line.startswith('#EXT-X-KEY'):\\r\\n key = Key()\\r\\n key.raw_line = line\\r\\n info = parse_m3u8_line(line)\\r\\n key.url = info.get('URI')\\r\\n key.method = info.get('METHOD')\\r\\n key.iv = info.get('IV')\\r\\n if key.method and key.url:\\r\\n if key.url.startswith('skd://'):\\r\\n # replace skd:// with https://\\r\\n key.url = key.url.replace('skd://', 'https://')\\r\\n\\r\\n key.url = urljoin(self.url, key.url)\\r\\n self.encrypted = True\\r\\n self.encryption_type = key.method\\r\\n self.current_key = key\\r\\n\\r\\n # stream #EXTINF tag must be followed by stream url\\r\\n elif line.startswith('#EXTINF'):\\r\\n try:\\r\\n self.seg_duration = float(line.split(':')[1].split(',')[0])\\r\\n self.total_duration += self.seg_duration\\r\\n except:\\r\\n pass\\r\\n\\r\\n next_line = lines[i + 1]\\r\\n seg = Segment()\\r\\n seg.url = next_line if not next_line.startswith('#') else None\\r\\n seg.duration = self.seg_duration\\r\\n seg.key = copy.copy(self.current_key)\\r\\n\\r\\n if seg.url:\\r\\n if seg.url.startswith('skd://'):\\r\\n # replace skd:// with https://\\r\\n seg.url = seg.url.replace('skd://', 'https://')\\r\\n\\r\\n seg.url = urljoin(self.url, seg.url)\\r\\n self.segments.append(seg)\\r\\n\\r\\n elif line.startswith('#EXT-X-ENDLIST'):\\r\\n # print('end of playlist')\\r\\n break\\r\\n\\r\\n # naming\\r\\n for i, seg in enumerate(self.segments):\\r\\n seg.name = os.path.join(self.d.temp_folder, f'{self.stream_type}_seg_{i + 1}.ts')\\r\\n\\r\\n if seg.key:\\r\\n seg.key.name = f'{seg.name}.key'\",\n \"def get_media_info(xmlsent):\\n media = {}\\n media_element = xmlsent.findall(\\\".//{%s}media\\\" % NS)\\n\\n if media_element:\\n media_element = media_element[0]\\n media = {'start': media_element.attrib['start'],\\n 'end': media_element.attrib['end'],\\n 'unit': media_element.attrib['unit']\\n }\\n return media\",\n \"def inf2dict(text):\\n lines = text.strip().split('\\\\n')\\n pairs, extra_lines = split_lines(lines)\\n return parse_pairs(pairs, extra_lines)\",\n \"def get_data(contents):\\n\\n header = {}\\n copy = contents.split(\\\"\\\\n\\\")\\n\\n header_contents = dict(\\n start_date=\\\"Start Date\\\",\\n end_date=\\\" End Date\\\",\\n subject=\\\" Subject\\\",\\n experiment=\\\" Experiment\\\",\\n group=\\\" Group\\\",\\n box=\\\" Box\\\",\\n start_time=\\\" Start Time\\\",\\n end_time=\\\" End Time\\\",\\n program=\\\" Program\\\",\\n msn=\\\" MSN\\\",\\n )\\n\\n for line in copy:\\n for key in header_contents:\\n heading = line.split(\\\":\\\")\\n if heading[0] == header_contents[key]:\\n if key == \\\"start_time\\\" or key == \\\"end_time\\\":\\n header[key] = (\\n heading[1].lstrip() + \\\":\\\" + heading[2] + \\\":\\\" + heading[3]\\n )\\n else:\\n header[key] = heading[1].lstrip()\\n\\n data = {}\\n copy = contents.split()\\n\\n uppercase = string.ascii_uppercase\\n\\n idx = []\\n for i, val in enumerate(copy):\\n if val[0] in uppercase and val[1] == \\\":\\\":\\n idx.append(i)\\n\\n for i, j in zip(idx[:-1], idx[1:]):\\n data[copy[i].lower()[0]] = [\\n timestamp for timestamp in copy[i + 1 : j] if timestamp[-1] != \\\":\\\"\\n ]\\n\\n return header, data\",\n \"def get_translations(self) -> Dict[str, Dict[str, Tuple[str, Type]]]:\\n\\n return {\\n 'material': {'elemental_proportion': ('elemental_proportions', dict)},\\n }\",\n \"def preprocess_text(text: str) -> Tuple[List[str], Dict]:\\n raise NotImplementedError\",\n \"def parse_book_record(root) -> dict:\\n\\n doc = {\\n \\\"abstract\\\": \\\"\\\",\\n \\\"pmid\\\": \\\"\\\",\\n \\\"title\\\": \\\"\\\",\\n \\\"authors\\\": [],\\n \\\"pub_date\\\": \\\"\\\",\\n \\\"journal_iso_title\\\": \\\"\\\",\\n \\\"journal_title\\\": \\\"\\\",\\n \\\"doi\\\": \\\"\\\",\\n \\\"compounds\\\": [],\\n \\\"mesh\\\": [],\\n }\\n\\n doc[\\\"pmid\\\"] = root.xpath(\\\".//PMID/text()\\\")[0]\\n\\n doc[\\\"title\\\"] = next(iter(root.xpath(\\\".//BookTitle/text()\\\")))\\n\\n doc[\\\"authors\\\"] = []\\n for author in root.xpath(\\\".//Author\\\"):\\n last_name = next(iter(author.xpath(\\\"LastName/text()\\\")), \\\"\\\")\\n first_name = next(iter(author.xpath(\\\"ForeName/text()\\\")), \\\"\\\")\\n initials = next(iter(author.xpath(\\\"Initials/text()\\\")), \\\"\\\")\\n if not first_name and initials:\\n first_name = initials\\n doc[\\\"authors\\\"].append(f\\\"{last_name}, {first_name}\\\")\\n\\n pub_year = next(iter(root.xpath(\\\".//Book/PubDate/Year/text()\\\")), None)\\n pub_mon = next(iter(root.xpath(\\\".//Book/PubDate/Month/text()\\\")), \\\"Jan\\\")\\n pub_day = next(iter(root.xpath(\\\".//Book/PubDate/Day/text()\\\")), \\\"01\\\")\\n medline_date = next(\\n iter(root.xpath(\\\".//Journal/JournalIssue/PubDate/MedlineDate/text()\\\")), None\\n )\\n\\n pub_date = process_pub_date(pub_year, pub_mon, pub_day, medline_date)\\n\\n doc[\\\"pub_date\\\"] = pub_date\\n\\n for abstracttext in root.xpath(\\\".//Abstract/AbstractText\\\"):\\n abstext = node_text(abstracttext)\\n\\n label = abstracttext.get(\\\"Label\\\", None)\\n if label:\\n doc[\\\"abstract\\\"] += f\\\"{label}: {abstext}\\\\n\\\"\\n else:\\n doc[\\\"abstract\\\"] += f\\\"{abstext}\\\\n\\\"\\n\\n doc[\\\"abstract\\\"] = doc[\\\"abstract\\\"].rstrip()\\n\\n return doc\",\n \"def add_subtags(path, pxml_subtags):\\n # print(\\\"CALLING... add_subtag\\\")\\n root, tree = gen_tree(path)\\n nmsps = root.nsmap['r']\\n for k,v in pxml_subtags.items():\\n subtag1 = tree.find(k)\\n for i in v:\\n if 'rId' not in i[1]:\\n rId = f\\\"{{{nmsps}}}id\\\"\\n subtext = etree.SubElement(subtag1, i[0])\\n subtext.attrib['id'] = i[1]\\n subtext.attrib[rId] = i[2]\\n else:\\n subtext = etree.SubElement(subtag1, i[0])\\n subtext.attrib[rId] = i[1]\\n tree.write(f'{output_path}/ppt/presentation.xml', pretty_print=True, xml_declaration=True, encoding='UTF-8', standalone=True)\\n return\",\n \"def subparse(block):\\n\\n verses = []\\n context = None\\n for char in block:\\n\\n if char == \\\"[\\\":\\n if verses: verses[-1][\\\"quran\\\"] = verses[-1][\\\"quran\\\"].strip()\\n verses.append({\\\"surah\\\": \\\"\\\", \\\"verse\\\": \\\"\\\", \\\"quran\\\": \\\"\\\"})\\n context = \\\"surah\\\"\\n elif char == \\\":\\\" and context == \\\"surah\\\":\\n verses[-1][\\\"surah\\\"] = int(verses[-1][\\\"surah\\\"])\\n context = \\\"verse\\\"\\n elif char == \\\"]\\\":\\n verses[-1][\\\"verse\\\"] = int(verses[-1][\\\"verse\\\"])\\n context = \\\"quran\\\"\\n else: verses[-1][context] += char\\n\\n verses[-1][\\\"quran\\\"] = verses[-1][\\\"quran\\\"].strip()\\n return verses\",\n \"def get_subtitle(annotation, sub_duration, video_clip, seen_annotations):\\n if len(annotation[\\\"text\\\"]) == 0:\\n return None\\n\\n annotation_txt = calculate_needed_subtitle_height(annotation, seen_annotations, video_clip)\\n\\n txt_clip = TextClip(annotation_txt, color=\\\"white\\\", fontsize=70, font='Sans Serif')\\n txt_clip = txt_clip.set_position((\\\"center\\\", get_subtitle_offset(annotation, seen_annotations, video_clip)))\\n txt_clip = txt_clip.set_start(float(annotation[\\\"time\\\"]) / 1000.0)\\n txt_clip = txt_clip.set_duration(sub_duration)\\n\\n return txt_clip\",\n \"def __init__(self, subtitle=None):\\n self.subtitle = subtitle\\n if not self.subtitle:\\n self.parse_subtitles()\",\n \"def xml_parse_prairie(xmlFileName,verbose=True):\\n if verbose:\\n print(\\\"parsing\\\",os.path.basename(xmlFileName))\\n assert os.path.exists(xmlFileName), \\\"can't find \\\"+xmlFileName\\n with open(xmlFileName) as f:\\n xml=f.read()\\n xml=xml.split(\\\">\\\")\\n for i,line in enumerate(xml):\\n xml[i]=line.strip()\\n xml=\\\"\\\".join(xml)\\n conf={}\\n for key in ['opticalZoom','objectiveLens', # physical lens\\n 'pixelsPerLine','linesPerFrame', # dimensions\\n 'dwellTime','framePeriod','scanLinePeriod' # pixel timing\\n 'laserPower', # laser settings\\n 'pmtGain~1~','pmtGain~2~', # PMT settings\\n 'INTENTIONAL_FAILURE', # just testing\\n ]:\\n val=xml_value_from_key(xml,key)\\n if val is not None:\\n conf[key.replace(\\\"~\\\",'')]=val\\n times=[float(x.split('\\\"')[1]) for x in xml.split(\\\"absoluteTime=\\\")[1:]]\\n conf[\\\"times\\\"]=np.array(times)\\n if verbose and len(conf.keys()):\\n print(\\\"XML parsing produced:\\\")\\n for key in sorted(conf.keys()):\\n if key is 'times':\\n print(\\\" times=[%d points]\\\"%len(times))\\n else:\\n print(\\\" %s=%s\\\"%(key,conf[key]))\\n return conf\",\n \"def _build_transcript(self):\\n\\n # Create the transcript dictionary\\n transcript_dict = dict()\\n for splitted in self._get_transcript_entries(self._data_directory):\\n transcript_dict[splitted[0]] = vocabulary.sentence_to_ids(splitted[1])\\n\\n return transcript_dict\",\n \"def recursive_parse_xml_to_dict(xml):\\n if not xml:\\n return {xml.tag: xml.text}\\n result = {}\\n for child in xml:\\n child_result = recursive_parse_xml_to_dict(child)\\n if child.tag != 'object':\\n result[child.tag] = child_result[child.tag]\\n else:\\n if child.tag not in result:\\n result[child.tag] = []\\n result[child.tag].append(child_result[child.tag])\\n return {xml.tag: result}\",\n \"def recursive_parse_xml_to_dict(xml):\\n if not xml:\\n return {xml.tag: xml.text}\\n result = {}\\n for child in xml:\\n child_result = recursive_parse_xml_to_dict(child)\\n if child.tag != 'object':\\n result[child.tag] = child_result[child.tag]\\n else:\\n if child.tag not in result:\\n result[child.tag] = []\\n result[child.tag].append(child_result[child.tag])\\n return {xml.tag: result}\",\n \"def __build_dictionary(self):\\n def recursive_generation(t):\\n \\\"\\\"\\\"\\n Nested helper function that recursively loops through an XML node to construct a dictionary.\\n Solution from http://stackoverflow.com/a/10077069 (2013-01-19)\\n \\\"\\\"\\\"\\n d = {t.tag: {} if t.attrib else None}\\n children = list(t)\\n\\n if children:\\n dd = defaultdict(list)\\n\\n for dc in map(recursive_generation, children):\\n for k, v in dc.iteritems():\\n dd[k].append(v)\\n\\n d = {t.tag: {k:v[0] if len(v) == 1 else v for k, v in dd.iteritems()}}\\n\\n if t.attrib:\\n d[t.tag].update(('@' + k, v) for k, v in t.attrib.iteritems())\\n\\n if t.text:\\n text = t.text.strip()\\n\\n if children or t.attrib:\\n if text:\\n d[t.tag]['#text'] = text\\n else:\\n d[t.tag] = text\\n\\n return d\\n \\n string_repr = etree.tostring(self._config_file, pretty_print=True)\\n element_tree = cElementTree.XML(string_repr)\\n \\n self._config_dict = recursive_generation(element_tree)\\n self._config_dict = self._config_dict[self._config_dict.keys()[0]]\",\n \"def parse_svn_info_xml(xml_string):\\r\\n d = {}\\r\\n tree = ET.fromstring(xml_string)\\r\\n entry = tree.find('.//entry')\\r\\n if entry:\\r\\n d['url'] = entry.find('url').text\\r\\n d['revision'] = int(entry.get('revision'))\\r\\n d['repos_url'] = tree.find('.//repository/root').text\\r\\n d['last_changed_rev'] = int(tree.find('.//commit').get('revision'))\\r\\n d['kind'] = entry.get('kind')\\r\\n return d\",\n \"def parsexml0(xmltext, startingat=0, toplevel=1,\\n # snarf in some globals\\n entityReplacer=unEscapeContentList,\\n #len=len, None=None\\n #LENCDATAMARKER=LENCDATAMARKER, CDATAMARKER=CDATAMARKER\\n ):\\n #print \\\"parsexml0\\\", repr(xmltext[startingat: startingat+10])\\n # DEFAULTS\\n NameString = NONAME\\n ContentList = AttDict = ExtraStuff = None\\n if toplevel is not None:\\n #if verbose: print \\\"at top level\\\"\\n #if startingat!=0:\\n # raise ValueError, \\\"have to start at 0 for top level!\\\"\\n xmltext = xmltext.strip()\\n cursor = startingat\\n #look for interesting starting points\\n firstbracket = xmltext.find(\\\"<\\\", cursor)\\n afterbracket2char = xmltext[firstbracket+1:firstbracket+3]\\n #print \\\"a\\\", repr(afterbracket2char)\\n #firstampersand = xmltext.find(\\\"&\\\", cursor)\\n #if firstampersand>0 and firstampersand<firstbracket:\\n # raise ValueError, \\\"I don't handle ampersands yet!!!\\\"\\n docontents = 1\\n if firstbracket<0:\\n # no tags\\n #if verbose: print \\\"no tags\\\"\\n if toplevel is not None:\\n #D = {NAMEKEY: NONAME, CONTENTSKEY: [xmltext[cursor:]]}\\n ContentList = [xmltext[cursor:]]\\n if entityReplacer: ContentList = entityReplacer(ContentList)\\n return (NameString, AttDict, ContentList, ExtraStuff), len(xmltext)\\n else:\\n raise ValueError(\\\"no tags at non-toplevel %s\\\" % repr(xmltext[cursor:cursor+20]))\\n #D = {}\\n L = []\\n # look for start tag\\n # NEED to force always outer level is unnamed!!!\\n #if toplevel and firstbracket>0:\\n #afterbracket2char = xmltext[firstbracket:firstbracket+2]\\n if toplevel is not None:\\n #print \\\"toplevel with no outer tag\\\"\\n NameString = name = NONAME\\n cursor = skip_prologue(xmltext, cursor)\\n #break\\n elif firstbracket<0:\\n raise ValueError(\\\"non top level entry should be at start tag: %s\\\" % repr(xmltext[:10]))\\n # special case: CDATA\\n elif afterbracket2char==\\\"![\\\" and xmltext[firstbracket:firstbracket+9]==\\\"<![CDATA[\\\":\\n #print \\\"in CDATA\\\", cursor\\n # skip straight to the close marker\\n startcdata = firstbracket+9\\n endcdata = xmltext.find(CDATAENDMARKER, startcdata)\\n if endcdata<0:\\n raise ValueError(\\\"unclosed CDATA %s\\\" % repr(xmltext[cursor:cursor+20]))\\n NameString = CDATAMARKER\\n ContentList = [xmltext[startcdata: endcdata]]\\n cursor = endcdata+len(CDATAENDMARKER)\\n docontents = None\\n # special case COMMENT\\n elif afterbracket2char==\\\"!-\\\" and xmltext[firstbracket:firstbracket+4]==\\\"<!--\\\":\\n #print \\\"in COMMENT\\\"\\n endcommentdashes = xmltext.find(\\\"--\\\", firstbracket+4)\\n if endcommentdashes<firstbracket:\\n raise ValueError(\\\"unterminated comment %s\\\" % repr(xmltext[cursor:cursor+20]))\\n endcomment = endcommentdashes+2\\n if xmltext[endcomment]!=\\\">\\\":\\n raise ValueError(\\\"invalid comment: contains double dashes %s\\\" % repr(xmltext[cursor:cursor+20]))\\n return (None, endcomment+1) # shortcut exit\\n else:\\n # get the rest of the tag\\n #if verbose: print \\\"parsing start tag\\\"\\n # make sure the tag isn't in doublequote pairs\\n closebracket = xmltext.find(\\\">\\\", firstbracket)\\n noclose = closebracket<0\\n startsearch = closebracket+1\\n pastfirstbracket = firstbracket+1\\n tagcontent = xmltext[pastfirstbracket:closebracket]\\n # shortcut, no equal means nothing but name in the tag content\\n if '=' not in tagcontent:\\n if tagcontent[-1]==\\\"/\\\":\\n # simple case\\n #print \\\"simple case\\\", tagcontent\\n tagcontent = tagcontent[:-1]\\n docontents = None\\n name = tagcontent.strip()\\n NameString = name\\n cursor = startsearch\\n else:\\n if '\\\"' in tagcontent:\\n # check double quotes\\n stop = None\\n # not inside double quotes! (the split should have odd length)\\n if noclose or len((tagcontent+\\\".\\\").split('\\\"'))% 2:\\n stop=1\\n while stop is None:\\n closebracket = xmltext.find(\\\">\\\", startsearch)\\n startsearch = closebracket+1\\n noclose = closebracket<0\\n tagcontent = xmltext[pastfirstbracket:closebracket]\\n # not inside double quotes! (the split should have odd length)\\n if noclose or len((tagcontent+\\\".\\\").split('\\\"'))% 2:\\n stop=1\\n if noclose:\\n raise ValueError(\\\"unclosed start tag %s\\\" % repr(xmltext[firstbracket:firstbracket+20]))\\n cursor = startsearch\\n #cursor = closebracket+1\\n # handle simple tag /> syntax\\n if xmltext[closebracket-1]==\\\"/\\\":\\n #if verbose: print \\\"it's a simple tag\\\"\\n closebracket = closebracket-1\\n tagcontent = tagcontent[:-1]\\n docontents = None\\n #tagcontent = xmltext[firstbracket+1:closebracket]\\n tagcontent = tagcontent.strip()\\n taglist = tagcontent.split(\\\"=\\\")\\n #if not taglist:\\n # raise ValueError, \\\"tag with no name %s\\\" % repr(xmltext[firstbracket:firstbracket+20])\\n taglist0 = taglist[0]\\n taglist0list = taglist0.split()\\n #if len(taglist0list)>2:\\n # raise ValueError, \\\"bad tag head %s\\\" % repr(taglist0)\\n name = taglist0list[0]\\n #print \\\"tag name is\\\", name\\n NameString = name\\n # now parse the attributes\\n attributename = taglist0list[-1]\\n # put a fake att name at end of last taglist entry for consistent parsing\\n taglist[-1] = taglist[-1]+\\\" f\\\"\\n AttDict = D = {}\\n taglistindex = 1\\n lasttaglistindex = len(taglist)\\n #for attentry in taglist[1:]:\\n while taglistindex<lasttaglistindex:\\n #print \\\"looking for attribute named\\\", attributename\\n attentry = taglist[taglistindex]\\n taglistindex = taglistindex+1\\n attentry = attentry.strip()\\n if attentry[0]!='\\\"':\\n raise ValueError(\\\"attribute value must start with double quotes\\\" + repr(attentry))\\n while '\\\"' not in attentry[1:]:\\n # must have an = inside the attribute value...\\n if taglistindex>lasttaglistindex:\\n raise ValueError(\\\"unclosed value \\\" + repr(attentry))\\n nextattentry = taglist[taglistindex]\\n taglistindex = taglistindex+1\\n attentry = \\\"%s=%s\\\" % (attentry, nextattentry)\\n attentry = attentry.strip() # only needed for while loop...\\n attlist = attentry.split()\\n nextattname = attlist[-1]\\n attvalue = attentry[:-len(nextattname)]\\n attvalue = attvalue.strip()\\n try:\\n first = attvalue[0]; last=attvalue[-1]\\n except:\\n raise ValueError(\\\"attvalue,attentry,attlist=\\\"+repr((attvalue, attentry,attlist)))\\n if first==last=='\\\"' or first==last==\\\"'\\\":\\n attvalue = attvalue[1:-1]\\n #print attributename, \\\"=\\\", attvalue\\n D[attributename] = attvalue\\n attributename = nextattname\\n # pass over other tags and content looking for end tag\\n if docontents is not None:\\n #print \\\"now looking for end tag\\\"\\n ContentList = L\\n while docontents is not None:\\n nextopenbracket = xmltext.find(\\\"<\\\", cursor)\\n if nextopenbracket<cursor:\\n #if verbose: print \\\"no next open bracket found\\\"\\n if name==NONAME:\\n #print \\\"no more tags for noname\\\", repr(xmltext[cursor:cursor+10])\\n docontents=None # done\\n remainder = xmltext[cursor:]\\n cursor = len(xmltext)\\n if remainder:\\n L.append(remainder)\\n else:\\n raise ValueError(\\\"no close bracket for %s found after %s\\\" % (name,repr(xmltext[cursor: cursor+20])))\\n # is it a close bracket?\\n elif xmltext[nextopenbracket+1]==\\\"/\\\":\\n #print \\\"found close bracket\\\", repr(xmltext[nextopenbracket:nextopenbracket+20])\\n nextclosebracket = xmltext.find(\\\">\\\", nextopenbracket)\\n if nextclosebracket<nextopenbracket:\\n raise ValueError(\\\"unclosed close tag %s\\\" % repr(xmltext[nextopenbracket: nextopenbracket+20]))\\n closetagcontents = xmltext[nextopenbracket+2: nextclosebracket]\\n closetaglist = closetagcontents.split()\\n #if len(closetaglist)!=1:\\n #print closetagcontents\\n #raise ValueError, \\\"bad close tag format %s\\\" % repr(xmltext[nextopenbracket: nextopenbracket+20])\\n # name should match\\n closename = closetaglist[0]\\n #if verbose: print \\\"closetag name is\\\", closename\\n if name!=closename:\\n prefix = xmltext[:cursor]\\n endlinenum = len(prefix.split(\\\"\\\\n\\\"))\\n prefix = xmltext[:startingat]\\n linenum = len(prefix.split(\\\"\\\\n\\\"))\\n raise ValueError(\\\"at lines %s...%s close tag name doesn't match %s...%s %s\\\" %(\\n linenum, endlinenum, repr(name), repr(closename), repr(xmltext[cursor: cursor+100])))\\n remainder = xmltext[cursor:nextopenbracket]\\n if remainder:\\n #if verbose: print \\\"remainder\\\", repr(remainder)\\n L.append(remainder)\\n cursor = nextclosebracket+1\\n #print \\\"for\\\", name, \\\"found close tag\\\"\\n docontents = None # done\\n # otherwise we are looking at a new tag, recursively parse it...\\n # first record any intervening content\\n else:\\n remainder = xmltext[cursor:nextopenbracket]\\n if remainder:\\n L.append(remainder)\\n #if verbose:\\n # #print \\\"skipping\\\", repr(remainder)\\n # #print \\\"--- recursively parsing starting at\\\", xmltext[nextopenbracket:nextopenbracket+20]\\n (parsetree, cursor) = parsexml0(xmltext, startingat=nextopenbracket, toplevel=None, entityReplacer=entityReplacer)\\n if parsetree:\\n L.append(parsetree)\\n # maybe should check for trailing garbage?\\n # toplevel:\\n # remainder = xmltext[cursor:].strip()\\n # if remainder:\\n # raise ValueError, \\\"trailing garbage at top level %s\\\" % repr(remainder[:20])\\n if ContentList:\\n if entityReplacer: ContentList = entityReplacer(ContentList)\\n t = (NameString, AttDict, ContentList, ExtraStuff)\\n return (t, cursor)\",\n \"def analysis_to_subword_dicts(ana):\\n return map(pairs_to_dict, chunk_subwords(analysis_to_pairs(ana)))\",\n \"def _parse_xml(self):\\n self.properties = {}\\n pages = self.root.findall('page')\\n self.pages = {} \\n\\n for page_num, page in enumerate(pages): \\n\\n _, _ , width, height = page.attrib[\\\"bbox\\\"].split(\\\",\\\")\\n width, height = float(width), float(height)\\n \\n page_object = {\\\"page\\\": page_num + 1 , \\\"width\\\": width, \\\"height\\\": height} \\n lines = self.root.findall('page[@id=\\\\'{}\\\\']/textbox/textline'.format(page_num+1)) \\n print(\\\"{} Number of Lines in Page {}\\\".format(len(lines), page_num))\\n \\n self.bbox = {'x1': [] , 'y1':[], 'x2':[], 'y2':[]}\\n textlines = self.root.findall('page[@id=\\\\'{}\\\\']/textbox/textline'.format(page_num+1)) \\n textlines = sorted(textlines, key= lambda x: -float(x.attrib['bbox'].split(',')[3]))\\n \\n \\n line_objects = []\\n for idx, item in enumerate(textlines):\\n item_props = self._extract_textline_properties(item)\\n bbox = item.attrib['bbox'].split(',')\\n item_props[\\\"x0\\\"] = Decimal(bbox[0])\\n item_props[\\\"x1\\\"] = Decimal(bbox[2])\\n item_props[\\\"y0\\\"] = Decimal(bbox[1])\\n item_props[\\\"y1\\\"] = Decimal(bbox[3])\\n item_props[\\\"top\\\"] = Decimal(height - float(bbox[3]))\\n item_props[\\\"bottom\\\"] = Decimal(height - float(bbox[1]))\\n\\n line_objects.append(item_props)\\n page_object[\\\"lines\\\"] = line_objects\\n \\n \\n others = [] \\n# for key in [\\\"rect\\\", \\\"figure\\\", \\\"layout/textgroup\\\", \\\"curve\\\"]: \\n for key in [\\\"curve\\\", \\\"rect\\\", \\\"figure\\\"]: \\n other_objs = self.root.findall('page[@id=\\\\'{}\\\\']/{}'.format(page_num+1, key)) \\n for idx, item in enumerate(other_objs):\\n \\n item_props = {\\\"type\\\": key}\\n# print(key, ET.tostring(item))\\n bbox = item.attrib['bbox'].split(',')\\n item_props[\\\"x0\\\"] = Decimal(bbox[0])\\n item_props[\\\"x1\\\"] = Decimal(bbox[2])\\n item_props[\\\"y0\\\"] = Decimal(bbox[1])\\n item_props[\\\"y1\\\"] = Decimal(bbox[3]) \\n item_props[\\\"top\\\"] = Decimal(height - float(bbox[3]))\\n item_props[\\\"bottom\\\"] = Decimal(height - float(bbox[1]))\\n others.append(item_props)\\n \\n page_object[\\\"others\\\"] = others\\n page = Page(page_object)\\n page_object[\\\"para\\\"] = page.para\\n page_object[\\\"plines\\\"] = page.lines\\n page_object[\\\"bigbox\\\"] = page.bigbox\\n page_object[\\\"components\\\"] = page.components\\n\\n self.pages[page_num+1] = page_object\",\n \"def __title_context_dict(data):\\n d = {}\\n if isinstance(data, str):\\n raw_data = __load_data(data)['data']\\n else:\\n raw_data = data['data']\\n for i in range(len(raw_data)):\\n title = raw_data[i]['title']\\n paragraphs = raw_data[i]['paragraphs']\\n text = []\\n for j in range(len(paragraphs)):\\n text.append(paragraphs[j]['context'])\\n context = ' '.join(text)\\n d[title] = context\\n return d\",\n \"def get_transcripts_from_youtube(youtube_id, settings, i18n):\\r\\n _ = i18n.ugettext\\r\\n\\r\\n utf8_parser = etree.XMLParser(encoding='utf-8')\\r\\n\\r\\n youtube_text_api = copy.deepcopy(settings.YOUTUBE['TEXT_API'])\\r\\n youtube_text_api['params']['v'] = youtube_id\\r\\n data = requests.get('http://' + youtube_text_api['url'], params=youtube_text_api['params'])\\r\\n\\r\\n if data.status_code != 200 or not data.text:\\r\\n msg = _(\\\"Can't receive transcripts from Youtube for {youtube_id}. Status code: {status_code}.\\\").format(\\r\\n youtube_id=youtube_id,\\r\\n status_code=data.status_code\\r\\n )\\r\\n raise GetTranscriptsFromYouTubeException(msg)\\r\\n\\r\\n sub_starts, sub_ends, sub_texts = [], [], []\\r\\n xmltree = etree.fromstring(data.content, parser=utf8_parser)\\r\\n for element in xmltree:\\r\\n if element.tag == \\\"text\\\":\\r\\n start = float(element.get(\\\"start\\\"))\\r\\n duration = float(element.get(\\\"dur\\\", 0)) # dur is not mandatory\\r\\n text = element.text\\r\\n end = start + duration\\r\\n\\r\\n if text:\\r\\n # Start and end should be ints representing the millisecond timestamp.\\r\\n sub_starts.append(int(start * 1000))\\r\\n sub_ends.append(int((end + 0.0001) * 1000))\\r\\n sub_texts.append(text.replace('\\\\n', ' '))\\r\\n\\r\\n return {'start': sub_starts, 'end': sub_ends, 'text': sub_texts}\",\n \"def variable_dicts(self):\\n \\n def get_variable_text(rtf_file):\\n \\\"Returns a list of variable_texts for each variable\\\"\\n st='Pos. = '\\n return rtf_file.split(st)[1:]\\n \\n def get_variable_name(variable_text):\\n st='Variable = '\\n b=variable_text.split(st)[1]\\n return b[b.find(' ')+1:b.find('\\\\t')]\\n \\n def find_pos(rtf):\\n a=rtf\\n b=a\\n return b[b.find(' ')+1:b.find('\\\\t')]\\n \\n def find_variable_label(rtf):\\n try:\\n a=rtf\\n b=a.split('Variable label = ')[1]\\n return b[b.find(' ')+1:b.find('\\\\\\\\par')]\\n except IndexError:\\n return None\\n \\n def find_variable_type(rtf):\\n if not 'This variable is ' in rtf: return ''\\n a=rtf\\n b=a.split('This variable is ')[1]\\n i1=b.find(' ')+1\\n i2=i1+b[i1:].find('}')\\n return b[i1:i2]\\n \\n def find_SPSS_measurement_level(rtf):\\n if not 'the SPSS measurement level is ' in rtf: return ''\\n a=rtf\\n b=a.split('the SPSS measurement level is ')[1]\\n i1=b.find(' ')+1\\n i2=i1+b[i1:].find('\\\\\\\\par')\\n return b[i1:i2]\\n \\n def find_SPSS_user_missing_values(rtf):\\n if not 'SPSS user missing values = ' in rtf: return dict()\\n a=rtf\\n d=a.split('SPSS user missing values = ')\\n if len(d)<2: return None\\n e=d[1]\\n i1=e.find(' ')+1\\n i2=i1+e[i1:].find('\\\\\\\\par')\\n f=e[i1:i2]\\n g=f.split(' ')\\n i=' '.join([g[0],g[2],g[4]])\\n return i\\n \\n def find_value_labels(rtf):\\n if not 'Value = ' in rtf: return dict()\\n a=rtf\\n d=a.split('Value = ')[1:]\\n z={}\\n for e in d:\\n value=e[e.find(' ')+1:e.find('\\\\t')]\\n value=float(value)\\n f=e.split('Label = ')[1]\\n label=f[f.find(' ')+1:f.find('\\\\\\\\par')]\\n z[value]=label\\n #print(z)\\n return z\\n \\n variable_texts=get_variable_text(self.rtf)\\n #pprint(variable_texts[0:2])\\n \\n result=[]\\n for variable_text in variable_texts:\\n d={'pos':find_pos(variable_text),\\n 'variable':get_variable_name(variable_text),\\n 'variable_label':find_variable_label(variable_text),\\n 'variable_type':find_variable_type(variable_text),\\n 'SPSS_measurement_level':find_SPSS_measurement_level(variable_text),\\n 'SPSS_user_missing_values':find_SPSS_user_missing_values(variable_text),\\n 'value_labels':find_value_labels(variable_text) \\n }\\n result.append(d)\\n \\n return result\",\n \"def xml_parser(xml_string):\\n def rec_parse(elements):\\n \\\"\\\"\\\"recursively add nodes to the dictionary\\\"\\\"\\\"\\n node = {\\\"name\\\": elements.tag, \\\"children\\\": []}\\n for elem in elements:\\n node[\\\"children\\\"].append(rec_parse(elem))\\n if len(elements) > 0:\\n rec_parse.max_depth += 1\\n return node\\n\\n root = Et.fromstring(xml_string)\\n rec_parse.max_depth = 0\\n xml_dict = rec_parse(root)\\n print(xml_dict, \\\", \\\", rec_parse.max_depth)\\n\\n return xml_dict, rec_parse.max_depth\",\n \"async def parse(self, raw: str) -> dict:\",\n \"def to_xml_dict(self):\\n root = super(MultiMonoComposer, self).to_xml_dict()\\n\\n # same as mono, except that <r:monograph> is now <r:monographVolume>\\n root[\\\"r:import\\\"] = MultiMonoComposer._swap_keys(\\n root[\\\"r:import\\\"],\\n \\\"r:monograph\\\",\\n \\\"r:monographVolume\\\"\\n )\\n\\n # same as mono, except that <r:title> is now <r:monographTitle>\\n mono_volume = root[\\\"r:import\\\"][\\\"r:monographVolume\\\"]\\n mono_volume[\\\"r:titleInfo\\\"] = MultiMonoComposer._swap_keys(\\n mono_volume[\\\"r:titleInfo\\\"],\\n \\\"r:title\\\",\\n \\\"r:monographTitle\\\"\\n )\\n\\n title_info = root[\\\"r:import\\\"][\\\"r:monographVolume\\\"][\\\"r:titleInfo\\\"]\\n if self.volume_title:\\n title_info[\\\"r:volumeTitle\\\"] = self.volume_title\\n\\n return root\",\n \"def parse_string(self, data):\\n from pyexpat import ExpatError\\n\\n from openff.toolkit.utils.exceptions import SMIRNOFFParseError\\n\\n # Parse XML file\\n try:\\n smirnoff_data = xmltodict.parse(data, attr_prefix=\\\"\\\")\\n return smirnoff_data\\n except ExpatError as e:\\n raise SMIRNOFFParseError(str(e))\",\n \"def _parse_subdefinitions(subdefinitions):\\r\\n parsed = {'definition': subdefinitions['difino']}\\r\\n parsed['examples'] = [\\r\\n {\\r\\n 'example': example['ekzemplo']\\r\\n } for example in subdefinitions['ekzemploj']]\\r\\n return parsed\",\n \"def parse(file, time_i, title_i_start, title_i_end, final_time_end):\\n file_iter = iter(file)\\n tokens = next(file_iter).split()\\n try:\\n while True:\\n time_start = tokens[time_i]\\n if not time_string(time_start):\\n print('error: could not interpret \\\\'{}\\\\' as time'\\n ''.format(time_start))\\n sys.exit(1)\\n chapter_string = ' '.join(tokens[title_i_start:title_i_end])\\n tokens = next(file_iter).split()\\n yield {\\n 'time_start': time_start,\\n 'time_end': tokens[time_i],\\n 'chapter_string': chapter_string\\n }\\n except StopIteration:\\n yield {\\n 'time_start': time_start,\\n 'time_end': final_time_end,\\n 'chapter_string': chapter_string\\n }\",\n \"def _decode_dictionary(data, sub=False):\\n\\n main_dict = {}\\n\\n if sub:\\n # We are decoding a sub-dictionary, XML is assumed compliant\\n tree = data\\n else:\\n fixed_data = XML_Fix(data)\\n tree = ET.fromstring(fixed_data) \\n\\n for child in tree:\\n for pair in child:\\n if len(pair) == 2:\\n key = _decode_value(pair[0].attrib['Value'])\\n val = None\\n if 'Type' in pair[1].attrib: \\n collection_type = pair[1].attrib['Type']\\n if collection_type == 'elsystem.collections.dictionary': # Handle sub-dictionary\\n val = _decode_dictionary(data=pair[1], sub=True)\\n elif collection_type == 'elsystem.collections.vector': # Handle sub-vector\\n val = _decode_vector(data=pair[1], sub=True)\\n else: # Handle normal pair\\n val = _decode_value( pair[1].attrib['Value'] )\\n main_dict[key] = val\\n\\n return main_dict\",\n \"def gettext(xmltext):\\n tree = ET.ElementTree(ET.fromstring(xmltext))\\n root = tree.getroot()\\n title = root.find('title')\\n result = title.text\\n for element in root.iterfind(\\\".//text/*\\\"):\\n result = result + \\\" \\\" + element.text\\n return result\",\n \"def xml_to_otr(xml_file, destination, speakers=False):\\n\\n tree = etree.parse(xml_file)\\n root = tree.getroot()\\n\\n # Check xml version and force encoding for compatibility purpose\\n if(len(root.findall(\\\".//word[@value]\\\")) > 0):\\n version = 'v2'\\n encoding = 'utf-8'\\n word_selector = 'value'\\n spk_selector = 'speaker'\\n gender_selector = 'gender'\\n elif(len(root.findall(\\\".//word[@sel]\\\")) > 0):\\n version = 'v1'\\n encoding = 'iso-8859-1'\\n word_selector = 'sel'\\n spk_selector = 'locuteur'\\n gender_selector = 'sexe'\\n else:\\n return []\\n\\n previous_speaker = None\\n previous_gender = None\\n speaker_turns = []\\n speaker_sentences = []\\n\\n output = codecs.open(destination, 'w', encoding = 'utf-8') if destination else sys.stdout\\n\\n try:\\n\\n json_output = {}\\n\\n html = \\\"\\\";\\n for i, sentence in enumerate(root):\\n if(i != 0):\\n html += \\\"</p>\\\";\\n\\n html += \\\"<p>\\\";\\n\\n speaker = sentence.attrib[spk_selector]\\n words = []\\n\\n if speakers:\\n # Speaker change\\n if(speaker != previous_speaker):\\n html += \\\"<p><strong>Locuteur {} :</strong> \\\".format(speaker);\\n else:\\n html += \\\"<p>\\\";\\n else:\\n html += \\\"<p>\\\";\\n\\n nb_words = len(sentence)\\n for j, word in enumerate(sentence):\\n value = word.attrib[word_selector]\\n space_after = \\\" \\\"\\n if(value.endswith(\\\"'\\\") or \\\\\\n (j+1 < nb_words and sentence[j+1].attrib[word_selector].startswith('-'))):\\n space_after=\\\"\\\"\\n\\n html += \\\"<span class=\\\\\\\"word\\\\\\\" data-start=\\\\\\\"{start}\\\\\\\">{value}{space}</span>\\\".format(start=word.attrib['start'], value=value, space=space_after)\\n\\n previous_speaker = speaker\\n previous_gender = sentence.attrib[gender_selector]\\n\\n\\n html += \\\"</p>\\\"\\n #import pprint; pprint.pprint(html)\\n\\n json_output['text'] = html\\n json_output['media_source'] = \\\"\\\"\\n print(json.dumps(json_output), file=output)\\n\\n\\n finally:\\n if output is not sys.stdout:\\n output.close()\",\n \"def content_for_regtext(instruction_xml):\\n label_parts, amdpar = label_amdpar_from(instruction_xml)\\n xml = find_section(amdpar)\\n\\n def parse_regtext():\\n sections = build_from_section(label_parts[0], xml)\\n if sections:\\n return sections[0]\\n\\n return xml, parse_regtext\",\n \"def extract_subjects(subject_info_xml, primary_str):\\n subject_info_pyxb = deserialize_subject_info(subject_info_xml)\\n subject_info_tree = d1_common.cert.subject_info.gen_subject_info_tree(\\n subject_info_pyxb, primary_str\\n )\\n return subject_info_tree.get_subject_set()\",\n \"def _meta_dict(self, node):\\n meta = {n: self._text(node, n) for n in ('source', 'date', 'key')}\\n meta.update(self.infon_dict(node))\\n return meta\",\n \"def getSubfield(h, field, Lsubs):\\n\\td = {}\\t\\n\\tfor k in Lsubs:\\n\\t\\ttheElement = h.documentElement.getElementsByTagName(field)[0]\\n\\t\\td[k] = str(theElement.getAttribute(k))\\n\\treturn d\",\n \"def parseTitle(string):\\n replacements={\\n 'PT':'p_{T} [GeV]'\\n ,'MET':'E_{T}^{miss} [GeV]'\\n ,'HT':'H_{T} [GeV]'\\n ,'HTG':'H_{T}^{gen} [GeV]'\\n ,'MET':'E_{T}^{miss} [GeV]'\\n ,'TREFF':'Trigger Effciency'\\n }\\n return reduce(lambda x, y: x.replace(y, replacements[y]), replacements,string)\",\n \"def parseSkillDesc():\\n\\ttry:\\n\\t\\thandle = app.OpenTextFile(app.GetLocalePath() + \\\"/skilldesc.txt\\\")\\n\\t\\tcount = app.GetTextFileLineCount(handle)\\n\\texcept IOError:\\n\\t\\tchat.AppendChat(1, \\\"Could not load \\\" + app.GetLocalePath() + \\\"/skilldesc.txt\\\")\\n\\t\\treturn\\n\\t\\n\\tskill_map = {}\\n\\n\\tfor i in range(count):\\n\\t\\tline = app.GetTextFileLine(handle, i)\\n\\t\\tif str(line).count(\\\"\\\\t\\\") >= 21:\\n\\t\\t\\tSkillData = str(line).split(\\\"\\\\t\\\")\\n\\t\\t\\tskill_map[int(SkillData[0])] = {\\n\\t\\t\\t\\t\\\"class\\\":str(SkillData[1]).lower(),\\n\\t\\t\\t\\t\\\"name\\\":str(SkillData[2]),\\n\\t\\t\\t\\t\\\"icon\\\":str(SkillData[12]),\\n\\t\\t\\t\\t}\\n\\t\\n\\tapp.CloseTextFile(handle)\\n\\t\\n\\treturn skill_map\",\n \"def getTextUnits_old(filename):\\n doc = Document(filename)\\n units = list()\\n \\n unit_tracker = defaultdict(int)\\n \\n non_units = [\\\"name:\\\", \\\"date:\\\", \\\"date\\\", \\\"series\\\", \\\"transcriber\\\", \\\"thesis:\\\", \\\"currently:\\\", \\\"note\\\", \\\"comment\\\", \\\"grandparents:\\\", \\\"transcript:\\\", \\\"note:\\\"]\\n\\n ongoing_answer = \\\"\\\"\\n\\n \\n\\n # iterate over all paragraphs to get text units\\n for para in doc.paragraphs:\\n paragraph = para.text\\n # ensure it is not an empty line\\n if len(paragraph.strip())>0:\\n # get first word\\n formatted_para = paragraph.lstrip()\\n unit_type = formatted_para.partition(' ')[0]\\n # in case it is in the format of e.g 'George Salton:'\\n \\n # e.g AJ:, B.\\n m = re.compile('[A-Z][A-Z]?[.|:|-]')\\n type1 = m.match(unit_type)\\n\\n # e.g [WJ]\\n n = re.compile('\\\\[[A-Z][A-Z]\\\\]')\\n typer2= n.match(unit_type)\\n\\n # timestamp e.g 15:01:27\\n o = re.compile('[0-9]?[0-9]:[0-9][0-9]:[0-9][0-9]')\\n type3 = o.match(unit_type) \\n \\n \\n \\n\\n\\n # else parse them according to formatting guidelines\\n if (\\\"Question:\\\" in unit_type or\\n type1 or\\n \\\"Answer:\\\" in unit_type or \\n typer2 or\\n type3):\\n\\n # check if there was an ongoing paragraph\\n #units.append({'unit': paragraph})\\n \\n if ongoing_answer: \\n units.append({'unit': ongoing_answer})\\n\\n # reset it\\n ongoing_answer = \\\"\\\"\\n ongoing_answer += paragraph\\n \\n # update tracker\\n unit_tracker[unit_type] += 1\\n\\n elif (unit_type.endswith(':') and\\n unit_type.lower() not in non_units and\\n unit_type[:-1].isalpha()):\\n \\n \\n units.append({'unit': paragraph})\\n # update tracker\\n unit_tracker[unit_type] += 1\\n \\n \\n # backup method,in case it is in the format of e.g 'George Salton:'\\n elif len(paragraph.split()) > 3:\\n backup_type = paragraph.split()[1]\\n backup_two = paragraph.split()[2]\\n\\n if ((':' in backup_type or backup_type.lower() not in non_units) or\\n (':' in backup_two or backup_two.lower() not in non_units)): \\n \\n if ((paragraph.strip()[0].islower() and len(paragraph.strip()) > 5) or (paragraph.strip()[-1] in ['.','!','?'])) and len(units) >0:\\n units[-1]['unit']=units[-1]['unit']+ ' '+paragraph\\n # update tracker\\n unit_tracker[unit_type] += 1\\n else:\\n units.append({'unit':paragraph})\\n unit_tracker[unit_type] += 1\\n # if it is none of these cases, maybe there is an ongoing answer\\n \\n elif (ongoing_answer and ongoing_answer != paragraph):\\n \\n if not any(non_unit in paragraph.lower() for non_unit in non_units):\\n ongoing_answer += paragraph\\n else:\\n units.append({'unit':paragraph})\\n\\n if len(unit_tracker) < 2:\\n return []\\n \\n return units\",\n \"def _convert_tags_to_dict(text_list_tags):\\n return OrderedDict([re.findall(r\\\"\\\"\\\"\\\\s*_(\\\\w+)\\\\s+(.+?)\\\\s*$\\\"\\\"\\\", row)[0] for row in text_list_tags])\",\n \"def _parse_sub(self, parsetree, text, fpos=0):\\r\\n curr = 0\\r\\n for match in self._reSubstitution.finditer(text):\\r\\n start = match.start()\\r\\n if start > curr:\\r\\n parsetree.append((\\\"str\\\", self._reComment.sub('', text[curr:start])))\\r\\n\\r\\n if match.group(\\\"sub\\\") is not None:\\r\\n if not match.group(\\\"end\\\"):\\r\\n raise TemplateSyntaxError(\\\"Missing closing tag '%s' for '%s'.\\\" \\r\\n % (self._sub_end, match.group()), self._errpos(fpos+start))\\r\\n if len(match.group(\\\"sub\\\")) > 0:\\r\\n self._testexpr(match.group(\\\"sub\\\"), fpos+start)\\r\\n parsetree.append((\\\"sub\\\", match.group(\\\"sub\\\")))\\r\\n else:\\r\\n assert(match.group(\\\"escsub\\\") is not None)\\r\\n if not match.group(\\\"escend\\\"):\\r\\n raise TemplateSyntaxError(\\\"Missing closing tag '%s' for '%s'.\\\"\\r\\n % (self._subesc_end, match.group()), self._errpos(fpos+start))\\r\\n if len(match.group(\\\"escsub\\\")) > 0:\\r\\n self._testexpr(match.group(\\\"escsub\\\"), fpos+start)\\r\\n parsetree.append((\\\"esc\\\", self.escape, match.group(\\\"escsub\\\")))\\r\\n\\r\\n curr = match.end()\\r\\n\\r\\n if len(text) > curr:\\r\\n parsetree.append((\\\"str\\\", self._reComment.sub('', text[curr:])))\",\n \"def test_parse_metadata_0(self):\\n data = ET.parse(\\\"data/metadata_0.xml\\\")\\n data_str = ET.tostring(data.getroot())\\n\\n dict = tesse_ros_bridge.utils.parse_metadata(data_str)\\n self.assertEqual(dict['position'], [-5.692576, 2.499105, 10.63836])\\n self.assertEqual(dict['quaternion'], [0, 0.5372996, 0, 0.8433914])\\n self.assertEqual(dict['velocity'], [0, -0.0004944276, 0])\\n self.assertEqual(dict['ang_vel'], [0, 0, 0])\\n self.assertEqual(dict['acceleration'], [0, 0.001516496, 0])\\n self.assertEqual(dict['ang_accel'], [0, 0, 0])\\n self.assertEqual(dict['time'], 7.935)\\n self.assertEqual(dict['collision_status'], False)\",\n \"def getSubtitlesContainer(self):\\n self.subtitleURLContainer = \\\"\\\"\\n\\n self.subtitleURLContainer += self.parametersDict['PreURL']\\n\\n for parameters in self.parametersDict:\\n if parameters != \\\"PreURL\\\":\\n self.subtitleURLContainer += \\\"&\\\"\\n self.subtitleURLContainer += parameters\\n self.subtitleURLContainer += \\\"=\\\"\\n self.subtitleURLContainer += self.parametersDict[parameters]\\n pass\",\n \"def tracktorDeserialize(path, titles=None):\\n tree = ET.parse(path)\\n root = tree.getroot()\\n tracks = {}\\n for entry in root.find(\\\"COLLECTION\\\").iter(\\\"ENTRY\\\"):\\n track = Track()\\n track.name = entry.attrib[\\\"TITLE\\\"]\\n track.path = entry.find(\\\"LOCATION\\\").attrib[\\\"FILE\\\"][:-4] #Removing .mp3\\n cues = [cue for cue in entry.iter(\\\"CUE_V2\\\") if cue.attrib[\\\"NAME\\\"] != \\\"AutoGrid\\\"]\\n track.features[\\\"Cues\\\"] = Signal([cue.attrib[\\\"NAME\\\"][:7] for cue in cues],\\n times=[float(cue.attrib[\\\"START\\\"]) / 1000 for cue in cues],\\n sparse=True)\\n tracks[track.path] = track\\n if titles:\\n for t in titles:\\n if t in tracks:\\n yield tracks[t]\\n else:\\n print(t, \\\"not in collection\\\")\\n dummytrack = Track()\\n dummytrack.features[\\\"Cues\\\"] = Signal(times=[])\\n yield dummytrack\\n # return [tracks[t] if t in tracks else Track() for t in titles]\\n else:\\n return tracks.values()\",\n \"def parse_data(self):\\n\\n msg = self.xml['dom'].childNodes[0]\\n self.data = xml_to_dicts(msg, False)\\n\\n # Get some metadata together\\n self.id = \\\"%s:%s\\\" % (self.data['src']['name']['#cdata'], self.data['src']['id']['#cdata'])\\n self.temp = self.data['tmpr']['#cdata']\\n self.watts = self.data['ch1']['watts']['#cdata']\\n\\n # Time - CurrentCost and local\\n self.date = {}\\n self.date['cc'] = [ int(self.data['date'][k]['#cdata']) for k in ('dsb','hr','min','sec') ]\\n self.date['now'] = localtime()\",\n \"def xml_to_json(xml_file, destination):\\n\\n tree = etree.parse(xml_file)\\n root = tree.getroot()\\n\\n # Check xml version and force encoding for compatibility purpose\\n if(len(root.findall(\\\".//word[@value]\\\")) > 0):\\n version = 'v2'\\n encoding = 'utf-8'\\n word_selector = 'value'\\n spk_selector = 'speaker'\\n gender_selector = 'gender'\\n elif(len(root.findall(\\\".//word[@sel]\\\")) > 0):\\n version = 'v1'\\n encoding = 'iso-8859-1'\\n word_selector = 'sel'\\n spk_selector = 'locuteur'\\n gender_selector = 'sexe'\\n else:\\n return []\\n\\n previous_speaker = None\\n previous_gender = None\\n speaker_turns = []\\n speaker_sentences = []\\n\\n output = codecs.open(destination, 'w', encoding = 'utf-8') if destination else sys.stdout\\n\\n try:\\n\\n for sentence in root:\\n speaker = sentence.attrib[spk_selector]\\n words = []\\n\\n # Speaker change\\n if(previous_speaker is not None and speaker != previous_speaker):\\n speaker_turns.append({\\n \\\"id\\\":previous_speaker,\\n \\\"gender\\\":previous_gender,\\n # No speaker id score for now in xml\\n \\\"score\\\": None,\\n \\\"sentences\\\":speaker_sentences\\n })\\n speaker_sentences = []\\n\\n for word in sentence:\\n json_word = {\\n \\\"start\\\": word.attrib['start'],\\n \\\"word\\\": word.attrib[word_selector],\\n # No named entity support for now\\n \\\"ne\\\": None\\n }\\n words.append(json_word)\\n\\n speaker_sentences.append(words)\\n\\n previous_speaker = speaker\\n previous_gender = sentence.attrib[gender_selector]\\n\\n\\n # Add the last sentence and last speaker turn\\n speaker_turns.append({\\n \\\"id\\\":previous_speaker,\\n \\\"gender\\\":previous_gender,\\n # No speaker id score for now in xml\\n \\\"score\\\": None,\\n \\\"sentences\\\":speaker_sentences\\n })\\n\\n\\n #import pprint; pprint.pprint(speaker_turns)\\n\\n json_output = {}\\n json_output['speaker_turns'] = speaker_turns\\n print(json.dumps(json_output), file=output)\\n\\n\\n finally:\\n if output is not sys.stdout:\\n output.close()\",\n \"def get_info_list(info_string, course):\\n info_list = []\\n split_on_newline = info_string.split(\\\"\\\\n\\\")\\n for elem in split_on_newline:\\n split = elem.split(\\\": \\\")\\n for s in split:\\n info_list.append(s)\\n info_list = info_list[1:-1]\\n info_tags = [\\n 'session', 'school', 'credits', 'level', 'offered',\\n 'visiting_students', 'erasmus_students',\\n ]\\n i = 0\\n for info_tag in info_tags:\\n course[info_tag] = new_dict(\\n info_list[i] + ': ', info_list[i + 1])\\n i += 2\\n return course\",\n \"def parseTSName(tsn):\\n parsedName = [int(nc.split(\\\"=\\\")[1]) for nc in tsn.split(\\\".\\\")[0].split(\\\"/\\\")[-1].split(\\\"_\\\")]\\n return {\\\"ti\\\": parsedName[0], \\\"intervalLen\\\": parsedName[1] - parsedName[0], \\\"sensor\\\": parsedName[2]}\",\n \"def transform_string_to_dictionary(data_text: str) -> Dict[str, float]:\\n # TODO: create an empty population dictionary\\n # TODO: iterate through each line of the data set\\n # TODO: extract the ordered pair on this line\\n # the ordered pair has the format:\\n # (Date, population count in thousands of persons)\\n # TODO: extract the dat and store it as a string\\n # TODO: convert the population count to a float and store it\\n # TODO: add the new key-value pair to the dictionary where\\n # the key is the date and the population is the value\\n # TODO: return the population dictionary\",\n \"def buildDictionaryFromXML(self, siteelement, elementstring):\\n variablename = \\\"\\\"\\n try:\\n if len(siteelement.find(elementstring).findall(\\\"entry\\\")) > 0:\\n variablename = {}\\n for entry in siteelement.find(elementstring).findall(\\\"entry\\\"):\\n variablename[entry.get(\\\"key\\\")] = entry.text\\n else:\\n return None\\n except:\\n return None\\n return variablename\",\n \"def __read_composite_template(self, text:str, start:int, end_marker:str) -> dict:\\n\\t\\tbind = {}\\n\\t\\tkey = None\\n\\t\\tleft = start\\n\\t\\ttry: right = text.rindex(end_marker)\\n\\t\\texcept ValueError: right=len(text)\\n\\t\\tsuffix = text[right+len(self.END_ASSY):]\\n\\t\\tassert suffix=='' or suffix.isspace()\\n\\t\\tfor match in re.finditer(r'<\\\\?(.*?)\\\\?>', text):\\n\\t\\t\\tbind[key] = text[left:match.start()].strip()\\n\\t\\t\\tkey = match.group(1).strip()\\n\\t\\t\\tleft = match.end()\\n\\t\\tbind[key] = text[left:right].strip()\\n\\t\\treturn bind\",\n \"def scene_to_text(scenes):\\n scene_text_dict = []\\n scene_text_list = []\\n for i, scene in enumerate(scenes):\\n if len(scene['frame_data']) == 0:\\n break\\n scene_image = Image.fromarray(scene['frame_data'])\\n str_text = pytesseract.image_to_string(scene_image)\\n #list_text = list(filter(('').__ne__, re.split(\\\" |\\\\n|, ｜. |:|.\\\\n|\\\\x0c\\\", str_text)))\\n list_text = list(filter(('').__ne__, re.split(\\\" |\\\\n\\\", str_text)))\\n bag_of_word = collections.Counter(list_text)\\n scene_text_dict.append(\\n {'start': scene['start'], \\n 'end': scene['end'], \\n 'bag_of_word': dict(bag_of_word)\\n })\\n scene_text_list.append(list_text)\\n return scene_text_dict, scene_text_list\",\n \"def doc_title_table(title_file):\\n with open(title_file , 'r') as f :\\n lines = f.readlines()\\n raw_text = \\\"\\\".join(l for l in lines)\\n left_idx_num = [ m.end(0) for m in re.finditer(r\\\"<num>\\\",raw_text)]\\n right_idx_num = [ m.start(0) for m in re.finditer(r\\\"</num>\\\",raw_text)]\\n\\n left_idx_title = [ m.end(0) for m in re.finditer(r\\\"<title>\\\",raw_text)]\\n right_idx_title = [ m.start(0) for m in re.finditer(r\\\"</title>\\\",raw_text)]\\n\\n docs_title_dict = {}\\n for i in range(len(left_idx_num)):\\n docs_title_dict[raw_text[left_idx_num[i]+1:right_idx_num[i]-1]] = raw_text[left_idx_title[i]+1:right_idx_title[i]-1]\\n return docs_title_dict\",\n \"def setup_parser(self) -> Dict[str, Any]:\\n\\n\\t# % year,doy, RH(m), Month, day, azimuth(deg),freq, satNu, LSP amp,pk2noise,UTC(hr) \\n\\t# 2021 9 4.888 1 9 225.3 1 2 9.51 3.23 10.08\\n\\t# 2021 9 5.018 1 9 181.3 1 15 7.79 2.84 15.67\\n\\t# 2021 9 5.123 1 9 185.4 1 16 6.27 3.01 0.68\\n #----+----0----+----1----+----2----+----3----+----4----+----5----+----6----+----7\\n return dict(\\n skip_header=1,\\n names=(\\n \\\"year\\\",\\n \\\"doy\\\",\\n \\\"reflection_height\\\",\\n \\\"month\\\",\\n \\\"day\\\",\\n \\\"azimuth\\\",\\n \\\"frequency\\\",\\n \\\"satellite\\\",\\n \\\"amplitude\\\",\\n \\\"peak2noise\\\",\\n \\\"hour\\\",\\n ),\\n dtype=(\\\"f8\\\", \\\"f8\\\", \\\"f8\\\", \\\"f8\\\", \\\"f8\\\", \\\"f8\\\", \\\"f8\\\", \\\"f8\\\", \\\"f8\\\", \\\"f8\\\", \\\"f8\\\"),\\n )\",\n \"def agline2(line):\\n \\n vals = {}\\n y = line.strip('\\\\n').split(',')\\n y.extend(y[0].strip('.MTS').split('_'))\\n \\n #print(y)\\n \\n x = ['movie', 'moviecode', 'offset', 'well', 'agmin', 'agsec', 'agdur', \\n 'agtype', 'agcomm', 'escmin', 'escsec', 'escdur', 'esctype', 'escbeh', \\n 'esccomm', 'gen', 'date', 'assay', 'fps', 'flyid', 'side', 'moviepart']\\n \\n z = zip(x, y)\\n\\n for item in z:\\n vals[item[0]] = item[1]\\n\\n return(vals)\",\n \"def xml_children_as_dict(node):\\n return dict((e.tag, e.text) for e in node)\",\n \"def _parseXmlInter(self, xml_str):\\n EOW = []\\n phones = []\\n explains = []\\n\\n root = ET.fromstring(xml_str)\\n\\n for explain_xml in root.iter(self.TAG_EXPLEIN):\\n\\n if len(explain_xml) > 0 and explain_xml[0].tag == self.TAG_POS: # 存在词性\\n explain = explain_xml[0].text + explain_xml[0].tail\\n\\n else:\\n if explain_xml.text == None:\\n continue\\n else:\\n explain = explain_xml.text\\n\\n explains.append(explain)\\n\\n for phone_xml in root.iter(self.TAG_PHONE):\\n if phone_xml.text == None:\\n continue\\n phones.append(phone_xml.text)\\n\\n EOW_xml = root.find(self.TAG_EOW)\\n if EOW_xml != None:\\n EOW = EOW_xml.text.split('|')\\n\\n return EOW, phones, explains\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5741043","0.56276953","0.55804926","0.54216254","0.5318582","0.5317567","0.53144175","0.53124976","0.53016436","0.5292441","0.52581465","0.5189917","0.51402706","0.5140158","0.51315385","0.5113792","0.51061213","0.5029709","0.50141513","0.5013694","0.5004582","0.49833387","0.49742106","0.49516615","0.49435478","0.49234658","0.49220994","0.48875117","0.4879956","0.48568577","0.48560366","0.4839201","0.48277372","0.48254815","0.4824599","0.48233593","0.48197263","0.4810844","0.47998703","0.47957173","0.4795568","0.47892883","0.47816104","0.47743723","0.47720686","0.47712782","0.4761366","0.4761215","0.47606894","0.47594976","0.4756616","0.47557727","0.47512004","0.47352263","0.47332668","0.47323993","0.4731107","0.47228968","0.471876","0.47172406","0.4713644","0.47115016","0.47056645","0.47053435","0.4698779","0.469797","0.46945816","0.46687528","0.46686143","0.46682552","0.46643123","0.46555406","0.46498516","0.4647703","0.46390927","0.46333903","0.46311274","0.46151412","0.46129078","0.46128422","0.4611415","0.4609441","0.46011817","0.4586228","0.45776623","0.45758018","0.4575154","0.45721322","0.45714334","0.45699736","0.45591652","0.45562932","0.45544532","0.45543593","0.4554137","0.45526075","0.45522052","0.4549938","0.45485058","0.45475972"],"string":"[\n \"0.5741043\",\n \"0.56276953\",\n \"0.55804926\",\n \"0.54216254\",\n \"0.5318582\",\n \"0.5317567\",\n \"0.53144175\",\n \"0.53124976\",\n \"0.53016436\",\n \"0.5292441\",\n \"0.52581465\",\n \"0.5189917\",\n \"0.51402706\",\n \"0.5140158\",\n \"0.51315385\",\n \"0.5113792\",\n \"0.51061213\",\n \"0.5029709\",\n \"0.50141513\",\n \"0.5013694\",\n \"0.5004582\",\n \"0.49833387\",\n \"0.49742106\",\n \"0.49516615\",\n \"0.49435478\",\n \"0.49234658\",\n \"0.49220994\",\n \"0.48875117\",\n \"0.4879956\",\n \"0.48568577\",\n \"0.48560366\",\n \"0.4839201\",\n \"0.48277372\",\n \"0.48254815\",\n \"0.4824599\",\n \"0.48233593\",\n \"0.48197263\",\n \"0.4810844\",\n \"0.47998703\",\n \"0.47957173\",\n \"0.4795568\",\n \"0.47892883\",\n \"0.47816104\",\n \"0.47743723\",\n \"0.47720686\",\n \"0.47712782\",\n \"0.4761366\",\n \"0.4761215\",\n \"0.47606894\",\n \"0.47594976\",\n \"0.4756616\",\n \"0.47557727\",\n \"0.47512004\",\n \"0.47352263\",\n \"0.47332668\",\n \"0.47323993\",\n \"0.4731107\",\n \"0.47228968\",\n \"0.471876\",\n \"0.47172406\",\n \"0.4713644\",\n \"0.47115016\",\n \"0.47056645\",\n \"0.47053435\",\n \"0.4698779\",\n \"0.469797\",\n \"0.46945816\",\n \"0.46687528\",\n \"0.46686143\",\n \"0.46682552\",\n \"0.46643123\",\n \"0.46555406\",\n \"0.46498516\",\n \"0.4647703\",\n \"0.46390927\",\n \"0.46333903\",\n \"0.46311274\",\n \"0.46151412\",\n \"0.46129078\",\n \"0.46128422\",\n \"0.4611415\",\n \"0.4609441\",\n \"0.46011817\",\n \"0.4586228\",\n \"0.45776623\",\n \"0.45758018\",\n \"0.4575154\",\n \"0.45721322\",\n \"0.45714334\",\n \"0.45699736\",\n \"0.45591652\",\n \"0.45562932\",\n \"0.45544532\",\n \"0.45543593\",\n \"0.4554137\",\n \"0.45526075\",\n \"0.45522052\",\n \"0.4549938\",\n \"0.45485058\",\n \"0.45475972\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.67018545"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":92981,"cells":{"query":{"kind":"string","value":"From subtitle dictionary function returns value."},"document":{"kind":"string","value":"def return_xml_dict_entry_value(self,dict_entry, dict_entry_position):\n\tvalue = self.subtitle_dict[dict_entry][dict_entry_position]\n\treturn value[0]"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def edx_get_subtitle(url, headers):\n \"\"\" or None if no subtitles are available \"\"\"\n try:\n jsonString = get_page_contents(url, headers)\n jsonObject = json.loads(jsonString)\n return edx_json2srt(jsonObject)\n except URLError as e:\n print('[warning] edX subtitles (error:%s)' % e.reason)\n return None\n except ValueError as e:\n print('[warning] edX subtitles (error:%s)' % e.message)\n return None","def edx_get_subtitle(url, headers):\n try:\n json_object = get_page_contents_as_json(url, headers)\n return edx_json2srt(json_object)\n except URLError as e:\n _print('[warning] edX subtitles (error:%s)' % e.reason)\n return None\n except ValueError as e:\n _print('[warning] edX subtitles (error:%s)' % e.message)\n return None","def get_subtitle(annotation, sub_duration, video_clip, seen_annotations):\n if len(annotation[\"text\"]) == 0:\n return None\n\n annotation_txt = calculate_needed_subtitle_height(annotation, seen_annotations, video_clip)\n\n txt_clip = TextClip(annotation_txt, color=\"white\", fontsize=70, font='Sans Serif')\n txt_clip = txt_clip.set_position((\"center\", get_subtitle_offset(annotation, seen_annotations, video_clip)))\n txt_clip = txt_clip.set_start(float(annotation[\"time\"]) / 1000.0)\n txt_clip = txt_clip.set_duration(sub_duration)\n\n return txt_clip","def extract_subtitle_track(path_to_mkv):\n handler = SubtitleHandler()\n with open(path_to_mkv, \"rb\") as fp:\n mkvparse.mkvparse(fp, handler)\n\n return handler.subs","def get_subtitles(self, index: int):\n\n match = self.re_subs[index - 1]\n start = convert_subs_time(match[1])\n end = convert_subs_time(match[2])\n subtitles = match[3]\n subtitles = clean_text(subtitles)\n\n return (subtitles, start, end)","def getSubtitleURL(self):\n\n # If it is a movie, we use this methodology -\n try:\n IndexingParameters = [\"subtitleUrls\", 0, \"url\"]\n TitleParamters = [\n \"catalogMetadata\", \"catalog\", \"title\", \"episodeNumber\"]\n subRequestObject = requests.get(self.subtitleURLContainer)\n\n parsedJsonObject = json.loads(str(subRequestObject.text))\n SubsURL = parsedJsonObject[IndexingParameters[0]][\n IndexingParameters[1]][IndexingParameters[2]]\n if self.title == \"Amazonsubtitles\":\n try:\n self.title = parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[2]] + \"_\" + str(\n parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[3]])\n except:\n pass\n\n return SubsURL\n\n except:\n pass\n pass","def get_subtitles(self, title):\n return library.subtitles.get_subtitle_url(title)","def __init__(self, subtitle=None):\n self.subtitle = subtitle\n if not self.subtitle:\n self.parse_subtitles()","def stat_subtitle(self, release_name, movie_dir):\n ret = {}\n for root_dir, child_folders, file_names in os.walk(movie_dir):\n for file_name in file_names:\n if not file_name.startswith(release_name):\n continue\n\n subtitle_info = get_subtitle_info(file_name)\n if not subtitle_info:\n continue\n\n if 'lang' not in subtitle_info:\n continue\n\n lang = subtitle_info['lang']\n if lang not in ret:\n ret[lang] = []\n\n ret[lang].append(file_name)\n\n # Sort result\n for lang in ret:\n ret[lang] = sorted(ret[lang])\n\n return ret","def get_subtitle_print(subs: List[Track]) -> List[str]:\n data = []\n if not subs:\n data.append(\"--\")\n for sub in subs:\n line_items = []\n\n # following sub.title tree checks and supports three different language and title scenarios\n # The second scenario is the recommended option to choose if you are open to choosing any\n # The third scenario should be used if you have nothing unique to state about the track\n # | Language | Track Title | Output |\n # | ------------ | ----------------------------- | --------------------------------------------- |\n # | es / Spanish | Spanish (Latin American, SDH) | - Spanish (Latin American, SDH), SubRip (SRT) |\n # | es / Spanish | Latin American (SDH) | - Spanish, Latin American (SDH), SubRip (SRT) |\n # | es / Spanish | None | - Spanish, SubRip (SRT) |\n language = pycountry.languages.get(alpha_2=sub.language).name\n if sub.title:\n if language.lower() in sub.title.lower():\n line_items.append(sub.title)\n else:\n line_items.append(f\"{language}, {sub.title}\")\n else:\n line_items.append(language)\n\n line_items.append(sub.format.replace(\"UTF-8\", \"SubRip (SRT)\"))\n\n line = \"- \" + \", \".join(line_items)\n data += [\n (\" \" + x if i > 0 else x)\n for i, x in enumerate(textwrap.wrap(line, 64))\n ]\n return data","def subtitle(self, txt):\n num = len(txt)\n ticks = \"-\" * num\n print(txt)\n print(ticks)","def update_transcript_info(ensembl_info, word, value):\n if \"transcript\" in word:\n if \"id\" in word:\n ensembl_info[\"ensembl_transcript_id\"] = value\n elif \"start\" in word:\n ensembl_info[\"transcript_start\"] = int(value)\n elif \"end\" in word:\n ensembl_info[\"transcript_end\"] = int(value)\n return ensembl_info","def convert_to_tvr_subtitle(df: pd.DataFrame) -> pd.DataFrame:\n\tpass","def get_subtitle_offset(annotation, seen_annotations, clip):\n if not annotation[\"time\"] in seen_annotations:\n return clip.h - SUBTILE_OFFSET\n else:\n return clip.h - SUBTILE_OFFSET * (seen_annotations[annotation[\"time\"]] + 1)","def get_subtitleinfo(fileFullName):\n sys.stdout.write(\"Requesting subtitle info...\\n\")\n\n #接口获取字幕信息\n response = requests.post(\n \"https://www.shooter.cn/api/subapi.php\",\n verify=False,\n params= {\n 'filehash': ComputeFileHash(fileFullName),\n 'pathinfo': os.path.realpath(fileFullName),\n 'format': 'json',\n 'lang': \"Chn\",\n },\n )\n #未找到字幕处理\n if response.text == u'\\xff':\n sys.stderr.write(\"Subtitle not found.\\n\")\n sys.exit(1)\n return response","def extract(self, json_str, sub_number):\n topic_dict = json.loads(json_str)\n # print(topic_dict)\n\n if ('children' not in topic_dict):\n raise RuntimeError('topic tree json data has no children.')\n\n sub_topic_title = topic_dict['standalone_title']\n\n # 1. sub: subject (math, physic)\n # 2. nb_main: main topic number (addition/subtraction, fraction, ...)\n # 3. nb_sub: sub topic number\n # 4. nb_video: video title number\n # 5. sub_topic_title:\n # 6. video_title:\n # 7. d1: text translation duration time\n # 8. d2: voice over, edit duration time\n # 9. d3: subtitle duration time\n # 10. d4: total duration time\n # 11. s1: start date\n # 12. s2: end date\n # 13. s3: elapsed date\n # 14. status:\n # 15. finished bool\n # 16. update bool\n # 17. new at 2017 bool\n # 18. video_url:\n # 19. id:\n\n video_idx=1\n retstr = ''\n for i in topic_dict['children']:\n if (i['kind'] == 'Video'):\n line_str = ' , {_nb_main}, {_nb_sub}, {_nb_video}, {_sub_topic_title}, {_video_title}, {_d1}, {_d2}, {_d3}, {_d4}, {_s1}, {_s2}, {_s3}, {_status}, , , , {_video_url}, {_id}\\n'.\\\n format(\n _nb_main=1,\n _nb_sub=sub_number,\n _nb_video=video_idx,\n _sub_topic_title=sub_topic_title,\n _video_title=i['title'],\n _d1='00:00:00', _d2='00:00:00',\n _d3='00:00:00', _d4='00:00:00',\n _s1='2017-05-01', _s2='2017-05-01', _s3=0,\n _status='not_started',\n _video_url=i['url'],\n _id=i['internal_id'])\n video_idx += 1\n retstr += line_str\n else:\n verbose_mes = '# Skip kind [{kind}]: {title}'.format(\n kind=i['kind'], title=i['title'])\n self.verbose_out(verbose_mes)\n\n return retstr","def get_captions(video_id):\n try:\n transcript = YouTubeTranscriptApi.get_transcript(video_id)\n \n #parse only string and remove the time of captions\n text = []\n for txt in transcript:\n text.append(txt['text'])\n return text\n except:\n text = \"No Captions\"\n return text","def to_srt(self, subtitles):\n \n srt_data = ''\n subtitle_num = self.start_index\n for subtitle in subtitles:\n subtitle_num += 1\n \n offset = self.start_time\n \n start_time = self._ms_to_time(subtitle['start_time'] + offset)\n end_time = self._ms_to_time(subtitle['end_time'] + offset)\n \n content = subtitle['content'].replace('<br>', ' ')\n \n srt_data += str(subtitle_num) + '\\r\\n'\n srt_data += '%s --> %s' % (start_time, end_time) + '\\r\\n'\n srt_data += content + '\\r\\n'\n srt_data += '\\r\\n'\n \n self.end_index = subtitle_num\n \n return srt_data","def extract_value(k, d, f=''):\n if k in d:\n if f != '':\n p = f(d[k])\n else:\n p = d[k]\n\n if type(p) == str:\n v = unicode_decode(p)\n else:\n v = p\n else:\n v = unicode_decode('')\n return v","def translator(dict):\n f = lambda match: dict.get(match.group(), match.group())\n return lambda expression: _word_pattern.sub(f,expression)","def get_movie_snippet(doc_id, data):\n doc_id = str(doc_id)\n return doc_id, data[doc_id]['Title'][0], data[doc_id]['Text'][:300]+'......'","def get_transcript(self, transcript_format='srt'):\r\n lang = self.transcript_language\r\n\r\n if lang == 'en':\r\n if self.sub: # HTML5 case and (Youtube case for new style videos)\r\n transcript_name = self.sub\r\n elif self.youtube_id_1_0: # old courses\r\n transcript_name = self.youtube_id_1_0\r\n else:\r\n log.debug(\"No subtitles for 'en' language\")\r\n raise ValueError\r\n\r\n data = Transcript.asset(self.location, transcript_name, lang).data\r\n filename = u'{}.{}'.format(transcript_name, transcript_format)\r\n content = Transcript.convert(data, 'sjson', transcript_format)\r\n else:\r\n data = Transcript.asset(self.location, None, None, self.transcripts[lang]).data\r\n filename = u'{}.{}'.format(os.path.splitext(self.transcripts[lang])[0], transcript_format)\r\n content = Transcript.convert(data, 'srt', transcript_format)\r\n\r\n if not content:\r\n log.debug('no subtitles produced in get_transcript')\r\n raise ValueError\r\n\r\n return content, filename, Transcript.mime_types[transcript_format]","def add_subtitles(media_id, req):\n\n media_hndl = media_map.get(media_id)\n if not media_hndl:\n raise FileNotFoundError('{} is not a registered media_id'.format(media_id))\n\n subfile = None\n if req.data:\n subfile = json.loads(req.data.decode('utf-8')).get('filename')\n if not subfile:\n raise AttributeError('No filename specified in the request')\n\n if not subfile:\n if not media_hndl.path:\n raise NotImplementedError(\n 'Subtitles are currently only supported for local media files')\n\n req = {\n 'type': 'request',\n 'action': 'media.subtitles.get_subtitles',\n 'args': {\n 'resource': media_hndl.path,\n }\n }\n\n try:\n subtitles = send_message(req).output or []\n except Exception as e:\n raise RuntimeError('Could not get subtitles: {}'.format(str(e)))\n\n if not subtitles:\n raise FileNotFoundError('No subtitles found for resource {}'.\n format(media_hndl.path))\n\n req = {\n 'type': 'request',\n 'action': 'media.subtitles.download',\n 'args': {\n 'link': subtitles[0].get('SubDownloadLink'),\n 'media_resource': media_hndl.path,\n 'convert_to_vtt': True,\n }\n }\n\n subfile = (send_message(req).output or {}).get('filename')\n\n media_hndl.set_subtitles(subfile)\n return {\n 'filename': subfile,\n 'url': get_remote_base_url() + '/media/subtitles/' + media_id + '.vtt',\n }","def is_subtitle(self):\n val = False\n if self.__dict__['codec_type']:\n if self.__dict__['codec_type'] == 'subtitle':\n val = True\n return val","def extract_subs_value(text):\n parts = text.split()\n value = float(parts[-1])\n\n return value","def __getitem__(self, index):\n\n frames = self.frames[index]\n caption = self.captions[index]\n assert len(frames.shape) == 3\n\n # Convert captions to indices and add BOS/EOS markers.\n parsed_caption = self.parse_caption(caption)\n parsed_caption = np.array(parsed_caption)\n return frames, parsed_caption","def test_get_subtitles(self):\n\n (subtitles, start, end) = self.sp.get_subtitles(INDEX)\n self.assertEqual(subtitles, INDEX_SUBTITLES, 'Check get_subtitles.')","def parseTitle(string):\n replacements={\n 'PT':'p_{T} [GeV]'\n ,'MET':'E_{T}^{miss} [GeV]'\n ,'HT':'H_{T} [GeV]'\n ,'HTG':'H_{T}^{gen} [GeV]'\n ,'MET':'E_{T}^{miss} [GeV]'\n ,'TREFF':'Trigger Effciency'\n }\n return reduce(lambda x, y: x.replace(y, replacements[y]), replacements,string)","def subtitle_header(slide, title: str):\n top = Inches(0.61)\n left = Inches(0.42)\n height = Inches(0.5)\n width = Inches(0.5)\n txt_box = slide.shapes.add_textbox(left, top, width, height)\n text_frame = txt_box.text_frame\n\n paragraph = text_frame.paragraphs[0]\n paragraph.text = title\n paragraph.font.bold = False\n paragraph.font.size = Pt(22)\n paragraph.font.name = 'Times New Roman'\n\n return slide","def get_time_intervals(subtitle, regex=r\"\\S+\"):\n # module webvtt only gets the line-captions, not individual words, so it's time for some regex!\n # The time corresponding to a word is when that word *starts*\n # words = (match.group(\"word\") for match in WORD_REGEX.finditer(subtitle))\n time_words = [\n (m.group(\"time1\") or m.group(\"time2\"), m.group(\"word1\") or m.group(\"word2\"))\n for m in TIME_WORD_REGEX.finditer(subtitle)\n ]\n # Incorrect format, which would lead to trouble zipping\n if len(time_words) == 0:\n return []\n times, words = zip(*time_words)\n # Quickly search lines starting from the end\n final_time = next(match.group(\"time\") for line in reversed(subtitle.split(\"\\n\")) for match in [re.search(FINAL_TIME_REGEX, line)] if match)\n # timestamps[i] is the time the word starts at if i is the index of the start of a word\n timestamps = {}\n word_indices = {}\n # Build search_str while computing time_stamps by adding one word and one space at a time\n search_str = ''\n words = list(words)\n last_time = 0\n for j, (word, time) in enumerate(zip(words, times)):\n i = len(search_str)\n time = parse_time(time)\n timestamps[i] = time\n if time - last_time > 10:\n search_str += '[ … ] '\n last_time = time\n word_indices[i] = j\n search_str += word + ' '\n i = len(search_str)\n timestamps[i] = final_time\n word_indices[i] = len(words)\n # Trim off the final space\n # Inconsistent capitalization, so just lowercase\n search_str = search_str[:-1].lower()\n for match in re.finditer(regex, search_str):\n start, end = match.span()\n start_index = max(i for i in timestamps if i<=start)\n end_index = min(i for i in timestamps if i>end)\n yield Interval(\n timestamps[start_index],\n timestamps[end_index],\n word_indices[start_index],\n word_indices[end_index],\n match.group(0)\n )","def extract_transcript(resp: str):\n if 'result' not in resp:\n raise ValueError({'Error non valid response from api: {}'.format(resp)})\n for line in resp.split(\"\\n\"):\n try:\n line_json = json.loads(line)\n out = line_json['result'][0]['alternative'][0]['transcript']\n return out\n except:\n continue","def get_words_with_end_times(subtitle_file_path):\n\n with open(subtitle_file_path) as subtitle_file:\n\n # Remove first 4 lines (containing meta information)\n for j in range(0, 4):\n subtitle_file.readline()\n\n text = subtitle_file.read()\n\n # Check if the subtitle file supports individual word times\n if text.find(\"<c>\") == -1:\n print(\"Individual word times are not supported for file: \" + subtitle_file_path)\n return None, None\n\n chunks = text.split(\" \\n\\n\") # split into chunks for easier data processing\n\n words = list()\n word_end_times = list()\n\n for chunk in chunks:\n chunk_lines = chunk.split(\"\\n\")\n words_line = chunk_lines[2]\n\n words_in_chunk = []\n word_end_times_in_chunk = []\n\n first_word_end_index = words_line.find(\"<\")\n if first_word_end_index != -1:\n first_word = words_line[\n 0:first_word_end_index] # get the first word (can't be found using method below)\n\n words_in_chunk = re.findall(\"<c> [\\S]*</c>\", words_line) # get all words\n words_in_chunk = [w[4:-4] for w in words_in_chunk] # strip <c> and <c/>\n\n word_end_times_in_chunk = re.findall(\"<\\d\\d:\\d\\d:\\d\\d.\\d\\d\\d>\", words_line) # get all word end times\n word_end_times_in_chunk = [t[1:-1] for t in word_end_times_in_chunk] # strip < and >\n else:\n # Only one word\n first_word = words_line\n\n last_time = chunk_lines[4][17:29] # end time for the last word\n\n words_in_chunk.insert(0, first_word)\n word_end_times_in_chunk.append(last_time)\n\n words.extend(words_in_chunk)\n word_end_times.extend(word_end_times_in_chunk)\n\n # For the last chunk we have to get the word end time from somewhere else\n first_line_in_last_chunk = chunks[-1].split(\"\\n\")[0]\n last_time = first_line_in_last_chunk[17:29]\n word_end_times.pop()\n word_end_times.append(last_time)\n\n if len(words) != len(word_end_times):\n print(\"Warning: word count does not match times count\")\n\n return words, word_end_times","def subjectReadForTitle(titles, title):\n # Try the title and also the 2 fields that result from splitting it on its\n # first space (if any).\n for t in set([title] + title.split(maxsplit=1)):\n try:\n return titles.readsAlignments.getSubjectSequence(t)\n except KeyError:\n continue\n raise KeyError(title)","def get_subreddit_translation(subreddit, bible_section):\n\n if bible_section == \"Old Testament\":\n section = \"ot_default\"\n elif bible_section == \"New Testament\":\n section = \"nt_default\"\n else:\n section = \"deut_default\"\n with _conn.cursor() as cur:\n cur.execute(\"SELECT %s FROM subreddit_translations WHERE sub = '%s';\" % (section, subreddit.lower()))\n try:\n trans = cur.fetchone()[0]\n return trans\n except (psycopg2.ProgrammingError, TypeError) as e:\n return None","def extract_sub(s: str):\n subject = re.search(r'sub-\\d+', s)[0]\n return subject","def __calculate_title(video_data):\n title = 'Unknown'\n if 'fulltitle' in video_data.keys():\n title = video_data['fulltitle']\n elif 'title' in video_data.keys():\n title = video_data['title']\n elif '_filename' in video_data.keys():\n title = video_data['_filename']\n return title","def play_movie_with_subs(self, filmid):\n self.logger.debug('play_movie_with_subs')\n start = time.time()\n #\n film = self.database.retrieve_film_info(filmid)\n if film is None:\n self.logger.error(\"no film for download \" + self.plugin.language(30991))\n self.notifier.show_error(30990, self.plugin.language(30991))\n return\n ttmname = os.path.join(self.settings.getDatapath(), 'subtitle.ttml')\n srtname = os.path.join(self.settings.getDatapath(), 'subtitle.srt')\n subs = []\n if self.download_subtitle(film, ttmname, srtname, 'subtitle'):\n subs.append(srtname)\n # (_, listitem) = FilmUI(self.plugin).get_list_item(None, film)\n (_, listitem) = FilmlistUi(self.plugin)._generateListItem(film)\n self.logger.debug('SUBTITLE FOUND {} from url {}' , subs, film.url_sub)\n if listitem:\n if subs:\n listitem.setSubtitles(subs)\n self.plugin.set_resolved_url(True, listitem)\n self.logger.debug('play_movie_with_subs processed: {} sec', time.time() - start)","def download_subtitle(search, results, filename, min_match=0,\n force=0, debug=0):\n s = Subseek()\n subtitleurl = False\n for result in s.order_match(search, results):\n match_text = s.clean_text(s.clean_html(result['text']),False,\n s.detect_encoding(s.clean_html(result['text']))\n ) + \" \" + s.clean_text(s.clean_html(result['description']),False,\n s.detect_encoding(s.clean_html(result['description'])))\n subtitleurl = result['link']\n rating_weight = s.text_weight(search, match_text)\n max_weight = s.text_weight(search)\n rating_match = rating_weight/max_weight*100\n if debug == 1:\n print \"Subtitle File URL: \" + subtitleurl\n print \" Text To Search: \" + search\n print \" Text To Match: \" + match_text\n print \" Text Match (%): \" + str(round(rating_match,2)) + \"%\"\n # check minimal match to use\n if rating_match >= min_match:\n downloaded = s.download(subtitleurl, filename + '.tmp')\n if downloaded == False:\n if debug == 1:\n print \"Error: connection or file creation failed\"\n subtitleurl = False\n else:\n if debug == 1:\n print \"File downloaded\"\n # unrar, unzip or get srt file\n typefile = s.get_sub_file_from_file(filename + '.tmp',\n search, force)\n if typefile == False:\n if debug == 1:\n print \"Subtitle file not found\"\n subtitleurl = False\n else:\n if debug == 1:\n print \"Subtitle file found in \" + typefile\n subtitleurl = True\n break\n else:\n if debug == 1:\n print \"Error: match less than \" + str(round(min_match,2))+ \"%\"\n subtitleurl = False\n break\n\n return subtitleurl","def __init__(self, subtitles_file, subtitles_language: str, audio_language: str):\n\n subtitles_binary = subtitles_file.read()\n encoding = detect_encoding(subtitles_binary)['encoding']\n self.subtitles = subtitles_binary.decode(encoding)\n self.encoding = encoding\n logger.debug(f'Subtitles Encoding: {encoding}')\n logger.debug(f'Subtitles[:100]: {[self.subtitles[:1000]]}')\n self.read_subtitles()\n self.audio_language = audio_language\n\n # Detect subtitles language\n if(subtitles_language == 'ad'): # ad = Auto Detect\n detected_language = detect_language(self.subtitles)\n logger.debug(f\"Subtitles language detected as {detected_language}\")\n\n # True if the detected language in google's supported languages\n language_items = any(map(\n lambda lang: lang['language'] == detected_language, Constants.GOOGLE_LANGUAGES))\n if(language_items is False):\n raise Exception(\n f'Detected language {detected_language} is not supported.')\n self.subtitles_language = detected_language\n\n else:\n self.subtitles_language = subtitles_language\n\n self.translator = CustomTranslator(self.subtitles_language, audio_language)","def translation(self, youtube_id):\r\n if youtube_id:\r\n # Youtube case:\r\n if self.transcript_language == 'en':\r\n return Transcript.asset(self.location, youtube_id).data\r\n\r\n youtube_ids = youtube_speed_dict(self)\r\n assert youtube_id in youtube_ids\r\n\r\n try:\r\n sjson_transcript = Transcript.asset(self.location, youtube_id, self.transcript_language).data\r\n except (NotFoundError):\r\n log.info(\"Can't find content in storage for %s transcript: generating.\", youtube_id)\r\n generate_sjson_for_all_speeds(\r\n self,\r\n self.transcripts[self.transcript_language],\r\n {speed: youtube_id for youtube_id, speed in youtube_ids.iteritems()},\r\n self.transcript_language\r\n )\r\n sjson_transcript = Transcript.asset(self.location, youtube_id, self.transcript_language).data\r\n\r\n return sjson_transcript\r\n else:\r\n # HTML5 case\r\n if self.transcript_language == 'en':\r\n return Transcript.asset(self.location, self.sub).data\r\n else:\r\n return get_or_create_sjson(self)","def getSubtitlesContainer(self):\n self.subtitleURLContainer = \"\"\n\n self.subtitleURLContainer += self.parametersDict['PreURL']\n\n for parameters in self.parametersDict:\n if parameters != \"PreURL\":\n self.subtitleURLContainer += \"&\"\n self.subtitleURLContainer += parameters\n self.subtitleURLContainer += \"=\"\n self.subtitleURLContainer += self.parametersDict[parameters]\n pass","def get_translation(self):","def __getitem__(self, index):\n txt_seq = self.txt_seqs[index]\n word_id_seq, punc_id_seq = self._preprocess(txt_seq)\n return word_id_seq, punc_id_seq","def main():\n parser = argparse.ArgumentParser()\n parser.add_argument('source_path', help=\"Path to the video or audio file to subtitle\",\n nargs='?')\n parser.add_argument('-C', '--concurrency', help=\"Number of concurrent API requests to make\",\n type=int, default=DEFAULT_CONCURRENCY)\n parser.add_argument('-o', '--output',\n help=\"Output path for subtitles (by default, subtitles are saved in \\\n the same directory and name as the source path)\")\n parser.add_argument('-F', '--format', help=\"Destination subtitle format\",\n default=DEFAULT_SUBTITLE_FORMAT)\n parser.add_argument('-S', '--src-language', help=\"Language spoken in source file\",\n default=DEFAULT_SRC_LANGUAGE)\n parser.add_argument('-D', '--dst-language', help=\"Desired language for the subtitles\",\n default=DEFAULT_DST_LANGUAGE)\n parser.add_argument('-K', '--api-key',\n help=\"The Google Translate API key to be used. \\\n (Required for subtitle translation)\")\n parser.add_argument('--list-formats', help=\"List all available subtitle formats\",\n action='store_true')\n parser.add_argument('--list-languages', help=\"List all available source/destination languages\",\n action='store_true')\n\n parser.add_argument('--min_height', help=\"minimum height from 0 - 100%\", type=float, default=93)\n\n parser.add_argument('--max_height', help=\"maximum height from 0 - 100%\", type=float, default=99)\n\n parser.add_argument('--l_v', help=\"Light sensitive\", type=float, default=210)\n\n parser.add_argument('--debug', help=\"Allows to show cropped image on the desktop\", action='store_true', default=True)\n\n parser.add_argument('--cloud', help=\"Use google cloud compute to extract text\", action='store_true', default=False)\n\n parser.add_argument('--disable_time', help=\"Parse time function\", action='store_true')\n\n parser.add_argument('--all', help=\"Render all files\", action='store_true')\n\n args = parser.parse_args()\n\n if args.list_formats:\n print(\"List of formats:\")\n for subtitle_format in FORMATTERS:\n print(\"{format}\".format(format=subtitle_format))\n return 0\n\n if args.list_languages:\n print(\"List of all languages:\")\n for code, language in sorted(LANGUAGE_CODES.items()):\n print(\"{code}\\t{language}\".format(code=code, language=language))\n return 0\n\n if not validate(args):\n return 1\n\n try:\n if args.all:\n for file in os.listdir():\n # *.avi *.flv *.mkv *.mpg *.mp4 *.webm\n if file.endswith('.avi') or file.endswith('.flv') or file.endswith('.mkv') or file.endswith('.mpg') or file.endswith('.mp4') or file.endswith(\".webm\"):\n st = time.time()\n subtitle_file_path = generate_subtitles(\n source_path=file,\n dst_language=args.dst_language,\n output=args.output,\n debug=args.debug,\n cloud=args.cloud,\n disable_time=args.disable_time,\n min_height=args.min_height,\n max_height=args.max_height,\n l_v=args.l_v,\n )\n print(\"Subtitles file created at {} time consumer: {}\".format(subtitle_file_path, time.time() - st))\n else:\n st = time.time()\n subtitle_file_path = generate_subtitles(\n source_path=args.source_path,\n dst_language=args.dst_language,\n output=args.output,\n debug=args.debug,\n cloud=args.cloud,\n disable_time=args.disable_time,\n min_height=args.min_height,\n max_height=args.max_height,\n l_v=args.l_v,\n )\n print(\"Subtitles file created at {} time consumer: {}\".format(subtitle_file_path, time.time() - st))\n except KeyboardInterrupt:\n return 1\n\n return 0","def extract(data, key):\n for d in data:\n if d.startswith(key):\n return d.replace(key+':','').strip() #remove the parser tag then remove the spaces","def subtext(self) -> Union[LocalizedString, None]:\n return self._subtext","def _var_id_sub(self, sprintf):\n id_list = map(lambda x: self.cdict[x][1], sprintf[\"vars\"] )\n return sprintf[\"text\"] % tuple(id_list)","def bib_scalar(biblio, key):\n return biblio[key][0]","def _value(value, text_key, text):\n return {'value': value, 'text': {text_key: text}}","def dummy_add_transcript():\n return {\n \"message\": \"AddTranscript\",\n \"format\": \"2.1\",\n \"metadata\": {\n \"start_time\": 0.0, \"end_time\": 2.0, \"transcript\": \"Foo\\nBar.\"},\n \"results\": [\n {\n \"type\": \"word\",\n \"start_time\": 0.0,\n \"end_time\": 1.0,\n \"alternatives\": [\n {\"content\": \"foo\", \"confidence\": 1.0, \"language\": \"en\"},\n ],\n },\n {\n \"type\": \"speaker_change\",\n \"start_time\": 1.0,\n \"end_time\": 1.0,\n \"score\": 0.8,\n },\n {\n \"type\": \"word\",\n \"start_time\": 1.0,\n \"end_time\": 2.0,\n \"alternatives\": [\n {\"content\": \"bar\", \"confidence\": 1.0, \"language\": \"en\"},\n ],\n },\n {\n \"type\": \"punctuation\",\n \"start_time\": 2.0,\n \"end_time\": 2.0,\n \"alternatives\": [{\"content\": \".\", \"confidence\": 1.0}],\n },\n ],\n }","def download_subtitle(self, film, ttmname, srtname, filename):\n self.logger.debug('download_subtitle')\n ret = False\n if film.url_sub:\n progress = KodiProgressDialog()\n progress.create(30978, filename + u'.ttml')\n # pylint: disable=broad-except\n try:\n progress.update(0)\n mvutils.url_retrieve_vfs(\n film.url_sub, ttmname, progress.url_retrieve_hook)\n try:\n ttml2srtConverter = ttml2srt()\n ttml2srtConverter.do(xbmcvfs.File(ttmname, 'r'),\n xbmcvfs.File(srtname, 'w'))\n ret = True\n except Exception as err:\n self.logger.error('Failed to convert to srt: {}', err)\n progress.close()\n except Exception as err:\n progress.close()\n self.logger.error(\n 'Failure downloading {}: {}', film.url_sub, err)\n return ret","def calculate_needed_subtitle_height(annotation, seen_annotations, video_clip):\n width = video_clip.w\n text = annotation[\"text\"].encode('utf-8')\n if len(text) > width / 40:\n text, lines_inserted = newlinify_string(text, int(width / 40))\n add_to_subtitle_offset(annotation, seen_annotations, lines_inserted - 1)\n\n return text","def get(self,section,key):\n value = ConfigParser.get(self,section,key)\n if value.startswith('\"') or value.startswith(\"'\"):\n return value\n if re.search(r\":\",value):\n out_dict = {}\n pieces = valuesplit(\",\")\n for piece in pieces:\n key,v = piece.split(\":\")\n out_dict[key] = translate(v)\n return out_dict\n elif re.search(\",\",value):\n values = value.split(\",\")\n return [translate(v) for v in values]\n return translate(value)","def give_movie_subtitle_consistent_data(self, movie_file_data, subtitle_file_data):\n m_s_temp_data = []\n preliminary_movie_subtitle_list = self.compare_movie_and_subtitle_FileData(movie_file_data, subtitle_file_data)\n for x in preliminary_movie_subtitle_list:\n \"\"\" Delete 0 'propability' registry\"\"\"\n if x['propability'] != 0:\n m_s_temp_data.append(x)\n\n temp_movieList = []\n for x in m_s_temp_data:\n \"\"\"Check what movies are still in registry\"\"\"\n if x['movie'] not in temp_movieList:\n temp_movieList.append(x['movie'])\n \n final_movie_subtitle_list = []\n matching_movie = False\n for x in temp_movieList:\n \"\"\"For all movies in temp_movieList checks best subtitles\"\"\"\n final_propability = 0\n for y in preliminary_movie_subtitle_list:\n if y['movie'] == x and y['propability'] > final_propability:\n if self.__file_path == y['movie']:\n \"\"\"Check it primary movie is in results matching_movie = True\"\"\"\n matching_movie = True\n best_entry = y\n final_propability = y['propability']\n final_movie_subtitle_list.append(best_entry) \n\t \n\t\"\"\"Filtering by subtitle name - if there is no multiple subtitles\"\"\"\n\tpreliminary_movie_subtitle_list = final_movie_subtitle_list\n\ttemp_movieList = [] #now subtile\n\tfor x in preliminary_movie_subtitle_list:\n \"\"\"Check what movies are still in registry\"\"\"\n if x['subtitle'] not in temp_movieList:\n temp_movieList.append(x['subtitle'])\n\t\t\t\t\n\tfinal_movie_subtitle_list = []\t\n\tmatching_movie = False\n for x in temp_movieList: #now subtile\n \"\"\"For all subtitles in temp_movieList which now is subtitle checks best movie\n\t This makes that one subtitle don't belong to multi movies.\t \n\t \"\"\"\n final_propability = 0\n for y in preliminary_movie_subtitle_list:\n if y['subtitle'] == x and y['propability'] > final_propability:\n if self.__file_path == y['movie']:\n \"\"\"Check it primary movie is in results matching_movie = True\"\"\"\n matching_movie = True\n best_entry = y\n final_propability = y['propability']\n final_movie_subtitle_list.append(best_entry)\n\t\n if matching_movie == True:\n return final_movie_subtitle_list\n else:\n return []","def is_subtitle(file):\n return file.lower().endswith(SUBTITLE_EXTENSIONS)","def play_video(path):\r\n #logger.info(\"######: {}, log: {}########\".format('rk8', path))\r\n #original=https://api.hotstar.com/h/v1/play?contentId=1000238814\r\n #path=\"https://api.hotstar.com/h/v2/play/in/contents/1000238814\"\r\n # Create a playable item with a path to play.\r\n data = make_request(path)\r\n #logger.info(\"######: {}, log: {}########\".format('rk3', path))\r\n if not data:\r\n return\r\n\r\n def get_subtitle(url):\r\n #\r\n # https://hses.akamaized.net/videos/hotstarint/hostages/1260003409/1558430241469/\r\n # 265b9dab22d4e9a033e6df6f89639f17/master.m3u8?hdnea=st=1560107863~exp=1560111463~acl=\r\n # /*~hmac=2f6fb393159ed5fa1b12bbf12e954eb377cfa0fc852d4ff5eb24446233237620\r\n #\r\n # https://hses.akamaized.net/videos/hotstarint/hostages/1260003409/1558430241469/\r\n # 5d0f83c3ccbf4501cf952bdfc8c0d785/subtitle/lang_en/sub-0.vtt\r\n #\r\n _url = urlparse(url)\r\n values = _url._asdict()\r\n values['query'] = ''\r\n values['path'] = '{}/subtitle/lang_en/sub-0.vtt'.format(\"/\".join(values['path'].split('/')[:-1]))\r\n\r\n subtitle_url = ParseResult(**values).geturl()\r\n # subtitle_file = kodiutils.download_url_content_to_temp(subtitle_url, '{}-{}.srt'.format(\r\n # Zee5Plugin.safe_string(item['title']),\r\n # subtitle_lang,\r\n # ))\r\n\r\n return subtitle_url\r\n\r\n #logger.info(\"######: {}, log: {}########\".format('rk6', data))\r\n #item = data['body']['results']['item']\r\n item=data['body']['results']['playBackSets'][0]\r\n path = item['playbackUrl']\r\n licenseURL = item.get('licenseUrl')\r\n subtitle = get_subtitle(path)\r\n\r\n logger.info('Playing video URL: {}, licenseURL: {}, subtitle: {}'.format(path, licenseURL, subtitle))\r\n\r\n play_item = xbmcgui.ListItem(path=path)\r\n if licenseURL:\r\n play_item.setProperty('inputstreamaddon', 'inputstream.adaptive')\r\n play_item.setProperty('inputstream.adaptive.manifest_type', 'hls')\r\n play_item.setMimeType('application/dash+xml')\r\n play_item.setContentLookup(False)\r\n\r\n play_item.setSubtitles([get_subtitle(path)])\r\n\r\n # Pass the item to the Kodi player.\r\n xbmcplugin.setResolvedUrl(_handle, True, listitem=play_item)","def load_subj(loc='./data/'):\n pos, neg = [], []\n with open(os.path.join(loc, 'SUBJ', 'subj.objective'), 'rb') as f:\n for line in f:\n pos.append(line.decode('latin-1').strip())\n with open(os.path.join(loc, 'SUBJ', 'subj.subjective'), 'rb') as f:\n for line in f:\n neg.append(line.decode('latin-1').strip())\n return pos, neg","def read_subtitles(self):\n\n # Group 1: index, Group 2: Start Time, Group 3: End Time, Group 4: Text\n\n patterns = [\n r\"(\\d+)\\n(\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d) --> (\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d)\\n((?:.+\\n)*.+)\",\n r\"(\\d+)\\r\\n(\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d) --> (\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d)\\r\\n((?:.+\\r\\n)*.+)\",\n # Reports pattern\n r\"(\\d+)\\r(\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d) --> (\\d\\d:\\d\\d:\\d\\d,\\d\\d\\d)\\n((?:.+\\r)*.+)\"\n ]\n\n for pattern in patterns:\n re_subs = re.findall(pattern, self.subtitles, re.M | re.I)\n if(len(re_subs) > 1):\n self.re_subs = re_subs\n return\n\n raise Exception(\n f're_subs length is {len(re_subs)}. Maybe the regex pattern is falty?')","def dummy_movie_snippet(doc_id):\n with open('2018_movies.json') as f:\n doc = json.load(f)\n doc_file = doc[doc_id]\n s = doc_file['Text'][:100] + \"......\"\n return (doc_id, doc_file['Title'], s)","def _getText(self, item): # TODO: move this method to more suitable place when possible (scripting base class)\r\n if not isinstance(item, basestring):\r\n return item\r\n\r\n translation = self.phone.getTranslation(item)\r\n if translation != None:\r\n return translation\r\n\r\n return item","def substitution(plainText, key):\n return plainText","def __getitem__(self, title):\n if self.valid_title(title):\n return title + ', ' + \\\n str(self.stats(title)) + ', ' + \\\n str(self.stats(title, type='max')) + ', ' + \\\n str(self.stats(title, type='avg')) + ', ' + \\\n str(self.stats(title, type='count')) + ', ' + \\\n str(self.stats(title, type='last'))\n else:\n print ('Timer Error %s not created or stopped' % title)","def dict2title(title):\n L = title\n y = ''.join(dictionary[int(i)] + \" \" for i in L if i > 0)\n y=y.replace('\"', \"\")\n return y","def __getitem__(self, index):\n txt_seq = self.txt_seqs[index]\n word_id_seq = self._preprocess(txt_seq)\n return word_id_seq, txt_seq","def _decode_captions(self, captions):\n singleton = False\n if captions.ndim == 1:\n singleton = True\n captions = captions[None]\n decoded = []\n N, T = captions.shape\n for i in range(N):\n words = []\n for t in range(T):\n word = self.idx_to_vocab[captions[i, t]]\n if word != '<NULL>':\n words.append(word)\n if word == '<END>':\n break\n decoded.append(' '.join(words))\n if singleton:\n decoded = decoded[0]\n return decoded","def __getitem__(self, key):\n return self.__contents.get(key)","def translate(key, dictionary):\n if key in dictionary:\n return dictionary[key]\n if key in dictionary.values():\n return key\n raise Exception(\"no entry {} in dictionary {}\".format(key, dictionary))","def get(self, encoding_id, input_stream_id, **kwargs):\n # type: (string_types, string_types, dict) -> DvbSubtitleInputStream\n\n return self.api_client.get(\n '/encoding/encodings/{encoding_id}/input-streams/subtitles/dvb-subtitle/{input_stream_id}',\n path_params={'encoding_id': encoding_id, 'input_stream_id': input_stream_id},\n type=DvbSubtitleInputStream,\n **kwargs\n )","def substitute(script, submap):\n\n match = config.TEMPLATE_RE.search(script)\n if match:\n template_type = match.groupdict()['type']\n try:\n return config.TEMPLATE_TYPEMAP[template_type](script, submap)\n except KeyError:\n logger.error('Unsupported template type: %s' % template_type)\n raise\n return script","def parse(t):\n return t","def parse_title(self, pre):\n # Extract datapoints\n title_text = str(pre)\n title = {}\n\n identity_data = self.identity_regex.search(title_text)\n title['linc'] = int(identity_data.group(1).strip().replace(' ', ''))\n title['short_legal'] = identity_data.group(2).strip().replace(';', ' ')\n title['title_number'] = identity_data.group(3).strip()\n\n try:\n title['ats_reference'] = self.ats_regex.search(title_text).group(1).replace(';',' ')\n except AttributeError:\n title['ats_reference'] = ''\n\n title['municipality'] = self.municipality_regex.search(title_text).group(1).replace('\\r','')\n\n try:\n references = self.reference_regex.search(title_text).group(1).split(\"\\n\")\n references = [i.strip() for i in references]\n references = list(filter(None, references))\n title['reference_number'] = references\n except AttributeError:\n title['reference_number'] = ['']\n\n payday_raw = self.payday_regex.search(title_text).group(3).strip('</pre>').strip()\n title['registration'] = payday_raw[:11]\n title['date'] = reversed(payday_raw[15:25].split('/'))\n title['date'] = '-'.join(title['date'])\n title['document_type'] = payday_raw[27:46].strip()\n\n title['value'] = self._try_int(payday_raw[46:62].strip())\n title['consideration'] = self._try_int(payday_raw[62:80].strip())\n\n if \"CONDOMINIUM\" in title_text:\n title['condo'] = True\n else:\n title['condo'] = False\n\n title['title_text'] = title_text.strip('<pre>').strip('</pre>').strip()\n\n return title","def __getitem__(self, item):\n\n return {'text': self.texts[item],\n 'label': self.labels[item]}","def test_read_subtitles(self):\n\n re_subs_length = len(self.sp.re_subs)\n self.assertEqual(re_subs_length, SAMPLE_SUBTITLES_GROUPS_AMOUNT,\n 'Check re_subs length (maybe the regex pattern?).')","def resolve_translation(obj, _):\n return obj.translation.decode()","def process_transcript(transcript_label):\n transcript_key = f\"{transcript_label}.json\"\n\n # Load Transcribe output from S3.\n raw_transcript = get_transcribe_output(transcript_key)\n\n # Parse to assign speaker parts.\n speaker_parts = assign_speakers(raw_transcript)\n\n # Identify Karen and Georgia.\n assigned = karen_or_georgia(speaker_parts)\n\n # Update the full transcript.\n build_transcript(assigned)\n\n # Upload the latest transcript to S3.\n s3 = boto3.resource(\"s3\")\n s3.Bucket(os.getenv(\"S3_BUCKET\")).upload_file(\"main_transcript.txt\", \"main_transcript.txt\")","def extract_movie_titles(dictionary):\n results = dictionary['Similar']['Results']\n lstmt = [d['Name'] for d in results]\n return lstmt","def get_subject(subject_content, data_key=\"b\"):\n (header, data) = get_data(subject_content)\n data = get_events(data[data_key])\n\n return header, data","def _parse_season_entry (self, season, video, sorting):\n return {\n season['summary']['id']: {\n 'idx': sorting[season['summary']['id']],\n 'id': season['summary']['id'],\n 'text': season['summary']['name'],\n 'shortName': season['summary']['shortName'],\n 'boxarts': {\n 'small': video['boxarts']['_342x192']['jpg']['url'],\n 'big': video['boxarts']['_1280x720']['jpg']['url']\n },\n 'interesting_moment': video['interestingMoment']['_665x375']['jpg']['url'],\n }\n }","def generate_subs_from_source(speed_subs, subs_type, subs_filedata, item, language='en'):\r\n _ = item.runtime.service(item, \"i18n\").ugettext\r\n if subs_type.lower() != 'srt':\r\n raise TranscriptsGenerationException(_(\"We support only SubRip (*.srt) transcripts format.\"))\r\n try:\r\n srt_subs_obj = SubRipFile.from_string(subs_filedata)\r\n except Exception as ex:\r\n msg = _(\"Something wrong with SubRip transcripts file during parsing. Inner message is {error_message}\").format(\r\n error_message=ex.message\r\n )\r\n raise TranscriptsGenerationException(msg)\r\n if not srt_subs_obj:\r\n raise TranscriptsGenerationException(_(\"Something wrong with SubRip transcripts file during parsing.\"))\r\n\r\n sub_starts = []\r\n sub_ends = []\r\n sub_texts = []\r\n\r\n for sub in srt_subs_obj:\r\n sub_starts.append(sub.start.ordinal)\r\n sub_ends.append(sub.end.ordinal)\r\n sub_texts.append(sub.text.replace('\\n', ' '))\r\n\r\n subs = {\r\n 'start': sub_starts,\r\n 'end': sub_ends,\r\n 'text': sub_texts}\r\n\r\n for speed, subs_id in speed_subs.iteritems():\r\n save_subs_to_store(\r\n generate_subs(speed, 1, subs),\r\n subs_id,\r\n item,\r\n language\r\n )\r\n\r\n return subs","def map2mw_Aug(d,k1,entry):\n L = entry.metad['L']\n if L in ['7201','7202']: # 7203 relates to 'hay'\n return 'hA'\n if k1 in map2mw_special_Aug:\n return map2mw_special_Aug[k1]\n regexes = [\n u'<ab>aug.</ab> de {%(.*?)%}',\n u'<ab>aug.</ab> {%(.*?)%}',\n u'<ab>aug.</ab> du <ab>c.</ab> de {%(.*?)%}',\n\n ]\n line = entry.datalines[0] # first line of entry in bur.txt\n for regex in regexes:\n m = re.search(regex,line)\n if m:\n root = m.group(1) # root in \n root_slp1=roman_slp1_mw(root,'verb',d)\n if root_slp1 != None:\n return root_slp1\n\n return '?'","def create(self, encoding_id, dvb_subtitle_input_stream, **kwargs):\n # type: (string_types, DvbSubtitleInputStream, dict) -> DvbSubtitleInputStream\n\n return self.api_client.post(\n '/encoding/encodings/{encoding_id}/input-streams/subtitles/dvb-subtitle',\n dvb_subtitle_input_stream,\n path_params={'encoding_id': encoding_id},\n type=DvbSubtitleInputStream,\n **kwargs\n )","def standalize_yt2t(input_file):\n logger.info('Reading file: %s', input_file)\n lines = [line.rstrip('\\n') for line in open(input_file)]\n lines = [line.split('\\t') for line in lines]\n\n logger.info('Building caption dictionary for each video key')\n video_ids = []\n capdict = {}\n for line in lines:\n video_id = line[0]\n if video_id in capdict:\n capdict[video_id].append(line[1])\n else:\n capdict[video_id] = [line[1]]\n video_ids.append(video_id)\n\n # create the json blob\n videos = []\n captions = []\n counter = itertools.count()\n for video_id in video_ids:\n\n vid = int(video_id[3:])\n jvid = {}\n jvid['category'] = 'unknown'\n jvid['video_id'] = video_id\n jvid['id'] = vid\n jvid['start_time'] = -1\n jvid['end_time'] = -1\n jvid['url'] = ''\n videos.append(jvid)\n\n for caption in capdict[video_id]:\n jcap = {}\n jcap['id'] = next(counter)\n jcap['video_id'] = vid\n jcap['caption'] = unicode(caption, errors='ignore')\n captions.append(jcap)\n\n out = {}\n out['info'] = {}\n out['videos'] = videos\n out['captions'] = captions\n\n return out","def get(self, msgid):\r\n return self.trans.get(msgid, str(msgid))","def uploadSubtitles(self, filepath):\n url = f'{self.key}/subtitles'\n filename = os.path.basename(filepath)\n subFormat = os.path.splitext(filepath)[1][1:]\n with open(filepath, 'rb') as subfile:\n params = {'title': filename,\n 'format': subFormat\n }\n headers = {'Accept': 'text/plain, */*'}\n self._server.query(url, self._server._session.post, data=subfile, params=params, headers=headers)\n return self","def download_data(self, format = 'srt'):\n \n def to_ascii(data):\n \"\"\"\n Remove non-ascii characters\n \"\"\"\n return ''.join([x for x in data if ord(x) < 128])\n \n url = self.config.subtitles['url'] % (self.media_resource_id)\n \n print url\n resp, content = httplib2.Http(\".cache\").request(url, \"GET\")\n \n subtitles = json.loads(content)['subtitles']\n \n final_data = ''\n if format == 'srt':\n final_data += self.to_srt(subtitles)\n else:\n final_data += subtitles\n \n return to_ascii(final_data)","def __getitem__(self, key):\n for section in self.header.values():\n for ckey, val in section.items():\n if ckey == key:\n return val\n else:\n raise ValueError","def __getitem__(self, key):\n if type(key) is str:\n return self.encode(key)\n elif type(key) is list or type(key) is tuple:\n return self.decode(key)","def kwextract(s):\n try:\n return strip(s, \"$\").strip().split(\": \")[1]\n except IndexError:\n return \"<unknown>\"","def printable(title, subtitle=None, resp=None):\n title = getfirst(title)\n subtitle = getfirst(subtitle)\n resp = getfirst(resp)\n if subtitle:\n title += \" : \" + subtitle\n if resp:\n title += \" / \" + resp\n return title","def return_xml_dict(self):\n\ttry:\n\t self.Correct_MultiRoot_XML()\n\t self.subtitle_dict = sorted(self.xmltodict(self.XML_String)['subtitle'],key=itemgetter('imdb','cd'))\n\t #self.subtitle_dict = self.xmltodict(self.XML_String)['subtitle']\n\t print \"XML subtitle list downloaded and converted to dict\"\n\t return True\n\texcept:\n\t print \"XML subtitle list not downloaded or converterd.\"\n\t return False","def subtitlePath_and_subtitleFileData(self,file_path_list):\n subtile_file_data = [] \n for x in file_path_list:\n subtile_file_data.append((x, self.guessFileData(x)))\n return subtile_file_data","def from_dict(contents: dict, stype: str, sname: str):\n string = \"SiiNunit\\n{\\n \" + stype + \" : \" + sname + \"\\n {\\n\"\n\n for key, value in contents.items():\n match = pattern.match(key)\n groups = match.groups()\n name = groups[0]\n\n # Convert the item to the correct format\n if isinstance(value, str):\n val = f\"\\\"{value}\\\"\"\n elif \"@\" in groups and \"tuple\" in groups:\n val = str(tuple(value))\n else:\n val = str(value)\n\n if \"@\" in groups and groups[3].isnumeric():\n vprint(f\"Writing to SII: {Fore.LIGHTCYAN_EX}{name}[]: {val}{Style.RESET_ALL}\")\n string += \" \" + groups[0] + \"[]: \" + val + \"\\n\"\n elif isinstance(value, list) and \"tuple\" not in groups:\n i = 0\n for item in value:\n if isinstance(item, list):\n item = tuple(item)\n vprint(f\"Writing to SII: {Fore.LIGHTCYAN_EX}{name}[{i}]: {item}{Style.RESET_ALL}\")\n string += \" \" + groups[0] + f\"[{i}]: \" + str(item) + \"\\n\"\n i += 1\n else:\n vprint(f\"Writing to SII: {Fore.LIGHTCYAN_EX}{name}: {val}{Style.RESET_ALL}\")\n string += \" \" + groups[0] + \": \" + val + \"\\n\"\n\n string += \" }\\n}\\n\"\n\n return string","def get_info(data):\n # type: (dict) -> dict\n item = data.get(\"item\", {})\n plot = item.get(\"summary\", data.get(\"description\"))\n if plot and isinstance(plot, list):\n plot = plot[0]\n # TODO : some-kind of duration calculation...\n return {\n \"title\": item.get(\"title\", \"\").title(),\n \"plot\": plot,\n \"year\": extract_year(item.get(\"date\", \"\")),\n \"genre\": item.get(\"genre\")\n }","def Extract_MetaData(data, key):\n return data.get(key)","def getSubtitles(self):\n\n self.createSoupObject()\n self.getcustomerID()\n self.getToken()\n self.getTitle()\n\n if self.debug:\n print(self.title)\n\n self.getVideoType()\n if self.debug:\n print(self.videoType)\n\n if self.videoType == \"movie\":\n\n self.getAsinID1() # Method-1\n if self.debug:\n print(self.parametersDict['asin'])\n\n returnValue = self.standardFunctionCalls()\n if returnValue != 1:\n self.videoType = \"tv\"\n\n if self.videoType != \"movie\":\n\n self.getAsinID2()\n if self.debug:\n print(self.asinList)\n\n self.parametersDict['asin'] = self.asinList\n currentTitle = self.title\n\n try:\n returnValue = self.standardFunctionCalls()\n except:\n pass\n self.title = currentTitle\n\n return returnValue","def __getitem__(self, key):\n return self.metadata_dict[key]","def get_movie_data(doc_id, data):\n doc_id = str(doc_id)\n movie_object = {\"title\": data[doc_id]['Title'][0],\n \"director\": data[doc_id]['Director'][0],\n \"location\": data[doc_id]['Location'][0] if len(data[doc_id]['Location']) > 0 else data[doc_id]['Location'],\n \"text\": data[doc_id]['Text']\n }\n return movie_object","def generate_srt_from_sjson(sjson_subs, speed):\r\n\r\n output = ''\r\n\r\n equal_len = len(sjson_subs['start']) == len(sjson_subs['end']) == len(sjson_subs['text'])\r\n if not equal_len:\r\n return output\r\n\r\n sjson_speed_1 = generate_subs(speed, 1, sjson_subs)\r\n\r\n for i in range(len(sjson_speed_1['start'])):\r\n item = SubRipItem(\r\n index=i,\r\n start=SubRipTime(milliseconds=sjson_speed_1['start'][i]),\r\n end=SubRipTime(milliseconds=sjson_speed_1['end'][i]),\r\n text=sjson_speed_1['text'][i]\r\n )\r\n output += (unicode(item))\r\n output += '\\n'\r\n return output","def subtitle(string):\n print(\"{}\\n{}\\n\".format(bold(string), underline(string, \"-\")))","def GetValue(self, key):\n return self._metadata_dict[key]"],"string":"[\n \"def edx_get_subtitle(url, headers):\\n \\\"\\\"\\\" or None if no subtitles are available \\\"\\\"\\\"\\n try:\\n jsonString = get_page_contents(url, headers)\\n jsonObject = json.loads(jsonString)\\n return edx_json2srt(jsonObject)\\n except URLError as e:\\n print('[warning] edX subtitles (error:%s)' % e.reason)\\n return None\\n except ValueError as e:\\n print('[warning] edX subtitles (error:%s)' % e.message)\\n return None\",\n \"def edx_get_subtitle(url, headers):\\n try:\\n json_object = get_page_contents_as_json(url, headers)\\n return edx_json2srt(json_object)\\n except URLError as e:\\n _print('[warning] edX subtitles (error:%s)' % e.reason)\\n return None\\n except ValueError as e:\\n _print('[warning] edX subtitles (error:%s)' % e.message)\\n return None\",\n \"def get_subtitle(annotation, sub_duration, video_clip, seen_annotations):\\n if len(annotation[\\\"text\\\"]) == 0:\\n return None\\n\\n annotation_txt = calculate_needed_subtitle_height(annotation, seen_annotations, video_clip)\\n\\n txt_clip = TextClip(annotation_txt, color=\\\"white\\\", fontsize=70, font='Sans Serif')\\n txt_clip = txt_clip.set_position((\\\"center\\\", get_subtitle_offset(annotation, seen_annotations, video_clip)))\\n txt_clip = txt_clip.set_start(float(annotation[\\\"time\\\"]) / 1000.0)\\n txt_clip = txt_clip.set_duration(sub_duration)\\n\\n return txt_clip\",\n \"def extract_subtitle_track(path_to_mkv):\\n handler = SubtitleHandler()\\n with open(path_to_mkv, \\\"rb\\\") as fp:\\n mkvparse.mkvparse(fp, handler)\\n\\n return handler.subs\",\n \"def get_subtitles(self, index: int):\\n\\n match = self.re_subs[index - 1]\\n start = convert_subs_time(match[1])\\n end = convert_subs_time(match[2])\\n subtitles = match[3]\\n subtitles = clean_text(subtitles)\\n\\n return (subtitles, start, end)\",\n \"def getSubtitleURL(self):\\n\\n # If it is a movie, we use this methodology -\\n try:\\n IndexingParameters = [\\\"subtitleUrls\\\", 0, \\\"url\\\"]\\n TitleParamters = [\\n \\\"catalogMetadata\\\", \\\"catalog\\\", \\\"title\\\", \\\"episodeNumber\\\"]\\n subRequestObject = requests.get(self.subtitleURLContainer)\\n\\n parsedJsonObject = json.loads(str(subRequestObject.text))\\n SubsURL = parsedJsonObject[IndexingParameters[0]][\\n IndexingParameters[1]][IndexingParameters[2]]\\n if self.title == \\\"Amazonsubtitles\\\":\\n try:\\n self.title = parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[2]] + \\\"_\\\" + str(\\n parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[3]])\\n except:\\n pass\\n\\n return SubsURL\\n\\n except:\\n pass\\n pass\",\n \"def get_subtitles(self, title):\\n return library.subtitles.get_subtitle_url(title)\",\n \"def __init__(self, subtitle=None):\\n self.subtitle = subtitle\\n if not self.subtitle:\\n self.parse_subtitles()\",\n \"def stat_subtitle(self, release_name, movie_dir):\\n ret = {}\\n for root_dir, child_folders, file_names in os.walk(movie_dir):\\n for file_name in file_names:\\n if not file_name.startswith(release_name):\\n continue\\n\\n subtitle_info = get_subtitle_info(file_name)\\n if not subtitle_info:\\n continue\\n\\n if 'lang' not in subtitle_info:\\n continue\\n\\n lang = subtitle_info['lang']\\n if lang not in ret:\\n ret[lang] = []\\n\\n ret[lang].append(file_name)\\n\\n # Sort result\\n for lang in ret:\\n ret[lang] = sorted(ret[lang])\\n\\n return ret\",\n \"def get_subtitle_print(subs: List[Track]) -> List[str]:\\n data = []\\n if not subs:\\n data.append(\\\"--\\\")\\n for sub in subs:\\n line_items = []\\n\\n # following sub.title tree checks and supports three different language and title scenarios\\n # The second scenario is the recommended option to choose if you are open to choosing any\\n # The third scenario should be used if you have nothing unique to state about the track\\n # | Language | Track Title | Output |\\n # | ------------ | ----------------------------- | --------------------------------------------- |\\n # | es / Spanish | Spanish (Latin American, SDH) | - Spanish (Latin American, SDH), SubRip (SRT) |\\n # | es / Spanish | Latin American (SDH) | - Spanish, Latin American (SDH), SubRip (SRT) |\\n # | es / Spanish | None | - Spanish, SubRip (SRT) |\\n language = pycountry.languages.get(alpha_2=sub.language).name\\n if sub.title:\\n if language.lower() in sub.title.lower():\\n line_items.append(sub.title)\\n else:\\n line_items.append(f\\\"{language}, {sub.title}\\\")\\n else:\\n line_items.append(language)\\n\\n line_items.append(sub.format.replace(\\\"UTF-8\\\", \\\"SubRip (SRT)\\\"))\\n\\n line = \\\"- \\\" + \\\", \\\".join(line_items)\\n data += [\\n (\\\" \\\" + x if i > 0 else x)\\n for i, x in enumerate(textwrap.wrap(line, 64))\\n ]\\n return data\",\n \"def subtitle(self, txt):\\n num = len(txt)\\n ticks = \\\"-\\\" * num\\n print(txt)\\n print(ticks)\",\n \"def update_transcript_info(ensembl_info, word, value):\\n if \\\"transcript\\\" in word:\\n if \\\"id\\\" in word:\\n ensembl_info[\\\"ensembl_transcript_id\\\"] = value\\n elif \\\"start\\\" in word:\\n ensembl_info[\\\"transcript_start\\\"] = int(value)\\n elif \\\"end\\\" in word:\\n ensembl_info[\\\"transcript_end\\\"] = int(value)\\n return ensembl_info\",\n \"def convert_to_tvr_subtitle(df: pd.DataFrame) -> pd.DataFrame:\\n\\tpass\",\n \"def get_subtitle_offset(annotation, seen_annotations, clip):\\n if not annotation[\\\"time\\\"] in seen_annotations:\\n return clip.h - SUBTILE_OFFSET\\n else:\\n return clip.h - SUBTILE_OFFSET * (seen_annotations[annotation[\\\"time\\\"]] + 1)\",\n \"def get_subtitleinfo(fileFullName):\\n sys.stdout.write(\\\"Requesting subtitle info...\\\\n\\\")\\n\\n #接口获取字幕信息\\n response = requests.post(\\n \\\"https://www.shooter.cn/api/subapi.php\\\",\\n verify=False,\\n params= {\\n 'filehash': ComputeFileHash(fileFullName),\\n 'pathinfo': os.path.realpath(fileFullName),\\n 'format': 'json',\\n 'lang': \\\"Chn\\\",\\n },\\n )\\n #未找到字幕处理\\n if response.text == u'\\\\xff':\\n sys.stderr.write(\\\"Subtitle not found.\\\\n\\\")\\n sys.exit(1)\\n return response\",\n \"def extract(self, json_str, sub_number):\\n topic_dict = json.loads(json_str)\\n # print(topic_dict)\\n\\n if ('children' not in topic_dict):\\n raise RuntimeError('topic tree json data has no children.')\\n\\n sub_topic_title = topic_dict['standalone_title']\\n\\n # 1. sub: subject (math, physic)\\n # 2. nb_main: main topic number (addition/subtraction, fraction, ...)\\n # 3. nb_sub: sub topic number\\n # 4. nb_video: video title number\\n # 5. sub_topic_title:\\n # 6. video_title:\\n # 7. d1: text translation duration time\\n # 8. d2: voice over, edit duration time\\n # 9. d3: subtitle duration time\\n # 10. d4: total duration time\\n # 11. s1: start date\\n # 12. s2: end date\\n # 13. s3: elapsed date\\n # 14. status:\\n # 15. finished bool\\n # 16. update bool\\n # 17. new at 2017 bool\\n # 18. video_url:\\n # 19. id:\\n\\n video_idx=1\\n retstr = ''\\n for i in topic_dict['children']:\\n if (i['kind'] == 'Video'):\\n line_str = ' , {_nb_main}, {_nb_sub}, {_nb_video}, {_sub_topic_title}, {_video_title}, {_d1}, {_d2}, {_d3}, {_d4}, {_s1}, {_s2}, {_s3}, {_status}, , , , {_video_url}, {_id}\\\\n'.\\\\\\n format(\\n _nb_main=1,\\n _nb_sub=sub_number,\\n _nb_video=video_idx,\\n _sub_topic_title=sub_topic_title,\\n _video_title=i['title'],\\n _d1='00:00:00', _d2='00:00:00',\\n _d3='00:00:00', _d4='00:00:00',\\n _s1='2017-05-01', _s2='2017-05-01', _s3=0,\\n _status='not_started',\\n _video_url=i['url'],\\n _id=i['internal_id'])\\n video_idx += 1\\n retstr += line_str\\n else:\\n verbose_mes = '# Skip kind [{kind}]: {title}'.format(\\n kind=i['kind'], title=i['title'])\\n self.verbose_out(verbose_mes)\\n\\n return retstr\",\n \"def get_captions(video_id):\\n try:\\n transcript = YouTubeTranscriptApi.get_transcript(video_id)\\n \\n #parse only string and remove the time of captions\\n text = []\\n for txt in transcript:\\n text.append(txt['text'])\\n return text\\n except:\\n text = \\\"No Captions\\\"\\n return text\",\n \"def to_srt(self, subtitles):\\n \\n srt_data = ''\\n subtitle_num = self.start_index\\n for subtitle in subtitles:\\n subtitle_num += 1\\n \\n offset = self.start_time\\n \\n start_time = self._ms_to_time(subtitle['start_time'] + offset)\\n end_time = self._ms_to_time(subtitle['end_time'] + offset)\\n \\n content = subtitle['content'].replace('<br>', ' ')\\n \\n srt_data += str(subtitle_num) + '\\\\r\\\\n'\\n srt_data += '%s --> %s' % (start_time, end_time) + '\\\\r\\\\n'\\n srt_data += content + '\\\\r\\\\n'\\n srt_data += '\\\\r\\\\n'\\n \\n self.end_index = subtitle_num\\n \\n return srt_data\",\n \"def extract_value(k, d, f=''):\\n if k in d:\\n if f != '':\\n p = f(d[k])\\n else:\\n p = d[k]\\n\\n if type(p) == str:\\n v = unicode_decode(p)\\n else:\\n v = p\\n else:\\n v = unicode_decode('')\\n return v\",\n \"def translator(dict):\\n f = lambda match: dict.get(match.group(), match.group())\\n return lambda expression: _word_pattern.sub(f,expression)\",\n \"def get_movie_snippet(doc_id, data):\\n doc_id = str(doc_id)\\n return doc_id, data[doc_id]['Title'][0], data[doc_id]['Text'][:300]+'......'\",\n \"def get_transcript(self, transcript_format='srt'):\\r\\n lang = self.transcript_language\\r\\n\\r\\n if lang == 'en':\\r\\n if self.sub: # HTML5 case and (Youtube case for new style videos)\\r\\n transcript_name = self.sub\\r\\n elif self.youtube_id_1_0: # old courses\\r\\n transcript_name = self.youtube_id_1_0\\r\\n else:\\r\\n log.debug(\\\"No subtitles for 'en' language\\\")\\r\\n raise ValueError\\r\\n\\r\\n data = Transcript.asset(self.location, transcript_name, lang).data\\r\\n filename = u'{}.{}'.format(transcript_name, transcript_format)\\r\\n content = Transcript.convert(data, 'sjson', transcript_format)\\r\\n else:\\r\\n data = Transcript.asset(self.location, None, None, self.transcripts[lang]).data\\r\\n filename = u'{}.{}'.format(os.path.splitext(self.transcripts[lang])[0], transcript_format)\\r\\n content = Transcript.convert(data, 'srt', transcript_format)\\r\\n\\r\\n if not content:\\r\\n log.debug('no subtitles produced in get_transcript')\\r\\n raise ValueError\\r\\n\\r\\n return content, filename, Transcript.mime_types[transcript_format]\",\n \"def add_subtitles(media_id, req):\\n\\n media_hndl = media_map.get(media_id)\\n if not media_hndl:\\n raise FileNotFoundError('{} is not a registered media_id'.format(media_id))\\n\\n subfile = None\\n if req.data:\\n subfile = json.loads(req.data.decode('utf-8')).get('filename')\\n if not subfile:\\n raise AttributeError('No filename specified in the request')\\n\\n if not subfile:\\n if not media_hndl.path:\\n raise NotImplementedError(\\n 'Subtitles are currently only supported for local media files')\\n\\n req = {\\n 'type': 'request',\\n 'action': 'media.subtitles.get_subtitles',\\n 'args': {\\n 'resource': media_hndl.path,\\n }\\n }\\n\\n try:\\n subtitles = send_message(req).output or []\\n except Exception as e:\\n raise RuntimeError('Could not get subtitles: {}'.format(str(e)))\\n\\n if not subtitles:\\n raise FileNotFoundError('No subtitles found for resource {}'.\\n format(media_hndl.path))\\n\\n req = {\\n 'type': 'request',\\n 'action': 'media.subtitles.download',\\n 'args': {\\n 'link': subtitles[0].get('SubDownloadLink'),\\n 'media_resource': media_hndl.path,\\n 'convert_to_vtt': True,\\n }\\n }\\n\\n subfile = (send_message(req).output or {}).get('filename')\\n\\n media_hndl.set_subtitles(subfile)\\n return {\\n 'filename': subfile,\\n 'url': get_remote_base_url() + '/media/subtitles/' + media_id + '.vtt',\\n }\",\n \"def is_subtitle(self):\\n val = False\\n if self.__dict__['codec_type']:\\n if self.__dict__['codec_type'] == 'subtitle':\\n val = True\\n return val\",\n \"def extract_subs_value(text):\\n parts = text.split()\\n value = float(parts[-1])\\n\\n return value\",\n \"def __getitem__(self, index):\\n\\n frames = self.frames[index]\\n caption = self.captions[index]\\n assert len(frames.shape) == 3\\n\\n # Convert captions to indices and add BOS/EOS markers.\\n parsed_caption = self.parse_caption(caption)\\n parsed_caption = np.array(parsed_caption)\\n return frames, parsed_caption\",\n \"def test_get_subtitles(self):\\n\\n (subtitles, start, end) = self.sp.get_subtitles(INDEX)\\n self.assertEqual(subtitles, INDEX_SUBTITLES, 'Check get_subtitles.')\",\n \"def parseTitle(string):\\n replacements={\\n 'PT':'p_{T} [GeV]'\\n ,'MET':'E_{T}^{miss} [GeV]'\\n ,'HT':'H_{T} [GeV]'\\n ,'HTG':'H_{T}^{gen} [GeV]'\\n ,'MET':'E_{T}^{miss} [GeV]'\\n ,'TREFF':'Trigger Effciency'\\n }\\n return reduce(lambda x, y: x.replace(y, replacements[y]), replacements,string)\",\n \"def subtitle_header(slide, title: str):\\n top = Inches(0.61)\\n left = Inches(0.42)\\n height = Inches(0.5)\\n width = Inches(0.5)\\n txt_box = slide.shapes.add_textbox(left, top, width, height)\\n text_frame = txt_box.text_frame\\n\\n paragraph = text_frame.paragraphs[0]\\n paragraph.text = title\\n paragraph.font.bold = False\\n paragraph.font.size = Pt(22)\\n paragraph.font.name = 'Times New Roman'\\n\\n return slide\",\n \"def get_time_intervals(subtitle, regex=r\\\"\\\\S+\\\"):\\n # module webvtt only gets the line-captions, not individual words, so it's time for some regex!\\n # The time corresponding to a word is when that word *starts*\\n # words = (match.group(\\\"word\\\") for match in WORD_REGEX.finditer(subtitle))\\n time_words = [\\n (m.group(\\\"time1\\\") or m.group(\\\"time2\\\"), m.group(\\\"word1\\\") or m.group(\\\"word2\\\"))\\n for m in TIME_WORD_REGEX.finditer(subtitle)\\n ]\\n # Incorrect format, which would lead to trouble zipping\\n if len(time_words) == 0:\\n return []\\n times, words = zip(*time_words)\\n # Quickly search lines starting from the end\\n final_time = next(match.group(\\\"time\\\") for line in reversed(subtitle.split(\\\"\\\\n\\\")) for match in [re.search(FINAL_TIME_REGEX, line)] if match)\\n # timestamps[i] is the time the word starts at if i is the index of the start of a word\\n timestamps = {}\\n word_indices = {}\\n # Build search_str while computing time_stamps by adding one word and one space at a time\\n search_str = ''\\n words = list(words)\\n last_time = 0\\n for j, (word, time) in enumerate(zip(words, times)):\\n i = len(search_str)\\n time = parse_time(time)\\n timestamps[i] = time\\n if time - last_time > 10:\\n search_str += '[ … ] '\\n last_time = time\\n word_indices[i] = j\\n search_str += word + ' '\\n i = len(search_str)\\n timestamps[i] = final_time\\n word_indices[i] = len(words)\\n # Trim off the final space\\n # Inconsistent capitalization, so just lowercase\\n search_str = search_str[:-1].lower()\\n for match in re.finditer(regex, search_str):\\n start, end = match.span()\\n start_index = max(i for i in timestamps if i<=start)\\n end_index = min(i for i in timestamps if i>end)\\n yield Interval(\\n timestamps[start_index],\\n timestamps[end_index],\\n word_indices[start_index],\\n word_indices[end_index],\\n match.group(0)\\n )\",\n \"def extract_transcript(resp: str):\\n if 'result' not in resp:\\n raise ValueError({'Error non valid response from api: {}'.format(resp)})\\n for line in resp.split(\\\"\\\\n\\\"):\\n try:\\n line_json = json.loads(line)\\n out = line_json['result'][0]['alternative'][0]['transcript']\\n return out\\n except:\\n continue\",\n \"def get_words_with_end_times(subtitle_file_path):\\n\\n with open(subtitle_file_path) as subtitle_file:\\n\\n # Remove first 4 lines (containing meta information)\\n for j in range(0, 4):\\n subtitle_file.readline()\\n\\n text = subtitle_file.read()\\n\\n # Check if the subtitle file supports individual word times\\n if text.find(\\\"<c>\\\") == -1:\\n print(\\\"Individual word times are not supported for file: \\\" + subtitle_file_path)\\n return None, None\\n\\n chunks = text.split(\\\" \\\\n\\\\n\\\") # split into chunks for easier data processing\\n\\n words = list()\\n word_end_times = list()\\n\\n for chunk in chunks:\\n chunk_lines = chunk.split(\\\"\\\\n\\\")\\n words_line = chunk_lines[2]\\n\\n words_in_chunk = []\\n word_end_times_in_chunk = []\\n\\n first_word_end_index = words_line.find(\\\"<\\\")\\n if first_word_end_index != -1:\\n first_word = words_line[\\n 0:first_word_end_index] # get the first word (can't be found using method below)\\n\\n words_in_chunk = re.findall(\\\"<c> [\\\\S]*</c>\\\", words_line) # get all words\\n words_in_chunk = [w[4:-4] for w in words_in_chunk] # strip <c> and <c/>\\n\\n word_end_times_in_chunk = re.findall(\\\"<\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d.\\\\d\\\\d\\\\d>\\\", words_line) # get all word end times\\n word_end_times_in_chunk = [t[1:-1] for t in word_end_times_in_chunk] # strip < and >\\n else:\\n # Only one word\\n first_word = words_line\\n\\n last_time = chunk_lines[4][17:29] # end time for the last word\\n\\n words_in_chunk.insert(0, first_word)\\n word_end_times_in_chunk.append(last_time)\\n\\n words.extend(words_in_chunk)\\n word_end_times.extend(word_end_times_in_chunk)\\n\\n # For the last chunk we have to get the word end time from somewhere else\\n first_line_in_last_chunk = chunks[-1].split(\\\"\\\\n\\\")[0]\\n last_time = first_line_in_last_chunk[17:29]\\n word_end_times.pop()\\n word_end_times.append(last_time)\\n\\n if len(words) != len(word_end_times):\\n print(\\\"Warning: word count does not match times count\\\")\\n\\n return words, word_end_times\",\n \"def subjectReadForTitle(titles, title):\\n # Try the title and also the 2 fields that result from splitting it on its\\n # first space (if any).\\n for t in set([title] + title.split(maxsplit=1)):\\n try:\\n return titles.readsAlignments.getSubjectSequence(t)\\n except KeyError:\\n continue\\n raise KeyError(title)\",\n \"def get_subreddit_translation(subreddit, bible_section):\\n\\n if bible_section == \\\"Old Testament\\\":\\n section = \\\"ot_default\\\"\\n elif bible_section == \\\"New Testament\\\":\\n section = \\\"nt_default\\\"\\n else:\\n section = \\\"deut_default\\\"\\n with _conn.cursor() as cur:\\n cur.execute(\\\"SELECT %s FROM subreddit_translations WHERE sub = '%s';\\\" % (section, subreddit.lower()))\\n try:\\n trans = cur.fetchone()[0]\\n return trans\\n except (psycopg2.ProgrammingError, TypeError) as e:\\n return None\",\n \"def extract_sub(s: str):\\n subject = re.search(r'sub-\\\\d+', s)[0]\\n return subject\",\n \"def __calculate_title(video_data):\\n title = 'Unknown'\\n if 'fulltitle' in video_data.keys():\\n title = video_data['fulltitle']\\n elif 'title' in video_data.keys():\\n title = video_data['title']\\n elif '_filename' in video_data.keys():\\n title = video_data['_filename']\\n return title\",\n \"def play_movie_with_subs(self, filmid):\\n self.logger.debug('play_movie_with_subs')\\n start = time.time()\\n #\\n film = self.database.retrieve_film_info(filmid)\\n if film is None:\\n self.logger.error(\\\"no film for download \\\" + self.plugin.language(30991))\\n self.notifier.show_error(30990, self.plugin.language(30991))\\n return\\n ttmname = os.path.join(self.settings.getDatapath(), 'subtitle.ttml')\\n srtname = os.path.join(self.settings.getDatapath(), 'subtitle.srt')\\n subs = []\\n if self.download_subtitle(film, ttmname, srtname, 'subtitle'):\\n subs.append(srtname)\\n # (_, listitem) = FilmUI(self.plugin).get_list_item(None, film)\\n (_, listitem) = FilmlistUi(self.plugin)._generateListItem(film)\\n self.logger.debug('SUBTITLE FOUND {} from url {}' , subs, film.url_sub)\\n if listitem:\\n if subs:\\n listitem.setSubtitles(subs)\\n self.plugin.set_resolved_url(True, listitem)\\n self.logger.debug('play_movie_with_subs processed: {} sec', time.time() - start)\",\n \"def download_subtitle(search, results, filename, min_match=0,\\n force=0, debug=0):\\n s = Subseek()\\n subtitleurl = False\\n for result in s.order_match(search, results):\\n match_text = s.clean_text(s.clean_html(result['text']),False,\\n s.detect_encoding(s.clean_html(result['text']))\\n ) + \\\" \\\" + s.clean_text(s.clean_html(result['description']),False,\\n s.detect_encoding(s.clean_html(result['description'])))\\n subtitleurl = result['link']\\n rating_weight = s.text_weight(search, match_text)\\n max_weight = s.text_weight(search)\\n rating_match = rating_weight/max_weight*100\\n if debug == 1:\\n print \\\"Subtitle File URL: \\\" + subtitleurl\\n print \\\" Text To Search: \\\" + search\\n print \\\" Text To Match: \\\" + match_text\\n print \\\" Text Match (%): \\\" + str(round(rating_match,2)) + \\\"%\\\"\\n # check minimal match to use\\n if rating_match >= min_match:\\n downloaded = s.download(subtitleurl, filename + '.tmp')\\n if downloaded == False:\\n if debug == 1:\\n print \\\"Error: connection or file creation failed\\\"\\n subtitleurl = False\\n else:\\n if debug == 1:\\n print \\\"File downloaded\\\"\\n # unrar, unzip or get srt file\\n typefile = s.get_sub_file_from_file(filename + '.tmp',\\n search, force)\\n if typefile == False:\\n if debug == 1:\\n print \\\"Subtitle file not found\\\"\\n subtitleurl = False\\n else:\\n if debug == 1:\\n print \\\"Subtitle file found in \\\" + typefile\\n subtitleurl = True\\n break\\n else:\\n if debug == 1:\\n print \\\"Error: match less than \\\" + str(round(min_match,2))+ \\\"%\\\"\\n subtitleurl = False\\n break\\n\\n return subtitleurl\",\n \"def __init__(self, subtitles_file, subtitles_language: str, audio_language: str):\\n\\n subtitles_binary = subtitles_file.read()\\n encoding = detect_encoding(subtitles_binary)['encoding']\\n self.subtitles = subtitles_binary.decode(encoding)\\n self.encoding = encoding\\n logger.debug(f'Subtitles Encoding: {encoding}')\\n logger.debug(f'Subtitles[:100]: {[self.subtitles[:1000]]}')\\n self.read_subtitles()\\n self.audio_language = audio_language\\n\\n # Detect subtitles language\\n if(subtitles_language == 'ad'): # ad = Auto Detect\\n detected_language = detect_language(self.subtitles)\\n logger.debug(f\\\"Subtitles language detected as {detected_language}\\\")\\n\\n # True if the detected language in google's supported languages\\n language_items = any(map(\\n lambda lang: lang['language'] == detected_language, Constants.GOOGLE_LANGUAGES))\\n if(language_items is False):\\n raise Exception(\\n f'Detected language {detected_language} is not supported.')\\n self.subtitles_language = detected_language\\n\\n else:\\n self.subtitles_language = subtitles_language\\n\\n self.translator = CustomTranslator(self.subtitles_language, audio_language)\",\n \"def translation(self, youtube_id):\\r\\n if youtube_id:\\r\\n # Youtube case:\\r\\n if self.transcript_language == 'en':\\r\\n return Transcript.asset(self.location, youtube_id).data\\r\\n\\r\\n youtube_ids = youtube_speed_dict(self)\\r\\n assert youtube_id in youtube_ids\\r\\n\\r\\n try:\\r\\n sjson_transcript = Transcript.asset(self.location, youtube_id, self.transcript_language).data\\r\\n except (NotFoundError):\\r\\n log.info(\\\"Can't find content in storage for %s transcript: generating.\\\", youtube_id)\\r\\n generate_sjson_for_all_speeds(\\r\\n self,\\r\\n self.transcripts[self.transcript_language],\\r\\n {speed: youtube_id for youtube_id, speed in youtube_ids.iteritems()},\\r\\n self.transcript_language\\r\\n )\\r\\n sjson_transcript = Transcript.asset(self.location, youtube_id, self.transcript_language).data\\r\\n\\r\\n return sjson_transcript\\r\\n else:\\r\\n # HTML5 case\\r\\n if self.transcript_language == 'en':\\r\\n return Transcript.asset(self.location, self.sub).data\\r\\n else:\\r\\n return get_or_create_sjson(self)\",\n \"def getSubtitlesContainer(self):\\n self.subtitleURLContainer = \\\"\\\"\\n\\n self.subtitleURLContainer += self.parametersDict['PreURL']\\n\\n for parameters in self.parametersDict:\\n if parameters != \\\"PreURL\\\":\\n self.subtitleURLContainer += \\\"&\\\"\\n self.subtitleURLContainer += parameters\\n self.subtitleURLContainer += \\\"=\\\"\\n self.subtitleURLContainer += self.parametersDict[parameters]\\n pass\",\n \"def get_translation(self):\",\n \"def __getitem__(self, index):\\n txt_seq = self.txt_seqs[index]\\n word_id_seq, punc_id_seq = self._preprocess(txt_seq)\\n return word_id_seq, punc_id_seq\",\n \"def main():\\n parser = argparse.ArgumentParser()\\n parser.add_argument('source_path', help=\\\"Path to the video or audio file to subtitle\\\",\\n nargs='?')\\n parser.add_argument('-C', '--concurrency', help=\\\"Number of concurrent API requests to make\\\",\\n type=int, default=DEFAULT_CONCURRENCY)\\n parser.add_argument('-o', '--output',\\n help=\\\"Output path for subtitles (by default, subtitles are saved in \\\\\\n the same directory and name as the source path)\\\")\\n parser.add_argument('-F', '--format', help=\\\"Destination subtitle format\\\",\\n default=DEFAULT_SUBTITLE_FORMAT)\\n parser.add_argument('-S', '--src-language', help=\\\"Language spoken in source file\\\",\\n default=DEFAULT_SRC_LANGUAGE)\\n parser.add_argument('-D', '--dst-language', help=\\\"Desired language for the subtitles\\\",\\n default=DEFAULT_DST_LANGUAGE)\\n parser.add_argument('-K', '--api-key',\\n help=\\\"The Google Translate API key to be used. \\\\\\n (Required for subtitle translation)\\\")\\n parser.add_argument('--list-formats', help=\\\"List all available subtitle formats\\\",\\n action='store_true')\\n parser.add_argument('--list-languages', help=\\\"List all available source/destination languages\\\",\\n action='store_true')\\n\\n parser.add_argument('--min_height', help=\\\"minimum height from 0 - 100%\\\", type=float, default=93)\\n\\n parser.add_argument('--max_height', help=\\\"maximum height from 0 - 100%\\\", type=float, default=99)\\n\\n parser.add_argument('--l_v', help=\\\"Light sensitive\\\", type=float, default=210)\\n\\n parser.add_argument('--debug', help=\\\"Allows to show cropped image on the desktop\\\", action='store_true', default=True)\\n\\n parser.add_argument('--cloud', help=\\\"Use google cloud compute to extract text\\\", action='store_true', default=False)\\n\\n parser.add_argument('--disable_time', help=\\\"Parse time function\\\", action='store_true')\\n\\n parser.add_argument('--all', help=\\\"Render all files\\\", action='store_true')\\n\\n args = parser.parse_args()\\n\\n if args.list_formats:\\n print(\\\"List of formats:\\\")\\n for subtitle_format in FORMATTERS:\\n print(\\\"{format}\\\".format(format=subtitle_format))\\n return 0\\n\\n if args.list_languages:\\n print(\\\"List of all languages:\\\")\\n for code, language in sorted(LANGUAGE_CODES.items()):\\n print(\\\"{code}\\\\t{language}\\\".format(code=code, language=language))\\n return 0\\n\\n if not validate(args):\\n return 1\\n\\n try:\\n if args.all:\\n for file in os.listdir():\\n # *.avi *.flv *.mkv *.mpg *.mp4 *.webm\\n if file.endswith('.avi') or file.endswith('.flv') or file.endswith('.mkv') or file.endswith('.mpg') or file.endswith('.mp4') or file.endswith(\\\".webm\\\"):\\n st = time.time()\\n subtitle_file_path = generate_subtitles(\\n source_path=file,\\n dst_language=args.dst_language,\\n output=args.output,\\n debug=args.debug,\\n cloud=args.cloud,\\n disable_time=args.disable_time,\\n min_height=args.min_height,\\n max_height=args.max_height,\\n l_v=args.l_v,\\n )\\n print(\\\"Subtitles file created at {} time consumer: {}\\\".format(subtitle_file_path, time.time() - st))\\n else:\\n st = time.time()\\n subtitle_file_path = generate_subtitles(\\n source_path=args.source_path,\\n dst_language=args.dst_language,\\n output=args.output,\\n debug=args.debug,\\n cloud=args.cloud,\\n disable_time=args.disable_time,\\n min_height=args.min_height,\\n max_height=args.max_height,\\n l_v=args.l_v,\\n )\\n print(\\\"Subtitles file created at {} time consumer: {}\\\".format(subtitle_file_path, time.time() - st))\\n except KeyboardInterrupt:\\n return 1\\n\\n return 0\",\n \"def extract(data, key):\\n for d in data:\\n if d.startswith(key):\\n return d.replace(key+':','').strip() #remove the parser tag then remove the spaces\",\n \"def subtext(self) -> Union[LocalizedString, None]:\\n return self._subtext\",\n \"def _var_id_sub(self, sprintf):\\n id_list = map(lambda x: self.cdict[x][1], sprintf[\\\"vars\\\"] )\\n return sprintf[\\\"text\\\"] % tuple(id_list)\",\n \"def bib_scalar(biblio, key):\\n return biblio[key][0]\",\n \"def _value(value, text_key, text):\\n return {'value': value, 'text': {text_key: text}}\",\n \"def dummy_add_transcript():\\n return {\\n \\\"message\\\": \\\"AddTranscript\\\",\\n \\\"format\\\": \\\"2.1\\\",\\n \\\"metadata\\\": {\\n \\\"start_time\\\": 0.0, \\\"end_time\\\": 2.0, \\\"transcript\\\": \\\"Foo\\\\nBar.\\\"},\\n \\\"results\\\": [\\n {\\n \\\"type\\\": \\\"word\\\",\\n \\\"start_time\\\": 0.0,\\n \\\"end_time\\\": 1.0,\\n \\\"alternatives\\\": [\\n {\\\"content\\\": \\\"foo\\\", \\\"confidence\\\": 1.0, \\\"language\\\": \\\"en\\\"},\\n ],\\n },\\n {\\n \\\"type\\\": \\\"speaker_change\\\",\\n \\\"start_time\\\": 1.0,\\n \\\"end_time\\\": 1.0,\\n \\\"score\\\": 0.8,\\n },\\n {\\n \\\"type\\\": \\\"word\\\",\\n \\\"start_time\\\": 1.0,\\n \\\"end_time\\\": 2.0,\\n \\\"alternatives\\\": [\\n {\\\"content\\\": \\\"bar\\\", \\\"confidence\\\": 1.0, \\\"language\\\": \\\"en\\\"},\\n ],\\n },\\n {\\n \\\"type\\\": \\\"punctuation\\\",\\n \\\"start_time\\\": 2.0,\\n \\\"end_time\\\": 2.0,\\n \\\"alternatives\\\": [{\\\"content\\\": \\\".\\\", \\\"confidence\\\": 1.0}],\\n },\\n ],\\n }\",\n \"def download_subtitle(self, film, ttmname, srtname, filename):\\n self.logger.debug('download_subtitle')\\n ret = False\\n if film.url_sub:\\n progress = KodiProgressDialog()\\n progress.create(30978, filename + u'.ttml')\\n # pylint: disable=broad-except\\n try:\\n progress.update(0)\\n mvutils.url_retrieve_vfs(\\n film.url_sub, ttmname, progress.url_retrieve_hook)\\n try:\\n ttml2srtConverter = ttml2srt()\\n ttml2srtConverter.do(xbmcvfs.File(ttmname, 'r'),\\n xbmcvfs.File(srtname, 'w'))\\n ret = True\\n except Exception as err:\\n self.logger.error('Failed to convert to srt: {}', err)\\n progress.close()\\n except Exception as err:\\n progress.close()\\n self.logger.error(\\n 'Failure downloading {}: {}', film.url_sub, err)\\n return ret\",\n \"def calculate_needed_subtitle_height(annotation, seen_annotations, video_clip):\\n width = video_clip.w\\n text = annotation[\\\"text\\\"].encode('utf-8')\\n if len(text) > width / 40:\\n text, lines_inserted = newlinify_string(text, int(width / 40))\\n add_to_subtitle_offset(annotation, seen_annotations, lines_inserted - 1)\\n\\n return text\",\n \"def get(self,section,key):\\n value = ConfigParser.get(self,section,key)\\n if value.startswith('\\\"') or value.startswith(\\\"'\\\"):\\n return value\\n if re.search(r\\\":\\\",value):\\n out_dict = {}\\n pieces = valuesplit(\\\",\\\")\\n for piece in pieces:\\n key,v = piece.split(\\\":\\\")\\n out_dict[key] = translate(v)\\n return out_dict\\n elif re.search(\\\",\\\",value):\\n values = value.split(\\\",\\\")\\n return [translate(v) for v in values]\\n return translate(value)\",\n \"def give_movie_subtitle_consistent_data(self, movie_file_data, subtitle_file_data):\\n m_s_temp_data = []\\n preliminary_movie_subtitle_list = self.compare_movie_and_subtitle_FileData(movie_file_data, subtitle_file_data)\\n for x in preliminary_movie_subtitle_list:\\n \\\"\\\"\\\" Delete 0 'propability' registry\\\"\\\"\\\"\\n if x['propability'] != 0:\\n m_s_temp_data.append(x)\\n\\n temp_movieList = []\\n for x in m_s_temp_data:\\n \\\"\\\"\\\"Check what movies are still in registry\\\"\\\"\\\"\\n if x['movie'] not in temp_movieList:\\n temp_movieList.append(x['movie'])\\n \\n final_movie_subtitle_list = []\\n matching_movie = False\\n for x in temp_movieList:\\n \\\"\\\"\\\"For all movies in temp_movieList checks best subtitles\\\"\\\"\\\"\\n final_propability = 0\\n for y in preliminary_movie_subtitle_list:\\n if y['movie'] == x and y['propability'] > final_propability:\\n if self.__file_path == y['movie']:\\n \\\"\\\"\\\"Check it primary movie is in results matching_movie = True\\\"\\\"\\\"\\n matching_movie = True\\n best_entry = y\\n final_propability = y['propability']\\n final_movie_subtitle_list.append(best_entry) \\n\\t \\n\\t\\\"\\\"\\\"Filtering by subtitle name - if there is no multiple subtitles\\\"\\\"\\\"\\n\\tpreliminary_movie_subtitle_list = final_movie_subtitle_list\\n\\ttemp_movieList = [] #now subtile\\n\\tfor x in preliminary_movie_subtitle_list:\\n \\\"\\\"\\\"Check what movies are still in registry\\\"\\\"\\\"\\n if x['subtitle'] not in temp_movieList:\\n temp_movieList.append(x['subtitle'])\\n\\t\\t\\t\\t\\n\\tfinal_movie_subtitle_list = []\\t\\n\\tmatching_movie = False\\n for x in temp_movieList: #now subtile\\n \\\"\\\"\\\"For all subtitles in temp_movieList which now is subtitle checks best movie\\n\\t This makes that one subtitle don't belong to multi movies.\\t \\n\\t \\\"\\\"\\\"\\n final_propability = 0\\n for y in preliminary_movie_subtitle_list:\\n if y['subtitle'] == x and y['propability'] > final_propability:\\n if self.__file_path == y['movie']:\\n \\\"\\\"\\\"Check it primary movie is in results matching_movie = True\\\"\\\"\\\"\\n matching_movie = True\\n best_entry = y\\n final_propability = y['propability']\\n final_movie_subtitle_list.append(best_entry)\\n\\t\\n if matching_movie == True:\\n return final_movie_subtitle_list\\n else:\\n return []\",\n \"def is_subtitle(file):\\n return file.lower().endswith(SUBTITLE_EXTENSIONS)\",\n \"def play_video(path):\\r\\n #logger.info(\\\"######: {}, log: {}########\\\".format('rk8', path))\\r\\n #original=https://api.hotstar.com/h/v1/play?contentId=1000238814\\r\\n #path=\\\"https://api.hotstar.com/h/v2/play/in/contents/1000238814\\\"\\r\\n # Create a playable item with a path to play.\\r\\n data = make_request(path)\\r\\n #logger.info(\\\"######: {}, log: {}########\\\".format('rk3', path))\\r\\n if not data:\\r\\n return\\r\\n\\r\\n def get_subtitle(url):\\r\\n #\\r\\n # https://hses.akamaized.net/videos/hotstarint/hostages/1260003409/1558430241469/\\r\\n # 265b9dab22d4e9a033e6df6f89639f17/master.m3u8?hdnea=st=1560107863~exp=1560111463~acl=\\r\\n # /*~hmac=2f6fb393159ed5fa1b12bbf12e954eb377cfa0fc852d4ff5eb24446233237620\\r\\n #\\r\\n # https://hses.akamaized.net/videos/hotstarint/hostages/1260003409/1558430241469/\\r\\n # 5d0f83c3ccbf4501cf952bdfc8c0d785/subtitle/lang_en/sub-0.vtt\\r\\n #\\r\\n _url = urlparse(url)\\r\\n values = _url._asdict()\\r\\n values['query'] = ''\\r\\n values['path'] = '{}/subtitle/lang_en/sub-0.vtt'.format(\\\"/\\\".join(values['path'].split('/')[:-1]))\\r\\n\\r\\n subtitle_url = ParseResult(**values).geturl()\\r\\n # subtitle_file = kodiutils.download_url_content_to_temp(subtitle_url, '{}-{}.srt'.format(\\r\\n # Zee5Plugin.safe_string(item['title']),\\r\\n # subtitle_lang,\\r\\n # ))\\r\\n\\r\\n return subtitle_url\\r\\n\\r\\n #logger.info(\\\"######: {}, log: {}########\\\".format('rk6', data))\\r\\n #item = data['body']['results']['item']\\r\\n item=data['body']['results']['playBackSets'][0]\\r\\n path = item['playbackUrl']\\r\\n licenseURL = item.get('licenseUrl')\\r\\n subtitle = get_subtitle(path)\\r\\n\\r\\n logger.info('Playing video URL: {}, licenseURL: {}, subtitle: {}'.format(path, licenseURL, subtitle))\\r\\n\\r\\n play_item = xbmcgui.ListItem(path=path)\\r\\n if licenseURL:\\r\\n play_item.setProperty('inputstreamaddon', 'inputstream.adaptive')\\r\\n play_item.setProperty('inputstream.adaptive.manifest_type', 'hls')\\r\\n play_item.setMimeType('application/dash+xml')\\r\\n play_item.setContentLookup(False)\\r\\n\\r\\n play_item.setSubtitles([get_subtitle(path)])\\r\\n\\r\\n # Pass the item to the Kodi player.\\r\\n xbmcplugin.setResolvedUrl(_handle, True, listitem=play_item)\",\n \"def load_subj(loc='./data/'):\\n pos, neg = [], []\\n with open(os.path.join(loc, 'SUBJ', 'subj.objective'), 'rb') as f:\\n for line in f:\\n pos.append(line.decode('latin-1').strip())\\n with open(os.path.join(loc, 'SUBJ', 'subj.subjective'), 'rb') as f:\\n for line in f:\\n neg.append(line.decode('latin-1').strip())\\n return pos, neg\",\n \"def read_subtitles(self):\\n\\n # Group 1: index, Group 2: Start Time, Group 3: End Time, Group 4: Text\\n\\n patterns = [\\n r\\\"(\\\\d+)\\\\n(\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d) --> (\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d)\\\\n((?:.+\\\\n)*.+)\\\",\\n r\\\"(\\\\d+)\\\\r\\\\n(\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d) --> (\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d)\\\\r\\\\n((?:.+\\\\r\\\\n)*.+)\\\",\\n # Reports pattern\\n r\\\"(\\\\d+)\\\\r(\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d) --> (\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d,\\\\d\\\\d\\\\d)\\\\n((?:.+\\\\r)*.+)\\\"\\n ]\\n\\n for pattern in patterns:\\n re_subs = re.findall(pattern, self.subtitles, re.M | re.I)\\n if(len(re_subs) > 1):\\n self.re_subs = re_subs\\n return\\n\\n raise Exception(\\n f're_subs length is {len(re_subs)}. Maybe the regex pattern is falty?')\",\n \"def dummy_movie_snippet(doc_id):\\n with open('2018_movies.json') as f:\\n doc = json.load(f)\\n doc_file = doc[doc_id]\\n s = doc_file['Text'][:100] + \\\"......\\\"\\n return (doc_id, doc_file['Title'], s)\",\n \"def _getText(self, item): # TODO: move this method to more suitable place when possible (scripting base class)\\r\\n if not isinstance(item, basestring):\\r\\n return item\\r\\n\\r\\n translation = self.phone.getTranslation(item)\\r\\n if translation != None:\\r\\n return translation\\r\\n\\r\\n return item\",\n \"def substitution(plainText, key):\\n return plainText\",\n \"def __getitem__(self, title):\\n if self.valid_title(title):\\n return title + ', ' + \\\\\\n str(self.stats(title)) + ', ' + \\\\\\n str(self.stats(title, type='max')) + ', ' + \\\\\\n str(self.stats(title, type='avg')) + ', ' + \\\\\\n str(self.stats(title, type='count')) + ', ' + \\\\\\n str(self.stats(title, type='last'))\\n else:\\n print ('Timer Error %s not created or stopped' % title)\",\n \"def dict2title(title):\\n L = title\\n y = ''.join(dictionary[int(i)] + \\\" \\\" for i in L if i > 0)\\n y=y.replace('\\\"', \\\"\\\")\\n return y\",\n \"def __getitem__(self, index):\\n txt_seq = self.txt_seqs[index]\\n word_id_seq = self._preprocess(txt_seq)\\n return word_id_seq, txt_seq\",\n \"def _decode_captions(self, captions):\\n singleton = False\\n if captions.ndim == 1:\\n singleton = True\\n captions = captions[None]\\n decoded = []\\n N, T = captions.shape\\n for i in range(N):\\n words = []\\n for t in range(T):\\n word = self.idx_to_vocab[captions[i, t]]\\n if word != '<NULL>':\\n words.append(word)\\n if word == '<END>':\\n break\\n decoded.append(' '.join(words))\\n if singleton:\\n decoded = decoded[0]\\n return decoded\",\n \"def __getitem__(self, key):\\n return self.__contents.get(key)\",\n \"def translate(key, dictionary):\\n if key in dictionary:\\n return dictionary[key]\\n if key in dictionary.values():\\n return key\\n raise Exception(\\\"no entry {} in dictionary {}\\\".format(key, dictionary))\",\n \"def get(self, encoding_id, input_stream_id, **kwargs):\\n # type: (string_types, string_types, dict) -> DvbSubtitleInputStream\\n\\n return self.api_client.get(\\n '/encoding/encodings/{encoding_id}/input-streams/subtitles/dvb-subtitle/{input_stream_id}',\\n path_params={'encoding_id': encoding_id, 'input_stream_id': input_stream_id},\\n type=DvbSubtitleInputStream,\\n **kwargs\\n )\",\n \"def substitute(script, submap):\\n\\n match = config.TEMPLATE_RE.search(script)\\n if match:\\n template_type = match.groupdict()['type']\\n try:\\n return config.TEMPLATE_TYPEMAP[template_type](script, submap)\\n except KeyError:\\n logger.error('Unsupported template type: %s' % template_type)\\n raise\\n return script\",\n \"def parse(t):\\n return t\",\n \"def parse_title(self, pre):\\n # Extract datapoints\\n title_text = str(pre)\\n title = {}\\n\\n identity_data = self.identity_regex.search(title_text)\\n title['linc'] = int(identity_data.group(1).strip().replace(' ', ''))\\n title['short_legal'] = identity_data.group(2).strip().replace(';', ' ')\\n title['title_number'] = identity_data.group(3).strip()\\n\\n try:\\n title['ats_reference'] = self.ats_regex.search(title_text).group(1).replace(';',' ')\\n except AttributeError:\\n title['ats_reference'] = ''\\n\\n title['municipality'] = self.municipality_regex.search(title_text).group(1).replace('\\\\r','')\\n\\n try:\\n references = self.reference_regex.search(title_text).group(1).split(\\\"\\\\n\\\")\\n references = [i.strip() for i in references]\\n references = list(filter(None, references))\\n title['reference_number'] = references\\n except AttributeError:\\n title['reference_number'] = ['']\\n\\n payday_raw = self.payday_regex.search(title_text).group(3).strip('</pre>').strip()\\n title['registration'] = payday_raw[:11]\\n title['date'] = reversed(payday_raw[15:25].split('/'))\\n title['date'] = '-'.join(title['date'])\\n title['document_type'] = payday_raw[27:46].strip()\\n\\n title['value'] = self._try_int(payday_raw[46:62].strip())\\n title['consideration'] = self._try_int(payday_raw[62:80].strip())\\n\\n if \\\"CONDOMINIUM\\\" in title_text:\\n title['condo'] = True\\n else:\\n title['condo'] = False\\n\\n title['title_text'] = title_text.strip('<pre>').strip('</pre>').strip()\\n\\n return title\",\n \"def __getitem__(self, item):\\n\\n return {'text': self.texts[item],\\n 'label': self.labels[item]}\",\n \"def test_read_subtitles(self):\\n\\n re_subs_length = len(self.sp.re_subs)\\n self.assertEqual(re_subs_length, SAMPLE_SUBTITLES_GROUPS_AMOUNT,\\n 'Check re_subs length (maybe the regex pattern?).')\",\n \"def resolve_translation(obj, _):\\n return obj.translation.decode()\",\n \"def process_transcript(transcript_label):\\n transcript_key = f\\\"{transcript_label}.json\\\"\\n\\n # Load Transcribe output from S3.\\n raw_transcript = get_transcribe_output(transcript_key)\\n\\n # Parse to assign speaker parts.\\n speaker_parts = assign_speakers(raw_transcript)\\n\\n # Identify Karen and Georgia.\\n assigned = karen_or_georgia(speaker_parts)\\n\\n # Update the full transcript.\\n build_transcript(assigned)\\n\\n # Upload the latest transcript to S3.\\n s3 = boto3.resource(\\\"s3\\\")\\n s3.Bucket(os.getenv(\\\"S3_BUCKET\\\")).upload_file(\\\"main_transcript.txt\\\", \\\"main_transcript.txt\\\")\",\n \"def extract_movie_titles(dictionary):\\n results = dictionary['Similar']['Results']\\n lstmt = [d['Name'] for d in results]\\n return lstmt\",\n \"def get_subject(subject_content, data_key=\\\"b\\\"):\\n (header, data) = get_data(subject_content)\\n data = get_events(data[data_key])\\n\\n return header, data\",\n \"def _parse_season_entry (self, season, video, sorting):\\n return {\\n season['summary']['id']: {\\n 'idx': sorting[season['summary']['id']],\\n 'id': season['summary']['id'],\\n 'text': season['summary']['name'],\\n 'shortName': season['summary']['shortName'],\\n 'boxarts': {\\n 'small': video['boxarts']['_342x192']['jpg']['url'],\\n 'big': video['boxarts']['_1280x720']['jpg']['url']\\n },\\n 'interesting_moment': video['interestingMoment']['_665x375']['jpg']['url'],\\n }\\n }\",\n \"def generate_subs_from_source(speed_subs, subs_type, subs_filedata, item, language='en'):\\r\\n _ = item.runtime.service(item, \\\"i18n\\\").ugettext\\r\\n if subs_type.lower() != 'srt':\\r\\n raise TranscriptsGenerationException(_(\\\"We support only SubRip (*.srt) transcripts format.\\\"))\\r\\n try:\\r\\n srt_subs_obj = SubRipFile.from_string(subs_filedata)\\r\\n except Exception as ex:\\r\\n msg = _(\\\"Something wrong with SubRip transcripts file during parsing. Inner message is {error_message}\\\").format(\\r\\n error_message=ex.message\\r\\n )\\r\\n raise TranscriptsGenerationException(msg)\\r\\n if not srt_subs_obj:\\r\\n raise TranscriptsGenerationException(_(\\\"Something wrong with SubRip transcripts file during parsing.\\\"))\\r\\n\\r\\n sub_starts = []\\r\\n sub_ends = []\\r\\n sub_texts = []\\r\\n\\r\\n for sub in srt_subs_obj:\\r\\n sub_starts.append(sub.start.ordinal)\\r\\n sub_ends.append(sub.end.ordinal)\\r\\n sub_texts.append(sub.text.replace('\\\\n', ' '))\\r\\n\\r\\n subs = {\\r\\n 'start': sub_starts,\\r\\n 'end': sub_ends,\\r\\n 'text': sub_texts}\\r\\n\\r\\n for speed, subs_id in speed_subs.iteritems():\\r\\n save_subs_to_store(\\r\\n generate_subs(speed, 1, subs),\\r\\n subs_id,\\r\\n item,\\r\\n language\\r\\n )\\r\\n\\r\\n return subs\",\n \"def map2mw_Aug(d,k1,entry):\\n L = entry.metad['L']\\n if L in ['7201','7202']: # 7203 relates to 'hay'\\n return 'hA'\\n if k1 in map2mw_special_Aug:\\n return map2mw_special_Aug[k1]\\n regexes = [\\n u'<ab>aug.</ab> de {%(.*?)%}',\\n u'<ab>aug.</ab> {%(.*?)%}',\\n u'<ab>aug.</ab> du <ab>c.</ab> de {%(.*?)%}',\\n\\n ]\\n line = entry.datalines[0] # first line of entry in bur.txt\\n for regex in regexes:\\n m = re.search(regex,line)\\n if m:\\n root = m.group(1) # root in \\n root_slp1=roman_slp1_mw(root,'verb',d)\\n if root_slp1 != None:\\n return root_slp1\\n\\n return '?'\",\n \"def create(self, encoding_id, dvb_subtitle_input_stream, **kwargs):\\n # type: (string_types, DvbSubtitleInputStream, dict) -> DvbSubtitleInputStream\\n\\n return self.api_client.post(\\n '/encoding/encodings/{encoding_id}/input-streams/subtitles/dvb-subtitle',\\n dvb_subtitle_input_stream,\\n path_params={'encoding_id': encoding_id},\\n type=DvbSubtitleInputStream,\\n **kwargs\\n )\",\n \"def standalize_yt2t(input_file):\\n logger.info('Reading file: %s', input_file)\\n lines = [line.rstrip('\\\\n') for line in open(input_file)]\\n lines = [line.split('\\\\t') for line in lines]\\n\\n logger.info('Building caption dictionary for each video key')\\n video_ids = []\\n capdict = {}\\n for line in lines:\\n video_id = line[0]\\n if video_id in capdict:\\n capdict[video_id].append(line[1])\\n else:\\n capdict[video_id] = [line[1]]\\n video_ids.append(video_id)\\n\\n # create the json blob\\n videos = []\\n captions = []\\n counter = itertools.count()\\n for video_id in video_ids:\\n\\n vid = int(video_id[3:])\\n jvid = {}\\n jvid['category'] = 'unknown'\\n jvid['video_id'] = video_id\\n jvid['id'] = vid\\n jvid['start_time'] = -1\\n jvid['end_time'] = -1\\n jvid['url'] = ''\\n videos.append(jvid)\\n\\n for caption in capdict[video_id]:\\n jcap = {}\\n jcap['id'] = next(counter)\\n jcap['video_id'] = vid\\n jcap['caption'] = unicode(caption, errors='ignore')\\n captions.append(jcap)\\n\\n out = {}\\n out['info'] = {}\\n out['videos'] = videos\\n out['captions'] = captions\\n\\n return out\",\n \"def get(self, msgid):\\r\\n return self.trans.get(msgid, str(msgid))\",\n \"def uploadSubtitles(self, filepath):\\n url = f'{self.key}/subtitles'\\n filename = os.path.basename(filepath)\\n subFormat = os.path.splitext(filepath)[1][1:]\\n with open(filepath, 'rb') as subfile:\\n params = {'title': filename,\\n 'format': subFormat\\n }\\n headers = {'Accept': 'text/plain, */*'}\\n self._server.query(url, self._server._session.post, data=subfile, params=params, headers=headers)\\n return self\",\n \"def download_data(self, format = 'srt'):\\n \\n def to_ascii(data):\\n \\\"\\\"\\\"\\n Remove non-ascii characters\\n \\\"\\\"\\\"\\n return ''.join([x for x in data if ord(x) < 128])\\n \\n url = self.config.subtitles['url'] % (self.media_resource_id)\\n \\n print url\\n resp, content = httplib2.Http(\\\".cache\\\").request(url, \\\"GET\\\")\\n \\n subtitles = json.loads(content)['subtitles']\\n \\n final_data = ''\\n if format == 'srt':\\n final_data += self.to_srt(subtitles)\\n else:\\n final_data += subtitles\\n \\n return to_ascii(final_data)\",\n \"def __getitem__(self, key):\\n for section in self.header.values():\\n for ckey, val in section.items():\\n if ckey == key:\\n return val\\n else:\\n raise ValueError\",\n \"def __getitem__(self, key):\\n if type(key) is str:\\n return self.encode(key)\\n elif type(key) is list or type(key) is tuple:\\n return self.decode(key)\",\n \"def kwextract(s):\\n try:\\n return strip(s, \\\"$\\\").strip().split(\\\": \\\")[1]\\n except IndexError:\\n return \\\"<unknown>\\\"\",\n \"def printable(title, subtitle=None, resp=None):\\n title = getfirst(title)\\n subtitle = getfirst(subtitle)\\n resp = getfirst(resp)\\n if subtitle:\\n title += \\\" : \\\" + subtitle\\n if resp:\\n title += \\\" / \\\" + resp\\n return title\",\n \"def return_xml_dict(self):\\n\\ttry:\\n\\t self.Correct_MultiRoot_XML()\\n\\t self.subtitle_dict = sorted(self.xmltodict(self.XML_String)['subtitle'],key=itemgetter('imdb','cd'))\\n\\t #self.subtitle_dict = self.xmltodict(self.XML_String)['subtitle']\\n\\t print \\\"XML subtitle list downloaded and converted to dict\\\"\\n\\t return True\\n\\texcept:\\n\\t print \\\"XML subtitle list not downloaded or converterd.\\\"\\n\\t return False\",\n \"def subtitlePath_and_subtitleFileData(self,file_path_list):\\n subtile_file_data = [] \\n for x in file_path_list:\\n subtile_file_data.append((x, self.guessFileData(x)))\\n return subtile_file_data\",\n \"def from_dict(contents: dict, stype: str, sname: str):\\n string = \\\"SiiNunit\\\\n{\\\\n \\\" + stype + \\\" : \\\" + sname + \\\"\\\\n {\\\\n\\\"\\n\\n for key, value in contents.items():\\n match = pattern.match(key)\\n groups = match.groups()\\n name = groups[0]\\n\\n # Convert the item to the correct format\\n if isinstance(value, str):\\n val = f\\\"\\\\\\\"{value}\\\\\\\"\\\"\\n elif \\\"@\\\" in groups and \\\"tuple\\\" in groups:\\n val = str(tuple(value))\\n else:\\n val = str(value)\\n\\n if \\\"@\\\" in groups and groups[3].isnumeric():\\n vprint(f\\\"Writing to SII: {Fore.LIGHTCYAN_EX}{name}[]: {val}{Style.RESET_ALL}\\\")\\n string += \\\" \\\" + groups[0] + \\\"[]: \\\" + val + \\\"\\\\n\\\"\\n elif isinstance(value, list) and \\\"tuple\\\" not in groups:\\n i = 0\\n for item in value:\\n if isinstance(item, list):\\n item = tuple(item)\\n vprint(f\\\"Writing to SII: {Fore.LIGHTCYAN_EX}{name}[{i}]: {item}{Style.RESET_ALL}\\\")\\n string += \\\" \\\" + groups[0] + f\\\"[{i}]: \\\" + str(item) + \\\"\\\\n\\\"\\n i += 1\\n else:\\n vprint(f\\\"Writing to SII: {Fore.LIGHTCYAN_EX}{name}: {val}{Style.RESET_ALL}\\\")\\n string += \\\" \\\" + groups[0] + \\\": \\\" + val + \\\"\\\\n\\\"\\n\\n string += \\\" }\\\\n}\\\\n\\\"\\n\\n return string\",\n \"def get_info(data):\\n # type: (dict) -> dict\\n item = data.get(\\\"item\\\", {})\\n plot = item.get(\\\"summary\\\", data.get(\\\"description\\\"))\\n if plot and isinstance(plot, list):\\n plot = plot[0]\\n # TODO : some-kind of duration calculation...\\n return {\\n \\\"title\\\": item.get(\\\"title\\\", \\\"\\\").title(),\\n \\\"plot\\\": plot,\\n \\\"year\\\": extract_year(item.get(\\\"date\\\", \\\"\\\")),\\n \\\"genre\\\": item.get(\\\"genre\\\")\\n }\",\n \"def Extract_MetaData(data, key):\\n return data.get(key)\",\n \"def getSubtitles(self):\\n\\n self.createSoupObject()\\n self.getcustomerID()\\n self.getToken()\\n self.getTitle()\\n\\n if self.debug:\\n print(self.title)\\n\\n self.getVideoType()\\n if self.debug:\\n print(self.videoType)\\n\\n if self.videoType == \\\"movie\\\":\\n\\n self.getAsinID1() # Method-1\\n if self.debug:\\n print(self.parametersDict['asin'])\\n\\n returnValue = self.standardFunctionCalls()\\n if returnValue != 1:\\n self.videoType = \\\"tv\\\"\\n\\n if self.videoType != \\\"movie\\\":\\n\\n self.getAsinID2()\\n if self.debug:\\n print(self.asinList)\\n\\n self.parametersDict['asin'] = self.asinList\\n currentTitle = self.title\\n\\n try:\\n returnValue = self.standardFunctionCalls()\\n except:\\n pass\\n self.title = currentTitle\\n\\n return returnValue\",\n \"def __getitem__(self, key):\\n return self.metadata_dict[key]\",\n \"def get_movie_data(doc_id, data):\\n doc_id = str(doc_id)\\n movie_object = {\\\"title\\\": data[doc_id]['Title'][0],\\n \\\"director\\\": data[doc_id]['Director'][0],\\n \\\"location\\\": data[doc_id]['Location'][0] if len(data[doc_id]['Location']) > 0 else data[doc_id]['Location'],\\n \\\"text\\\": data[doc_id]['Text']\\n }\\n return movie_object\",\n \"def generate_srt_from_sjson(sjson_subs, speed):\\r\\n\\r\\n output = ''\\r\\n\\r\\n equal_len = len(sjson_subs['start']) == len(sjson_subs['end']) == len(sjson_subs['text'])\\r\\n if not equal_len:\\r\\n return output\\r\\n\\r\\n sjson_speed_1 = generate_subs(speed, 1, sjson_subs)\\r\\n\\r\\n for i in range(len(sjson_speed_1['start'])):\\r\\n item = SubRipItem(\\r\\n index=i,\\r\\n start=SubRipTime(milliseconds=sjson_speed_1['start'][i]),\\r\\n end=SubRipTime(milliseconds=sjson_speed_1['end'][i]),\\r\\n text=sjson_speed_1['text'][i]\\r\\n )\\r\\n output += (unicode(item))\\r\\n output += '\\\\n'\\r\\n return output\",\n \"def subtitle(string):\\n print(\\\"{}\\\\n{}\\\\n\\\".format(bold(string), underline(string, \\\"-\\\")))\",\n \"def GetValue(self, key):\\n return self._metadata_dict[key]\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6290816","0.61481214","0.60934126","0.59526104","0.5819839","0.5644419","0.5638596","0.5580923","0.5557902","0.53163785","0.5266296","0.5250043","0.51997524","0.51850265","0.51807094","0.5156665","0.51562893","0.5116406","0.50712675","0.503532","0.49858674","0.49511912","0.4943421","0.49427328","0.4925962","0.49198818","0.48683915","0.48649934","0.4861258","0.48444584","0.48415032","0.48135668","0.48135483","0.48048285","0.47928953","0.4784513","0.4779737","0.47544092","0.47353533","0.4726998","0.47214815","0.47186136","0.4696495","0.46892962","0.4683177","0.4680129","0.4679521","0.46764493","0.46741033","0.46639776","0.46586025","0.465351","0.4652065","0.46505398","0.4646243","0.46452308","0.46438822","0.4641884","0.4631204","0.46291575","0.46288097","0.46123445","0.45925933","0.45794046","0.45692936","0.45662355","0.45655373","0.45646554","0.45628655","0.455931","0.4554957","0.455302","0.45518038","0.45500785","0.45399952","0.45367587","0.4525106","0.45191044","0.45185474","0.45006442","0.44995004","0.44972414","0.4496806","0.44917274","0.44891542","0.44890803","0.44888532","0.44887587","0.44867006","0.4486369","0.44854838","0.44838503","0.44709194","0.44598004","0.4456242","0.44554776","0.44541705","0.44470692","0.44455826","0.44435778"],"string":"[\n \"0.6290816\",\n \"0.61481214\",\n \"0.60934126\",\n \"0.59526104\",\n \"0.5819839\",\n \"0.5644419\",\n \"0.5638596\",\n \"0.5580923\",\n \"0.5557902\",\n \"0.53163785\",\n \"0.5266296\",\n \"0.5250043\",\n \"0.51997524\",\n \"0.51850265\",\n \"0.51807094\",\n \"0.5156665\",\n \"0.51562893\",\n \"0.5116406\",\n \"0.50712675\",\n \"0.503532\",\n \"0.49858674\",\n \"0.49511912\",\n \"0.4943421\",\n \"0.49427328\",\n \"0.4925962\",\n \"0.49198818\",\n \"0.48683915\",\n \"0.48649934\",\n \"0.4861258\",\n \"0.48444584\",\n \"0.48415032\",\n \"0.48135668\",\n \"0.48135483\",\n \"0.48048285\",\n \"0.47928953\",\n \"0.4784513\",\n \"0.4779737\",\n \"0.47544092\",\n \"0.47353533\",\n \"0.4726998\",\n \"0.47214815\",\n \"0.47186136\",\n \"0.4696495\",\n \"0.46892962\",\n \"0.4683177\",\n \"0.4680129\",\n \"0.4679521\",\n \"0.46764493\",\n \"0.46741033\",\n \"0.46639776\",\n \"0.46586025\",\n \"0.465351\",\n \"0.4652065\",\n \"0.46505398\",\n \"0.4646243\",\n \"0.46452308\",\n \"0.46438822\",\n \"0.4641884\",\n \"0.4631204\",\n \"0.46291575\",\n \"0.46288097\",\n \"0.46123445\",\n \"0.45925933\",\n \"0.45794046\",\n \"0.45692936\",\n \"0.45662355\",\n \"0.45655373\",\n \"0.45646554\",\n \"0.45628655\",\n \"0.455931\",\n \"0.4554957\",\n \"0.455302\",\n \"0.45518038\",\n \"0.45500785\",\n \"0.45399952\",\n \"0.45367587\",\n \"0.4525106\",\n \"0.45191044\",\n \"0.45185474\",\n \"0.45006442\",\n \"0.44995004\",\n \"0.44972414\",\n \"0.4496806\",\n \"0.44917274\",\n \"0.44891542\",\n \"0.44890803\",\n \"0.44888532\",\n \"0.44887587\",\n \"0.44867006\",\n \"0.4486369\",\n \"0.44854838\",\n \"0.44838503\",\n \"0.44709194\",\n \"0.44598004\",\n \"0.4456242\",\n \"0.44554776\",\n \"0.44541705\",\n \"0.44470692\",\n \"0.44455826\",\n \"0.44435778\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6423573"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":92982,"cells":{"query":{"kind":"string","value":"Function saves downloaded zip string on given path anf destroy self.zip_string if saveing is succesfull."},"document":{"kind":"string","value":"def save_downloaded_zip(self, dict_entry_to_download):\n\tif self.download_subtitle_zip(dict_entry_to_download) == True:\n\t try:\n\t\tzip_file = open(self.ZipFilePath,\"wb\")\n\t\tzip_file.write(self.zip_string)\n\t\tzip_file.close\t\t\n\t\tprint \"Zipfile: %s saved on hdd.\" % self.ZipFilePath\n\t\tdel self.zip_string\n\t\treturn True\n\t except:\n\t\tprint \"Problems with Zipfile: %s saveing on hdd.\" % self.ZipFilePath\n\t\treturn False"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def zipsave(self):\n\n filename = filedialog.asksaveasfilename(initialdir=self.root.cache_dir,\n title='Save As',\n filetypes=[('Zip', '.zip')],\n defaultextension='')\n self.save_entry.clear()\n self.save_entry.insert(tk.END, filename)\n self.root.cache_dir = filename","def save(self, d: pathlib.Path) -> pathlib.Path:\n p = self.local_path(d)\n if not p.exists():\n if self.path_in_zip:\n with zipfile.ZipFile(p, 'w', compression=zipfile.ZIP_DEFLATED) as zf:\n zf.writestr(self.path_in_zip, self.mimetype.write(self.read()))\n else:\n self.mimetype.write(self.read(), p)\n return p","def write_zip(self, zip_file, callback=None):\n\n def _cb(*args):\n if callback:\n callback(*args)\n\n try:\n _cb('zip-in-progress', True)\n curr_path = os.path.dirname(os.path.abspath(__file__))\n save_path = curr_path + \"/user_downloads\"\n\n if not os.path.exists(save_path):\n os.makedirs(save_path)\n\n name_of_file = \"gmail_images.zip\"\n full_file_name = os.path.join(save_path, name_of_file)\n fp = open(full_file_name, \"w\")\n fp.write(zip_file)\n fp.close()\n zip_file.close()\n _cb('zip-complete, True')\n _cb('write-zip', True, name_of_file)\n\n return True\n\n except:\n\n _cb('write-zip', False)\n\n return False","def finalize_zip(zip, filename):\n zip.close()\n with open(filename, 'wb') as file:\n file.write(zipbytes.getvalue())","def save(self, archive: Path):\n with zipfile.ZipFile(\n archive, mode=\"w\", compression=zipfile.ZIP_DEFLATED, compresslevel=9\n ) as zf:\n zf.writestr(\"data.json\", data=self.serialize())","def write_str_to_zipfile(zf, path, bytes, mode=0644):\n now = time.localtime(time.time())[:6]\n info = zipfile.ZipInfo(path)\n info.date_time = now\n info.compress_type = zipfile.ZIP_DEFLATED\n info.external_attr = (mode & 0xFFFF) << 16\n zf.writestr(info, bytes)","def download_zip(self, path: Path) -> Path:\n if not self.url:\n raise ValueError(\"Release must have a valid url to download the zip.\")\n\n with requests.get(self.url, stream=True) as response:\n with open(path, \"wb\") as download_file:\n shutil.copyfileobj(response.raw, download_file)\n\n return path","def save_zip(zip_file, archive_dir):\n zipdata = zipfile.ZipFile(zip_file, mode='w')\n\n for root, dirs, files in os.walk(archive_dir):\n for name in files:\n fname = os.path.join(root, name)\n zipdata.write(fname)\n zipdata.close()","def zip_compress(self, destination):\n\n if destination is not None and isinstance(destination, str):\n with ZipFile(destination, \"w\") as thezip:\n thezip.write(self.file)","def get_zip_writer(zipfile: ZipFile):\n dump_folder = CONF['packfile_dump', '']\n if not dump_folder:\n return zipfile.write\n\n dump_folder = os.path.abspath(dump_folder)\n\n # Delete files in the folder, but don't delete the folder itself.\n try:\n dump_files = os.listdir(dump_folder)\n except FileNotFoundError:\n pass\n else:\n for name in dump_files:\n name = os.path.join(dump_folder, name)\n if os.path.isdir(name):\n shutil.rmtree(name)\n else:\n os.remove(name)\n\n def write_to_zip(filename, arcname):\n dump_loc = os.path.join(dump_folder, arcname)\n os.makedirs(os.path.dirname(dump_loc), exist_ok=True)\n shutil.copy(filename, dump_loc)\n zipfile.write(filename, arcname)\n return write_to_zip","def write_to_path(self, path):\n assert not path.exists()\n fout = path.open(\"wb\")\n fout.write(self.to_string())\n assert not fout.close()\n path.setdata()","def open_writable_zipfile(path):\n try:\n return ZipFile(path, 'w', ZIP_DEFLATED)\n except RuntimeError: # pragma: nocover\n # zlib module not available\n return ZipFile(path, 'w')","def _download_zip(self, zip_url, dest_dir):\n # TODO(jsirois): Wrap with workunits, progress meters, checksums.\n self.context.log.info('Downloading {}...'.format(zip_url))\n sess = requests.session()\n sess.mount('file://', self.LocalFileAdapter())\n res = sess.get(zip_url)\n if not res.status_code == requests.codes.ok:\n raise TaskError('Failed to download {} ({} error)'.format(zip_url, res.status_code))\n\n with open_zip(BytesIO(res.content)) as zfile:\n safe_mkdir(dest_dir)\n for info in zfile.infolist():\n if info.filename.endswith('/'):\n # Skip directories.\n continue\n # Strip zip directory name from files.\n filename = os.path.relpath(info.filename, get_basedir(info.filename))\n f = safe_open(os.path.join(dest_dir, filename), 'w')\n f.write(zfile.read(info))\n f.close()","def download_zip_file(zip_remote, save_dir, force_overwrite, cleanup=False):\n zip_download_path = download_from_remote(zip_remote, save_dir, force_overwrite)\n unzip(zip_download_path, cleanup=cleanup)","def download_data():\n\n if not os.path.exists(zipfile_path):\n print(f'Downloading {config.download_url} to {zipfile_path}')\n urlretrieve(config.download_url, zipfile_path)\n print(f'Successfully downloaded {zipfile_path}')\n\n zip_ref = ZipFile(zipfile_path, 'r')\n zip_ref.extractall(config.raw_data_dir)\n zip_ref.close()\n\n os.rename(f\"{config.raw_data_dir}/cornell movie-dialogs corpus\", extracted_dir)","def get_zip_file(self):\n io = StringIO()\n zf = zipfile.ZipFile(io, \"w\")\n try:\n for track in self.get_tracks():\n zf.write(track.file_name,\n track.safe_file_name,\n zipfile.ZIP_DEFLATED)\n finally:\n zf.close()\n\n io.reset()\n io.seek(0, 2)\n length = io.tell()\n io.reset()\n return io,\\\n cleanse_filename(\"%s - %s.zip\" % (self.name, self.year)),\\\n length","def downloadData(self, strZipUrl: str) -> str:\n wget.download(strZipUrl, os.path.join(self.strDataDir, os.path.basename(strZipUrl)))\n\n return os.path.join(self.strDataDir, os.path.basename(strZipUrl))","def test_deferred_close_by_archive(self):\n z = ZipFile(self.f, 'w')\n o = z.writestream(FILENAMES[0])\n z.close()\n self.assertIsNotNone(z._a)\n self.assertIsNotNone(z._stream)\n if PY3:\n o.write('testdata')\n else:\n o.write(unicode('testdata'))\n o.close()\n self.assertIsNone(z._a)\n self.assertIsNone(z._stream)\n z.close()","def zip_data(self) -> None:\n zipf = zipfile.ZipFile('output.zip', 'w', zipfile.ZIP_DEFLATED)\n self._zipdir(self.path, zipf)\n zipf.close()","def get_file_into_zip(zip_path: str) -> str:\n\n # Read csv file from zip and save it as csv.\n with zipfile.ZipFile(zip_path) as zf:\n\n csv_file_in_zip = zf.namelist()[0]\n csv_path = zip_path.replace('zip', 'csv')\n\n with open(csv_path, \"wb\") as f:\n\n f.write(zf.read(csv_file_in_zip))\n\n\n os.remove(zip_path)\n\n zip_filename = zip_path.split('/')[-1]\n csv_filename = csv_path.split('/')[-1]\n\n print(f\"Extracting csv from zip... {zip_filename} Saving... {csv_filename}\")\n print(f\"Deleting... {zip_filename}\")\n\n return csv_path","def _zip_dir(path):\n file_path = '/tmp/iapydependencies-' + uuid.uuid1().hex + \".zip\"\n _make_archive(_get_dir_entries(path, True), file_path, path[0:path.rfind('/')])\n return file_path","def AddToZip(self, input_zip, output_zip, input_path=None):\n\n self.UnmountAll()\n\n common.ZipWriteStr(output_zip, \"META-INF/com/google/android/updater-script\",\n \"\\n\".join(self.script) + \"\\n\")\n\n if input_path is None:\n data = input_zip.read(\"OTA/bin/updater\")\n else:\n data = open(input_path, \"rb\").read()\n common.ZipWriteStr(output_zip, \"META-INF/com/google/android/update-binary\",\n data, perms=0o755)","def save(self, path):\n (folder, filename) = os.path.split(path)\n (name, extension) = os.path.splitext(filename)\n\n if not name:\n raise ValueError, \"name is required\"\n\n path = os.path.join(folder, name + self.extension)\n f = open(path, \"wb\")\n f.write(self.contents)\n f.close()\n\n return path","def download_file(url, path):\n file_name = path + url.split(\"/\")[-1]\n req = requests.get(url)\n zipped_info = req.content\n print(file_name)\n if not os.path.isfile(file_name):\n print(\"file doesnt exist, writing\", file_name)\n with open(file_name, 'wb') as f:\n f.write(zipped_info)\n else:\n print(\"file exists\", file_name)","def close(self) -> None:\n\n if self.closed:\n return\n\n if 'r' not in self.mode:\n if self.metadata is not None:\n self.writestr(self._distinfo_path(\"METADATA\"),\n str(self.metadata).encode())\n if self.wheeldata is not None:\n self.writestr(self._distinfo_path(\"WHEEL\"),\n str(self.wheeldata).encode())\n self._zip.writestr(self._distinfo_path(\"RECORD\"),\n str(self.record).encode())\n\n self._zip.close()","def save_file(save_dir, filename, data):\n logging.info('\\tSaving to... {}'.format(save_dir))\n if not os.path.isdir(save_dir):\n os.mkdir(save_dir)\n\n filepath = '{0}/{1}'.format(save_dir, filename)\n with open(filepath, 'w+') as outfile:\n json.dump(data, outfile)\n\n zipfilepath = filepath.replace('.json','.zip')\n with zipfile.ZipFile(zipfilepath, 'w', zipfile.ZIP_DEFLATED) as zf:\n zf.write(filepath)\n\n #os.remove(filepath)","def save(self):\n if self.hasChanged:\n filePath = self.path\n tempPath = filePath+'.tmp'\n fileDir = os.path.split(filePath)[0]\n if not os.path.exists(fileDir): os.makedirs(fileDir)\n cPickle.dump(self.data,open(tempPath,'w'))\n renameFile(tempPath,filePath,True)\n self.hasChanged = False","def _download_zip_model(model_url: str, model_path: str) -> str:\n if os.path.exists(model_path):\n return model_path\n extract_dir = os.path.dirname(model_path)\n url_model_name = os.path.basename(urlparse(model_url).path)\n tmp_zip_file_path = os.path.join(extract_dir, url_model_name)\n _download_file(model_url, tmp_zip_file_path)\n _unzip_file(tmp_zip_file_path, extract_dir)\n return model_path","def close(self):\n self.myzip.close()","def Extract_zip_file (path_to_zip,dir_to_save_into):\n with zipfile.ZipFile(path_to_zip) as zf:\n \n for member in tqdm(zf.namelist(), desc='Extracting'):\n try:\n if ('annotations' in member) and (member.endswith('.json')): \n zf.extract(member, dir_to_save_into)\n shutil.move(os.path.join(dir_to_save_into,member),dir_to_save_into)\n if ('train' in member):\n zf.extract(member, dir_to_save_into)\n if ('test' in member):\n zf.extract(member, dir_to_save_into)\n if ('val' in member):\n zf.extract(member, dir_to_save_into)\n except zipfile.error as e:\n pass\n\n #delete zip\n os.remove(path_to_zip)\n if(os.path.isdir(os.path.join(dir_to_save_into,'annotations'))):\n # remove the tmp annotations directory\n shutil.rmtree(os.path.join(dir_to_save_into,'annotations'))","def save_to_tmp(bucket, key, string=True):\n mode = 'w' if string else 'wb'\n \n # Get data:\n s3 = boto3.client('s3')\n a = s3.get_object(Bucket=bucket, Key=key)\n data = a['Body'].read()\n if string:\n data = data.decode('utf-8')\n \n # Save to temp folder:\n filename = '/tmp/' + key.split('/')[-1]\n with open(filename, mode) as f:\n f.write(data)\n \n return filename","def store_source(zipfile_name, directory, storage_directory):\n if directory in ZIP_EXCLUDES:\n zip_command = ['zip', '-x ' + '-x'.join(ZIP_EXCLUDES[directory]), '-r', zipfile_name, directory]\n else:\n zip_command = ['zip', '-r', zipfile_name, directory]\n\n if exists(zipfile_name):\n os.remove(zipfile_name)\n\n try:\n logging.debug('Zipping Source: %s', zip_command)\n check_output(zip_command)\n except CalledProcessError as build_error:\n logging.error('Could not zip source, Return Code %s, Command %s', build_error.returncode, build_error.cmd)\n logging.error(build_error.output)\n os.remove(zipfile_name)\n return False\n\n qmk_storage.save_file(zipfile_name, os.path.join(storage_directory, zipfile_name), 'application/zip')\n os.remove(zipfile_name)\n\n return True","def zip_file(file_path: str) -> str:\n zip_file_path: str = file_path + \".gz\"\n\n print(f\"Compressing {file_path} into {zip_file_path}\")\n timestamp=path.getmtime(file_path)\n with open(file_path, \"rb\") as read_stream:\n with gzip.open(zip_file_path, \"wb\") as write_stream:\n shutil.copyfileobj(read_stream, write_stream)\n os.utime(zip_file_path, (timestamp,timestamp) )\n\n return zip_file_path","def _create_zip_file(self) -> BytesIO:\n zip_file_io = BytesIO()\n with ZipFile(zip_file_io, 'w') as zip_file:\n for image_scraper_model in self._url_model.image_scraper.all():\n image_absolute_path = self._get_image_absolute_path(image_scraper_model)\n zip_file_image_path = self._get_zip_file_image_path(image_absolute_path)\n zip_file.write(image_absolute_path, zip_file_image_path)\n zip_file.close()\n return zip_file_io","def save(cls, name, string=False):\n if not string:\n pickle.dump(cls.__data[name], open(cls.dirpath + name + '.p', 'wb'))\n else:\n fd = open(cls.dirpath + name + '.txt', 'wb')\n fd.write(str(cls.__data[name]))\n fd.close()\n del cls.__data[name]","def save(self, export_path: str):","def save(self, path):\n pickle.dump(self, open(path, 'wb'))","def make_zip(self):\n shutil.make_archive(self.name, 'zip', self.name)","def _save_file(self, file_path, data):\n self._ensure_directory(os.path.dirname(file_path))\n with open(file_path, \"wb\") as f:\n f.write(data)","def WriteFinalize(self):\n if not self._file_object:\n raise IOError('Unable to write to closed serialized data stream.')\n\n offset = self._file_object.tell()\n self._file_object.close()\n self._file_object = None\n\n current_working_directory = os.getcwd()\n try:\n os.chdir(self._temporary_path)\n self._zip_file.write(self.name)\n finally:\n os.remove(self.name)\n os.chdir(current_working_directory)\n\n return offset","def writeFileToZip(zipFile, sourcePath, targetPath):\n targetPath = targetPath.replace(\"\\\\\", \"/\") # Zips use forward slashes\n utcTime = time.gmtime(os.stat(sourcePath).st_mtime)\n \n if os.path.isdir(sourcePath):\n if not targetPath.endswith(\"/\"):\n targetPath += \"/\" # Trailing slash denotes directory for some zip packages\n\n zi = zipfile.ZipInfo(targetPath, utcTime[0:6])\n zi.compress_type = zipfile.ZIP_DEFLATED\n zi.external_attr = 0x00000010L # FILE_ATTRIBUTE_DIRECTORY\n zipFile.writestr(zi, \"\")\n else: \n f = open(sourcePath, \"rb\")\n try:\n data = f.read()\n finally:\n f.close()\n \n zi = zipfile.ZipInfo(targetPath, utcTime[0:6])\n zi.compress_type = zipfile.ZIP_DEFLATED\n zi.external_attr = 0x00000020L # FILE_ATTRIBUTE_ARCHIVE\n zipFile.writestr(zi, data)","def writestr(self,\n zinfo_or_arcname: Union[ZipInfo, str],\n data: Union[bytes, str]) -> None:\n\n # XXX: ZipFile.writestr() does not normalize arcpaths the same way\n # ZipFile.write() does, and so this method won't do that either\n\n arcname = (\n zinfo_or_arcname.filename\n if isinstance(zinfo_or_arcname, ZipInfo)\n else zinfo_or_arcname\n )\n\n self._zip.writestr(zinfo_or_arcname, data)\n self.refresh_record(arcname)","def zip_single(source_path, destination_path, password):\n\n if not destination_path:\n destination_path = source_path\n\n if not destination_path.endswith(\".zip\"):\n suffix = destination_path.split(\".\")[1]\n if destination_path.endswith(\".\" + suffix):\n destination_path = destination_path.replace(\".\" + suffix, '')\n destination_path += \".zip\"\n\n if password:\n z = pyzipper.AESZipFile(destination_path, 'w', compression=pyzipper.ZIP_LZMA, encryption=pyzipper.WZ_AES)\n z.setpassword(password)\n else:\n z = pyzipper.ZipFile(destination_path, 'w', compression=pyzipper.ZIP_LZMA)\n\n try:\n z.write(source_path)\n print(f\"{destination_path} created successfully.\")\n except Exception:\n tb = traceback.format_exc()\n print(\"Something went wrong\")\n print(tb)\n finally:\n z.close()","def _open_zip(self):\n self.buffer = io.BytesIO()\n self.zf = zipfile.ZipFile(self.buffer, \"w\", zipfile.ZIP_DEFLATED)","def toZip(self, file, zip_location):\n zip_file = zipfile.ZipFile(zip_location, 'w')\n if os.path.isfile(file):\n zip_file.write(file)\n else:\n self.__addFolderToZip(zip_file, file)\n print \"Wrote %s to %s\"%(file,zip_location)\n zip_file.close()","def make_empty_zip(self):\n buffer = BytesIO()\n file = ZipFile(buffer, 'w')\n file.close()\n return buffer","def save_file(self, response):\r\n # Extract filename from response url\r\n filename = re.search('[^/]+(?=/$|$)', response.url).group(0)\r\n\r\n # Prepend download folder name to the filename\r\n filename = self.config[\"folder\"] + filename\r\n os.makedirs(os.path.dirname(filename), exist_ok=True)\r\n\r\n # Write contents to file\r\n with open(filename, 'wb') as f:\r\n f.write(response.content)\r\n\r\n # Print message displaying the absolute filepath for convenience\r\n print(\"Downloaded file to \" + os.path.abspath(filename))","def save(self, path):\n if path.endswith(\".gz\"):\n file = gzip.open(path, \"w\", 9)\n else:\n file = open(path, \"wb\")\n\n # update the settings in the data to the latest value\n data = json.loads(self.value)\n data[\"settings\"] = self.settings\n\n file.write(json.dumps(data).encode(\"utf8\"))\n file.close()","def _check_zip_file (filename, path_unzip, outfile) :\n assert path_unzip is not None\n file,ext = os.path.splitext (filename)\n ext = ext.lower ()\n if ext == \".gz\" :\n \n import gzip\n \n if outfile is None :\n dest = filename.split (\"!\")\n dest = dest [ len(dest)-1 ]\n ext = os.path.splitext (dest) [1]\n dest = dest.replace (ext, \".txt\")\n path = os.path.split (filename)\n path = \"/\".join (path [:len (path)-1])\n dest = path + \"/\" + dest\n else :\n dest = outfile\n \n if not os.path.exists (dest) :\n file = gzip.GzipFile (filename, \"r\")\n if outfile is None :\n dest = os.path.split (dest) [1]\n dest = os.path.join (path_unzip, dest)\n \n if os.path.exists (dest) :\n st1 = datetime.datetime.utcfromtimestamp (os.stat (filename).st_mtime)\n st2 = datetime.datetime.utcfromtimestamp (os.stat (dest).st_mtime)\n if st2 > st1 : \n fLOG (\"ungzipping file (already done)\", dest)\n return dest\n \n fLOG (\"ungzipping file\", dest)\n f = open (dest, \"w\")\n data = file.read (2**27)\n size = 0\n while len (data) > 0 :\n size += len (data)\n fLOG (\"ungzipping \", size, \"bytes\")\n if isinstance (data, bytes) : f.write (bytes.decode (data))\n else : f.write (data)\n data = file.read (2**27)\n f.close ()\n file.close ()\n \n return dest\n \n if ext == \".zip\" :\n \n import zipfile\n try :\n file = zipfile.ZipFile (filename, \"r\")\n except Exception as e :\n fLOG (\"problem with \", filename)\n raise e\n \n if len (file.infolist()) != 1:\n if outfile is not None :\n raise PQHException (\"the archive contains %d files and not one as you expected by filling outfile\" % len (file.infolist()))\n fLOG (\"unzip file (multiple) \", filename)\n #message = \"\\n\".join ([ fi.filename for fi in file.infolist() ] )\n #raise Exception.YstException(\"ColumnInfoSet.load_from_file: file %s contains no file or more than one file\\n\" + message)\n folder = os.path.split (filename) [0]\n todo = 0\n _zip7_path = r\"c:\\Program Files\\7-Zip\"\n zip7 = os.path.exists (_zip7_path)\n wait = [ ]\n for info in file.infolist () :\n fileinside = info.filename\n dest = os.path.join (folder, fileinside)\n if not os.path.exists (dest) :\n fol = os.path.split (dest) [0]\n if not os.path.exists (fol) : os.makedirs (fol)\n if os.path.exists (dest) :\n st1 = datetime.datetime.utcfromtimestamp (os.stat (filename).st_mtime)\n st2 = datetime.datetime.utcfromtimestamp (os.stat (dest).st_mtime)\n if st2 > st1 : \n continue\n \n if not sys.platform.startswith(\"win\") or not zip7 :\n data = file.read (fileinside)\n dest = os.path.split (dest) [1]\n dest = os.path.join (path_unzip, dest)\n fLOG (\"unzipping file\", dest)\n wait.append(dest)\n f = open (dest, \"w\")\n if isinstance (data, bytes) :\n f.write (str (data))\n else :\n f.write (data)\n f.close ()\n else :\n todo += 1\n \n if todo > 0 and zip7 :\n dest = os.path.realpath (path_unzip)\n cmd = '\"' + _zip7_path + '\\\\7z.exe\" e -y -o\"%s\" \"%s\"' % (dest, os.path.realpath (filename)) \n out,err = run_cmd (cmd, wait = True)\n if len (err) > 0 : raise PQHException (\"command {0} failed\\n{1}\".format(cmd,err))\n if \"Error\" in out : raise PQHException (\"command {0} failed\\n{1}\".format(cmd,out))\n else :\n dest = path_unzip\n \n file.close ()\n \n ch = False\n while not ch :\n ch = True\n for a in wait :\n if not os.path.exists(a) : \n ch = False\n break\n time.sleep(0.5)\n \n return dest\n \n else :\n for info in file.infolist () :\n fileinside = info.filename\n \n path = os.path.split (filename)\n dest = outfile if outfile is not None else path [0] + \"/\" + fileinside\n if not os.path.exists (dest) :\n data = file.read (fileinside)\n if outfile is None :\n dest = os.path.split (dest) [1]\n dest = os.path.join (path_unzip, dest)\n \n if os.path.exists (dest) :\n st1 = datetime.datetime.utcfromtimestamp (os.stat (filename).st_mtime)\n st2 = datetime.datetime.utcfromtimestamp (os.stat (dest).st_mtime)\n if st2 > st1 : \n fLOG(\"unzipping one file (already done)\", dest)\n return dest\n \n fLOG(\"unzipping one file\", dest)\n f = open (dest, \"w\")\n if isinstance (data, bytes) :\n f.write (bytes.decode (data))\n else :\n f.write (data)\n f.close ()\n file.close ()\n return dest\n \n return filename","def write(self, path_in_disk=None, compression=False, skip_disk=False, dest_path=None):\n\n # Don't double-path a file already in 'patched'\n if 'patched' not in self.filename:\n dest_path = path.join(self.dest_disk.dir, self.filename)\n else:\n if dest_path is None:\n dest_path = self.filename\n\n dest_path = dest_path.replace(\"original/\", \"\")\n print(\"dest_path is\", dest_path)\n\n with open(dest_path, 'wb') as fileopen:\n fileopen.write(self.filestring)\n\n if compression:\n print('compressing now')\n compressed_path = compress(dest_path)\n print(compressed_path)\n dest_path = compressed_path\n\n if not skip_disk:\n print(\"inserting:\", dest_path)\n self.dest_disk.insert(dest_path, path_in_disk=path_in_disk)\n return dest_path","def save_log_file(save_file_name, save_file_bytes):\n cwd = getcwd() # Gets Current Working Directory\n log_dir = cwd + \"/\" + \"Logs\"\n if not exists(log_dir):\n mkdir(log_dir)\n log_file_path = log_dir + \"/\" + save_file_name + \".zip\"\n with open(log_file_path, \"wb\") as f:\n f.write(save_file_bytes)\n return log_file_path","def backup(self):\n if self.url is not None:\n\n # zip backup folder\n zipapp.create_archive(self.logs_directory, self.send_zip)\n\n # then send zipped folder to the URL\n try:\n requests.post(self.url, files={\n 'uploaded_file': (os.path.basename(self.send_zip), open(self.send_zip, 'rb')),\n })\n except requests.exceptions.ConnectionError as error:\n print(error)","def save(self, path):\n f = open(path, 'w')\n f.write(self.content().encode('utf-8'))\n f.close()","def save(self, path, name=None):\n if not os.path.exists(path):\n os.makedirs(path)\n name = name or self.name\n path = os.path.join(path, name)\n with open(path, 'wb') as pickle_file:\n pickle.dump(self, pickle_file)","def extract_and_clean(zipper, zip_path, filename):\n zipper.extract(zip_path)\n if \"/\" in zip_path :\n os.rename(zip_path, filename)\n shutil.rmtree(zip_path.split('/')[0])","def _maybe_download_and_extract(self, filename):\n if not os.path.exists(self.work_dir):\n os.mkdir(self.work_dir)\n filepath = os.path.join(self.work_dir, filename)\n if not os.path.exists(filepath):\n filepath, _ = urllib.urlretrieve(self.url + filename, filepath)\n statinfo = os.stat(filepath)\n log.info('Successfully downloaded', filename, statinfo.st_size,\n 'bytes.')\n log.info('Extracting zip file ... ')\n f = zipfile.ZipFile(filepath)\n f.extractall(path=self.work_dir)\n log.info('Extraction finished ... ')","def save(self, path):\n with tempfile.TemporaryDirectory() as td:\n U.save_state(os.path.join(td, \"model\"))\n arc_name = os.path.join(td, \"packed.zip\")\n with zipfile.ZipFile(arc_name, 'w') as zipf:\n for root, dirs, files in os.walk(td):\n for fname in files:\n file_path = os.path.join(root, fname)\n if file_path != arc_name:\n zipf.write(file_path, os.path.relpath(file_path, td))\n with open(arc_name, \"rb\") as f:\n model_data = f.read()\n with open(path, \"wb\") as f:\n dill.dump((model_data, self._act_params), f)","def save_zip_of_df(df, dst_zip_path):\n dst_zip_path = Path(dst_zip_path)\n df.to_csv(dst_zip_path,\n compression=dict(method=\"zip\", archive_name=dst_zip_path.with_suffix(\".csv\").name))\n return dst_zip_path","def extract_file(self):\n# path_destination = os.path.join(\n# self.root, self.resources.replace(\".zip\", \"\"))\n# os.makedirs(path_destination, exist_ok=True)\n shutil.unpack_archive(os.path.join(\n self.root, self.resources), self.root)\n os.remove(os.path.join(self.root, self.resources))","def save_to_file(self, string):\n with open(self.output_path, \"w\") as text_file:\n text_file.write(string)\n print \"Saved to file \" + self.output_path","def compressIfNeeded(self):\n\n if self._mode == \"zip\":\n zip_folder(self._rootExportPath, self.getZipArchiveFullPath())","def save(self, path):\n if isinstance(path, str) and path.startswith(\"s3://\"):\n raise NotImplementedError(\"TODO: Implement saving to s3\")\n path = Path(path).resolve()\n \n # Make a folder to save things into\n if path.suffix == \".zip\":\n folder = path.parent / f\"tmp_{path.stem}\"\n else:\n folder = path\n folder.mkdir(parents=True, exist_ok=False)\n \n # Save the trace - ugly hack needed due to multiindex not being supported yet\n ifd = self.ifd_.copy()\n ifd.constant_data = ifd.constant_data.reset_index('idx')\n ifd.observed_data = ifd.observed_data.reset_index('idx')\n ifd.prior_predictive = ifd.prior_predictive.reset_index('idx')\n ifd.posterior_predictive = ifd.posterior_predictive.reset_index('idx')\n ifd.log_likelihood = ifd.log_likelihood.reset_index('idx')\n az.to_netcdf(ifd, folder / \"ifd.nc\")\n \n # Save other data\n self.C_mean_.rename(\"C_mean_\").to_csv(folder / \"C_mean_.csv\")\n self.C_std_.rename(\"C_std_\").to_csv(folder / \"C_std_.csv\")\n \n if path.suffix == \".zip\":\n # Save to zip\n zf = ZipFile(path, mode='w')\n for file in folder.glob(\"*\"):\n zf.write(folder / file.name, arcname=file.name)\n zf.close()\n shutil.rmtree(folder)","def save(self, path: str):\n pass","def GetAndSave(self, url, save_suffix, unzip=False):\n self.connection.request('GET',\n '/data/' + url,\n headers={'content-type': 'text/plain'})\n response = self.connection.getresponse()\n file_name = Clean(url) + save_suffix\n destination = os.path.join(self.path, file_name)\n\n if response.status != 200:\n raise IOError(url)\n\n if unzip:\n s = StringIO.StringIO(response.read())\n content = gzip.GzipFile(fileobj=s).read()\n else:\n content = response.read()\n\n with open(destination, 'w') as f:\n f.write(content)\n return content","def zipdir(path, zippath):\n execStr = ['zip', '-r',zippath, path]\n print ' '.join(execStr)\n proc = subprocess.Popen(execStr, stdout=PIPE, stderr=PIPE)\n (output, error) = proc.communicate()\n if error: print 'error: ', error\n print 'output: ', output","def _save_file(json_response, path, filename):\n if path is not None:\n if path[-1] != \"/\":\n path = path+\"/\"\n filepath = os.path.join(path, filename)\n if not os.path.exists(path):\n os.makedirs(path)\n\n with open(filepath+'.json', 'w') as output_file:\n output_file.write(json_response.text)","def save(self, hash_str, mime_type):\n if not os.path.exists(self.path):\n os.makedirs(self.path)\n data = self._get_resource_by_hash(hash_str)\n file_name = hash_str + MIME_TO_EXTESION_MAPPING[mime_type]\n file_path = os.path.join(self.path, file_name)\n if not os.path.isfile(file_path):\n with open(file_path, \"w\") as f:\n f.write(data)\n return \"file://\" + file_path","def make_zip_file(self, post_content):\n file_path, file_url = self.save_file(post_content['shortcode'] + '.zip', self.make_empty_zip())\n with ZipFile(file_path, 'w') as zipf:\n if post_content['igtv'] is True:\n zipf.writestr('igtv_link.txt', post_content['urls'][0][2])\n else:\n for url in post_content['urls']:\n zipf.writestr(self.get_content_name(url[2]), requests.get(url[2]).content)\n\n if 'text' in post_content:\n zipf.writestr('caption.txt', post_content['text'])\n return file_url","def zip_mail(self, comp_filename, zip_path, destination=''):\r\n\r\n pass\r\n # TODO Remodel this.\r","def save_string(cls, name, string):\n fd = open(cls.dirpath + name + '.txt', 'wb')\n fd.write(string)\n fd.close()","def download_zip(url, folder=None):\n\n # get this file folder name and save the file name\n if not folder:\n folder = os.path.dirname(os.path.abspath(__file__))\n file_name = os.path.split(url)[1]\n\n # Download the file from \"url\" and save it locally under \"file_name\":\n try:\n with urllib.request.urlopen(url) as response, open(folder + \"/\" + file_name, 'wb') as out_file:\n shutil.copyfileobj(response, out_file)\n except urllib.error.URLError as e:\n print('urllib.error.URLError')\n raise Exception(e)\n except Exception as e:\n raise Exception(e)\n else:\n return folder,file_name","def download_data(self):\n headers = {'User-Agent': 'Mozilla/5.0',}\n\n #Request for html data of url page\n r = requests.get(self.url, headers = headers, allow_redirects=True)\n soup = BeautifulSoup(r.text, \"html.parser\")\n\n #Checking if folder path exists, if not, creats it\n i=0\n while i<len(self.folder)-1:\n if self.folder[i] == '/':\n if not os.path.isdir(self.folder[:i]):\n os.mkdir(self.folder[:i])\n i+=1\n if i==len(self.folder)-1:\n if not os.path.isdir(self.folder):\n os.mkdir(self.folder)\n\n # if not os.path.isdir(self.folder):\n # os.mkdir(self.folder)\n\n #Gets every href to zip file with data\n entries = []\n for link in soup.find_all('a'):\n if re.search(\"^data/.*.zip\", link.get('href')):\n entries.append(link.get('href'))\n\n #Gets the newest dataset\n self.getCurrentData(entries)\n\n i=0\n #Saves each file in dataset\n for list in self.ListOfZipFiles:\n if not os.path.isfile(self.folder+list[4:]):\n r = requests.get(self.url+list)\n open(self.folder+list[4:], 'wb').write(r.content)\n #deletes prefix \"data/\"\n self.ListOfZipFiles[i] = list[4:]\n i+=1","def getzip(url, zipfile, unzipdir):\n done_file = os.path.join(unzipdir, '.'+os.path.basename(zipfile)+'.done')\n if file_exists(done_file):\n print('{} already downloaded and extracted; skipping. To reinstall \"rm {}\"'.format(os.path.basename(zipfile), done_file))\n else:\n print('Downloading {} as {}.'.format(url, zipfile))\n urlretrieve(url, zipfile)\n print('Extracting {} into {}.'.format(zipfile, unzipdir))\n with ZipFile(zipfile, 'r') as zip:\n zip.extractall(unzipdir)\n os.remove(zipfile)\n with open(done_file, 'w'):\n pass","def test_writepath_directory(self):\n z = ZipFile(self.f, 'w')\n z.writepath(None, pathname='/testdir', folder=True)\n z.writepath(None, pathname='/testdir/testinside', folder=True)\n z.close()\n self.f.close()\n\n f = open(ZIPPATH, mode='r')\n z = ZipFile(f, 'r')\n\n entries = z.infolist()\n\n assert len(entries) == 2\n assert entries[0].isdir()\n z.close()\n f.close()","def zipfile(filepath, cleanup=False):\n\tzfile = filepath+\".gz\"\n\twith open(filepath, 'rb') as f_in:\n\t\twith gzip.open(zfile, 'wb') as f_out:\n\t\t\tf_out.writelines(f_in)\t\n\t\n\tif cleanup and file_exists(zfile):\n\t\tos.remove(filepath)\n\treturn zfile","def save_into_html_file(path_html_file: str, response):\n html_file = open(path_html_file, 'w')\n html_file.writelines(response)\n html_file.close()\n\n with zipfile.ZipFile(path_html_file.replace('.html', '.zip'), 'w') as zf:\n zf.write(path_html_file, compress_type=zipfile.ZIP_DEFLATED)\n zf.close()\n os.remove(path_html_file)","def create_zip(self, db, submission, request, logger, passwd=None,\r\n mat_dir=None, no_subdirs=None):\r\n if db(db.material.leak_id==submission.id).select().first():\r\n try:\r\n filedir = str(db(db.submission.leak_id==submission.id).select(\r\n db.submission.dirname).first().dirname)\r\n filedir = os.path.join(request.folder, \"material\", filedir)\r\n except:\r\n logger.error('create_zip: invalid filedir')\r\n return dict(error='invalid filedir')\r\n err = None\r\n try:\r\n # XXX should need some refactoring\r\n if not mat_dir:\r\n mat_dir = filedir\r\n splitted = os.path.split(mat_dir)\r\n if splitted[-1].isdigit():\r\n filedir = \"%s-%s\" % (splitted[-2], splitted[-1])\r\n if no_subdirs:\r\n save_file = filedir + \"-0\"\r\n # get only files, no subdirectories\r\n files = [f for f in os.listdir(mat_dir)\r\n if not os.path.isdir(os.path.join(mat_dir, f))]\r\n else:\r\n save_file = filedir\r\n files = os.listdir(mat_dir)\r\n # XXX: issue #51\r\n if passwd and os.path.exists(mat_dir):\r\n logger.error('Encrypted ZIP function disabled, due to security redesign needs')\r\n return 0\r\n # cmd = 'zip -e -P%(passwd) %(zipfile).zip %(files)' % dict(\r\n # passwd=passwd, zipfile=filedir,\r\n # files=\" \".join(files))\r\n # subprocess.check_call(cmd.split())\r\n elif not passwd and os.path.exists(mat_dir):\r\n zipf = zipfile.ZipFile(save_file+'.zip', 'w')\r\n for f in files:\r\n path = os.path.join(mat_dir, f)\r\n zipf.write(path, f)\r\n subdirs = os.walk(path)\r\n for subdir in subdirs:\r\n inner_subdir = os.path.split(subdir[0])[-1]\r\n if not inner_subdir.isdigit():\r\n inner_subdir = \"\"\r\n for subfile in subdir[2]:\r\n zipf.write(os.path.join(subdir[0], subfile),\r\n os.path.join(inner_subdir,subfile))\r\n else:\r\n logger.error('create_zip: invalid path')\r\n except RuntimeError as err:\r\n logger.error('create_zip: error in creating zip')\r\n try:\r\n zipf.close()\r\n except (RuntimeError, zipfile.error) as err:\r\n logger.info('create_zip: error when trying to save zip')\r\n except subprocess.CalledProcessError as err :\r\n logger.error('create_zip: error in creating zip')\r\n finally:\r\n return dict(error=err) if err else None","def save(self,cookie_jar):\n if not os.path.exists(self.path):\n os.makedirs(self.path)\n with open(self.file_path, \"wb\") as cookie_file:\n cookie_file.write(bytearray(pickle.dumps(cookie_jar)))","def save(self, path):\n np.savez_compressed(path, **self.model_dict)","def download_file(self, name):\n #TODO: handle exceptions\n archive_name = name + \".json.gz\"\n file_name = join(self.new_data_dir, name + \".json\")\n\n try:\n urlretrieve(\"http://data.githubarchive.org/\" + archive_name,\n filename=join(self.downloaded_data_dir, archive_name))\n except IOError:\n self.logger.error(__name__ + \": \" + \"unable to download file (error creating connection).\")\n\n try:\n archive = gz_open(join(self.downloaded_data_dir, archive_name))\n except IOError:\n self.logger.error(__name__ + \": \" + \"unable to open gzipped file (file not created).\")\n else:\n json_file = open(file_name, \"w\")\n json_file.write(archive.read())\n\n archive.close()\n json_file.close()\n\n remove(join(self.downloaded_data_dir, archive_name))\n\n return file_name","def save(self, filename):\n import pickle\n if path.dirname(filename) and not path.exists(path.dirname(filename)):\n makedirs(path.dirname(filename))\n pickle.dump(self, open(filename, 'wb'), protocol=-1)","def zip_data_file(task_id, task_name, data_path):\n zip_file_dir = os.path.join(FILE_PATH, task_id + \".zip\")\n file = zipfile.ZipFile(zip_file_dir, \"w\", zipfile.ZIP_DEFLATED)\n sample_path = os.path.join(data_path, \"datasets\", str(task_id) + \"_\" + task_name + \".csv\")\n true_dag_path = os.path.join(data_path, \"true\", str(task_id) + \"_\" + task_name + \".npz\")\n file.write(sample_path)\n file.write(true_dag_path)\n file.close()\n return zip_file_dir","def save(self, filename = 'array_zest', path = '/home/eric/dev/insitu/data/zs_recovery/'):\n filename = filename# + '_Lx_' + str(self.Lx) + 'm_Ly_' + str(self.Ly) + 'm'\n self.path_filename = path + filename + '.pkl'\n f = open(self.path_filename, 'wb')\n pickle.dump(self.__dict__, f, 2)\n f.close()","def save(self, path):\n with open(path, 'wb') as f:\n pkl.dump(self, f)","def save(self, path):\n pass","def save(self, path):\n pass","def save(self, path):\n pass","def compress_experiment(self, exp_id):\n exp_folder = self.um.experiment_path(str(exp_id))[:-1]\n exp_folder = os.path.join(os.path.dirname(\n os.path.realpath(__file__)), exp_folder)\n archive_name = os.path.join(os.path.dirname(os.path.realpath(__file__)),\n \"backup\", str(exp_id)+\".zip\")\n\n print exp_folder, archive_name\n retval = self.um.compress_folder_zip(exp_folder, archive_name)\n if retval:\n return \"Success\"\n else:\n return \"Failure\"","def save(self, path):\n print(\"Warning: Default save used\")\n with open(path, 'wb') as f:\n pickle.dump(self, f)","def localpath_download(self, *path, **kwargs):\n pathname = self.localpath(*path)\n if not os.path.exists(pathname):\n self.download.unwrapped(self, *path, **kwargs)\n return pathname","def download(self):\n if not os.path.isdir(self.save_path):\n try:\n os.mkdir(self.save_path)\n except IOError:\n print(\"Can't create subfolder. \"\n \"Check that you have write access for \"\n \"{}\".format(self.save_path))\n\n sub_zip_file = request.urlopen(self.download_link)\n sub_gzip = gzip.GzipFile(fileobj=StringIO(sub_zip_file.read()))\n subtitle_content = sub_gzip.read()\n try:\n with open(self.full_path, 'wb') as subtitle_output:\n subtitle_output.write(subtitle_content)\n print(\"Downloaded subtitle...\")\n except IOError:\n print(\"Couldn't save subtitle, permissions issue?\")","def picklesave(obj, path):\n with open(path, 'wb') as file:\n pickle.dump(obj, file)","def check_request_and_create_zipfile() -> None:\n\n session = DBSession()\n\n for site_page in session.query(SitePage).filter(SitePage.status != STATUS_ARCHIVE_READY):\n data = create_zipfile(url_page=site_page.url)\n\n site_page.zipfile = pickle.dumps(data)\n site_page.status = STATUS_ARCHIVE_READY\n session.add(site_page)\n session.commit()\n\n session.close()","def zipdata(filename: str) -> None:\n\n # Generate the path to the project TODO: check if this is entire project or server\n directoryName = ROOT.split(\"/\")[-3]\n codeDestination = \"/\".join(ROOT.split(\"/\")[:-2])\n\n # Create the output file\n zippedFile = zipfile.ZipFile(filename, \"w\", compression=zipfile.ZIP_DEFLATED)\n\n # Walk over the directory and save all files\n for abspath, dirnames, filenames in os.walk(codeDestination):\n local = abspath[abspath.index(directoryName):]\n [zippedFile.write(os.path.join(abspath, name), os.path.join(local, name)) for name in filenames]\n\n # Close the zip file\n zippedFile.close()","def ZipResultFolder(md5_key, cnt):\n subfoldername = md5_key[:2]\n md5_subfolder = \"%s/%s\"%(path_cache, subfoldername)\n cachedir = \"%s/%s/%s\"%(path_cache, subfoldername, md5_key)\n zipfile_cache = cachedir + \".zip\"\n if os.path.exists(cachedir) and not os.path.exists(zipfile_cache):\n origpath = os.getcwd()\n os.chdir(md5_subfolder)\n targetfile = os.path.join(cachedir, \"query.result.txt\")\n if os.path.exists(targetfile):\n cmd = [\"zip\", \"-rq\", \"%s.zip\"%(md5_key), md5_key]\n cmdline = \" \".join(cmd)\n try:\n print((\"%d: %s\"%(cnt, cmdline)))\n subprocess.check_call(cmd)\n print((\"%d: %s\"%(cnt, \"rmtree(%s)\"%(md5_key) )))\n os.system(\"chown %s:%s %s\"%(user, group, \"%s.zip\"%(md5_key)))\n shutil.rmtree(md5_key)\n except:\n print(\"Failed to zip folder %s\"%(cachedir), file=sys.stderr)\n raise\n else:\n print((\"%d: %s\"%(cnt, \"bad result! just rmtree(%s)\"%(md5_key) )))\n shutil.rmtree(md5_key)\n os.chdir(origpath)\n elif os.path.exists(zipfile_cache):\n #check weather the zipped file is a valid prediction result\n try:\n with ZipFile(zipfile_cache, \"rb\") as myzip:\n li = myzip.namelist()\n target = \"%s/query.result.txt\"%(md5_key)\n if target in li:\n print((\"%d: %s\"%(cnt, \"Valid zipped result for %s\"%(md5_key) )))\n else:\n print((\"%d: %s\"%(cnt, \"bad zipped result! just delete zipfile(%s)\"%(md5_key) )))\n os.remove(zipfile_cache)\n except Exception as e:\n print((\"%d: %s\"%(cnt, \"BadZipFile! just delete zipfile(%s)\"%(md5_key) )))\n os.remove(zipfile_cache)","def download_zipped_model(manifest, assert_hash=False):\n zipped_model_path = manifest[\"model_filepath\"]\n zipped_model = client.file(zipped_model_path).getFile().name\n if assert_hash:\n assert_model_md5(zipped_model)\n return zipped_model_path","def getZipArchiveFullPath(self):\n\n if self._mode == \"zip\":\n return self._rootExportPath + \".zip\"\n\n return \"\"","def zip_dir(path: str, zip_filename: str) -> None:\n with zipfile.ZipFile(zip_filename, \"w\", zipfile.ZIP_DEFLATED) as zip_file:\n for root, dirs, files in os.walk(path):\n for file in files:\n f = os.path.join(root, file)\n zip_file.write(f, f[len(path) :])","def write_filepath(self, filename, file_format='FASTA', zipout=False):\n \n file_obj = open_with_intermediates(filename,'w')\n if zipout:\n file_obj.close()\n file_obj = StringIO()\n self.write(file_obj, file_format=file_format)\n if zipout:\n import gzip\n file_obj_gz = gzip.open(filename, \"wb\", 6)\n file_obj_gz.write(str.encode(file_obj.getvalue()))\n file_obj_gz.close()\n file_obj.close()","def write_filepath(self, filename, file_format='FASTA', zipout=False):\n \n file_obj = open_with_intermediates(filename,'w')\n if zipout:\n file_obj.close()\n file_obj = StringIO()\n self.write(file_obj, file_format=file_format)\n if zipout:\n import gzip\n file_obj_gz = gzip.open(filename, \"wb\", 6)\n file_obj_gz.write(str.encode(file_obj.getvalue()))\n file_obj_gz.close()\n file_obj.close()"],"string":"[\n \"def zipsave(self):\\n\\n filename = filedialog.asksaveasfilename(initialdir=self.root.cache_dir,\\n title='Save As',\\n filetypes=[('Zip', '.zip')],\\n defaultextension='')\\n self.save_entry.clear()\\n self.save_entry.insert(tk.END, filename)\\n self.root.cache_dir = filename\",\n \"def save(self, d: pathlib.Path) -> pathlib.Path:\\n p = self.local_path(d)\\n if not p.exists():\\n if self.path_in_zip:\\n with zipfile.ZipFile(p, 'w', compression=zipfile.ZIP_DEFLATED) as zf:\\n zf.writestr(self.path_in_zip, self.mimetype.write(self.read()))\\n else:\\n self.mimetype.write(self.read(), p)\\n return p\",\n \"def write_zip(self, zip_file, callback=None):\\n\\n def _cb(*args):\\n if callback:\\n callback(*args)\\n\\n try:\\n _cb('zip-in-progress', True)\\n curr_path = os.path.dirname(os.path.abspath(__file__))\\n save_path = curr_path + \\\"/user_downloads\\\"\\n\\n if not os.path.exists(save_path):\\n os.makedirs(save_path)\\n\\n name_of_file = \\\"gmail_images.zip\\\"\\n full_file_name = os.path.join(save_path, name_of_file)\\n fp = open(full_file_name, \\\"w\\\")\\n fp.write(zip_file)\\n fp.close()\\n zip_file.close()\\n _cb('zip-complete, True')\\n _cb('write-zip', True, name_of_file)\\n\\n return True\\n\\n except:\\n\\n _cb('write-zip', False)\\n\\n return False\",\n \"def finalize_zip(zip, filename):\\n zip.close()\\n with open(filename, 'wb') as file:\\n file.write(zipbytes.getvalue())\",\n \"def save(self, archive: Path):\\n with zipfile.ZipFile(\\n archive, mode=\\\"w\\\", compression=zipfile.ZIP_DEFLATED, compresslevel=9\\n ) as zf:\\n zf.writestr(\\\"data.json\\\", data=self.serialize())\",\n \"def write_str_to_zipfile(zf, path, bytes, mode=0644):\\n now = time.localtime(time.time())[:6]\\n info = zipfile.ZipInfo(path)\\n info.date_time = now\\n info.compress_type = zipfile.ZIP_DEFLATED\\n info.external_attr = (mode & 0xFFFF) << 16\\n zf.writestr(info, bytes)\",\n \"def download_zip(self, path: Path) -> Path:\\n if not self.url:\\n raise ValueError(\\\"Release must have a valid url to download the zip.\\\")\\n\\n with requests.get(self.url, stream=True) as response:\\n with open(path, \\\"wb\\\") as download_file:\\n shutil.copyfileobj(response.raw, download_file)\\n\\n return path\",\n \"def save_zip(zip_file, archive_dir):\\n zipdata = zipfile.ZipFile(zip_file, mode='w')\\n\\n for root, dirs, files in os.walk(archive_dir):\\n for name in files:\\n fname = os.path.join(root, name)\\n zipdata.write(fname)\\n zipdata.close()\",\n \"def zip_compress(self, destination):\\n\\n if destination is not None and isinstance(destination, str):\\n with ZipFile(destination, \\\"w\\\") as thezip:\\n thezip.write(self.file)\",\n \"def get_zip_writer(zipfile: ZipFile):\\n dump_folder = CONF['packfile_dump', '']\\n if not dump_folder:\\n return zipfile.write\\n\\n dump_folder = os.path.abspath(dump_folder)\\n\\n # Delete files in the folder, but don't delete the folder itself.\\n try:\\n dump_files = os.listdir(dump_folder)\\n except FileNotFoundError:\\n pass\\n else:\\n for name in dump_files:\\n name = os.path.join(dump_folder, name)\\n if os.path.isdir(name):\\n shutil.rmtree(name)\\n else:\\n os.remove(name)\\n\\n def write_to_zip(filename, arcname):\\n dump_loc = os.path.join(dump_folder, arcname)\\n os.makedirs(os.path.dirname(dump_loc), exist_ok=True)\\n shutil.copy(filename, dump_loc)\\n zipfile.write(filename, arcname)\\n return write_to_zip\",\n \"def write_to_path(self, path):\\n assert not path.exists()\\n fout = path.open(\\\"wb\\\")\\n fout.write(self.to_string())\\n assert not fout.close()\\n path.setdata()\",\n \"def open_writable_zipfile(path):\\n try:\\n return ZipFile(path, 'w', ZIP_DEFLATED)\\n except RuntimeError: # pragma: nocover\\n # zlib module not available\\n return ZipFile(path, 'w')\",\n \"def _download_zip(self, zip_url, dest_dir):\\n # TODO(jsirois): Wrap with workunits, progress meters, checksums.\\n self.context.log.info('Downloading {}...'.format(zip_url))\\n sess = requests.session()\\n sess.mount('file://', self.LocalFileAdapter())\\n res = sess.get(zip_url)\\n if not res.status_code == requests.codes.ok:\\n raise TaskError('Failed to download {} ({} error)'.format(zip_url, res.status_code))\\n\\n with open_zip(BytesIO(res.content)) as zfile:\\n safe_mkdir(dest_dir)\\n for info in zfile.infolist():\\n if info.filename.endswith('/'):\\n # Skip directories.\\n continue\\n # Strip zip directory name from files.\\n filename = os.path.relpath(info.filename, get_basedir(info.filename))\\n f = safe_open(os.path.join(dest_dir, filename), 'w')\\n f.write(zfile.read(info))\\n f.close()\",\n \"def download_zip_file(zip_remote, save_dir, force_overwrite, cleanup=False):\\n zip_download_path = download_from_remote(zip_remote, save_dir, force_overwrite)\\n unzip(zip_download_path, cleanup=cleanup)\",\n \"def download_data():\\n\\n if not os.path.exists(zipfile_path):\\n print(f'Downloading {config.download_url} to {zipfile_path}')\\n urlretrieve(config.download_url, zipfile_path)\\n print(f'Successfully downloaded {zipfile_path}')\\n\\n zip_ref = ZipFile(zipfile_path, 'r')\\n zip_ref.extractall(config.raw_data_dir)\\n zip_ref.close()\\n\\n os.rename(f\\\"{config.raw_data_dir}/cornell movie-dialogs corpus\\\", extracted_dir)\",\n \"def get_zip_file(self):\\n io = StringIO()\\n zf = zipfile.ZipFile(io, \\\"w\\\")\\n try:\\n for track in self.get_tracks():\\n zf.write(track.file_name,\\n track.safe_file_name,\\n zipfile.ZIP_DEFLATED)\\n finally:\\n zf.close()\\n\\n io.reset()\\n io.seek(0, 2)\\n length = io.tell()\\n io.reset()\\n return io,\\\\\\n cleanse_filename(\\\"%s - %s.zip\\\" % (self.name, self.year)),\\\\\\n length\",\n \"def downloadData(self, strZipUrl: str) -> str:\\n wget.download(strZipUrl, os.path.join(self.strDataDir, os.path.basename(strZipUrl)))\\n\\n return os.path.join(self.strDataDir, os.path.basename(strZipUrl))\",\n \"def test_deferred_close_by_archive(self):\\n z = ZipFile(self.f, 'w')\\n o = z.writestream(FILENAMES[0])\\n z.close()\\n self.assertIsNotNone(z._a)\\n self.assertIsNotNone(z._stream)\\n if PY3:\\n o.write('testdata')\\n else:\\n o.write(unicode('testdata'))\\n o.close()\\n self.assertIsNone(z._a)\\n self.assertIsNone(z._stream)\\n z.close()\",\n \"def zip_data(self) -> None:\\n zipf = zipfile.ZipFile('output.zip', 'w', zipfile.ZIP_DEFLATED)\\n self._zipdir(self.path, zipf)\\n zipf.close()\",\n \"def get_file_into_zip(zip_path: str) -> str:\\n\\n # Read csv file from zip and save it as csv.\\n with zipfile.ZipFile(zip_path) as zf:\\n\\n csv_file_in_zip = zf.namelist()[0]\\n csv_path = zip_path.replace('zip', 'csv')\\n\\n with open(csv_path, \\\"wb\\\") as f:\\n\\n f.write(zf.read(csv_file_in_zip))\\n\\n\\n os.remove(zip_path)\\n\\n zip_filename = zip_path.split('/')[-1]\\n csv_filename = csv_path.split('/')[-1]\\n\\n print(f\\\"Extracting csv from zip... {zip_filename} Saving... {csv_filename}\\\")\\n print(f\\\"Deleting... {zip_filename}\\\")\\n\\n return csv_path\",\n \"def _zip_dir(path):\\n file_path = '/tmp/iapydependencies-' + uuid.uuid1().hex + \\\".zip\\\"\\n _make_archive(_get_dir_entries(path, True), file_path, path[0:path.rfind('/')])\\n return file_path\",\n \"def AddToZip(self, input_zip, output_zip, input_path=None):\\n\\n self.UnmountAll()\\n\\n common.ZipWriteStr(output_zip, \\\"META-INF/com/google/android/updater-script\\\",\\n \\\"\\\\n\\\".join(self.script) + \\\"\\\\n\\\")\\n\\n if input_path is None:\\n data = input_zip.read(\\\"OTA/bin/updater\\\")\\n else:\\n data = open(input_path, \\\"rb\\\").read()\\n common.ZipWriteStr(output_zip, \\\"META-INF/com/google/android/update-binary\\\",\\n data, perms=0o755)\",\n \"def save(self, path):\\n (folder, filename) = os.path.split(path)\\n (name, extension) = os.path.splitext(filename)\\n\\n if not name:\\n raise ValueError, \\\"name is required\\\"\\n\\n path = os.path.join(folder, name + self.extension)\\n f = open(path, \\\"wb\\\")\\n f.write(self.contents)\\n f.close()\\n\\n return path\",\n \"def download_file(url, path):\\n file_name = path + url.split(\\\"/\\\")[-1]\\n req = requests.get(url)\\n zipped_info = req.content\\n print(file_name)\\n if not os.path.isfile(file_name):\\n print(\\\"file doesnt exist, writing\\\", file_name)\\n with open(file_name, 'wb') as f:\\n f.write(zipped_info)\\n else:\\n print(\\\"file exists\\\", file_name)\",\n \"def close(self) -> None:\\n\\n if self.closed:\\n return\\n\\n if 'r' not in self.mode:\\n if self.metadata is not None:\\n self.writestr(self._distinfo_path(\\\"METADATA\\\"),\\n str(self.metadata).encode())\\n if self.wheeldata is not None:\\n self.writestr(self._distinfo_path(\\\"WHEEL\\\"),\\n str(self.wheeldata).encode())\\n self._zip.writestr(self._distinfo_path(\\\"RECORD\\\"),\\n str(self.record).encode())\\n\\n self._zip.close()\",\n \"def save_file(save_dir, filename, data):\\n logging.info('\\\\tSaving to... {}'.format(save_dir))\\n if not os.path.isdir(save_dir):\\n os.mkdir(save_dir)\\n\\n filepath = '{0}/{1}'.format(save_dir, filename)\\n with open(filepath, 'w+') as outfile:\\n json.dump(data, outfile)\\n\\n zipfilepath = filepath.replace('.json','.zip')\\n with zipfile.ZipFile(zipfilepath, 'w', zipfile.ZIP_DEFLATED) as zf:\\n zf.write(filepath)\\n\\n #os.remove(filepath)\",\n \"def save(self):\\n if self.hasChanged:\\n filePath = self.path\\n tempPath = filePath+'.tmp'\\n fileDir = os.path.split(filePath)[0]\\n if not os.path.exists(fileDir): os.makedirs(fileDir)\\n cPickle.dump(self.data,open(tempPath,'w'))\\n renameFile(tempPath,filePath,True)\\n self.hasChanged = False\",\n \"def _download_zip_model(model_url: str, model_path: str) -> str:\\n if os.path.exists(model_path):\\n return model_path\\n extract_dir = os.path.dirname(model_path)\\n url_model_name = os.path.basename(urlparse(model_url).path)\\n tmp_zip_file_path = os.path.join(extract_dir, url_model_name)\\n _download_file(model_url, tmp_zip_file_path)\\n _unzip_file(tmp_zip_file_path, extract_dir)\\n return model_path\",\n \"def close(self):\\n self.myzip.close()\",\n \"def Extract_zip_file (path_to_zip,dir_to_save_into):\\n with zipfile.ZipFile(path_to_zip) as zf:\\n \\n for member in tqdm(zf.namelist(), desc='Extracting'):\\n try:\\n if ('annotations' in member) and (member.endswith('.json')): \\n zf.extract(member, dir_to_save_into)\\n shutil.move(os.path.join(dir_to_save_into,member),dir_to_save_into)\\n if ('train' in member):\\n zf.extract(member, dir_to_save_into)\\n if ('test' in member):\\n zf.extract(member, dir_to_save_into)\\n if ('val' in member):\\n zf.extract(member, dir_to_save_into)\\n except zipfile.error as e:\\n pass\\n\\n #delete zip\\n os.remove(path_to_zip)\\n if(os.path.isdir(os.path.join(dir_to_save_into,'annotations'))):\\n # remove the tmp annotations directory\\n shutil.rmtree(os.path.join(dir_to_save_into,'annotations'))\",\n \"def save_to_tmp(bucket, key, string=True):\\n mode = 'w' if string else 'wb'\\n \\n # Get data:\\n s3 = boto3.client('s3')\\n a = s3.get_object(Bucket=bucket, Key=key)\\n data = a['Body'].read()\\n if string:\\n data = data.decode('utf-8')\\n \\n # Save to temp folder:\\n filename = '/tmp/' + key.split('/')[-1]\\n with open(filename, mode) as f:\\n f.write(data)\\n \\n return filename\",\n \"def store_source(zipfile_name, directory, storage_directory):\\n if directory in ZIP_EXCLUDES:\\n zip_command = ['zip', '-x ' + '-x'.join(ZIP_EXCLUDES[directory]), '-r', zipfile_name, directory]\\n else:\\n zip_command = ['zip', '-r', zipfile_name, directory]\\n\\n if exists(zipfile_name):\\n os.remove(zipfile_name)\\n\\n try:\\n logging.debug('Zipping Source: %s', zip_command)\\n check_output(zip_command)\\n except CalledProcessError as build_error:\\n logging.error('Could not zip source, Return Code %s, Command %s', build_error.returncode, build_error.cmd)\\n logging.error(build_error.output)\\n os.remove(zipfile_name)\\n return False\\n\\n qmk_storage.save_file(zipfile_name, os.path.join(storage_directory, zipfile_name), 'application/zip')\\n os.remove(zipfile_name)\\n\\n return True\",\n \"def zip_file(file_path: str) -> str:\\n zip_file_path: str = file_path + \\\".gz\\\"\\n\\n print(f\\\"Compressing {file_path} into {zip_file_path}\\\")\\n timestamp=path.getmtime(file_path)\\n with open(file_path, \\\"rb\\\") as read_stream:\\n with gzip.open(zip_file_path, \\\"wb\\\") as write_stream:\\n shutil.copyfileobj(read_stream, write_stream)\\n os.utime(zip_file_path, (timestamp,timestamp) )\\n\\n return zip_file_path\",\n \"def _create_zip_file(self) -> BytesIO:\\n zip_file_io = BytesIO()\\n with ZipFile(zip_file_io, 'w') as zip_file:\\n for image_scraper_model in self._url_model.image_scraper.all():\\n image_absolute_path = self._get_image_absolute_path(image_scraper_model)\\n zip_file_image_path = self._get_zip_file_image_path(image_absolute_path)\\n zip_file.write(image_absolute_path, zip_file_image_path)\\n zip_file.close()\\n return zip_file_io\",\n \"def save(cls, name, string=False):\\n if not string:\\n pickle.dump(cls.__data[name], open(cls.dirpath + name + '.p', 'wb'))\\n else:\\n fd = open(cls.dirpath + name + '.txt', 'wb')\\n fd.write(str(cls.__data[name]))\\n fd.close()\\n del cls.__data[name]\",\n \"def save(self, export_path: str):\",\n \"def save(self, path):\\n pickle.dump(self, open(path, 'wb'))\",\n \"def make_zip(self):\\n shutil.make_archive(self.name, 'zip', self.name)\",\n \"def _save_file(self, file_path, data):\\n self._ensure_directory(os.path.dirname(file_path))\\n with open(file_path, \\\"wb\\\") as f:\\n f.write(data)\",\n \"def WriteFinalize(self):\\n if not self._file_object:\\n raise IOError('Unable to write to closed serialized data stream.')\\n\\n offset = self._file_object.tell()\\n self._file_object.close()\\n self._file_object = None\\n\\n current_working_directory = os.getcwd()\\n try:\\n os.chdir(self._temporary_path)\\n self._zip_file.write(self.name)\\n finally:\\n os.remove(self.name)\\n os.chdir(current_working_directory)\\n\\n return offset\",\n \"def writeFileToZip(zipFile, sourcePath, targetPath):\\n targetPath = targetPath.replace(\\\"\\\\\\\\\\\", \\\"/\\\") # Zips use forward slashes\\n utcTime = time.gmtime(os.stat(sourcePath).st_mtime)\\n \\n if os.path.isdir(sourcePath):\\n if not targetPath.endswith(\\\"/\\\"):\\n targetPath += \\\"/\\\" # Trailing slash denotes directory for some zip packages\\n\\n zi = zipfile.ZipInfo(targetPath, utcTime[0:6])\\n zi.compress_type = zipfile.ZIP_DEFLATED\\n zi.external_attr = 0x00000010L # FILE_ATTRIBUTE_DIRECTORY\\n zipFile.writestr(zi, \\\"\\\")\\n else: \\n f = open(sourcePath, \\\"rb\\\")\\n try:\\n data = f.read()\\n finally:\\n f.close()\\n \\n zi = zipfile.ZipInfo(targetPath, utcTime[0:6])\\n zi.compress_type = zipfile.ZIP_DEFLATED\\n zi.external_attr = 0x00000020L # FILE_ATTRIBUTE_ARCHIVE\\n zipFile.writestr(zi, data)\",\n \"def writestr(self,\\n zinfo_or_arcname: Union[ZipInfo, str],\\n data: Union[bytes, str]) -> None:\\n\\n # XXX: ZipFile.writestr() does not normalize arcpaths the same way\\n # ZipFile.write() does, and so this method won't do that either\\n\\n arcname = (\\n zinfo_or_arcname.filename\\n if isinstance(zinfo_or_arcname, ZipInfo)\\n else zinfo_or_arcname\\n )\\n\\n self._zip.writestr(zinfo_or_arcname, data)\\n self.refresh_record(arcname)\",\n \"def zip_single(source_path, destination_path, password):\\n\\n if not destination_path:\\n destination_path = source_path\\n\\n if not destination_path.endswith(\\\".zip\\\"):\\n suffix = destination_path.split(\\\".\\\")[1]\\n if destination_path.endswith(\\\".\\\" + suffix):\\n destination_path = destination_path.replace(\\\".\\\" + suffix, '')\\n destination_path += \\\".zip\\\"\\n\\n if password:\\n z = pyzipper.AESZipFile(destination_path, 'w', compression=pyzipper.ZIP_LZMA, encryption=pyzipper.WZ_AES)\\n z.setpassword(password)\\n else:\\n z = pyzipper.ZipFile(destination_path, 'w', compression=pyzipper.ZIP_LZMA)\\n\\n try:\\n z.write(source_path)\\n print(f\\\"{destination_path} created successfully.\\\")\\n except Exception:\\n tb = traceback.format_exc()\\n print(\\\"Something went wrong\\\")\\n print(tb)\\n finally:\\n z.close()\",\n \"def _open_zip(self):\\n self.buffer = io.BytesIO()\\n self.zf = zipfile.ZipFile(self.buffer, \\\"w\\\", zipfile.ZIP_DEFLATED)\",\n \"def toZip(self, file, zip_location):\\n zip_file = zipfile.ZipFile(zip_location, 'w')\\n if os.path.isfile(file):\\n zip_file.write(file)\\n else:\\n self.__addFolderToZip(zip_file, file)\\n print \\\"Wrote %s to %s\\\"%(file,zip_location)\\n zip_file.close()\",\n \"def make_empty_zip(self):\\n buffer = BytesIO()\\n file = ZipFile(buffer, 'w')\\n file.close()\\n return buffer\",\n \"def save_file(self, response):\\r\\n # Extract filename from response url\\r\\n filename = re.search('[^/]+(?=/$|$)', response.url).group(0)\\r\\n\\r\\n # Prepend download folder name to the filename\\r\\n filename = self.config[\\\"folder\\\"] + filename\\r\\n os.makedirs(os.path.dirname(filename), exist_ok=True)\\r\\n\\r\\n # Write contents to file\\r\\n with open(filename, 'wb') as f:\\r\\n f.write(response.content)\\r\\n\\r\\n # Print message displaying the absolute filepath for convenience\\r\\n print(\\\"Downloaded file to \\\" + os.path.abspath(filename))\",\n \"def save(self, path):\\n if path.endswith(\\\".gz\\\"):\\n file = gzip.open(path, \\\"w\\\", 9)\\n else:\\n file = open(path, \\\"wb\\\")\\n\\n # update the settings in the data to the latest value\\n data = json.loads(self.value)\\n data[\\\"settings\\\"] = self.settings\\n\\n file.write(json.dumps(data).encode(\\\"utf8\\\"))\\n file.close()\",\n \"def _check_zip_file (filename, path_unzip, outfile) :\\n assert path_unzip is not None\\n file,ext = os.path.splitext (filename)\\n ext = ext.lower ()\\n if ext == \\\".gz\\\" :\\n \\n import gzip\\n \\n if outfile is None :\\n dest = filename.split (\\\"!\\\")\\n dest = dest [ len(dest)-1 ]\\n ext = os.path.splitext (dest) [1]\\n dest = dest.replace (ext, \\\".txt\\\")\\n path = os.path.split (filename)\\n path = \\\"/\\\".join (path [:len (path)-1])\\n dest = path + \\\"/\\\" + dest\\n else :\\n dest = outfile\\n \\n if not os.path.exists (dest) :\\n file = gzip.GzipFile (filename, \\\"r\\\")\\n if outfile is None :\\n dest = os.path.split (dest) [1]\\n dest = os.path.join (path_unzip, dest)\\n \\n if os.path.exists (dest) :\\n st1 = datetime.datetime.utcfromtimestamp (os.stat (filename).st_mtime)\\n st2 = datetime.datetime.utcfromtimestamp (os.stat (dest).st_mtime)\\n if st2 > st1 : \\n fLOG (\\\"ungzipping file (already done)\\\", dest)\\n return dest\\n \\n fLOG (\\\"ungzipping file\\\", dest)\\n f = open (dest, \\\"w\\\")\\n data = file.read (2**27)\\n size = 0\\n while len (data) > 0 :\\n size += len (data)\\n fLOG (\\\"ungzipping \\\", size, \\\"bytes\\\")\\n if isinstance (data, bytes) : f.write (bytes.decode (data))\\n else : f.write (data)\\n data = file.read (2**27)\\n f.close ()\\n file.close ()\\n \\n return dest\\n \\n if ext == \\\".zip\\\" :\\n \\n import zipfile\\n try :\\n file = zipfile.ZipFile (filename, \\\"r\\\")\\n except Exception as e :\\n fLOG (\\\"problem with \\\", filename)\\n raise e\\n \\n if len (file.infolist()) != 1:\\n if outfile is not None :\\n raise PQHException (\\\"the archive contains %d files and not one as you expected by filling outfile\\\" % len (file.infolist()))\\n fLOG (\\\"unzip file (multiple) \\\", filename)\\n #message = \\\"\\\\n\\\".join ([ fi.filename for fi in file.infolist() ] )\\n #raise Exception.YstException(\\\"ColumnInfoSet.load_from_file: file %s contains no file or more than one file\\\\n\\\" + message)\\n folder = os.path.split (filename) [0]\\n todo = 0\\n _zip7_path = r\\\"c:\\\\Program Files\\\\7-Zip\\\"\\n zip7 = os.path.exists (_zip7_path)\\n wait = [ ]\\n for info in file.infolist () :\\n fileinside = info.filename\\n dest = os.path.join (folder, fileinside)\\n if not os.path.exists (dest) :\\n fol = os.path.split (dest) [0]\\n if not os.path.exists (fol) : os.makedirs (fol)\\n if os.path.exists (dest) :\\n st1 = datetime.datetime.utcfromtimestamp (os.stat (filename).st_mtime)\\n st2 = datetime.datetime.utcfromtimestamp (os.stat (dest).st_mtime)\\n if st2 > st1 : \\n continue\\n \\n if not sys.platform.startswith(\\\"win\\\") or not zip7 :\\n data = file.read (fileinside)\\n dest = os.path.split (dest) [1]\\n dest = os.path.join (path_unzip, dest)\\n fLOG (\\\"unzipping file\\\", dest)\\n wait.append(dest)\\n f = open (dest, \\\"w\\\")\\n if isinstance (data, bytes) :\\n f.write (str (data))\\n else :\\n f.write (data)\\n f.close ()\\n else :\\n todo += 1\\n \\n if todo > 0 and zip7 :\\n dest = os.path.realpath (path_unzip)\\n cmd = '\\\"' + _zip7_path + '\\\\\\\\7z.exe\\\" e -y -o\\\"%s\\\" \\\"%s\\\"' % (dest, os.path.realpath (filename)) \\n out,err = run_cmd (cmd, wait = True)\\n if len (err) > 0 : raise PQHException (\\\"command {0} failed\\\\n{1}\\\".format(cmd,err))\\n if \\\"Error\\\" in out : raise PQHException (\\\"command {0} failed\\\\n{1}\\\".format(cmd,out))\\n else :\\n dest = path_unzip\\n \\n file.close ()\\n \\n ch = False\\n while not ch :\\n ch = True\\n for a in wait :\\n if not os.path.exists(a) : \\n ch = False\\n break\\n time.sleep(0.5)\\n \\n return dest\\n \\n else :\\n for info in file.infolist () :\\n fileinside = info.filename\\n \\n path = os.path.split (filename)\\n dest = outfile if outfile is not None else path [0] + \\\"/\\\" + fileinside\\n if not os.path.exists (dest) :\\n data = file.read (fileinside)\\n if outfile is None :\\n dest = os.path.split (dest) [1]\\n dest = os.path.join (path_unzip, dest)\\n \\n if os.path.exists (dest) :\\n st1 = datetime.datetime.utcfromtimestamp (os.stat (filename).st_mtime)\\n st2 = datetime.datetime.utcfromtimestamp (os.stat (dest).st_mtime)\\n if st2 > st1 : \\n fLOG(\\\"unzipping one file (already done)\\\", dest)\\n return dest\\n \\n fLOG(\\\"unzipping one file\\\", dest)\\n f = open (dest, \\\"w\\\")\\n if isinstance (data, bytes) :\\n f.write (bytes.decode (data))\\n else :\\n f.write (data)\\n f.close ()\\n file.close ()\\n return dest\\n \\n return filename\",\n \"def write(self, path_in_disk=None, compression=False, skip_disk=False, dest_path=None):\\n\\n # Don't double-path a file already in 'patched'\\n if 'patched' not in self.filename:\\n dest_path = path.join(self.dest_disk.dir, self.filename)\\n else:\\n if dest_path is None:\\n dest_path = self.filename\\n\\n dest_path = dest_path.replace(\\\"original/\\\", \\\"\\\")\\n print(\\\"dest_path is\\\", dest_path)\\n\\n with open(dest_path, 'wb') as fileopen:\\n fileopen.write(self.filestring)\\n\\n if compression:\\n print('compressing now')\\n compressed_path = compress(dest_path)\\n print(compressed_path)\\n dest_path = compressed_path\\n\\n if not skip_disk:\\n print(\\\"inserting:\\\", dest_path)\\n self.dest_disk.insert(dest_path, path_in_disk=path_in_disk)\\n return dest_path\",\n \"def save_log_file(save_file_name, save_file_bytes):\\n cwd = getcwd() # Gets Current Working Directory\\n log_dir = cwd + \\\"/\\\" + \\\"Logs\\\"\\n if not exists(log_dir):\\n mkdir(log_dir)\\n log_file_path = log_dir + \\\"/\\\" + save_file_name + \\\".zip\\\"\\n with open(log_file_path, \\\"wb\\\") as f:\\n f.write(save_file_bytes)\\n return log_file_path\",\n \"def backup(self):\\n if self.url is not None:\\n\\n # zip backup folder\\n zipapp.create_archive(self.logs_directory, self.send_zip)\\n\\n # then send zipped folder to the URL\\n try:\\n requests.post(self.url, files={\\n 'uploaded_file': (os.path.basename(self.send_zip), open(self.send_zip, 'rb')),\\n })\\n except requests.exceptions.ConnectionError as error:\\n print(error)\",\n \"def save(self, path):\\n f = open(path, 'w')\\n f.write(self.content().encode('utf-8'))\\n f.close()\",\n \"def save(self, path, name=None):\\n if not os.path.exists(path):\\n os.makedirs(path)\\n name = name or self.name\\n path = os.path.join(path, name)\\n with open(path, 'wb') as pickle_file:\\n pickle.dump(self, pickle_file)\",\n \"def extract_and_clean(zipper, zip_path, filename):\\n zipper.extract(zip_path)\\n if \\\"/\\\" in zip_path :\\n os.rename(zip_path, filename)\\n shutil.rmtree(zip_path.split('/')[0])\",\n \"def _maybe_download_and_extract(self, filename):\\n if not os.path.exists(self.work_dir):\\n os.mkdir(self.work_dir)\\n filepath = os.path.join(self.work_dir, filename)\\n if not os.path.exists(filepath):\\n filepath, _ = urllib.urlretrieve(self.url + filename, filepath)\\n statinfo = os.stat(filepath)\\n log.info('Successfully downloaded', filename, statinfo.st_size,\\n 'bytes.')\\n log.info('Extracting zip file ... ')\\n f = zipfile.ZipFile(filepath)\\n f.extractall(path=self.work_dir)\\n log.info('Extraction finished ... ')\",\n \"def save(self, path):\\n with tempfile.TemporaryDirectory() as td:\\n U.save_state(os.path.join(td, \\\"model\\\"))\\n arc_name = os.path.join(td, \\\"packed.zip\\\")\\n with zipfile.ZipFile(arc_name, 'w') as zipf:\\n for root, dirs, files in os.walk(td):\\n for fname in files:\\n file_path = os.path.join(root, fname)\\n if file_path != arc_name:\\n zipf.write(file_path, os.path.relpath(file_path, td))\\n with open(arc_name, \\\"rb\\\") as f:\\n model_data = f.read()\\n with open(path, \\\"wb\\\") as f:\\n dill.dump((model_data, self._act_params), f)\",\n \"def save_zip_of_df(df, dst_zip_path):\\n dst_zip_path = Path(dst_zip_path)\\n df.to_csv(dst_zip_path,\\n compression=dict(method=\\\"zip\\\", archive_name=dst_zip_path.with_suffix(\\\".csv\\\").name))\\n return dst_zip_path\",\n \"def extract_file(self):\\n# path_destination = os.path.join(\\n# self.root, self.resources.replace(\\\".zip\\\", \\\"\\\"))\\n# os.makedirs(path_destination, exist_ok=True)\\n shutil.unpack_archive(os.path.join(\\n self.root, self.resources), self.root)\\n os.remove(os.path.join(self.root, self.resources))\",\n \"def save_to_file(self, string):\\n with open(self.output_path, \\\"w\\\") as text_file:\\n text_file.write(string)\\n print \\\"Saved to file \\\" + self.output_path\",\n \"def compressIfNeeded(self):\\n\\n if self._mode == \\\"zip\\\":\\n zip_folder(self._rootExportPath, self.getZipArchiveFullPath())\",\n \"def save(self, path):\\n if isinstance(path, str) and path.startswith(\\\"s3://\\\"):\\n raise NotImplementedError(\\\"TODO: Implement saving to s3\\\")\\n path = Path(path).resolve()\\n \\n # Make a folder to save things into\\n if path.suffix == \\\".zip\\\":\\n folder = path.parent / f\\\"tmp_{path.stem}\\\"\\n else:\\n folder = path\\n folder.mkdir(parents=True, exist_ok=False)\\n \\n # Save the trace - ugly hack needed due to multiindex not being supported yet\\n ifd = self.ifd_.copy()\\n ifd.constant_data = ifd.constant_data.reset_index('idx')\\n ifd.observed_data = ifd.observed_data.reset_index('idx')\\n ifd.prior_predictive = ifd.prior_predictive.reset_index('idx')\\n ifd.posterior_predictive = ifd.posterior_predictive.reset_index('idx')\\n ifd.log_likelihood = ifd.log_likelihood.reset_index('idx')\\n az.to_netcdf(ifd, folder / \\\"ifd.nc\\\")\\n \\n # Save other data\\n self.C_mean_.rename(\\\"C_mean_\\\").to_csv(folder / \\\"C_mean_.csv\\\")\\n self.C_std_.rename(\\\"C_std_\\\").to_csv(folder / \\\"C_std_.csv\\\")\\n \\n if path.suffix == \\\".zip\\\":\\n # Save to zip\\n zf = ZipFile(path, mode='w')\\n for file in folder.glob(\\\"*\\\"):\\n zf.write(folder / file.name, arcname=file.name)\\n zf.close()\\n shutil.rmtree(folder)\",\n \"def save(self, path: str):\\n pass\",\n \"def GetAndSave(self, url, save_suffix, unzip=False):\\n self.connection.request('GET',\\n '/data/' + url,\\n headers={'content-type': 'text/plain'})\\n response = self.connection.getresponse()\\n file_name = Clean(url) + save_suffix\\n destination = os.path.join(self.path, file_name)\\n\\n if response.status != 200:\\n raise IOError(url)\\n\\n if unzip:\\n s = StringIO.StringIO(response.read())\\n content = gzip.GzipFile(fileobj=s).read()\\n else:\\n content = response.read()\\n\\n with open(destination, 'w') as f:\\n f.write(content)\\n return content\",\n \"def zipdir(path, zippath):\\n execStr = ['zip', '-r',zippath, path]\\n print ' '.join(execStr)\\n proc = subprocess.Popen(execStr, stdout=PIPE, stderr=PIPE)\\n (output, error) = proc.communicate()\\n if error: print 'error: ', error\\n print 'output: ', output\",\n \"def _save_file(json_response, path, filename):\\n if path is not None:\\n if path[-1] != \\\"/\\\":\\n path = path+\\\"/\\\"\\n filepath = os.path.join(path, filename)\\n if not os.path.exists(path):\\n os.makedirs(path)\\n\\n with open(filepath+'.json', 'w') as output_file:\\n output_file.write(json_response.text)\",\n \"def save(self, hash_str, mime_type):\\n if not os.path.exists(self.path):\\n os.makedirs(self.path)\\n data = self._get_resource_by_hash(hash_str)\\n file_name = hash_str + MIME_TO_EXTESION_MAPPING[mime_type]\\n file_path = os.path.join(self.path, file_name)\\n if not os.path.isfile(file_path):\\n with open(file_path, \\\"w\\\") as f:\\n f.write(data)\\n return \\\"file://\\\" + file_path\",\n \"def make_zip_file(self, post_content):\\n file_path, file_url = self.save_file(post_content['shortcode'] + '.zip', self.make_empty_zip())\\n with ZipFile(file_path, 'w') as zipf:\\n if post_content['igtv'] is True:\\n zipf.writestr('igtv_link.txt', post_content['urls'][0][2])\\n else:\\n for url in post_content['urls']:\\n zipf.writestr(self.get_content_name(url[2]), requests.get(url[2]).content)\\n\\n if 'text' in post_content:\\n zipf.writestr('caption.txt', post_content['text'])\\n return file_url\",\n \"def zip_mail(self, comp_filename, zip_path, destination=''):\\r\\n\\r\\n pass\\r\\n # TODO Remodel this.\\r\",\n \"def save_string(cls, name, string):\\n fd = open(cls.dirpath + name + '.txt', 'wb')\\n fd.write(string)\\n fd.close()\",\n \"def download_zip(url, folder=None):\\n\\n # get this file folder name and save the file name\\n if not folder:\\n folder = os.path.dirname(os.path.abspath(__file__))\\n file_name = os.path.split(url)[1]\\n\\n # Download the file from \\\"url\\\" and save it locally under \\\"file_name\\\":\\n try:\\n with urllib.request.urlopen(url) as response, open(folder + \\\"/\\\" + file_name, 'wb') as out_file:\\n shutil.copyfileobj(response, out_file)\\n except urllib.error.URLError as e:\\n print('urllib.error.URLError')\\n raise Exception(e)\\n except Exception as e:\\n raise Exception(e)\\n else:\\n return folder,file_name\",\n \"def download_data(self):\\n headers = {'User-Agent': 'Mozilla/5.0',}\\n\\n #Request for html data of url page\\n r = requests.get(self.url, headers = headers, allow_redirects=True)\\n soup = BeautifulSoup(r.text, \\\"html.parser\\\")\\n\\n #Checking if folder path exists, if not, creats it\\n i=0\\n while i<len(self.folder)-1:\\n if self.folder[i] == '/':\\n if not os.path.isdir(self.folder[:i]):\\n os.mkdir(self.folder[:i])\\n i+=1\\n if i==len(self.folder)-1:\\n if not os.path.isdir(self.folder):\\n os.mkdir(self.folder)\\n\\n # if not os.path.isdir(self.folder):\\n # os.mkdir(self.folder)\\n\\n #Gets every href to zip file with data\\n entries = []\\n for link in soup.find_all('a'):\\n if re.search(\\\"^data/.*.zip\\\", link.get('href')):\\n entries.append(link.get('href'))\\n\\n #Gets the newest dataset\\n self.getCurrentData(entries)\\n\\n i=0\\n #Saves each file in dataset\\n for list in self.ListOfZipFiles:\\n if not os.path.isfile(self.folder+list[4:]):\\n r = requests.get(self.url+list)\\n open(self.folder+list[4:], 'wb').write(r.content)\\n #deletes prefix \\\"data/\\\"\\n self.ListOfZipFiles[i] = list[4:]\\n i+=1\",\n \"def getzip(url, zipfile, unzipdir):\\n done_file = os.path.join(unzipdir, '.'+os.path.basename(zipfile)+'.done')\\n if file_exists(done_file):\\n print('{} already downloaded and extracted; skipping. To reinstall \\\"rm {}\\\"'.format(os.path.basename(zipfile), done_file))\\n else:\\n print('Downloading {} as {}.'.format(url, zipfile))\\n urlretrieve(url, zipfile)\\n print('Extracting {} into {}.'.format(zipfile, unzipdir))\\n with ZipFile(zipfile, 'r') as zip:\\n zip.extractall(unzipdir)\\n os.remove(zipfile)\\n with open(done_file, 'w'):\\n pass\",\n \"def test_writepath_directory(self):\\n z = ZipFile(self.f, 'w')\\n z.writepath(None, pathname='/testdir', folder=True)\\n z.writepath(None, pathname='/testdir/testinside', folder=True)\\n z.close()\\n self.f.close()\\n\\n f = open(ZIPPATH, mode='r')\\n z = ZipFile(f, 'r')\\n\\n entries = z.infolist()\\n\\n assert len(entries) == 2\\n assert entries[0].isdir()\\n z.close()\\n f.close()\",\n \"def zipfile(filepath, cleanup=False):\\n\\tzfile = filepath+\\\".gz\\\"\\n\\twith open(filepath, 'rb') as f_in:\\n\\t\\twith gzip.open(zfile, 'wb') as f_out:\\n\\t\\t\\tf_out.writelines(f_in)\\t\\n\\t\\n\\tif cleanup and file_exists(zfile):\\n\\t\\tos.remove(filepath)\\n\\treturn zfile\",\n \"def save_into_html_file(path_html_file: str, response):\\n html_file = open(path_html_file, 'w')\\n html_file.writelines(response)\\n html_file.close()\\n\\n with zipfile.ZipFile(path_html_file.replace('.html', '.zip'), 'w') as zf:\\n zf.write(path_html_file, compress_type=zipfile.ZIP_DEFLATED)\\n zf.close()\\n os.remove(path_html_file)\",\n \"def create_zip(self, db, submission, request, logger, passwd=None,\\r\\n mat_dir=None, no_subdirs=None):\\r\\n if db(db.material.leak_id==submission.id).select().first():\\r\\n try:\\r\\n filedir = str(db(db.submission.leak_id==submission.id).select(\\r\\n db.submission.dirname).first().dirname)\\r\\n filedir = os.path.join(request.folder, \\\"material\\\", filedir)\\r\\n except:\\r\\n logger.error('create_zip: invalid filedir')\\r\\n return dict(error='invalid filedir')\\r\\n err = None\\r\\n try:\\r\\n # XXX should need some refactoring\\r\\n if not mat_dir:\\r\\n mat_dir = filedir\\r\\n splitted = os.path.split(mat_dir)\\r\\n if splitted[-1].isdigit():\\r\\n filedir = \\\"%s-%s\\\" % (splitted[-2], splitted[-1])\\r\\n if no_subdirs:\\r\\n save_file = filedir + \\\"-0\\\"\\r\\n # get only files, no subdirectories\\r\\n files = [f for f in os.listdir(mat_dir)\\r\\n if not os.path.isdir(os.path.join(mat_dir, f))]\\r\\n else:\\r\\n save_file = filedir\\r\\n files = os.listdir(mat_dir)\\r\\n # XXX: issue #51\\r\\n if passwd and os.path.exists(mat_dir):\\r\\n logger.error('Encrypted ZIP function disabled, due to security redesign needs')\\r\\n return 0\\r\\n # cmd = 'zip -e -P%(passwd) %(zipfile).zip %(files)' % dict(\\r\\n # passwd=passwd, zipfile=filedir,\\r\\n # files=\\\" \\\".join(files))\\r\\n # subprocess.check_call(cmd.split())\\r\\n elif not passwd and os.path.exists(mat_dir):\\r\\n zipf = zipfile.ZipFile(save_file+'.zip', 'w')\\r\\n for f in files:\\r\\n path = os.path.join(mat_dir, f)\\r\\n zipf.write(path, f)\\r\\n subdirs = os.walk(path)\\r\\n for subdir in subdirs:\\r\\n inner_subdir = os.path.split(subdir[0])[-1]\\r\\n if not inner_subdir.isdigit():\\r\\n inner_subdir = \\\"\\\"\\r\\n for subfile in subdir[2]:\\r\\n zipf.write(os.path.join(subdir[0], subfile),\\r\\n os.path.join(inner_subdir,subfile))\\r\\n else:\\r\\n logger.error('create_zip: invalid path')\\r\\n except RuntimeError as err:\\r\\n logger.error('create_zip: error in creating zip')\\r\\n try:\\r\\n zipf.close()\\r\\n except (RuntimeError, zipfile.error) as err:\\r\\n logger.info('create_zip: error when trying to save zip')\\r\\n except subprocess.CalledProcessError as err :\\r\\n logger.error('create_zip: error in creating zip')\\r\\n finally:\\r\\n return dict(error=err) if err else None\",\n \"def save(self,cookie_jar):\\n if not os.path.exists(self.path):\\n os.makedirs(self.path)\\n with open(self.file_path, \\\"wb\\\") as cookie_file:\\n cookie_file.write(bytearray(pickle.dumps(cookie_jar)))\",\n \"def save(self, path):\\n np.savez_compressed(path, **self.model_dict)\",\n \"def download_file(self, name):\\n #TODO: handle exceptions\\n archive_name = name + \\\".json.gz\\\"\\n file_name = join(self.new_data_dir, name + \\\".json\\\")\\n\\n try:\\n urlretrieve(\\\"http://data.githubarchive.org/\\\" + archive_name,\\n filename=join(self.downloaded_data_dir, archive_name))\\n except IOError:\\n self.logger.error(__name__ + \\\": \\\" + \\\"unable to download file (error creating connection).\\\")\\n\\n try:\\n archive = gz_open(join(self.downloaded_data_dir, archive_name))\\n except IOError:\\n self.logger.error(__name__ + \\\": \\\" + \\\"unable to open gzipped file (file not created).\\\")\\n else:\\n json_file = open(file_name, \\\"w\\\")\\n json_file.write(archive.read())\\n\\n archive.close()\\n json_file.close()\\n\\n remove(join(self.downloaded_data_dir, archive_name))\\n\\n return file_name\",\n \"def save(self, filename):\\n import pickle\\n if path.dirname(filename) and not path.exists(path.dirname(filename)):\\n makedirs(path.dirname(filename))\\n pickle.dump(self, open(filename, 'wb'), protocol=-1)\",\n \"def zip_data_file(task_id, task_name, data_path):\\n zip_file_dir = os.path.join(FILE_PATH, task_id + \\\".zip\\\")\\n file = zipfile.ZipFile(zip_file_dir, \\\"w\\\", zipfile.ZIP_DEFLATED)\\n sample_path = os.path.join(data_path, \\\"datasets\\\", str(task_id) + \\\"_\\\" + task_name + \\\".csv\\\")\\n true_dag_path = os.path.join(data_path, \\\"true\\\", str(task_id) + \\\"_\\\" + task_name + \\\".npz\\\")\\n file.write(sample_path)\\n file.write(true_dag_path)\\n file.close()\\n return zip_file_dir\",\n \"def save(self, filename = 'array_zest', path = '/home/eric/dev/insitu/data/zs_recovery/'):\\n filename = filename# + '_Lx_' + str(self.Lx) + 'm_Ly_' + str(self.Ly) + 'm'\\n self.path_filename = path + filename + '.pkl'\\n f = open(self.path_filename, 'wb')\\n pickle.dump(self.__dict__, f, 2)\\n f.close()\",\n \"def save(self, path):\\n with open(path, 'wb') as f:\\n pkl.dump(self, f)\",\n \"def save(self, path):\\n pass\",\n \"def save(self, path):\\n pass\",\n \"def save(self, path):\\n pass\",\n \"def compress_experiment(self, exp_id):\\n exp_folder = self.um.experiment_path(str(exp_id))[:-1]\\n exp_folder = os.path.join(os.path.dirname(\\n os.path.realpath(__file__)), exp_folder)\\n archive_name = os.path.join(os.path.dirname(os.path.realpath(__file__)),\\n \\\"backup\\\", str(exp_id)+\\\".zip\\\")\\n\\n print exp_folder, archive_name\\n retval = self.um.compress_folder_zip(exp_folder, archive_name)\\n if retval:\\n return \\\"Success\\\"\\n else:\\n return \\\"Failure\\\"\",\n \"def save(self, path):\\n print(\\\"Warning: Default save used\\\")\\n with open(path, 'wb') as f:\\n pickle.dump(self, f)\",\n \"def localpath_download(self, *path, **kwargs):\\n pathname = self.localpath(*path)\\n if not os.path.exists(pathname):\\n self.download.unwrapped(self, *path, **kwargs)\\n return pathname\",\n \"def download(self):\\n if not os.path.isdir(self.save_path):\\n try:\\n os.mkdir(self.save_path)\\n except IOError:\\n print(\\\"Can't create subfolder. \\\"\\n \\\"Check that you have write access for \\\"\\n \\\"{}\\\".format(self.save_path))\\n\\n sub_zip_file = request.urlopen(self.download_link)\\n sub_gzip = gzip.GzipFile(fileobj=StringIO(sub_zip_file.read()))\\n subtitle_content = sub_gzip.read()\\n try:\\n with open(self.full_path, 'wb') as subtitle_output:\\n subtitle_output.write(subtitle_content)\\n print(\\\"Downloaded subtitle...\\\")\\n except IOError:\\n print(\\\"Couldn't save subtitle, permissions issue?\\\")\",\n \"def picklesave(obj, path):\\n with open(path, 'wb') as file:\\n pickle.dump(obj, file)\",\n \"def check_request_and_create_zipfile() -> None:\\n\\n session = DBSession()\\n\\n for site_page in session.query(SitePage).filter(SitePage.status != STATUS_ARCHIVE_READY):\\n data = create_zipfile(url_page=site_page.url)\\n\\n site_page.zipfile = pickle.dumps(data)\\n site_page.status = STATUS_ARCHIVE_READY\\n session.add(site_page)\\n session.commit()\\n\\n session.close()\",\n \"def zipdata(filename: str) -> None:\\n\\n # Generate the path to the project TODO: check if this is entire project or server\\n directoryName = ROOT.split(\\\"/\\\")[-3]\\n codeDestination = \\\"/\\\".join(ROOT.split(\\\"/\\\")[:-2])\\n\\n # Create the output file\\n zippedFile = zipfile.ZipFile(filename, \\\"w\\\", compression=zipfile.ZIP_DEFLATED)\\n\\n # Walk over the directory and save all files\\n for abspath, dirnames, filenames in os.walk(codeDestination):\\n local = abspath[abspath.index(directoryName):]\\n [zippedFile.write(os.path.join(abspath, name), os.path.join(local, name)) for name in filenames]\\n\\n # Close the zip file\\n zippedFile.close()\",\n \"def ZipResultFolder(md5_key, cnt):\\n subfoldername = md5_key[:2]\\n md5_subfolder = \\\"%s/%s\\\"%(path_cache, subfoldername)\\n cachedir = \\\"%s/%s/%s\\\"%(path_cache, subfoldername, md5_key)\\n zipfile_cache = cachedir + \\\".zip\\\"\\n if os.path.exists(cachedir) and not os.path.exists(zipfile_cache):\\n origpath = os.getcwd()\\n os.chdir(md5_subfolder)\\n targetfile = os.path.join(cachedir, \\\"query.result.txt\\\")\\n if os.path.exists(targetfile):\\n cmd = [\\\"zip\\\", \\\"-rq\\\", \\\"%s.zip\\\"%(md5_key), md5_key]\\n cmdline = \\\" \\\".join(cmd)\\n try:\\n print((\\\"%d: %s\\\"%(cnt, cmdline)))\\n subprocess.check_call(cmd)\\n print((\\\"%d: %s\\\"%(cnt, \\\"rmtree(%s)\\\"%(md5_key) )))\\n os.system(\\\"chown %s:%s %s\\\"%(user, group, \\\"%s.zip\\\"%(md5_key)))\\n shutil.rmtree(md5_key)\\n except:\\n print(\\\"Failed to zip folder %s\\\"%(cachedir), file=sys.stderr)\\n raise\\n else:\\n print((\\\"%d: %s\\\"%(cnt, \\\"bad result! just rmtree(%s)\\\"%(md5_key) )))\\n shutil.rmtree(md5_key)\\n os.chdir(origpath)\\n elif os.path.exists(zipfile_cache):\\n #check weather the zipped file is a valid prediction result\\n try:\\n with ZipFile(zipfile_cache, \\\"rb\\\") as myzip:\\n li = myzip.namelist()\\n target = \\\"%s/query.result.txt\\\"%(md5_key)\\n if target in li:\\n print((\\\"%d: %s\\\"%(cnt, \\\"Valid zipped result for %s\\\"%(md5_key) )))\\n else:\\n print((\\\"%d: %s\\\"%(cnt, \\\"bad zipped result! just delete zipfile(%s)\\\"%(md5_key) )))\\n os.remove(zipfile_cache)\\n except Exception as e:\\n print((\\\"%d: %s\\\"%(cnt, \\\"BadZipFile! just delete zipfile(%s)\\\"%(md5_key) )))\\n os.remove(zipfile_cache)\",\n \"def download_zipped_model(manifest, assert_hash=False):\\n zipped_model_path = manifest[\\\"model_filepath\\\"]\\n zipped_model = client.file(zipped_model_path).getFile().name\\n if assert_hash:\\n assert_model_md5(zipped_model)\\n return zipped_model_path\",\n \"def getZipArchiveFullPath(self):\\n\\n if self._mode == \\\"zip\\\":\\n return self._rootExportPath + \\\".zip\\\"\\n\\n return \\\"\\\"\",\n \"def zip_dir(path: str, zip_filename: str) -> None:\\n with zipfile.ZipFile(zip_filename, \\\"w\\\", zipfile.ZIP_DEFLATED) as zip_file:\\n for root, dirs, files in os.walk(path):\\n for file in files:\\n f = os.path.join(root, file)\\n zip_file.write(f, f[len(path) :])\",\n \"def write_filepath(self, filename, file_format='FASTA', zipout=False):\\n \\n file_obj = open_with_intermediates(filename,'w')\\n if zipout:\\n file_obj.close()\\n file_obj = StringIO()\\n self.write(file_obj, file_format=file_format)\\n if zipout:\\n import gzip\\n file_obj_gz = gzip.open(filename, \\\"wb\\\", 6)\\n file_obj_gz.write(str.encode(file_obj.getvalue()))\\n file_obj_gz.close()\\n file_obj.close()\",\n \"def write_filepath(self, filename, file_format='FASTA', zipout=False):\\n \\n file_obj = open_with_intermediates(filename,'w')\\n if zipout:\\n file_obj.close()\\n file_obj = StringIO()\\n self.write(file_obj, file_format=file_format)\\n if zipout:\\n import gzip\\n file_obj_gz = gzip.open(filename, \\\"wb\\\", 6)\\n file_obj_gz.write(str.encode(file_obj.getvalue()))\\n file_obj_gz.close()\\n file_obj.close()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.69184697","0.6477389","0.6425179","0.63842976","0.6137987","0.6123069","0.5896687","0.5882788","0.5697541","0.5678088","0.5674914","0.5637382","0.56089973","0.5559134","0.5541039","0.5518614","0.55055565","0.54959124","0.5464814","0.54589176","0.5444477","0.5441234","0.5399635","0.5387581","0.5375379","0.53513867","0.5348888","0.5313087","0.53020674","0.5300335","0.527506","0.5246876","0.5230862","0.5200068","0.5199742","0.5183333","0.51825273","0.51821464","0.51762927","0.51750886","0.51706415","0.5169839","0.5168735","0.5166277","0.51642704","0.516293","0.5154777","0.51524067","0.51459694","0.5140192","0.5117362","0.51163757","0.51142883","0.51021606","0.5098167","0.5085237","0.50848347","0.50810707","0.5078396","0.50726753","0.50682306","0.50509816","0.50476396","0.5021424","0.5012774","0.50117415","0.50077945","0.5006061","0.5003123","0.50024706","0.4997393","0.498989","0.49852863","0.49851686","0.49786347","0.49646252","0.49592087","0.49543124","0.49535584","0.49419597","0.4934711","0.49315068","0.49198344","0.49109697","0.487668","0.487668","0.487668","0.4866349","0.4865327","0.48643136","0.48552096","0.48447317","0.48430392","0.4840637","0.48283646","0.482743","0.4819156","0.4815043","0.48107243","0.48107243"],"string":"[\n \"0.69184697\",\n \"0.6477389\",\n \"0.6425179\",\n \"0.63842976\",\n \"0.6137987\",\n \"0.6123069\",\n \"0.5896687\",\n \"0.5882788\",\n \"0.5697541\",\n \"0.5678088\",\n \"0.5674914\",\n \"0.5637382\",\n \"0.56089973\",\n \"0.5559134\",\n \"0.5541039\",\n \"0.5518614\",\n \"0.55055565\",\n \"0.54959124\",\n \"0.5464814\",\n \"0.54589176\",\n \"0.5444477\",\n \"0.5441234\",\n \"0.5399635\",\n \"0.5387581\",\n \"0.5375379\",\n \"0.53513867\",\n \"0.5348888\",\n \"0.5313087\",\n \"0.53020674\",\n \"0.5300335\",\n \"0.527506\",\n \"0.5246876\",\n \"0.5230862\",\n \"0.5200068\",\n \"0.5199742\",\n \"0.5183333\",\n \"0.51825273\",\n \"0.51821464\",\n \"0.51762927\",\n \"0.51750886\",\n \"0.51706415\",\n \"0.5169839\",\n \"0.5168735\",\n \"0.5166277\",\n \"0.51642704\",\n \"0.516293\",\n \"0.5154777\",\n \"0.51524067\",\n \"0.51459694\",\n \"0.5140192\",\n \"0.5117362\",\n \"0.51163757\",\n \"0.51142883\",\n \"0.51021606\",\n \"0.5098167\",\n \"0.5085237\",\n \"0.50848347\",\n \"0.50810707\",\n \"0.5078396\",\n \"0.50726753\",\n \"0.50682306\",\n \"0.50509816\",\n \"0.50476396\",\n \"0.5021424\",\n \"0.5012774\",\n \"0.50117415\",\n \"0.50077945\",\n \"0.5006061\",\n \"0.5003123\",\n \"0.50024706\",\n \"0.4997393\",\n \"0.498989\",\n \"0.49852863\",\n \"0.49851686\",\n \"0.49786347\",\n \"0.49646252\",\n \"0.49592087\",\n \"0.49543124\",\n \"0.49535584\",\n \"0.49419597\",\n \"0.4934711\",\n \"0.49315068\",\n \"0.49198344\",\n \"0.49109697\",\n \"0.487668\",\n \"0.487668\",\n \"0.487668\",\n \"0.4866349\",\n \"0.4865327\",\n \"0.48643136\",\n \"0.48552096\",\n \"0.48447317\",\n \"0.48430392\",\n \"0.4840637\",\n \"0.48283646\",\n \"0.482743\",\n \"0.4819156\",\n \"0.4815043\",\n \"0.48107243\",\n \"0.48107243\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7418616"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":92983,"cells":{"query":{"kind":"string","value":"Napisy 24 GET request for subtitle zip downloading. Data is stored in self.zip_string."},"document":{"kind":"string","value":"def download_subtitle_zip(self, dict_entry_to_download):\n\trequest_subtitle_list = \"http://napisy24.pl/download/%s/\" % str(self.return_xml_dict_entry_value(dict_entry_to_download,'id'))\n\trepeat = 3\n\twhile repeat > 0: \n repeat = repeat - 1\n\t #request_subtitle_list = \"/libs/webapi.php?title=%s\" % self.MovieName\n\t r1_status = self.__connect_with_server(request_subtitle_list, \"download_subtilte_zip\") \n if r1_status != 302:\n print \"Fetching subtitle failed, HTTP code: %s\" % (str(r1_status))\n time.sleep(0.5)\n continue\n else:\n repeat = 0\n \n if self.zip_string == None:\n print \"Subtitle NOT DOWNLOADED\"\n repeat = 0\n continue\n\n if self.zip_string is None or self.zip_string == \"\":\n print \"Subtitle NOT DOWNLOADED\"\n continue\n \n if self.zip_string[0:2] == 'PK':\n\t print \"Success to download subtitle zip.\"\n return True\n else:\n\t print \"Reild to download subtitle zip.\"\n return False"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def download(self):\n if not os.path.isdir(self.save_path):\n try:\n os.mkdir(self.save_path)\n except IOError:\n print(\"Can't create subfolder. \"\n \"Check that you have write access for \"\n \"{}\".format(self.save_path))\n\n sub_zip_file = request.urlopen(self.download_link)\n sub_gzip = gzip.GzipFile(fileobj=StringIO(sub_zip_file.read()))\n subtitle_content = sub_gzip.read()\n try:\n with open(self.full_path, 'wb') as subtitle_output:\n subtitle_output.write(subtitle_content)\n print(\"Downloaded subtitle...\")\n except IOError:\n print(\"Couldn't save subtitle, permissions issue?\")","def download_data(self, format = 'srt'):\n \n def to_ascii(data):\n \"\"\"\n Remove non-ascii characters\n \"\"\"\n return ''.join([x for x in data if ord(x) < 128])\n \n url = self.config.subtitles['url'] % (self.media_resource_id)\n \n print url\n resp, content = httplib2.Http(\".cache\").request(url, \"GET\")\n \n subtitles = json.loads(content)['subtitles']\n \n final_data = ''\n if format == 'srt':\n final_data += self.to_srt(subtitles)\n else:\n final_data += subtitles\n \n return to_ascii(final_data)","def downloadData(self, strZipUrl: str) -> str:\n wget.download(strZipUrl, os.path.join(self.strDataDir, os.path.basename(strZipUrl)))\n\n return os.path.join(self.strDataDir, os.path.basename(strZipUrl))","def download(self, language, filename, filetype):\n if language not in self.languages.keys():\n print \"Theres's no subtitle in this language\"\n sys.exit()\n url = \"http://www.youtube.com/api/timedtext?v={0}&lang={1}\".format(self.video_id, language)\n self.subtitle = urllib2.urlopen(url)\n if filetype == \"srt\":\n self.writeSRTFile(filename)\n else:\n self.writeXMLFile(filename)","def get_sample_zip(self, sha256):\n return self.__make_api_call('get/sample/{}/zip'.format(sha256))","def download_data(self, format = 'srt'):\n resp, content = httplib2.Http(\".cache\").request(self.url, \"GET\")\n suburl = json.loads(content)['url']\n resp, content = httplib2.Http(\".cache\").request(suburl, \"GET\")\n\n return content","def download():\n response = requests.get(URL, stream=True)\n\n file = open(FILE_NAME, 'wb')\n file.write(response.content)\n\n with zipfile.ZipFile(FILE_NAME, 'r') as zip_ref:\n zip_ref.extractall()\n\n file.close()\n os.remove(FILE_NAME)","def unzip_subtitles(self, zip_filepath):\n with ZipFile(zip_filepath, 'r') as zip_obj:\n filenames = zip_obj.namelist()\n\n subtitle_filenames = [fn for fn in filenames if fn.endswith('.srt')]\n for fn in subtitle_filenames:\n zip_obj.extract(fn, self.temp_storage_dir)\n\n return subtitle_filenames","def test_result_file_path_get(self):\n headers = { \n 'Accept': 'application/zip',\n }\n response = self.client.open(\n '/v1/result/{file_path}'.format(file_path='file_path_example'),\n method='GET',\n headers=headers)\n self.assert200(response,\n 'Response body is : ' + response.data.decode('utf-8'))","def download_zip(self, path: Path) -> Path:\n if not self.url:\n raise ValueError(\"Release must have a valid url to download the zip.\")\n\n with requests.get(self.url, stream=True) as response:\n with open(path, \"wb\") as download_file:\n shutil.copyfileobj(response.raw, download_file)\n\n return path","def download_data():\n\n if not os.path.exists(zipfile_path):\n print(f'Downloading {config.download_url} to {zipfile_path}')\n urlretrieve(config.download_url, zipfile_path)\n print(f'Successfully downloaded {zipfile_path}')\n\n zip_ref = ZipFile(zipfile_path, 'r')\n zip_ref.extractall(config.raw_data_dir)\n zip_ref.close()\n\n os.rename(f\"{config.raw_data_dir}/cornell movie-dialogs corpus\", extracted_dir)","def _download(data_folder): # pragma: no cover\n\n logger.info(f\"Downloading {SOURCE_URL}.\")\n\n with urlopen(SOURCE_URL) as zipresp:\n with zipfile.ZipFile(io.BytesIO(zipresp.read())) as zfile:\n zfile.extractall(data_folder)","def download_transcripts(request):\r\n locator = request.GET.get('locator')\r\n if not locator:\r\n log.debug('GET data without \"locator\" property.')\r\n raise Http404\r\n\r\n try:\r\n item = _get_item(request, request.GET)\r\n except (InvalidKeyError, ItemNotFoundError):\r\n log.debug(\"Can't find item by locator.\")\r\n raise Http404\r\n\r\n subs_id = request.GET.get('subs_id')\r\n if not subs_id:\r\n log.debug('GET data without \"subs_id\" property.')\r\n raise Http404\r\n\r\n if item.category != 'video':\r\n log.debug('transcripts are supported only for video\" modules.')\r\n raise Http404\r\n\r\n filename = 'subs_{0}.srt.sjson'.format(subs_id)\r\n content_location = StaticContent.compute_location(item.location.course_key, filename)\r\n try:\r\n sjson_transcripts = contentstore().find(content_location)\r\n log.debug(\"Downloading subs for %s id\", subs_id)\r\n str_subs = generate_srt_from_sjson(json.loads(sjson_transcripts.data), speed=1.0)\r\n if not str_subs:\r\n log.debug('generate_srt_from_sjson produces no subtitles')\r\n raise Http404\r\n response = HttpResponse(str_subs, content_type='application/x-subrip')\r\n response['Content-Disposition'] = 'attachment; filename=\"{0}.srt\"'.format(subs_id)\r\n return response\r\n except NotFoundError:\r\n log.debug(\"Can't find content in storage for %s subs\", subs_id)\r\n raise Http404","def download_extract_zip(url):\n response = requests.get(url)\n with ZipFile(BytesIO(response.content)) as thezip:\n for zipinfo in thezip.infolist():\n with thezip.open(zipinfo) as thefile:\n df = pd.read_csv(thefile)\n return (df)","def create_download_response(self):\n zip_file_io = self._create_zip_file()\n content_type = 'application/x-zip-compressed'\n extension = 'zip'\n file_name = self._get_file_name()\n resp = HttpResponse(zip_file_io.getvalue(), content_type=content_type)\n resp['Content-Disposition'] = 'attachment; filename={}.{}'.format(file_name, extension)\n return resp","def downloadDfxpTranscript(self, SubsLink):\n try:\n subRequestObject = requests.get(SubsLink)\n # print(subRequestObject.text)\n subRequestObject.encoding = 'utf-8'\n\n subsFileHandler = open(self.title + \".dfxp\", \"w\")\n print(\"Creating ~ '%s.dfxp' ...\" % (self.title))\n subsFileHandler.write(subRequestObject.text)\n subsFileHandler.close()\n return 1\n\n except:\n return 0\n\n pass","def download_archive(self):\n\n def time_convert(structure):\n \"\"\"\n :param structure: tuple representation of time\n :return: GitHub archive time\n \"\"\"\n \n \n join_number_to_zero = lambda number: (\"\" if number > 9 else \"0\") + str(number)\n\n return \"%s-%s-%s-%s\" % (\n structure.tm_year, join_number_to_zero(structure.tm_mon), join_number_to_zero(structure.tm_mday),\n structure.tm_hour)\n\n current_time = self.get_time()\n self.logger.debug(__name__ + \": \" + \"current time: \" + str(gmtime(current_time)))\n\n difference = -25200\n #timezone difference in seconds between GMT and west coast of USA\n\n downloading_time = int(timegm(self.config[\"last_connection_time\"])) + 3600\n self.logger.debug(__name__ + \": \" + \"downloading time: \" + str(gmtime(downloading_time)))\n\n if downloading_time > current_time - 7200:\n self.logger.info(__name__ + \": \" + \"unable to download file (time limiting).\")\n return\n\n downloading_time += difference\n\n json_file_name = self.download_file(time_convert(gmtime(downloading_time)))\n\n self.config[\"last_connection_time\"] = gmtime(downloading_time - difference)\n self.logger.debug(__name__ + \": \" + \"last_connection_time: \" + str(self.config[\"last_connection_time\"]))\n\n return json_file_name","def request_event(topic, url_path, zipcodes):\n\n events = []\n\n for zp, _, _ in zipcodes:\n default_args = dict(\n zip=zp,\n topic=topic,\n key=os.environ['MEETUP_API_KEY']\n )\n\n print(default_args)\n\n r = requests.get(url_path, params=default_args)\n results = r.text\n try:\n json_data = json.loads(results)\n events.append(json_data['results'])\n except Exception as e:\n logging.exception(f'Error: {e}')\n\n return events","def fmarket_download():\r\n name = request.args[\"address\"]\r\n markets = get_zipcode_markets(name)\r\n\r\n return Response(markets.to_json(), 200, mimetype=\"application/json\")","def request(self, params: Dict[str, Any]) -> Response:\n\n resp: Response = requests.get(self.base_url, params=params, timeout=10)\n resp.raise_for_status()\n\n headers: str = resp.headers[\"content-disposition\"]\n\n if re.search(r\"\\.xml\\.zip;$\", headers):\n raise NoDataAvailableError(\"No data available for this query.\")\n\n return resp","def run_script():\n var=raw_input(\"Enter a Zipcode: \")\n address='http://www.uszip.com/zip/'+var\n conn=urllib.urlopen(address)\n t=[]\n for line in conn.fp:\n\tline=line.strip()\n\tif '<title>' in line:\n\t line.split()\n\t print line[7:-16]\n\tif 'Total population' in line:\n\t line=line.strip('z')\n\t loc=line.index('Total population')\n\t loc2=line.index('<span')\n\t print line[(loc+25):loc2]","def get_zipinfo(self):\n zipinfo = zipfile.ZipInfo()\n zipinfo.filename = self.translated_path()\n zipinfo.date_time = self.get_mod_time()\n zipinfo.file_size = self.get_size()\n return zipinfo","def download_data():\n url = 'https://www.dropbox.com/s/h9ubx22ftdkyvd5/ml-latest-small.zip?dl=1'\n urllib.request.urlretrieve(url, 'ml-latest-small.zip')\n zfile = zipfile.ZipFile('ml-latest-small.zip')\n zfile.extractall()\n zfile.close()","def _download(self, request_dict={}):\n html = super()._download(request_dict)\n self.extract_cases_from_subpages(html)\n return html","def download_sample():\n sample_id = demisto.getArg('id')\n r = req('GET', SUB_API + 'samples/' + sample_id + '/sample.zip')\n ec = {'ThreatGrid.DownloadedSamples.Id': sample_id}\n demisto.results([\n {\n 'Type': entryTypes['note'],\n 'EntryContext': ec,\n 'HumanReadable': '### ThreatGrid Sample Download - \\n'\n + 'Your download request has been completed successfully for ' + sample_id,\n 'Contents': ec,\n 'ContentsFormat': formats['json']\n },\n fileResult(sample_id + '-sample.zip', r.content)\n ])","def bike_download():\r\n name = request.args[\"address\"]\r\n stations = get_zipcode_stations(name)\r\n\r\n return Response(stations.to_json(), 200, mimetype=\"application/json\")","def main(file_url, file_path):\n\n # extract file from the link\n\n if not os.path.exists(file_path):\n os.makedirs(file_path, exist_ok=True)\n \n r = requests.get(str(file_url))\n\n #unzip the zip file\n z = zipfile.ZipFile(io.BytesIO(r.content))\n z.extractall(path = file_path)","def package(request, name):\n return HttpResponse(get_koji_download_url(name), mimetype='application/json')","def package(request, name):\n return HttpResponse(get_koji_download_url(name), mimetype='application/json')","def download_data():\r\n print('Downloading cifar-10 data...')\r\n request.urlretrieve(dataurl)\r\n print('Done')\r\n print('Please unzip files. command is:')\r\n print('gzip -d cifar-10-python.tar.gz')\r\n print('tar -xf cifar-10-python.tar')\r\n exit()","async def get(name, version, results, progress):\n\n buf = BytesIO()\n\n client = httpx.AsyncClient()\n\n async with client.stream(\n \"GET\", f\"https://pydocs.github.io/pkg/{name}-{version}.zip\"\n ) as response:\n total = int(response.headers[\"Content-Length\"])\n\n download_task = progress.add_task(f\"Download {name} {version}\", total=total)\n async for chunk in response.aiter_bytes():\n buf.write(chunk)\n progress.update(download_task, completed=response.num_bytes_downloaded)\n\n if response.status_code != 200:\n results[(name, version)] = None\n else:\n buf.seek(0)\n results[(name, version)] = buf.read()","def ctakeout_download():\r\n name = request.args[\"address\"]\r\n takeouts = get_zipcode_takeouts(name)\r\n\r\n return Response(takeouts.to_json(), 200, mimetype=\"application/json\")","def download(oformat, param, stream, year, month, timestep, back, queue):\n update = False\n if back and timestep != 'mon':\n print('You can the backwards option only with monthly data')\n sys.exit()\n if queue:\n dump_args(update, oformat, stream, list(param), year, list(month), timestep, back)\n else: \n api_request(update, oformat, stream, list(param), year, list(month), timestep, back)","def GetAndSave(self, url, save_suffix, unzip=False):\n self.connection.request('GET',\n '/data/' + url,\n headers={'content-type': 'text/plain'})\n response = self.connection.getresponse()\n file_name = Clean(url) + save_suffix\n destination = os.path.join(self.path, file_name)\n\n if response.status != 200:\n raise IOError(url)\n\n if unzip:\n s = StringIO.StringIO(response.read())\n content = gzip.GzipFile(fileobj=s).read()\n else:\n content = response.read()\n\n with open(destination, 'w') as f:\n f.write(content)\n return content","def load_zip_folder(req_path, name, ext, zip_path):\n BASE_DIR = ROOT\n full_path = \"%s/%s.%s\" % (req_path, name, ext)\n full_real_path = get_real_path(BASE_DIR, full_path)\n try:\n zip_path = unquote(zip_path).encode('utf-8')\n except Exception as e:\n logger.info(\"Failed to encode: %s\", zip_path)\n\n if not os.path.exists(full_real_path):\n logger.error(\"No Path: %s\", full_real_path)\n return ('', 204)\n\n if ext not in archive_exts:\n return ('', 204)\n\n #get list of files in folder in zip file\n data = ComixData(Directories=[], Files=[])\n with zipfile.ZipFile(full_real_path) as zf:\n for name in zf.namelist():\n name = name.decode('euc-kr').encode('utf-8')\n pardir, basename = os.path.split(name)\n if basename and zip_path == pardir:\n logger.info(\"get_files_in_zip_path: %s, %s\", pardir, basename)\n data.Files.append(basename)\n if len(data.Files):\n response = flask.Response(json.dumps(data._asdict(), ensure_ascii=False), headers=None)\n return response\n\n return ('', 204)","def _download_zip(self, zip_url, dest_dir):\n # TODO(jsirois): Wrap with workunits, progress meters, checksums.\n self.context.log.info('Downloading {}...'.format(zip_url))\n sess = requests.session()\n sess.mount('file://', self.LocalFileAdapter())\n res = sess.get(zip_url)\n if not res.status_code == requests.codes.ok:\n raise TaskError('Failed to download {} ({} error)'.format(zip_url, res.status_code))\n\n with open_zip(BytesIO(res.content)) as zfile:\n safe_mkdir(dest_dir)\n for info in zfile.infolist():\n if info.filename.endswith('/'):\n # Skip directories.\n continue\n # Strip zip directory name from files.\n filename = os.path.relpath(info.filename, get_basedir(info.filename))\n f = safe_open(os.path.join(dest_dir, filename), 'w')\n f.write(zfile.read(info))\n f.close()","def get(self, zipcode):\n response = hereService.getWeatherByZipcode(zipcode)\n return response","def fetch(data_dir):\n file_path = os.path.join(data_dir, DESTINATION, ZIP_NAME)\n result_path = os.path.join(data_dir, DESTINATION, NAME)\n return utils.fetch(URL, file_path, result_path)","def download(self):\r\n \r\n # RAR Files names\r\n if self.debug==0:\r\n rar_files_name = [\"K001.rar\",\"K002.rar\",\"K003.rar\",\"K004.rar\",\"K005.rar\",\"K006.rar\",\r\n \"KA01.rar\", \"KA03.rar\", \"KA04.rar\", \"KA05.rar\", \"KA06.rar\", \"KA07.rar\", \r\n \"KA08.rar\", \"KA09.rar\", \"KA15.rar\", \"KA16.rar\", \"KA22.rar\", \"KA30.rar\", \r\n \"KB23.rar\", \"KB24.rar\", \"KB27.rar\", \r\n \"KI01.rar\", \"KI03.rar\", \"KI04.rar\", \"KI05.rar\", \"KI07.rar\", \"KI08.rar\", \r\n \"KI14.rar\", \"KI16.rar\", \"KI17.rar\", \"KI18.rar\", \"KI21.rar\"]\r\n else:\r\n rar_files_name = [\"K002.rar\", \"KA01.rar\", \"KI01.rar\"]\r\n\r\n url = self.url\r\n \r\n dirname = self.rawfilesdir\r\n dir_rar = \"rar_files\"\r\n if not os.path.isdir(dirname):\r\n os.mkdir(dirname)\r\n if not os.path.isdir(os.path.join(dirname, dir_rar)):\r\n os.mkdir(os.path.join(dirname, dir_rar))\r\n \r\n\r\n print(\"Downloading RAR files:\")\r\n for i in rar_files_name:\r\n file_name = i\r\n if not os.path.exists(os.path.join(dirname, dir_rar, file_name)):\r\n urllib.request.urlretrieve(url+file_name, os.path.join(dirname, dir_rar, file_name))\r\n print(file_name)\r\n \r\n print(\"Extracting files:\")\r\n for i in rar_files_name:\r\n if not os.path.exists(os.path.join(dirname, i[:4])):\r\n file_name = os.path.join(dirname, dir_rar, i)\r\n Archive(file_name).extractall(dirname) \r\n print(i)\r\n\r\n if self.debug==0:\r\n files_path = self.files\r\n else:\r\n files_path = files_debug(self.rawfilesdir)\r\n\r\n print(files_path)\r\n self.files = files_path","def unzip() -> None:\n logger = logging.getLogger(__name__)\n logger.info('Download the dataset')\n\n # define the destination\n destination = project_dir / 'data' / 'raw'\n\n # extract zip\n zip_file = ZipFile(destination / \"original.zip\")\n zip_file.extractall(destination)","def get_text(self, url, *, timeout, headers):","def download(self):\n debug(str(self) + ' Downloading from newzbin.com..')\n if not NewzbinDownloader.canDownload():\n debug(str(self) + ' download: No www.newzbin.com login information')\n return\n\n info('Downloading newzbin NZB: %s ' % self.msgId)\n self.handleNZBDownloadFromNewzbin()","def fetch_zenodo(self):\n\n # retrieve content from URL\n try:\n logging.info(f\"Downloading example data from {self.url}\")\n r = requests.get(self.url, stream=True)\n with io.BytesIO() as stream:\n with tqdm.wrapattr(\n stream,\n 'write',\n file=sys.stdout,\n miniters=1,\n desc=self.url,\n total=int(r.headers.get('content-length', 0))\n ) as file:\n for chunk in r.iter_content(chunk_size=4096):\n file.write(chunk)\n with zipfile.ZipFile(stream) as zipped:\n # extract each file in the zipped dir to the project\n for f in zipped.namelist():\n logging.info(\"Unzipped: {}\".format(os.path.join(self.destination, f)))\n zipped.extract(f, self.destination)\n\n logging.info(\"Download and install complete.\")\n\n self.close_logger()\n\n except requests.exceptions.MissingSchema:\n msg = f\"Unable to download data from {self.url}\"\n logging.exception(msg)\n self.close_logger()\n raise","def get_my_zip_code(\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = GetMyZipCode.create(\n namespace=namespace,\n )\n return run_request(request, additional_headers=x_additional_headers, **kwargs)","def download_subtitle(search, results, filename, min_match=0,\n force=0, debug=0):\n s = Subseek()\n subtitleurl = False\n for result in s.order_match(search, results):\n match_text = s.clean_text(s.clean_html(result['text']),False,\n s.detect_encoding(s.clean_html(result['text']))\n ) + \" \" + s.clean_text(s.clean_html(result['description']),False,\n s.detect_encoding(s.clean_html(result['description'])))\n subtitleurl = result['link']\n rating_weight = s.text_weight(search, match_text)\n max_weight = s.text_weight(search)\n rating_match = rating_weight/max_weight*100\n if debug == 1:\n print \"Subtitle File URL: \" + subtitleurl\n print \" Text To Search: \" + search\n print \" Text To Match: \" + match_text\n print \" Text Match (%): \" + str(round(rating_match,2)) + \"%\"\n # check minimal match to use\n if rating_match >= min_match:\n downloaded = s.download(subtitleurl, filename + '.tmp')\n if downloaded == False:\n if debug == 1:\n print \"Error: connection or file creation failed\"\n subtitleurl = False\n else:\n if debug == 1:\n print \"File downloaded\"\n # unrar, unzip or get srt file\n typefile = s.get_sub_file_from_file(filename + '.tmp',\n search, force)\n if typefile == False:\n if debug == 1:\n print \"Subtitle file not found\"\n subtitleurl = False\n else:\n if debug == 1:\n print \"Subtitle file found in \" + typefile\n subtitleurl = True\n break\n else:\n if debug == 1:\n print \"Error: match less than \" + str(round(min_match,2))+ \"%\"\n subtitleurl = False\n break\n\n return subtitleurl","def fetch(self, url) -> bytes:\n buffer = self.download(url)\n zfs = ZipFileSystem(buffer, \"r\")\n return zfs.open(zfs.glob(\"*\")[0]).read()","def download_text_command():\n # 1. Get input scan id from Demisto\n scanid = demisto.args().get('scanid')\n # 2. Get the forensic webpage text from SlashNext API\n response = download_text(scanid=scanid)\n if response.get('errorNo') != 0:\n return\n # 3. Parse and format the response\n text_base64 = response.get('textData').get('textBase64')\n text_data = base64.b64decode(text_base64)\n\n text_file = fileResult('slashnext_{}.txt'.format(scanid), text_data, entryTypes['file'])\n\n demisto.results({\n 'Type': entryTypes['file'],\n 'ContentsFormat': formats['text'],\n 'Contents': 'Forensics: Webpage Rendered Text for URL Scan ID = {}'.format(scanid),\n 'File': text_file.get('File'),\n 'FileID': text_file.get('FileID')\n })","def download_test_files(request):\n\n # Log the start of the function\n logger.info(\"=========== returns ms1 test files from code directory input/ms1\")\n\n # create an absolute path to the 'example_data_dir' containing the test data files, then create\n # absolute paths to each test data file. Note the test data files are located in this code base.\n example_data_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)),'..','..','input/ms1')\n pos_input = os.path.join(example_data_dir, example_pos_filename)\n neg_input = os.path.join(example_data_dir, example_neg_filename)\n tracer_file = os.path.join(example_data_dir, example_tracer_filename)\n run_sequence_pos_file = os.path.join(example_data_dir, example_run_sequence_pos_filename)\n run_sequence_neg_file = os.path.join(example_data_dir, example_run_sequence_neg_filename)\n\n # create filenames\n filename1 = 'ms1_pos_input_test_data.csv'\n filename2 = 'ms1_neg_input_test_data.csv'\n filename3 = 'ms1_tracer_test_data.csv'\n filename4 = 'ms1_run_sequence_pos_test_data.csv'\n filename5 = 'ms1_run_sequence_neg_test_data.csv'\n\n # List of files to be zipped\n files_to_zip = {filename1: pos_input, filename2: neg_input, filename3: tracer_file, filename4: run_sequence_pos_file, filename5: run_sequence_neg_file}\n\n # Create an in-memory zip file\n in_memory_zip = BytesIO()\n with ZipFile(in_memory_zip, 'w', ZIP_DEFLATED) as zipf:\n # Add each file to the zipfile\n for filename in files_to_zip:\n logger.info('filename: {}'.format(filename))\n file_path = files_to_zip[filename]\n with open(file_path, 'rb') as file:\n file_content = file.read()\n zipf.writestr(filename, file_content)\n # The ZipFile object is automatically closed when exiting the 'with' block\n\n zip_filename = \"ms1_test_data_files.zip\"\n # Create an HTTP response with the zip file attached for download\n response = HttpResponse(in_memory_zip.getvalue(),content_type='application/zip')\n response['Content-Disposition'] = 'attachment; filename=' + zip_filename\n response['Content-length'] = in_memory_zip.tell()\n\n # Return the HTTP response\n return response","def _GetDownloadUrl(self):\n\n # Using access_token to get the transcript for the meeting that's mapped to meeting_id\n get_meeting_headers = {\n 'authorization': \"Bearer {access_token}\".format(access_token=self.access_token),\n 'content-type': \"application/json\"\n }\n try:\n request_endpoint = \"/v2/users/me/recordings?from=2000-01-01\"\n self.conn.request(\"GET\", request_endpoint, headers=get_meeting_headers)\n res = self.conn.getresponse()\n data = res.read().decode(\"utf-8\")\n response = json.loads(data)\n except:\n print(\"Bad Response to access recordings.\")\n print(data)\n \n # Download the transcript if it exists\n download_url = None\n print(88888888888888888)\n print(response)\n for meeting in response[\"meetings\"]:\n if \"recording_files\" not in meeting or meeting[\"id\"] != self.meeting_id:\n continue\n for recording_file in meeting[\"recording_files\"]:\n if \"recording_type\" not in recording_file:\n continue\n if recording_file[\"file_type\"] == \"TRANSCRIPT\": \n download_url = \"{endpoint}?access_token={access_token}\".format(endpoint=str(recording_file[\"download_url\"]), access_token=self.access_token)\n return download_url","def prepare_zip(self, filename, *args, **kwargs):\n\n return '/vsizip/' + filename, args, kwargs","def download(data_type, gs_aoi, main_dir):\n # Get URLs for tiles covered by a polygon:\n # ----------------------------------------\n tiles = get_tile_names(gs_aoi)\n print('Found {} products'.format(len(tiles['tile_names'])))\n\n # Make sure temporary folder for download exists:\n # -----------------------------------------------\n dwn_dir = join(main_dir, data_type)\n if not exists(dwn_dir):\n makedirs(dwn_dir)\n\n # Proceed to download:\n # --------------------\n if data_type == 'DTM':\n # DOWNLOAD DTM FILES & UNZIP:\n # ---------------------------\n print('\\nDownloading DTM files:')\n for num, name in enumerate(tiles['dtm_url']):\n print('{} of {}'.format(num+1, len(tiles['dtm_url'])))\n dwn_stat, file_name = download_file(name, dwn_dir)\n print('File {}.'.format(dwn_stat))\n extract_zip(join(dwn_dir, file_name))\n # Delete ZIP file after extraction\n remove(join(dwn_dir, file_name))\n \n # Finished downloading:\n # ---------------------\n out_msg = 'Finished downloading DTM files!'\n \n elif data_type == 'LAZ':\n # DOWNLOAD LAZ FILES:\n # -------------------\n print('\\nDownloading LAZ files:')\n for num, name in enumerate(tiles['laz_url']):\n print('{} of {}'.format(num+1, len(tiles['laz_url'])))\n dwn_stat, _ = download_file(name, dwn_dir)\n print('File {}.'.format(dwn_stat))\n \n # Finished downloading:\n # ---------------------\n out_msg = 'Finished downloading LAZ files!'\n \n else:\n dwn_dir = None\n out_msg = 'Unexpected data_type'\n \n # Output dictionary:\n # ------------------\n out = {'out_msg': out_msg,\n 'out_dir': dwn_dir}\n \n return out","def download_data(self):\n headers = {'User-Agent': 'Mozilla/5.0',}\n\n #Request for html data of url page\n r = requests.get(self.url, headers = headers, allow_redirects=True)\n soup = BeautifulSoup(r.text, \"html.parser\")\n\n #Checking if folder path exists, if not, creats it\n i=0\n while i<len(self.folder)-1:\n if self.folder[i] == '/':\n if not os.path.isdir(self.folder[:i]):\n os.mkdir(self.folder[:i])\n i+=1\n if i==len(self.folder)-1:\n if not os.path.isdir(self.folder):\n os.mkdir(self.folder)\n\n # if not os.path.isdir(self.folder):\n # os.mkdir(self.folder)\n\n #Gets every href to zip file with data\n entries = []\n for link in soup.find_all('a'):\n if re.search(\"^data/.*.zip\", link.get('href')):\n entries.append(link.get('href'))\n\n #Gets the newest dataset\n self.getCurrentData(entries)\n\n i=0\n #Saves each file in dataset\n for list in self.ListOfZipFiles:\n if not os.path.isfile(self.folder+list[4:]):\n r = requests.get(self.url+list)\n open(self.folder+list[4:], 'wb').write(r.content)\n #deletes prefix \"data/\"\n self.ListOfZipFiles[i] = list[4:]\n i+=1","def download(self, method, url, downloader, *args, **kwargs):\n if method.startswith('URL'):\n return downloader.enqueue_file(url, filename=partial(self.mk_filename, *args))\n\n raise NoData","def download(self, filename = None, format = 'srt', append = False):\n \n data = self.download_data(format)\n \n if filename != None:\n extension = '' if filename.lower().endswith('.srt') else '.srt'\n \n sys.stdout.write('Saving subtitle...\\n')\n \n out_dir = self.config.subtitles['out']\n if os.path.isfile(out_dir):\n raise OSError('Video output directory is not a directory, but is a file')\n elif not os.path.isdir(out_dir):\n os.mkdir(out_dir)\n \n mod = 'a' if append else 'w'\n f = open(out_dir + os.path.sep + filename + extension, mod)\n f.write(data)\n f.close()\n \n return data","def download():\n raise NotImplementedError","async def get_my_zip_code_async(\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = GetMyZipCode.create(\n namespace=namespace,\n )\n return await run_request_async(\n request, additional_headers=x_additional_headers, **kwargs\n )","def download(self, *args, **kwargs):\n return wb.download(*args, **kwargs)","def download_and_unzip(url, zip_path, csv_path, data_folder):\n\n download_from_url(url, zip_path)\n\n unzip(zip_path, csv_path, data_folder)\n\n print('Done.')","def _download_from_url(self) -> bytes:\n response = requests.get(self.url, allow_redirects=True)\n return response.content","def _download(self):\n self._system.download_file(\"http://curl.haxx.se/download/\" + self._tar_name)","def _download_project(name, apikey):\n payload = {'apikey': apikey, 'project': name, 'version': 'portia'}\n r = requests.get(DASH_API_URL + 'as/project-slybot.zip', params=payload)\n return r.content","def __connect_with_server(self,get_operatoin,server_reuest_type):\n\twhat_is_downloaded = server_reuest_type\n\tself.XML_String = None\n\tself.zip_string = None\n\ttry:\n\t conn = httplib.HTTPConnection(self.NAPISY24_url)\n\t conn.request(\"GET\", get_operatoin)\n\t r1 = conn.getresponse()\n\t print r1.status, r1.reason\n\t if what_is_downloaded == \"downloada_subtitle_list_by_film_name\" or what_is_downloaded == \"downloada_subtitle_list_by_IMDB\":\n\t\tself.XML_String = r1.read()\n\t elif what_is_downloaded == \"download_subtilte_zip\":\t\t\n\t\tself.zip_string = r1.read()\n\t return r1.status#, r1.reason\n\texcept (IOError, OSError), e:\n\t print >> sys.stderr, \"Napisy24.pl server connection error.\"\n\t time.sleep(0.5)","def testZipUrl(self):\n try:\n remoteLocator = self.__zipFileUrl\n # fn = self.__fileU.getFileName(remoteLocator)\n ok = self.__fileU.isLocal(remoteLocator)\n self.assertFalse(ok)\n #\n lPath = os.path.join(self.__workPath, self.__fileU.getFileName(self.__zipFileUrl))\n ok = self.__fileU.get(remoteLocator, lPath)\n self.assertTrue(ok)\n ok = self.__fileU.exists(lPath)\n self.assertTrue(ok)\n ok = self.__fileU.isLocal(lPath)\n self.assertTrue(ok)\n tPath = self.__fileU.getFilePath(lPath)\n self.assertEqual(lPath, tPath)\n fp = self.__fileU.uncompress(lPath, outputDir=self.__workPath)\n ok = fp.endswith(\"Food_Display_Table.xlsx\")\n self.assertTrue(ok)\n\n except Exception as e:\n logger.exception(\"Failing with %s\", str(e))\n self.fail()","def office_download_data(parser, args, params):\n parser.add_argument(\n '--station_list', type=str, help='Station file from IRIS',\n required=True, metavar='x')\n parser.add_argument(\n '--recording_time', type=int, \n help='Recording time from event start (seconds)', metavar='x',\n required=True)\n parser.add_argument(\n '--padding_time', type=int,\n help='Padding time', metavar='x',\n required=True)\n parser.add_argument(\n '--with_waveforms', action='store_true',\n help='Download waveform data (instead of just station data)')\n \n local_args = parser.parse_known_args(args)\n \n station_list = local_args[0].station_list\n with_waveforms = local_args[0].with_waveforms\n padding_time = local_args[0].padding_time\n recording_time = local_args[0].recording_time\n control.download_data(params, station_list, with_waveforms, recording_time,\n padding_time)","def certificates(request, course_id):\n\n course_event = get_object_or_404(CourseEvent, pk=course_id)\n outzip = get_certificates_zip(course_id)\n with open(outzip, 'rb') as myzip:\n response = HttpResponse(myzip.read())\n response['Content-Disposition'] = 'attachment; filename=certifikaty-{}-{}.zip'.format(\n course_event.date.strftime(\"%Y-%m-%d\"),\n course_event.course_type.title\n )\n response['Content-Type'] = 'application/x-zip'\n return response","def unzip_data():\n zip_ref = zipfile.ZipFile(data_zip, 'r')\n zip_ref.extractall('')\n zip_ref.close()","def DownloadFilesFromAPI(self, task_data: Dict[str, List[str]],\n path: str) -> Optional[str]:\n result = None\n self.RefreshClientCredentials()\n api_instance = turbinia_request_results_api.TurbiniaRequestResultsApi(\n self.client)\n try:\n task_id = task_data.get('id')\n api_response = api_instance.get_task_output(\n task_id, _preload_content=False)\n filename = f'{task_id}-'\n\n # Create a temporary file to write the response to.\n file = tempfile.NamedTemporaryFile(\n mode='wb', prefix=f'{filename}', suffix='.tgz', delete=False)\n local_path = file.name\n self.logger.info(f'Downloading output for task {task_id} to {local_path}')\n # Read the response and write to the file.\n for chunk in api_response.read_chunked():\n file.write(chunk)\n file.close()\n\n # Extract the files from the tgz file.\n extracted_path = self._ExtractFiles(local_path, path)\n if os.path.exists(extracted_path):\n result = extracted_path\n self.PublishMessage(\n f'Extracted output file to {result} for task {task_id}')\n except turbinia_api_lib.ApiException as exception:\n self.ModuleError(\n f'Unable to download task data: {exception}', critical=False)\n except OSError as exception:\n self.ModuleError(f'Unable to write to file: {exception}', critical=False)\n\n return result","def get_workspace_zip(self):\n workspace_api = '/ws/'\n # print(\"Checking Workspaces For: {}\".format(self.url))\n workspace_elements = self._grab_tags(self.url + workspace_api)\n workspace_links = []\n root_domain = urllib.parse.urlparse(self.url).scheme + '://' + urllib.parse.urlparse(self.url).netloc\n for link in workspace_elements.find_all(name='a', href=True):\n if '/execution/node/' in link['href']:\n workspace_links.append(link['href'])\n if len(workspace_links) > 0:\n for workspace_link in workspace_links:\n single_workspace_elements = self._grab_tags(root_domain + workspace_link)\n for link in single_workspace_elements.find_all(name='a', href=True):\n if '/*zip*/' in link['href']:\n # URL returned as relative link, must reconstruct\n print(\"FOUND ZIP: {}\".format(root_domain + workspace_link + link['href']))\n return root_domain + workspace_link + link['href']","def download(request, snippet_id):\n snippet = get_object_or_404(Snippet, pk=snippet_id)\n response = HttpResponse(snippet.code, mimetype='text/plain')\n response['Content-Disposition'] = 'attachment; filename=%s.%s' % (snippet.id,\n snippet.language.file_extension)\n response['Content-Type'] = snippet.language.mime_type\n return response","def zip_open_text(zip, filename):\n if isinstance(zip, FakeZip):\n return zip.open(filename)\n else:\n # Wrap the zip file to decode.\n return io.TextIOWrapper(zip.open(filename, 'r'), encoding='utf8')","def download():\n toydata = requests.get(DATA_URL).json()\n return toydata","def download_one_zip(data_url, data_dir):\r\n\r\n zipfile_path, unzip_dir = zip_file_name_from_url(data_url, data_dir)\r\n if not is_there_file(zipfile_path, unzip_dir):\r\n if not os.path.isdir(unzip_dir):\r\n os.makedirs(unzip_dir)\r\n r = requests.get(data_url, stream=True)\r\n with open(zipfile_path, \"wb\") as py_file:\r\n for chunk in r.iter_content(chunk_size=1024): # 1024 bytes\r\n if chunk:\r\n py_file.write(chunk)\r\n unzip_nested_zip(zipfile_path, unzip_dir), download_small_file","def transmit(self, location, args):\r\n args = dict(args)\r\n args['utf8'] = '\\u2713'\r\n\r\n data = json.dumps(args)\r\n\r\n\r\n req = urlrequest.Request(self.host + location, data, self.headers)\r\n\r\n if self.timeout:\r\n response = urlrequest.urlopen(req, None, self.timeout)\r\n else:\r\n response = urlrequest.urlopen(req)\r\n\r\n code = response.code\r\n data = response.fp.read()\r\n\r\n log.info(\"Response status: %s\\nResponse data: \\n%s\\n\" % (code, data))","def download():\n base_loc = DATA_DIR + '/raw/human_activity'\n loc = base_loc + '/human_activity.zip'\n if os.path.exists(loc):\n print('Path already exists at {}. If you wish to re-download you must delete this folder.'.format(loc))\n return\n if not os.path.exists(base_loc):\n os.mkdir(base_loc)\n\n url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/00341/HAPT%20Data%20Set.zip'\n urllib.request.urlretrieve(url, loc)\n\n with zipfile.ZipFile(loc, 'r') as zip_ref:\n zip_ref.extractall(base_loc)","def fromZip(self, zip_location,extract_location):\n zip_file = zipfile.ZipFile(zip_location,'r')\n zip_file.extractall(extract_location)","def dowload_vt():\n print get_date_time_now() + \" ==> Download VT Samples started!\"\n print get_date_time_now() + \" ==> Nothing downloaded\"","def generate(self, text):\n self.__params['text']=text\n self._data = requests.get(self.TTS_URL, params=self.__params,\n stream=False).iter_content()","def download_text(scanid):\n # Create the required data dictionary for Download/Text\n api_data = {\n 'scanid': scanid\n }\n response = http_request(endpoint=DL_TEXT_API, data=api_data)\n\n if response.get('errorNo') == 1:\n demisto.results(\n 'Your Url Scan request is submitted to the cloud and may take up-to 60 seconds to complete.\\n'\n 'Please check back later using \"slashnext-download-text\" command with Scan ID = {}'.format(scanid))\n elif response.get('errorNo') != 0:\n return_error('API Returned, {}:{}'.format(response.get('errorNo'), response.get('errorMsg')))\n\n return response","def download (httpfile, path_unzip = None, outfile = None) :\n if path_unzip is None : path_unzip = GetPath ()\n file = _check_source (httpfile, path_unzip = path_unzip, outfile = outfile)\n return file","def getROZip(self, rouri):\n (status, reason, headers, uri, data) = self.doRequestFollowRedirect(rouri,\n method=\"GET\", accept=\"application/zip\")\n if status in [200, 404]:\n return (status, reason, headers, URIRef(uri), data)\n raise self.error(\"Error retrieving RO as ZIP file\",\n \"%03d %s\"%(status, reason))","def search_and_download_raw(self, search_term):\n \n # delete old file if it exists\n if path.exists(self.SEARCH_RESULTS_ZIP_FILE_NAME):\n os.remove(self.SEARCH_RESULTS_ZIP_FILE_NAME)\n \n # perform search and download zip archive of all matching studies\n self.browser.get(self.CLINICAL_TRIALS_BASE_URL + urlencode({\"term\": search_term}))\n\n try:\n self.browser.find_element_by_id('downloadAdvancedForm').submit()\n \n # wait for the zip archive to download; for some reason there has to be a delay, else the zip file will not finish\n # downloading correctly...\n while (not path.exists(self.SEARCH_RESULTS_ZIP_FILE_NAME)) or (not zipfile.is_zipfile(self.SEARCH_RESULTS_ZIP_FILE_NAME)):\n sleep(.1)\n\n os.rename(self.SEARCH_RESULTS_ZIP_FILE_NAME, \"clinical_trials_gov_results_%s.zip\" % search_term)\n\n return \"clinical_trials_gov_results_%s.zip\" % search_term\n except NoSuchElementException as e:\n print(e)\n return None","def tile(self, z, x, y_tms):\n logger.debug(_(\"Download tile %s\") % ((z, x, y_tms),))\n # Render each keyword in URL ({s}, {x}, {y}, {z}, {size} ... )\n size = self.tilesize\n s = self.tiles_subdomains[(x + y_tms) % len(self.tiles_subdomains)];\n y_osm = (2**int(z) - 1) - int(y_tms)\n try:\n url = self.tiles_url.format(**locals())\n except KeyError, e:\n raise DownloadError(_(\"Unknown keyword %s in URL\") % e)\n logger.debug(_(\"Retrieve tile at %s\") % url)\n r = DOWNLOAD_RETRIES\n sleeptime = 1\n while r > 0:\n try:\n request = urllib2.Request(url)\n for header, value in self.headers.items():\n request.add_header(header, value)\n stream = urllib2.urlopen(request)\n assert stream.getcode() == 200\n return stream.read()\n except (AssertionError, IOError), e:\n logger.debug(_(\"Download error, retry (%s left). (%s)\") % (r, e))\n r -= 1\n time.sleep(sleeptime)\n # progressivly sleep longer to wait for this tile\n if (sleeptime <= 10) and (r % 2 == 0):\n sleeptime += 1 # increase wait\n raise DownloadError(_(\"Cannot download URL %s\") % url)","def cli(date, path, mission):\n download.main(path, mission, date)","def getzip_requests(url, zipfile, unzipdir):\n with closing(requests.get(url, stream=True)) as r:\n if r.headers.get('content-type') == None or r.headers.get('content-type') != 'application/zip':\n warning = \"{} doesn't seem to be a zip file. Unzipping may fail.\".format(url)\n warn(warning)\n with open(zipfile, 'wb') as fd:\n for chunk in r.iter_content():\n fd.write(chunk)\n with ZipFile(zipfile, 'r') as zip:\n zip.extractall(unzipdir)\n os.remove(zipfile)","def GET(self, subresource: str = \"\", **kwargs: str) -> bytes:\n\n q = kwargs.get(\"q\", \"\")\n wayback = kwargs.get(\"wayback\", \"\")\n offset = int(kwargs.get(\"offset\", 0))\n max_days = int(kwargs.get(\"max_days\", 180))\n per_page = int(kwargs.get(\"per_page\", 20))\n order = kwargs.get(\"order\", \"rank\")\n\n if q:\n return self.search(q, per_page, offset, order)\n\n if wayback:\n return self.check_wayback_availability(wayback)\n\n if subresource == \"taglist\":\n return self.taglist()\n\n return self.index(per_page, offset, order, max_days)","def play_video(path):\r\n #logger.info(\"######: {}, log: {}########\".format('rk8', path))\r\n #original=https://api.hotstar.com/h/v1/play?contentId=1000238814\r\n #path=\"https://api.hotstar.com/h/v2/play/in/contents/1000238814\"\r\n # Create a playable item with a path to play.\r\n data = make_request(path)\r\n #logger.info(\"######: {}, log: {}########\".format('rk3', path))\r\n if not data:\r\n return\r\n\r\n def get_subtitle(url):\r\n #\r\n # https://hses.akamaized.net/videos/hotstarint/hostages/1260003409/1558430241469/\r\n # 265b9dab22d4e9a033e6df6f89639f17/master.m3u8?hdnea=st=1560107863~exp=1560111463~acl=\r\n # /*~hmac=2f6fb393159ed5fa1b12bbf12e954eb377cfa0fc852d4ff5eb24446233237620\r\n #\r\n # https://hses.akamaized.net/videos/hotstarint/hostages/1260003409/1558430241469/\r\n # 5d0f83c3ccbf4501cf952bdfc8c0d785/subtitle/lang_en/sub-0.vtt\r\n #\r\n _url = urlparse(url)\r\n values = _url._asdict()\r\n values['query'] = ''\r\n values['path'] = '{}/subtitle/lang_en/sub-0.vtt'.format(\"/\".join(values['path'].split('/')[:-1]))\r\n\r\n subtitle_url = ParseResult(**values).geturl()\r\n # subtitle_file = kodiutils.download_url_content_to_temp(subtitle_url, '{}-{}.srt'.format(\r\n # Zee5Plugin.safe_string(item['title']),\r\n # subtitle_lang,\r\n # ))\r\n\r\n return subtitle_url\r\n\r\n #logger.info(\"######: {}, log: {}########\".format('rk6', data))\r\n #item = data['body']['results']['item']\r\n item=data['body']['results']['playBackSets'][0]\r\n path = item['playbackUrl']\r\n licenseURL = item.get('licenseUrl')\r\n subtitle = get_subtitle(path)\r\n\r\n logger.info('Playing video URL: {}, licenseURL: {}, subtitle: {}'.format(path, licenseURL, subtitle))\r\n\r\n play_item = xbmcgui.ListItem(path=path)\r\n if licenseURL:\r\n play_item.setProperty('inputstreamaddon', 'inputstream.adaptive')\r\n play_item.setProperty('inputstream.adaptive.manifest_type', 'hls')\r\n play_item.setMimeType('application/dash+xml')\r\n play_item.setContentLookup(False)\r\n\r\n play_item.setSubtitles([get_subtitle(path)])\r\n\r\n # Pass the item to the Kodi player.\r\n xbmcplugin.setResolvedUrl(_handle, True, listitem=play_item)","def get_subtitleinfo(fileFullName):\n sys.stdout.write(\"Requesting subtitle info...\\n\")\n\n #接口获取字幕信息\n response = requests.post(\n \"https://www.shooter.cn/api/subapi.php\",\n verify=False,\n params= {\n 'filehash': ComputeFileHash(fileFullName),\n 'pathinfo': os.path.realpath(fileFullName),\n 'format': 'json',\n 'lang': \"Chn\",\n },\n )\n #未找到字幕处理\n if response.text == u'\\xff':\n sys.stderr.write(\"Subtitle not found.\\n\")\n sys.exit(1)\n return response","def zipname(self):\n _, tail = os.path.split(self.url)\n return self.folder + '/' + tail","def _download(self):\n self._system.download(\"http://geant4.web.cern.ch/geant4/support/source/\" + self._tar_name)","def download_flight_data():\n response = requests.get(FlightAndRoutConst.URL_FLIGHTS_OF_SPRING_AIRLINE,\n headers={'Content-type': 'text/html; charset=utf-8'})\n output_path = build_file_name()\n # Using response.text instead of response.content for chinese string display\n IOUtils.write_to_file(str(response.text), output_path)\n return output_path","def download():\n try:\n cli.run(\n [URL, '--output', TEMP_DIR],\n )\n except SystemExit:\n return None","def downloadObject(self, obj, workingDir=None):\n\n fp = Path(obj.name).with_suffix('.zip')\n if workingDir:\n fp = Path(workingDir, fp)\n\n return self._download(self.fullUrl(obj.downloadUrl), fp.name)","def download_and_unzip_data(url, destination, prefix='state-'):\n # make sure destination exists or create a temporary directory\n if not destination:\n destination = tempfile.mkdtemp(prefix=prefix)\n logger.debug(\"Created temp directory {}\".format(destination))\n else:\n if not os.path.exists(destination):\n os.makedirs(destination)\n logger.info(\"Created {}\".format(destination))\n zip_filename = get_zipfile_path(url, destination)\n # don't re-download data if raw data file already exists\n if os.path.exists(zip_filename):\n logger.debug(\"{} exists, skipping download\".format(zip_filename))\n else:\n logger.debug(\"Downloading data to {}\".format(zip_filename))\n response = requests.get(url, stream=True)\n # XXX check status code here; e.g., if permissions haven't been granted\n # for a file being downloaded from S3 a 403 will be returned\n content_length = int(response.headers.get('content-length'))\n start = time.clock()\n downloaded = 0\n with open(zip_filename, 'wb') as f:\n for chunk in response.iter_content(chunk_size=1024):\n if chunk:\n downloaded += len(chunk)\n now = time.clock()\n if (now - start) >= 5:\n logger.debug('{0:.2g}% downloaded'.format(downloaded/content_length*100))\n start = now\n f.write(chunk)\n f.flush()\n logger.debug('100% downloaded')\n\n unzip_data(destination, url=url)\n return destination","def download_analysis(group_id, project_label, analysis_label, save_dir, file_starts_with=None, api_key=None):\n api_key = get_fw_api(api_key)\n fw = flywheel.Client(api_key)\n project = fw.lookup(f\"{group_id}/{project_label}\")\n\n orig_dir = Path.cwd()\n out_dir = Path(save_dir) / analysis_label\n zip_out_dir = out_dir / \"00_zip\"\n extract_out_dir = out_dir / \"00_extract\"\n zip_out_dir.mkdir(parents=True, exist_ok=True)\n extract_out_dir.mkdir(parents=True, exist_ok=True)\n\n os.chdir(zip_out_dir)\n\n print(\"DOWNLOAD\")\n for subject in project.subjects():\n print(subject.label)\n analyses = fw.get_container_analyses(subject.id, filter=f'label=\"{analysis_label}\"')\n assert len(analyses) <= 1, \"More than one analysis found\"\n\n # if no analyses on subject level, look into sessions\n if not analyses:\n analyses = []\n for session in subject.sessions():\n analyses_session = fw.get_container_analyses(session.id, filter=f'label=\"{analysis_label}\"')\n assert len(analyses_session) <= 1, \"More than one analysis found\"\n analyses += analyses_session\n\n if analyses:\n for analysis in analyses:\n if analysis.files:\n files = [file_obj.name for file_obj in analysis.files]\n else:\n files = []\n\n # filter files\n download_files = []\n if file_starts_with:\n for f in files:\n if f.startswith(file_starts_with):\n download_files.append(f)\n else:\n download_files = files\n\n for file in download_files:\n print(file)\n analysis.download_file(file, file)\n\n print(\"UNZIP\")\n zipfiles = list(zip_out_dir.glob(\"*.zip\"))\n for file in zipfiles:\n with ZipFile(file, \"r\") as zip_ref:\n zip_ref.extractall(extract_out_dir)\n\n print(\"MOVE AND CLEAN UP\")\n # remove id hierarchy and move to out_dir\n # e.g., '5f34/sub-x/ses-y/func/*bold.json'\n # 'sub-x/ses-y/func/*bold.json'\n os.chdir(extract_out_dir)\n file_tree = [f for f in Path(\".\").rglob(\"*\") if f.is_file()]\n file_overwritten = []\n for in_file in file_tree:\n out_file = out_dir / Path(*in_file.parts[1:])\n out_file.parent.mkdir(parents=True, exist_ok=True)\n print(in_file, out_file)\n if out_file.is_file():\n file_overwritten.append(out_file)\n in_file.rename(out_file)\n\n if file_overwritten:\n file_overwritten_str = '\\n'.join([str(f) for f in set(file_overwritten)])\n warn(f\"{len(set(file_overwritten))} have been overwritten, because of multiple files with the same name in \"\n f\"different analyses.\\n{file_overwritten_str}\")\n shutil.rmtree(extract_out_dir)\n shutil.rmtree(zip_out_dir)\n\n print(\"DONE\")\n os.chdir(orig_dir)","def download(self, api_route, dest_path, payload=None, file_type_header=None, extract_archives=True):\n resp = None\n payload = payload or {}\n file_type_header = file_type_header or self.default_file_type_header\n\n try:\n # Fetch the file from the API.\n resp = self.api.get(api_route, payload=payload, stream=True)\n except KeyboardInterrupt:\n exit()\n\n # Extract further info about the downloaded file.\n file_ext, file_is_archive = self._analyze_response_file(resp, file_type_header)\n\n # Calculate the final path to save downloaded file at.\n save_to, extract_to = self._calc_final_dest(\n dest_path,\n file_ext,\n file_is_archive,\n extract_archives,\n payload.get('name') or self.default_name\n )\n\n # Stream file to save path.\n self._stream_to_path(save_to, resp.response_obj, int(resp.headers.get('Content-Length')))\n\n # If no archive extraction needed, just return the path at which the file was saved.\n if not extract_to:\n return save_to\n\n # Extract archive to final destination.\n extract_zip(save_to, extract_to)\n\n return extract_to","def download_dataset():\n \n ID = \"1-3_oB5iSF-c_V65-uSdUlo024NzlgSYZ\"\n script1 = f\"\"\"\n wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --quiet --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id='{ID} -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\\1\\n/p')&id=\"{ID} -O Data.zip && rm -rf /tmp/cookies.txt\n \"\"\"\n script2 = \"\"\"unzip Data.zip\"\"\"\n\n os.system(script1)\n os.system(script2)","def download_data():\n url = 'https://www.dropbox.com/s/8oehplrobcgi9cq/imdb.tgz?dl=1'\n urllib.request.urlretrieve(url, 'imdb.tgz')\n tar = tarfile.open(\"imdb.tgz\")\n tar.extractall()\n tar.close()","def getSubtitleURL(self):\n\n # If it is a movie, we use this methodology -\n try:\n IndexingParameters = [\"subtitleUrls\", 0, \"url\"]\n TitleParamters = [\n \"catalogMetadata\", \"catalog\", \"title\", \"episodeNumber\"]\n subRequestObject = requests.get(self.subtitleURLContainer)\n\n parsedJsonObject = json.loads(str(subRequestObject.text))\n SubsURL = parsedJsonObject[IndexingParameters[0]][\n IndexingParameters[1]][IndexingParameters[2]]\n if self.title == \"Amazonsubtitles\":\n try:\n self.title = parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[2]] + \"_\" + str(\n parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[3]])\n except:\n pass\n\n return SubsURL\n\n except:\n pass\n pass","def download(self):\n if not self.url:\n raise RuntimeError(self.tips)\n\n download_file_name = os.path.join(\n self.raw_path, os.path.splitext(os.path.basename(self.url))[0]\n )\n file_format = self.url.split(\".\")[-1]\n if \"amazon\" in self.url:\n raw_file_path = os.path.join(\n self.raw_path, f\"{self.dataset_name}.json.{file_format}\"\n )\n else:\n raw_file_path = os.path.join(\n self.raw_path, f\"{self.dataset_name}.{file_format}\"\n )\n if \"1drv.ms\" in self.url:\n file_format = \"zip\"\n raw_file_path = os.path.join(\n self.raw_path, f\"{self.dataset_name}.{file_format}\"\n )\n if not os.path.exists(raw_file_path):\n print(f\"download_file: url: {self.url}, raw_file_path: {raw_file_path}\")\n download_file(self.url, raw_file_path)\n if \"amazon\" in raw_file_path:\n # amazon dataset do not unzip\n print(\"amazon dataset do not decompress\")\n return\n elif file_format == \"gz\":\n file_name = raw_file_path.replace(\".gz\", \"\")\n with gzip.open(raw_file_path, \"rb\") as fin:\n with open(file_name, \"wb\") as fout:\n shutil.copyfileobj(fin, fout)\n else:\n shutil.unpack_archive(\n raw_file_path, self.raw_path, format=get_format(file_format)\n )\n\n if not os.path.exists(download_file_name):\n return\n elif os.path.isdir(download_file_name):\n os.rename(\n download_file_name, os.path.join(self.raw_path, self.dataset_name)\n )\n else:\n os.rename(\n download_file_name,\n os.path.join(\n self.raw_path,\n f'{self.dataset_name}.{download_file_name.split(\".\")[-1]}',\n ),\n )","def download():\n\treturn response.download(request, db)"],"string":"[\n \"def download(self):\\n if not os.path.isdir(self.save_path):\\n try:\\n os.mkdir(self.save_path)\\n except IOError:\\n print(\\\"Can't create subfolder. \\\"\\n \\\"Check that you have write access for \\\"\\n \\\"{}\\\".format(self.save_path))\\n\\n sub_zip_file = request.urlopen(self.download_link)\\n sub_gzip = gzip.GzipFile(fileobj=StringIO(sub_zip_file.read()))\\n subtitle_content = sub_gzip.read()\\n try:\\n with open(self.full_path, 'wb') as subtitle_output:\\n subtitle_output.write(subtitle_content)\\n print(\\\"Downloaded subtitle...\\\")\\n except IOError:\\n print(\\\"Couldn't save subtitle, permissions issue?\\\")\",\n \"def download_data(self, format = 'srt'):\\n \\n def to_ascii(data):\\n \\\"\\\"\\\"\\n Remove non-ascii characters\\n \\\"\\\"\\\"\\n return ''.join([x for x in data if ord(x) < 128])\\n \\n url = self.config.subtitles['url'] % (self.media_resource_id)\\n \\n print url\\n resp, content = httplib2.Http(\\\".cache\\\").request(url, \\\"GET\\\")\\n \\n subtitles = json.loads(content)['subtitles']\\n \\n final_data = ''\\n if format == 'srt':\\n final_data += self.to_srt(subtitles)\\n else:\\n final_data += subtitles\\n \\n return to_ascii(final_data)\",\n \"def downloadData(self, strZipUrl: str) -> str:\\n wget.download(strZipUrl, os.path.join(self.strDataDir, os.path.basename(strZipUrl)))\\n\\n return os.path.join(self.strDataDir, os.path.basename(strZipUrl))\",\n \"def download(self, language, filename, filetype):\\n if language not in self.languages.keys():\\n print \\\"Theres's no subtitle in this language\\\"\\n sys.exit()\\n url = \\\"http://www.youtube.com/api/timedtext?v={0}&lang={1}\\\".format(self.video_id, language)\\n self.subtitle = urllib2.urlopen(url)\\n if filetype == \\\"srt\\\":\\n self.writeSRTFile(filename)\\n else:\\n self.writeXMLFile(filename)\",\n \"def get_sample_zip(self, sha256):\\n return self.__make_api_call('get/sample/{}/zip'.format(sha256))\",\n \"def download_data(self, format = 'srt'):\\n resp, content = httplib2.Http(\\\".cache\\\").request(self.url, \\\"GET\\\")\\n suburl = json.loads(content)['url']\\n resp, content = httplib2.Http(\\\".cache\\\").request(suburl, \\\"GET\\\")\\n\\n return content\",\n \"def download():\\n response = requests.get(URL, stream=True)\\n\\n file = open(FILE_NAME, 'wb')\\n file.write(response.content)\\n\\n with zipfile.ZipFile(FILE_NAME, 'r') as zip_ref:\\n zip_ref.extractall()\\n\\n file.close()\\n os.remove(FILE_NAME)\",\n \"def unzip_subtitles(self, zip_filepath):\\n with ZipFile(zip_filepath, 'r') as zip_obj:\\n filenames = zip_obj.namelist()\\n\\n subtitle_filenames = [fn for fn in filenames if fn.endswith('.srt')]\\n for fn in subtitle_filenames:\\n zip_obj.extract(fn, self.temp_storage_dir)\\n\\n return subtitle_filenames\",\n \"def test_result_file_path_get(self):\\n headers = { \\n 'Accept': 'application/zip',\\n }\\n response = self.client.open(\\n '/v1/result/{file_path}'.format(file_path='file_path_example'),\\n method='GET',\\n headers=headers)\\n self.assert200(response,\\n 'Response body is : ' + response.data.decode('utf-8'))\",\n \"def download_zip(self, path: Path) -> Path:\\n if not self.url:\\n raise ValueError(\\\"Release must have a valid url to download the zip.\\\")\\n\\n with requests.get(self.url, stream=True) as response:\\n with open(path, \\\"wb\\\") as download_file:\\n shutil.copyfileobj(response.raw, download_file)\\n\\n return path\",\n \"def download_data():\\n\\n if not os.path.exists(zipfile_path):\\n print(f'Downloading {config.download_url} to {zipfile_path}')\\n urlretrieve(config.download_url, zipfile_path)\\n print(f'Successfully downloaded {zipfile_path}')\\n\\n zip_ref = ZipFile(zipfile_path, 'r')\\n zip_ref.extractall(config.raw_data_dir)\\n zip_ref.close()\\n\\n os.rename(f\\\"{config.raw_data_dir}/cornell movie-dialogs corpus\\\", extracted_dir)\",\n \"def _download(data_folder): # pragma: no cover\\n\\n logger.info(f\\\"Downloading {SOURCE_URL}.\\\")\\n\\n with urlopen(SOURCE_URL) as zipresp:\\n with zipfile.ZipFile(io.BytesIO(zipresp.read())) as zfile:\\n zfile.extractall(data_folder)\",\n \"def download_transcripts(request):\\r\\n locator = request.GET.get('locator')\\r\\n if not locator:\\r\\n log.debug('GET data without \\\"locator\\\" property.')\\r\\n raise Http404\\r\\n\\r\\n try:\\r\\n item = _get_item(request, request.GET)\\r\\n except (InvalidKeyError, ItemNotFoundError):\\r\\n log.debug(\\\"Can't find item by locator.\\\")\\r\\n raise Http404\\r\\n\\r\\n subs_id = request.GET.get('subs_id')\\r\\n if not subs_id:\\r\\n log.debug('GET data without \\\"subs_id\\\" property.')\\r\\n raise Http404\\r\\n\\r\\n if item.category != 'video':\\r\\n log.debug('transcripts are supported only for video\\\" modules.')\\r\\n raise Http404\\r\\n\\r\\n filename = 'subs_{0}.srt.sjson'.format(subs_id)\\r\\n content_location = StaticContent.compute_location(item.location.course_key, filename)\\r\\n try:\\r\\n sjson_transcripts = contentstore().find(content_location)\\r\\n log.debug(\\\"Downloading subs for %s id\\\", subs_id)\\r\\n str_subs = generate_srt_from_sjson(json.loads(sjson_transcripts.data), speed=1.0)\\r\\n if not str_subs:\\r\\n log.debug('generate_srt_from_sjson produces no subtitles')\\r\\n raise Http404\\r\\n response = HttpResponse(str_subs, content_type='application/x-subrip')\\r\\n response['Content-Disposition'] = 'attachment; filename=\\\"{0}.srt\\\"'.format(subs_id)\\r\\n return response\\r\\n except NotFoundError:\\r\\n log.debug(\\\"Can't find content in storage for %s subs\\\", subs_id)\\r\\n raise Http404\",\n \"def download_extract_zip(url):\\n response = requests.get(url)\\n with ZipFile(BytesIO(response.content)) as thezip:\\n for zipinfo in thezip.infolist():\\n with thezip.open(zipinfo) as thefile:\\n df = pd.read_csv(thefile)\\n return (df)\",\n \"def create_download_response(self):\\n zip_file_io = self._create_zip_file()\\n content_type = 'application/x-zip-compressed'\\n extension = 'zip'\\n file_name = self._get_file_name()\\n resp = HttpResponse(zip_file_io.getvalue(), content_type=content_type)\\n resp['Content-Disposition'] = 'attachment; filename={}.{}'.format(file_name, extension)\\n return resp\",\n \"def downloadDfxpTranscript(self, SubsLink):\\n try:\\n subRequestObject = requests.get(SubsLink)\\n # print(subRequestObject.text)\\n subRequestObject.encoding = 'utf-8'\\n\\n subsFileHandler = open(self.title + \\\".dfxp\\\", \\\"w\\\")\\n print(\\\"Creating ~ '%s.dfxp' ...\\\" % (self.title))\\n subsFileHandler.write(subRequestObject.text)\\n subsFileHandler.close()\\n return 1\\n\\n except:\\n return 0\\n\\n pass\",\n \"def download_archive(self):\\n\\n def time_convert(structure):\\n \\\"\\\"\\\"\\n :param structure: tuple representation of time\\n :return: GitHub archive time\\n \\\"\\\"\\\"\\n \\n \\n join_number_to_zero = lambda number: (\\\"\\\" if number > 9 else \\\"0\\\") + str(number)\\n\\n return \\\"%s-%s-%s-%s\\\" % (\\n structure.tm_year, join_number_to_zero(structure.tm_mon), join_number_to_zero(structure.tm_mday),\\n structure.tm_hour)\\n\\n current_time = self.get_time()\\n self.logger.debug(__name__ + \\\": \\\" + \\\"current time: \\\" + str(gmtime(current_time)))\\n\\n difference = -25200\\n #timezone difference in seconds between GMT and west coast of USA\\n\\n downloading_time = int(timegm(self.config[\\\"last_connection_time\\\"])) + 3600\\n self.logger.debug(__name__ + \\\": \\\" + \\\"downloading time: \\\" + str(gmtime(downloading_time)))\\n\\n if downloading_time > current_time - 7200:\\n self.logger.info(__name__ + \\\": \\\" + \\\"unable to download file (time limiting).\\\")\\n return\\n\\n downloading_time += difference\\n\\n json_file_name = self.download_file(time_convert(gmtime(downloading_time)))\\n\\n self.config[\\\"last_connection_time\\\"] = gmtime(downloading_time - difference)\\n self.logger.debug(__name__ + \\\": \\\" + \\\"last_connection_time: \\\" + str(self.config[\\\"last_connection_time\\\"]))\\n\\n return json_file_name\",\n \"def request_event(topic, url_path, zipcodes):\\n\\n events = []\\n\\n for zp, _, _ in zipcodes:\\n default_args = dict(\\n zip=zp,\\n topic=topic,\\n key=os.environ['MEETUP_API_KEY']\\n )\\n\\n print(default_args)\\n\\n r = requests.get(url_path, params=default_args)\\n results = r.text\\n try:\\n json_data = json.loads(results)\\n events.append(json_data['results'])\\n except Exception as e:\\n logging.exception(f'Error: {e}')\\n\\n return events\",\n \"def fmarket_download():\\r\\n name = request.args[\\\"address\\\"]\\r\\n markets = get_zipcode_markets(name)\\r\\n\\r\\n return Response(markets.to_json(), 200, mimetype=\\\"application/json\\\")\",\n \"def request(self, params: Dict[str, Any]) -> Response:\\n\\n resp: Response = requests.get(self.base_url, params=params, timeout=10)\\n resp.raise_for_status()\\n\\n headers: str = resp.headers[\\\"content-disposition\\\"]\\n\\n if re.search(r\\\"\\\\.xml\\\\.zip;$\\\", headers):\\n raise NoDataAvailableError(\\\"No data available for this query.\\\")\\n\\n return resp\",\n \"def run_script():\\n var=raw_input(\\\"Enter a Zipcode: \\\")\\n address='http://www.uszip.com/zip/'+var\\n conn=urllib.urlopen(address)\\n t=[]\\n for line in conn.fp:\\n\\tline=line.strip()\\n\\tif '<title>' in line:\\n\\t line.split()\\n\\t print line[7:-16]\\n\\tif 'Total population' in line:\\n\\t line=line.strip('z')\\n\\t loc=line.index('Total population')\\n\\t loc2=line.index('<span')\\n\\t print line[(loc+25):loc2]\",\n \"def get_zipinfo(self):\\n zipinfo = zipfile.ZipInfo()\\n zipinfo.filename = self.translated_path()\\n zipinfo.date_time = self.get_mod_time()\\n zipinfo.file_size = self.get_size()\\n return zipinfo\",\n \"def download_data():\\n url = 'https://www.dropbox.com/s/h9ubx22ftdkyvd5/ml-latest-small.zip?dl=1'\\n urllib.request.urlretrieve(url, 'ml-latest-small.zip')\\n zfile = zipfile.ZipFile('ml-latest-small.zip')\\n zfile.extractall()\\n zfile.close()\",\n \"def _download(self, request_dict={}):\\n html = super()._download(request_dict)\\n self.extract_cases_from_subpages(html)\\n return html\",\n \"def download_sample():\\n sample_id = demisto.getArg('id')\\n r = req('GET', SUB_API + 'samples/' + sample_id + '/sample.zip')\\n ec = {'ThreatGrid.DownloadedSamples.Id': sample_id}\\n demisto.results([\\n {\\n 'Type': entryTypes['note'],\\n 'EntryContext': ec,\\n 'HumanReadable': '### ThreatGrid Sample Download - \\\\n'\\n + 'Your download request has been completed successfully for ' + sample_id,\\n 'Contents': ec,\\n 'ContentsFormat': formats['json']\\n },\\n fileResult(sample_id + '-sample.zip', r.content)\\n ])\",\n \"def bike_download():\\r\\n name = request.args[\\\"address\\\"]\\r\\n stations = get_zipcode_stations(name)\\r\\n\\r\\n return Response(stations.to_json(), 200, mimetype=\\\"application/json\\\")\",\n \"def main(file_url, file_path):\\n\\n # extract file from the link\\n\\n if not os.path.exists(file_path):\\n os.makedirs(file_path, exist_ok=True)\\n \\n r = requests.get(str(file_url))\\n\\n #unzip the zip file\\n z = zipfile.ZipFile(io.BytesIO(r.content))\\n z.extractall(path = file_path)\",\n \"def package(request, name):\\n return HttpResponse(get_koji_download_url(name), mimetype='application/json')\",\n \"def package(request, name):\\n return HttpResponse(get_koji_download_url(name), mimetype='application/json')\",\n \"def download_data():\\r\\n print('Downloading cifar-10 data...')\\r\\n request.urlretrieve(dataurl)\\r\\n print('Done')\\r\\n print('Please unzip files. command is:')\\r\\n print('gzip -d cifar-10-python.tar.gz')\\r\\n print('tar -xf cifar-10-python.tar')\\r\\n exit()\",\n \"async def get(name, version, results, progress):\\n\\n buf = BytesIO()\\n\\n client = httpx.AsyncClient()\\n\\n async with client.stream(\\n \\\"GET\\\", f\\\"https://pydocs.github.io/pkg/{name}-{version}.zip\\\"\\n ) as response:\\n total = int(response.headers[\\\"Content-Length\\\"])\\n\\n download_task = progress.add_task(f\\\"Download {name} {version}\\\", total=total)\\n async for chunk in response.aiter_bytes():\\n buf.write(chunk)\\n progress.update(download_task, completed=response.num_bytes_downloaded)\\n\\n if response.status_code != 200:\\n results[(name, version)] = None\\n else:\\n buf.seek(0)\\n results[(name, version)] = buf.read()\",\n \"def ctakeout_download():\\r\\n name = request.args[\\\"address\\\"]\\r\\n takeouts = get_zipcode_takeouts(name)\\r\\n\\r\\n return Response(takeouts.to_json(), 200, mimetype=\\\"application/json\\\")\",\n \"def download(oformat, param, stream, year, month, timestep, back, queue):\\n update = False\\n if back and timestep != 'mon':\\n print('You can the backwards option only with monthly data')\\n sys.exit()\\n if queue:\\n dump_args(update, oformat, stream, list(param), year, list(month), timestep, back)\\n else: \\n api_request(update, oformat, stream, list(param), year, list(month), timestep, back)\",\n \"def GetAndSave(self, url, save_suffix, unzip=False):\\n self.connection.request('GET',\\n '/data/' + url,\\n headers={'content-type': 'text/plain'})\\n response = self.connection.getresponse()\\n file_name = Clean(url) + save_suffix\\n destination = os.path.join(self.path, file_name)\\n\\n if response.status != 200:\\n raise IOError(url)\\n\\n if unzip:\\n s = StringIO.StringIO(response.read())\\n content = gzip.GzipFile(fileobj=s).read()\\n else:\\n content = response.read()\\n\\n with open(destination, 'w') as f:\\n f.write(content)\\n return content\",\n \"def load_zip_folder(req_path, name, ext, zip_path):\\n BASE_DIR = ROOT\\n full_path = \\\"%s/%s.%s\\\" % (req_path, name, ext)\\n full_real_path = get_real_path(BASE_DIR, full_path)\\n try:\\n zip_path = unquote(zip_path).encode('utf-8')\\n except Exception as e:\\n logger.info(\\\"Failed to encode: %s\\\", zip_path)\\n\\n if not os.path.exists(full_real_path):\\n logger.error(\\\"No Path: %s\\\", full_real_path)\\n return ('', 204)\\n\\n if ext not in archive_exts:\\n return ('', 204)\\n\\n #get list of files in folder in zip file\\n data = ComixData(Directories=[], Files=[])\\n with zipfile.ZipFile(full_real_path) as zf:\\n for name in zf.namelist():\\n name = name.decode('euc-kr').encode('utf-8')\\n pardir, basename = os.path.split(name)\\n if basename and zip_path == pardir:\\n logger.info(\\\"get_files_in_zip_path: %s, %s\\\", pardir, basename)\\n data.Files.append(basename)\\n if len(data.Files):\\n response = flask.Response(json.dumps(data._asdict(), ensure_ascii=False), headers=None)\\n return response\\n\\n return ('', 204)\",\n \"def _download_zip(self, zip_url, dest_dir):\\n # TODO(jsirois): Wrap with workunits, progress meters, checksums.\\n self.context.log.info('Downloading {}...'.format(zip_url))\\n sess = requests.session()\\n sess.mount('file://', self.LocalFileAdapter())\\n res = sess.get(zip_url)\\n if not res.status_code == requests.codes.ok:\\n raise TaskError('Failed to download {} ({} error)'.format(zip_url, res.status_code))\\n\\n with open_zip(BytesIO(res.content)) as zfile:\\n safe_mkdir(dest_dir)\\n for info in zfile.infolist():\\n if info.filename.endswith('/'):\\n # Skip directories.\\n continue\\n # Strip zip directory name from files.\\n filename = os.path.relpath(info.filename, get_basedir(info.filename))\\n f = safe_open(os.path.join(dest_dir, filename), 'w')\\n f.write(zfile.read(info))\\n f.close()\",\n \"def get(self, zipcode):\\n response = hereService.getWeatherByZipcode(zipcode)\\n return response\",\n \"def fetch(data_dir):\\n file_path = os.path.join(data_dir, DESTINATION, ZIP_NAME)\\n result_path = os.path.join(data_dir, DESTINATION, NAME)\\n return utils.fetch(URL, file_path, result_path)\",\n \"def download(self):\\r\\n \\r\\n # RAR Files names\\r\\n if self.debug==0:\\r\\n rar_files_name = [\\\"K001.rar\\\",\\\"K002.rar\\\",\\\"K003.rar\\\",\\\"K004.rar\\\",\\\"K005.rar\\\",\\\"K006.rar\\\",\\r\\n \\\"KA01.rar\\\", \\\"KA03.rar\\\", \\\"KA04.rar\\\", \\\"KA05.rar\\\", \\\"KA06.rar\\\", \\\"KA07.rar\\\", \\r\\n \\\"KA08.rar\\\", \\\"KA09.rar\\\", \\\"KA15.rar\\\", \\\"KA16.rar\\\", \\\"KA22.rar\\\", \\\"KA30.rar\\\", \\r\\n \\\"KB23.rar\\\", \\\"KB24.rar\\\", \\\"KB27.rar\\\", \\r\\n \\\"KI01.rar\\\", \\\"KI03.rar\\\", \\\"KI04.rar\\\", \\\"KI05.rar\\\", \\\"KI07.rar\\\", \\\"KI08.rar\\\", \\r\\n \\\"KI14.rar\\\", \\\"KI16.rar\\\", \\\"KI17.rar\\\", \\\"KI18.rar\\\", \\\"KI21.rar\\\"]\\r\\n else:\\r\\n rar_files_name = [\\\"K002.rar\\\", \\\"KA01.rar\\\", \\\"KI01.rar\\\"]\\r\\n\\r\\n url = self.url\\r\\n \\r\\n dirname = self.rawfilesdir\\r\\n dir_rar = \\\"rar_files\\\"\\r\\n if not os.path.isdir(dirname):\\r\\n os.mkdir(dirname)\\r\\n if not os.path.isdir(os.path.join(dirname, dir_rar)):\\r\\n os.mkdir(os.path.join(dirname, dir_rar))\\r\\n \\r\\n\\r\\n print(\\\"Downloading RAR files:\\\")\\r\\n for i in rar_files_name:\\r\\n file_name = i\\r\\n if not os.path.exists(os.path.join(dirname, dir_rar, file_name)):\\r\\n urllib.request.urlretrieve(url+file_name, os.path.join(dirname, dir_rar, file_name))\\r\\n print(file_name)\\r\\n \\r\\n print(\\\"Extracting files:\\\")\\r\\n for i in rar_files_name:\\r\\n if not os.path.exists(os.path.join(dirname, i[:4])):\\r\\n file_name = os.path.join(dirname, dir_rar, i)\\r\\n Archive(file_name).extractall(dirname) \\r\\n print(i)\\r\\n\\r\\n if self.debug==0:\\r\\n files_path = self.files\\r\\n else:\\r\\n files_path = files_debug(self.rawfilesdir)\\r\\n\\r\\n print(files_path)\\r\\n self.files = files_path\",\n \"def unzip() -> None:\\n logger = logging.getLogger(__name__)\\n logger.info('Download the dataset')\\n\\n # define the destination\\n destination = project_dir / 'data' / 'raw'\\n\\n # extract zip\\n zip_file = ZipFile(destination / \\\"original.zip\\\")\\n zip_file.extractall(destination)\",\n \"def get_text(self, url, *, timeout, headers):\",\n \"def download(self):\\n debug(str(self) + ' Downloading from newzbin.com..')\\n if not NewzbinDownloader.canDownload():\\n debug(str(self) + ' download: No www.newzbin.com login information')\\n return\\n\\n info('Downloading newzbin NZB: %s ' % self.msgId)\\n self.handleNZBDownloadFromNewzbin()\",\n \"def fetch_zenodo(self):\\n\\n # retrieve content from URL\\n try:\\n logging.info(f\\\"Downloading example data from {self.url}\\\")\\n r = requests.get(self.url, stream=True)\\n with io.BytesIO() as stream:\\n with tqdm.wrapattr(\\n stream,\\n 'write',\\n file=sys.stdout,\\n miniters=1,\\n desc=self.url,\\n total=int(r.headers.get('content-length', 0))\\n ) as file:\\n for chunk in r.iter_content(chunk_size=4096):\\n file.write(chunk)\\n with zipfile.ZipFile(stream) as zipped:\\n # extract each file in the zipped dir to the project\\n for f in zipped.namelist():\\n logging.info(\\\"Unzipped: {}\\\".format(os.path.join(self.destination, f)))\\n zipped.extract(f, self.destination)\\n\\n logging.info(\\\"Download and install complete.\\\")\\n\\n self.close_logger()\\n\\n except requests.exceptions.MissingSchema:\\n msg = f\\\"Unable to download data from {self.url}\\\"\\n logging.exception(msg)\\n self.close_logger()\\n raise\",\n \"def get_my_zip_code(\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = GetMyZipCode.create(\\n namespace=namespace,\\n )\\n return run_request(request, additional_headers=x_additional_headers, **kwargs)\",\n \"def download_subtitle(search, results, filename, min_match=0,\\n force=0, debug=0):\\n s = Subseek()\\n subtitleurl = False\\n for result in s.order_match(search, results):\\n match_text = s.clean_text(s.clean_html(result['text']),False,\\n s.detect_encoding(s.clean_html(result['text']))\\n ) + \\\" \\\" + s.clean_text(s.clean_html(result['description']),False,\\n s.detect_encoding(s.clean_html(result['description'])))\\n subtitleurl = result['link']\\n rating_weight = s.text_weight(search, match_text)\\n max_weight = s.text_weight(search)\\n rating_match = rating_weight/max_weight*100\\n if debug == 1:\\n print \\\"Subtitle File URL: \\\" + subtitleurl\\n print \\\" Text To Search: \\\" + search\\n print \\\" Text To Match: \\\" + match_text\\n print \\\" Text Match (%): \\\" + str(round(rating_match,2)) + \\\"%\\\"\\n # check minimal match to use\\n if rating_match >= min_match:\\n downloaded = s.download(subtitleurl, filename + '.tmp')\\n if downloaded == False:\\n if debug == 1:\\n print \\\"Error: connection or file creation failed\\\"\\n subtitleurl = False\\n else:\\n if debug == 1:\\n print \\\"File downloaded\\\"\\n # unrar, unzip or get srt file\\n typefile = s.get_sub_file_from_file(filename + '.tmp',\\n search, force)\\n if typefile == False:\\n if debug == 1:\\n print \\\"Subtitle file not found\\\"\\n subtitleurl = False\\n else:\\n if debug == 1:\\n print \\\"Subtitle file found in \\\" + typefile\\n subtitleurl = True\\n break\\n else:\\n if debug == 1:\\n print \\\"Error: match less than \\\" + str(round(min_match,2))+ \\\"%\\\"\\n subtitleurl = False\\n break\\n\\n return subtitleurl\",\n \"def fetch(self, url) -> bytes:\\n buffer = self.download(url)\\n zfs = ZipFileSystem(buffer, \\\"r\\\")\\n return zfs.open(zfs.glob(\\\"*\\\")[0]).read()\",\n \"def download_text_command():\\n # 1. Get input scan id from Demisto\\n scanid = demisto.args().get('scanid')\\n # 2. Get the forensic webpage text from SlashNext API\\n response = download_text(scanid=scanid)\\n if response.get('errorNo') != 0:\\n return\\n # 3. Parse and format the response\\n text_base64 = response.get('textData').get('textBase64')\\n text_data = base64.b64decode(text_base64)\\n\\n text_file = fileResult('slashnext_{}.txt'.format(scanid), text_data, entryTypes['file'])\\n\\n demisto.results({\\n 'Type': entryTypes['file'],\\n 'ContentsFormat': formats['text'],\\n 'Contents': 'Forensics: Webpage Rendered Text for URL Scan ID = {}'.format(scanid),\\n 'File': text_file.get('File'),\\n 'FileID': text_file.get('FileID')\\n })\",\n \"def download_test_files(request):\\n\\n # Log the start of the function\\n logger.info(\\\"=========== returns ms1 test files from code directory input/ms1\\\")\\n\\n # create an absolute path to the 'example_data_dir' containing the test data files, then create\\n # absolute paths to each test data file. Note the test data files are located in this code base.\\n example_data_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)),'..','..','input/ms1')\\n pos_input = os.path.join(example_data_dir, example_pos_filename)\\n neg_input = os.path.join(example_data_dir, example_neg_filename)\\n tracer_file = os.path.join(example_data_dir, example_tracer_filename)\\n run_sequence_pos_file = os.path.join(example_data_dir, example_run_sequence_pos_filename)\\n run_sequence_neg_file = os.path.join(example_data_dir, example_run_sequence_neg_filename)\\n\\n # create filenames\\n filename1 = 'ms1_pos_input_test_data.csv'\\n filename2 = 'ms1_neg_input_test_data.csv'\\n filename3 = 'ms1_tracer_test_data.csv'\\n filename4 = 'ms1_run_sequence_pos_test_data.csv'\\n filename5 = 'ms1_run_sequence_neg_test_data.csv'\\n\\n # List of files to be zipped\\n files_to_zip = {filename1: pos_input, filename2: neg_input, filename3: tracer_file, filename4: run_sequence_pos_file, filename5: run_sequence_neg_file}\\n\\n # Create an in-memory zip file\\n in_memory_zip = BytesIO()\\n with ZipFile(in_memory_zip, 'w', ZIP_DEFLATED) as zipf:\\n # Add each file to the zipfile\\n for filename in files_to_zip:\\n logger.info('filename: {}'.format(filename))\\n file_path = files_to_zip[filename]\\n with open(file_path, 'rb') as file:\\n file_content = file.read()\\n zipf.writestr(filename, file_content)\\n # The ZipFile object is automatically closed when exiting the 'with' block\\n\\n zip_filename = \\\"ms1_test_data_files.zip\\\"\\n # Create an HTTP response with the zip file attached for download\\n response = HttpResponse(in_memory_zip.getvalue(),content_type='application/zip')\\n response['Content-Disposition'] = 'attachment; filename=' + zip_filename\\n response['Content-length'] = in_memory_zip.tell()\\n\\n # Return the HTTP response\\n return response\",\n \"def _GetDownloadUrl(self):\\n\\n # Using access_token to get the transcript for the meeting that's mapped to meeting_id\\n get_meeting_headers = {\\n 'authorization': \\\"Bearer {access_token}\\\".format(access_token=self.access_token),\\n 'content-type': \\\"application/json\\\"\\n }\\n try:\\n request_endpoint = \\\"/v2/users/me/recordings?from=2000-01-01\\\"\\n self.conn.request(\\\"GET\\\", request_endpoint, headers=get_meeting_headers)\\n res = self.conn.getresponse()\\n data = res.read().decode(\\\"utf-8\\\")\\n response = json.loads(data)\\n except:\\n print(\\\"Bad Response to access recordings.\\\")\\n print(data)\\n \\n # Download the transcript if it exists\\n download_url = None\\n print(88888888888888888)\\n print(response)\\n for meeting in response[\\\"meetings\\\"]:\\n if \\\"recording_files\\\" not in meeting or meeting[\\\"id\\\"] != self.meeting_id:\\n continue\\n for recording_file in meeting[\\\"recording_files\\\"]:\\n if \\\"recording_type\\\" not in recording_file:\\n continue\\n if recording_file[\\\"file_type\\\"] == \\\"TRANSCRIPT\\\": \\n download_url = \\\"{endpoint}?access_token={access_token}\\\".format(endpoint=str(recording_file[\\\"download_url\\\"]), access_token=self.access_token)\\n return download_url\",\n \"def prepare_zip(self, filename, *args, **kwargs):\\n\\n return '/vsizip/' + filename, args, kwargs\",\n \"def download(data_type, gs_aoi, main_dir):\\n # Get URLs for tiles covered by a polygon:\\n # ----------------------------------------\\n tiles = get_tile_names(gs_aoi)\\n print('Found {} products'.format(len(tiles['tile_names'])))\\n\\n # Make sure temporary folder for download exists:\\n # -----------------------------------------------\\n dwn_dir = join(main_dir, data_type)\\n if not exists(dwn_dir):\\n makedirs(dwn_dir)\\n\\n # Proceed to download:\\n # --------------------\\n if data_type == 'DTM':\\n # DOWNLOAD DTM FILES & UNZIP:\\n # ---------------------------\\n print('\\\\nDownloading DTM files:')\\n for num, name in enumerate(tiles['dtm_url']):\\n print('{} of {}'.format(num+1, len(tiles['dtm_url'])))\\n dwn_stat, file_name = download_file(name, dwn_dir)\\n print('File {}.'.format(dwn_stat))\\n extract_zip(join(dwn_dir, file_name))\\n # Delete ZIP file after extraction\\n remove(join(dwn_dir, file_name))\\n \\n # Finished downloading:\\n # ---------------------\\n out_msg = 'Finished downloading DTM files!'\\n \\n elif data_type == 'LAZ':\\n # DOWNLOAD LAZ FILES:\\n # -------------------\\n print('\\\\nDownloading LAZ files:')\\n for num, name in enumerate(tiles['laz_url']):\\n print('{} of {}'.format(num+1, len(tiles['laz_url'])))\\n dwn_stat, _ = download_file(name, dwn_dir)\\n print('File {}.'.format(dwn_stat))\\n \\n # Finished downloading:\\n # ---------------------\\n out_msg = 'Finished downloading LAZ files!'\\n \\n else:\\n dwn_dir = None\\n out_msg = 'Unexpected data_type'\\n \\n # Output dictionary:\\n # ------------------\\n out = {'out_msg': out_msg,\\n 'out_dir': dwn_dir}\\n \\n return out\",\n \"def download_data(self):\\n headers = {'User-Agent': 'Mozilla/5.0',}\\n\\n #Request for html data of url page\\n r = requests.get(self.url, headers = headers, allow_redirects=True)\\n soup = BeautifulSoup(r.text, \\\"html.parser\\\")\\n\\n #Checking if folder path exists, if not, creats it\\n i=0\\n while i<len(self.folder)-1:\\n if self.folder[i] == '/':\\n if not os.path.isdir(self.folder[:i]):\\n os.mkdir(self.folder[:i])\\n i+=1\\n if i==len(self.folder)-1:\\n if not os.path.isdir(self.folder):\\n os.mkdir(self.folder)\\n\\n # if not os.path.isdir(self.folder):\\n # os.mkdir(self.folder)\\n\\n #Gets every href to zip file with data\\n entries = []\\n for link in soup.find_all('a'):\\n if re.search(\\\"^data/.*.zip\\\", link.get('href')):\\n entries.append(link.get('href'))\\n\\n #Gets the newest dataset\\n self.getCurrentData(entries)\\n\\n i=0\\n #Saves each file in dataset\\n for list in self.ListOfZipFiles:\\n if not os.path.isfile(self.folder+list[4:]):\\n r = requests.get(self.url+list)\\n open(self.folder+list[4:], 'wb').write(r.content)\\n #deletes prefix \\\"data/\\\"\\n self.ListOfZipFiles[i] = list[4:]\\n i+=1\",\n \"def download(self, method, url, downloader, *args, **kwargs):\\n if method.startswith('URL'):\\n return downloader.enqueue_file(url, filename=partial(self.mk_filename, *args))\\n\\n raise NoData\",\n \"def download(self, filename = None, format = 'srt', append = False):\\n \\n data = self.download_data(format)\\n \\n if filename != None:\\n extension = '' if filename.lower().endswith('.srt') else '.srt'\\n \\n sys.stdout.write('Saving subtitle...\\\\n')\\n \\n out_dir = self.config.subtitles['out']\\n if os.path.isfile(out_dir):\\n raise OSError('Video output directory is not a directory, but is a file')\\n elif not os.path.isdir(out_dir):\\n os.mkdir(out_dir)\\n \\n mod = 'a' if append else 'w'\\n f = open(out_dir + os.path.sep + filename + extension, mod)\\n f.write(data)\\n f.close()\\n \\n return data\",\n \"def download():\\n raise NotImplementedError\",\n \"async def get_my_zip_code_async(\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = GetMyZipCode.create(\\n namespace=namespace,\\n )\\n return await run_request_async(\\n request, additional_headers=x_additional_headers, **kwargs\\n )\",\n \"def download(self, *args, **kwargs):\\n return wb.download(*args, **kwargs)\",\n \"def download_and_unzip(url, zip_path, csv_path, data_folder):\\n\\n download_from_url(url, zip_path)\\n\\n unzip(zip_path, csv_path, data_folder)\\n\\n print('Done.')\",\n \"def _download_from_url(self) -> bytes:\\n response = requests.get(self.url, allow_redirects=True)\\n return response.content\",\n \"def _download(self):\\n self._system.download_file(\\\"http://curl.haxx.se/download/\\\" + self._tar_name)\",\n \"def _download_project(name, apikey):\\n payload = {'apikey': apikey, 'project': name, 'version': 'portia'}\\n r = requests.get(DASH_API_URL + 'as/project-slybot.zip', params=payload)\\n return r.content\",\n \"def __connect_with_server(self,get_operatoin,server_reuest_type):\\n\\twhat_is_downloaded = server_reuest_type\\n\\tself.XML_String = None\\n\\tself.zip_string = None\\n\\ttry:\\n\\t conn = httplib.HTTPConnection(self.NAPISY24_url)\\n\\t conn.request(\\\"GET\\\", get_operatoin)\\n\\t r1 = conn.getresponse()\\n\\t print r1.status, r1.reason\\n\\t if what_is_downloaded == \\\"downloada_subtitle_list_by_film_name\\\" or what_is_downloaded == \\\"downloada_subtitle_list_by_IMDB\\\":\\n\\t\\tself.XML_String = r1.read()\\n\\t elif what_is_downloaded == \\\"download_subtilte_zip\\\":\\t\\t\\n\\t\\tself.zip_string = r1.read()\\n\\t return r1.status#, r1.reason\\n\\texcept (IOError, OSError), e:\\n\\t print >> sys.stderr, \\\"Napisy24.pl server connection error.\\\"\\n\\t time.sleep(0.5)\",\n \"def testZipUrl(self):\\n try:\\n remoteLocator = self.__zipFileUrl\\n # fn = self.__fileU.getFileName(remoteLocator)\\n ok = self.__fileU.isLocal(remoteLocator)\\n self.assertFalse(ok)\\n #\\n lPath = os.path.join(self.__workPath, self.__fileU.getFileName(self.__zipFileUrl))\\n ok = self.__fileU.get(remoteLocator, lPath)\\n self.assertTrue(ok)\\n ok = self.__fileU.exists(lPath)\\n self.assertTrue(ok)\\n ok = self.__fileU.isLocal(lPath)\\n self.assertTrue(ok)\\n tPath = self.__fileU.getFilePath(lPath)\\n self.assertEqual(lPath, tPath)\\n fp = self.__fileU.uncompress(lPath, outputDir=self.__workPath)\\n ok = fp.endswith(\\\"Food_Display_Table.xlsx\\\")\\n self.assertTrue(ok)\\n\\n except Exception as e:\\n logger.exception(\\\"Failing with %s\\\", str(e))\\n self.fail()\",\n \"def office_download_data(parser, args, params):\\n parser.add_argument(\\n '--station_list', type=str, help='Station file from IRIS',\\n required=True, metavar='x')\\n parser.add_argument(\\n '--recording_time', type=int, \\n help='Recording time from event start (seconds)', metavar='x',\\n required=True)\\n parser.add_argument(\\n '--padding_time', type=int,\\n help='Padding time', metavar='x',\\n required=True)\\n parser.add_argument(\\n '--with_waveforms', action='store_true',\\n help='Download waveform data (instead of just station data)')\\n \\n local_args = parser.parse_known_args(args)\\n \\n station_list = local_args[0].station_list\\n with_waveforms = local_args[0].with_waveforms\\n padding_time = local_args[0].padding_time\\n recording_time = local_args[0].recording_time\\n control.download_data(params, station_list, with_waveforms, recording_time,\\n padding_time)\",\n \"def certificates(request, course_id):\\n\\n course_event = get_object_or_404(CourseEvent, pk=course_id)\\n outzip = get_certificates_zip(course_id)\\n with open(outzip, 'rb') as myzip:\\n response = HttpResponse(myzip.read())\\n response['Content-Disposition'] = 'attachment; filename=certifikaty-{}-{}.zip'.format(\\n course_event.date.strftime(\\\"%Y-%m-%d\\\"),\\n course_event.course_type.title\\n )\\n response['Content-Type'] = 'application/x-zip'\\n return response\",\n \"def unzip_data():\\n zip_ref = zipfile.ZipFile(data_zip, 'r')\\n zip_ref.extractall('')\\n zip_ref.close()\",\n \"def DownloadFilesFromAPI(self, task_data: Dict[str, List[str]],\\n path: str) -> Optional[str]:\\n result = None\\n self.RefreshClientCredentials()\\n api_instance = turbinia_request_results_api.TurbiniaRequestResultsApi(\\n self.client)\\n try:\\n task_id = task_data.get('id')\\n api_response = api_instance.get_task_output(\\n task_id, _preload_content=False)\\n filename = f'{task_id}-'\\n\\n # Create a temporary file to write the response to.\\n file = tempfile.NamedTemporaryFile(\\n mode='wb', prefix=f'{filename}', suffix='.tgz', delete=False)\\n local_path = file.name\\n self.logger.info(f'Downloading output for task {task_id} to {local_path}')\\n # Read the response and write to the file.\\n for chunk in api_response.read_chunked():\\n file.write(chunk)\\n file.close()\\n\\n # Extract the files from the tgz file.\\n extracted_path = self._ExtractFiles(local_path, path)\\n if os.path.exists(extracted_path):\\n result = extracted_path\\n self.PublishMessage(\\n f'Extracted output file to {result} for task {task_id}')\\n except turbinia_api_lib.ApiException as exception:\\n self.ModuleError(\\n f'Unable to download task data: {exception}', critical=False)\\n except OSError as exception:\\n self.ModuleError(f'Unable to write to file: {exception}', critical=False)\\n\\n return result\",\n \"def get_workspace_zip(self):\\n workspace_api = '/ws/'\\n # print(\\\"Checking Workspaces For: {}\\\".format(self.url))\\n workspace_elements = self._grab_tags(self.url + workspace_api)\\n workspace_links = []\\n root_domain = urllib.parse.urlparse(self.url).scheme + '://' + urllib.parse.urlparse(self.url).netloc\\n for link in workspace_elements.find_all(name='a', href=True):\\n if '/execution/node/' in link['href']:\\n workspace_links.append(link['href'])\\n if len(workspace_links) > 0:\\n for workspace_link in workspace_links:\\n single_workspace_elements = self._grab_tags(root_domain + workspace_link)\\n for link in single_workspace_elements.find_all(name='a', href=True):\\n if '/*zip*/' in link['href']:\\n # URL returned as relative link, must reconstruct\\n print(\\\"FOUND ZIP: {}\\\".format(root_domain + workspace_link + link['href']))\\n return root_domain + workspace_link + link['href']\",\n \"def download(request, snippet_id):\\n snippet = get_object_or_404(Snippet, pk=snippet_id)\\n response = HttpResponse(snippet.code, mimetype='text/plain')\\n response['Content-Disposition'] = 'attachment; filename=%s.%s' % (snippet.id,\\n snippet.language.file_extension)\\n response['Content-Type'] = snippet.language.mime_type\\n return response\",\n \"def zip_open_text(zip, filename):\\n if isinstance(zip, FakeZip):\\n return zip.open(filename)\\n else:\\n # Wrap the zip file to decode.\\n return io.TextIOWrapper(zip.open(filename, 'r'), encoding='utf8')\",\n \"def download():\\n toydata = requests.get(DATA_URL).json()\\n return toydata\",\n \"def download_one_zip(data_url, data_dir):\\r\\n\\r\\n zipfile_path, unzip_dir = zip_file_name_from_url(data_url, data_dir)\\r\\n if not is_there_file(zipfile_path, unzip_dir):\\r\\n if not os.path.isdir(unzip_dir):\\r\\n os.makedirs(unzip_dir)\\r\\n r = requests.get(data_url, stream=True)\\r\\n with open(zipfile_path, \\\"wb\\\") as py_file:\\r\\n for chunk in r.iter_content(chunk_size=1024): # 1024 bytes\\r\\n if chunk:\\r\\n py_file.write(chunk)\\r\\n unzip_nested_zip(zipfile_path, unzip_dir), download_small_file\",\n \"def transmit(self, location, args):\\r\\n args = dict(args)\\r\\n args['utf8'] = '\\\\u2713'\\r\\n\\r\\n data = json.dumps(args)\\r\\n\\r\\n\\r\\n req = urlrequest.Request(self.host + location, data, self.headers)\\r\\n\\r\\n if self.timeout:\\r\\n response = urlrequest.urlopen(req, None, self.timeout)\\r\\n else:\\r\\n response = urlrequest.urlopen(req)\\r\\n\\r\\n code = response.code\\r\\n data = response.fp.read()\\r\\n\\r\\n log.info(\\\"Response status: %s\\\\nResponse data: \\\\n%s\\\\n\\\" % (code, data))\",\n \"def download():\\n base_loc = DATA_DIR + '/raw/human_activity'\\n loc = base_loc + '/human_activity.zip'\\n if os.path.exists(loc):\\n print('Path already exists at {}. If you wish to re-download you must delete this folder.'.format(loc))\\n return\\n if not os.path.exists(base_loc):\\n os.mkdir(base_loc)\\n\\n url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/00341/HAPT%20Data%20Set.zip'\\n urllib.request.urlretrieve(url, loc)\\n\\n with zipfile.ZipFile(loc, 'r') as zip_ref:\\n zip_ref.extractall(base_loc)\",\n \"def fromZip(self, zip_location,extract_location):\\n zip_file = zipfile.ZipFile(zip_location,'r')\\n zip_file.extractall(extract_location)\",\n \"def dowload_vt():\\n print get_date_time_now() + \\\" ==> Download VT Samples started!\\\"\\n print get_date_time_now() + \\\" ==> Nothing downloaded\\\"\",\n \"def generate(self, text):\\n self.__params['text']=text\\n self._data = requests.get(self.TTS_URL, params=self.__params,\\n stream=False).iter_content()\",\n \"def download_text(scanid):\\n # Create the required data dictionary for Download/Text\\n api_data = {\\n 'scanid': scanid\\n }\\n response = http_request(endpoint=DL_TEXT_API, data=api_data)\\n\\n if response.get('errorNo') == 1:\\n demisto.results(\\n 'Your Url Scan request is submitted to the cloud and may take up-to 60 seconds to complete.\\\\n'\\n 'Please check back later using \\\"slashnext-download-text\\\" command with Scan ID = {}'.format(scanid))\\n elif response.get('errorNo') != 0:\\n return_error('API Returned, {}:{}'.format(response.get('errorNo'), response.get('errorMsg')))\\n\\n return response\",\n \"def download (httpfile, path_unzip = None, outfile = None) :\\n if path_unzip is None : path_unzip = GetPath ()\\n file = _check_source (httpfile, path_unzip = path_unzip, outfile = outfile)\\n return file\",\n \"def getROZip(self, rouri):\\n (status, reason, headers, uri, data) = self.doRequestFollowRedirect(rouri,\\n method=\\\"GET\\\", accept=\\\"application/zip\\\")\\n if status in [200, 404]:\\n return (status, reason, headers, URIRef(uri), data)\\n raise self.error(\\\"Error retrieving RO as ZIP file\\\",\\n \\\"%03d %s\\\"%(status, reason))\",\n \"def search_and_download_raw(self, search_term):\\n \\n # delete old file if it exists\\n if path.exists(self.SEARCH_RESULTS_ZIP_FILE_NAME):\\n os.remove(self.SEARCH_RESULTS_ZIP_FILE_NAME)\\n \\n # perform search and download zip archive of all matching studies\\n self.browser.get(self.CLINICAL_TRIALS_BASE_URL + urlencode({\\\"term\\\": search_term}))\\n\\n try:\\n self.browser.find_element_by_id('downloadAdvancedForm').submit()\\n \\n # wait for the zip archive to download; for some reason there has to be a delay, else the zip file will not finish\\n # downloading correctly...\\n while (not path.exists(self.SEARCH_RESULTS_ZIP_FILE_NAME)) or (not zipfile.is_zipfile(self.SEARCH_RESULTS_ZIP_FILE_NAME)):\\n sleep(.1)\\n\\n os.rename(self.SEARCH_RESULTS_ZIP_FILE_NAME, \\\"clinical_trials_gov_results_%s.zip\\\" % search_term)\\n\\n return \\\"clinical_trials_gov_results_%s.zip\\\" % search_term\\n except NoSuchElementException as e:\\n print(e)\\n return None\",\n \"def tile(self, z, x, y_tms):\\n logger.debug(_(\\\"Download tile %s\\\") % ((z, x, y_tms),))\\n # Render each keyword in URL ({s}, {x}, {y}, {z}, {size} ... )\\n size = self.tilesize\\n s = self.tiles_subdomains[(x + y_tms) % len(self.tiles_subdomains)];\\n y_osm = (2**int(z) - 1) - int(y_tms)\\n try:\\n url = self.tiles_url.format(**locals())\\n except KeyError, e:\\n raise DownloadError(_(\\\"Unknown keyword %s in URL\\\") % e)\\n logger.debug(_(\\\"Retrieve tile at %s\\\") % url)\\n r = DOWNLOAD_RETRIES\\n sleeptime = 1\\n while r > 0:\\n try:\\n request = urllib2.Request(url)\\n for header, value in self.headers.items():\\n request.add_header(header, value)\\n stream = urllib2.urlopen(request)\\n assert stream.getcode() == 200\\n return stream.read()\\n except (AssertionError, IOError), e:\\n logger.debug(_(\\\"Download error, retry (%s left). (%s)\\\") % (r, e))\\n r -= 1\\n time.sleep(sleeptime)\\n # progressivly sleep longer to wait for this tile\\n if (sleeptime <= 10) and (r % 2 == 0):\\n sleeptime += 1 # increase wait\\n raise DownloadError(_(\\\"Cannot download URL %s\\\") % url)\",\n \"def cli(date, path, mission):\\n download.main(path, mission, date)\",\n \"def getzip_requests(url, zipfile, unzipdir):\\n with closing(requests.get(url, stream=True)) as r:\\n if r.headers.get('content-type') == None or r.headers.get('content-type') != 'application/zip':\\n warning = \\\"{} doesn't seem to be a zip file. Unzipping may fail.\\\".format(url)\\n warn(warning)\\n with open(zipfile, 'wb') as fd:\\n for chunk in r.iter_content():\\n fd.write(chunk)\\n with ZipFile(zipfile, 'r') as zip:\\n zip.extractall(unzipdir)\\n os.remove(zipfile)\",\n \"def GET(self, subresource: str = \\\"\\\", **kwargs: str) -> bytes:\\n\\n q = kwargs.get(\\\"q\\\", \\\"\\\")\\n wayback = kwargs.get(\\\"wayback\\\", \\\"\\\")\\n offset = int(kwargs.get(\\\"offset\\\", 0))\\n max_days = int(kwargs.get(\\\"max_days\\\", 180))\\n per_page = int(kwargs.get(\\\"per_page\\\", 20))\\n order = kwargs.get(\\\"order\\\", \\\"rank\\\")\\n\\n if q:\\n return self.search(q, per_page, offset, order)\\n\\n if wayback:\\n return self.check_wayback_availability(wayback)\\n\\n if subresource == \\\"taglist\\\":\\n return self.taglist()\\n\\n return self.index(per_page, offset, order, max_days)\",\n \"def play_video(path):\\r\\n #logger.info(\\\"######: {}, log: {}########\\\".format('rk8', path))\\r\\n #original=https://api.hotstar.com/h/v1/play?contentId=1000238814\\r\\n #path=\\\"https://api.hotstar.com/h/v2/play/in/contents/1000238814\\\"\\r\\n # Create a playable item with a path to play.\\r\\n data = make_request(path)\\r\\n #logger.info(\\\"######: {}, log: {}########\\\".format('rk3', path))\\r\\n if not data:\\r\\n return\\r\\n\\r\\n def get_subtitle(url):\\r\\n #\\r\\n # https://hses.akamaized.net/videos/hotstarint/hostages/1260003409/1558430241469/\\r\\n # 265b9dab22d4e9a033e6df6f89639f17/master.m3u8?hdnea=st=1560107863~exp=1560111463~acl=\\r\\n # /*~hmac=2f6fb393159ed5fa1b12bbf12e954eb377cfa0fc852d4ff5eb24446233237620\\r\\n #\\r\\n # https://hses.akamaized.net/videos/hotstarint/hostages/1260003409/1558430241469/\\r\\n # 5d0f83c3ccbf4501cf952bdfc8c0d785/subtitle/lang_en/sub-0.vtt\\r\\n #\\r\\n _url = urlparse(url)\\r\\n values = _url._asdict()\\r\\n values['query'] = ''\\r\\n values['path'] = '{}/subtitle/lang_en/sub-0.vtt'.format(\\\"/\\\".join(values['path'].split('/')[:-1]))\\r\\n\\r\\n subtitle_url = ParseResult(**values).geturl()\\r\\n # subtitle_file = kodiutils.download_url_content_to_temp(subtitle_url, '{}-{}.srt'.format(\\r\\n # Zee5Plugin.safe_string(item['title']),\\r\\n # subtitle_lang,\\r\\n # ))\\r\\n\\r\\n return subtitle_url\\r\\n\\r\\n #logger.info(\\\"######: {}, log: {}########\\\".format('rk6', data))\\r\\n #item = data['body']['results']['item']\\r\\n item=data['body']['results']['playBackSets'][0]\\r\\n path = item['playbackUrl']\\r\\n licenseURL = item.get('licenseUrl')\\r\\n subtitle = get_subtitle(path)\\r\\n\\r\\n logger.info('Playing video URL: {}, licenseURL: {}, subtitle: {}'.format(path, licenseURL, subtitle))\\r\\n\\r\\n play_item = xbmcgui.ListItem(path=path)\\r\\n if licenseURL:\\r\\n play_item.setProperty('inputstreamaddon', 'inputstream.adaptive')\\r\\n play_item.setProperty('inputstream.adaptive.manifest_type', 'hls')\\r\\n play_item.setMimeType('application/dash+xml')\\r\\n play_item.setContentLookup(False)\\r\\n\\r\\n play_item.setSubtitles([get_subtitle(path)])\\r\\n\\r\\n # Pass the item to the Kodi player.\\r\\n xbmcplugin.setResolvedUrl(_handle, True, listitem=play_item)\",\n \"def get_subtitleinfo(fileFullName):\\n sys.stdout.write(\\\"Requesting subtitle info...\\\\n\\\")\\n\\n #接口获取字幕信息\\n response = requests.post(\\n \\\"https://www.shooter.cn/api/subapi.php\\\",\\n verify=False,\\n params= {\\n 'filehash': ComputeFileHash(fileFullName),\\n 'pathinfo': os.path.realpath(fileFullName),\\n 'format': 'json',\\n 'lang': \\\"Chn\\\",\\n },\\n )\\n #未找到字幕处理\\n if response.text == u'\\\\xff':\\n sys.stderr.write(\\\"Subtitle not found.\\\\n\\\")\\n sys.exit(1)\\n return response\",\n \"def zipname(self):\\n _, tail = os.path.split(self.url)\\n return self.folder + '/' + tail\",\n \"def _download(self):\\n self._system.download(\\\"http://geant4.web.cern.ch/geant4/support/source/\\\" + self._tar_name)\",\n \"def download_flight_data():\\n response = requests.get(FlightAndRoutConst.URL_FLIGHTS_OF_SPRING_AIRLINE,\\n headers={'Content-type': 'text/html; charset=utf-8'})\\n output_path = build_file_name()\\n # Using response.text instead of response.content for chinese string display\\n IOUtils.write_to_file(str(response.text), output_path)\\n return output_path\",\n \"def download():\\n try:\\n cli.run(\\n [URL, '--output', TEMP_DIR],\\n )\\n except SystemExit:\\n return None\",\n \"def downloadObject(self, obj, workingDir=None):\\n\\n fp = Path(obj.name).with_suffix('.zip')\\n if workingDir:\\n fp = Path(workingDir, fp)\\n\\n return self._download(self.fullUrl(obj.downloadUrl), fp.name)\",\n \"def download_and_unzip_data(url, destination, prefix='state-'):\\n # make sure destination exists or create a temporary directory\\n if not destination:\\n destination = tempfile.mkdtemp(prefix=prefix)\\n logger.debug(\\\"Created temp directory {}\\\".format(destination))\\n else:\\n if not os.path.exists(destination):\\n os.makedirs(destination)\\n logger.info(\\\"Created {}\\\".format(destination))\\n zip_filename = get_zipfile_path(url, destination)\\n # don't re-download data if raw data file already exists\\n if os.path.exists(zip_filename):\\n logger.debug(\\\"{} exists, skipping download\\\".format(zip_filename))\\n else:\\n logger.debug(\\\"Downloading data to {}\\\".format(zip_filename))\\n response = requests.get(url, stream=True)\\n # XXX check status code here; e.g., if permissions haven't been granted\\n # for a file being downloaded from S3 a 403 will be returned\\n content_length = int(response.headers.get('content-length'))\\n start = time.clock()\\n downloaded = 0\\n with open(zip_filename, 'wb') as f:\\n for chunk in response.iter_content(chunk_size=1024):\\n if chunk:\\n downloaded += len(chunk)\\n now = time.clock()\\n if (now - start) >= 5:\\n logger.debug('{0:.2g}% downloaded'.format(downloaded/content_length*100))\\n start = now\\n f.write(chunk)\\n f.flush()\\n logger.debug('100% downloaded')\\n\\n unzip_data(destination, url=url)\\n return destination\",\n \"def download_analysis(group_id, project_label, analysis_label, save_dir, file_starts_with=None, api_key=None):\\n api_key = get_fw_api(api_key)\\n fw = flywheel.Client(api_key)\\n project = fw.lookup(f\\\"{group_id}/{project_label}\\\")\\n\\n orig_dir = Path.cwd()\\n out_dir = Path(save_dir) / analysis_label\\n zip_out_dir = out_dir / \\\"00_zip\\\"\\n extract_out_dir = out_dir / \\\"00_extract\\\"\\n zip_out_dir.mkdir(parents=True, exist_ok=True)\\n extract_out_dir.mkdir(parents=True, exist_ok=True)\\n\\n os.chdir(zip_out_dir)\\n\\n print(\\\"DOWNLOAD\\\")\\n for subject in project.subjects():\\n print(subject.label)\\n analyses = fw.get_container_analyses(subject.id, filter=f'label=\\\"{analysis_label}\\\"')\\n assert len(analyses) <= 1, \\\"More than one analysis found\\\"\\n\\n # if no analyses on subject level, look into sessions\\n if not analyses:\\n analyses = []\\n for session in subject.sessions():\\n analyses_session = fw.get_container_analyses(session.id, filter=f'label=\\\"{analysis_label}\\\"')\\n assert len(analyses_session) <= 1, \\\"More than one analysis found\\\"\\n analyses += analyses_session\\n\\n if analyses:\\n for analysis in analyses:\\n if analysis.files:\\n files = [file_obj.name for file_obj in analysis.files]\\n else:\\n files = []\\n\\n # filter files\\n download_files = []\\n if file_starts_with:\\n for f in files:\\n if f.startswith(file_starts_with):\\n download_files.append(f)\\n else:\\n download_files = files\\n\\n for file in download_files:\\n print(file)\\n analysis.download_file(file, file)\\n\\n print(\\\"UNZIP\\\")\\n zipfiles = list(zip_out_dir.glob(\\\"*.zip\\\"))\\n for file in zipfiles:\\n with ZipFile(file, \\\"r\\\") as zip_ref:\\n zip_ref.extractall(extract_out_dir)\\n\\n print(\\\"MOVE AND CLEAN UP\\\")\\n # remove id hierarchy and move to out_dir\\n # e.g., '5f34/sub-x/ses-y/func/*bold.json'\\n # 'sub-x/ses-y/func/*bold.json'\\n os.chdir(extract_out_dir)\\n file_tree = [f for f in Path(\\\".\\\").rglob(\\\"*\\\") if f.is_file()]\\n file_overwritten = []\\n for in_file in file_tree:\\n out_file = out_dir / Path(*in_file.parts[1:])\\n out_file.parent.mkdir(parents=True, exist_ok=True)\\n print(in_file, out_file)\\n if out_file.is_file():\\n file_overwritten.append(out_file)\\n in_file.rename(out_file)\\n\\n if file_overwritten:\\n file_overwritten_str = '\\\\n'.join([str(f) for f in set(file_overwritten)])\\n warn(f\\\"{len(set(file_overwritten))} have been overwritten, because of multiple files with the same name in \\\"\\n f\\\"different analyses.\\\\n{file_overwritten_str}\\\")\\n shutil.rmtree(extract_out_dir)\\n shutil.rmtree(zip_out_dir)\\n\\n print(\\\"DONE\\\")\\n os.chdir(orig_dir)\",\n \"def download(self, api_route, dest_path, payload=None, file_type_header=None, extract_archives=True):\\n resp = None\\n payload = payload or {}\\n file_type_header = file_type_header or self.default_file_type_header\\n\\n try:\\n # Fetch the file from the API.\\n resp = self.api.get(api_route, payload=payload, stream=True)\\n except KeyboardInterrupt:\\n exit()\\n\\n # Extract further info about the downloaded file.\\n file_ext, file_is_archive = self._analyze_response_file(resp, file_type_header)\\n\\n # Calculate the final path to save downloaded file at.\\n save_to, extract_to = self._calc_final_dest(\\n dest_path,\\n file_ext,\\n file_is_archive,\\n extract_archives,\\n payload.get('name') or self.default_name\\n )\\n\\n # Stream file to save path.\\n self._stream_to_path(save_to, resp.response_obj, int(resp.headers.get('Content-Length')))\\n\\n # If no archive extraction needed, just return the path at which the file was saved.\\n if not extract_to:\\n return save_to\\n\\n # Extract archive to final destination.\\n extract_zip(save_to, extract_to)\\n\\n return extract_to\",\n \"def download_dataset():\\n \\n ID = \\\"1-3_oB5iSF-c_V65-uSdUlo024NzlgSYZ\\\"\\n script1 = f\\\"\\\"\\\"\\n wget --load-cookies /tmp/cookies.txt \\\"https://docs.google.com/uc?export=download&confirm=$(wget --quiet --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id='{ID} -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\\\\1\\\\n/p')&id=\\\"{ID} -O Data.zip && rm -rf /tmp/cookies.txt\\n \\\"\\\"\\\"\\n script2 = \\\"\\\"\\\"unzip Data.zip\\\"\\\"\\\"\\n\\n os.system(script1)\\n os.system(script2)\",\n \"def download_data():\\n url = 'https://www.dropbox.com/s/8oehplrobcgi9cq/imdb.tgz?dl=1'\\n urllib.request.urlretrieve(url, 'imdb.tgz')\\n tar = tarfile.open(\\\"imdb.tgz\\\")\\n tar.extractall()\\n tar.close()\",\n \"def getSubtitleURL(self):\\n\\n # If it is a movie, we use this methodology -\\n try:\\n IndexingParameters = [\\\"subtitleUrls\\\", 0, \\\"url\\\"]\\n TitleParamters = [\\n \\\"catalogMetadata\\\", \\\"catalog\\\", \\\"title\\\", \\\"episodeNumber\\\"]\\n subRequestObject = requests.get(self.subtitleURLContainer)\\n\\n parsedJsonObject = json.loads(str(subRequestObject.text))\\n SubsURL = parsedJsonObject[IndexingParameters[0]][\\n IndexingParameters[1]][IndexingParameters[2]]\\n if self.title == \\\"Amazonsubtitles\\\":\\n try:\\n self.title = parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[2]] + \\\"_\\\" + str(\\n parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[3]])\\n except:\\n pass\\n\\n return SubsURL\\n\\n except:\\n pass\\n pass\",\n \"def download(self):\\n if not self.url:\\n raise RuntimeError(self.tips)\\n\\n download_file_name = os.path.join(\\n self.raw_path, os.path.splitext(os.path.basename(self.url))[0]\\n )\\n file_format = self.url.split(\\\".\\\")[-1]\\n if \\\"amazon\\\" in self.url:\\n raw_file_path = os.path.join(\\n self.raw_path, f\\\"{self.dataset_name}.json.{file_format}\\\"\\n )\\n else:\\n raw_file_path = os.path.join(\\n self.raw_path, f\\\"{self.dataset_name}.{file_format}\\\"\\n )\\n if \\\"1drv.ms\\\" in self.url:\\n file_format = \\\"zip\\\"\\n raw_file_path = os.path.join(\\n self.raw_path, f\\\"{self.dataset_name}.{file_format}\\\"\\n )\\n if not os.path.exists(raw_file_path):\\n print(f\\\"download_file: url: {self.url}, raw_file_path: {raw_file_path}\\\")\\n download_file(self.url, raw_file_path)\\n if \\\"amazon\\\" in raw_file_path:\\n # amazon dataset do not unzip\\n print(\\\"amazon dataset do not decompress\\\")\\n return\\n elif file_format == \\\"gz\\\":\\n file_name = raw_file_path.replace(\\\".gz\\\", \\\"\\\")\\n with gzip.open(raw_file_path, \\\"rb\\\") as fin:\\n with open(file_name, \\\"wb\\\") as fout:\\n shutil.copyfileobj(fin, fout)\\n else:\\n shutil.unpack_archive(\\n raw_file_path, self.raw_path, format=get_format(file_format)\\n )\\n\\n if not os.path.exists(download_file_name):\\n return\\n elif os.path.isdir(download_file_name):\\n os.rename(\\n download_file_name, os.path.join(self.raw_path, self.dataset_name)\\n )\\n else:\\n os.rename(\\n download_file_name,\\n os.path.join(\\n self.raw_path,\\n f'{self.dataset_name}.{download_file_name.split(\\\".\\\")[-1]}',\\n ),\\n )\",\n \"def download():\\n\\treturn response.download(request, db)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.62294996","0.573122","0.5613491","0.56069106","0.54558396","0.53945196","0.5256225","0.5209892","0.5174074","0.5155498","0.51524377","0.5145467","0.5109938","0.51030266","0.51014733","0.50734365","0.50671315","0.50465274","0.50144225","0.5005846","0.49877387","0.49658453","0.4944006","0.4919","0.4913695","0.4906728","0.4901483","0.4878431","0.4878431","0.4874475","0.48735952","0.48594403","0.48520896","0.4845884","0.48433593","0.48367923","0.4803106","0.48023212","0.4786029","0.47768742","0.4767346","0.47596952","0.47459584","0.47437268","0.47150302","0.47046235","0.47044745","0.47043127","0.47037578","0.46948978","0.46558648","0.46449816","0.46362346","0.46348378","0.46337855","0.46263275","0.46157938","0.4606996","0.4588307","0.45843333","0.4583419","0.45799443","0.45784494","0.45750612","0.45713195","0.45701283","0.45659694","0.4563764","0.45630166","0.45625013","0.45573694","0.45564994","0.45471954","0.45471478","0.45438716","0.45438635","0.45427647","0.45407405","0.4539198","0.45385236","0.453704","0.4533261","0.4531902","0.4531831","0.45252758","0.4519072","0.45150903","0.4510849","0.45053002","0.45026615","0.45018503","0.4498162","0.44966114","0.44963107","0.44915366","0.44869393","0.44866478","0.44815442","0.44764152","0.44738847"],"string":"[\n \"0.62294996\",\n \"0.573122\",\n \"0.5613491\",\n \"0.56069106\",\n \"0.54558396\",\n \"0.53945196\",\n \"0.5256225\",\n \"0.5209892\",\n \"0.5174074\",\n \"0.5155498\",\n \"0.51524377\",\n \"0.5145467\",\n \"0.5109938\",\n \"0.51030266\",\n \"0.51014733\",\n \"0.50734365\",\n \"0.50671315\",\n \"0.50465274\",\n \"0.50144225\",\n \"0.5005846\",\n \"0.49877387\",\n \"0.49658453\",\n \"0.4944006\",\n \"0.4919\",\n \"0.4913695\",\n \"0.4906728\",\n \"0.4901483\",\n \"0.4878431\",\n \"0.4878431\",\n \"0.4874475\",\n \"0.48735952\",\n \"0.48594403\",\n \"0.48520896\",\n \"0.4845884\",\n \"0.48433593\",\n \"0.48367923\",\n \"0.4803106\",\n \"0.48023212\",\n \"0.4786029\",\n \"0.47768742\",\n \"0.4767346\",\n \"0.47596952\",\n \"0.47459584\",\n \"0.47437268\",\n \"0.47150302\",\n \"0.47046235\",\n \"0.47044745\",\n \"0.47043127\",\n \"0.47037578\",\n \"0.46948978\",\n \"0.46558648\",\n \"0.46449816\",\n \"0.46362346\",\n \"0.46348378\",\n \"0.46337855\",\n \"0.46263275\",\n \"0.46157938\",\n \"0.4606996\",\n \"0.4588307\",\n \"0.45843333\",\n \"0.4583419\",\n \"0.45799443\",\n \"0.45784494\",\n \"0.45750612\",\n \"0.45713195\",\n \"0.45701283\",\n \"0.45659694\",\n \"0.4563764\",\n \"0.45630166\",\n \"0.45625013\",\n \"0.45573694\",\n \"0.45564994\",\n \"0.45471954\",\n \"0.45471478\",\n \"0.45438716\",\n \"0.45438635\",\n \"0.45427647\",\n \"0.45407405\",\n \"0.4539198\",\n \"0.45385236\",\n \"0.453704\",\n \"0.4533261\",\n \"0.4531902\",\n \"0.4531831\",\n \"0.45252758\",\n \"0.4519072\",\n \"0.45150903\",\n \"0.4510849\",\n \"0.45053002\",\n \"0.45026615\",\n \"0.45018503\",\n \"0.4498162\",\n \"0.44966114\",\n \"0.44963107\",\n \"0.44915366\",\n \"0.44869393\",\n \"0.44866478\",\n \"0.44815442\",\n \"0.44764152\",\n \"0.44738847\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6889805"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":92984,"cells":{"query":{"kind":"string","value":"Funstion takes movie file path and based on EXTENSIONS from myListy.pl returns list of movies in movie file directory"},"document":{"kind":"string","value":"def __return_movie_file_list(self, movie_path):\n movie_dir = movie_path.rsplit(\"/\",1)[0]\n movie_file_list =[]\n movie_extentionds = self.__movie_file_extensions(self.__file_extentions)\n for x in os.listdir(movie_dir):\n if x.rsplit(\".\",1)[-1]in movie_extentionds:\n movie_file_list.append(movie_dir+\"/\"+x)\t\t\n\t#USUNAC URL Z NAPISY24\n return movie_file_list"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_movies(path):\n movies_list = []\n \n \n for f in os.listdir(path):\n \n full_file_path = join(path,f)\n if isdir(full_file_path):\n \n movies_list.extend( get_movies(full_file_path) )\n \n elif isfile(full_file_path) and full_file_path[-3:] in util.extension:\n m = Movie(f, full_file_path)\n movies_list.append(m)\n \n return movies_list","def loadMovieList():\n # Read the fixed movieulary list\n fid = open('movie.txt', 'r', encoding='UTF-8')\n ls = fid.readlines()\n fid.close()\n movieList = [i[i.find(' ')+1:-1] for i in ls]\n return movieList","def get_movie_data(files: list) -> list:\n pass","def load_file_list(path=None, regx='\\.npz'):\n if path == False:\n path = os.getcwd()\n file_list = os.listdir(path)\n return_list = []\n for idx, f in enumerate(file_list):\n if re.search(regx, f):\n return_list.append(f)\n # return_list.sort()\n print('Match file list = %s' % return_list)\n print('Number of files = %d' % len(return_list))\n return return_list","def scan_videos(path, wildcard, extensions=[]):\n\n files = glob(os.path.join(path, wildcard), recursive=True)\n files = [x for x in files if os.path.isfile(x)]\n if len(extensions) > 0:\n files = filter_extensions(files, extensions)\n\n return files","def list_of_medias_ext(args, sourcedir):\n result = list()\n listdir = sorted_listdir(os.listdir(sourcedir))\n if '.nomedia' not in listdir:\n for basename in listdir:\n fullname = os.path.join(sourcedir, basename)\n if os.path.isdir(fullname) and basename != '$RECYCLE.BIN' and contains_media(args, fullname):\n result.append(fullname)\n else:\n if is_media_within_dates(fullname, args.dates):\n result.append(fullname)\n return result","def test_return_only_filenames_under_ext():\n hardcodedpath = \"/home/dados/VideoAudio/Yt videos/Soc Sams vi/Lang Sams vi/Chinese Sams vi/\" \\\n \"Harbin Mandarin yu/BMC 19v 12' 2018 4h Beginning Mandarin Chinese Lessons yu Harbin ytpl/a\"\n path_in_arg_if_any = None\n for arg in sys.argv:\n if arg.startswith('-ppath='):\n path_in_arg_if_any = arg[len('-ppath='):]\n if path_in_arg_if_any is None:\n path_in_arg_if_any = hardcodedpath\n ppath = path_in_arg_if_any\n filenames = os.listdir(ppath)\n filenames.sort()\n print(filenames)\n retlist = return_only_filenames_under_ext(filenames, ppath)\n print(retlist)","def getFiles(directory, showName, extension):\n os.chdir(directory)\n \n list = []\n \n for file in glob.glob(\"*\"+showName+\"*.\"+extension):\n list.append(file)\n \n return list","def read_movies(filename):\n movies = []\n # TODO: Read the file correctly and instantiate movie objects to store them\n # inside the movies list.\n return movies","def getVideoFilesFromFileList(filelist):\n videoFileList = []\n for videoFile in filenames:\n videoRoot, videoExt = os.path.splitext(videoFile)\n if videoExt in ['.mov', '.mp4', '.mkv', '.avi']:\n videoFileList.append(videoFile)\n return videoFileList","def get_movies():\n\n # ouverture du fichier de notre liste de films\n with open(DATA_FILE,\"r\") as f:\n movies_list = json.load(f)\n\n # notre liste des instances\n movies = [Movie(m)for m in movies_list] \n return movies","def imdb_load():\n for root, dirs, filenames in os.walk(os.path.dirname(__file__) + \"/imdb\"):\n for file_name in filenames:\n if file_name.find(\".json\") > 0:\n Movie.imdb_load_file(os.path.dirname(__file__) + \"/imdb/\" + file_name)\n return Movie.__movies","def load_video_paths(dir):\n VIDEO_EXTENSIONS = ['.mov', '.MOV', '.mp4']\n video_paths = []\n\n # traverse directory to obtain only paths to videos\n for dir_name, _, paths in sorted(os.walk(os.path.expanduser(dir))):\n for path in paths:\n if any(path.endswith(extensions) for extensions in VIDEO_EXTENSIONS):\n video_paths.append(os.path.expanduser(dir_name + '/' + path))\n\n return video_paths","def filter_videos(\n files: list\n):\n#cSpell:words webm vchd rmvb gifv xvid vidx\n video_extensions = [\n \"WEBM\",\n \"MPG\",\"MP2\", \"MPEG\", \"MPE\", \"MPV\",\n \"OGV\",\"OGG\",\n \"MP4\", \"M4P\", \"M4V\",\n \"AVI\",\n \"WMV\",\n \"MOV\",\"QT\",\n \"FLV\",\"SWF\",\n \"F4V\",\"F4P\",\"F4A\",\"F4B\",\n \"VCHD\",\n \"RMVB\",\"RM\",\n \"VOB\",\n \"MKV\",\n \"MTS\", \"M2TS\", \"TS\",\n \"MNG\",\n \"GIFV\",\n \"GIF\",\n \"DRC\",\n \"XVID\",\n \"VIDX\",\n \"ASF\",\n \"AMV\",\n \"M2V\",\n \"SVI\",\n \"3GP\",\n \"MXF\",\n \"ROQ\",\n \"NSV\",\n \"3G2\",\n ]\n return filter_files_by_extension(files, video_extensions)\n ...","def movie_list(self):\n return self._request_obj(self._urls[\"movie_list\"], key=\"genres\")","def list_type_in_dir(path, extension):\n path, extension = check_args(path, extension)\n files = os.listdir(path)\n file_list = [os.path.join(path, f)\n for f in fnmatch.filter(files, '*' + extension)]\n\n return file_list","def readPlayerImageFiles(self):\n currentPath = os.path.dirname(os.path.abspath(__file__))\n listOfFileNames=[]\n for i in os.listdir(currentPath):\n if re.match(\"player\\_\\d+\",i): #i.endswith(\".gif\")\n listOfFileNames.append(currentPath+'/'+i)\n return listOfFileNames","def list_phonebooks(path=\".\"):\n files = os.listdir(path)\n for file in files:\n if file.endswith(EXTENSION):\n print file","def getVideosPath(self):\r\n videoTypes = [\r\n ('MP4 files', '*.mp4'),\r\n ('3GP files', '*.3gp'),\r\n ('WMV files', '*.wmv'),\r\n ('FLV files', '*.flv'),\r\n ('AVI files', '*.avi'),\r\n ]\r\n global filenames\r\n filenames = askopenfilenames(title=\"Select video files\", multiple=True, )","def get_all_videos(dir, extension='mp4'):\n\n list_video_fn = []\n for dirpath, dirnames, filenames in os.walk(dir):\n for filename in [f for f in filenames if f.endswith(extension)]:\n fn = os.path.join(dirpath, filename)\n list_video_fn.append(fn)\n\n return list_video_fn","def MovieScan():\r\n for root, dirnames, filenames in os.walk(dlPath):\r\n for extend in movtypes:\r\n for filename in fnmatch.filter(filenames, extend):\r\n matches.append(os.path.join(root, filename))\r\n print(os.path.join(root, filename))\r\n shutil.move(os.path.join(root, filename), os.path.join(moviePath, filename))\r\n print color.GREEN + 'File succesfully moved!' + color.ENDC\r\n print 'Finished Scanning For Movies'","def list_movies(category):\n movies = get_movies(category)\n listing = []\n for movie in movies:\n list_item = xbmcgui.ListItem(label=movie[0])\n list_item.setArt({'thumb': movie[1],\n 'icon': movie[1],\n 'fanart': movie[1]})\n list_item.setInfo('video', {'title': movie[0]})\n if 'Next Page' in movie[0]:\n url = '{0}?action=list_category&category={1}'.format(_url, movie[2])\n else:\n url = '{0}?action=list_movie&thumb={1}&movie={2}'.format(_url, movie[1], movie[2])\n is_folder = True\n listing.append((url, list_item, is_folder))\n xbmcplugin.addDirectoryItems(_handle, listing, len(listing))\n xbmcplugin.endOfDirectory(_handle)","def listar_extension(dir_name, ext='.png'):\n\n list_ext = []\n for root, dirs, files in os.walk(directorio):\n for name in files:\n if ext in name:\n list_ext.append(name)\n for name in dirs:\n if ext in name:\n list_ext.append(name)\n\n return list_ext","def load_video_data(fpath):\n videos = []\n with open(fpath) as f:\n d1 = json.load(f)['items']\n videos += append_videos(d1)\n return videos","def getMediaFileList(path):\n\n fileTypes = (\"jpg\", \"mov\", \"mp4\")\n fileList = []\n for base_dir, dirs, files in os.walk(path):\n fileList.extend([os.path.join(base_dir, f) for f in files if f.split(\".\")[1].lower() in fileTypes])\n\n # for the new canon camera, ther are some .Trash and trashinfo files, want to ignore them\n fileList = [file for file in fileList if \"trash\" not in file and \"Trash\" not in file]\n return fileList","def load_movies_data(filename):\n movies = []\n with open(filename) as movies_file:\n try:\n data = json.load(movies_file)\n except json.decoder.JSONDecodeError:\n logging.critical(\"Cannot get movies data.\")\n return movies\n\n for movie_data in data:\n try:\n movies.append(media.Movie(**movie_data))\n except TypeError:\n logging.warning(\"Cannot load a movie; skipping an item\")\n\n return movies","def get_all_videos_in_directory(directory: str):\n\n all_files_and_folders = os.listdir(directory)\n\n only_videos = []\n for file in all_files_and_folders:\n if is_video(file):\n only_videos.append(file)\n ...\n\n return only_videos","def top_ten_movies(path):\n content = open(path, \"r\")\n topten = []\n for x in content:\n topten.append(x) \n return topten","def getFilmTitles(checkFolder):\n\n files = [str(x) for x in Path(checkFolder).rglob(\"*\")]\n libFilmFiles = list(map(os.path.basename,files)) # Remove the path\n libFilmTitles = [os.path.splitext(x)[0] for x in libFilmFiles]\n return libFilmTitles","def test_extensions(self):\n dummy_folder = TestOspaListDir.get_dummy_folder()\n need_result = []\n for i in range(1, 4):\n need_result.append(os.path.join(dummy_folder, 'memes', 'meme monty python', 'meme{}.jpg'.format(i)))\n need_result.append(os.path.join(dummy_folder, 'memes', 'meme1.jpg'))\n need_result.append(os.path.join(dummy_folder, 'memes', 'meme2.png'))\n need_result.append(os.path.join(dummy_folder, 'memes', 'meme4.jpg'))\n need_result.append(os.path.join(dummy_folder, 'memes', 'meme4.png'))\n\n for i in ['antigravity.png',\n 'egg.png',\n 'holy_grenade.png',\n 'spam.jpg',\n ]:\n need_result.append(os.path.join(dummy_folder, i))\n\n result = listdir(dummy_folder, full_path=True, only_files=True, walk=True, extensions=['jpg', 'png'])\n self.assertEqual(sorted(result), sorted(need_result))\n result = listdir(dummy_folder, full_path=True, only_files=True, walk=True, extensions=['.jpg', '.png'])\n self.assertEqual(sorted(result), sorted(need_result))\n result = listdir(dummy_folder, full_path=True, only_files=True, walk=True, extensions=['.JPG', 'png'])\n self.assertEqual(sorted(result), sorted(need_result))\n result = listdir(dummy_folder, full_path=True, only_files=True, walk=True, extensions=('.JPG', 'png'))\n self.assertEqual(sorted(result), sorted(need_result))\n result = listdir(dummy_folder, full_path=True, only_files=True, walk=True, extensions={'.JPG', 'png'})\n self.assertEqual(sorted(result), sorted(need_result))","def create_movie(file_path_list, movie_name_list, movie_path, file_type='png',\n fps=1, movie_type='mp4', codec='mpeg4'):\n for movie_name, file_path in zip(movie_name_list, file_path_list):\n file_list = sorted(glob.glob(file_path + '*.' + file_type))\n print(file_list)\n\n # Generate clip\n clip = ImageSequenceClip(file_list, fps=fps)\n # Write out clip\n if not os.path.isdir(movie_path):\n os.makedirs(movie_path)\n clip.write_videofile(\n movie_path +\n movie_name +\n '.' +\n movie_type,\n codec=codec)\n clip.write_gif(movie_path + movie_name + '.gif')\n\n print('Created movie ' + movie_path + movie_name)","def list_files(file, folder, extension = '*.evtx'):\r\n if file:\r\n return [file]\r\n elif folder:\r\n return [ y for x in os.walk(folder) for y in glob(os.path.join(x[0], extension))]\r\n else:\r\n return []","def filelist(filepath: str, ext: str = None) -> list:\n file_list = []\n for path, _, files in os.walk(filepath):\n for name in files:\n _, extension = os.path.splitext(name)\n if ext is None or extension == ext:\n file_list.append(os.path.join(path, name))\n\n return file_list","def list_videos(movie,thumb):\n\n videos = get_videos(movie)\n listing = []\n for video in videos:\n list_item = xbmcgui.ListItem(label=video[0])\n list_item.setArt({'thumb': thumb,\n 'icon': thumb,\n 'fanart': thumb})\n list_item.setInfo('video', {'title': video[0]})\n list_item.setProperty('IsPlayable', 'true')\n url = '{0}?action=play&video={1}'.format(_url, video[1])\n is_folder = False\n listing.append((url, list_item, is_folder))\n\n xbmcplugin.addDirectoryItems(_handle, listing, len(listing))\n xbmcplugin.endOfDirectory(_handle)","def _get_movies(self):\n\n return self.data_file['movies']","def grab_files(folder_path, ext='.h5', first4=None):\r\n folder_path=os.path.normpath(folder_path)\r\n if first4 in locals():\r\n # incorporate the excerpt of the filename\r\n dir_List=[f for f in os.scandir(folder_path) if f.is_file()==True and \r\n f.name[-len(ext):]==ext and f.name[:4]==first4] \r\n else:\r\n #do it without the excerpt\r\n dir_List=[f for f in os.scandir(folder_path) if f.is_file()==True and \r\n f.name[-len(ext):]==ext]\r\n \r\n return dir_List","def get_videos_of_folder(folder):\n\n Settings.dev_print(\"getting videos of folder: {}\".format(folder.get_title()))\n if not folder: return []\n videos = []\n files = []\n valid_videos = [\".mp4\",\".mov\"]\n for f in os.listdir(folder.get_path()):\n ext = os.path.splitext(f)[1]\n if ext.lower() not in valid_videos:\n continue\n file = File()\n setattr(file, \"path\", os.path.join(folder.get_path(),f))\n files.append(file)\n Settings.maybe_print(\"video path: {}\".format(os.path.join(folder.get_path(),f)))\n return files","def get_files_suffix_list(suffixes, flist, Lshow=False, Ldir=False):\n matched_files=[]\n dirs=[]\n files=[]\n for fname in flist:\n if os.path.isdir(fname):\n dirs.append(fname)\n else:\n files.append(fname)\n for suff in suffixes:\n for fname in files:\n #print(f\" {suff} in {fname} ?\")\n if fname.endswith(suff):\n matched_files.append(fname)\n matched_files.extend(dirs) \n return matched_files","def read_files_to_list(fdir, expression='*.json'):\n filelist = []\n for file in glob.glob(path.join(fdir, expression)):\n filelist.append(file)\n return filelist","def movies_filename(self):\n pass","def get_file_list() -> List[str]:\n filenames = []\n os.makedirs(\"sequence\", exist_ok=True)\n for file in glob.glob(\"sequence/*.smp\"):\n filenames.append(file.replace(\"sequence/\", \"\"))\n return filenames","def getMediaFiles(path):\n fileList = getMediaFileList(path)\n # dirList = getDirectoryList(path)\n\n # results = map(getMediaFiles, dirList)\n\n # for result in results:\n # fileList = fileList + result\n\n return fileList","def get_imlist2(path):\n return [\n os.path.join(path, f) for f in os.listdir(path) if f.endswith('.ppm')\n ]","def _filter_files(file_dir: Union[str, Path], is_viya4: Optional[bool] = False) -> list:\n file_names = []\n file_names.extend(sorted(Path(file_dir).glob(\"*.json\")))\n if is_viya4:\n file_names.extend(sorted(Path(file_dir).glob(\"score_*.py\")))\n file_names.extend(sorted(Path(file_dir).glob(\"*.pickle\")))\n # Include H2O.ai MOJO files\n file_names.extend(sorted(Path(file_dir).glob(\"*.mojo\")))\n if file_names:\n return file_names\n else:\n raise FileNotFoundError(\n \"No valid model files were found in the provided file directory.\"\n )","def find_files(extensions):\n\n return [fname for fname in os.listdir('.') if fname.endswith(extensions)]","def filelisting(directory, suffix = 'tcx'):\n files = []\n for f in os.listdir(directory):\n fullpath = os.path.join(directory, f)\n if os.path.isfile(fullpath) and f.endswith(suffix):\n files.append(fullpath)\n return files","def list_a_file_type(path, extension):\n path, extension = check_args(path, extension)\n file_list = [os.path.join(dirpath, f)\n for dirpath, dirnames, files in os.walk(path)\n for f in fnmatch.filter(files, '*' + extension)]\n\n return file_list","def load_video_data(self):\n self.file_videos = [\n Video.from_file(path, self)\n for path in self.video_dir.glob('*.json')\n ]","def get_music_files(pth: pathlib.Path) -> typing.List[mutagen.FileType]:\n file_names = [os.path.join(pth, f) for f in os.listdir(pth)]\n files = [mutagen.File(f) for f in file_names if os.path.isfile(f)]\n return [f for f in files if f is not None]","def get_files(start_str = \"sim_\"):\n n = len(start_str)\n file_list = [f for f in os.listdir(in_path) if f[0:n] == start_str]\n return file_list","def getMusic(self, path):\n music =[]\n files = [ f for f in listdir(path) if isfile(join(path,f))]\n for f in files:\n m = join(path,f)\n #if not f.endswith('.mp3'):\n # files.remove(f)\n if f.endswith('.mp3'):\n music.append(m)\n return music","def filter_paths(path):\n return [\"{}/{}\".format(path, f) for f in os.listdir(path) if\n f.endswith(FILE_EXTENSION_VM)]","def list_of_medias(args, sourcedir, recursive):\n files = list_of_files(sourcedir, recursive)\n return [_ for _ in files if is_media_within_dates(_, args.dates)]","def get_files(path, extension):\n extension = listify(extension)\n return [p for p in path.ls() if p.suffix in extension and \"(\" not in p.stem]","def get_files_with_extension(self, extension=sys.argv[1]) -> list:\n if extension == \"\":\n raise EnvironmentError(\"No extension provided!\")\n\n result = []\n for idx, file in enumerate(self.file_list):\n if re.search(extension + \"$\", file):\n result.append(file)\n\n if len(result) == 0:\n raise Exception(\"No {} files found.\".format(extension))\n\n return result","def gather_videos(files):\r\n # Because we are using a set, no duplicates will be present\r\n videos = set()\r\n for item in files:\r\n # Crawl subfolders\r\n if os.path.isdir(item):\r\n for root, _, filenames in os.walk(item):\r\n for filename in filenames:\r\n filepath = os.path.join(root, filename)\r\n # Check if its a video\r\n if YoutubeService.valid_video_file(filepath):\r\n videos.add(filepath)\r\n # If it exists it is a single file, check if its a video\r\n elif os.path.exists(item) and YoutubeService.valid_video_file(item):\r\n videos.add(item)\r\n return videos","def listFiles(self):\n current_month = NoaaCycle.last_month()\n # 2do archive contain extra path: data/noaa/metar/2011-* ; better is 2011-*\n dir_regex = os.path.join(self.download_dir, \"%s-*\" % current_month)\n self.archive_name = os.path.join(self.download_dir, current_month)\n return glob.glob(dir_regex)","def test_get_filenames_by_ext():\n tmpdir = os.path.join(tempfile.gettempdir(), \"jade-test-tmp87alkj8ew\")\n os.makedirs(tmpdir, exist_ok=True)\n\n data = {\"A\": 1, \"B\": 2}\n json_file = os.path.join(tmpdir, \"a.json\")\n dump_data(data, json_file)\n\n toml_file = os.path.join(tmpdir, \"b.toml\")\n dump_data(data, toml_file)\n\n filenames = get_filenames_by_ext(tmpdir, \".json\")\n assert \"a.json\" in next(filenames)\n\n filenames = get_filenames_by_ext(tmpdir, \".toml\")\n assert \"b.toml\" in next(filenames)","def list_movie():\n if not MOVIES:\n print('No stored movies yet')\n\n for movie in MOVIES:\n print(f\"{movie['name']} ({movie['year']}) - Director by '{movie['director']}'\")","def get_maps(path: str, ext: str) -> list:\n result = [\n y for x in os.walk(path) for y in glob(os.path.join(x[0], \"*.{}\".format(ext)))\n ]\n\n return result","def get_files(path: str, extension: str = '.wav') -> List[Path]:\n\n return list(Path(path).expanduser().resolve().rglob(f'*{extension}'))","def _findfile(self,path,label):\n files=[];filenames=os.listdir(path)\n for name in filenames:\n if os.path.splitext(name)[0]==str(label):\n files.append(name)\n return files","def create_file_list(path, extension='.png'):\n file_list = []\n for root, _, files in os.walk(path, topdown=False):\n for name in files:\n if name.endswith(extension):\n full_name = os.path.join(root, name)\n file_list.append(full_name)\n\n return file_list","def get_file_extensions():\n my_files_ext = []\n for file in os.listdir(os.getcwd()):\n if os.path.isfile(file):\n file_info = os.path.splitext(file)\n file_ext = file_info[1]\n my_files_ext.append(file_ext)\n return [file for file in my_files_ext]","def with_path(path):\n seen = set()\n seen_add = seen.add\n videos = []\n all_videos = list(mythVideo.searchVideos(filename = path))\n\n for video in all_videos:\n if video.season > 0:\n video.label = video.title + \" - Season \" + str(video.season)\n\n if video.label not in seen and not seen_add(video.label):\n video.url = \"/videos/\" + video.title + \"/season/\" + str(video.season)\n videos.append(video)\n\n else:\n video.label = video.title + \" - \" + video.subtitle\n video.url = \"/videos/\" + video.title + \"/\" + video.hash\n videos.append(video)\n\n if len(videos) == 1:\n videos[0].pic = url_for('.video_image', title = title, hash = videos[0].hash)\n videos[0].feplay = url_for('.video_feplay', title = title, hash = hash)\n return render_template('recording.html', item = videos[0])\n\n videos = sorted(videos, key = lambda video: video.season)\n return render_template('list.html', items = videos, page_title = title)","def collect_files_with_extensions(self, extension: str) -> List[str]:\n occurrences = []\n for position in os.listdir(self.directory):\n if os.path.isdir(position):\n for file in os.listdir(position):\n if os.path.isfile(os.path.join(position, file)) and file.endswith(\n extension\n ):\n occurrences.append(os.path.join(self.directory, position, file))\n return occurrences","def get_movie_info_from_folder(folder):\n if not os.path.exists(folder):\n raise ValueError(\"folder does not exists\")\n for file in os.listdir(folder):\n filename = os.path.join(folder, file)\n if os.path.isfile(filename):\n e = ET.parse(filename).getroot()\n for result in e[1]:\n attributes = dict()\n for bindings in result:\n attributes[bindings.attrib['name']] = bindings[0].text\n if len(attributes['title']) > 0:\n yield Movie(**attributes)","def list(self):\n return [os.splitext(el)[0] for el in\n os.listdir(str(self.model_dir))]","def get_movies():\n tree = get_tree()\n movie_list = [movie.get(\"title\") for movie in tree.getroot().findall(\"movie\")]\n return movie_list","def listen_files_list(self, directory):\r\n files = [f for f in os.listdir(directory) if\r\n f[-len(self.fileExt):] == self.fileExt]\r\n return files","def load_movies():\n filepath = \"./seed_data/u.item\"\n movies = open(filepath)\n\n for movie in movies:\n movie = movie.rstrip().split('|')\n title = movie[1][:-7]\n title = title.decode(\"latin-1\")\n if movie[2]:\n date = datetime.strptime(movie[2], '%d-%b-%Y')\n else:\n date = None\n db_movie = Movie(\n movie_id = movie[0], title = title, \n released_at = date, imdb_url = movie[4])\n db.session.add(db_movie)\n\n db.session.commit()","def list_directory(path):\n files = []\n for f in listdir(path):\n if isfile(join(path, f)) and f.endswith('.mp3'):\n files.append(f)\n return files","def txtfiles2pylist(mypath: str) -> list:\n\n import glob\n filenames = glob.glob(f'{mypath}/*.txt')\n res = []\n for filename in filenames:\n with open(filename, 'r', encoding='utf-8') as file:\n data = file.read()\n res.append(data)\n return res","def get_imlist(path):\n\treturn [os.path.join( path, f) for f in os.listdir(path) if f.endswith('.jpg')]","def get_imlist(path):\n return [os.path.join(path, f) for f in os.listdir(path) if f.endswith('.jpg')]","def __init__(self, _format):\n path = _format + os.sep + \"playlists\"\n self.__playlists = []\n for root, directory, files in os.walk(path):\n for file in files:\n if file.endswith(\".txt\"):\n self.__playlists.append(file[:-4])","def initFileList(self,extension):\r\n self.listExec.Clear()\r\n for fname in os.listdir(\"data\"):\r\n #print 'testing file ' , fname\r\n \r\n if extension in fname :\r\n #print fname\r\n self.listExec.Append(fname)\r\n self.Refresh()","def get_imdb_list():\n list_file = 'imdb.txt'\n name_column = 26\n f = open(list_file, 'r')\n film_list = []\n pos = 0\n\n for line in f:\n pos += 1\n words = line.split()\n name = line[name_column:-1]\n # could be problematic is there are brackets in the film name\n year = name[name.find('(') + 1:name.find(')')]\n name = name.replace('(' + year + ')', '')\n film = {\n 'pos': pos,\n 'score': Decimal(words[2]),\n 'name': name.strip(),\n 'year': year\n }\n film_list.append(film)\n f.close()\n return film_list","def create_list_menu(self):\n films = []\n try:\n for root, dirs, files in os.walk(str(self.initial_directory)):\n for file in files:\n if file.endswith(('.mkv', '.avi', '.mp4')) and not file.endswith(('.sample.mkv', '.sample.avi', 'sample.mp4')):\n films.append(os.path.join(root, file))\n except TypeError:\n raise(\"Error\")\n films.sort(key=lambda s: s.lower().split('/')[-1])\n [self.create_film_entry(film) for film in films]\n self.menubar.add_cascade(label=\"All Films\", menu=self.list_menu)","def standardize_file_names(source):\n # Convert File Names into a List\n video_list = os.listdir(source)\n print(video_list)\n \n # Switch into the Directory and rename all files\n os.chdir(source)\n for i in range(len(video_list)):\n os.rename(video_list[i], 'video'+ str(i) + '.MOV')","def get_lst_images(file_path):\n return [i for i in os.listdir(file_path) if i != '.DS_Store']","def dir_search(ext, file_path='./'):\n try:\n return [file_path + \"/\" + file for file in os.listdir(file_path) if file.endswith(ext)]\n except OSError as e:\n logger.error(e)\n return []\n except Exception as e:\n logger.error(e)\n return []","def _filenames(self, dir_or_file):\n if os.path.isdir(dir_or_file):\n return glob(os.path.join(dir_or_file, \"*.txt\"))\n else:\n return [dir_or_file]","def load_movies(self, file_name):\n\n in_file = open('{}'.format(file_name), 'r')\n for line in in_file:\n line_str = line.strip().split(',')\n # Create movie instance and convert year to an integer\n movie = Movie(line_str[INDEX_OF_TITLE], int(line_str[INDEX_OF_YEAR]), line_str[INDEX_OF_CATEGORY],\n True if line_str[INDEX_OF_STATUS] == WATCHED else False)\n self.movies.append(movie)\n in_file.close()","def last_videos_recorded(self) -> list:\n return sorted(glob.glob(VIDEOS_DIR), key=os.path.getmtime)[-20:]","def get_filestream(data_dir: str, ext: str) -> Iterable[str]:\n return listdir(data_dir) \\\n | where(lambda p: p.endswith(ext)) \\\n | select( lambda p: join(data_dir,p))","def _findVideoFile(self, videofile):\n for vf in self.vflist:\n if vf.startswith(videofile + '.'):\n videosource = os.path.join(self.vfdir, vf)\n return videosource","def get_oscars_best_picture_list():\n list_file = 'oscar_best_picture_list.txt'\n f = open(list_file, 'r')\n film_list = []\n\n for line in f:\n words = line.split('-')\n film = {\n 'year': words[0][:-1],\n 'name': words[1][2:-2]\n }\n film_list.append(film)\n f.close()\n # Reverse as we want newest first not last\n film_list.reverse()\n return film_list","def createFileList(my_dir, term):\n \n for subdir, dirs, files in os.walk(my_dir):\n for file in files:\n if re.search(re.escape(term), file):\n result = os.path.join(subdir, file)\n fileList.append(result)\n return fileList","def get_files_from_of_type(path: str, ext: str) -> List[str]:\n files = []\n for root, dirnames, filenames in os.walk(path):\n for filename in fnmatch.filter(filenames, \"*.\" + str(ext)):\n files.append(os.path.join(root, filename))\n if not files:\n logging.error(\"No language files found in folder: \" + str(os.sep.join([convert_vars.BASE_PATH, \"source\"])))\n logging.debug(f\" --- found {len(files)} files of type {ext}. Showing first few:\\n* \" + str(\"\\n* \".join(files[:3])))\n return files","def list_files(directory, extension):\n file_list = listdir(directory)\n included_list = []\n for f in file_list:\n for ext in extension:\n if f.endswith('.' + ext):\n included_list.append(f)\n break\n return included_list","def stat_subtitle(self, release_name, movie_dir):\n ret = {}\n for root_dir, child_folders, file_names in os.walk(movie_dir):\n for file_name in file_names:\n if not file_name.startswith(release_name):\n continue\n\n subtitle_info = get_subtitle_info(file_name)\n if not subtitle_info:\n continue\n\n if 'lang' not in subtitle_info:\n continue\n\n lang = subtitle_info['lang']\n if lang not in ret:\n ret[lang] = []\n\n ret[lang].append(file_name)\n\n # Sort result\n for lang in ret:\n ret[lang] = sorted(ret[lang])\n\n return ret","def getlistofpossibletitles(fileitem,shows):\n title = []\n title.append(fileitem)\n lookfor = fileitem.replace(\".\",\" \")\n title.append(lookfor)\n lookfor = fileitem.replace('-',\" \")\n title.append(lookfor)\n return title","def _convert_to_movies(the_movie_db, raw_movies):\n\n movies = list()\n for movie in raw_movies:\n poster = \"\"\n if 'poster_path' in movie:\n poster = constants.POSTER_URL + movie['poster_path']\n\n success, movie_trailer_url = the_movie_db.get_movie_trailer(movie['id'])\n if not success:\n print \"something went wrong with movie: {}\".format(movie['id'])\n\n movies.append(\n media.Movie(movie['title'], poster, movie_trailer_url)\n )\n\n return movies","def _collect_files(folders, extention='Default'):\r\n if isinstance(extention, str):\r\n if extention.lower() == 'default':\r\n extention = ['.*']\r\n else:\r\n extention = [extention]\r\n files = []\r\n for f in folders:\r\n for e in extention:\r\n files += glob(os.path.join(f, f'*{e}'))\r\n return files","def getListOfFiles(directory, extension):\n allFiles = [f for f in os.listdir(directory) if\n os.path.isfile(os.path.join(directory, f)) and f.endswith(extension)]\n return allFiles","def list_all(train_dir):\r\n path = train_dir\r\n result = []\r\n for fn in os.listdir(path): #fn 表示的是文件名\r\n result.append(fn)\r\n return result","def all_mpfile_names(mpfile_directory=MPFILE_DIRECTORY):\n mpfile_names = [fname for fname in os.listdir(mpfile_directory)\n if (fname.endswith(\".txt\")) and (fname.startswith(\"MP_\"))]\n return mpfile_names","def movie_path_list_fixture(tmpdir_factory):\n path_list = []\n\n parent_tmpdir = tmpdir_factory.mktemp(\"movies_for_test\")\n rng = np.random.default_rng(172312)\n this_dir = tempfile.mkdtemp(dir=parent_tmpdir)\n this_path = tempfile.mkstemp(dir=this_dir, suffix=\".h5\")[1]\n with h5py.File(this_path, \"w\") as out_file:\n out_file.create_dataset(\"data\", data=rng.random((12, 512, 512)))\n\n path_list.append(this_path)\n\n this_dir = tempfile.mkdtemp(dir=parent_tmpdir)\n this_dir = pathlib.Path(this_dir) / \"processed\"\n this_dir.mkdir()\n this_path = this_dir / \"concat_31Hz_0.h5\"\n with h5py.File(this_path, \"w\") as out_file:\n out_file.create_dataset(\"data\", data=rng.random((12, 512, 512)))\n path_list.append(str(this_path.resolve().absolute()))\n\n this_dir = tempfile.mkdtemp(dir=parent_tmpdir)\n this_dir = pathlib.Path(this_dir) / \"processed\"\n this_dir.mkdir()\n this_path = this_dir / \"motion_corrected_video.h5\"\n with h5py.File(this_path, \"w\") as out_file:\n out_file.create_dataset(\"data\", data=rng.random((12, 512, 512)))\n path_list.append(str(this_path.resolve().absolute()))\n\n yield path_list\n\n for this_path in path_list:\n this_path = pathlib.Path(this_path)\n if this_path.is_file():\n this_path.unlink()","def get_filepaths(extract_dir):\n\n index = []\n labels = []\n _extract_dir = os.path.join(extract_dir, 'UCF-101')\n for folder in os.listdir(_extract_dir):\n labels.append(folder)\n folderpath = os.path.join(_extract_dir, folder)\n\n if not os.path.isdir(folderpath):\n continue\n\n for filename in os.listdir(folderpath):\n if 'avi' not in filename:\n continue\n\n if filename[0] == '.':\n continue\n\n filepath = os.path.join(folderpath, filename)\n\n if os.path.exists(filepath):\n index.append(filepath)\n else:\n print(filepath)\n return index, labels"],"string":"[\n \"def get_movies(path):\\n movies_list = []\\n \\n \\n for f in os.listdir(path):\\n \\n full_file_path = join(path,f)\\n if isdir(full_file_path):\\n \\n movies_list.extend( get_movies(full_file_path) )\\n \\n elif isfile(full_file_path) and full_file_path[-3:] in util.extension:\\n m = Movie(f, full_file_path)\\n movies_list.append(m)\\n \\n return movies_list\",\n \"def loadMovieList():\\n # Read the fixed movieulary list\\n fid = open('movie.txt', 'r', encoding='UTF-8')\\n ls = fid.readlines()\\n fid.close()\\n movieList = [i[i.find(' ')+1:-1] for i in ls]\\n return movieList\",\n \"def get_movie_data(files: list) -> list:\\n pass\",\n \"def load_file_list(path=None, regx='\\\\.npz'):\\n if path == False:\\n path = os.getcwd()\\n file_list = os.listdir(path)\\n return_list = []\\n for idx, f in enumerate(file_list):\\n if re.search(regx, f):\\n return_list.append(f)\\n # return_list.sort()\\n print('Match file list = %s' % return_list)\\n print('Number of files = %d' % len(return_list))\\n return return_list\",\n \"def scan_videos(path, wildcard, extensions=[]):\\n\\n files = glob(os.path.join(path, wildcard), recursive=True)\\n files = [x for x in files if os.path.isfile(x)]\\n if len(extensions) > 0:\\n files = filter_extensions(files, extensions)\\n\\n return files\",\n \"def list_of_medias_ext(args, sourcedir):\\n result = list()\\n listdir = sorted_listdir(os.listdir(sourcedir))\\n if '.nomedia' not in listdir:\\n for basename in listdir:\\n fullname = os.path.join(sourcedir, basename)\\n if os.path.isdir(fullname) and basename != '$RECYCLE.BIN' and contains_media(args, fullname):\\n result.append(fullname)\\n else:\\n if is_media_within_dates(fullname, args.dates):\\n result.append(fullname)\\n return result\",\n \"def test_return_only_filenames_under_ext():\\n hardcodedpath = \\\"/home/dados/VideoAudio/Yt videos/Soc Sams vi/Lang Sams vi/Chinese Sams vi/\\\" \\\\\\n \\\"Harbin Mandarin yu/BMC 19v 12' 2018 4h Beginning Mandarin Chinese Lessons yu Harbin ytpl/a\\\"\\n path_in_arg_if_any = None\\n for arg in sys.argv:\\n if arg.startswith('-ppath='):\\n path_in_arg_if_any = arg[len('-ppath='):]\\n if path_in_arg_if_any is None:\\n path_in_arg_if_any = hardcodedpath\\n ppath = path_in_arg_if_any\\n filenames = os.listdir(ppath)\\n filenames.sort()\\n print(filenames)\\n retlist = return_only_filenames_under_ext(filenames, ppath)\\n print(retlist)\",\n \"def getFiles(directory, showName, extension):\\n os.chdir(directory)\\n \\n list = []\\n \\n for file in glob.glob(\\\"*\\\"+showName+\\\"*.\\\"+extension):\\n list.append(file)\\n \\n return list\",\n \"def read_movies(filename):\\n movies = []\\n # TODO: Read the file correctly and instantiate movie objects to store them\\n # inside the movies list.\\n return movies\",\n \"def getVideoFilesFromFileList(filelist):\\n videoFileList = []\\n for videoFile in filenames:\\n videoRoot, videoExt = os.path.splitext(videoFile)\\n if videoExt in ['.mov', '.mp4', '.mkv', '.avi']:\\n videoFileList.append(videoFile)\\n return videoFileList\",\n \"def get_movies():\\n\\n # ouverture du fichier de notre liste de films\\n with open(DATA_FILE,\\\"r\\\") as f:\\n movies_list = json.load(f)\\n\\n # notre liste des instances\\n movies = [Movie(m)for m in movies_list] \\n return movies\",\n \"def imdb_load():\\n for root, dirs, filenames in os.walk(os.path.dirname(__file__) + \\\"/imdb\\\"):\\n for file_name in filenames:\\n if file_name.find(\\\".json\\\") > 0:\\n Movie.imdb_load_file(os.path.dirname(__file__) + \\\"/imdb/\\\" + file_name)\\n return Movie.__movies\",\n \"def load_video_paths(dir):\\n VIDEO_EXTENSIONS = ['.mov', '.MOV', '.mp4']\\n video_paths = []\\n\\n # traverse directory to obtain only paths to videos\\n for dir_name, _, paths in sorted(os.walk(os.path.expanduser(dir))):\\n for path in paths:\\n if any(path.endswith(extensions) for extensions in VIDEO_EXTENSIONS):\\n video_paths.append(os.path.expanduser(dir_name + '/' + path))\\n\\n return video_paths\",\n \"def filter_videos(\\n files: list\\n):\\n#cSpell:words webm vchd rmvb gifv xvid vidx\\n video_extensions = [\\n \\\"WEBM\\\",\\n \\\"MPG\\\",\\\"MP2\\\", \\\"MPEG\\\", \\\"MPE\\\", \\\"MPV\\\",\\n \\\"OGV\\\",\\\"OGG\\\",\\n \\\"MP4\\\", \\\"M4P\\\", \\\"M4V\\\",\\n \\\"AVI\\\",\\n \\\"WMV\\\",\\n \\\"MOV\\\",\\\"QT\\\",\\n \\\"FLV\\\",\\\"SWF\\\",\\n \\\"F4V\\\",\\\"F4P\\\",\\\"F4A\\\",\\\"F4B\\\",\\n \\\"VCHD\\\",\\n \\\"RMVB\\\",\\\"RM\\\",\\n \\\"VOB\\\",\\n \\\"MKV\\\",\\n \\\"MTS\\\", \\\"M2TS\\\", \\\"TS\\\",\\n \\\"MNG\\\",\\n \\\"GIFV\\\",\\n \\\"GIF\\\",\\n \\\"DRC\\\",\\n \\\"XVID\\\",\\n \\\"VIDX\\\",\\n \\\"ASF\\\",\\n \\\"AMV\\\",\\n \\\"M2V\\\",\\n \\\"SVI\\\",\\n \\\"3GP\\\",\\n \\\"MXF\\\",\\n \\\"ROQ\\\",\\n \\\"NSV\\\",\\n \\\"3G2\\\",\\n ]\\n return filter_files_by_extension(files, video_extensions)\\n ...\",\n \"def movie_list(self):\\n return self._request_obj(self._urls[\\\"movie_list\\\"], key=\\\"genres\\\")\",\n \"def list_type_in_dir(path, extension):\\n path, extension = check_args(path, extension)\\n files = os.listdir(path)\\n file_list = [os.path.join(path, f)\\n for f in fnmatch.filter(files, '*' + extension)]\\n\\n return file_list\",\n \"def readPlayerImageFiles(self):\\n currentPath = os.path.dirname(os.path.abspath(__file__))\\n listOfFileNames=[]\\n for i in os.listdir(currentPath):\\n if re.match(\\\"player\\\\_\\\\d+\\\",i): #i.endswith(\\\".gif\\\")\\n listOfFileNames.append(currentPath+'/'+i)\\n return listOfFileNames\",\n \"def list_phonebooks(path=\\\".\\\"):\\n files = os.listdir(path)\\n for file in files:\\n if file.endswith(EXTENSION):\\n print file\",\n \"def getVideosPath(self):\\r\\n videoTypes = [\\r\\n ('MP4 files', '*.mp4'),\\r\\n ('3GP files', '*.3gp'),\\r\\n ('WMV files', '*.wmv'),\\r\\n ('FLV files', '*.flv'),\\r\\n ('AVI files', '*.avi'),\\r\\n ]\\r\\n global filenames\\r\\n filenames = askopenfilenames(title=\\\"Select video files\\\", multiple=True, )\",\n \"def get_all_videos(dir, extension='mp4'):\\n\\n list_video_fn = []\\n for dirpath, dirnames, filenames in os.walk(dir):\\n for filename in [f for f in filenames if f.endswith(extension)]:\\n fn = os.path.join(dirpath, filename)\\n list_video_fn.append(fn)\\n\\n return list_video_fn\",\n \"def MovieScan():\\r\\n for root, dirnames, filenames in os.walk(dlPath):\\r\\n for extend in movtypes:\\r\\n for filename in fnmatch.filter(filenames, extend):\\r\\n matches.append(os.path.join(root, filename))\\r\\n print(os.path.join(root, filename))\\r\\n shutil.move(os.path.join(root, filename), os.path.join(moviePath, filename))\\r\\n print color.GREEN + 'File succesfully moved!' + color.ENDC\\r\\n print 'Finished Scanning For Movies'\",\n \"def list_movies(category):\\n movies = get_movies(category)\\n listing = []\\n for movie in movies:\\n list_item = xbmcgui.ListItem(label=movie[0])\\n list_item.setArt({'thumb': movie[1],\\n 'icon': movie[1],\\n 'fanart': movie[1]})\\n list_item.setInfo('video', {'title': movie[0]})\\n if 'Next Page' in movie[0]:\\n url = '{0}?action=list_category&category={1}'.format(_url, movie[2])\\n else:\\n url = '{0}?action=list_movie&thumb={1}&movie={2}'.format(_url, movie[1], movie[2])\\n is_folder = True\\n listing.append((url, list_item, is_folder))\\n xbmcplugin.addDirectoryItems(_handle, listing, len(listing))\\n xbmcplugin.endOfDirectory(_handle)\",\n \"def listar_extension(dir_name, ext='.png'):\\n\\n list_ext = []\\n for root, dirs, files in os.walk(directorio):\\n for name in files:\\n if ext in name:\\n list_ext.append(name)\\n for name in dirs:\\n if ext in name:\\n list_ext.append(name)\\n\\n return list_ext\",\n \"def load_video_data(fpath):\\n videos = []\\n with open(fpath) as f:\\n d1 = json.load(f)['items']\\n videos += append_videos(d1)\\n return videos\",\n \"def getMediaFileList(path):\\n\\n fileTypes = (\\\"jpg\\\", \\\"mov\\\", \\\"mp4\\\")\\n fileList = []\\n for base_dir, dirs, files in os.walk(path):\\n fileList.extend([os.path.join(base_dir, f) for f in files if f.split(\\\".\\\")[1].lower() in fileTypes])\\n\\n # for the new canon camera, ther are some .Trash and trashinfo files, want to ignore them\\n fileList = [file for file in fileList if \\\"trash\\\" not in file and \\\"Trash\\\" not in file]\\n return fileList\",\n \"def load_movies_data(filename):\\n movies = []\\n with open(filename) as movies_file:\\n try:\\n data = json.load(movies_file)\\n except json.decoder.JSONDecodeError:\\n logging.critical(\\\"Cannot get movies data.\\\")\\n return movies\\n\\n for movie_data in data:\\n try:\\n movies.append(media.Movie(**movie_data))\\n except TypeError:\\n logging.warning(\\\"Cannot load a movie; skipping an item\\\")\\n\\n return movies\",\n \"def get_all_videos_in_directory(directory: str):\\n\\n all_files_and_folders = os.listdir(directory)\\n\\n only_videos = []\\n for file in all_files_and_folders:\\n if is_video(file):\\n only_videos.append(file)\\n ...\\n\\n return only_videos\",\n \"def top_ten_movies(path):\\n content = open(path, \\\"r\\\")\\n topten = []\\n for x in content:\\n topten.append(x) \\n return topten\",\n \"def getFilmTitles(checkFolder):\\n\\n files = [str(x) for x in Path(checkFolder).rglob(\\\"*\\\")]\\n libFilmFiles = list(map(os.path.basename,files)) # Remove the path\\n libFilmTitles = [os.path.splitext(x)[0] for x in libFilmFiles]\\n return libFilmTitles\",\n \"def test_extensions(self):\\n dummy_folder = TestOspaListDir.get_dummy_folder()\\n need_result = []\\n for i in range(1, 4):\\n need_result.append(os.path.join(dummy_folder, 'memes', 'meme monty python', 'meme{}.jpg'.format(i)))\\n need_result.append(os.path.join(dummy_folder, 'memes', 'meme1.jpg'))\\n need_result.append(os.path.join(dummy_folder, 'memes', 'meme2.png'))\\n need_result.append(os.path.join(dummy_folder, 'memes', 'meme4.jpg'))\\n need_result.append(os.path.join(dummy_folder, 'memes', 'meme4.png'))\\n\\n for i in ['antigravity.png',\\n 'egg.png',\\n 'holy_grenade.png',\\n 'spam.jpg',\\n ]:\\n need_result.append(os.path.join(dummy_folder, i))\\n\\n result = listdir(dummy_folder, full_path=True, only_files=True, walk=True, extensions=['jpg', 'png'])\\n self.assertEqual(sorted(result), sorted(need_result))\\n result = listdir(dummy_folder, full_path=True, only_files=True, walk=True, extensions=['.jpg', '.png'])\\n self.assertEqual(sorted(result), sorted(need_result))\\n result = listdir(dummy_folder, full_path=True, only_files=True, walk=True, extensions=['.JPG', 'png'])\\n self.assertEqual(sorted(result), sorted(need_result))\\n result = listdir(dummy_folder, full_path=True, only_files=True, walk=True, extensions=('.JPG', 'png'))\\n self.assertEqual(sorted(result), sorted(need_result))\\n result = listdir(dummy_folder, full_path=True, only_files=True, walk=True, extensions={'.JPG', 'png'})\\n self.assertEqual(sorted(result), sorted(need_result))\",\n \"def create_movie(file_path_list, movie_name_list, movie_path, file_type='png',\\n fps=1, movie_type='mp4', codec='mpeg4'):\\n for movie_name, file_path in zip(movie_name_list, file_path_list):\\n file_list = sorted(glob.glob(file_path + '*.' + file_type))\\n print(file_list)\\n\\n # Generate clip\\n clip = ImageSequenceClip(file_list, fps=fps)\\n # Write out clip\\n if not os.path.isdir(movie_path):\\n os.makedirs(movie_path)\\n clip.write_videofile(\\n movie_path +\\n movie_name +\\n '.' +\\n movie_type,\\n codec=codec)\\n clip.write_gif(movie_path + movie_name + '.gif')\\n\\n print('Created movie ' + movie_path + movie_name)\",\n \"def list_files(file, folder, extension = '*.evtx'):\\r\\n if file:\\r\\n return [file]\\r\\n elif folder:\\r\\n return [ y for x in os.walk(folder) for y in glob(os.path.join(x[0], extension))]\\r\\n else:\\r\\n return []\",\n \"def filelist(filepath: str, ext: str = None) -> list:\\n file_list = []\\n for path, _, files in os.walk(filepath):\\n for name in files:\\n _, extension = os.path.splitext(name)\\n if ext is None or extension == ext:\\n file_list.append(os.path.join(path, name))\\n\\n return file_list\",\n \"def list_videos(movie,thumb):\\n\\n videos = get_videos(movie)\\n listing = []\\n for video in videos:\\n list_item = xbmcgui.ListItem(label=video[0])\\n list_item.setArt({'thumb': thumb,\\n 'icon': thumb,\\n 'fanart': thumb})\\n list_item.setInfo('video', {'title': video[0]})\\n list_item.setProperty('IsPlayable', 'true')\\n url = '{0}?action=play&video={1}'.format(_url, video[1])\\n is_folder = False\\n listing.append((url, list_item, is_folder))\\n\\n xbmcplugin.addDirectoryItems(_handle, listing, len(listing))\\n xbmcplugin.endOfDirectory(_handle)\",\n \"def _get_movies(self):\\n\\n return self.data_file['movies']\",\n \"def grab_files(folder_path, ext='.h5', first4=None):\\r\\n folder_path=os.path.normpath(folder_path)\\r\\n if first4 in locals():\\r\\n # incorporate the excerpt of the filename\\r\\n dir_List=[f for f in os.scandir(folder_path) if f.is_file()==True and \\r\\n f.name[-len(ext):]==ext and f.name[:4]==first4] \\r\\n else:\\r\\n #do it without the excerpt\\r\\n dir_List=[f for f in os.scandir(folder_path) if f.is_file()==True and \\r\\n f.name[-len(ext):]==ext]\\r\\n \\r\\n return dir_List\",\n \"def get_videos_of_folder(folder):\\n\\n Settings.dev_print(\\\"getting videos of folder: {}\\\".format(folder.get_title()))\\n if not folder: return []\\n videos = []\\n files = []\\n valid_videos = [\\\".mp4\\\",\\\".mov\\\"]\\n for f in os.listdir(folder.get_path()):\\n ext = os.path.splitext(f)[1]\\n if ext.lower() not in valid_videos:\\n continue\\n file = File()\\n setattr(file, \\\"path\\\", os.path.join(folder.get_path(),f))\\n files.append(file)\\n Settings.maybe_print(\\\"video path: {}\\\".format(os.path.join(folder.get_path(),f)))\\n return files\",\n \"def get_files_suffix_list(suffixes, flist, Lshow=False, Ldir=False):\\n matched_files=[]\\n dirs=[]\\n files=[]\\n for fname in flist:\\n if os.path.isdir(fname):\\n dirs.append(fname)\\n else:\\n files.append(fname)\\n for suff in suffixes:\\n for fname in files:\\n #print(f\\\" {suff} in {fname} ?\\\")\\n if fname.endswith(suff):\\n matched_files.append(fname)\\n matched_files.extend(dirs) \\n return matched_files\",\n \"def read_files_to_list(fdir, expression='*.json'):\\n filelist = []\\n for file in glob.glob(path.join(fdir, expression)):\\n filelist.append(file)\\n return filelist\",\n \"def movies_filename(self):\\n pass\",\n \"def get_file_list() -> List[str]:\\n filenames = []\\n os.makedirs(\\\"sequence\\\", exist_ok=True)\\n for file in glob.glob(\\\"sequence/*.smp\\\"):\\n filenames.append(file.replace(\\\"sequence/\\\", \\\"\\\"))\\n return filenames\",\n \"def getMediaFiles(path):\\n fileList = getMediaFileList(path)\\n # dirList = getDirectoryList(path)\\n\\n # results = map(getMediaFiles, dirList)\\n\\n # for result in results:\\n # fileList = fileList + result\\n\\n return fileList\",\n \"def get_imlist2(path):\\n return [\\n os.path.join(path, f) for f in os.listdir(path) if f.endswith('.ppm')\\n ]\",\n \"def _filter_files(file_dir: Union[str, Path], is_viya4: Optional[bool] = False) -> list:\\n file_names = []\\n file_names.extend(sorted(Path(file_dir).glob(\\\"*.json\\\")))\\n if is_viya4:\\n file_names.extend(sorted(Path(file_dir).glob(\\\"score_*.py\\\")))\\n file_names.extend(sorted(Path(file_dir).glob(\\\"*.pickle\\\")))\\n # Include H2O.ai MOJO files\\n file_names.extend(sorted(Path(file_dir).glob(\\\"*.mojo\\\")))\\n if file_names:\\n return file_names\\n else:\\n raise FileNotFoundError(\\n \\\"No valid model files were found in the provided file directory.\\\"\\n )\",\n \"def find_files(extensions):\\n\\n return [fname for fname in os.listdir('.') if fname.endswith(extensions)]\",\n \"def filelisting(directory, suffix = 'tcx'):\\n files = []\\n for f in os.listdir(directory):\\n fullpath = os.path.join(directory, f)\\n if os.path.isfile(fullpath) and f.endswith(suffix):\\n files.append(fullpath)\\n return files\",\n \"def list_a_file_type(path, extension):\\n path, extension = check_args(path, extension)\\n file_list = [os.path.join(dirpath, f)\\n for dirpath, dirnames, files in os.walk(path)\\n for f in fnmatch.filter(files, '*' + extension)]\\n\\n return file_list\",\n \"def load_video_data(self):\\n self.file_videos = [\\n Video.from_file(path, self)\\n for path in self.video_dir.glob('*.json')\\n ]\",\n \"def get_music_files(pth: pathlib.Path) -> typing.List[mutagen.FileType]:\\n file_names = [os.path.join(pth, f) for f in os.listdir(pth)]\\n files = [mutagen.File(f) for f in file_names if os.path.isfile(f)]\\n return [f for f in files if f is not None]\",\n \"def get_files(start_str = \\\"sim_\\\"):\\n n = len(start_str)\\n file_list = [f for f in os.listdir(in_path) if f[0:n] == start_str]\\n return file_list\",\n \"def getMusic(self, path):\\n music =[]\\n files = [ f for f in listdir(path) if isfile(join(path,f))]\\n for f in files:\\n m = join(path,f)\\n #if not f.endswith('.mp3'):\\n # files.remove(f)\\n if f.endswith('.mp3'):\\n music.append(m)\\n return music\",\n \"def filter_paths(path):\\n return [\\\"{}/{}\\\".format(path, f) for f in os.listdir(path) if\\n f.endswith(FILE_EXTENSION_VM)]\",\n \"def list_of_medias(args, sourcedir, recursive):\\n files = list_of_files(sourcedir, recursive)\\n return [_ for _ in files if is_media_within_dates(_, args.dates)]\",\n \"def get_files(path, extension):\\n extension = listify(extension)\\n return [p for p in path.ls() if p.suffix in extension and \\\"(\\\" not in p.stem]\",\n \"def get_files_with_extension(self, extension=sys.argv[1]) -> list:\\n if extension == \\\"\\\":\\n raise EnvironmentError(\\\"No extension provided!\\\")\\n\\n result = []\\n for idx, file in enumerate(self.file_list):\\n if re.search(extension + \\\"$\\\", file):\\n result.append(file)\\n\\n if len(result) == 0:\\n raise Exception(\\\"No {} files found.\\\".format(extension))\\n\\n return result\",\n \"def gather_videos(files):\\r\\n # Because we are using a set, no duplicates will be present\\r\\n videos = set()\\r\\n for item in files:\\r\\n # Crawl subfolders\\r\\n if os.path.isdir(item):\\r\\n for root, _, filenames in os.walk(item):\\r\\n for filename in filenames:\\r\\n filepath = os.path.join(root, filename)\\r\\n # Check if its a video\\r\\n if YoutubeService.valid_video_file(filepath):\\r\\n videos.add(filepath)\\r\\n # If it exists it is a single file, check if its a video\\r\\n elif os.path.exists(item) and YoutubeService.valid_video_file(item):\\r\\n videos.add(item)\\r\\n return videos\",\n \"def listFiles(self):\\n current_month = NoaaCycle.last_month()\\n # 2do archive contain extra path: data/noaa/metar/2011-* ; better is 2011-*\\n dir_regex = os.path.join(self.download_dir, \\\"%s-*\\\" % current_month)\\n self.archive_name = os.path.join(self.download_dir, current_month)\\n return glob.glob(dir_regex)\",\n \"def test_get_filenames_by_ext():\\n tmpdir = os.path.join(tempfile.gettempdir(), \\\"jade-test-tmp87alkj8ew\\\")\\n os.makedirs(tmpdir, exist_ok=True)\\n\\n data = {\\\"A\\\": 1, \\\"B\\\": 2}\\n json_file = os.path.join(tmpdir, \\\"a.json\\\")\\n dump_data(data, json_file)\\n\\n toml_file = os.path.join(tmpdir, \\\"b.toml\\\")\\n dump_data(data, toml_file)\\n\\n filenames = get_filenames_by_ext(tmpdir, \\\".json\\\")\\n assert \\\"a.json\\\" in next(filenames)\\n\\n filenames = get_filenames_by_ext(tmpdir, \\\".toml\\\")\\n assert \\\"b.toml\\\" in next(filenames)\",\n \"def list_movie():\\n if not MOVIES:\\n print('No stored movies yet')\\n\\n for movie in MOVIES:\\n print(f\\\"{movie['name']} ({movie['year']}) - Director by '{movie['director']}'\\\")\",\n \"def get_maps(path: str, ext: str) -> list:\\n result = [\\n y for x in os.walk(path) for y in glob(os.path.join(x[0], \\\"*.{}\\\".format(ext)))\\n ]\\n\\n return result\",\n \"def get_files(path: str, extension: str = '.wav') -> List[Path]:\\n\\n return list(Path(path).expanduser().resolve().rglob(f'*{extension}'))\",\n \"def _findfile(self,path,label):\\n files=[];filenames=os.listdir(path)\\n for name in filenames:\\n if os.path.splitext(name)[0]==str(label):\\n files.append(name)\\n return files\",\n \"def create_file_list(path, extension='.png'):\\n file_list = []\\n for root, _, files in os.walk(path, topdown=False):\\n for name in files:\\n if name.endswith(extension):\\n full_name = os.path.join(root, name)\\n file_list.append(full_name)\\n\\n return file_list\",\n \"def get_file_extensions():\\n my_files_ext = []\\n for file in os.listdir(os.getcwd()):\\n if os.path.isfile(file):\\n file_info = os.path.splitext(file)\\n file_ext = file_info[1]\\n my_files_ext.append(file_ext)\\n return [file for file in my_files_ext]\",\n \"def with_path(path):\\n seen = set()\\n seen_add = seen.add\\n videos = []\\n all_videos = list(mythVideo.searchVideos(filename = path))\\n\\n for video in all_videos:\\n if video.season > 0:\\n video.label = video.title + \\\" - Season \\\" + str(video.season)\\n\\n if video.label not in seen and not seen_add(video.label):\\n video.url = \\\"/videos/\\\" + video.title + \\\"/season/\\\" + str(video.season)\\n videos.append(video)\\n\\n else:\\n video.label = video.title + \\\" - \\\" + video.subtitle\\n video.url = \\\"/videos/\\\" + video.title + \\\"/\\\" + video.hash\\n videos.append(video)\\n\\n if len(videos) == 1:\\n videos[0].pic = url_for('.video_image', title = title, hash = videos[0].hash)\\n videos[0].feplay = url_for('.video_feplay', title = title, hash = hash)\\n return render_template('recording.html', item = videos[0])\\n\\n videos = sorted(videos, key = lambda video: video.season)\\n return render_template('list.html', items = videos, page_title = title)\",\n \"def collect_files_with_extensions(self, extension: str) -> List[str]:\\n occurrences = []\\n for position in os.listdir(self.directory):\\n if os.path.isdir(position):\\n for file in os.listdir(position):\\n if os.path.isfile(os.path.join(position, file)) and file.endswith(\\n extension\\n ):\\n occurrences.append(os.path.join(self.directory, position, file))\\n return occurrences\",\n \"def get_movie_info_from_folder(folder):\\n if not os.path.exists(folder):\\n raise ValueError(\\\"folder does not exists\\\")\\n for file in os.listdir(folder):\\n filename = os.path.join(folder, file)\\n if os.path.isfile(filename):\\n e = ET.parse(filename).getroot()\\n for result in e[1]:\\n attributes = dict()\\n for bindings in result:\\n attributes[bindings.attrib['name']] = bindings[0].text\\n if len(attributes['title']) > 0:\\n yield Movie(**attributes)\",\n \"def list(self):\\n return [os.splitext(el)[0] for el in\\n os.listdir(str(self.model_dir))]\",\n \"def get_movies():\\n tree = get_tree()\\n movie_list = [movie.get(\\\"title\\\") for movie in tree.getroot().findall(\\\"movie\\\")]\\n return movie_list\",\n \"def listen_files_list(self, directory):\\r\\n files = [f for f in os.listdir(directory) if\\r\\n f[-len(self.fileExt):] == self.fileExt]\\r\\n return files\",\n \"def load_movies():\\n filepath = \\\"./seed_data/u.item\\\"\\n movies = open(filepath)\\n\\n for movie in movies:\\n movie = movie.rstrip().split('|')\\n title = movie[1][:-7]\\n title = title.decode(\\\"latin-1\\\")\\n if movie[2]:\\n date = datetime.strptime(movie[2], '%d-%b-%Y')\\n else:\\n date = None\\n db_movie = Movie(\\n movie_id = movie[0], title = title, \\n released_at = date, imdb_url = movie[4])\\n db.session.add(db_movie)\\n\\n db.session.commit()\",\n \"def list_directory(path):\\n files = []\\n for f in listdir(path):\\n if isfile(join(path, f)) and f.endswith('.mp3'):\\n files.append(f)\\n return files\",\n \"def txtfiles2pylist(mypath: str) -> list:\\n\\n import glob\\n filenames = glob.glob(f'{mypath}/*.txt')\\n res = []\\n for filename in filenames:\\n with open(filename, 'r', encoding='utf-8') as file:\\n data = file.read()\\n res.append(data)\\n return res\",\n \"def get_imlist(path):\\n\\treturn [os.path.join( path, f) for f in os.listdir(path) if f.endswith('.jpg')]\",\n \"def get_imlist(path):\\n return [os.path.join(path, f) for f in os.listdir(path) if f.endswith('.jpg')]\",\n \"def __init__(self, _format):\\n path = _format + os.sep + \\\"playlists\\\"\\n self.__playlists = []\\n for root, directory, files in os.walk(path):\\n for file in files:\\n if file.endswith(\\\".txt\\\"):\\n self.__playlists.append(file[:-4])\",\n \"def initFileList(self,extension):\\r\\n self.listExec.Clear()\\r\\n for fname in os.listdir(\\\"data\\\"):\\r\\n #print 'testing file ' , fname\\r\\n \\r\\n if extension in fname :\\r\\n #print fname\\r\\n self.listExec.Append(fname)\\r\\n self.Refresh()\",\n \"def get_imdb_list():\\n list_file = 'imdb.txt'\\n name_column = 26\\n f = open(list_file, 'r')\\n film_list = []\\n pos = 0\\n\\n for line in f:\\n pos += 1\\n words = line.split()\\n name = line[name_column:-1]\\n # could be problematic is there are brackets in the film name\\n year = name[name.find('(') + 1:name.find(')')]\\n name = name.replace('(' + year + ')', '')\\n film = {\\n 'pos': pos,\\n 'score': Decimal(words[2]),\\n 'name': name.strip(),\\n 'year': year\\n }\\n film_list.append(film)\\n f.close()\\n return film_list\",\n \"def create_list_menu(self):\\n films = []\\n try:\\n for root, dirs, files in os.walk(str(self.initial_directory)):\\n for file in files:\\n if file.endswith(('.mkv', '.avi', '.mp4')) and not file.endswith(('.sample.mkv', '.sample.avi', 'sample.mp4')):\\n films.append(os.path.join(root, file))\\n except TypeError:\\n raise(\\\"Error\\\")\\n films.sort(key=lambda s: s.lower().split('/')[-1])\\n [self.create_film_entry(film) for film in films]\\n self.menubar.add_cascade(label=\\\"All Films\\\", menu=self.list_menu)\",\n \"def standardize_file_names(source):\\n # Convert File Names into a List\\n video_list = os.listdir(source)\\n print(video_list)\\n \\n # Switch into the Directory and rename all files\\n os.chdir(source)\\n for i in range(len(video_list)):\\n os.rename(video_list[i], 'video'+ str(i) + '.MOV')\",\n \"def get_lst_images(file_path):\\n return [i for i in os.listdir(file_path) if i != '.DS_Store']\",\n \"def dir_search(ext, file_path='./'):\\n try:\\n return [file_path + \\\"/\\\" + file for file in os.listdir(file_path) if file.endswith(ext)]\\n except OSError as e:\\n logger.error(e)\\n return []\\n except Exception as e:\\n logger.error(e)\\n return []\",\n \"def _filenames(self, dir_or_file):\\n if os.path.isdir(dir_or_file):\\n return glob(os.path.join(dir_or_file, \\\"*.txt\\\"))\\n else:\\n return [dir_or_file]\",\n \"def load_movies(self, file_name):\\n\\n in_file = open('{}'.format(file_name), 'r')\\n for line in in_file:\\n line_str = line.strip().split(',')\\n # Create movie instance and convert year to an integer\\n movie = Movie(line_str[INDEX_OF_TITLE], int(line_str[INDEX_OF_YEAR]), line_str[INDEX_OF_CATEGORY],\\n True if line_str[INDEX_OF_STATUS] == WATCHED else False)\\n self.movies.append(movie)\\n in_file.close()\",\n \"def last_videos_recorded(self) -> list:\\n return sorted(glob.glob(VIDEOS_DIR), key=os.path.getmtime)[-20:]\",\n \"def get_filestream(data_dir: str, ext: str) -> Iterable[str]:\\n return listdir(data_dir) \\\\\\n | where(lambda p: p.endswith(ext)) \\\\\\n | select( lambda p: join(data_dir,p))\",\n \"def _findVideoFile(self, videofile):\\n for vf in self.vflist:\\n if vf.startswith(videofile + '.'):\\n videosource = os.path.join(self.vfdir, vf)\\n return videosource\",\n \"def get_oscars_best_picture_list():\\n list_file = 'oscar_best_picture_list.txt'\\n f = open(list_file, 'r')\\n film_list = []\\n\\n for line in f:\\n words = line.split('-')\\n film = {\\n 'year': words[0][:-1],\\n 'name': words[1][2:-2]\\n }\\n film_list.append(film)\\n f.close()\\n # Reverse as we want newest first not last\\n film_list.reverse()\\n return film_list\",\n \"def createFileList(my_dir, term):\\n \\n for subdir, dirs, files in os.walk(my_dir):\\n for file in files:\\n if re.search(re.escape(term), file):\\n result = os.path.join(subdir, file)\\n fileList.append(result)\\n return fileList\",\n \"def get_files_from_of_type(path: str, ext: str) -> List[str]:\\n files = []\\n for root, dirnames, filenames in os.walk(path):\\n for filename in fnmatch.filter(filenames, \\\"*.\\\" + str(ext)):\\n files.append(os.path.join(root, filename))\\n if not files:\\n logging.error(\\\"No language files found in folder: \\\" + str(os.sep.join([convert_vars.BASE_PATH, \\\"source\\\"])))\\n logging.debug(f\\\" --- found {len(files)} files of type {ext}. Showing first few:\\\\n* \\\" + str(\\\"\\\\n* \\\".join(files[:3])))\\n return files\",\n \"def list_files(directory, extension):\\n file_list = listdir(directory)\\n included_list = []\\n for f in file_list:\\n for ext in extension:\\n if f.endswith('.' + ext):\\n included_list.append(f)\\n break\\n return included_list\",\n \"def stat_subtitle(self, release_name, movie_dir):\\n ret = {}\\n for root_dir, child_folders, file_names in os.walk(movie_dir):\\n for file_name in file_names:\\n if not file_name.startswith(release_name):\\n continue\\n\\n subtitle_info = get_subtitle_info(file_name)\\n if not subtitle_info:\\n continue\\n\\n if 'lang' not in subtitle_info:\\n continue\\n\\n lang = subtitle_info['lang']\\n if lang not in ret:\\n ret[lang] = []\\n\\n ret[lang].append(file_name)\\n\\n # Sort result\\n for lang in ret:\\n ret[lang] = sorted(ret[lang])\\n\\n return ret\",\n \"def getlistofpossibletitles(fileitem,shows):\\n title = []\\n title.append(fileitem)\\n lookfor = fileitem.replace(\\\".\\\",\\\" \\\")\\n title.append(lookfor)\\n lookfor = fileitem.replace('-',\\\" \\\")\\n title.append(lookfor)\\n return title\",\n \"def _convert_to_movies(the_movie_db, raw_movies):\\n\\n movies = list()\\n for movie in raw_movies:\\n poster = \\\"\\\"\\n if 'poster_path' in movie:\\n poster = constants.POSTER_URL + movie['poster_path']\\n\\n success, movie_trailer_url = the_movie_db.get_movie_trailer(movie['id'])\\n if not success:\\n print \\\"something went wrong with movie: {}\\\".format(movie['id'])\\n\\n movies.append(\\n media.Movie(movie['title'], poster, movie_trailer_url)\\n )\\n\\n return movies\",\n \"def _collect_files(folders, extention='Default'):\\r\\n if isinstance(extention, str):\\r\\n if extention.lower() == 'default':\\r\\n extention = ['.*']\\r\\n else:\\r\\n extention = [extention]\\r\\n files = []\\r\\n for f in folders:\\r\\n for e in extention:\\r\\n files += glob(os.path.join(f, f'*{e}'))\\r\\n return files\",\n \"def getListOfFiles(directory, extension):\\n allFiles = [f for f in os.listdir(directory) if\\n os.path.isfile(os.path.join(directory, f)) and f.endswith(extension)]\\n return allFiles\",\n \"def list_all(train_dir):\\r\\n path = train_dir\\r\\n result = []\\r\\n for fn in os.listdir(path): #fn 表示的是文件名\\r\\n result.append(fn)\\r\\n return result\",\n \"def all_mpfile_names(mpfile_directory=MPFILE_DIRECTORY):\\n mpfile_names = [fname for fname in os.listdir(mpfile_directory)\\n if (fname.endswith(\\\".txt\\\")) and (fname.startswith(\\\"MP_\\\"))]\\n return mpfile_names\",\n \"def movie_path_list_fixture(tmpdir_factory):\\n path_list = []\\n\\n parent_tmpdir = tmpdir_factory.mktemp(\\\"movies_for_test\\\")\\n rng = np.random.default_rng(172312)\\n this_dir = tempfile.mkdtemp(dir=parent_tmpdir)\\n this_path = tempfile.mkstemp(dir=this_dir, suffix=\\\".h5\\\")[1]\\n with h5py.File(this_path, \\\"w\\\") as out_file:\\n out_file.create_dataset(\\\"data\\\", data=rng.random((12, 512, 512)))\\n\\n path_list.append(this_path)\\n\\n this_dir = tempfile.mkdtemp(dir=parent_tmpdir)\\n this_dir = pathlib.Path(this_dir) / \\\"processed\\\"\\n this_dir.mkdir()\\n this_path = this_dir / \\\"concat_31Hz_0.h5\\\"\\n with h5py.File(this_path, \\\"w\\\") as out_file:\\n out_file.create_dataset(\\\"data\\\", data=rng.random((12, 512, 512)))\\n path_list.append(str(this_path.resolve().absolute()))\\n\\n this_dir = tempfile.mkdtemp(dir=parent_tmpdir)\\n this_dir = pathlib.Path(this_dir) / \\\"processed\\\"\\n this_dir.mkdir()\\n this_path = this_dir / \\\"motion_corrected_video.h5\\\"\\n with h5py.File(this_path, \\\"w\\\") as out_file:\\n out_file.create_dataset(\\\"data\\\", data=rng.random((12, 512, 512)))\\n path_list.append(str(this_path.resolve().absolute()))\\n\\n yield path_list\\n\\n for this_path in path_list:\\n this_path = pathlib.Path(this_path)\\n if this_path.is_file():\\n this_path.unlink()\",\n \"def get_filepaths(extract_dir):\\n\\n index = []\\n labels = []\\n _extract_dir = os.path.join(extract_dir, 'UCF-101')\\n for folder in os.listdir(_extract_dir):\\n labels.append(folder)\\n folderpath = os.path.join(_extract_dir, folder)\\n\\n if not os.path.isdir(folderpath):\\n continue\\n\\n for filename in os.listdir(folderpath):\\n if 'avi' not in filename:\\n continue\\n\\n if filename[0] == '.':\\n continue\\n\\n filepath = os.path.join(folderpath, filename)\\n\\n if os.path.exists(filepath):\\n index.append(filepath)\\n else:\\n print(filepath)\\n return index, labels\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.77624446","0.69705206","0.6920418","0.65718144","0.65128","0.64938384","0.6462537","0.6437294","0.6373601","0.63549864","0.6350856","0.6319466","0.629446","0.6210759","0.6183799","0.61389726","0.6127222","0.61024976","0.6081276","0.60760933","0.607265","0.60622543","0.60118693","0.600817","0.599676","0.5989141","0.59670407","0.59472877","0.5925699","0.5922714","0.59159297","0.5898291","0.58933574","0.5889048","0.5853606","0.5841529","0.58306974","0.58195585","0.5819072","0.57935804","0.5787465","0.57755613","0.5762862","0.57565665","0.5751979","0.5751938","0.57467574","0.5736935","0.5713704","0.5711788","0.5709007","0.5690846","0.56849295","0.5675814","0.5672312","0.5672238","0.56371295","0.56351966","0.56337583","0.56322914","0.56304544","0.5628825","0.562042","0.56135064","0.56131077","0.56123114","0.5606408","0.56049234","0.5598663","0.559145","0.5589443","0.5589294","0.5587603","0.5582349","0.5576637","0.55671","0.55514324","0.5537051","0.55348957","0.55321205","0.5531455","0.5530618","0.55304646","0.55246294","0.5522009","0.55206704","0.55136335","0.5508912","0.5508184","0.54884326","0.54802054","0.5472696","0.547091","0.5468105","0.546066","0.5442297","0.54408485","0.5437502","0.54224944","0.5417596"],"string":"[\n \"0.77624446\",\n \"0.69705206\",\n \"0.6920418\",\n \"0.65718144\",\n \"0.65128\",\n \"0.64938384\",\n \"0.6462537\",\n \"0.6437294\",\n \"0.6373601\",\n \"0.63549864\",\n \"0.6350856\",\n \"0.6319466\",\n \"0.629446\",\n \"0.6210759\",\n \"0.6183799\",\n \"0.61389726\",\n \"0.6127222\",\n \"0.61024976\",\n \"0.6081276\",\n \"0.60760933\",\n \"0.607265\",\n \"0.60622543\",\n \"0.60118693\",\n \"0.600817\",\n \"0.599676\",\n \"0.5989141\",\n \"0.59670407\",\n \"0.59472877\",\n \"0.5925699\",\n \"0.5922714\",\n \"0.59159297\",\n \"0.5898291\",\n \"0.58933574\",\n \"0.5889048\",\n \"0.5853606\",\n \"0.5841529\",\n \"0.58306974\",\n \"0.58195585\",\n \"0.5819072\",\n \"0.57935804\",\n \"0.5787465\",\n \"0.57755613\",\n \"0.5762862\",\n \"0.57565665\",\n \"0.5751979\",\n \"0.5751938\",\n \"0.57467574\",\n \"0.5736935\",\n \"0.5713704\",\n \"0.5711788\",\n \"0.5709007\",\n \"0.5690846\",\n \"0.56849295\",\n \"0.5675814\",\n \"0.5672312\",\n \"0.5672238\",\n \"0.56371295\",\n \"0.56351966\",\n \"0.56337583\",\n \"0.56322914\",\n \"0.56304544\",\n \"0.5628825\",\n \"0.562042\",\n \"0.56135064\",\n \"0.56131077\",\n \"0.56123114\",\n \"0.5606408\",\n \"0.56049234\",\n \"0.5598663\",\n \"0.559145\",\n \"0.5589443\",\n \"0.5589294\",\n \"0.5587603\",\n \"0.5582349\",\n \"0.5576637\",\n \"0.55671\",\n \"0.55514324\",\n \"0.5537051\",\n \"0.55348957\",\n \"0.55321205\",\n \"0.5531455\",\n \"0.5530618\",\n \"0.55304646\",\n \"0.55246294\",\n \"0.5522009\",\n \"0.55206704\",\n \"0.55136335\",\n \"0.5508912\",\n \"0.5508184\",\n \"0.54884326\",\n \"0.54802054\",\n \"0.5472696\",\n \"0.547091\",\n \"0.5468105\",\n \"0.546066\",\n \"0.5442297\",\n \"0.54408485\",\n \"0.5437502\",\n \"0.54224944\",\n \"0.5417596\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7945257"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":92985,"cells":{"query":{"kind":"string","value":"Function returns structure (file_path, {guesseFileData})"},"document":{"kind":"string","value":"def subtitlePath_and_subtitleFileData(self,file_path_list):\n subtile_file_data = [] \n for x in file_path_list:\n subtile_file_data.append((x, self.guessFileData(x)))\n return subtile_file_data"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_file_data(filename):","def raw_file_structure(self):\n return None","def get_data(found_file, created_file):\n\n try:\n fh_f = fits.open(found_file)\n print('Found file has: ', fh_f.info())\n except Exception:\n print(' FATAL ERROR: Unable to open found file ', found_file)\n\n try:\n fh_c = fits.open(created_file)\n print('Created file has: ', fh_c.info())\n except Exception:\n print(' FATAL ERROR: Unable to open created file ', created_file)\n\n try:\n data_f = fh_f['SCI'].data\n except Exception:\n print(' FATAL ERROR: data for found data was expected in SCI extension')\n\n try:\n data_c = fh_c['SCI'].data\n except Exception:\n try:\n data_c = fh_c[0].data\n except Exception:\n print(' FATAL ERROR: created data expected in either SCI or 0 extensions')\n\n return fh_f, fh_c, data_f, data_c","def extract_data(file_name):\r\n input_file_name = file_name\r\n \r\n def sort_data(input_file): \r\n \"\"\"This function extraxts the row data from the imput file\"\"\" \r\n with open(input_file,\"r\") as input_file: \r\n data = input_file.readlines() \r\n row_data = [] \r\n for line in data: \r\n row_data.append(line.split(', ')) \r\n return row_data \r\n \r\n data = sort_data(input_file_name)\r\n \r\n start_vertex = (float(data[0][0].split(' ')[0]),float(data[0][0].split(' ')[1]))\r\n end_vertex = (float(data[1][0].split(' ')[0]),float(data[1][0].split(' ')[1]))\r\n \r\n obstacles = {}\r\n for i in range(2, len(data)):\r\n lista = []\r\n for j in range(len(data[i])):\r\n lista.append( (float(data[i][j].split(' ')[0]),float(data[i][j].split(' ')[1])) )\r\n obstacles[i-1] = lista\r\n \r\n return start_vertex,end_vertex, obstacles","def get_data(filename):\n df = gpd.read_file(filename, index=\"OBJECTID\")\n # Sort along the length column, which orders the points from top\n # to bottom\n fplencol = [x for x in df.columns if x.startswith(\"fpLen\")][0]\n df = df.sort_values(fplencol, ascending=True)\n df = run_checks(df)\n snapdf = gpd.read_file(\n filename.replace(\"smpldef3m\", \"snaps3m\"), index=\"OBJECTID\"\n )\n # Compute full rotation string\n # OK, be careful here. Presently, the 8 char field covers\n # 2010 thru 2017, so we rotate to cover the first and last years\n # 2007 2011[1]\n # 2008 2010[0]\n # 2009 2011[1]\n # 2018 2016[6]\n # 2019 2017[7]\n # 2020 2018[6]\n s = df[\"CropRotatn_CY_2017\"]\n df[\"landuse\"] = (\n s.str[1]\n + s.str[0]\n + s.str[1]\n + s\n + s.str[6]\n + s.str[7]\n + s.str[6]\n + s.str[7]\n )\n s = df[\"Management_CY_2017\"]\n df[\"management\"] = (\n s.str[1]\n + s.str[0]\n + s.str[1]\n + s\n + s.str[6]\n + s.str[7]\n + s.str[6]\n + s.str[7]\n )\n return df, snapdf","def get_gml_data(file_path):\n\n bbox = (2.34592e7,100+6.704e6,2.34603e7,700+6.704e6)\n return gpd.read_file(file_path, bbox=bbox)","def get_file(self) -> tuple:\r\n hash_md5 = hashlib.md5()\r\n with open(self.yara_base_file, \"rb\") as f:\r\n file_map = f.read()\r\n get_file_dict = get_matches(self, file_map)\r\n hash_md5.update(file_map)\r\n return hash_md5.hexdigest(), get_file_dict","def get_content(self, file_path: str) -> Tuple[defaultdict, str]:\n tags = self.__metadata__(file_path)\n html = self.__html__(tags)\n tags[\"file_path\"] = f\"images/gallery/{file_path.split(os.path.sep)[-1]}\"\n self.image_paths.append(file_path)\n return tags, html","def loadBattleData(league):\n path = os.path.dirname(os.path.realpath(__file__))\n fString = None\n try:\n idx = LEAGUERANKS.index(league)\n fString = path+RANKSTOWINLOSEFILES[idx]\n except:\n #No file associated with the league.\n return None, None\n\n try:\n with open(fString, \"r+\") as f:\n battleData = json.loads(f.readline())\n except Exception as e:\n print(e)\n return None, None\n \n fString = path+WINHTMLFILES[idx]\n\n try:\n with open(fString, \"r+\") as f:\n htmlData = json.loads(f.readline())\n return battleData, htmlData\n except:\n return battleData, None","def existing_village_file(kovetz):\n try:\n cat77 = nbt.NBTFile(kovetz)\n except IOError:\n raise Exception(\"Hmm. Unfortunately, the file requested does not exist :(\")\n tick4 = cat77['data']['Tick'].value\n return cat77, tick4","def get_prep(file_name):\n\n headers = {\n \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:60.0) Gecko/20100101 Firefox/60.0\"}\n\n url = \"https://rp18.ine.mx/assets/JSON/PRESIDENTE/NACIONAL/Presidente_NACIONAL.json\"\n\n with requests.get(url, headers=headers) as response:\n\n # Save a copy for future analysis.\n with open(\"./raw_data/{}.json\".format(file_name), \"w\", encoding=\"utf-8\") as temp_file:\n temp_file.write(response.text)\n\n candidates = list()\n percentages = list()\n votes = list()\n colors = list()\n\n json_data = response.json()\n\n for item in json_data[\"votosCandidatoPartidoCoalicion\"]:\n\n name = item[\"nombreCandidatoPropietario\"]\n\n if item[\"siglasPartido\"] == \"CNR\":\n name = \"Candidatos No Registrados\"\n\n if item[\"siglasPartido\"] == \"VN\":\n name = \"Nulos\"\n\n color = \"#{}\".format(item[\"colorPartido\"])\n colors.append(color)\n\n candidates.append(name)\n percentages.append(float(item[\"porcentaje\"]))\n votes.append(int(item[\"total\"]))\n\n return dict({\"candidates\": candidates, \"percentages\": percentages,\n \"votes\": votes, \"colors\": colors, \"totalVotos\": json_data[\"totalVotos\"],\n \"actasCapturadas\": json_data[\"actasCapturadas\"][\"porcentaje\"]})","def metadata_obj(filelike):\n\tif test_hachoir_extension(filelike.name):\n\t\tmetadata = metadata_for_filelike(filelike)\n\t\tif metadata:\n\t\t\tdata = dict([\n\t\t\t\t(data.key, data.values[0].value)\n\t\t\t\tfor data in metadata\n\t\t\t\tif data.values\n\t\t\t\t])\n\t\telse:\n\t\t\tdata=None\n\telif test_3D_extension(filelike.name):# 3D not in the extention \n\t\tdata = {'mime_type':'model'}\n\telse:\n\t\tdata = None\n\t\t\n\treturn data","def insert_good_data():\n get_file_reply(files[0][0], files[0][1])\n get_file_reply(files[1][0], files[1][1])","def read_files():\n with open(\"CvixLerC9.loc\") as loc, open(\"CvixLerC9.qua\") as qua:\n qua_file = (qua.read().split('\\n'))\n qua_file = qua_file[8:-1]\n new_qua = []\n for q in qua_file:\n new_qua.append(q.split('\\t')) # [['1', '1.279502474'], ['3', '0.303712231']....]\n\n new_loc = {}\n header = ''\n read = False\n for i in loc:\n i = i.replace(\"\\n\", '')\n if read:\n for j in i:\n if \" \" != j:\n if header in new_loc.keys():\n new_loc[header].append(j)\n else:\n new_loc[header] = [j]\n if \"(a,b)\" in i:\n header = i\n read = True\n else:\n read = False\n\n elif read:\n for j in i:\n if \" \" != j:\n if header in new_loc.keys():\n new_loc[header].append(j)\n else:\n new_loc[header] = [j]\n\n return new_loc, new_qua","def get_record_from_file(file_path, keys_to_use):\n # Read these files 1 by 1 into JSON objects, put them into a tuple\n with open(file_path) as artwork_file:\n content = json.load(artwork_file)\n \n # Create an empty list, & for every key in the list, we extract the data & append to the record list,\n # then return the data in tuple form\n record = []\n for field in keys_to_use:\n record.append(content[field])\n \n return tuple(record)","def obtain_pocket_data(dyn_id, traj_list) -> tuple:\n\n THRESHOLD_DRUGGABILITY = 200\n\n root = settings.MEDIA_ROOT\n pock_path = os.path.join(root,\"Precomputed/MDpocket\")\n # 3 level dictionary with: trajectory: pocketID: descriptors\n pockets = {}\n # 3 level dictionary with: trajectory: pocketID: path_to_coordinates_file.pdb\n traj_pockID_coordfile = {}\n # dictionary with: trajectory: path_to_isovalue_file.dx\n traj_isovalueFile = {}\n\n for mytraj in traj_list:\n\n try:\n # DEFINING PATHS\n traj_id = mytraj[2]\n traj_name = mytraj[1] \n\n traj_pock_path = os.path.join(pock_path,\"%s_mdpocket\"%(traj_name))\n pockets_coords_path = os.path.join(traj_pock_path, \"DBSCANclustering_coordinates_pdb_%s\"%(traj_name))\n pockets_json_txt = \"Final_OUTPUT_%s\"%(traj_name)\n path_json_txt = os.path.join(traj_pock_path, pockets_json_txt)\n\n # ISOVALUE DICTIONARY\n isovalue = os.path.join(traj_pock_path,\"mdpocket/mdpout_freq.dx\")\n traj_isovalueFile[traj_name] = isovalue\n\n # COORDINATE FILE DICTIONARY\n f = open(path_json_txt)\n pockID_coordfile = {}\n if os.path.isdir(pockets_coords_path):\n for file in os.listdir(pockets_coords_path):\n pocketid = int(file.split(\"_\")[0])\n pockID_coordfile[pocketid] = file\n traj_pockID_coordfile[traj_name] = pockID_coordfile\n\n # DESCRIPTORS DICTIONARY\n pocket_data = json.load(f)\n\n # Obtaining % druggability using volumes\n for pocket_dict in pocket_data[\"data\"]:\n n_above_threshold = len([ v for v in pocket_dict[\"volumes\"] if v >= THRESHOLD_DRUGGABILITY ])\n n_total = len(pocket_dict[\"volumes\"])\n pocket_dict[\"perc_druggability\"] = round( (n_above_threshold / n_total) * 100)\n\n # DESCRIPTORS DICTIONARY\n trajectory_pockData = {}\n for descriptors in pocket_data['data']:\n for key, value in descriptors.items():\n\n trajectory_pockData[descriptors['name']] = descriptors\n pockets[traj_id] = pocket_data\n\n except FileNotFoundError:\n print(\"[*] INFO - POCKET DATA: Pockets data not available for trajectory ID: \" + str(traj_id))\n\n return(pockets, traj_pockID_coordfile, traj_isovalueFile)","def prepare_misc_data(self):\n if 'misc_input_files' in self.man:\n data = self.man['misc_input_files']\n else:\n return None\n\n data_new_format = {}\n for item in data:\n token = item['token']\n if not token in data_new_format:\n data_new_format[token] = []\n data_new_format[token].append(item['file'])\n return data_new_format","def extract_data(file_name=default_file_name):\n fille = abs_path(file_name)\n try:\n jfile = open(fille)\n except FileNotFoundError:\n create_file(fille)\n jfile = open(fille)\n data = json.load(jfile)\n if(not 'Students' in data.keys()):\n create_file(fille)\n jfile = open(fille)\n data = json.load(jfile)\n return data","def get_pocket_pdb_files(request, pocket_data) -> dict:\n\n # Unpack parameters\n pockets, traj_pockID_coordfile, traj_isovalueFile = pocket_data\n traj_name = request.POST.get(\"traj_name\")\n pocketid_and_color_list = json.loads(request.POST.get(\"pocketid_and_color_list\"))\n # Obtain each pocket's PDB file\n pocket_pdbs = {}\n for pocketID, color in map(lambda x: (x[\"id\"], x[\"color\"]), pocketid_and_color_list):\n pocket_pdb_file = traj_pockID_coordfile[traj_name][str(pocketID)]\n pocket_pdbs[pocketID] = (pocket_pdb_file, color)\n\n return pocket_pdbs","def handle_uploaded_file(uploaded_file, duck_id, duck_name, comments):\n title = 'Duck #' + str(duck_id) + ' (' + duck_name + ')'\n tags = \"duckiehunt\"\n\n file_path = write_upload_to_file(uploaded_file, settings.UPLOAD_PATH)\n photo_info = upload_to_flickr(file_path, title, comments, settings.FLICKR_PHOTO_IS_PUBLIC, tags)\n return photo_info","def read_gaf_out(go_path):\n out = io.makedeephash()\n header = []\n temp = {}\n for line in open(go_path, mode=\"r\"):\n line = line.rstrip(\"\\n\")\n if line.startswith(str(\"ID\") + \"\\t\"):\n header = re.split(r\"\\t+\", line)\n else:\n things = re.split(r\"\\t+\", line)\n temp = dict(zip(header, things))\n if len(temp.keys()) > 0:\n pr = str.upper(temp[\"GN\"])\n for k in temp.keys():\n # if the key is the same\n if out[pr][k] and k != \"ID\" or \"GN\":\n out[pr][k] = \";\".join([str(out[pr][k]), temp[k]])\n elif k != \"ID\" or \"GN\":\n out[pr][k] = temp[k]\n return out","def read_grp(fname):\n global DAYS\n uint_types = [DAYS,\n 'Current crop type', \n 'Current residue on ground type', \n 'Previous residue on ground type', \n 'Old residue on ground type', \n 'Current dead root type', \n 'Previous dead root type', \n 'Old dead root type']\n\n meta = {}\n data = None\n header = []\n\n meta['fname'] = fname\n meta['id'] = ''.join([L for L in fname if L in '0123456789'])\n \n fid = open(fname, 'rb')\n for i, line in enumerate(fid.readlines()):\n line_as_list = line.strip().split()\n\n if len(line_as_list) == 0:\n continue\n\n elif line_as_list[0][0] == '#':\n continue\n\n elif line_as_list[0] == 'int':\n try:\n meta[line[1]] = int(line[2])\n except:\n pass\n \n elif line_as_list[0] == 'float':\n try:\n meta[line[1]] = float(line[2])\n except:\n pass\n\n elif line_as_list[0] == 'char':\n continue\n\n elif line_as_list[0][0] == '{':\n cname = line.strip()[1:-1].replace(r'kg/m', r'kg*m**-1') \\\n .replace(r'kg/m**2', r'kg*m**-2') \\\n .replace(r'kg/m**3', r'kg*m**-3') \\\n .replace(r'kg/m**4', r'kg*m**-4') \\\n .replace(r'mm/hr', r'mm*hr**-1') \\\n .replace(r'mm/h', r'mm*hr**-1') \\\n .replace(r'm/day', r'm*day**-1') \\\n .replace(r'g/cc', r'g*cc**-1') \\\n .replace(r'kg-s/m**4', r'kg-s*m**-4') \\\n .replace(r's/m', r's*m**-1') \\\n .replace(r'Irrigation_volume_supplied/unit_area',\n r'Irrigation_volume_supplied*unit_area**-1')\n header.append(cname)\n\n else:\n if len(header) == len(line_as_list):\n \n # if we are here and data == None we need to initialize the data dictionary\n if data == None:\n data = {}\n for cname in header:\n typecode = ('f', 'h')[any([cname==s for s in uint_types])]\n data[cname] = array.array(typecode)\n\n for (cname, string) in zip(header, line_as_list):\n if any([cname==s for s in uint_types]):\n value = int(string)\n else:\n value = float(string)\n\n if cname == DAYS:\n\n if value in set(data[DAYS]):\n break\n\n data[cname].append(value)\n\n else:\n raise Exception('Failed to parse line %i, unexpected number of columns.'%(i+1))\n \n fid.close()\n\n # pack the table data into numpy arrays\n for (cname, v) in data.items():\n dtype = (np.float32, np.int16)[any([cname==s for s in uint_types])]\n data[cname] = np.array(v, dtype=dtype)\n\n return (meta, data)","def parse_cluedata(input_path: str):\n\n\twith open(input_path, 'r') as clue_backup:\n\t\tjson_structure = json.loads(clue_backup.read())\n\n\tassert 'data' in json_structure, \".cluedata file does not have the expected structure\"\n\n\treturn json_structure","def get_info(frame_or_sketch_or_vid_path):\n if \".mp4\" not in frame_or_sketch_or_vid_path:\n # invalid file path ()\n # TODO: allow other video extensions\n return None\n\n ret_dict = {}\n ret_dict[\"path\"] = frame_or_sketch_or_vid_path\n ret_dict[\"file_name\"] = utils.get_file_name(frame_or_sketch_or_vid_path)\n ret_dict[\"file_ext\"] = utils.get_file_ext(frame_or_sketch_or_vid_path)\n\n # find video file name = video_id\n file_dir_last = utils.get_nth_parentdir(frame_or_sketch_or_vid_path)\n\n # file_dir_full = utils.get_file_path(frame_or_sketch_or_vid_path)\n # file_name = utils.get_full_file_name(frame_or_sketch_or_vid_path)\n\n video_id = f\"{file_dir_last.split('.mp4_')[0]}.mp4\"\n start_end_time = file_dir_last.split(\".mp4_\")[1]\n start_end_time_parts = start_end_time.split(\"_\")\n\n # OLD\n # tmp = frame_or_sketch_or_vid_path.rsplit(\"video_\")[1].replace(\".mp4\", \"\")\n # tmp_parts = tmp.split(\"/\")[0].split(\"_\") # remove frame part if existent\n # ret_dict[\"video_id\"] = tmp_parts[0]\n # ret_dict[\"start_time\"] = float(tmp_parts[1])\n # ret_dict[\"end_time\"] = ret_dict[\"start_time\"]\n\n ret_dict[\"video_id\"] = video_id\n ret_dict[\"start_time\"] = float(start_end_time_parts[0])\n if len(start_end_time_parts) > 1:\n ret_dict[\"end_time\"] = float(start_end_time_parts[1])\n\n if ret_dict[\"file_ext\"] == \".jpg\":\n ret_dict[\"frame\"] = int(ret_dict[\"file_name\"].split(\"_\")[1])\n elif ret_dict[\"file_ext\"] == \".json\":\n ret_dict[\"frame\"] = get_sketch_frame(ret_dict[\"path\"])\n else:\n ret_dict[\"fps\"] = get_fps(ret_dict[\"path\"])\n ret_dict[\"start_frame\"] = time_to_frame(ret_dict[\"start_time\"], ret_dict[\"fps\"])\n ret_dict[\"end_frame\"] = time_to_frame(ret_dict[\"end_time\"], ret_dict[\"fps\"])\n return ret_dict","def forge_files(self) -> Dict[str, BaseForge]:\n\t\treturn self._forge_files","def get_data_ge(logger, file):\n fp = open(file, 'rb')\n offset = 8192\n\n fp.seek(18)\n size, nframes = st.unpack('<ih',fp.read(6))\n if size != 2048:\n logger.error('GE image size unexpected: '+str(size))\n return None, 0, 0\n\n fsize = os.stat(str(fp).split(\"'\")[1]).st_size\n nframes_calc = (fsize - offset)/(2*size**2)\n\n if nframes != nframes_calc:\n logger.error('GE number frames unexpected: '+str(nframes))\n return None, 0, 0\n\n pos = offset\n fp.seek(pos)\n\n return fp, int(nframes_calc), size*size","def get_file_data(self):\n self.switch_row(self.PATTERN_INFO_ROW)\n\n # get background image file path\n if self.row[0] != 'No image':\n # set path to background image, and get/set screen size\n self.bg_img_path = self.row[self.BG_IMAGE_INDEX]\n self.screen_width = int(self.row[self.WIDTH_INDEX])\n self.screen_height = int(self.row[self.HEIGHT_INDEX])\n self.SCREEN_SIZE = self.screen_width, self.screen_height\n self.bg = True\n \n # get number of landmarks\n self.num_lndmrks = int(self.row[self.LNDMRK_NUM_INDEX])\n\n # get starting row number for mpo path data\n self.data_start_row = self.num_lndmrks + 1\n self.tot_data_rows = self.tot_rows - self.data_start_row\n self.data_row_num = self.data_start_row","def read_gif(self, filename):\n blocks = {}\n with open(os.path.join(self.template_dir, filename), 'rb') as gif_fd:\n blocks['header'] = gif_fd.read(6)\n assert blocks['header'] in (b'GIF87a', b'GIF89a')\n blocks['lcd'] = gif_fd.read(7) # logical screen descriptor\n assert blocks['lcd'].endswith(b'\\xe3\\x10\\x00') # gct of 16 colours\n blocks['gct'] = gif_fd.read(16 * 3) # global colour table\n blocks['img_descriptor'] = gif_fd.read(10) # image descriptor\n assert blocks['img_descriptor'][0] == 0x2c\n assert blocks['img_descriptor'][9] == 0\n # img data\n blocks['img_data'] = gif_fd.read(1) # LZW min code size\n while True: # img data sub-blocks\n blocks['img_data'] += gif_fd.read(1) # sub-block data size\n if blocks['img_data'][-1] == 0:\n break # final sub-block (size 0)\n blocks['img_data'] += gif_fd.read(blocks['img_data'][-1])\n assert gif_fd.read(1) == b'\\x3b' # trailer\n return blocks","def file_to_dictionary():\n\n return;","def get_uploaded_struct(self):\n parser = PDBParser()\n structure = parser.get_structure('STRUCT_OBJ',\n os.path.join(self.struct_dir, self.struct_name))\n return structure","def parse_files(usage: str, full_time: str, part_time: str, semester: str, total_courses: int) -> dict:\n one = filter_for_semester(open(usage, 'r').readlines(), semester)\n two = get_rows_with_usage(one)\n usage_file = remove_duplicate_crn(two)\n no_dup_r = remove_duplicate_royal(two)\n full_time_file = open(full_time, 'r').readlines()\n full_r = list()\n part_r = list()\n for x in full_time_file:\n y = x.split(DELIMITER)\n full_r.append(y[FAC_ROYAL])\n part_time_file = open(part_time, 'r').readlines()\n for x in part_time_file:\n y = x.split(DELIMITER)\n part_r.append(y[FAC_ROYAL])\n full = list()\n part = list()\n staff = list()\n for x in range(len(part_r)):\n part_r[x] = part_r[x].strip(\"\\\"\")\n for x in range(len(full_r)):\n full_r[x] = full_r[x].strip(\"\\\"\")\n for x in no_dup_r:\n y = x.split(DELIMITER)\n if y[USAGE_ROYAL] in full_r:\n full.append(y)\n elif y[USAGE_ROYAL] in part_r:\n part.append(y)\n else:\n staff.append(y)\n return {'semester_no_dup_crn': usage_file,\n 'semester_no_dup_r': no_dup_r,\n 'semester': two,\n 'full_time': full,\n 'len_full': len(full_time_file),\n 'part_time': part,\n 'len_part': len(part_time_file),\n 'staff': staff,\n 'total_courses': total_courses}","def prepare_feature(ground_truth, file_name):\n base_file_name = os.path.basename(file_name)\n gtp = GroundtruthReader(ground_truth)\n from_ground_truth = gtp.lookup_filename(base_file_name)\n image = create_image(file_name)\n if image is not None:\n image_feature = image_to_array(image)\n return {'image_feature': image_feature, 'labels': from_ground_truth}\n else:\n return None","def get_file_chunks(file, model, workspace, header, user):\n uri = (\"https://api.anaplan.com/1/3/workspaces/{}/models/{}/\"\n \"files/{}/chunks/\").format(workspace, model, file)\n response = requests.get(uri, headers = header)\n return json.loads(response.text.encode(\"utf-8\"))","def _get_file_data_object(self, file_path, spec_header):\n logger.DLOG(\"Creating FVaRFileData object from file '%s'\", file_path)\n return acm.Risk().CreateScenarioFileData(file_path,\n spec_header.DelimiterChar(), spec_header.CommentChar())","def readSurfaceGeo(b18path):\n if not os.path.isfile(b18path):\n print(\"b18 building file not found! Please check!\")\n pass\n else:\n b18file = open(b18path,\"r\")\n b18data = b18file.readlines()\n srfGeoBlock = getDataParagraph(\"_EXTENSION_BuildingGeometry_START_\", \"_EXTENSION_BuildingGeometry_END_\", b18data)\n #now get vertex's coordinate xyz\n vertexdict = dict() #{vertexID:[x,y,z]}\n srfbasicinfo = dict() #{surfaceID:[vertexID]}\n srfInfo = dict() #{surfaceID:[vertices coordinate]}\n for line in srfGeoBlock:\n dline = line.split()\n if \"vertex\" in dline:\n vertexdict[int(dline[1])] = [float(xyz) for xyz in dline[2:]] #{vertexID:[x,y,z]}\n if \"wall\" in dline or \"window\" in dline or \"floor\" in dline or \"ceiling\" in dline or \"roof\" in dline:\n srfbasicinfo[int(dline[1])] = [[int(nrID) for nrID in dline[2:]],dline[0]] #{surfaceID:[[vertexID],construction]}\n #print srfbasicinfo[int(dline[1])]\n for key in srfbasicinfo.keys():\n srfInfo[key] = []\n for vertices in srfbasicinfo[key][0]:\n srfInfo[key].append(vertexdict[vertices])\n b18file.close()\n return srfInfo,vertexdict,srfbasicinfo\n #actually only need srfInfo\n #just getting everything out for now, incase will need to use those","def extract_from_game(game_path):\n with open(game_path) as sgf_file:\n game_data = sgf_file.read().encode('utf-8')\n\n try:\n g = sgf.Sgf_game.from_bytes(game_data)\n _, moves = sgf_moves.get_setup_and_moves(g)\n except BaseException:\n print(\"bad file: \", game_path)\n return Counter(), {}\n\n return (extract_corners(moves), 1 if g.get_winner().lower() == 'b' else 0)","def parse_file(self, path, max_resolution, threshold, proteins={}):\n\n \"\"\"\n create regex pattern here so it is not done repeatedly while parsing file\n\n groups:\n 0 - Protein ID\n 1 - Chain ID\n 2 - Length of protein chain\n 3 - Exptl.\n 4 - Resolution\n 5 - R-factor\n 6 - FreeRValue\n \"\"\"\n regex_str = '(\\w{4})(\\w)\\s+(\\d+)\\s+(\\w+)\\s+([\\d\\.]+)\\s+([\\d\\.]+)\\s+([\\d\\.]+)'\n regex_pattern = re.compile(regex_str)\n\n printc('Processing: %s' % path)\n\n raw = None\n try:\n _file = gzip.open(path, 'r')\n\n #first line is labels, discard it\n _file.readline()\n\n for line in _file:\n match = regex_pattern.match(line)\n if match:\n groups = match.groups()\n\n if groups[0] in proteins:\n # if protein already exists just update the additional\n # chain information. The properties should not change\n # between records in the selection file.\n protein = proteins[groups[0]]\n if not groups[1] in protein['chains']:\n protein['chains'].append(groups[1])\n #print 'Selecting Protein: %s Chain: %s Threshold: %s' % (groups[0],groups[1], threshold)\n\n else:\n # protein is not in proteins dict yet create initial\n # structure from parsed properties.\n resolution = float(groups[4])\n if resolution > 0 and resolution <= max_resolution:\n proteins[groups[0]] = {\n 'code':groups[0],\n 'chains':[groups[1]],\n 'resolution':groups[4],\n 'rfactor':groups[5],\n 'rfree':groups[6],\n 'threshold':threshold\n }\n\n #print 'Selecting Protein: %s Chain: %s Threshold: %s' % (groups[0],groups[1], threshold)\n\n finally:\n if _file:\n _file.close()\n\n return proteins","def _testData(cls, name, asFile):\n data = {\n\n # Input 1: one PNG image, except the data makes no real sense\n \"input1\": \"\"\"89 PNG 0d0a1a0a\n 0000000d.IHDR 00000003000000020800000000 b81f39c6\n 00000004.gAMA 000186a0 31e8965f\n 00000007.tIME 07de061b0b2624 1f307ad5\n 00000008.IDAT 696d673164617461 ce8a4999\n 00000000.IEND ae426082\"\"\",\n\n # Input 2: slightly different, data in two chunks\n \"input2\": \"\"\"89 PNG 0d0a1a0a\n 0000000d.IHDR 00000003000000020800000000 b81f39c6\n 00000004.gAMA 000186a0 31e8965f\n 00000004.IDAT 696d6732 0e69ab1d\n 00000004.IDAT 64617461 6694cb78\n 00000000.IEND ae426082\"\"\",\n\n # Expected output 1: both images as frames of an animation\n \"anim12\": \"\"\"89 PNG 0d0a1a0a\n 0000000d.IHDR 00000003000000020800000000 b81f39c6\n 00000004.gAMA 000186a0 31e8965f\n 00000008.acTL 0000000200000000 f38d9370\n 0000001a.fcTL 000000000000000300000002\n 0000000000000000056712340100 b4f729c9\n 00000008.IDAT 696d673164617461 ce8a4999\n 0000001a.fcTL 000000010000000300000002\n 000000000000000000c800640100 1b92eb4d\n 00000008.fdAT 00000002696d6732 9cfb89a3\n 00000008.fdAT 0000000364617461 c966c076\n 00000000.IEND ae426082\"\"\",\n\n # Expected output 2: first image as fallback, second as animation\n \"still1anim2\": \"\"\"89 PNG 0d0a1a0a\n 0000000d.IHDR 00000003000000020800000000 b81f39c6\n 00000004.gAMA 000186a0 31e8965f\n 00000008.acTL 0000000100000000 b42de9a0\n 00000008.IDAT 696d673164617461 ce8a4999\n 0000001a.fcTL 000000000000000300000002\n 0000000000000000056712340100 b4f729c9\n 00000008.fdAT 00000001696d6732 db5bf373\n 00000008.fdAT 0000000264617461 f406e9c6\n 00000000.IEND ae426082\"\"\",\n\n }\n d = cls._hex2bin(data[name])\n if asFile:\n from sage.misc.temporary_file import tmp_filename\n fn = tmp_filename(ext=\".png\")\n with open(fn, 'wb') as f:\n f.write(d)\n return fn\n return d","def retrive_scanning_scheme(self, Nest_data_directory, file_keyword = 'PMT_0Zmax'):\r\n fileNameList = []\r\n# ImgSequenceNum = 0\r\n for file in os.listdir(Nest_data_directory):\r\n if file_keyword in file:\r\n fileNameList.append(file)\r\n \r\n RoundNumberList = []\r\n CoordinatesList = []\r\n for eachfilename in fileNameList:\r\n # Get how many rounds are there\r\n try:\r\n RoundNumberList.append(eachfilename[eachfilename.index('Round'):eachfilename.index('_Grid')])\r\n except:\r\n RoundNumberList.append(eachfilename[eachfilename.index('Round'):eachfilename.index('_Coord')])\r\n \r\n RoundNumberList = list(dict.fromkeys(RoundNumberList)) # Remove Duplicates\r\n \r\n CoordinatesList.append(eachfilename[eachfilename.index('Coord'):eachfilename.index('_PMT')])\r\n CoordinatesList = list(dict.fromkeys(CoordinatesList))\r\n \r\n# print(RoundNumberList, CoordinatesList, fileNameList)\r\n return RoundNumberList, CoordinatesList, fileNameList","def getBMData(filename):\n\n data = {}\n f = open(filename)\n line = f.readline() \n data['name'], data['gender'], data['age'] = [], [], []\n data['division'], data['country'], data['time'] = [], [], []\n while line != '':\n split = line.split(',')\n data['name'].append(split[0])\n data['gender'].append(split[1])\n data['age'].append(int(split[2]))\n data['division'].append(int(split[3]))\n data['country'].append(split[4]) \n data['time'].append(float(split[5][:-1])) #remove \\n\n line = f.readline()\n f.close()\n return data","def read_reference_data():\n return {f:read_local_file(f) for f in os.listdir(DATA_DIR)}","def stat_file(self, path, info):\n return {}","def get_data(self, n=-1): \n try:\n return Profile(os.path.join(self.name, self.files[n]))\n except IndexError:\n return None","def get_data(fname: str) -> dict:\n with open(fname) as f:\n return [rec.split() for rec in f.read().split(\"\\n\\n\")]","def get_additional_data_from_files(df, file_description): # file description one of [\"video\", \"eaf\", \"seg\", \"gentle\"]\n if file_description == \"gentle\":\n file_folder = FILE_BASE + \"/gentle/\"\n is_gentle_file = True\n else:\n file_folder = FILE_BASE + \"/original/\"\n is_gentle_file = False\n\n file_df = None\n\n if file_description not in list(FILE_DESCRIPTIONS_TO_EXT.keys()):\n print(\"Unknown file description! Don't know what to do with %s files...\" % file_description)\n return None\n\n else:\n print(\"Load and extract information from %s files...\" % file_description)\n #pbar = tqdm.tqdm(total = len(np.unique(df[\"source_file\"])),desc='Files', position=0,leave=True,file=sys.stdout)\n #file_log = tqdm.tqdm(total=0, position=1, bar_format='{desc}',leave=True,file=sys.stdout)\n print(\"Total files to laod and preprocess: \", len(np.unique(df[\"source_file\"])))\n \n for i,file in enumerate(np.unique(df[\"source_file\"])):\n if i%100 == 0:\n print(\"File: \",i)\n \n filepath = file_folder + get_file_path(file,is_gentle_file=is_gentle_file) + FILE_DESCRIPTIONS_TO_EXT[file_description]\n\n if file_description == \"video\":\n file_i_df = mp4_file_processing.get_word_video_snippet_size(df, filepath)\n elif file_description == \"eaf\":\n speech_annotation_eaf_data, gesture_eaf_data = eaf_file_processing.read_eaf(filepath)\n file_i_df = eaf_file_processing.map_gestures_to_annotation(speech_annotation_eaf_data, gesture_eaf_data, remove_pauses=False)\n file_i_df = eaf_file_processing.binary_encode_gestures(file_i_df, gesture_column=\"gesture\")\n\n elif file_description == \"seg\":\n file_i_df = seg_file_processing.get_seg_file_pos_info(filepath)\n\n elif file_description == \"gentle\":\n file_i_df = gentle_file_processing.get_gentle_file_transcripts(filepath)\n \n else:\n print(\"Unknown file format!!!\")\n return \n\n if file_df is None:\n file_df = file_i_df\n else:\n file_df = pd.concat([file_df, file_i_df], ignore_index=True)\n\n #file_log.set_description_str(f'Processed file: {file}')\n #pbar.update(1)\n #sleep(0.02)\n #file_log.close()\n #pbar.close()\n return file_df","def parse_path_image(proto_path, instance, model_path):\n\n # split the file name into parts\n name_parts = proto_path.split('_')\n # get the base path for the current model\n base_path = eval('instance.request.user.profile.' + model_path)\n # get the different parameters from the model\n # get the date\n date = datetime.datetime.strptime(name_parts[0], '%Y%m%d')\n\n # get the animal\n animal = Mouse.objects.get(mouse_name='_'.join(name_parts[1:4]))\n\n # get the region\n region = name_parts[4]\n\n # define the path for the different files\n bfpath = join(base_path, '_'.join((name_parts[0], animal.mouse_name, 'BF', region)) + '.tif')\n flpath = bfpath.replace('BF', 'FL')\n flgreenpath = bfpath.replace('BF', 'FLgreen')\n otherpath = bfpath.replace('BF', 'OTHER')\n\n return {'owner': instance.request.user,\n 'mouse': animal,\n 'window_date': date,\n 'bfPath': bfpath,\n 'flPath': flpath,\n 'flgreenPath': flgreenpath,\n 'otherPath': otherpath,\n 'region': region}","def read_sample(sample_path):\n files = os.listdir(sample_path)\n json_path = [f for f in files if f.endswith('_read-info.json')]\n assert len(json_path) == 1, 'There should be exactly 1 *_read-info.json file in the sample (.smpl)'\n # get base for sample\n with open(os.path.join(sample_path, json_path[0]), 'r') as f:\n sample = json.load(f)\n # get sample info\n info_path = [f for f in files if f.endswith('info.csv')]\n assert len(info_path) == 1, 'There should be exactly 1 *_info.csv file in the sample (.smpl)'\n sample['info'] = pd.read_csv(os.path.join(sample_path, info_path[0]))\n info_path = os.path.join(sample_path, info_path[0])\n # get individual sample\n regex = re.compile(r'id-\\d*_t-\\d*')\n pairs = [f for f in files if len(regex.findall(f)) > 0]\n for str_pair in pairs:\n pair_dir = os.path.join(sample_path, str_pair)\n pair_dict = {}\n # get df\n df_path = os.path.join(pair_dir, str_pair + '_df.csv')\n pair_dict['df'] = pd.read_csv(df_path)\n pair_dict['df_path'] = df_path\n pair_dict['info_path'] = info_path\n # get tracks\n tracks_path = os.path.join(pair_dir, str_pair + '_tracks.zarr')\n pair_dict['tracks'] = zarr.open(tracks_path)\n # get b_box\n bbox_path = os.path.join(pair_dir, str_pair + '_bbox.json')\n with open(bbox_path, 'r') as f:\n bbox = json.load(f)\n new_bbox = {}\n for key in bbox.keys():\n args = list(bbox[key])\n new_bbox[key] = slice(*args)\n pair_dict['b_box'] = new_bbox\n # find out if corrs exist and read if so\n corr_path = [f for f in os.listdir(pair_dir) if f.endswith('_corr.json')]\n if len(corr_path) > 0:\n with open(os.path.join(pair_dir, corr_path[0]), 'r') as f:\n corr = json.load(f)\n pair_dict['corr'] = corr\n # if image exists, read\n img_path = os.path.join(pair_dir, str_pair + '_image.zarr')\n if os.path.exists(img_path):\n img = zarr.open(img_path)\n #print(img, img_path)\n pair_dict['image'] = img\n # if labels exist, read\n lab_path = os.path.join(pair_dir, str_pair + '_labels.zarr')\n if os.path.exists(lab_path):\n lab = zarr.open(lab_path)\n #print(lab.shape)\n pair_dict['labels'] = lab\n # add pair to sample\n id_re = re.compile(r'id-\\d*')\n ID = id_re.findall(str_pair)[0][3:]\n t_re = re.compile(r't-\\d*')\n t = t_re.findall(str_pair)[0][2:]\n pair = (int(ID), int(t))\n sample[pair] = pair_dict\n #print(str_pair, pair)\n #print(list(sample.keys()))\n #print(list(sample[eval(pairs[0])].keys()))\n return sample","def _read_pairs(self):\n pairs = []\n with open(self.pairs_path, 'r') as f:\n for line in f.readlines()[1:]: # skip header\n pair = line.strip().split()\n pairs.append(pair)\n\n file_ext = 'jpg'\n lfw_dir = self.images_root_path\n path_list = []\n\n for pair in pairs:\n if len(pair) == 3:\n path0 = osp.join(lfw_dir, pair[0], pair[0] + '_' + '%04d' % int(pair[1]) + '.' + file_ext)\n id0 = pair[0]\n path1 = osp.join(lfw_dir, pair[0], pair[0] + '_' + '%04d' % int(pair[2]) + '.' + file_ext)\n id1 = pair[0]\n issame = True\n elif len(pair) == 4:\n path0 = osp.join(lfw_dir, pair[0], pair[0] + '_' + '%04d' % int(pair[1]) + '.' + file_ext)\n id0 = pair[0]\n path1 = osp.join(lfw_dir, pair[2], pair[2] + '_' + '%04d' % int(pair[3]) + '.' + file_ext)\n id1 = pair[0]\n issame = False\n\n path_list.append((path0, path1, issame, id0, id1))\n\n # skf = StratifiedKFold(n_splits=10, shuffle=True, random_state=42)\n\n # dataset = []\n # for _, test_index in skf.split(np.zeros_like(path_list), [item[2] for item in path_list]):\n # for idx in test_index:\n # dataset.append(path_list[idx])\n\n # return dataset\n return path_list","def get_files_io():\n if GC.conf['general']['training']:\n files_zip = {\n 'raw': os.path.join(COOKED_DATA, 'train.txt'),\n 'new': os.path.join(COOKED_DATA, 'train_new.txt'),\n 'norm': os.path.join(COOKED_DATA, 'train_norm.txt'),\n 'manu': os.path.join(RAW_DATA, 'others', 'temp_updt_manu.txt'),\n 'labels': os.path.join(TRAIN_DATA, 'train_norm.txt_labels.pkl'),\n 'segll': os.path.join(TRAIN_DATA, 'train_norm.txt_seginf_loglab.pkl'),\n 'segdl': os.path.join(TRAIN_DATA, 'train_norm.txt_seginf_deeplog.pkl'),\n 'struct': os.path.join(TRAIN_DATA, 'train_norm.txt_structured.csv'),\n 'output': TRAIN_DATA\n }\n else:\n files_zip = {\n 'raw': os.path.join(COOKED_DATA, 'test.txt'),\n 'new': os.path.join(COOKED_DATA, 'test_new.txt'),\n 'norm': os.path.join(COOKED_DATA, 'test_norm.txt'),\n 'labels': os.path.join(TEST_DATA, 'test_norm.txt_labels.pkl'),\n 'segll': os.path.join(TEST_DATA, 'test_norm.txt_seginf_loglab.pkl'),\n 'segdl': os.path.join(TEST_DATA, 'test_norm.txt_seginf_deeplog.pkl'),\n 'map_norm_raw': os.path.join(TEST_DATA, 'map_norm_raw.pkl'),\n 'map_norm_rcv': os.path.join(TEST_DATA, 'map_norm_rcv.pkl'),\n 'norm_rcv': os.path.join(TEST_DATA, 'test_norm_rcv.txt'),\n 'struct': os.path.join(TEST_DATA, 'test_norm.txt_structured.csv'),\n 'struct_rcv': os.path.join(TEST_DATA, 'test_norm_rcv.txt_structured.csv'),\n 'top': os.path.join(TEST_DATA, 'analysis_summary_top.txt'),\n 'sum': os.path.join(TEST_DATA, 'analysis_summary.csv'),\n 'rst_llab': os.path.join(TEST_DATA, 'results_loglab.csv'),\n 'rst_dlog': os.path.join(TEST_DATA, 'results_deeplog.txt'),\n 'rst_llzr': os.path.join(TEST_DATA, 'results_loglizer.csv'),\n 'dbg': os.path.join(TEST_DATA, 'debug.csv'),\n 'output': TEST_DATA\n }\n return files_zip","def make_file_dict():\r\n fileDict = {'pageUrls': [],\r\n 'pageFileNames': [],\r\n 'pageIds': [],\r\n 'fileUrls': [],\r\n 'fileIds': [],\r\n 'fileNames': [],\r\n 'cssUrls': [],\r\n 'cssFileNames': [],\r\n 'imgUrls': [],\r\n 'imgFileNames': []}\r\n return fileDict","def gbk_parse(fname):\n fhand = _open_file(gbkfname)\n unk = 1 \n\n for record in SeqIO.parse(fhand, \"genbank\"):\n\n gene_tags = dict()\n tx_tags = collections.defaultdict(list) \n exon = collections.defaultdict(list) \n cds = collections.defaultdict(list) \n mol_type, chr_id = None, None \n\n for rec in record.features:\n\n if rec.type == 'source':\n mol_type = rec.qualifiers['mol_type'][0]\n try:\n chr_id = rec.qualifiers['chromosome'][0]\n except:\n chr_id = record.name \n continue \n\n strand='-'\n strand='+' if rec.strand>0 else strand\n \n fid = None \n try:\n fid = rec.qualifiers['gene'][0]\n except:\n pass\n\n transcript_id = None\n try:\n transcript_id = rec.qualifiers['transcript_id'][0]\n except:\n pass \n\n if re.search(r'gene', rec.type):\n gene_tags[fid] = (rec.location._start.position+1, \n rec.location._end.position, \n strand,\n rec.type,\n rec.qualifiers['note'][0])\n elif rec.type == 'exon':\n exon[fid].append((rec.location._start.position+1, \n rec.location._end.position))\n elif rec.type=='CDS':\n cds[fid].append((rec.location._start.position+1, \n rec.location._end.position))\n else: \n # get all transcripts \n if transcript_id: \n tx_tags[fid].append((rec.location._start.position+1,\n rec.location._end.position, \n transcript_id,\n rec.type))\n # record extracted, generate feature table\n unk = feature_table(chr_id, mol_type, strand, gene_tags, tx_tags, cds, exon, unk)\n \n #break\n fhand.close()","def get_progress_file_info(filename):\n # Open the file and read it\n with open(filename,'r') as f:\n data = f.readlines()\n # Eat whitespace\n data = [s.lstrip().rstrip() for s in data]\n # Split the strings in each line \n data[0] = data[0].split(' ')\n data[1] = data[1].split(\"/\")\n # Now, based on position, we can start getting parameters\n current_sweep,final_sweep = [int(i) for i in data[1]]\n target_area = int(data[0][0])\n area_damping = float(data[0][1])\n save_every_n_sweeps = int(data[0][-1])\n if len(data[0]) == 3:\n target_std = default_target_std\n std_damping = default_std_damping\n else:\n target_std,std_damping = [float(s) for s in data[0][-2:-1]]\n # Gather data function is, of course, gather_data_to_1_file\n gather_data_function = output.gather_data_to_1_file\n # Same for algorithm\n algorithm = default_algorithm\n # v5 and v6 damping don't matter\n v5damping = default_v5damping\n v6damping = default_v6damping\n # The filename we want to output is the same file but with\n # *.boundary2p1 at the end.\n filename = filename.rstrip(output.tracking_suffix)+output.output_suffix\n # Return the parameters as a tuple\n params = parameters(filename,\n target_area,area_damping,\n target_std,std_damping,\n current_sweep,final_sweep,\n save_every_n_sweeps,\n v5damping,v6damping,\n algorithm,\n gather_data_function)\n return params","def read_file(file):\n if opts.input_type == 'fits':\n data = fileio.read_fits(file)\n else:\n data = fileio.read_ascii(file)\n c_id = data[0,:]\n g_num = np.array(range(len(c_id)), dtype = 'int')\n g_id = data[3,:]\n g_ra = np.array(data[4,:], dtype = 'float')\n g_dec = np.array(data[5,:], dtype = 'float')\n g_z = np.array(data[6,:], dtype = 'float')\n return c_id, g_num, g_id, g_ra, g_dec, g_z","def parse_gff(g):\n # We also want to store the mRNA->gene information!\n mrna_par = {}\n # And the CDS->mRNA information\n cds_dat = {}\n with open(g, 'r') as f:\n for line in f:\n # if the line is empty or starts with a #, we will skip it\n if line.startswith('#') or line == '\\n':\n continue\n else:\n tmp = line.strip().split('\\t')\n feat_type = tmp[2]\n if feat_type == 'mRNA':\n meta = tmp[8].split(';')\n for m in meta:\n if m.startswith('ID='):\n tx_id = m.split('=')[1]\n if m.startswith('Parent='):\n tx_par = m.split('=')[1]\n mrna_par[tx_id] = tx_par\n elif feat_type == 'CDS':\n scaf = tmp[0]\n start = tmp[3]\n end = tmp[4]\n strand = tmp[6]\n phase = tmp[7]\n meta = tmp[8].split(';')\n for m in meta:\n if m.startswith('ID='):\n cds_id = m.split('=')[1]\n if m.startswith('Parent='):\n cds_par = m.split('=')[1]\n if strand == '-':\n strand = -1\n else:\n strand = 1\n # Watch out for transcripts where there are multiple CDS.\n # This will require a nested dictionary of lists.\n if cds_par in cds_dat:\n pass\n else:\n cds_dat[cds_par] = {}\n if cds_id in cds_dat[cds_par]:\n pass\n else:\n cds_dat[cds_par][cds_id] = []\n # We want to make a SequenceFeature for each CDS chunk\n # Keep in mind that GFF is 1-based, so we have to adjust\n # the start position!\n cds_feat = SeqFeature(\n FeatureLocation(int(start)-1, int(end), strand=strand),\n type=\"CDS\",\n id=cds_id)\n # Add some qualifiers to modify the behavior\n # Use the \"standard\" genetic code from NCBI\n cds_feat.qualifiers['transl_tabl'] = [1]\n # Then, append it into the corresponding dictionary item\n # keeping the chromosome (scaffold) name and phase with it\n cds_dat[cds_par][cds_id].append((cds_feat, scaf, phase))\n else:\n continue\n return (mrna_par, cds_dat)","def test_file_access():\n file = gff.GFFFile()\n entry_scaffold = (\"ab\", \"cd\", 1, 2, None, None, None, {\"Id\":\"foo\"})\n entry = (\"a\",) + entry_scaffold\n file.append(*entry)\n assert file[0] == entry\n file.append(*((\"b\",) + entry_scaffold))\n file.insert(1, *((\"c\",) + entry_scaffold))\n file[1] = (\"d\",) + entry_scaffold\n file.insert(3, *((\"e\",) + entry_scaffold))\n del file[2]\n assert [seqid for seqid, _, _, _, _, _, _, _, _ in file] \\\n == [\"a\", \"d\", \"e\", ]","def get_g(file_name):\n \n r,g = np.loadtxt(file_name, dtype = 'float', unpack = 'true')\n \n return r,g","def get(self):\n data = []\n full_path = self.get_current_file()\n\n if self.is_allowed(full_path):\n data = self.get_file_info(full_path)\n else:\n abort(403, message=\"You are not allowed to this path\")\n\n result = {\"data\": data}\n return result","def setup_data( self ):\n with open( f'{project_dir}/data/05_source_key_data.json', 'r', encoding='utf-8' ) as f:\n dct = json.loads( f.read() )\n with open( f'{project_dir}/data/04_snapshot_open_textbook.json', 'r', encoding='utf-8' ) as f:\n lst = json.loads( f.read() )\n return ( dct, lst )","def read_drugable_genes(mypath):\n drug = pd.read_csv('data/drugability/interactions.tsv', sep='\\t')\n drug_types = ['inhibitor', 'antagonist', 'blocker', 'channel blocker', 'gating inhibitor', 'negative modulator', 'channel blocker,gating inhibitor',\n 'allosteric modulator,antagonist', 'inhibitor allosteric modulator', 'suppressor', 'antagonist,inhibitor']\n drug = drug[drug.interaction_types.isin(drug_types)]\n cts = drug.groupby(['drug_name', 'interaction_claim_source'])['gene_name'].nunique().sort_values(ascending=True)\n single_drug_impact = cts[cts==1].copy().index.to_series().reset_index()['drug_name'].unique()\n drug = drug[drug['drug_name'].isin(single_drug_impact)].dropna(subset=['gene_name'])\n\n # create a table of gene 2 drug relationships\n gene2drug = drug.groupby('gene_name')['drug_name'].agg(lambda x: ','.join(list(set(x)))).reset_index()\n #gene_names = drug['gene_name'].unique()\n return gene2drug","def parse(self):\n results = {}\n\n # get the signature info via the codesign utility\n args = [\"codesign\",\"-dvvvv\", self.file_name]\n proc = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n output, error_output = proc.communicate()\n if proc.returncode: #error, probably file not signed\n results[\"signature\"] = error_output\n else:\n results[\"signature\"] = output\n\n #get the file object\n file_object = open(self.file_name, 'rb')\n\n\n #Use the macho library to parse out some structures\n pFile = MachO(self.file_name)\n\n #if this is a fat file, it will have multiple Mach-O objects inside it\n results[\"FAT_header\"] = self.parseFATHeader(file_object, pFile)\n\n #parse all the Mach-O headers\n i = 1\n for h in pFile.headers:\n results[\"MachO_header\" + str(i)] = self.parseMachOHeader(h, file_object)\n i +=1\n\n #close the file\n file_object.close()\n\n #return the dict of results\n return results","def get_content(self, file_path: str) -> Tuple[defaultdict, str]:\n if not os.path.exists(file_path): # If file doesn't exist\n raise FileNotFoundError(f\"{fg(1)} Could not find file: {file_path}{fg(15)}\\n\")\n html = self.__html__(file_path)\n metadata = self.__metadata__()\n return metadata, html","def file_init():\r\n answer_files, ran, answers = initialize_files(\"DBF_\", 15, \".txt\")\r\n answer_files, answers = file_scan(answer_files, ran, answers)\r\n answer_files2, answers = open_read_files(answer_files, answers)\r\n stor_lib = group(answer_files2, answers)\r\n return stor_lib","def parse(cls, raw_folder: str) -> Dict[str, Any]:\n folder_path = os.path.abspath(raw_folder)\n data = dict()\n files = os.listdir(folder_path)\n for file in files:\n if is_ignored(file):\n continue\n try:\n file = os.path.join(raw_folder, file)\n datum = cls.process_file(file)\n except FileNotCompatible:\n continue\n\n _, kwrd = os.path.split(file)\n kwrd = os.path.splitext(kwrd)[0]\n data[kwrd] = datum\n\n return data","def file_data(self):\n return self.read(self.file)","def recognize_pic(path):\n results = recognize(path, access_token, cookie, fb_dtsg)\n\n names = [str(result['name']) for result in results]\n print ('%s contains %s' % (path, names))\n\n return {\n \"filename\": path,\n \"friends\": names\n }","def load_file(fpath):\n sick_data = {'X_A': [], 'X_B': [], 'y': []}\n with open(fpath, 'r', encoding='utf-8') as f:\n for line in f:\n text = line.strip().split('\\t')\n sick_data['X_A'].append(text[5].split())\n sick_data['X_B'].append(text[6].split())\n sick_data['y'].append(float(text[4]))\n return sick_data","def parse_file(filename):\n filepath = root + filename\n try:\n if filename.endswith('.txt'):\n with open(filepath) as file:\n return file.read().splitlines()\n elif filename.endswith('.csv'):\n reader = csv.reader(open(filepath))\n result = {}\n for row in reader:\n key = row[0]\n result[key] = row[1]\n return result\n except FileNotFoundError:\n with open(filepath,\"w+\") as file:\n append_string_to_textfile(filename, \"Placeholder\")\n print(\"here\")\n return (parse_file(filename))","def readFile(file_name):\n if file_name.split('.')[-1] == 'thid':\n x,m,w = readThid(file_name)\n e = np.empty_like(x)\n e[:] = np.nan\n return x,m,w,e\n else:\n return readParams(file_name)","def parse_files():\n focus, stars, errors = [], [], []\n\n # Parse the plot file.\n with open(tempfile.gettempdir() + '/cuplt.tmp') as current_plot:\n # Record the focus vector.\n for component in current_plot.readline().split():\n focus.append(float(component))\n\n # Record all of the stars.\n for line in current_plot:\n star = []\n for component in line.split():\n star.append(float(component))\n stars.append(star)\n\n # If desired, parse the error file.\n if err_flag:\n with open(tempfile.gettempdir() + '/errplt.tmp') as error_plot:\n for line in error_plot:\n error = []\n\n for a, component in enumerate(line.split()):\n if a < 4:\n error.append(float(component))\n else:\n error.append(component)\n errors.append([error])\n\n # Return all items as a dictionary.\n return {'fov': fov, 'focus': focus, 'stars': stars, 'errors': errors}","def save_file():\n generic = pull_list()\n result = list()\n i = 0\n while True:\n try:\n if generic[i].startswith('CVE'):\n cve_pattern = \"^CVE-\\d+-\\d+|^CVE-\\d+-[X]+\"\n header = re.findall(cve_pattern, generic[i])[0]\n i += 1\n notes = list()\n while not generic[i].startswith('CVE'):\n commit_pattern = \"http[s]?:\\/\\/.+commit\\/[\\S]+\"\n if re.search(commit_pattern, generic[i]):\n link = re.findall(commit_pattern, generic[i])\n notes.append(link[0])\n i += 1\n if notes != list():\n result.append(Data(header, notes))\n except IndexError:\n print('Finished')\n break\n return result","def creeStructureDonnees(fileName):\n with open(fileName, 'r') as source:\n # Enregistre les caracteristiques de l'instance dans la variable carac\n r, s, u, p, m = source.readline().split()\n carac = {'R': int(r), 'S': int(s), 'U': int(u), 'P': int(p), 'M': int(m)}\n dicoObstacles = {}\n dicoRangees = {}\n \n # Enregistre dans le dictionnaire dicoObstacles les slots indisponibles tel que :\n # - cle = numero de la rangee\n # - valeur = liste de numeros de slot qui sont indisponibles\n for i in range(0, carac['R']):\n dicoObstacles[str(i)] = []\n dicoRangees[str(i)]= ['' for j in range(carac['S'])]\n \n i = 0\n while i < carac['U']:\n row, slot = source.readline().split()\n dicoObstacles[str(row)].append(int(slot))\n dicoRangees[str(row)][int(slot)] = 'x'\n i += 1\n \n # Trie les liste de numero de slot pour chaque rangee\n for k, v in dicoObstacles.items():\n dicoObstacles[k].sort()\n \n # Enregistre les serveurs dans une liste.\n # Un element de la liste est un triplet : [identifiant du serveur, sa taille, sa capacite]\n serverId = 0\n listeServeurs = []\n line = source.readline()\n while line != \"\":\n size, capacity = line.split()\n listeServeurs.append([serverId, int(size), int(capacity)])\n line = source.readline()\n serverId += 1\n \n # Trie par capacite decroissante\n listeServeurs.sort(key = lambda tup : tup[2], reverse = True) \n source.close()\n \n return carac, dicoObstacles, listeServeurs, dicoRangees","def insert_bad_data():\n get_file_reply(files[2][0], files[2][1])","def parse_triangle_files(self):\n nodes = {}\n boundary_nodes = []\n\n # parse node file into nodes\n with open(self.files['node']) as node_file:\n header = True\n for line in node_file:\n if header:\n header = False\n continue\n content = list(filter(lambda a: bool(a), line.split(' '))) # pylint: disable=W0108\n if not '#' in content[0]:\n is_boundary = content[3] == '1\\n'\n nodes[int(content[0])] = {\n 'id': int(content[0]),\n 'coords': [int(content[1]), int(content[2])],\n 'distance': 0 if is_boundary else None,\n 'relations': [],\n 'level_cycles': [], # ids of any level cycles this node is a part of\n 'level_paths': [], # ids of any level paths this node is a part of\n 'is_root_element': False,\n 'betweener_paths': []\n }\n if is_boundary:\n boundary_nodes.append(int(content[0]))\n node_file.close()\n\n # parse edge files into node relations\n with open(self.files['edge']) as edge_file:\n header = True\n for line in edge_file:\n if header:\n header = False\n continue\n content = list(filter(bool, line.split(' ')))\n if not '#' in content[0]:\n nodes[int(content[1])]['relations'].append(int(content[2]))\n nodes[int(content[2])]['relations'].append(int(content[1]))\n edge_file.close()\n\n # with open(self.files['ele']) as ele_file:\n # header = True\n # for line in edge_file:\n # if header:\n # header = False\n # continue\n # content = list(filter(bool, line.split(' ')))\n # if not '#' in content[0]:\n # nodes[int(content[1])]['relations'].append(int(content[2]))\n # nodes[int(content[2])]['relations'].append(int(content[1]))\n # edge_file.close()\n\n # sorts relations clockwise\n for node_id, node in nodes.items():\n nodes[node_id]['relations'] = sorted(node['relations'], key=(\n lambda related_node_id: (\n self.calculate_clockwise_angle_and_distance(node, nodes.get(related_node_id)) # pylint: disable=W0640\n )\n ))\n\n levels = self.get_levels(nodes, boundary_nodes)\n\n for level in levels:\n for node_id in level['node_ids']:\n self.identify_special_nodes(nodes, node_id)\n\n return nodes, boundary_nodes, levels","def _read_file(self):\n\n with open(self.file_name, 'rb') as f:\n new_test = struct.unpack('<l', f.read(8)[4:])[0]\n f.close()\n\n with open(self.file_name, 'rb') as f:\n old_test = struct.unpack('<h', f.read(6)[4:])[0]\n f.close()\n\n with open(self.file_name, 'rb') as f:\n other_test = struct.unpack('<l', f.read(20)[16:])[0]\n f.close()\n\n open_file = open(self.file_name, 'rb')\n\n if (other_test==202):\n raw = open_file.read(1236)[11:]\n self.model = '202'\n elif ((not new_test==102) and old_test==102):\n raw = open_file.read(1133)\n self.model = '102old'\n elif (new_test==102 and old_test==102):\n raw = open_file.read(1224)\n self.model = '102new'\n\n self.header = DpHeader(raw, self.model)\n\n self.data = DpData(open_file, \n self.model, \n self.header.interferogram_size, \n self.header.number_of_coadds, \n 2048*self.header.zero_fill,\n self.header.laser_wavelength_microns, \n self.header.dispersion_constant_xm,\n self.header.dispersion_constant_xb)\n\n open_file.close()","def json_data(self):\n return_data = []\n\n # Loop over num files\n for ifile in range(len(self.data)):\n\n # Loop over steps\n file_return_data = {}\n for istep in range(len(self.data[ifile])):\n file_return_data[istep] = {}\n for key in self.data[ifile][istep]:\n file_return_data[istep][key] = self.data[ifile][istep][key].tolist()\n\n return_data.append(file_return_data)\n\n return return_data","def read_frames_from_file(file_name):\n tracklets = parseXML(file_name)\n\n\n frames = {}\n for trackletObj in tracklets:\n \tfor translation, rotation, state, occlusion, truncation, amtOcclusion, amtBorders, absoluteFrameNumber, velo in trackletObj:\n \t\tobj = {'type': trackletObj.objectType, 'l':translation, 'v': velo}\n \t\tif not frames.has_key(absoluteFrameNumber):\n \t\t\tframes[absoluteFrameNumber] = []\n \t\tframes[absoluteFrameNumber].append(obj)\n return frames","def get_gbk_files(self):\n\n db_name = []\n for file in os.listdir(os.getcwd()):\n if file.endswith('.db'):\n db_name.append(str(file))\n\n for G_key, G_value in self.what.tier_frame_dict.items():\n Tier = G_key\n os.chdir(self.path)\n os.mkdir(Tier)\n os.chdir(Tier)\n Tier_path = os.getcwd()\n for Gene in self.what.tier_frame_dict[Tier].T:\n os.chdir(Tier_path)\n os.mkdir(Gene)\n os.chdir(Gene)\n for Organism in self.what.org_list:\n Accession = str(self.what.gene_dict[Gene][Organism])\n Accession, Sup, Version = Accession.partition('.')\n Accession = Accession.upper()\n server_flag = False\n for name in db_name:\n if server_flag is True:\n break\n name = str(name)\n server = BioSeqDatabase.open_database(\n driver='sqlite3', db=where.VERT_MAM + ('/Databases/%s' % name))\n for sub_db_name in server.keys():\n db = server[sub_db_name]\n\n try:\n record = db.lookup(accession=Accession)\n with open('%s_%s.gbk' % (Gene, Organism), 'w') as GB_file:\n GB_file.write(record.format('genbank'))\n print(GB_file.name, 'created')\n server_flag = True\n break\n except IndexError:\n print('Index Error')\n continue","def return_file_read(_):\n return [\"scorevideo LOG\", \"File: log.mat\"]","def _GetImageInfo(self,path):\n hd = Header(path, scan=True)\n hdr = hd.hdr\n self.hdr = hdr\n if hdr is None:\n# Either a ref.dat file or it isn't an imaging file.\n if 'ref' in path and 'dat' in path:\n self.refdats[os.path.realpath(path)] = True\n info = {'type':'refdat'}\n return info\n else:\n return None\n elif hdr['filetype'] == 'dicom' and not path.endswith('.yaml'):\n# Write a yaml file to the raw data directory if possible.\n dirname, outfile = self._yaml_filename(path)\n yaml_name = '%s/%s' % (dirname, outfile)\n if not os.path.exists(yaml_name):\n# Create yaml file using dirname,\n# e.g., ../anatomicals/S2_EFGRE3D/s2_efgre3d.yaml\n try:\n hd.write_hdr_to_yaml('%s/%s' % (dirname,outfile))\n except IOError:\n# This is a nonessential function, so ignore exceptions\n# such as access violations.\n pass\n elif hdr['filetype'] == 'dicom' or hdr['filetype'] == 'ge_ifile':\n if not os.path.isdir(path):\n path = os.path.dirname(path)\n shdr = hdr['subhdr']\n nhdr = hdr['native_header']\n self.shdr = shdr\n if 'dti' in shdr.get('PulseSequenceName','').lower() \\\n or 'dti' in nhdr.get('PulseSequenceFile',''):\n psdname = 'dti'\n else:\n psdname = os.path.basename((shdr.get('PulseSequenceName','').strip()).lower())\n info = {'psdname':psdname, \\\n 'acqtime':shdr['AcqTime'], \\\n 'series':int(shdr['SeriesNumber']), \\\n 'plane':hdr['plane'].strip(), \\\n 'type':self.imgtype.get(psdname,None), \\\n 'plane':hdr['plane'], \\\n 'acqtime':shdr['SeriesTime'], \\\n# 'fmapdir':None, \\\n 'refdat':None, \\\n 'imgfile':None, \\\n 'base':None, \\\n 'tdim':int(hdr['tdim']), \\\n 'echo_spacing':None, \\\n 'filetype':'brik', \\\n 'suffix':self.suffix.get(hdr['filetype'], 'brik'), \\\n 'data_filetype':hdr['filetype']}\n if info['type'] == 'localizer':\n# Don't process the localizer.\n return info\n if isinstance(info['acqtime'], int):\n info['acquisition_time'] = time.ctime(info['acqtime'])\n if nhdr.get('ImageFormat',('unknown'))[0] == 'DERIVED' and info['type'] == 'epi':\n# Sometimes screenshots are defined as epis.\n info['type'] = None\n\n# Call the method appropriate to the type of scan in this series.\n stat = apply( self.GetInfoMethods.get(info['type'], self._NoInfo), \\\n [info, path])\n if stat:\n info = {'type':'break'}\n return info\n info['suffix'] = self.suffix.get(info['filetype'], 'brik')\n return info","def read_parse_raw_data(path):\n file_list = TopologyHelper.get_file_list(path)\n print(\"Reading \" + str(len(file_list)) + \" files from \" + path)\n topology_info = []\n file_name = []\n for file in file_list:\n try:\n r = TopologyHelper.parse_file(file)\n tmp = (r[0])['Topology']\n topology_info.append(tmp)\n t = r[1]\n file_name.append(t)\n except:\n continue\n print(\"Parsing completed\")\n return file_name, topology_info","def create_dicts(self):\n \n # remove this string from filename to make output file names more manageable\n pre_output1 = self.file1.replace(\"_Guys121919_CGH_1100_Jul11\", '')\n pre_output2 = self.file2.replace(\"_Guys121919_CGH_1100_Jul11\", '')\n \n # Build the output file name.\n # if prefix is present add it\n if self.out_file_prefix is not None:\n # concatenate prefix, filenames and dyes into output filename file1_file1_dye_file2_file2_dye.txt\n self.outputfilename = self.out_file_prefix+pre_output1.replace(\".txt\", '') + \"_\" + self.file1_dye + \"_\" + pre_output2.replace(\".txt\", '') + \"_\" + self.file2_dye + \".txt\"\n # if no prefix don't add it!\n else:\n # concatenate filenames and dyes into output filename file1_file1_dye_file2_file2_dye.txt\n self.outputfilename = pre_output1.replace(\".txt\", '') + \"_\" + self.file1_dye + \"_\" + pre_output2.replace(\".txt\", '') + \"_\" + self.file2_dye + \".txt\"\n\n # add temp to end of file name to create a temporary output filename\n self.tempoutputfilename = self.outputfilename.replace(\".txt\", '') + \"temp.txt\"\n\n # open temp output file\n self.tempoutputfile = open(self.outputfolder + self.tempoutputfilename, 'w')\n\n \n # open FE files\n file1_open = open(self.chosenfolder + self.file1, 'r')\n file2_open = open(self.chosenfolder + self.file2, 'r')\n\n # open file1 and create a dict of the features.\n for linenumber, line in enumerate(file1_open):\n if linenumber >= 10:\n splitline = line.split('\\t')\n self.file1_dict[int(splitline[1])] = line\n # get n of rows in file1 (take the linenumber of the last line)\n self.file1_len = linenumber\n\n # repeat for features in second file but first writing the feparam and stats to temp file - when pairing with control this ensures the \"header\" comes from the test (file2) not control (file1), NB NEITHER ARE ACCURATE!!!!\n for linenumber, line in enumerate(file2_open):\n if linenumber < 10:\n self.tempoutputfile.write(line)\n # then add all features to a dictionary, with the unique feature number as a key\n if linenumber >= 10:\n splitline = line.split('\\t')\n self.file2_dict[int(splitline[1])] = line\n # get n of rows in file2\n self.file2_len = linenumber\n\n # close files\n file1_open.close()\n file2_open.close()","def read_struct_file(struct_file,return_type=GeoStruct):\n\n VARTYPE = {1:SphVario,2:ExpVario,3:GauVario,4:None}\n assert os.path.exists(struct_file)\n structures = []\n variograms = []\n with open(struct_file,'r') as f:\n while True:\n line = f.readline()\n if line == '':\n break\n line = line.strip().lower()\n if line.startswith(\"structure\"):\n name = line.strip().split()[1]\n nugget,transform,variogram_info = _read_structure_attributes(f)\n s = return_type(nugget=nugget,transform=transform,name=name)\n s.variogram_info = variogram_info\n # not sure what is going on, but if I don't copy s here,\n # all the structures end up sharing all the variograms later\n structures.append(copy.deepcopy(s))\n elif line.startswith(\"variogram\"):\n name = line.strip().split()[1].lower()\n vartype,bearing,a,anisotropy = _read_variogram(f)\n if name in variogram_info:\n v = VARTYPE[vartype](variogram_info[name],a,anisotropy=anisotropy,\n bearing=bearing,name=name)\n variograms.append(v)\n\n for i,st in enumerate(structures):\n for vname in st.variogram_info:\n vfound = None\n for v in variograms:\n if v.name == vname:\n vfound = v\n break\n if vfound is None:\n raise Exception(\"variogram {0} not found for structure {1}\".\\\n format(vname,s.name))\n\n st.variograms.append(vfound)\n if len(structures) == 1:\n return structures[0]\n return structures","def dbase():\r\n albums_data = {}\r\n song_dict = {}\r\n songs_list = []\r\n with open(PATH, 'r') as f:\r\n data = f.read()\r\n temp = data.split(\"#\")\r\n for album in temp[1:]:\r\n index = album.find(\"::\")\r\n albums_data[album[:index]] = \"\"\r\n for album in temp[1:]:\r\n album = album.split(\"*\")\r\n album_name = album[0][:-7]\r\n release_Date = album[0][-5:]\r\n del album[0]\r\n for song in album:\r\n info = song.split(\"::\")\r\n song_name = info[0]\r\n del info[0]\r\n songs_list = info\r\n song_dict[song_name] = songs_list\r\n albums_data[album_name] = (song_dict.copy(), release_Date)\r\n song_dict.clear()\r\n return albums_data","def from_file(file_name, format='') -> Union['flare.struc.Structure',\n List['flare.struc.Structure']]:\n\n try:\n with open(file_name, 'r') as _:\n pass\n except:\n raise FileNotFoundError\n\n if 'xyz' in file_name or 'xyz' in format.lower():\n raise NotImplementedError\n\n if 'json' in format.lower() or '.json' in file_name:\n # Assumed format is one FLARE structure per line,\n # or one line with many FLARE structures\n with open(file_name, 'r') as f:\n thelines = f.readlines()\n\n non_empty_lines = [loads(line) for line in thelines if\n len(line) > 2]\n\n structures = [Structure.from_dict(struc_dict) for struc_dict in\n non_empty_lines]\n\n if len(structures) == 1:\n return structures[0]\n else:\n return structures\n\n is_poscar = 'POSCAR' in file_name or 'CONTCAR' in file_name or 'vasp' in format.lower()\n if is_poscar and _pmg_present:\n pmg_structure = pmgvaspio.Poscar.from_file(file_name).structure\n return Structure.from_pmg_structure(pmg_structure)\n elif is_poscar and not _pmg_present:\n raise ImportError(\"Pymatgen not imported; \" \\\n \"functionality requires pymatgen.\")","def getattr(self, path, *args, **pargs):\n path, meta = self.find_cue_path(path)\n if('.flaccuesplit.' in path):\n try:\n raw_path = path\n path, flaccue_details = path.split('.flaccuesplit.')\n path = self.clean_path(path)\n times, extension = os.path.splitext(flaccue_details)\n # Get the info for the base file.\n st = os.lstat(path)\n toreturn = dict((key, getattr(st, key)) for key in (\n 'st_atime', 'st_ctime', 'st_gid', 'st_mode', 'st_mtime',\n 'st_nlink', 'st_size', 'st_uid'))\n # Estimate the file size.\n f = mutagen.File(path)\n start, end = times.split('.')\n # Minutes:Seconds:Frames\n # 75 frames per second.\n start_split = [int(x) for x in start.split(':')]\n if(len(start_split) != 3):\n start_time = 0\n else:\n start_time = start_split[0]*60 + start_split[1] + start_split[2]/75\n end_split = [int(x) for x in end.split(':')]\n if(len(end_split) != 3):\n end_time = f.info.length\n else:\n end_time = end_split[0]*60 + end_split[1] + end_split[2]/75\n toreturn['st_size'] = int((end_time - start_time) *\n f.info.channels *\n (f.info.bits_per_sample/8) *\n f.info.sample_rate)\n # Ensure the mode shows the file as readable.\n toreturn['st_mode'] = toreturn['st_mode'] | 0o444\n return toreturn\n except Exception:\n print(f'Error getting attributes for {raw_path}:', file=sys.stderr, flush=True)\n import traceback\n traceback.print_exc()\n # Otherwise, just get the normal info.\n path = self.clean_path(path)\n st = os.lstat(path)\n toreturn = dict((key, getattr(st, key)) for key in (\n 'st_atime', 'st_ctime', 'st_gid', 'st_mode', 'st_mtime',\n 'st_nlink', 'st_size', 'st_uid'))\n # Ensure the mode shows the file as readable.\n toreturn['st_mode'] = toreturn['st_mode'] | 0o444\n return toreturn","def get_patches(self, username, filename) -> Tuple[str, List[str]] or None:\r\n file_id = self.get_file_id(username, filename)\r\n if file_id not in self.patch_history:\r\n file_path = self.users_dir / username / filename\r\n file_patches = self.try_load_file(file_path)\r\n if file_patches is not None:\r\n self.patch_history[file_id] = file_patches\r\n else:\r\n return None\r\n return file_id, self.patch_history[file_id]","def readfile(self,filenm,delimiter):\n\n timefiledata = []\n timefileextra = {}\n fixtimeflag = False\n hour0=hour1=False\n\n\n if isinstance(filenm,(str,unicode)):\n timeobject = readTextFile(filenm,delimiter)\n else:\n timeobject = filenm\n\n\n for idx,lines in enumerate(timeobject):\n\n try:\n floatlines = map(float,lines)\n month,date,hour = floatlines[:3]\n dataval = floatlines[3:]\n ##Code to check if the first time value is 1.0. If so subtract every hour by 0.5\n\n if not hour1 or hour0:\n hour1 = hour\n if hour0==1.0 and hour1==2.0:\n #Go back to the array that stores timevalues and fix the hour and time stamp\n timefiledata[0]['h']=0.5\n timefiledata[0]['tstamp']=timeStamp(1,1,0.5)\n fixtimeflag=True\n\n if not hour0:\n hour0 = hour\n\n if fixtimeflag:\n hour = hour-0.5\n ##Code to check if the first time value is 1.0. If so subtract every hour by 0.5\n\n timestamp = timeStamp(month,date,hour)\n\n timefiledata.append({\"m\":month,\"d\":date,\"h\":hour,\"readStadicData\":dataval,\"tstamp\":timestamp})\n\n except ValueError:\n print(sys.exc_info())\n timefileextra[lines[0]]=lines[1]\n\n return (timefiledata,timefileextra)","def ReadInputFile(file:int)->EvenMorePizza:\n self.files = ('a_example.in','b_little_bit_of_everything.in', 'c_many_ingredients.in','d_many_pizzas.in','e_many_teams.in')\n \n EvenMorePizza temporalValue\n \n file = open(files[file])#open the file\n data = doc.Read().strip(' ,\\n').split('\\n')\n file.close()#close the file\n #set the title of the command\n data_head = data[0].strip(' ,\\n').split(' ')\n temporalValue.AvailablePizza = int(data_head[0])\n temporalValue.Team2ppl = int(data_head[1])\n temporalValue.Team3ppl = int(data_head[2])\n temporalValue.Team4ppl = int(data_head[3])\n #set the other ingredients\n count = 0\n for a in data[1:]:\n x = a.strip(' ,\\n').split(' ')\n temporalValue.ingredients[count] = x[1:]\n count += 1","def get_file(filename: str) -> dict:\n return loads(open(f\"data/gamedata/{filename}.json\", \"r\", encoding=\"utf-8\").read())","def associate_files(self):\n # Open starinfo file and define structured array\n starinfo_file = self.starinfo_file\n nstar = sum(1 for line in open(starinfo_file))\n infoname = ['obj', 'std', 'caldir', 'altname']\n infofmt = ['|S25', '|S25', '|S25', '|S25']\n starinfo = np.zeros(nstar, dtype={\n 'names': infoname, 'formats': infofmt})\n with open(starinfo_file, 'r') as arq:\n for i in range(nstar):\n linelist = arq.readline().split()\n for j in range(len(infoname)):\n starinfo[i][j] = linelist[j]\n\n if self.stored_sens:\n self.load_storedsens()\n\n os.chdir(self.raw_dir)\n\n l = glob.glob('*.fits')\n l.sort()\n\n headers = []\n headers_ext1 = []\n for i in l:\n try:\n headers.append(fits.getheader(i, ext=0))\n headers_ext1.append(fits.getheader(i, ext=1))\n except IOError:\n print('IOError reading file {:s}.'.format(i))\n raise SystemExit(0)\n\n oversc = np.array(\n [('overscan') in i for i in headers_ext1], dtype='bool')\n\n mjds = np.array([i['mjd-obs'] for i in headers_ext1], dtype='float32')\n idx = np.arange(len(l))\n\n images = np.array([\n l[i] for i in idx if (\n (headers[i]['obstype'] == 'OBJECT') &\n (headers[i]['object'] != 'Twilight') &\n (headers[i]['obsclass'] != 'acq'))])\n\n field_names = [\n 'filename', 'observatory', 'instrument', 'detector',\n 'grating', 'filter1', 'obsclass', 'object', 'obstype',\n 'grating_wl', 'overscan', 'mjd', 'ccdsum']\n types = [\n 'S120', 'S60', 'S60', 'S60', 'S60', 'S60', 'S60', 'S60', 'S60',\n 'float32', 'bool', 'float32', 'S60']\n hdrkeys = [\n 'observat', 'instrume', 'detector', 'grating', 'filter1',\n 'obsclass', 'object', 'obstype', 'grwlen']\n\n hdrpars_type = [\n (field_names[i], types[i]) for i in range(len(field_names))]\n\n hdrpars = np.array([\n ((l[i],) + tuple([headers[i][j] for j in hdrkeys]) +\n (oversc[i],) + (mjds[i],) + (headers_ext1[i]['ccdsum'],))\n for i in idx], dtype=hdrpars_type)\n\n associated = []\n\n for i, j in enumerate(images):\n\n # Take great care when changing this.\n hdr = fits.getheader(j, ext=0)\n hdr_ext1 = fits.getheader(j, ext=1)\n mjd = hdr_ext1['mjd-obs']\n\n element = {\n 'image': j, 'observatory': hdr['observat'],\n 'instrument': hdr['instrume'],\n 'detector': hdr['detector'], 'grating_wl': hdr['grwlen'],\n 'mjd': mjd, 'grating': hdr['grating'],\n 'filter1': hdr['filter1'], 'obsclass': hdr['obsclass'],\n 'object': hdr['object']}\n\n if self.stored_sens:\n ssf = self.stored_sensfunc\n element['standard_star'] = ssf['filename'][\n (ssf['observatory'] == hdr['observat']) &\n (ssf['detector'] == hdr['detector']) &\n (ssf['grating'] == hdr['grating']) &\n (ssf['instrument'] == hdr['instrume']) &\n (ssf['filter1'] == hdr['filter1']) &\n (ssf['maskname'] == hdr['maskname'])]\n else:\n element['standard_star'] = hdrpars['filename'][\n (hdrpars['obstype'] == 'OBJECT') &\n (np.array([k in ['partnerCal', 'progCal']\n for k in hdrpars['obsclass']], dtype='bool')) &\n (hdrpars['object'] != 'Twilight') &\n (hdrpars['observatory'] == hdr['observat']) &\n (hdrpars['detector'] == hdr['detector']) &\n (hdrpars['grating'] == hdr['grating']) &\n (hdrpars['filter1'] == hdr['filter1']) &\n (abs(hdrpars['grating_wl'] - hdr['grwlen']) <=\n self.cfg.getfloat('associations', 'stdstar_wltol')) &\n (abs(mjds - mjd) <=\n self.cfg.getfloat('associations', 'stdstar_ttol'))]\n\n element['flat'] = hdrpars['filename'][\n (hdrpars['obstype'] == 'FLAT') &\n (hdrpars['observatory'] == hdr['observat']) &\n (hdrpars['grating'] == hdr['grating']) &\n (hdrpars['grating_wl'] == hdr['grwlen']) &\n (hdrpars['detector'] == hdr['detector']) &\n (abs(mjds - mjd) <= self.cfg.getfloat('associations',\n 'flat_ttol'))]\n\n element['twilight'] = hdrpars['filename'][\n (hdrpars['object'] == 'Twilight') &\n (hdrpars['obstype'] == 'OBJECT') &\n (hdrpars['observatory'] == hdr['observat']) &\n (hdrpars['detector'] == hdr['detector']) &\n (hdrpars['grating'] == hdr['grating']) &\n (abs(hdrpars['grating_wl'] - hdr['grwlen']) <=\n self.cfg.getfloat('associations', 'twilight_wltol')) &\n (abs(mjds - mjd) <=\n self.cfg.getfloat('associations', 'twilight_ttol'))]\n\n c = 'twilight'\n if len(element[c]) > 1:\n element[c] = closest_in_time(element[c], j)\n elif len(element[c]) == 1:\n element[c] = element[c][0]\n elif len(element[c]) == 0:\n element[c] = ''\n\n # A flat close to the twilight observation for a better\n # response function.\n if element['twilight']:\n twipars = hdrpars[hdrpars['filename'] == element['twilight']]\n element['twilight_flat'] = hdrpars['filename'][\n (hdrpars['obstype'] == 'FLAT') &\n (hdrpars['observatory'] == twipars['observatory']) &\n (hdrpars['detector'] == twipars['detector']) &\n (hdrpars['grating'] == twipars['grating']) &\n (hdrpars['grating_wl'] == twipars['grating_wl']) &\n (abs(mjds - twipars['mjd']) <= self.cfg.getfloat(\n 'associations', 'twilight_ttol'))]\n else:\n element['twilight_flat'] = np.array([], dtype='S60')\n\n element['arc'] = hdrpars['filename'][\n # (hdrpars['object'] == 'CuAr') &\n (hdrpars['obstype'] == 'ARC') &\n (hdrpars['observatory'] == hdr['observat']) &\n (hdrpars['detector'] == hdr['detector']) &\n (hdrpars['grating'] == hdr['grating']) &\n (hdrpars['grating_wl'] == hdr['grwlen']) &\n (abs(mjds - mjd) <=\n self.cfg.getfloat('associations', 'arc_ttol'))]\n\n element['bias'] = hdrpars['filename'][\n (hdrpars['obstype'] == 'BIAS') &\n (hdrpars['observatory'] == hdr['observat']) &\n (hdrpars['detector'] == hdr['detector']) &\n (abs(mjds - mjd) <=\n self.cfg.getfloat('associations', 'bias_ttol')) &\n (\n (hdrpars['overscan'] & (self.fl_over == 'yes')) |\n (~hdrpars['overscan'] & (self.fl_over == 'no'))\n )]\n\n im = fits.open(element['image'])\n ishape = np.array(im[1].data.shape, dtype='float32')\n im.close()\n del(im)\n\n validBiases = np.ones(len(element['bias']), dtype='bool')\n k = 0\n\n for biasImage in element['bias']:\n\n bias = fits.open(biasImage)\n bshape = np.array(bias[1].data.shape, dtype='float32')\n bias.close()\n del(bias)\n\n #\n # Elinates biases if they differ in array size from\n # the science image. Small differences are normal due to\n # the overscan subtraction in processed bias frames.\n #\n if np.any(np.abs(bshape / ishape - 1.0) > 0.10):\n validBiases[k] = False\n\n k += 1\n\n element['bias'] = element['bias'][validBiases]\n del(k)\n\n element['bpm'] = hdrpars['filename'][\n (hdrpars['obstype'] == 'BPM') &\n (hdrpars['observatory'] == hdr['observat']) &\n (hdrpars['detector'] == hdr['detector']) &\n (hdrpars['ccdsum'] == hdr_ext1['ccdsum'])]\n\n categories = ['flat', 'bias', 'arc', 'standard_star',\n 'bpm', 'twilight_flat']\n\n for c in categories:\n if len(element[c]) > 1:\n element[c] = closest_in_time(element[c], j)\n elif len(element[c]) == 0:\n element[c] = ''\n elif len(element[c]) == 1:\n element[c] = (element[c])[0]\n\n associated.append(element)\n\n # Define mdf filename\n # Based in gprepare.cl\n # Did not account for observation in Nod-and-Shuffle\n for i in associated:\n header_flat = [\n k for j, k in enumerate(headers) if l[j] == i['flat']\n ]\n if len(header_flat):\n header_flat = header_flat[0]\n MaskName = header_flat['maskname']\n if MaskName == \"IFU-2\":\n slits = 'both'\n elif MaskName == \"IFU-B\":\n slits = 'blue'\n elif MaskName == \"IFU-R\":\n slits = 'red'\n i['slits'] = slits\n\n if self.object_filter:\n objs = self.object_filter.split(',')\n sci_ims = [\n i for i in associated if (\n (i['obsclass'] == 'science') &\n (i['object'] in objs))]\n else:\n sci_ims = [i for i in associated if i['obsclass'] == 'science']\n\n if self.all_stars:\n std_ims = [\n i for i in associated if i['obsclass'] in ['partnerCal',\n 'progCal']]\n else:\n used_stds = [i['standard_star'] for i in sci_ims]\n std_ims = [i for i in associated if i['image'] in used_stds]\n\n # Get star info from starinfo.dat\n possible_names = np.concatenate((starinfo['obj'], starinfo['std'],\n starinfo['altname']))\n n_names = len(possible_names)\n\n for i, j in enumerate(possible_names):\n possible_names[i] = (j.lower()).replace(' ', '')\n\n for i in std_ims:\n # Removes the 'standard_star' key if the dictionary\n # element in question refers to a standard star.\n del i['standard_star']\n starname = (i['object'].lower()).replace(' ', '')\n\n try:\n stdstar_idx = (\n np.arange(n_names)[possible_names == starname] %\n (n_names / 3))[0]\n except:\n raise Exception(\n 'Standard star named {:s} not found in file {:s}'.\n format(starname, starinfo_file))\n\n i['stdstar'] = starinfo[stdstar_idx]['std']\n\n if starinfo[stdstar_idx]['caldir'] == 'gireds_data':\n i['caldir'] = pkg_resources.resource_filename(\n 'gireds', 'data/')\n else:\n i['caldir'] = starinfo[stdstar_idx]['caldir']\n\n self.sci = sci_ims\n self.std = std_ims\n\n # Writes the file association dictionary to an ASCII file\n # in the run directory.\n\n if not self.dry_run:\n try:\n os.mkdir(self.products_dir)\n except OSError as err:\n if err.errno == 17:\n pass\n else:\n raise err\n try:\n os.mkdir(self.run_dir)\n except OSError as err:\n if err.errno == 17:\n pass\n else:\n raise err\n\n if not self.dry_run:\n os.chdir(self.run_dir)\n json.dump(\n sci_ims, open('file_associations_sci.dat', 'w'),\n sort_keys=True, indent=4)\n json.dump(\n std_ims, open('file_associations_std.dat', 'w'),\n sort_keys=True, indent=4)","def getfile(self, name):\n try:\n datname = self.getname(name, \"dat\")\n tadname = self.getname(name, \"tad\")\n if datname and tadname:\n return Datafile(name, open(datname, \"rb\"), open(tadname, \"rb\"), self.kod)\n except IOError:\n return","def get_inputdata(path):\n import os, json\n \n json_list = list()\n for filename in os.listdir(path):\n if 'json' in filename:\n json_list.append(filename)\n\n SMI_list = list()\n MP_list = []\n for item in json_list:\n sample = json.load(open(path+item))\n smi = sample['smiles']\n mp = float(sample['Tm'])\n MP_list.append(mp)\n SMI_list.append(smi)\n \n return SMI_list, MP_list","def get_synthia_file_pairs(sequence='*', frame='*', ext='.png',\n direction='*', type2='*', gt_type='LABELS',\n root_folder=SYNTHIA_FOLDER, file_template=SYNTHIA_FILE_TEMPLATE):\n input_file_template = file_template.format(\n root=root_folder, type='RGB', type2=type2, direction=direction,\n len_fill=1, filler='*', seq=sequence, frame=frame, ext=ext)\n input_files = glob.glob(input_file_template)\n\n gt_file_template = file_template.format(\n root=root_folder, type=os.path.join('GT', gt_type), type2=type2, direction=direction,\n len_fill=1, filler='*', seq=sequence, frame=frame, ext=ext)\n gt_files = glob.glob(gt_file_template)\n\n assert (len(input_files) == len(gt_files))\n return sorted(input_files), sorted(gt_files)","def sgd_features(filepath=None):\n\n if filepath == None:\n filepath=load_sgd_tab()\n\n arabic_to_roman_dict=chromosomename_roman_to_arabic()[0]\n \n with open(filepath) as f:\n lines = f.readlines()\n\n\n feature_list = []\n feature_orf_dict = {}\n feature_ars_dict = {}\n feature_telomere_dict = {}\n feature_ltr_dict = {}\n feature_centromere_dict = {}\n feature_Xelement_dict = {}\n feature_intron_dict = {}\n feature_ncrna_dict = {}\n feature_ncexon_dict = {}\n feature_trna_dict = {}\n feature_snorna_dict = {}\n feature_teg_dict = {}\n feature_5p_utrintron_dict = {}\n feature_mas_dict = {}\n feature_snrna_dict = {}\n feature_rrna_dict = {}\n feature_ets_dict = {}\n feature_its_dict = {}\n feature_oor_dict = {}\n feature_telrna_dict = {}\n \n for line in lines:\n l = line.strip('\\n').split('\\t')\n if not l[1] in feature_list:\n feature_list.append(l[1])\n\n if not l[8].endswith('micron') and not l[8] == '':\n chromosome = arabic_to_roman_dict.get(int(l[8]))\n if l[1] == 'ORF':\n feature_orf_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'ARS':\n feature_ars_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'telomere':\n feature_telomere_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'long_terminal_repeat':\n feature_ltr_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'centromere':\n feature_centromere_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'X_element':\n feature_Xelement_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'intron':\n feature_intron_dict[l[6]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'ncRNA_gene':\n feature_ncrna_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'noncoding_exon':\n feature_ncexon_dict[l[6]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'tRNA_gene':\n feature_trna_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'snoRNA_gene':\n feature_snorna_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'transposable_element_gene':\n feature_teg_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'five_prime_UTR_intron':\n feature_5p_utrintron_dict[l[6]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'matrix_attachment_site':\n feature_mas_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'snRNA_gene':\n feature_snrna_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'rRNA_gene':\n feature_rrna_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'external_transcribed_spacer_region':\n feature_ets_dict[l[6]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'internal_transcribed_spacer_region':\n feature_its_dict[l[6]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'origin_of_replication':\n feature_oor_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n elif l[1] == 'telomerase_RNA_gene':\n feature_telrna_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\n\n\n \n\n\n genomicregions_list = ['ORF', 'ARS', 'Telomere', 'long_terminal_repeat',\n 'Centromere', 'X_element', 'Intron', 'ncRNA_gene',\n 'Noncoding_exon', 'tRNA_gene', 'snoRNA_gene',\n 'transposable_element_gene', 'five_prime_UTR_intron',\n 'matrix_attachment_site', 'snRNA_gene', 'rRNA_gene',\n 'external_transcribed_spacer_region',\n 'internal_transcribed_spacer_region',\n 'origin_of_replication', 'telomerase_RNA_gene']\n\n\n return(genomicregions_list, feature_orf_dict, feature_ars_dict, feature_telomere_dict,\n feature_ltr_dict, feature_centromere_dict, feature_Xelement_dict, feature_intron_dict,\n feature_ncrna_dict, feature_ncexon_dict, feature_trna_dict,\n feature_snorna_dict, feature_teg_dict, feature_5p_utrintron_dict,\n feature_mas_dict, feature_snrna_dict, feature_rrna_dict,\n feature_ets_dict, feature_its_dict, feature_oor_dict,\n feature_telrna_dict)","def _borehole_structure_data(self):\n file_loc = self.data_path / \"03_GeologicalMapping\" / \"02_BoreholeIntersections\"\n columns = [\"depth\", \"azimuth\", \"dip\", \"aperture\", \"type\"]\n\n data = []\n for borehole in self.boreholes:\n path = file_loc / (borehole + \"_structures.txt\")\n frame = pd.read_csv(\n path, sep=None, names=columns, skiprows=2, engine=\"python\"\n )\n frame[\"borehole\"] = borehole\n data.append(frame)\n df = pd.concat(data, ignore_index=True)\n return df","def parse_data(self, path_to_file):\n\n line_dict, rel_dict = self.create_dicts(path_to_file)\n \n line_df = self.create_dataframe(line_dict, ['line'])\n rel_df = self.create_dataframe(rel_dict, ['relation'])\n\n line_df['relation'] = rel_df['relation']\n\n return (line_df, rel_df)","def map_file_data(file_obj, file_events):\n file_as_dict = {\n \"premis:originalName\": file_obj.currentlocation,\n \"original_name\": escape(file_obj.originallocation),\n # needs investigation\n \"sanitized_file_name\": get_sanitized_file_name(\n get_file_name_cleanup(file_events)\n ),\n \"prov:generatedAtTime\": file_obj.modificationtime.strftime(\n \"%Y-%m-%dT%H:%M:%SZ\"\n ),\n \"premis:fixity\": {\n \"checksum_type\": convert_to_premis_hash_function(file_obj.checksumtype),\n \"Checksum\": file_obj.checksum,\n },\n \"premis:identifier\": file_obj.uuid,\n \"premis:size\": file_obj.size,\n \"file_name\": file_obj.label,\n # not sure if this is the file name or if we should stick with\n \"dct:FileFormat\": map_file_format_info(\n get_file_format_event(file_events), get_file_validation_event(file_events)\n ),\n \"file_validation\": map_file_validation_info(\n get_file_validation_event(file_events)\n ),\n \"file_normalization\": map_file_normalization_info(\n get_file_normalization_event(file_events)\n ),\n \"events\": list_file_events(file_events),\n }\n return file_as_dict","def open_and_read_file():\n file_path = sys.argv[1]\n #print file_path\n file_data = open(file_path, 'r')\n gettysburg = file_data.read()\n\n return gettysburg","def readStatFile(filePath):\n f = open(filePath, 'r')\n\n allStats = {}\n overviewStats = {}\n category = ''\n folder = ''\n method = ''\n\n for line in f:\n # Check if the line contains the 'cm' character and thus provides information of the specific folder\n if 'cm' in line:\n words = line.split()\n\n for word in words:\n if '/' in word:\n # All processed folder has either a /MoG or /SubSENSE folder. Exploit this to get the filename\n category = os.path.basename(os.path.dirname(os.path.dirname(os.path.normpath(filePath))))\n folder = os.path.basename(os.path.dirname(os.path.normpath(filePath)))\n method = word\n\n # Get the raw FP, TN, etc. count\n folderNumbers = {'TP': words[4], 'FP': words[5], 'FN': words[6], 'TN': words[7],\n 'ErrorShadow': words[8]}\n overviewStats[method] = folderNumbers\n\n\n # CHeck if line is not empty, does not contain certain characters, and that the folder has been found\n if '#' not in line and 'cm' not in line and line and folder and '\\n' != line and method:\n measures = line.split()\n\n isRealMeasure = True\n\n for measure in measures:\n if not RepresentsFloat(measure):\n isRealMeasure = False\n break\n\n\n if len(measures) == 7 and isRealMeasure:\n folderStats = {'recall': measures[0], 'specificity': measures[1], 'FPR': measures[2], 'FNR': measures[3], \n 'PBC': measures[4], 'precision': measures[5], 'f-measure': measures[6]}\n allStats[method] = folderStats\n\n method = ''\n\n return allStats, overviewStats","def stitchable_infiles(gdf):\n gdf['date'] = pd.DatetimeIndex(gdf.sensing_start).date\n for date, gdf_date in gdf.groupby('date'):\n for relative_orbit_number, gdf_rob in gdf_date.groupby('relative_orbit_number'):\n for passdir, gdf_passdir in gdf_rob.groupby('passdir'):\n for spacecraft, gdf_spacecraft in gdf_passdir.groupby('spacecraft'):\n for somode, gdf_somode in gdf_spacecraft.groupby('sensor_operational_mode'):\n fp = _get_footprint_union(gdf_spacecraft)\n meta = dict(\n date=date, relative_orbit_number=relative_orbit_number,\n passdir=passdir, sensor_operational_mode=somode,\n spacecraft=spacecraft, footprint_union=fp)\n yield meta, gdf_somode['filepath'].values.tolist()","def readbstfolder(BSTfilefolder):\n obsfileinfo = filefolder2obsfileinfo(BSTfilefolder)\n maxnrsbs = obsfileinfo['max_nr_bls']\n BSTdirls = os.listdir(BSTfilefolder)\n BSTfiles = [f for f in BSTdirls if f.endswith('.dat')]\n\n # Now read the BST pol data\n BST_dtype = numpy.dtype(('f8', (maxnrsbs,)))\n BSTdata = {}\n for BSTpolfile in BSTfiles:\n pol = BSTpolfile[-5]\n with open(os.path.join(BSTfilefolder, BSTpolfile), \"rb\") as fin:\n BSTdata[pol] = numpy.fromfile(fin, dtype=BST_dtype)\n return BSTdata, obsfileinfo"],"string":"[\n \"def get_file_data(filename):\",\n \"def raw_file_structure(self):\\n return None\",\n \"def get_data(found_file, created_file):\\n\\n try:\\n fh_f = fits.open(found_file)\\n print('Found file has: ', fh_f.info())\\n except Exception:\\n print(' FATAL ERROR: Unable to open found file ', found_file)\\n\\n try:\\n fh_c = fits.open(created_file)\\n print('Created file has: ', fh_c.info())\\n except Exception:\\n print(' FATAL ERROR: Unable to open created file ', created_file)\\n\\n try:\\n data_f = fh_f['SCI'].data\\n except Exception:\\n print(' FATAL ERROR: data for found data was expected in SCI extension')\\n\\n try:\\n data_c = fh_c['SCI'].data\\n except Exception:\\n try:\\n data_c = fh_c[0].data\\n except Exception:\\n print(' FATAL ERROR: created data expected in either SCI or 0 extensions')\\n\\n return fh_f, fh_c, data_f, data_c\",\n \"def extract_data(file_name):\\r\\n input_file_name = file_name\\r\\n \\r\\n def sort_data(input_file): \\r\\n \\\"\\\"\\\"This function extraxts the row data from the imput file\\\"\\\"\\\" \\r\\n with open(input_file,\\\"r\\\") as input_file: \\r\\n data = input_file.readlines() \\r\\n row_data = [] \\r\\n for line in data: \\r\\n row_data.append(line.split(', ')) \\r\\n return row_data \\r\\n \\r\\n data = sort_data(input_file_name)\\r\\n \\r\\n start_vertex = (float(data[0][0].split(' ')[0]),float(data[0][0].split(' ')[1]))\\r\\n end_vertex = (float(data[1][0].split(' ')[0]),float(data[1][0].split(' ')[1]))\\r\\n \\r\\n obstacles = {}\\r\\n for i in range(2, len(data)):\\r\\n lista = []\\r\\n for j in range(len(data[i])):\\r\\n lista.append( (float(data[i][j].split(' ')[0]),float(data[i][j].split(' ')[1])) )\\r\\n obstacles[i-1] = lista\\r\\n \\r\\n return start_vertex,end_vertex, obstacles\",\n \"def get_data(filename):\\n df = gpd.read_file(filename, index=\\\"OBJECTID\\\")\\n # Sort along the length column, which orders the points from top\\n # to bottom\\n fplencol = [x for x in df.columns if x.startswith(\\\"fpLen\\\")][0]\\n df = df.sort_values(fplencol, ascending=True)\\n df = run_checks(df)\\n snapdf = gpd.read_file(\\n filename.replace(\\\"smpldef3m\\\", \\\"snaps3m\\\"), index=\\\"OBJECTID\\\"\\n )\\n # Compute full rotation string\\n # OK, be careful here. Presently, the 8 char field covers\\n # 2010 thru 2017, so we rotate to cover the first and last years\\n # 2007 2011[1]\\n # 2008 2010[0]\\n # 2009 2011[1]\\n # 2018 2016[6]\\n # 2019 2017[7]\\n # 2020 2018[6]\\n s = df[\\\"CropRotatn_CY_2017\\\"]\\n df[\\\"landuse\\\"] = (\\n s.str[1]\\n + s.str[0]\\n + s.str[1]\\n + s\\n + s.str[6]\\n + s.str[7]\\n + s.str[6]\\n + s.str[7]\\n )\\n s = df[\\\"Management_CY_2017\\\"]\\n df[\\\"management\\\"] = (\\n s.str[1]\\n + s.str[0]\\n + s.str[1]\\n + s\\n + s.str[6]\\n + s.str[7]\\n + s.str[6]\\n + s.str[7]\\n )\\n return df, snapdf\",\n \"def get_gml_data(file_path):\\n\\n bbox = (2.34592e7,100+6.704e6,2.34603e7,700+6.704e6)\\n return gpd.read_file(file_path, bbox=bbox)\",\n \"def get_file(self) -> tuple:\\r\\n hash_md5 = hashlib.md5()\\r\\n with open(self.yara_base_file, \\\"rb\\\") as f:\\r\\n file_map = f.read()\\r\\n get_file_dict = get_matches(self, file_map)\\r\\n hash_md5.update(file_map)\\r\\n return hash_md5.hexdigest(), get_file_dict\",\n \"def get_content(self, file_path: str) -> Tuple[defaultdict, str]:\\n tags = self.__metadata__(file_path)\\n html = self.__html__(tags)\\n tags[\\\"file_path\\\"] = f\\\"images/gallery/{file_path.split(os.path.sep)[-1]}\\\"\\n self.image_paths.append(file_path)\\n return tags, html\",\n \"def loadBattleData(league):\\n path = os.path.dirname(os.path.realpath(__file__))\\n fString = None\\n try:\\n idx = LEAGUERANKS.index(league)\\n fString = path+RANKSTOWINLOSEFILES[idx]\\n except:\\n #No file associated with the league.\\n return None, None\\n\\n try:\\n with open(fString, \\\"r+\\\") as f:\\n battleData = json.loads(f.readline())\\n except Exception as e:\\n print(e)\\n return None, None\\n \\n fString = path+WINHTMLFILES[idx]\\n\\n try:\\n with open(fString, \\\"r+\\\") as f:\\n htmlData = json.loads(f.readline())\\n return battleData, htmlData\\n except:\\n return battleData, None\",\n \"def existing_village_file(kovetz):\\n try:\\n cat77 = nbt.NBTFile(kovetz)\\n except IOError:\\n raise Exception(\\\"Hmm. Unfortunately, the file requested does not exist :(\\\")\\n tick4 = cat77['data']['Tick'].value\\n return cat77, tick4\",\n \"def get_prep(file_name):\\n\\n headers = {\\n \\\"User-Agent\\\": \\\"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:60.0) Gecko/20100101 Firefox/60.0\\\"}\\n\\n url = \\\"https://rp18.ine.mx/assets/JSON/PRESIDENTE/NACIONAL/Presidente_NACIONAL.json\\\"\\n\\n with requests.get(url, headers=headers) as response:\\n\\n # Save a copy for future analysis.\\n with open(\\\"./raw_data/{}.json\\\".format(file_name), \\\"w\\\", encoding=\\\"utf-8\\\") as temp_file:\\n temp_file.write(response.text)\\n\\n candidates = list()\\n percentages = list()\\n votes = list()\\n colors = list()\\n\\n json_data = response.json()\\n\\n for item in json_data[\\\"votosCandidatoPartidoCoalicion\\\"]:\\n\\n name = item[\\\"nombreCandidatoPropietario\\\"]\\n\\n if item[\\\"siglasPartido\\\"] == \\\"CNR\\\":\\n name = \\\"Candidatos No Registrados\\\"\\n\\n if item[\\\"siglasPartido\\\"] == \\\"VN\\\":\\n name = \\\"Nulos\\\"\\n\\n color = \\\"#{}\\\".format(item[\\\"colorPartido\\\"])\\n colors.append(color)\\n\\n candidates.append(name)\\n percentages.append(float(item[\\\"porcentaje\\\"]))\\n votes.append(int(item[\\\"total\\\"]))\\n\\n return dict({\\\"candidates\\\": candidates, \\\"percentages\\\": percentages,\\n \\\"votes\\\": votes, \\\"colors\\\": colors, \\\"totalVotos\\\": json_data[\\\"totalVotos\\\"],\\n \\\"actasCapturadas\\\": json_data[\\\"actasCapturadas\\\"][\\\"porcentaje\\\"]})\",\n \"def metadata_obj(filelike):\\n\\tif test_hachoir_extension(filelike.name):\\n\\t\\tmetadata = metadata_for_filelike(filelike)\\n\\t\\tif metadata:\\n\\t\\t\\tdata = dict([\\n\\t\\t\\t\\t(data.key, data.values[0].value)\\n\\t\\t\\t\\tfor data in metadata\\n\\t\\t\\t\\tif data.values\\n\\t\\t\\t\\t])\\n\\t\\telse:\\n\\t\\t\\tdata=None\\n\\telif test_3D_extension(filelike.name):# 3D not in the extention \\n\\t\\tdata = {'mime_type':'model'}\\n\\telse:\\n\\t\\tdata = None\\n\\t\\t\\n\\treturn data\",\n \"def insert_good_data():\\n get_file_reply(files[0][0], files[0][1])\\n get_file_reply(files[1][0], files[1][1])\",\n \"def read_files():\\n with open(\\\"CvixLerC9.loc\\\") as loc, open(\\\"CvixLerC9.qua\\\") as qua:\\n qua_file = (qua.read().split('\\\\n'))\\n qua_file = qua_file[8:-1]\\n new_qua = []\\n for q in qua_file:\\n new_qua.append(q.split('\\\\t')) # [['1', '1.279502474'], ['3', '0.303712231']....]\\n\\n new_loc = {}\\n header = ''\\n read = False\\n for i in loc:\\n i = i.replace(\\\"\\\\n\\\", '')\\n if read:\\n for j in i:\\n if \\\" \\\" != j:\\n if header in new_loc.keys():\\n new_loc[header].append(j)\\n else:\\n new_loc[header] = [j]\\n if \\\"(a,b)\\\" in i:\\n header = i\\n read = True\\n else:\\n read = False\\n\\n elif read:\\n for j in i:\\n if \\\" \\\" != j:\\n if header in new_loc.keys():\\n new_loc[header].append(j)\\n else:\\n new_loc[header] = [j]\\n\\n return new_loc, new_qua\",\n \"def get_record_from_file(file_path, keys_to_use):\\n # Read these files 1 by 1 into JSON objects, put them into a tuple\\n with open(file_path) as artwork_file:\\n content = json.load(artwork_file)\\n \\n # Create an empty list, & for every key in the list, we extract the data & append to the record list,\\n # then return the data in tuple form\\n record = []\\n for field in keys_to_use:\\n record.append(content[field])\\n \\n return tuple(record)\",\n \"def obtain_pocket_data(dyn_id, traj_list) -> tuple:\\n\\n THRESHOLD_DRUGGABILITY = 200\\n\\n root = settings.MEDIA_ROOT\\n pock_path = os.path.join(root,\\\"Precomputed/MDpocket\\\")\\n # 3 level dictionary with: trajectory: pocketID: descriptors\\n pockets = {}\\n # 3 level dictionary with: trajectory: pocketID: path_to_coordinates_file.pdb\\n traj_pockID_coordfile = {}\\n # dictionary with: trajectory: path_to_isovalue_file.dx\\n traj_isovalueFile = {}\\n\\n for mytraj in traj_list:\\n\\n try:\\n # DEFINING PATHS\\n traj_id = mytraj[2]\\n traj_name = mytraj[1] \\n\\n traj_pock_path = os.path.join(pock_path,\\\"%s_mdpocket\\\"%(traj_name))\\n pockets_coords_path = os.path.join(traj_pock_path, \\\"DBSCANclustering_coordinates_pdb_%s\\\"%(traj_name))\\n pockets_json_txt = \\\"Final_OUTPUT_%s\\\"%(traj_name)\\n path_json_txt = os.path.join(traj_pock_path, pockets_json_txt)\\n\\n # ISOVALUE DICTIONARY\\n isovalue = os.path.join(traj_pock_path,\\\"mdpocket/mdpout_freq.dx\\\")\\n traj_isovalueFile[traj_name] = isovalue\\n\\n # COORDINATE FILE DICTIONARY\\n f = open(path_json_txt)\\n pockID_coordfile = {}\\n if os.path.isdir(pockets_coords_path):\\n for file in os.listdir(pockets_coords_path):\\n pocketid = int(file.split(\\\"_\\\")[0])\\n pockID_coordfile[pocketid] = file\\n traj_pockID_coordfile[traj_name] = pockID_coordfile\\n\\n # DESCRIPTORS DICTIONARY\\n pocket_data = json.load(f)\\n\\n # Obtaining % druggability using volumes\\n for pocket_dict in pocket_data[\\\"data\\\"]:\\n n_above_threshold = len([ v for v in pocket_dict[\\\"volumes\\\"] if v >= THRESHOLD_DRUGGABILITY ])\\n n_total = len(pocket_dict[\\\"volumes\\\"])\\n pocket_dict[\\\"perc_druggability\\\"] = round( (n_above_threshold / n_total) * 100)\\n\\n # DESCRIPTORS DICTIONARY\\n trajectory_pockData = {}\\n for descriptors in pocket_data['data']:\\n for key, value in descriptors.items():\\n\\n trajectory_pockData[descriptors['name']] = descriptors\\n pockets[traj_id] = pocket_data\\n\\n except FileNotFoundError:\\n print(\\\"[*] INFO - POCKET DATA: Pockets data not available for trajectory ID: \\\" + str(traj_id))\\n\\n return(pockets, traj_pockID_coordfile, traj_isovalueFile)\",\n \"def prepare_misc_data(self):\\n if 'misc_input_files' in self.man:\\n data = self.man['misc_input_files']\\n else:\\n return None\\n\\n data_new_format = {}\\n for item in data:\\n token = item['token']\\n if not token in data_new_format:\\n data_new_format[token] = []\\n data_new_format[token].append(item['file'])\\n return data_new_format\",\n \"def extract_data(file_name=default_file_name):\\n fille = abs_path(file_name)\\n try:\\n jfile = open(fille)\\n except FileNotFoundError:\\n create_file(fille)\\n jfile = open(fille)\\n data = json.load(jfile)\\n if(not 'Students' in data.keys()):\\n create_file(fille)\\n jfile = open(fille)\\n data = json.load(jfile)\\n return data\",\n \"def get_pocket_pdb_files(request, pocket_data) -> dict:\\n\\n # Unpack parameters\\n pockets, traj_pockID_coordfile, traj_isovalueFile = pocket_data\\n traj_name = request.POST.get(\\\"traj_name\\\")\\n pocketid_and_color_list = json.loads(request.POST.get(\\\"pocketid_and_color_list\\\"))\\n # Obtain each pocket's PDB file\\n pocket_pdbs = {}\\n for pocketID, color in map(lambda x: (x[\\\"id\\\"], x[\\\"color\\\"]), pocketid_and_color_list):\\n pocket_pdb_file = traj_pockID_coordfile[traj_name][str(pocketID)]\\n pocket_pdbs[pocketID] = (pocket_pdb_file, color)\\n\\n return pocket_pdbs\",\n \"def handle_uploaded_file(uploaded_file, duck_id, duck_name, comments):\\n title = 'Duck #' + str(duck_id) + ' (' + duck_name + ')'\\n tags = \\\"duckiehunt\\\"\\n\\n file_path = write_upload_to_file(uploaded_file, settings.UPLOAD_PATH)\\n photo_info = upload_to_flickr(file_path, title, comments, settings.FLICKR_PHOTO_IS_PUBLIC, tags)\\n return photo_info\",\n \"def read_gaf_out(go_path):\\n out = io.makedeephash()\\n header = []\\n temp = {}\\n for line in open(go_path, mode=\\\"r\\\"):\\n line = line.rstrip(\\\"\\\\n\\\")\\n if line.startswith(str(\\\"ID\\\") + \\\"\\\\t\\\"):\\n header = re.split(r\\\"\\\\t+\\\", line)\\n else:\\n things = re.split(r\\\"\\\\t+\\\", line)\\n temp = dict(zip(header, things))\\n if len(temp.keys()) > 0:\\n pr = str.upper(temp[\\\"GN\\\"])\\n for k in temp.keys():\\n # if the key is the same\\n if out[pr][k] and k != \\\"ID\\\" or \\\"GN\\\":\\n out[pr][k] = \\\";\\\".join([str(out[pr][k]), temp[k]])\\n elif k != \\\"ID\\\" or \\\"GN\\\":\\n out[pr][k] = temp[k]\\n return out\",\n \"def read_grp(fname):\\n global DAYS\\n uint_types = [DAYS,\\n 'Current crop type', \\n 'Current residue on ground type', \\n 'Previous residue on ground type', \\n 'Old residue on ground type', \\n 'Current dead root type', \\n 'Previous dead root type', \\n 'Old dead root type']\\n\\n meta = {}\\n data = None\\n header = []\\n\\n meta['fname'] = fname\\n meta['id'] = ''.join([L for L in fname if L in '0123456789'])\\n \\n fid = open(fname, 'rb')\\n for i, line in enumerate(fid.readlines()):\\n line_as_list = line.strip().split()\\n\\n if len(line_as_list) == 0:\\n continue\\n\\n elif line_as_list[0][0] == '#':\\n continue\\n\\n elif line_as_list[0] == 'int':\\n try:\\n meta[line[1]] = int(line[2])\\n except:\\n pass\\n \\n elif line_as_list[0] == 'float':\\n try:\\n meta[line[1]] = float(line[2])\\n except:\\n pass\\n\\n elif line_as_list[0] == 'char':\\n continue\\n\\n elif line_as_list[0][0] == '{':\\n cname = line.strip()[1:-1].replace(r'kg/m', r'kg*m**-1') \\\\\\n .replace(r'kg/m**2', r'kg*m**-2') \\\\\\n .replace(r'kg/m**3', r'kg*m**-3') \\\\\\n .replace(r'kg/m**4', r'kg*m**-4') \\\\\\n .replace(r'mm/hr', r'mm*hr**-1') \\\\\\n .replace(r'mm/h', r'mm*hr**-1') \\\\\\n .replace(r'm/day', r'm*day**-1') \\\\\\n .replace(r'g/cc', r'g*cc**-1') \\\\\\n .replace(r'kg-s/m**4', r'kg-s*m**-4') \\\\\\n .replace(r's/m', r's*m**-1') \\\\\\n .replace(r'Irrigation_volume_supplied/unit_area',\\n r'Irrigation_volume_supplied*unit_area**-1')\\n header.append(cname)\\n\\n else:\\n if len(header) == len(line_as_list):\\n \\n # if we are here and data == None we need to initialize the data dictionary\\n if data == None:\\n data = {}\\n for cname in header:\\n typecode = ('f', 'h')[any([cname==s for s in uint_types])]\\n data[cname] = array.array(typecode)\\n\\n for (cname, string) in zip(header, line_as_list):\\n if any([cname==s for s in uint_types]):\\n value = int(string)\\n else:\\n value = float(string)\\n\\n if cname == DAYS:\\n\\n if value in set(data[DAYS]):\\n break\\n\\n data[cname].append(value)\\n\\n else:\\n raise Exception('Failed to parse line %i, unexpected number of columns.'%(i+1))\\n \\n fid.close()\\n\\n # pack the table data into numpy arrays\\n for (cname, v) in data.items():\\n dtype = (np.float32, np.int16)[any([cname==s for s in uint_types])]\\n data[cname] = np.array(v, dtype=dtype)\\n\\n return (meta, data)\",\n \"def parse_cluedata(input_path: str):\\n\\n\\twith open(input_path, 'r') as clue_backup:\\n\\t\\tjson_structure = json.loads(clue_backup.read())\\n\\n\\tassert 'data' in json_structure, \\\".cluedata file does not have the expected structure\\\"\\n\\n\\treturn json_structure\",\n \"def get_info(frame_or_sketch_or_vid_path):\\n if \\\".mp4\\\" not in frame_or_sketch_or_vid_path:\\n # invalid file path ()\\n # TODO: allow other video extensions\\n return None\\n\\n ret_dict = {}\\n ret_dict[\\\"path\\\"] = frame_or_sketch_or_vid_path\\n ret_dict[\\\"file_name\\\"] = utils.get_file_name(frame_or_sketch_or_vid_path)\\n ret_dict[\\\"file_ext\\\"] = utils.get_file_ext(frame_or_sketch_or_vid_path)\\n\\n # find video file name = video_id\\n file_dir_last = utils.get_nth_parentdir(frame_or_sketch_or_vid_path)\\n\\n # file_dir_full = utils.get_file_path(frame_or_sketch_or_vid_path)\\n # file_name = utils.get_full_file_name(frame_or_sketch_or_vid_path)\\n\\n video_id = f\\\"{file_dir_last.split('.mp4_')[0]}.mp4\\\"\\n start_end_time = file_dir_last.split(\\\".mp4_\\\")[1]\\n start_end_time_parts = start_end_time.split(\\\"_\\\")\\n\\n # OLD\\n # tmp = frame_or_sketch_or_vid_path.rsplit(\\\"video_\\\")[1].replace(\\\".mp4\\\", \\\"\\\")\\n # tmp_parts = tmp.split(\\\"/\\\")[0].split(\\\"_\\\") # remove frame part if existent\\n # ret_dict[\\\"video_id\\\"] = tmp_parts[0]\\n # ret_dict[\\\"start_time\\\"] = float(tmp_parts[1])\\n # ret_dict[\\\"end_time\\\"] = ret_dict[\\\"start_time\\\"]\\n\\n ret_dict[\\\"video_id\\\"] = video_id\\n ret_dict[\\\"start_time\\\"] = float(start_end_time_parts[0])\\n if len(start_end_time_parts) > 1:\\n ret_dict[\\\"end_time\\\"] = float(start_end_time_parts[1])\\n\\n if ret_dict[\\\"file_ext\\\"] == \\\".jpg\\\":\\n ret_dict[\\\"frame\\\"] = int(ret_dict[\\\"file_name\\\"].split(\\\"_\\\")[1])\\n elif ret_dict[\\\"file_ext\\\"] == \\\".json\\\":\\n ret_dict[\\\"frame\\\"] = get_sketch_frame(ret_dict[\\\"path\\\"])\\n else:\\n ret_dict[\\\"fps\\\"] = get_fps(ret_dict[\\\"path\\\"])\\n ret_dict[\\\"start_frame\\\"] = time_to_frame(ret_dict[\\\"start_time\\\"], ret_dict[\\\"fps\\\"])\\n ret_dict[\\\"end_frame\\\"] = time_to_frame(ret_dict[\\\"end_time\\\"], ret_dict[\\\"fps\\\"])\\n return ret_dict\",\n \"def forge_files(self) -> Dict[str, BaseForge]:\\n\\t\\treturn self._forge_files\",\n \"def get_data_ge(logger, file):\\n fp = open(file, 'rb')\\n offset = 8192\\n\\n fp.seek(18)\\n size, nframes = st.unpack('<ih',fp.read(6))\\n if size != 2048:\\n logger.error('GE image size unexpected: '+str(size))\\n return None, 0, 0\\n\\n fsize = os.stat(str(fp).split(\\\"'\\\")[1]).st_size\\n nframes_calc = (fsize - offset)/(2*size**2)\\n\\n if nframes != nframes_calc:\\n logger.error('GE number frames unexpected: '+str(nframes))\\n return None, 0, 0\\n\\n pos = offset\\n fp.seek(pos)\\n\\n return fp, int(nframes_calc), size*size\",\n \"def get_file_data(self):\\n self.switch_row(self.PATTERN_INFO_ROW)\\n\\n # get background image file path\\n if self.row[0] != 'No image':\\n # set path to background image, and get/set screen size\\n self.bg_img_path = self.row[self.BG_IMAGE_INDEX]\\n self.screen_width = int(self.row[self.WIDTH_INDEX])\\n self.screen_height = int(self.row[self.HEIGHT_INDEX])\\n self.SCREEN_SIZE = self.screen_width, self.screen_height\\n self.bg = True\\n \\n # get number of landmarks\\n self.num_lndmrks = int(self.row[self.LNDMRK_NUM_INDEX])\\n\\n # get starting row number for mpo path data\\n self.data_start_row = self.num_lndmrks + 1\\n self.tot_data_rows = self.tot_rows - self.data_start_row\\n self.data_row_num = self.data_start_row\",\n \"def read_gif(self, filename):\\n blocks = {}\\n with open(os.path.join(self.template_dir, filename), 'rb') as gif_fd:\\n blocks['header'] = gif_fd.read(6)\\n assert blocks['header'] in (b'GIF87a', b'GIF89a')\\n blocks['lcd'] = gif_fd.read(7) # logical screen descriptor\\n assert blocks['lcd'].endswith(b'\\\\xe3\\\\x10\\\\x00') # gct of 16 colours\\n blocks['gct'] = gif_fd.read(16 * 3) # global colour table\\n blocks['img_descriptor'] = gif_fd.read(10) # image descriptor\\n assert blocks['img_descriptor'][0] == 0x2c\\n assert blocks['img_descriptor'][9] == 0\\n # img data\\n blocks['img_data'] = gif_fd.read(1) # LZW min code size\\n while True: # img data sub-blocks\\n blocks['img_data'] += gif_fd.read(1) # sub-block data size\\n if blocks['img_data'][-1] == 0:\\n break # final sub-block (size 0)\\n blocks['img_data'] += gif_fd.read(blocks['img_data'][-1])\\n assert gif_fd.read(1) == b'\\\\x3b' # trailer\\n return blocks\",\n \"def file_to_dictionary():\\n\\n return;\",\n \"def get_uploaded_struct(self):\\n parser = PDBParser()\\n structure = parser.get_structure('STRUCT_OBJ',\\n os.path.join(self.struct_dir, self.struct_name))\\n return structure\",\n \"def parse_files(usage: str, full_time: str, part_time: str, semester: str, total_courses: int) -> dict:\\n one = filter_for_semester(open(usage, 'r').readlines(), semester)\\n two = get_rows_with_usage(one)\\n usage_file = remove_duplicate_crn(two)\\n no_dup_r = remove_duplicate_royal(two)\\n full_time_file = open(full_time, 'r').readlines()\\n full_r = list()\\n part_r = list()\\n for x in full_time_file:\\n y = x.split(DELIMITER)\\n full_r.append(y[FAC_ROYAL])\\n part_time_file = open(part_time, 'r').readlines()\\n for x in part_time_file:\\n y = x.split(DELIMITER)\\n part_r.append(y[FAC_ROYAL])\\n full = list()\\n part = list()\\n staff = list()\\n for x in range(len(part_r)):\\n part_r[x] = part_r[x].strip(\\\"\\\\\\\"\\\")\\n for x in range(len(full_r)):\\n full_r[x] = full_r[x].strip(\\\"\\\\\\\"\\\")\\n for x in no_dup_r:\\n y = x.split(DELIMITER)\\n if y[USAGE_ROYAL] in full_r:\\n full.append(y)\\n elif y[USAGE_ROYAL] in part_r:\\n part.append(y)\\n else:\\n staff.append(y)\\n return {'semester_no_dup_crn': usage_file,\\n 'semester_no_dup_r': no_dup_r,\\n 'semester': two,\\n 'full_time': full,\\n 'len_full': len(full_time_file),\\n 'part_time': part,\\n 'len_part': len(part_time_file),\\n 'staff': staff,\\n 'total_courses': total_courses}\",\n \"def prepare_feature(ground_truth, file_name):\\n base_file_name = os.path.basename(file_name)\\n gtp = GroundtruthReader(ground_truth)\\n from_ground_truth = gtp.lookup_filename(base_file_name)\\n image = create_image(file_name)\\n if image is not None:\\n image_feature = image_to_array(image)\\n return {'image_feature': image_feature, 'labels': from_ground_truth}\\n else:\\n return None\",\n \"def get_file_chunks(file, model, workspace, header, user):\\n uri = (\\\"https://api.anaplan.com/1/3/workspaces/{}/models/{}/\\\"\\n \\\"files/{}/chunks/\\\").format(workspace, model, file)\\n response = requests.get(uri, headers = header)\\n return json.loads(response.text.encode(\\\"utf-8\\\"))\",\n \"def _get_file_data_object(self, file_path, spec_header):\\n logger.DLOG(\\\"Creating FVaRFileData object from file '%s'\\\", file_path)\\n return acm.Risk().CreateScenarioFileData(file_path,\\n spec_header.DelimiterChar(), spec_header.CommentChar())\",\n \"def readSurfaceGeo(b18path):\\n if not os.path.isfile(b18path):\\n print(\\\"b18 building file not found! Please check!\\\")\\n pass\\n else:\\n b18file = open(b18path,\\\"r\\\")\\n b18data = b18file.readlines()\\n srfGeoBlock = getDataParagraph(\\\"_EXTENSION_BuildingGeometry_START_\\\", \\\"_EXTENSION_BuildingGeometry_END_\\\", b18data)\\n #now get vertex's coordinate xyz\\n vertexdict = dict() #{vertexID:[x,y,z]}\\n srfbasicinfo = dict() #{surfaceID:[vertexID]}\\n srfInfo = dict() #{surfaceID:[vertices coordinate]}\\n for line in srfGeoBlock:\\n dline = line.split()\\n if \\\"vertex\\\" in dline:\\n vertexdict[int(dline[1])] = [float(xyz) for xyz in dline[2:]] #{vertexID:[x,y,z]}\\n if \\\"wall\\\" in dline or \\\"window\\\" in dline or \\\"floor\\\" in dline or \\\"ceiling\\\" in dline or \\\"roof\\\" in dline:\\n srfbasicinfo[int(dline[1])] = [[int(nrID) for nrID in dline[2:]],dline[0]] #{surfaceID:[[vertexID],construction]}\\n #print srfbasicinfo[int(dline[1])]\\n for key in srfbasicinfo.keys():\\n srfInfo[key] = []\\n for vertices in srfbasicinfo[key][0]:\\n srfInfo[key].append(vertexdict[vertices])\\n b18file.close()\\n return srfInfo,vertexdict,srfbasicinfo\\n #actually only need srfInfo\\n #just getting everything out for now, incase will need to use those\",\n \"def extract_from_game(game_path):\\n with open(game_path) as sgf_file:\\n game_data = sgf_file.read().encode('utf-8')\\n\\n try:\\n g = sgf.Sgf_game.from_bytes(game_data)\\n _, moves = sgf_moves.get_setup_and_moves(g)\\n except BaseException:\\n print(\\\"bad file: \\\", game_path)\\n return Counter(), {}\\n\\n return (extract_corners(moves), 1 if g.get_winner().lower() == 'b' else 0)\",\n \"def parse_file(self, path, max_resolution, threshold, proteins={}):\\n\\n \\\"\\\"\\\"\\n create regex pattern here so it is not done repeatedly while parsing file\\n\\n groups:\\n 0 - Protein ID\\n 1 - Chain ID\\n 2 - Length of protein chain\\n 3 - Exptl.\\n 4 - Resolution\\n 5 - R-factor\\n 6 - FreeRValue\\n \\\"\\\"\\\"\\n regex_str = '(\\\\w{4})(\\\\w)\\\\s+(\\\\d+)\\\\s+(\\\\w+)\\\\s+([\\\\d\\\\.]+)\\\\s+([\\\\d\\\\.]+)\\\\s+([\\\\d\\\\.]+)'\\n regex_pattern = re.compile(regex_str)\\n\\n printc('Processing: %s' % path)\\n\\n raw = None\\n try:\\n _file = gzip.open(path, 'r')\\n\\n #first line is labels, discard it\\n _file.readline()\\n\\n for line in _file:\\n match = regex_pattern.match(line)\\n if match:\\n groups = match.groups()\\n\\n if groups[0] in proteins:\\n # if protein already exists just update the additional\\n # chain information. The properties should not change\\n # between records in the selection file.\\n protein = proteins[groups[0]]\\n if not groups[1] in protein['chains']:\\n protein['chains'].append(groups[1])\\n #print 'Selecting Protein: %s Chain: %s Threshold: %s' % (groups[0],groups[1], threshold)\\n\\n else:\\n # protein is not in proteins dict yet create initial\\n # structure from parsed properties.\\n resolution = float(groups[4])\\n if resolution > 0 and resolution <= max_resolution:\\n proteins[groups[0]] = {\\n 'code':groups[0],\\n 'chains':[groups[1]],\\n 'resolution':groups[4],\\n 'rfactor':groups[5],\\n 'rfree':groups[6],\\n 'threshold':threshold\\n }\\n\\n #print 'Selecting Protein: %s Chain: %s Threshold: %s' % (groups[0],groups[1], threshold)\\n\\n finally:\\n if _file:\\n _file.close()\\n\\n return proteins\",\n \"def _testData(cls, name, asFile):\\n data = {\\n\\n # Input 1: one PNG image, except the data makes no real sense\\n \\\"input1\\\": \\\"\\\"\\\"89 PNG 0d0a1a0a\\n 0000000d.IHDR 00000003000000020800000000 b81f39c6\\n 00000004.gAMA 000186a0 31e8965f\\n 00000007.tIME 07de061b0b2624 1f307ad5\\n 00000008.IDAT 696d673164617461 ce8a4999\\n 00000000.IEND ae426082\\\"\\\"\\\",\\n\\n # Input 2: slightly different, data in two chunks\\n \\\"input2\\\": \\\"\\\"\\\"89 PNG 0d0a1a0a\\n 0000000d.IHDR 00000003000000020800000000 b81f39c6\\n 00000004.gAMA 000186a0 31e8965f\\n 00000004.IDAT 696d6732 0e69ab1d\\n 00000004.IDAT 64617461 6694cb78\\n 00000000.IEND ae426082\\\"\\\"\\\",\\n\\n # Expected output 1: both images as frames of an animation\\n \\\"anim12\\\": \\\"\\\"\\\"89 PNG 0d0a1a0a\\n 0000000d.IHDR 00000003000000020800000000 b81f39c6\\n 00000004.gAMA 000186a0 31e8965f\\n 00000008.acTL 0000000200000000 f38d9370\\n 0000001a.fcTL 000000000000000300000002\\n 0000000000000000056712340100 b4f729c9\\n 00000008.IDAT 696d673164617461 ce8a4999\\n 0000001a.fcTL 000000010000000300000002\\n 000000000000000000c800640100 1b92eb4d\\n 00000008.fdAT 00000002696d6732 9cfb89a3\\n 00000008.fdAT 0000000364617461 c966c076\\n 00000000.IEND ae426082\\\"\\\"\\\",\\n\\n # Expected output 2: first image as fallback, second as animation\\n \\\"still1anim2\\\": \\\"\\\"\\\"89 PNG 0d0a1a0a\\n 0000000d.IHDR 00000003000000020800000000 b81f39c6\\n 00000004.gAMA 000186a0 31e8965f\\n 00000008.acTL 0000000100000000 b42de9a0\\n 00000008.IDAT 696d673164617461 ce8a4999\\n 0000001a.fcTL 000000000000000300000002\\n 0000000000000000056712340100 b4f729c9\\n 00000008.fdAT 00000001696d6732 db5bf373\\n 00000008.fdAT 0000000264617461 f406e9c6\\n 00000000.IEND ae426082\\\"\\\"\\\",\\n\\n }\\n d = cls._hex2bin(data[name])\\n if asFile:\\n from sage.misc.temporary_file import tmp_filename\\n fn = tmp_filename(ext=\\\".png\\\")\\n with open(fn, 'wb') as f:\\n f.write(d)\\n return fn\\n return d\",\n \"def retrive_scanning_scheme(self, Nest_data_directory, file_keyword = 'PMT_0Zmax'):\\r\\n fileNameList = []\\r\\n# ImgSequenceNum = 0\\r\\n for file in os.listdir(Nest_data_directory):\\r\\n if file_keyword in file:\\r\\n fileNameList.append(file)\\r\\n \\r\\n RoundNumberList = []\\r\\n CoordinatesList = []\\r\\n for eachfilename in fileNameList:\\r\\n # Get how many rounds are there\\r\\n try:\\r\\n RoundNumberList.append(eachfilename[eachfilename.index('Round'):eachfilename.index('_Grid')])\\r\\n except:\\r\\n RoundNumberList.append(eachfilename[eachfilename.index('Round'):eachfilename.index('_Coord')])\\r\\n \\r\\n RoundNumberList = list(dict.fromkeys(RoundNumberList)) # Remove Duplicates\\r\\n \\r\\n CoordinatesList.append(eachfilename[eachfilename.index('Coord'):eachfilename.index('_PMT')])\\r\\n CoordinatesList = list(dict.fromkeys(CoordinatesList))\\r\\n \\r\\n# print(RoundNumberList, CoordinatesList, fileNameList)\\r\\n return RoundNumberList, CoordinatesList, fileNameList\",\n \"def getBMData(filename):\\n\\n data = {}\\n f = open(filename)\\n line = f.readline() \\n data['name'], data['gender'], data['age'] = [], [], []\\n data['division'], data['country'], data['time'] = [], [], []\\n while line != '':\\n split = line.split(',')\\n data['name'].append(split[0])\\n data['gender'].append(split[1])\\n data['age'].append(int(split[2]))\\n data['division'].append(int(split[3]))\\n data['country'].append(split[4]) \\n data['time'].append(float(split[5][:-1])) #remove \\\\n\\n line = f.readline()\\n f.close()\\n return data\",\n \"def read_reference_data():\\n return {f:read_local_file(f) for f in os.listdir(DATA_DIR)}\",\n \"def stat_file(self, path, info):\\n return {}\",\n \"def get_data(self, n=-1): \\n try:\\n return Profile(os.path.join(self.name, self.files[n]))\\n except IndexError:\\n return None\",\n \"def get_data(fname: str) -> dict:\\n with open(fname) as f:\\n return [rec.split() for rec in f.read().split(\\\"\\\\n\\\\n\\\")]\",\n \"def get_additional_data_from_files(df, file_description): # file description one of [\\\"video\\\", \\\"eaf\\\", \\\"seg\\\", \\\"gentle\\\"]\\n if file_description == \\\"gentle\\\":\\n file_folder = FILE_BASE + \\\"/gentle/\\\"\\n is_gentle_file = True\\n else:\\n file_folder = FILE_BASE + \\\"/original/\\\"\\n is_gentle_file = False\\n\\n file_df = None\\n\\n if file_description not in list(FILE_DESCRIPTIONS_TO_EXT.keys()):\\n print(\\\"Unknown file description! Don't know what to do with %s files...\\\" % file_description)\\n return None\\n\\n else:\\n print(\\\"Load and extract information from %s files...\\\" % file_description)\\n #pbar = tqdm.tqdm(total = len(np.unique(df[\\\"source_file\\\"])),desc='Files', position=0,leave=True,file=sys.stdout)\\n #file_log = tqdm.tqdm(total=0, position=1, bar_format='{desc}',leave=True,file=sys.stdout)\\n print(\\\"Total files to laod and preprocess: \\\", len(np.unique(df[\\\"source_file\\\"])))\\n \\n for i,file in enumerate(np.unique(df[\\\"source_file\\\"])):\\n if i%100 == 0:\\n print(\\\"File: \\\",i)\\n \\n filepath = file_folder + get_file_path(file,is_gentle_file=is_gentle_file) + FILE_DESCRIPTIONS_TO_EXT[file_description]\\n\\n if file_description == \\\"video\\\":\\n file_i_df = mp4_file_processing.get_word_video_snippet_size(df, filepath)\\n elif file_description == \\\"eaf\\\":\\n speech_annotation_eaf_data, gesture_eaf_data = eaf_file_processing.read_eaf(filepath)\\n file_i_df = eaf_file_processing.map_gestures_to_annotation(speech_annotation_eaf_data, gesture_eaf_data, remove_pauses=False)\\n file_i_df = eaf_file_processing.binary_encode_gestures(file_i_df, gesture_column=\\\"gesture\\\")\\n\\n elif file_description == \\\"seg\\\":\\n file_i_df = seg_file_processing.get_seg_file_pos_info(filepath)\\n\\n elif file_description == \\\"gentle\\\":\\n file_i_df = gentle_file_processing.get_gentle_file_transcripts(filepath)\\n \\n else:\\n print(\\\"Unknown file format!!!\\\")\\n return \\n\\n if file_df is None:\\n file_df = file_i_df\\n else:\\n file_df = pd.concat([file_df, file_i_df], ignore_index=True)\\n\\n #file_log.set_description_str(f'Processed file: {file}')\\n #pbar.update(1)\\n #sleep(0.02)\\n #file_log.close()\\n #pbar.close()\\n return file_df\",\n \"def parse_path_image(proto_path, instance, model_path):\\n\\n # split the file name into parts\\n name_parts = proto_path.split('_')\\n # get the base path for the current model\\n base_path = eval('instance.request.user.profile.' + model_path)\\n # get the different parameters from the model\\n # get the date\\n date = datetime.datetime.strptime(name_parts[0], '%Y%m%d')\\n\\n # get the animal\\n animal = Mouse.objects.get(mouse_name='_'.join(name_parts[1:4]))\\n\\n # get the region\\n region = name_parts[4]\\n\\n # define the path for the different files\\n bfpath = join(base_path, '_'.join((name_parts[0], animal.mouse_name, 'BF', region)) + '.tif')\\n flpath = bfpath.replace('BF', 'FL')\\n flgreenpath = bfpath.replace('BF', 'FLgreen')\\n otherpath = bfpath.replace('BF', 'OTHER')\\n\\n return {'owner': instance.request.user,\\n 'mouse': animal,\\n 'window_date': date,\\n 'bfPath': bfpath,\\n 'flPath': flpath,\\n 'flgreenPath': flgreenpath,\\n 'otherPath': otherpath,\\n 'region': region}\",\n \"def read_sample(sample_path):\\n files = os.listdir(sample_path)\\n json_path = [f for f in files if f.endswith('_read-info.json')]\\n assert len(json_path) == 1, 'There should be exactly 1 *_read-info.json file in the sample (.smpl)'\\n # get base for sample\\n with open(os.path.join(sample_path, json_path[0]), 'r') as f:\\n sample = json.load(f)\\n # get sample info\\n info_path = [f for f in files if f.endswith('info.csv')]\\n assert len(info_path) == 1, 'There should be exactly 1 *_info.csv file in the sample (.smpl)'\\n sample['info'] = pd.read_csv(os.path.join(sample_path, info_path[0]))\\n info_path = os.path.join(sample_path, info_path[0])\\n # get individual sample\\n regex = re.compile(r'id-\\\\d*_t-\\\\d*')\\n pairs = [f for f in files if len(regex.findall(f)) > 0]\\n for str_pair in pairs:\\n pair_dir = os.path.join(sample_path, str_pair)\\n pair_dict = {}\\n # get df\\n df_path = os.path.join(pair_dir, str_pair + '_df.csv')\\n pair_dict['df'] = pd.read_csv(df_path)\\n pair_dict['df_path'] = df_path\\n pair_dict['info_path'] = info_path\\n # get tracks\\n tracks_path = os.path.join(pair_dir, str_pair + '_tracks.zarr')\\n pair_dict['tracks'] = zarr.open(tracks_path)\\n # get b_box\\n bbox_path = os.path.join(pair_dir, str_pair + '_bbox.json')\\n with open(bbox_path, 'r') as f:\\n bbox = json.load(f)\\n new_bbox = {}\\n for key in bbox.keys():\\n args = list(bbox[key])\\n new_bbox[key] = slice(*args)\\n pair_dict['b_box'] = new_bbox\\n # find out if corrs exist and read if so\\n corr_path = [f for f in os.listdir(pair_dir) if f.endswith('_corr.json')]\\n if len(corr_path) > 0:\\n with open(os.path.join(pair_dir, corr_path[0]), 'r') as f:\\n corr = json.load(f)\\n pair_dict['corr'] = corr\\n # if image exists, read\\n img_path = os.path.join(pair_dir, str_pair + '_image.zarr')\\n if os.path.exists(img_path):\\n img = zarr.open(img_path)\\n #print(img, img_path)\\n pair_dict['image'] = img\\n # if labels exist, read\\n lab_path = os.path.join(pair_dir, str_pair + '_labels.zarr')\\n if os.path.exists(lab_path):\\n lab = zarr.open(lab_path)\\n #print(lab.shape)\\n pair_dict['labels'] = lab\\n # add pair to sample\\n id_re = re.compile(r'id-\\\\d*')\\n ID = id_re.findall(str_pair)[0][3:]\\n t_re = re.compile(r't-\\\\d*')\\n t = t_re.findall(str_pair)[0][2:]\\n pair = (int(ID), int(t))\\n sample[pair] = pair_dict\\n #print(str_pair, pair)\\n #print(list(sample.keys()))\\n #print(list(sample[eval(pairs[0])].keys()))\\n return sample\",\n \"def _read_pairs(self):\\n pairs = []\\n with open(self.pairs_path, 'r') as f:\\n for line in f.readlines()[1:]: # skip header\\n pair = line.strip().split()\\n pairs.append(pair)\\n\\n file_ext = 'jpg'\\n lfw_dir = self.images_root_path\\n path_list = []\\n\\n for pair in pairs:\\n if len(pair) == 3:\\n path0 = osp.join(lfw_dir, pair[0], pair[0] + '_' + '%04d' % int(pair[1]) + '.' + file_ext)\\n id0 = pair[0]\\n path1 = osp.join(lfw_dir, pair[0], pair[0] + '_' + '%04d' % int(pair[2]) + '.' + file_ext)\\n id1 = pair[0]\\n issame = True\\n elif len(pair) == 4:\\n path0 = osp.join(lfw_dir, pair[0], pair[0] + '_' + '%04d' % int(pair[1]) + '.' + file_ext)\\n id0 = pair[0]\\n path1 = osp.join(lfw_dir, pair[2], pair[2] + '_' + '%04d' % int(pair[3]) + '.' + file_ext)\\n id1 = pair[0]\\n issame = False\\n\\n path_list.append((path0, path1, issame, id0, id1))\\n\\n # skf = StratifiedKFold(n_splits=10, shuffle=True, random_state=42)\\n\\n # dataset = []\\n # for _, test_index in skf.split(np.zeros_like(path_list), [item[2] for item in path_list]):\\n # for idx in test_index:\\n # dataset.append(path_list[idx])\\n\\n # return dataset\\n return path_list\",\n \"def get_files_io():\\n if GC.conf['general']['training']:\\n files_zip = {\\n 'raw': os.path.join(COOKED_DATA, 'train.txt'),\\n 'new': os.path.join(COOKED_DATA, 'train_new.txt'),\\n 'norm': os.path.join(COOKED_DATA, 'train_norm.txt'),\\n 'manu': os.path.join(RAW_DATA, 'others', 'temp_updt_manu.txt'),\\n 'labels': os.path.join(TRAIN_DATA, 'train_norm.txt_labels.pkl'),\\n 'segll': os.path.join(TRAIN_DATA, 'train_norm.txt_seginf_loglab.pkl'),\\n 'segdl': os.path.join(TRAIN_DATA, 'train_norm.txt_seginf_deeplog.pkl'),\\n 'struct': os.path.join(TRAIN_DATA, 'train_norm.txt_structured.csv'),\\n 'output': TRAIN_DATA\\n }\\n else:\\n files_zip = {\\n 'raw': os.path.join(COOKED_DATA, 'test.txt'),\\n 'new': os.path.join(COOKED_DATA, 'test_new.txt'),\\n 'norm': os.path.join(COOKED_DATA, 'test_norm.txt'),\\n 'labels': os.path.join(TEST_DATA, 'test_norm.txt_labels.pkl'),\\n 'segll': os.path.join(TEST_DATA, 'test_norm.txt_seginf_loglab.pkl'),\\n 'segdl': os.path.join(TEST_DATA, 'test_norm.txt_seginf_deeplog.pkl'),\\n 'map_norm_raw': os.path.join(TEST_DATA, 'map_norm_raw.pkl'),\\n 'map_norm_rcv': os.path.join(TEST_DATA, 'map_norm_rcv.pkl'),\\n 'norm_rcv': os.path.join(TEST_DATA, 'test_norm_rcv.txt'),\\n 'struct': os.path.join(TEST_DATA, 'test_norm.txt_structured.csv'),\\n 'struct_rcv': os.path.join(TEST_DATA, 'test_norm_rcv.txt_structured.csv'),\\n 'top': os.path.join(TEST_DATA, 'analysis_summary_top.txt'),\\n 'sum': os.path.join(TEST_DATA, 'analysis_summary.csv'),\\n 'rst_llab': os.path.join(TEST_DATA, 'results_loglab.csv'),\\n 'rst_dlog': os.path.join(TEST_DATA, 'results_deeplog.txt'),\\n 'rst_llzr': os.path.join(TEST_DATA, 'results_loglizer.csv'),\\n 'dbg': os.path.join(TEST_DATA, 'debug.csv'),\\n 'output': TEST_DATA\\n }\\n return files_zip\",\n \"def make_file_dict():\\r\\n fileDict = {'pageUrls': [],\\r\\n 'pageFileNames': [],\\r\\n 'pageIds': [],\\r\\n 'fileUrls': [],\\r\\n 'fileIds': [],\\r\\n 'fileNames': [],\\r\\n 'cssUrls': [],\\r\\n 'cssFileNames': [],\\r\\n 'imgUrls': [],\\r\\n 'imgFileNames': []}\\r\\n return fileDict\",\n \"def gbk_parse(fname):\\n fhand = _open_file(gbkfname)\\n unk = 1 \\n\\n for record in SeqIO.parse(fhand, \\\"genbank\\\"):\\n\\n gene_tags = dict()\\n tx_tags = collections.defaultdict(list) \\n exon = collections.defaultdict(list) \\n cds = collections.defaultdict(list) \\n mol_type, chr_id = None, None \\n\\n for rec in record.features:\\n\\n if rec.type == 'source':\\n mol_type = rec.qualifiers['mol_type'][0]\\n try:\\n chr_id = rec.qualifiers['chromosome'][0]\\n except:\\n chr_id = record.name \\n continue \\n\\n strand='-'\\n strand='+' if rec.strand>0 else strand\\n \\n fid = None \\n try:\\n fid = rec.qualifiers['gene'][0]\\n except:\\n pass\\n\\n transcript_id = None\\n try:\\n transcript_id = rec.qualifiers['transcript_id'][0]\\n except:\\n pass \\n\\n if re.search(r'gene', rec.type):\\n gene_tags[fid] = (rec.location._start.position+1, \\n rec.location._end.position, \\n strand,\\n rec.type,\\n rec.qualifiers['note'][0])\\n elif rec.type == 'exon':\\n exon[fid].append((rec.location._start.position+1, \\n rec.location._end.position))\\n elif rec.type=='CDS':\\n cds[fid].append((rec.location._start.position+1, \\n rec.location._end.position))\\n else: \\n # get all transcripts \\n if transcript_id: \\n tx_tags[fid].append((rec.location._start.position+1,\\n rec.location._end.position, \\n transcript_id,\\n rec.type))\\n # record extracted, generate feature table\\n unk = feature_table(chr_id, mol_type, strand, gene_tags, tx_tags, cds, exon, unk)\\n \\n #break\\n fhand.close()\",\n \"def get_progress_file_info(filename):\\n # Open the file and read it\\n with open(filename,'r') as f:\\n data = f.readlines()\\n # Eat whitespace\\n data = [s.lstrip().rstrip() for s in data]\\n # Split the strings in each line \\n data[0] = data[0].split(' ')\\n data[1] = data[1].split(\\\"/\\\")\\n # Now, based on position, we can start getting parameters\\n current_sweep,final_sweep = [int(i) for i in data[1]]\\n target_area = int(data[0][0])\\n area_damping = float(data[0][1])\\n save_every_n_sweeps = int(data[0][-1])\\n if len(data[0]) == 3:\\n target_std = default_target_std\\n std_damping = default_std_damping\\n else:\\n target_std,std_damping = [float(s) for s in data[0][-2:-1]]\\n # Gather data function is, of course, gather_data_to_1_file\\n gather_data_function = output.gather_data_to_1_file\\n # Same for algorithm\\n algorithm = default_algorithm\\n # v5 and v6 damping don't matter\\n v5damping = default_v5damping\\n v6damping = default_v6damping\\n # The filename we want to output is the same file but with\\n # *.boundary2p1 at the end.\\n filename = filename.rstrip(output.tracking_suffix)+output.output_suffix\\n # Return the parameters as a tuple\\n params = parameters(filename,\\n target_area,area_damping,\\n target_std,std_damping,\\n current_sweep,final_sweep,\\n save_every_n_sweeps,\\n v5damping,v6damping,\\n algorithm,\\n gather_data_function)\\n return params\",\n \"def read_file(file):\\n if opts.input_type == 'fits':\\n data = fileio.read_fits(file)\\n else:\\n data = fileio.read_ascii(file)\\n c_id = data[0,:]\\n g_num = np.array(range(len(c_id)), dtype = 'int')\\n g_id = data[3,:]\\n g_ra = np.array(data[4,:], dtype = 'float')\\n g_dec = np.array(data[5,:], dtype = 'float')\\n g_z = np.array(data[6,:], dtype = 'float')\\n return c_id, g_num, g_id, g_ra, g_dec, g_z\",\n \"def parse_gff(g):\\n # We also want to store the mRNA->gene information!\\n mrna_par = {}\\n # And the CDS->mRNA information\\n cds_dat = {}\\n with open(g, 'r') as f:\\n for line in f:\\n # if the line is empty or starts with a #, we will skip it\\n if line.startswith('#') or line == '\\\\n':\\n continue\\n else:\\n tmp = line.strip().split('\\\\t')\\n feat_type = tmp[2]\\n if feat_type == 'mRNA':\\n meta = tmp[8].split(';')\\n for m in meta:\\n if m.startswith('ID='):\\n tx_id = m.split('=')[1]\\n if m.startswith('Parent='):\\n tx_par = m.split('=')[1]\\n mrna_par[tx_id] = tx_par\\n elif feat_type == 'CDS':\\n scaf = tmp[0]\\n start = tmp[3]\\n end = tmp[4]\\n strand = tmp[6]\\n phase = tmp[7]\\n meta = tmp[8].split(';')\\n for m in meta:\\n if m.startswith('ID='):\\n cds_id = m.split('=')[1]\\n if m.startswith('Parent='):\\n cds_par = m.split('=')[1]\\n if strand == '-':\\n strand = -1\\n else:\\n strand = 1\\n # Watch out for transcripts where there are multiple CDS.\\n # This will require a nested dictionary of lists.\\n if cds_par in cds_dat:\\n pass\\n else:\\n cds_dat[cds_par] = {}\\n if cds_id in cds_dat[cds_par]:\\n pass\\n else:\\n cds_dat[cds_par][cds_id] = []\\n # We want to make a SequenceFeature for each CDS chunk\\n # Keep in mind that GFF is 1-based, so we have to adjust\\n # the start position!\\n cds_feat = SeqFeature(\\n FeatureLocation(int(start)-1, int(end), strand=strand),\\n type=\\\"CDS\\\",\\n id=cds_id)\\n # Add some qualifiers to modify the behavior\\n # Use the \\\"standard\\\" genetic code from NCBI\\n cds_feat.qualifiers['transl_tabl'] = [1]\\n # Then, append it into the corresponding dictionary item\\n # keeping the chromosome (scaffold) name and phase with it\\n cds_dat[cds_par][cds_id].append((cds_feat, scaf, phase))\\n else:\\n continue\\n return (mrna_par, cds_dat)\",\n \"def test_file_access():\\n file = gff.GFFFile()\\n entry_scaffold = (\\\"ab\\\", \\\"cd\\\", 1, 2, None, None, None, {\\\"Id\\\":\\\"foo\\\"})\\n entry = (\\\"a\\\",) + entry_scaffold\\n file.append(*entry)\\n assert file[0] == entry\\n file.append(*((\\\"b\\\",) + entry_scaffold))\\n file.insert(1, *((\\\"c\\\",) + entry_scaffold))\\n file[1] = (\\\"d\\\",) + entry_scaffold\\n file.insert(3, *((\\\"e\\\",) + entry_scaffold))\\n del file[2]\\n assert [seqid for seqid, _, _, _, _, _, _, _, _ in file] \\\\\\n == [\\\"a\\\", \\\"d\\\", \\\"e\\\", ]\",\n \"def get_g(file_name):\\n \\n r,g = np.loadtxt(file_name, dtype = 'float', unpack = 'true')\\n \\n return r,g\",\n \"def get(self):\\n data = []\\n full_path = self.get_current_file()\\n\\n if self.is_allowed(full_path):\\n data = self.get_file_info(full_path)\\n else:\\n abort(403, message=\\\"You are not allowed to this path\\\")\\n\\n result = {\\\"data\\\": data}\\n return result\",\n \"def setup_data( self ):\\n with open( f'{project_dir}/data/05_source_key_data.json', 'r', encoding='utf-8' ) as f:\\n dct = json.loads( f.read() )\\n with open( f'{project_dir}/data/04_snapshot_open_textbook.json', 'r', encoding='utf-8' ) as f:\\n lst = json.loads( f.read() )\\n return ( dct, lst )\",\n \"def read_drugable_genes(mypath):\\n drug = pd.read_csv('data/drugability/interactions.tsv', sep='\\\\t')\\n drug_types = ['inhibitor', 'antagonist', 'blocker', 'channel blocker', 'gating inhibitor', 'negative modulator', 'channel blocker,gating inhibitor',\\n 'allosteric modulator,antagonist', 'inhibitor allosteric modulator', 'suppressor', 'antagonist,inhibitor']\\n drug = drug[drug.interaction_types.isin(drug_types)]\\n cts = drug.groupby(['drug_name', 'interaction_claim_source'])['gene_name'].nunique().sort_values(ascending=True)\\n single_drug_impact = cts[cts==1].copy().index.to_series().reset_index()['drug_name'].unique()\\n drug = drug[drug['drug_name'].isin(single_drug_impact)].dropna(subset=['gene_name'])\\n\\n # create a table of gene 2 drug relationships\\n gene2drug = drug.groupby('gene_name')['drug_name'].agg(lambda x: ','.join(list(set(x)))).reset_index()\\n #gene_names = drug['gene_name'].unique()\\n return gene2drug\",\n \"def parse(self):\\n results = {}\\n\\n # get the signature info via the codesign utility\\n args = [\\\"codesign\\\",\\\"-dvvvv\\\", self.file_name]\\n proc = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\\n output, error_output = proc.communicate()\\n if proc.returncode: #error, probably file not signed\\n results[\\\"signature\\\"] = error_output\\n else:\\n results[\\\"signature\\\"] = output\\n\\n #get the file object\\n file_object = open(self.file_name, 'rb')\\n\\n\\n #Use the macho library to parse out some structures\\n pFile = MachO(self.file_name)\\n\\n #if this is a fat file, it will have multiple Mach-O objects inside it\\n results[\\\"FAT_header\\\"] = self.parseFATHeader(file_object, pFile)\\n\\n #parse all the Mach-O headers\\n i = 1\\n for h in pFile.headers:\\n results[\\\"MachO_header\\\" + str(i)] = self.parseMachOHeader(h, file_object)\\n i +=1\\n\\n #close the file\\n file_object.close()\\n\\n #return the dict of results\\n return results\",\n \"def get_content(self, file_path: str) -> Tuple[defaultdict, str]:\\n if not os.path.exists(file_path): # If file doesn't exist\\n raise FileNotFoundError(f\\\"{fg(1)} Could not find file: {file_path}{fg(15)}\\\\n\\\")\\n html = self.__html__(file_path)\\n metadata = self.__metadata__()\\n return metadata, html\",\n \"def file_init():\\r\\n answer_files, ran, answers = initialize_files(\\\"DBF_\\\", 15, \\\".txt\\\")\\r\\n answer_files, answers = file_scan(answer_files, ran, answers)\\r\\n answer_files2, answers = open_read_files(answer_files, answers)\\r\\n stor_lib = group(answer_files2, answers)\\r\\n return stor_lib\",\n \"def parse(cls, raw_folder: str) -> Dict[str, Any]:\\n folder_path = os.path.abspath(raw_folder)\\n data = dict()\\n files = os.listdir(folder_path)\\n for file in files:\\n if is_ignored(file):\\n continue\\n try:\\n file = os.path.join(raw_folder, file)\\n datum = cls.process_file(file)\\n except FileNotCompatible:\\n continue\\n\\n _, kwrd = os.path.split(file)\\n kwrd = os.path.splitext(kwrd)[0]\\n data[kwrd] = datum\\n\\n return data\",\n \"def file_data(self):\\n return self.read(self.file)\",\n \"def recognize_pic(path):\\n results = recognize(path, access_token, cookie, fb_dtsg)\\n\\n names = [str(result['name']) for result in results]\\n print ('%s contains %s' % (path, names))\\n\\n return {\\n \\\"filename\\\": path,\\n \\\"friends\\\": names\\n }\",\n \"def load_file(fpath):\\n sick_data = {'X_A': [], 'X_B': [], 'y': []}\\n with open(fpath, 'r', encoding='utf-8') as f:\\n for line in f:\\n text = line.strip().split('\\\\t')\\n sick_data['X_A'].append(text[5].split())\\n sick_data['X_B'].append(text[6].split())\\n sick_data['y'].append(float(text[4]))\\n return sick_data\",\n \"def parse_file(filename):\\n filepath = root + filename\\n try:\\n if filename.endswith('.txt'):\\n with open(filepath) as file:\\n return file.read().splitlines()\\n elif filename.endswith('.csv'):\\n reader = csv.reader(open(filepath))\\n result = {}\\n for row in reader:\\n key = row[0]\\n result[key] = row[1]\\n return result\\n except FileNotFoundError:\\n with open(filepath,\\\"w+\\\") as file:\\n append_string_to_textfile(filename, \\\"Placeholder\\\")\\n print(\\\"here\\\")\\n return (parse_file(filename))\",\n \"def readFile(file_name):\\n if file_name.split('.')[-1] == 'thid':\\n x,m,w = readThid(file_name)\\n e = np.empty_like(x)\\n e[:] = np.nan\\n return x,m,w,e\\n else:\\n return readParams(file_name)\",\n \"def parse_files():\\n focus, stars, errors = [], [], []\\n\\n # Parse the plot file.\\n with open(tempfile.gettempdir() + '/cuplt.tmp') as current_plot:\\n # Record the focus vector.\\n for component in current_plot.readline().split():\\n focus.append(float(component))\\n\\n # Record all of the stars.\\n for line in current_plot:\\n star = []\\n for component in line.split():\\n star.append(float(component))\\n stars.append(star)\\n\\n # If desired, parse the error file.\\n if err_flag:\\n with open(tempfile.gettempdir() + '/errplt.tmp') as error_plot:\\n for line in error_plot:\\n error = []\\n\\n for a, component in enumerate(line.split()):\\n if a < 4:\\n error.append(float(component))\\n else:\\n error.append(component)\\n errors.append([error])\\n\\n # Return all items as a dictionary.\\n return {'fov': fov, 'focus': focus, 'stars': stars, 'errors': errors}\",\n \"def save_file():\\n generic = pull_list()\\n result = list()\\n i = 0\\n while True:\\n try:\\n if generic[i].startswith('CVE'):\\n cve_pattern = \\\"^CVE-\\\\d+-\\\\d+|^CVE-\\\\d+-[X]+\\\"\\n header = re.findall(cve_pattern, generic[i])[0]\\n i += 1\\n notes = list()\\n while not generic[i].startswith('CVE'):\\n commit_pattern = \\\"http[s]?:\\\\/\\\\/.+commit\\\\/[\\\\S]+\\\"\\n if re.search(commit_pattern, generic[i]):\\n link = re.findall(commit_pattern, generic[i])\\n notes.append(link[0])\\n i += 1\\n if notes != list():\\n result.append(Data(header, notes))\\n except IndexError:\\n print('Finished')\\n break\\n return result\",\n \"def creeStructureDonnees(fileName):\\n with open(fileName, 'r') as source:\\n # Enregistre les caracteristiques de l'instance dans la variable carac\\n r, s, u, p, m = source.readline().split()\\n carac = {'R': int(r), 'S': int(s), 'U': int(u), 'P': int(p), 'M': int(m)}\\n dicoObstacles = {}\\n dicoRangees = {}\\n \\n # Enregistre dans le dictionnaire dicoObstacles les slots indisponibles tel que :\\n # - cle = numero de la rangee\\n # - valeur = liste de numeros de slot qui sont indisponibles\\n for i in range(0, carac['R']):\\n dicoObstacles[str(i)] = []\\n dicoRangees[str(i)]= ['' for j in range(carac['S'])]\\n \\n i = 0\\n while i < carac['U']:\\n row, slot = source.readline().split()\\n dicoObstacles[str(row)].append(int(slot))\\n dicoRangees[str(row)][int(slot)] = 'x'\\n i += 1\\n \\n # Trie les liste de numero de slot pour chaque rangee\\n for k, v in dicoObstacles.items():\\n dicoObstacles[k].sort()\\n \\n # Enregistre les serveurs dans une liste.\\n # Un element de la liste est un triplet : [identifiant du serveur, sa taille, sa capacite]\\n serverId = 0\\n listeServeurs = []\\n line = source.readline()\\n while line != \\\"\\\":\\n size, capacity = line.split()\\n listeServeurs.append([serverId, int(size), int(capacity)])\\n line = source.readline()\\n serverId += 1\\n \\n # Trie par capacite decroissante\\n listeServeurs.sort(key = lambda tup : tup[2], reverse = True) \\n source.close()\\n \\n return carac, dicoObstacles, listeServeurs, dicoRangees\",\n \"def insert_bad_data():\\n get_file_reply(files[2][0], files[2][1])\",\n \"def parse_triangle_files(self):\\n nodes = {}\\n boundary_nodes = []\\n\\n # parse node file into nodes\\n with open(self.files['node']) as node_file:\\n header = True\\n for line in node_file:\\n if header:\\n header = False\\n continue\\n content = list(filter(lambda a: bool(a), line.split(' '))) # pylint: disable=W0108\\n if not '#' in content[0]:\\n is_boundary = content[3] == '1\\\\n'\\n nodes[int(content[0])] = {\\n 'id': int(content[0]),\\n 'coords': [int(content[1]), int(content[2])],\\n 'distance': 0 if is_boundary else None,\\n 'relations': [],\\n 'level_cycles': [], # ids of any level cycles this node is a part of\\n 'level_paths': [], # ids of any level paths this node is a part of\\n 'is_root_element': False,\\n 'betweener_paths': []\\n }\\n if is_boundary:\\n boundary_nodes.append(int(content[0]))\\n node_file.close()\\n\\n # parse edge files into node relations\\n with open(self.files['edge']) as edge_file:\\n header = True\\n for line in edge_file:\\n if header:\\n header = False\\n continue\\n content = list(filter(bool, line.split(' ')))\\n if not '#' in content[0]:\\n nodes[int(content[1])]['relations'].append(int(content[2]))\\n nodes[int(content[2])]['relations'].append(int(content[1]))\\n edge_file.close()\\n\\n # with open(self.files['ele']) as ele_file:\\n # header = True\\n # for line in edge_file:\\n # if header:\\n # header = False\\n # continue\\n # content = list(filter(bool, line.split(' ')))\\n # if not '#' in content[0]:\\n # nodes[int(content[1])]['relations'].append(int(content[2]))\\n # nodes[int(content[2])]['relations'].append(int(content[1]))\\n # edge_file.close()\\n\\n # sorts relations clockwise\\n for node_id, node in nodes.items():\\n nodes[node_id]['relations'] = sorted(node['relations'], key=(\\n lambda related_node_id: (\\n self.calculate_clockwise_angle_and_distance(node, nodes.get(related_node_id)) # pylint: disable=W0640\\n )\\n ))\\n\\n levels = self.get_levels(nodes, boundary_nodes)\\n\\n for level in levels:\\n for node_id in level['node_ids']:\\n self.identify_special_nodes(nodes, node_id)\\n\\n return nodes, boundary_nodes, levels\",\n \"def _read_file(self):\\n\\n with open(self.file_name, 'rb') as f:\\n new_test = struct.unpack('<l', f.read(8)[4:])[0]\\n f.close()\\n\\n with open(self.file_name, 'rb') as f:\\n old_test = struct.unpack('<h', f.read(6)[4:])[0]\\n f.close()\\n\\n with open(self.file_name, 'rb') as f:\\n other_test = struct.unpack('<l', f.read(20)[16:])[0]\\n f.close()\\n\\n open_file = open(self.file_name, 'rb')\\n\\n if (other_test==202):\\n raw = open_file.read(1236)[11:]\\n self.model = '202'\\n elif ((not new_test==102) and old_test==102):\\n raw = open_file.read(1133)\\n self.model = '102old'\\n elif (new_test==102 and old_test==102):\\n raw = open_file.read(1224)\\n self.model = '102new'\\n\\n self.header = DpHeader(raw, self.model)\\n\\n self.data = DpData(open_file, \\n self.model, \\n self.header.interferogram_size, \\n self.header.number_of_coadds, \\n 2048*self.header.zero_fill,\\n self.header.laser_wavelength_microns, \\n self.header.dispersion_constant_xm,\\n self.header.dispersion_constant_xb)\\n\\n open_file.close()\",\n \"def json_data(self):\\n return_data = []\\n\\n # Loop over num files\\n for ifile in range(len(self.data)):\\n\\n # Loop over steps\\n file_return_data = {}\\n for istep in range(len(self.data[ifile])):\\n file_return_data[istep] = {}\\n for key in self.data[ifile][istep]:\\n file_return_data[istep][key] = self.data[ifile][istep][key].tolist()\\n\\n return_data.append(file_return_data)\\n\\n return return_data\",\n \"def read_frames_from_file(file_name):\\n tracklets = parseXML(file_name)\\n\\n\\n frames = {}\\n for trackletObj in tracklets:\\n \\tfor translation, rotation, state, occlusion, truncation, amtOcclusion, amtBorders, absoluteFrameNumber, velo in trackletObj:\\n \\t\\tobj = {'type': trackletObj.objectType, 'l':translation, 'v': velo}\\n \\t\\tif not frames.has_key(absoluteFrameNumber):\\n \\t\\t\\tframes[absoluteFrameNumber] = []\\n \\t\\tframes[absoluteFrameNumber].append(obj)\\n return frames\",\n \"def get_gbk_files(self):\\n\\n db_name = []\\n for file in os.listdir(os.getcwd()):\\n if file.endswith('.db'):\\n db_name.append(str(file))\\n\\n for G_key, G_value in self.what.tier_frame_dict.items():\\n Tier = G_key\\n os.chdir(self.path)\\n os.mkdir(Tier)\\n os.chdir(Tier)\\n Tier_path = os.getcwd()\\n for Gene in self.what.tier_frame_dict[Tier].T:\\n os.chdir(Tier_path)\\n os.mkdir(Gene)\\n os.chdir(Gene)\\n for Organism in self.what.org_list:\\n Accession = str(self.what.gene_dict[Gene][Organism])\\n Accession, Sup, Version = Accession.partition('.')\\n Accession = Accession.upper()\\n server_flag = False\\n for name in db_name:\\n if server_flag is True:\\n break\\n name = str(name)\\n server = BioSeqDatabase.open_database(\\n driver='sqlite3', db=where.VERT_MAM + ('/Databases/%s' % name))\\n for sub_db_name in server.keys():\\n db = server[sub_db_name]\\n\\n try:\\n record = db.lookup(accession=Accession)\\n with open('%s_%s.gbk' % (Gene, Organism), 'w') as GB_file:\\n GB_file.write(record.format('genbank'))\\n print(GB_file.name, 'created')\\n server_flag = True\\n break\\n except IndexError:\\n print('Index Error')\\n continue\",\n \"def return_file_read(_):\\n return [\\\"scorevideo LOG\\\", \\\"File: log.mat\\\"]\",\n \"def _GetImageInfo(self,path):\\n hd = Header(path, scan=True)\\n hdr = hd.hdr\\n self.hdr = hdr\\n if hdr is None:\\n# Either a ref.dat file or it isn't an imaging file.\\n if 'ref' in path and 'dat' in path:\\n self.refdats[os.path.realpath(path)] = True\\n info = {'type':'refdat'}\\n return info\\n else:\\n return None\\n elif hdr['filetype'] == 'dicom' and not path.endswith('.yaml'):\\n# Write a yaml file to the raw data directory if possible.\\n dirname, outfile = self._yaml_filename(path)\\n yaml_name = '%s/%s' % (dirname, outfile)\\n if not os.path.exists(yaml_name):\\n# Create yaml file using dirname,\\n# e.g., ../anatomicals/S2_EFGRE3D/s2_efgre3d.yaml\\n try:\\n hd.write_hdr_to_yaml('%s/%s' % (dirname,outfile))\\n except IOError:\\n# This is a nonessential function, so ignore exceptions\\n# such as access violations.\\n pass\\n elif hdr['filetype'] == 'dicom' or hdr['filetype'] == 'ge_ifile':\\n if not os.path.isdir(path):\\n path = os.path.dirname(path)\\n shdr = hdr['subhdr']\\n nhdr = hdr['native_header']\\n self.shdr = shdr\\n if 'dti' in shdr.get('PulseSequenceName','').lower() \\\\\\n or 'dti' in nhdr.get('PulseSequenceFile',''):\\n psdname = 'dti'\\n else:\\n psdname = os.path.basename((shdr.get('PulseSequenceName','').strip()).lower())\\n info = {'psdname':psdname, \\\\\\n 'acqtime':shdr['AcqTime'], \\\\\\n 'series':int(shdr['SeriesNumber']), \\\\\\n 'plane':hdr['plane'].strip(), \\\\\\n 'type':self.imgtype.get(psdname,None), \\\\\\n 'plane':hdr['plane'], \\\\\\n 'acqtime':shdr['SeriesTime'], \\\\\\n# 'fmapdir':None, \\\\\\n 'refdat':None, \\\\\\n 'imgfile':None, \\\\\\n 'base':None, \\\\\\n 'tdim':int(hdr['tdim']), \\\\\\n 'echo_spacing':None, \\\\\\n 'filetype':'brik', \\\\\\n 'suffix':self.suffix.get(hdr['filetype'], 'brik'), \\\\\\n 'data_filetype':hdr['filetype']}\\n if info['type'] == 'localizer':\\n# Don't process the localizer.\\n return info\\n if isinstance(info['acqtime'], int):\\n info['acquisition_time'] = time.ctime(info['acqtime'])\\n if nhdr.get('ImageFormat',('unknown'))[0] == 'DERIVED' and info['type'] == 'epi':\\n# Sometimes screenshots are defined as epis.\\n info['type'] = None\\n\\n# Call the method appropriate to the type of scan in this series.\\n stat = apply( self.GetInfoMethods.get(info['type'], self._NoInfo), \\\\\\n [info, path])\\n if stat:\\n info = {'type':'break'}\\n return info\\n info['suffix'] = self.suffix.get(info['filetype'], 'brik')\\n return info\",\n \"def read_parse_raw_data(path):\\n file_list = TopologyHelper.get_file_list(path)\\n print(\\\"Reading \\\" + str(len(file_list)) + \\\" files from \\\" + path)\\n topology_info = []\\n file_name = []\\n for file in file_list:\\n try:\\n r = TopologyHelper.parse_file(file)\\n tmp = (r[0])['Topology']\\n topology_info.append(tmp)\\n t = r[1]\\n file_name.append(t)\\n except:\\n continue\\n print(\\\"Parsing completed\\\")\\n return file_name, topology_info\",\n \"def create_dicts(self):\\n \\n # remove this string from filename to make output file names more manageable\\n pre_output1 = self.file1.replace(\\\"_Guys121919_CGH_1100_Jul11\\\", '')\\n pre_output2 = self.file2.replace(\\\"_Guys121919_CGH_1100_Jul11\\\", '')\\n \\n # Build the output file name.\\n # if prefix is present add it\\n if self.out_file_prefix is not None:\\n # concatenate prefix, filenames and dyes into output filename file1_file1_dye_file2_file2_dye.txt\\n self.outputfilename = self.out_file_prefix+pre_output1.replace(\\\".txt\\\", '') + \\\"_\\\" + self.file1_dye + \\\"_\\\" + pre_output2.replace(\\\".txt\\\", '') + \\\"_\\\" + self.file2_dye + \\\".txt\\\"\\n # if no prefix don't add it!\\n else:\\n # concatenate filenames and dyes into output filename file1_file1_dye_file2_file2_dye.txt\\n self.outputfilename = pre_output1.replace(\\\".txt\\\", '') + \\\"_\\\" + self.file1_dye + \\\"_\\\" + pre_output2.replace(\\\".txt\\\", '') + \\\"_\\\" + self.file2_dye + \\\".txt\\\"\\n\\n # add temp to end of file name to create a temporary output filename\\n self.tempoutputfilename = self.outputfilename.replace(\\\".txt\\\", '') + \\\"temp.txt\\\"\\n\\n # open temp output file\\n self.tempoutputfile = open(self.outputfolder + self.tempoutputfilename, 'w')\\n\\n \\n # open FE files\\n file1_open = open(self.chosenfolder + self.file1, 'r')\\n file2_open = open(self.chosenfolder + self.file2, 'r')\\n\\n # open file1 and create a dict of the features.\\n for linenumber, line in enumerate(file1_open):\\n if linenumber >= 10:\\n splitline = line.split('\\\\t')\\n self.file1_dict[int(splitline[1])] = line\\n # get n of rows in file1 (take the linenumber of the last line)\\n self.file1_len = linenumber\\n\\n # repeat for features in second file but first writing the feparam and stats to temp file - when pairing with control this ensures the \\\"header\\\" comes from the test (file2) not control (file1), NB NEITHER ARE ACCURATE!!!!\\n for linenumber, line in enumerate(file2_open):\\n if linenumber < 10:\\n self.tempoutputfile.write(line)\\n # then add all features to a dictionary, with the unique feature number as a key\\n if linenumber >= 10:\\n splitline = line.split('\\\\t')\\n self.file2_dict[int(splitline[1])] = line\\n # get n of rows in file2\\n self.file2_len = linenumber\\n\\n # close files\\n file1_open.close()\\n file2_open.close()\",\n \"def read_struct_file(struct_file,return_type=GeoStruct):\\n\\n VARTYPE = {1:SphVario,2:ExpVario,3:GauVario,4:None}\\n assert os.path.exists(struct_file)\\n structures = []\\n variograms = []\\n with open(struct_file,'r') as f:\\n while True:\\n line = f.readline()\\n if line == '':\\n break\\n line = line.strip().lower()\\n if line.startswith(\\\"structure\\\"):\\n name = line.strip().split()[1]\\n nugget,transform,variogram_info = _read_structure_attributes(f)\\n s = return_type(nugget=nugget,transform=transform,name=name)\\n s.variogram_info = variogram_info\\n # not sure what is going on, but if I don't copy s here,\\n # all the structures end up sharing all the variograms later\\n structures.append(copy.deepcopy(s))\\n elif line.startswith(\\\"variogram\\\"):\\n name = line.strip().split()[1].lower()\\n vartype,bearing,a,anisotropy = _read_variogram(f)\\n if name in variogram_info:\\n v = VARTYPE[vartype](variogram_info[name],a,anisotropy=anisotropy,\\n bearing=bearing,name=name)\\n variograms.append(v)\\n\\n for i,st in enumerate(structures):\\n for vname in st.variogram_info:\\n vfound = None\\n for v in variograms:\\n if v.name == vname:\\n vfound = v\\n break\\n if vfound is None:\\n raise Exception(\\\"variogram {0} not found for structure {1}\\\".\\\\\\n format(vname,s.name))\\n\\n st.variograms.append(vfound)\\n if len(structures) == 1:\\n return structures[0]\\n return structures\",\n \"def dbase():\\r\\n albums_data = {}\\r\\n song_dict = {}\\r\\n songs_list = []\\r\\n with open(PATH, 'r') as f:\\r\\n data = f.read()\\r\\n temp = data.split(\\\"#\\\")\\r\\n for album in temp[1:]:\\r\\n index = album.find(\\\"::\\\")\\r\\n albums_data[album[:index]] = \\\"\\\"\\r\\n for album in temp[1:]:\\r\\n album = album.split(\\\"*\\\")\\r\\n album_name = album[0][:-7]\\r\\n release_Date = album[0][-5:]\\r\\n del album[0]\\r\\n for song in album:\\r\\n info = song.split(\\\"::\\\")\\r\\n song_name = info[0]\\r\\n del info[0]\\r\\n songs_list = info\\r\\n song_dict[song_name] = songs_list\\r\\n albums_data[album_name] = (song_dict.copy(), release_Date)\\r\\n song_dict.clear()\\r\\n return albums_data\",\n \"def from_file(file_name, format='') -> Union['flare.struc.Structure',\\n List['flare.struc.Structure']]:\\n\\n try:\\n with open(file_name, 'r') as _:\\n pass\\n except:\\n raise FileNotFoundError\\n\\n if 'xyz' in file_name or 'xyz' in format.lower():\\n raise NotImplementedError\\n\\n if 'json' in format.lower() or '.json' in file_name:\\n # Assumed format is one FLARE structure per line,\\n # or one line with many FLARE structures\\n with open(file_name, 'r') as f:\\n thelines = f.readlines()\\n\\n non_empty_lines = [loads(line) for line in thelines if\\n len(line) > 2]\\n\\n structures = [Structure.from_dict(struc_dict) for struc_dict in\\n non_empty_lines]\\n\\n if len(structures) == 1:\\n return structures[0]\\n else:\\n return structures\\n\\n is_poscar = 'POSCAR' in file_name or 'CONTCAR' in file_name or 'vasp' in format.lower()\\n if is_poscar and _pmg_present:\\n pmg_structure = pmgvaspio.Poscar.from_file(file_name).structure\\n return Structure.from_pmg_structure(pmg_structure)\\n elif is_poscar and not _pmg_present:\\n raise ImportError(\\\"Pymatgen not imported; \\\" \\\\\\n \\\"functionality requires pymatgen.\\\")\",\n \"def getattr(self, path, *args, **pargs):\\n path, meta = self.find_cue_path(path)\\n if('.flaccuesplit.' in path):\\n try:\\n raw_path = path\\n path, flaccue_details = path.split('.flaccuesplit.')\\n path = self.clean_path(path)\\n times, extension = os.path.splitext(flaccue_details)\\n # Get the info for the base file.\\n st = os.lstat(path)\\n toreturn = dict((key, getattr(st, key)) for key in (\\n 'st_atime', 'st_ctime', 'st_gid', 'st_mode', 'st_mtime',\\n 'st_nlink', 'st_size', 'st_uid'))\\n # Estimate the file size.\\n f = mutagen.File(path)\\n start, end = times.split('.')\\n # Minutes:Seconds:Frames\\n # 75 frames per second.\\n start_split = [int(x) for x in start.split(':')]\\n if(len(start_split) != 3):\\n start_time = 0\\n else:\\n start_time = start_split[0]*60 + start_split[1] + start_split[2]/75\\n end_split = [int(x) for x in end.split(':')]\\n if(len(end_split) != 3):\\n end_time = f.info.length\\n else:\\n end_time = end_split[0]*60 + end_split[1] + end_split[2]/75\\n toreturn['st_size'] = int((end_time - start_time) *\\n f.info.channels *\\n (f.info.bits_per_sample/8) *\\n f.info.sample_rate)\\n # Ensure the mode shows the file as readable.\\n toreturn['st_mode'] = toreturn['st_mode'] | 0o444\\n return toreturn\\n except Exception:\\n print(f'Error getting attributes for {raw_path}:', file=sys.stderr, flush=True)\\n import traceback\\n traceback.print_exc()\\n # Otherwise, just get the normal info.\\n path = self.clean_path(path)\\n st = os.lstat(path)\\n toreturn = dict((key, getattr(st, key)) for key in (\\n 'st_atime', 'st_ctime', 'st_gid', 'st_mode', 'st_mtime',\\n 'st_nlink', 'st_size', 'st_uid'))\\n # Ensure the mode shows the file as readable.\\n toreturn['st_mode'] = toreturn['st_mode'] | 0o444\\n return toreturn\",\n \"def get_patches(self, username, filename) -> Tuple[str, List[str]] or None:\\r\\n file_id = self.get_file_id(username, filename)\\r\\n if file_id not in self.patch_history:\\r\\n file_path = self.users_dir / username / filename\\r\\n file_patches = self.try_load_file(file_path)\\r\\n if file_patches is not None:\\r\\n self.patch_history[file_id] = file_patches\\r\\n else:\\r\\n return None\\r\\n return file_id, self.patch_history[file_id]\",\n \"def readfile(self,filenm,delimiter):\\n\\n timefiledata = []\\n timefileextra = {}\\n fixtimeflag = False\\n hour0=hour1=False\\n\\n\\n if isinstance(filenm,(str,unicode)):\\n timeobject = readTextFile(filenm,delimiter)\\n else:\\n timeobject = filenm\\n\\n\\n for idx,lines in enumerate(timeobject):\\n\\n try:\\n floatlines = map(float,lines)\\n month,date,hour = floatlines[:3]\\n dataval = floatlines[3:]\\n ##Code to check if the first time value is 1.0. If so subtract every hour by 0.5\\n\\n if not hour1 or hour0:\\n hour1 = hour\\n if hour0==1.0 and hour1==2.0:\\n #Go back to the array that stores timevalues and fix the hour and time stamp\\n timefiledata[0]['h']=0.5\\n timefiledata[0]['tstamp']=timeStamp(1,1,0.5)\\n fixtimeflag=True\\n\\n if not hour0:\\n hour0 = hour\\n\\n if fixtimeflag:\\n hour = hour-0.5\\n ##Code to check if the first time value is 1.0. If so subtract every hour by 0.5\\n\\n timestamp = timeStamp(month,date,hour)\\n\\n timefiledata.append({\\\"m\\\":month,\\\"d\\\":date,\\\"h\\\":hour,\\\"readStadicData\\\":dataval,\\\"tstamp\\\":timestamp})\\n\\n except ValueError:\\n print(sys.exc_info())\\n timefileextra[lines[0]]=lines[1]\\n\\n return (timefiledata,timefileextra)\",\n \"def ReadInputFile(file:int)->EvenMorePizza:\\n self.files = ('a_example.in','b_little_bit_of_everything.in', 'c_many_ingredients.in','d_many_pizzas.in','e_many_teams.in')\\n \\n EvenMorePizza temporalValue\\n \\n file = open(files[file])#open the file\\n data = doc.Read().strip(' ,\\\\n').split('\\\\n')\\n file.close()#close the file\\n #set the title of the command\\n data_head = data[0].strip(' ,\\\\n').split(' ')\\n temporalValue.AvailablePizza = int(data_head[0])\\n temporalValue.Team2ppl = int(data_head[1])\\n temporalValue.Team3ppl = int(data_head[2])\\n temporalValue.Team4ppl = int(data_head[3])\\n #set the other ingredients\\n count = 0\\n for a in data[1:]:\\n x = a.strip(' ,\\\\n').split(' ')\\n temporalValue.ingredients[count] = x[1:]\\n count += 1\",\n \"def get_file(filename: str) -> dict:\\n return loads(open(f\\\"data/gamedata/{filename}.json\\\", \\\"r\\\", encoding=\\\"utf-8\\\").read())\",\n \"def associate_files(self):\\n # Open starinfo file and define structured array\\n starinfo_file = self.starinfo_file\\n nstar = sum(1 for line in open(starinfo_file))\\n infoname = ['obj', 'std', 'caldir', 'altname']\\n infofmt = ['|S25', '|S25', '|S25', '|S25']\\n starinfo = np.zeros(nstar, dtype={\\n 'names': infoname, 'formats': infofmt})\\n with open(starinfo_file, 'r') as arq:\\n for i in range(nstar):\\n linelist = arq.readline().split()\\n for j in range(len(infoname)):\\n starinfo[i][j] = linelist[j]\\n\\n if self.stored_sens:\\n self.load_storedsens()\\n\\n os.chdir(self.raw_dir)\\n\\n l = glob.glob('*.fits')\\n l.sort()\\n\\n headers = []\\n headers_ext1 = []\\n for i in l:\\n try:\\n headers.append(fits.getheader(i, ext=0))\\n headers_ext1.append(fits.getheader(i, ext=1))\\n except IOError:\\n print('IOError reading file {:s}.'.format(i))\\n raise SystemExit(0)\\n\\n oversc = np.array(\\n [('overscan') in i for i in headers_ext1], dtype='bool')\\n\\n mjds = np.array([i['mjd-obs'] for i in headers_ext1], dtype='float32')\\n idx = np.arange(len(l))\\n\\n images = np.array([\\n l[i] for i in idx if (\\n (headers[i]['obstype'] == 'OBJECT') &\\n (headers[i]['object'] != 'Twilight') &\\n (headers[i]['obsclass'] != 'acq'))])\\n\\n field_names = [\\n 'filename', 'observatory', 'instrument', 'detector',\\n 'grating', 'filter1', 'obsclass', 'object', 'obstype',\\n 'grating_wl', 'overscan', 'mjd', 'ccdsum']\\n types = [\\n 'S120', 'S60', 'S60', 'S60', 'S60', 'S60', 'S60', 'S60', 'S60',\\n 'float32', 'bool', 'float32', 'S60']\\n hdrkeys = [\\n 'observat', 'instrume', 'detector', 'grating', 'filter1',\\n 'obsclass', 'object', 'obstype', 'grwlen']\\n\\n hdrpars_type = [\\n (field_names[i], types[i]) for i in range(len(field_names))]\\n\\n hdrpars = np.array([\\n ((l[i],) + tuple([headers[i][j] for j in hdrkeys]) +\\n (oversc[i],) + (mjds[i],) + (headers_ext1[i]['ccdsum'],))\\n for i in idx], dtype=hdrpars_type)\\n\\n associated = []\\n\\n for i, j in enumerate(images):\\n\\n # Take great care when changing this.\\n hdr = fits.getheader(j, ext=0)\\n hdr_ext1 = fits.getheader(j, ext=1)\\n mjd = hdr_ext1['mjd-obs']\\n\\n element = {\\n 'image': j, 'observatory': hdr['observat'],\\n 'instrument': hdr['instrume'],\\n 'detector': hdr['detector'], 'grating_wl': hdr['grwlen'],\\n 'mjd': mjd, 'grating': hdr['grating'],\\n 'filter1': hdr['filter1'], 'obsclass': hdr['obsclass'],\\n 'object': hdr['object']}\\n\\n if self.stored_sens:\\n ssf = self.stored_sensfunc\\n element['standard_star'] = ssf['filename'][\\n (ssf['observatory'] == hdr['observat']) &\\n (ssf['detector'] == hdr['detector']) &\\n (ssf['grating'] == hdr['grating']) &\\n (ssf['instrument'] == hdr['instrume']) &\\n (ssf['filter1'] == hdr['filter1']) &\\n (ssf['maskname'] == hdr['maskname'])]\\n else:\\n element['standard_star'] = hdrpars['filename'][\\n (hdrpars['obstype'] == 'OBJECT') &\\n (np.array([k in ['partnerCal', 'progCal']\\n for k in hdrpars['obsclass']], dtype='bool')) &\\n (hdrpars['object'] != 'Twilight') &\\n (hdrpars['observatory'] == hdr['observat']) &\\n (hdrpars['detector'] == hdr['detector']) &\\n (hdrpars['grating'] == hdr['grating']) &\\n (hdrpars['filter1'] == hdr['filter1']) &\\n (abs(hdrpars['grating_wl'] - hdr['grwlen']) <=\\n self.cfg.getfloat('associations', 'stdstar_wltol')) &\\n (abs(mjds - mjd) <=\\n self.cfg.getfloat('associations', 'stdstar_ttol'))]\\n\\n element['flat'] = hdrpars['filename'][\\n (hdrpars['obstype'] == 'FLAT') &\\n (hdrpars['observatory'] == hdr['observat']) &\\n (hdrpars['grating'] == hdr['grating']) &\\n (hdrpars['grating_wl'] == hdr['grwlen']) &\\n (hdrpars['detector'] == hdr['detector']) &\\n (abs(mjds - mjd) <= self.cfg.getfloat('associations',\\n 'flat_ttol'))]\\n\\n element['twilight'] = hdrpars['filename'][\\n (hdrpars['object'] == 'Twilight') &\\n (hdrpars['obstype'] == 'OBJECT') &\\n (hdrpars['observatory'] == hdr['observat']) &\\n (hdrpars['detector'] == hdr['detector']) &\\n (hdrpars['grating'] == hdr['grating']) &\\n (abs(hdrpars['grating_wl'] - hdr['grwlen']) <=\\n self.cfg.getfloat('associations', 'twilight_wltol')) &\\n (abs(mjds - mjd) <=\\n self.cfg.getfloat('associations', 'twilight_ttol'))]\\n\\n c = 'twilight'\\n if len(element[c]) > 1:\\n element[c] = closest_in_time(element[c], j)\\n elif len(element[c]) == 1:\\n element[c] = element[c][0]\\n elif len(element[c]) == 0:\\n element[c] = ''\\n\\n # A flat close to the twilight observation for a better\\n # response function.\\n if element['twilight']:\\n twipars = hdrpars[hdrpars['filename'] == element['twilight']]\\n element['twilight_flat'] = hdrpars['filename'][\\n (hdrpars['obstype'] == 'FLAT') &\\n (hdrpars['observatory'] == twipars['observatory']) &\\n (hdrpars['detector'] == twipars['detector']) &\\n (hdrpars['grating'] == twipars['grating']) &\\n (hdrpars['grating_wl'] == twipars['grating_wl']) &\\n (abs(mjds - twipars['mjd']) <= self.cfg.getfloat(\\n 'associations', 'twilight_ttol'))]\\n else:\\n element['twilight_flat'] = np.array([], dtype='S60')\\n\\n element['arc'] = hdrpars['filename'][\\n # (hdrpars['object'] == 'CuAr') &\\n (hdrpars['obstype'] == 'ARC') &\\n (hdrpars['observatory'] == hdr['observat']) &\\n (hdrpars['detector'] == hdr['detector']) &\\n (hdrpars['grating'] == hdr['grating']) &\\n (hdrpars['grating_wl'] == hdr['grwlen']) &\\n (abs(mjds - mjd) <=\\n self.cfg.getfloat('associations', 'arc_ttol'))]\\n\\n element['bias'] = hdrpars['filename'][\\n (hdrpars['obstype'] == 'BIAS') &\\n (hdrpars['observatory'] == hdr['observat']) &\\n (hdrpars['detector'] == hdr['detector']) &\\n (abs(mjds - mjd) <=\\n self.cfg.getfloat('associations', 'bias_ttol')) &\\n (\\n (hdrpars['overscan'] & (self.fl_over == 'yes')) |\\n (~hdrpars['overscan'] & (self.fl_over == 'no'))\\n )]\\n\\n im = fits.open(element['image'])\\n ishape = np.array(im[1].data.shape, dtype='float32')\\n im.close()\\n del(im)\\n\\n validBiases = np.ones(len(element['bias']), dtype='bool')\\n k = 0\\n\\n for biasImage in element['bias']:\\n\\n bias = fits.open(biasImage)\\n bshape = np.array(bias[1].data.shape, dtype='float32')\\n bias.close()\\n del(bias)\\n\\n #\\n # Elinates biases if they differ in array size from\\n # the science image. Small differences are normal due to\\n # the overscan subtraction in processed bias frames.\\n #\\n if np.any(np.abs(bshape / ishape - 1.0) > 0.10):\\n validBiases[k] = False\\n\\n k += 1\\n\\n element['bias'] = element['bias'][validBiases]\\n del(k)\\n\\n element['bpm'] = hdrpars['filename'][\\n (hdrpars['obstype'] == 'BPM') &\\n (hdrpars['observatory'] == hdr['observat']) &\\n (hdrpars['detector'] == hdr['detector']) &\\n (hdrpars['ccdsum'] == hdr_ext1['ccdsum'])]\\n\\n categories = ['flat', 'bias', 'arc', 'standard_star',\\n 'bpm', 'twilight_flat']\\n\\n for c in categories:\\n if len(element[c]) > 1:\\n element[c] = closest_in_time(element[c], j)\\n elif len(element[c]) == 0:\\n element[c] = ''\\n elif len(element[c]) == 1:\\n element[c] = (element[c])[0]\\n\\n associated.append(element)\\n\\n # Define mdf filename\\n # Based in gprepare.cl\\n # Did not account for observation in Nod-and-Shuffle\\n for i in associated:\\n header_flat = [\\n k for j, k in enumerate(headers) if l[j] == i['flat']\\n ]\\n if len(header_flat):\\n header_flat = header_flat[0]\\n MaskName = header_flat['maskname']\\n if MaskName == \\\"IFU-2\\\":\\n slits = 'both'\\n elif MaskName == \\\"IFU-B\\\":\\n slits = 'blue'\\n elif MaskName == \\\"IFU-R\\\":\\n slits = 'red'\\n i['slits'] = slits\\n\\n if self.object_filter:\\n objs = self.object_filter.split(',')\\n sci_ims = [\\n i for i in associated if (\\n (i['obsclass'] == 'science') &\\n (i['object'] in objs))]\\n else:\\n sci_ims = [i for i in associated if i['obsclass'] == 'science']\\n\\n if self.all_stars:\\n std_ims = [\\n i for i in associated if i['obsclass'] in ['partnerCal',\\n 'progCal']]\\n else:\\n used_stds = [i['standard_star'] for i in sci_ims]\\n std_ims = [i for i in associated if i['image'] in used_stds]\\n\\n # Get star info from starinfo.dat\\n possible_names = np.concatenate((starinfo['obj'], starinfo['std'],\\n starinfo['altname']))\\n n_names = len(possible_names)\\n\\n for i, j in enumerate(possible_names):\\n possible_names[i] = (j.lower()).replace(' ', '')\\n\\n for i in std_ims:\\n # Removes the 'standard_star' key if the dictionary\\n # element in question refers to a standard star.\\n del i['standard_star']\\n starname = (i['object'].lower()).replace(' ', '')\\n\\n try:\\n stdstar_idx = (\\n np.arange(n_names)[possible_names == starname] %\\n (n_names / 3))[0]\\n except:\\n raise Exception(\\n 'Standard star named {:s} not found in file {:s}'.\\n format(starname, starinfo_file))\\n\\n i['stdstar'] = starinfo[stdstar_idx]['std']\\n\\n if starinfo[stdstar_idx]['caldir'] == 'gireds_data':\\n i['caldir'] = pkg_resources.resource_filename(\\n 'gireds', 'data/')\\n else:\\n i['caldir'] = starinfo[stdstar_idx]['caldir']\\n\\n self.sci = sci_ims\\n self.std = std_ims\\n\\n # Writes the file association dictionary to an ASCII file\\n # in the run directory.\\n\\n if not self.dry_run:\\n try:\\n os.mkdir(self.products_dir)\\n except OSError as err:\\n if err.errno == 17:\\n pass\\n else:\\n raise err\\n try:\\n os.mkdir(self.run_dir)\\n except OSError as err:\\n if err.errno == 17:\\n pass\\n else:\\n raise err\\n\\n if not self.dry_run:\\n os.chdir(self.run_dir)\\n json.dump(\\n sci_ims, open('file_associations_sci.dat', 'w'),\\n sort_keys=True, indent=4)\\n json.dump(\\n std_ims, open('file_associations_std.dat', 'w'),\\n sort_keys=True, indent=4)\",\n \"def getfile(self, name):\\n try:\\n datname = self.getname(name, \\\"dat\\\")\\n tadname = self.getname(name, \\\"tad\\\")\\n if datname and tadname:\\n return Datafile(name, open(datname, \\\"rb\\\"), open(tadname, \\\"rb\\\"), self.kod)\\n except IOError:\\n return\",\n \"def get_inputdata(path):\\n import os, json\\n \\n json_list = list()\\n for filename in os.listdir(path):\\n if 'json' in filename:\\n json_list.append(filename)\\n\\n SMI_list = list()\\n MP_list = []\\n for item in json_list:\\n sample = json.load(open(path+item))\\n smi = sample['smiles']\\n mp = float(sample['Tm'])\\n MP_list.append(mp)\\n SMI_list.append(smi)\\n \\n return SMI_list, MP_list\",\n \"def get_synthia_file_pairs(sequence='*', frame='*', ext='.png',\\n direction='*', type2='*', gt_type='LABELS',\\n root_folder=SYNTHIA_FOLDER, file_template=SYNTHIA_FILE_TEMPLATE):\\n input_file_template = file_template.format(\\n root=root_folder, type='RGB', type2=type2, direction=direction,\\n len_fill=1, filler='*', seq=sequence, frame=frame, ext=ext)\\n input_files = glob.glob(input_file_template)\\n\\n gt_file_template = file_template.format(\\n root=root_folder, type=os.path.join('GT', gt_type), type2=type2, direction=direction,\\n len_fill=1, filler='*', seq=sequence, frame=frame, ext=ext)\\n gt_files = glob.glob(gt_file_template)\\n\\n assert (len(input_files) == len(gt_files))\\n return sorted(input_files), sorted(gt_files)\",\n \"def sgd_features(filepath=None):\\n\\n if filepath == None:\\n filepath=load_sgd_tab()\\n\\n arabic_to_roman_dict=chromosomename_roman_to_arabic()[0]\\n \\n with open(filepath) as f:\\n lines = f.readlines()\\n\\n\\n feature_list = []\\n feature_orf_dict = {}\\n feature_ars_dict = {}\\n feature_telomere_dict = {}\\n feature_ltr_dict = {}\\n feature_centromere_dict = {}\\n feature_Xelement_dict = {}\\n feature_intron_dict = {}\\n feature_ncrna_dict = {}\\n feature_ncexon_dict = {}\\n feature_trna_dict = {}\\n feature_snorna_dict = {}\\n feature_teg_dict = {}\\n feature_5p_utrintron_dict = {}\\n feature_mas_dict = {}\\n feature_snrna_dict = {}\\n feature_rrna_dict = {}\\n feature_ets_dict = {}\\n feature_its_dict = {}\\n feature_oor_dict = {}\\n feature_telrna_dict = {}\\n \\n for line in lines:\\n l = line.strip('\\\\n').split('\\\\t')\\n if not l[1] in feature_list:\\n feature_list.append(l[1])\\n\\n if not l[8].endswith('micron') and not l[8] == '':\\n chromosome = arabic_to_roman_dict.get(int(l[8]))\\n if l[1] == 'ORF':\\n feature_orf_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'ARS':\\n feature_ars_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'telomere':\\n feature_telomere_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'long_terminal_repeat':\\n feature_ltr_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'centromere':\\n feature_centromere_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'X_element':\\n feature_Xelement_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'intron':\\n feature_intron_dict[l[6]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'ncRNA_gene':\\n feature_ncrna_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'noncoding_exon':\\n feature_ncexon_dict[l[6]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'tRNA_gene':\\n feature_trna_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'snoRNA_gene':\\n feature_snorna_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'transposable_element_gene':\\n feature_teg_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'five_prime_UTR_intron':\\n feature_5p_utrintron_dict[l[6]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'matrix_attachment_site':\\n feature_mas_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'snRNA_gene':\\n feature_snrna_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'rRNA_gene':\\n feature_rrna_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'external_transcribed_spacer_region':\\n feature_ets_dict[l[6]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'internal_transcribed_spacer_region':\\n feature_its_dict[l[6]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'origin_of_replication':\\n feature_oor_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n elif l[1] == 'telomerase_RNA_gene':\\n feature_telrna_dict[l[3]] = [l[1], l[2], l[4], l[5], l[6], chromosome, l[9],l[10]]\\n\\n\\n \\n\\n\\n genomicregions_list = ['ORF', 'ARS', 'Telomere', 'long_terminal_repeat',\\n 'Centromere', 'X_element', 'Intron', 'ncRNA_gene',\\n 'Noncoding_exon', 'tRNA_gene', 'snoRNA_gene',\\n 'transposable_element_gene', 'five_prime_UTR_intron',\\n 'matrix_attachment_site', 'snRNA_gene', 'rRNA_gene',\\n 'external_transcribed_spacer_region',\\n 'internal_transcribed_spacer_region',\\n 'origin_of_replication', 'telomerase_RNA_gene']\\n\\n\\n return(genomicregions_list, feature_orf_dict, feature_ars_dict, feature_telomere_dict,\\n feature_ltr_dict, feature_centromere_dict, feature_Xelement_dict, feature_intron_dict,\\n feature_ncrna_dict, feature_ncexon_dict, feature_trna_dict,\\n feature_snorna_dict, feature_teg_dict, feature_5p_utrintron_dict,\\n feature_mas_dict, feature_snrna_dict, feature_rrna_dict,\\n feature_ets_dict, feature_its_dict, feature_oor_dict,\\n feature_telrna_dict)\",\n \"def _borehole_structure_data(self):\\n file_loc = self.data_path / \\\"03_GeologicalMapping\\\" / \\\"02_BoreholeIntersections\\\"\\n columns = [\\\"depth\\\", \\\"azimuth\\\", \\\"dip\\\", \\\"aperture\\\", \\\"type\\\"]\\n\\n data = []\\n for borehole in self.boreholes:\\n path = file_loc / (borehole + \\\"_structures.txt\\\")\\n frame = pd.read_csv(\\n path, sep=None, names=columns, skiprows=2, engine=\\\"python\\\"\\n )\\n frame[\\\"borehole\\\"] = borehole\\n data.append(frame)\\n df = pd.concat(data, ignore_index=True)\\n return df\",\n \"def parse_data(self, path_to_file):\\n\\n line_dict, rel_dict = self.create_dicts(path_to_file)\\n \\n line_df = self.create_dataframe(line_dict, ['line'])\\n rel_df = self.create_dataframe(rel_dict, ['relation'])\\n\\n line_df['relation'] = rel_df['relation']\\n\\n return (line_df, rel_df)\",\n \"def map_file_data(file_obj, file_events):\\n file_as_dict = {\\n \\\"premis:originalName\\\": file_obj.currentlocation,\\n \\\"original_name\\\": escape(file_obj.originallocation),\\n # needs investigation\\n \\\"sanitized_file_name\\\": get_sanitized_file_name(\\n get_file_name_cleanup(file_events)\\n ),\\n \\\"prov:generatedAtTime\\\": file_obj.modificationtime.strftime(\\n \\\"%Y-%m-%dT%H:%M:%SZ\\\"\\n ),\\n \\\"premis:fixity\\\": {\\n \\\"checksum_type\\\": convert_to_premis_hash_function(file_obj.checksumtype),\\n \\\"Checksum\\\": file_obj.checksum,\\n },\\n \\\"premis:identifier\\\": file_obj.uuid,\\n \\\"premis:size\\\": file_obj.size,\\n \\\"file_name\\\": file_obj.label,\\n # not sure if this is the file name or if we should stick with\\n \\\"dct:FileFormat\\\": map_file_format_info(\\n get_file_format_event(file_events), get_file_validation_event(file_events)\\n ),\\n \\\"file_validation\\\": map_file_validation_info(\\n get_file_validation_event(file_events)\\n ),\\n \\\"file_normalization\\\": map_file_normalization_info(\\n get_file_normalization_event(file_events)\\n ),\\n \\\"events\\\": list_file_events(file_events),\\n }\\n return file_as_dict\",\n \"def open_and_read_file():\\n file_path = sys.argv[1]\\n #print file_path\\n file_data = open(file_path, 'r')\\n gettysburg = file_data.read()\\n\\n return gettysburg\",\n \"def readStatFile(filePath):\\n f = open(filePath, 'r')\\n\\n allStats = {}\\n overviewStats = {}\\n category = ''\\n folder = ''\\n method = ''\\n\\n for line in f:\\n # Check if the line contains the 'cm' character and thus provides information of the specific folder\\n if 'cm' in line:\\n words = line.split()\\n\\n for word in words:\\n if '/' in word:\\n # All processed folder has either a /MoG or /SubSENSE folder. Exploit this to get the filename\\n category = os.path.basename(os.path.dirname(os.path.dirname(os.path.normpath(filePath))))\\n folder = os.path.basename(os.path.dirname(os.path.normpath(filePath)))\\n method = word\\n\\n # Get the raw FP, TN, etc. count\\n folderNumbers = {'TP': words[4], 'FP': words[5], 'FN': words[6], 'TN': words[7],\\n 'ErrorShadow': words[8]}\\n overviewStats[method] = folderNumbers\\n\\n\\n # CHeck if line is not empty, does not contain certain characters, and that the folder has been found\\n if '#' not in line and 'cm' not in line and line and folder and '\\\\n' != line and method:\\n measures = line.split()\\n\\n isRealMeasure = True\\n\\n for measure in measures:\\n if not RepresentsFloat(measure):\\n isRealMeasure = False\\n break\\n\\n\\n if len(measures) == 7 and isRealMeasure:\\n folderStats = {'recall': measures[0], 'specificity': measures[1], 'FPR': measures[2], 'FNR': measures[3], \\n 'PBC': measures[4], 'precision': measures[5], 'f-measure': measures[6]}\\n allStats[method] = folderStats\\n\\n method = ''\\n\\n return allStats, overviewStats\",\n \"def stitchable_infiles(gdf):\\n gdf['date'] = pd.DatetimeIndex(gdf.sensing_start).date\\n for date, gdf_date in gdf.groupby('date'):\\n for relative_orbit_number, gdf_rob in gdf_date.groupby('relative_orbit_number'):\\n for passdir, gdf_passdir in gdf_rob.groupby('passdir'):\\n for spacecraft, gdf_spacecraft in gdf_passdir.groupby('spacecraft'):\\n for somode, gdf_somode in gdf_spacecraft.groupby('sensor_operational_mode'):\\n fp = _get_footprint_union(gdf_spacecraft)\\n meta = dict(\\n date=date, relative_orbit_number=relative_orbit_number,\\n passdir=passdir, sensor_operational_mode=somode,\\n spacecraft=spacecraft, footprint_union=fp)\\n yield meta, gdf_somode['filepath'].values.tolist()\",\n \"def readbstfolder(BSTfilefolder):\\n obsfileinfo = filefolder2obsfileinfo(BSTfilefolder)\\n maxnrsbs = obsfileinfo['max_nr_bls']\\n BSTdirls = os.listdir(BSTfilefolder)\\n BSTfiles = [f for f in BSTdirls if f.endswith('.dat')]\\n\\n # Now read the BST pol data\\n BST_dtype = numpy.dtype(('f8', (maxnrsbs,)))\\n BSTdata = {}\\n for BSTpolfile in BSTfiles:\\n pol = BSTpolfile[-5]\\n with open(os.path.join(BSTfilefolder, BSTpolfile), \\\"rb\\\") as fin:\\n BSTdata[pol] = numpy.fromfile(fin, dtype=BST_dtype)\\n return BSTdata, obsfileinfo\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5878077","0.5440457","0.53874904","0.53820133","0.53557533","0.53333783","0.53244895","0.5290351","0.52806115","0.52697927","0.5260802","0.52478737","0.524652","0.523822","0.52320105","0.52174884","0.5207511","0.51975965","0.5183999","0.51685417","0.51426","0.51405036","0.5137058","0.5135971","0.51264596","0.5120028","0.51184374","0.5116302","0.5104712","0.50996137","0.5098045","0.509566","0.5081783","0.5078826","0.50533175","0.50422424","0.504095","0.5040849","0.5030426","0.50194836","0.50061816","0.5004538","0.498945","0.49893886","0.4985989","0.4975067","0.49643716","0.49622372","0.4951682","0.4945319","0.49323076","0.4923184","0.49117503","0.490519","0.49023336","0.4899274","0.48985302","0.4894242","0.48846352","0.4884206","0.48825243","0.4875442","0.48751202","0.48719463","0.48572004","0.4850185","0.48489836","0.4848907","0.4845814","0.48450777","0.48448497","0.48429424","0.48358598","0.48261887","0.48242044","0.48195046","0.48114207","0.48092514","0.48086154","0.48069045","0.48055595","0.48014978","0.47979605","0.4796572","0.4796317","0.47929755","0.47885206","0.47817472","0.4779365","0.47789606","0.47759828","0.47719166","0.4769928","0.47693247","0.47633472","0.47600886","0.47597486","0.47593996","0.47578987","0.47575814","0.47568694"],"string":"[\n \"0.5878077\",\n \"0.5440457\",\n \"0.53874904\",\n \"0.53820133\",\n \"0.53557533\",\n \"0.53333783\",\n \"0.53244895\",\n \"0.5290351\",\n \"0.52806115\",\n \"0.52697927\",\n \"0.5260802\",\n \"0.52478737\",\n \"0.524652\",\n \"0.523822\",\n \"0.52320105\",\n \"0.52174884\",\n \"0.5207511\",\n \"0.51975965\",\n \"0.5183999\",\n \"0.51685417\",\n \"0.51426\",\n \"0.51405036\",\n \"0.5137058\",\n \"0.5135971\",\n \"0.51264596\",\n \"0.5120028\",\n \"0.51184374\",\n \"0.5116302\",\n \"0.5104712\",\n \"0.50996137\",\n \"0.5098045\",\n \"0.509566\",\n \"0.5081783\",\n \"0.5078826\",\n \"0.50533175\",\n \"0.50422424\",\n \"0.504095\",\n \"0.5040849\",\n \"0.5030426\",\n \"0.50194836\",\n \"0.50061816\",\n \"0.5004538\",\n \"0.498945\",\n \"0.49893886\",\n \"0.4985989\",\n \"0.4975067\",\n \"0.49643716\",\n \"0.49622372\",\n \"0.4951682\",\n \"0.4945319\",\n \"0.49323076\",\n \"0.4923184\",\n \"0.49117503\",\n \"0.490519\",\n \"0.49023336\",\n \"0.4899274\",\n \"0.48985302\",\n \"0.4894242\",\n \"0.48846352\",\n \"0.4884206\",\n \"0.48825243\",\n \"0.4875442\",\n \"0.48751202\",\n \"0.48719463\",\n \"0.48572004\",\n \"0.4850185\",\n \"0.48489836\",\n \"0.4848907\",\n \"0.4845814\",\n \"0.48450777\",\n \"0.48448497\",\n \"0.48429424\",\n \"0.48358598\",\n \"0.48261887\",\n \"0.48242044\",\n \"0.48195046\",\n \"0.48114207\",\n \"0.48092514\",\n \"0.48086154\",\n \"0.48069045\",\n \"0.48055595\",\n \"0.48014978\",\n \"0.47979605\",\n \"0.4796572\",\n \"0.4796317\",\n \"0.47929755\",\n \"0.47885206\",\n \"0.47817472\",\n \"0.4779365\",\n \"0.47789606\",\n \"0.47759828\",\n \"0.47719166\",\n \"0.4769928\",\n \"0.47693247\",\n \"0.47633472\",\n \"0.47600886\",\n \"0.47597486\",\n \"0.47593996\",\n \"0.47578987\",\n \"0.47575814\",\n \"0.47568694\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":92986,"cells":{"query":{"kind":"string","value":"Returns best matching movie subtitle table."},"document":{"kind":"string","value":"def give_movie_subtitle_consistent_data(self, movie_file_data, subtitle_file_data):\n m_s_temp_data = []\n preliminary_movie_subtitle_list = self.compare_movie_and_subtitle_FileData(movie_file_data, subtitle_file_data)\n for x in preliminary_movie_subtitle_list:\n \"\"\" Delete 0 'propability' registry\"\"\"\n if x['propability'] != 0:\n m_s_temp_data.append(x)\n\n temp_movieList = []\n for x in m_s_temp_data:\n \"\"\"Check what movies are still in registry\"\"\"\n if x['movie'] not in temp_movieList:\n temp_movieList.append(x['movie'])\n \n final_movie_subtitle_list = []\n matching_movie = False\n for x in temp_movieList:\n \"\"\"For all movies in temp_movieList checks best subtitles\"\"\"\n final_propability = 0\n for y in preliminary_movie_subtitle_list:\n if y['movie'] == x and y['propability'] > final_propability:\n if self.__file_path == y['movie']:\n \"\"\"Check it primary movie is in results matching_movie = True\"\"\"\n matching_movie = True\n best_entry = y\n final_propability = y['propability']\n final_movie_subtitle_list.append(best_entry) \n\t \n\t\"\"\"Filtering by subtitle name - if there is no multiple subtitles\"\"\"\n\tpreliminary_movie_subtitle_list = final_movie_subtitle_list\n\ttemp_movieList = [] #now subtile\n\tfor x in preliminary_movie_subtitle_list:\n \"\"\"Check what movies are still in registry\"\"\"\n if x['subtitle'] not in temp_movieList:\n temp_movieList.append(x['subtitle'])\n\t\t\t\t\n\tfinal_movie_subtitle_list = []\t\n\tmatching_movie = False\n for x in temp_movieList: #now subtile\n \"\"\"For all subtitles in temp_movieList which now is subtitle checks best movie\n\t This makes that one subtitle don't belong to multi movies.\t \n\t \"\"\"\n final_propability = 0\n for y in preliminary_movie_subtitle_list:\n if y['subtitle'] == x and y['propability'] > final_propability:\n if self.__file_path == y['movie']:\n \"\"\"Check it primary movie is in results matching_movie = True\"\"\"\n matching_movie = True\n best_entry = y\n final_propability = y['propability']\n final_movie_subtitle_list.append(best_entry)\n\t\n if matching_movie == True:\n return final_movie_subtitle_list\n else:\n return []"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _best_matching_movie(movie):\n return (Levenshtein.distance(movie_name, movie.get('title').lower()),\n (0 - movie.get('votes', 0)),\n )","def download_subtitle(search, results, filename, min_match=0,\n force=0, debug=0):\n s = Subseek()\n subtitleurl = False\n for result in s.order_match(search, results):\n match_text = s.clean_text(s.clean_html(result['text']),False,\n s.detect_encoding(s.clean_html(result['text']))\n ) + \" \" + s.clean_text(s.clean_html(result['description']),False,\n s.detect_encoding(s.clean_html(result['description'])))\n subtitleurl = result['link']\n rating_weight = s.text_weight(search, match_text)\n max_weight = s.text_weight(search)\n rating_match = rating_weight/max_weight*100\n if debug == 1:\n print \"Subtitle File URL: \" + subtitleurl\n print \" Text To Search: \" + search\n print \" Text To Match: \" + match_text\n print \" Text Match (%): \" + str(round(rating_match,2)) + \"%\"\n # check minimal match to use\n if rating_match >= min_match:\n downloaded = s.download(subtitleurl, filename + '.tmp')\n if downloaded == False:\n if debug == 1:\n print \"Error: connection or file creation failed\"\n subtitleurl = False\n else:\n if debug == 1:\n print \"File downloaded\"\n # unrar, unzip or get srt file\n typefile = s.get_sub_file_from_file(filename + '.tmp',\n search, force)\n if typefile == False:\n if debug == 1:\n print \"Subtitle file not found\"\n subtitleurl = False\n else:\n if debug == 1:\n print \"Subtitle file found in \" + typefile\n subtitleurl = True\n break\n else:\n if debug == 1:\n print \"Error: match less than \" + str(round(min_match,2))+ \"%\"\n subtitleurl = False\n break\n\n return subtitleurl","def best_subtitle_url(search, full_search, path_file_name,\n min_match=0, force=0, deep=0, debug=0):\n # first search in subtitle search engines\n links = subtitle_search_engines_links(search, deep, debug)\n subtitle_url = download_best_subtitle(links,\n full_search,\n path_file_name,\n min_match, force, debug)\n # if not found use the external search engines\n if not subtitle_url:\n links = external_search_engines_links(search, deep, debug)\n subtitle_url = download_best_subtitle(links,\n full_search,\n path_file_name,\n min_match, force, debug)\n\n return subtitle_url","def get_title_similarity(self):\n title_words = []\n ignore_words = ['the', 'and', 'or', 'to', 'at', 'on', 'of']\n for w in self.target_movie.title.split(' '):\n w = w.strip('- ,:(){}[]')\n if w.lower() not in ignore_words:\n title_words.append(w)\n\n # if last word is a number then it's an year and should be ignored.\n if len(title_words) > 1 and title_words[-1].isdigit():\n title_words = title_words[:-1]\n\n print(title_words)\n res = self.db.query(Movie).filter(\n Movie.movie_id != self.target_movie.movie_id).filter(or_(\n Movie.title.ilike(r'%' + tw + r'%') for tw in title_words\n )).all()\n\n target_clean_title = string_cleanup(self.target_movie.title)\n\n print(\"%i records from partial title match\" % len(res))\n TSW = self.TITLE_SIMILARITY_WEIGHT\n for rec in res:\n mc_title = string_cleanup(rec.title)\n smid = rec.movie_id\n if smid not in self.recommendation_pool:\n self.recommendation_pool[smid] = {\n 'movie_obj': rec,\n 'title_similarity': jaccard_index(\n target_clean_title, mc_title, ' ') * TSW\n }\n\n else:\n self.recommendation_pool[smid]['title_similarity'] = \\\n jaccard_index(\n target_clean_title, mc_title, ' ') * TSW","def download_best_subtitle(links, full_search, path_file_name,\n min_match=0, force=0, debug=0):\n s = Subseek()\n if not links or len(links) == 0:\n return False\n else:\n results = []\n for link in links:\n if debug == 1:\n print \"Searching in \" + link['link']\n for provider in SUBTITLE_PROVIDERS:\n results_aux = s.get_subtitles_links(link['link'],\n provider)\n if results_aux is False or len(results_aux) == 0:\n if debug == 1:\n print \"No subtitles with '%s'\" % provider['name']\n else:\n if debug == 1:\n print \"%s subtitles with '%s'\" % (len(results_aux),\n provider['name'])\n results = results + results_aux\n # download the best subtitle of the entire list\n return download_subtitle(full_search,\n results,\n path_file_name,\n min_match,\n force,\n debug)","def content_model(movie_list,top_n):\r\n # Vectorise content for each movie in list_title\r\n input_matrix = vectoriser.transform(movies[movies['title'].isin(movie_list)].content)\r\n \r\n # Initiate list to store indeces of input movies\r\n m_idx = []\r\n \r\n for title in movie_list:\r\n for id in movies.movieId[movies['title']==title]:\r\n m_idx.append(indices[id])\r\n \r\n # Create list of similarities between each input movie and every other movie in the dataset \r\n sim = list(enumerate(cosine_similarity(content_matrix,\r\n input_matrix))) \r\n\r\n # Sort the list by the average similarity of the movies\r\n sim_scores = sorted(sim, key=lambda x: x[1].mean(), reverse=True)\r\n \r\n # Select the top-k values for recommendation\r\n sim_scores = sim_scores[0:20]\r\n\r\n # Select the indices of the top-k movies\r\n movie_indices = [i[0] for i in sim_scores if i[0] not in m_idx]\r\n \r\n # Return a list of the movie titles\r\n return movies.iloc[movie_indices].title[:top_n]","def get_most_similar_title(self, id, id_list):\n clf = self._get_model()\n vocab = clf.wv.vocab\n if id not in vocab:\n return \"\"\n id_list = [id for id in id_list if id in vocab] # ensure all in vocab\n id_book = self.id_book\n match = clf.wv.most_similar_to_given(id, id_list)\n return id_book['primaryTitle'].loc[id_book['tconst'] == int(match)].values[0]","def edx_get_subtitle(url, headers):\n \"\"\" or None if no subtitles are available \"\"\"\n try:\n jsonString = get_page_contents(url, headers)\n jsonObject = json.loads(jsonString)\n return edx_json2srt(jsonObject)\n except URLError as e:\n print('[warning] edX subtitles (error:%s)' % e.reason)\n return None\n except ValueError as e:\n print('[warning] edX subtitles (error:%s)' % e.message)\n return None","def getSubtitleURL(self):\n\n # If it is a movie, we use this methodology -\n try:\n IndexingParameters = [\"subtitleUrls\", 0, \"url\"]\n TitleParamters = [\n \"catalogMetadata\", \"catalog\", \"title\", \"episodeNumber\"]\n subRequestObject = requests.get(self.subtitleURLContainer)\n\n parsedJsonObject = json.loads(str(subRequestObject.text))\n SubsURL = parsedJsonObject[IndexingParameters[0]][\n IndexingParameters[1]][IndexingParameters[2]]\n if self.title == \"Amazonsubtitles\":\n try:\n self.title = parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[2]] + \"_\" + str(\n parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[3]])\n except:\n pass\n\n return SubsURL\n\n except:\n pass\n pass","def stat_subtitle(self, release_name, movie_dir):\n ret = {}\n for root_dir, child_folders, file_names in os.walk(movie_dir):\n for file_name in file_names:\n if not file_name.startswith(release_name):\n continue\n\n subtitle_info = get_subtitle_info(file_name)\n if not subtitle_info:\n continue\n\n if 'lang' not in subtitle_info:\n continue\n\n lang = subtitle_info['lang']\n if lang not in ret:\n ret[lang] = []\n\n ret[lang].append(file_name)\n\n # Sort result\n for lang in ret:\n ret[lang] = sorted(ret[lang])\n\n return ret","def tabler(subcorpus_names, list_of_dicts, num_rows):\n import pandas as pd\n cols = []\n for subcorp, data in zip(subcorpus_names, list_of_dicts):\n col = pd.Series([w for w, v in data.most_common(num_rows)], name = subcorp)\n cols.append(col)\n word_table = pd.concat(cols, axis = 1)\n return word_table","def content_model(movie_list,top_n=10):\n # Initializing the empty list of recommended movies\n recommended_movies = []\n data = data_preprocessing(27000)\n # Instantiating and generating the count matrix\n count_vec = CountVectorizer()\n count_matrix = count_vec.fit_transform(data['keyWords'])\n indices = pd.Series(data['title'])\n cosine_sim = cosine_similarity(count_matrix, count_matrix)\n # Getting the index of the movie that matches the title\n idx_1 = indices[indices == movie_list[0]].index[0]\n idx_2 = indices[indices == movie_list[1]].index[0]\n idx_3 = indices[indices == movie_list[2]].index[0]\n # Creating a Series with the similarity scores in descending order\n rank_1 = cosine_sim[idx_1]\n rank_2 = cosine_sim[idx_2]\n rank_3 = cosine_sim[idx_3]\n # Calculating the scores\n score_series_1 = pd.Series(rank_1).sort_values(ascending = False)\n score_series_2 = pd.Series(rank_2).sort_values(ascending = False)\n score_series_3 = pd.Series(rank_3).sort_values(ascending = False)\n # Getting the indexes of the 10 most similar movies\n listings = score_series_1.append(score_series_1).append(score_series_3).sort_values(ascending = False)\n\n # Store movie names\n recommended_movies = []\n # Appending the names of movies\n top_50_indexes = list(listings.iloc[1:50].index)\n # Removing chosen movies\n top_indexes = np.setdiff1d(top_50_indexes,[idx_1,idx_2,idx_3])\n for i in top_indexes[:top_n]:\n recommended_movies.append(list(movies['title'])[i])\n return recommended_movies","def find_table_by_title(table_list, title_pattern, index=0):\n\n rtable_list = find_tables_by_title(table_list, title_pattern)\n try:\n return rtable_list[index]\n except Exception:\n return None","def get_subtitle(annotation, sub_duration, video_clip, seen_annotations):\n if len(annotation[\"text\"]) == 0:\n return None\n\n annotation_txt = calculate_needed_subtitle_height(annotation, seen_annotations, video_clip)\n\n txt_clip = TextClip(annotation_txt, color=\"white\", fontsize=70, font='Sans Serif')\n txt_clip = txt_clip.set_position((\"center\", get_subtitle_offset(annotation, seen_annotations, video_clip)))\n txt_clip = txt_clip.set_start(float(annotation[\"time\"]) / 1000.0)\n txt_clip = txt_clip.set_duration(sub_duration)\n\n return txt_clip","def get_top_games_from_title_for_movie(mov_tmt_path: str,\n candidate_games: List[str],\n threshold=0.5) -> List[Dict]:\n if not mov_tmt_path or not candidate_games:\n return []\n ranking_info = get_matched_game_ranking_info_for_movie(\n movie_id=mov_tmt_path)\n res = []\n for app_id, score in ranking_info.items():\n if score >= threshold and app_id in candidate_games:\n game_obj: Game = Game.query.filter_by(app_id=app_id).all()[0]\n game_info = {\n 'app_id': app_id,\n 'name': game_obj.name,\n 'developer': \", \".join(json.loads(game_obj.developer)),\n 'publisher': \", \".join(json.loads(game_obj.publisher)),\n 'tags': json.loads(game_obj.tags),\n 'genre': json.loads(game_obj.genre),\n 'single_player': game_obj.single_player,\n 'multi_player': game_obj.multi_player,\n 'rating': game_obj.rating,\n 'mature_content': game_obj.mature_content,\n 'title_match_score': score}\n res.append(game_info)\n return res","def find_movie(imdb_file, title_regex):\n\n process = subprocess.run([\n \"grep\",\n \"-i\", # Case insensitive\n f'movie\\t[^\\t]*{title_regex}', # Only match movies\n imdb_file\n ], stdout=subprocess.PIPE)\n hits = [dict(zip(COLUMNS, hit.decode(\"utf-8\").split(\"\\t\")))\n for hit in process.stdout.split(b\"\\n\")[:-1]]\n # Try to filter out irrelevant hits, e.g. that don't yet exist or are porn\n legitimate_hits = [hit for hit in hits\n if hit[\"startYear\"] != \"\\\\N\" and\n hit[\"isAdult\"] == \"0\"]\n return legitimate_hits","def edx_get_subtitle(url, headers):\n try:\n json_object = get_page_contents_as_json(url, headers)\n return edx_json2srt(json_object)\n except URLError as e:\n _print('[warning] edX subtitles (error:%s)' % e.reason)\n return None\n except ValueError as e:\n _print('[warning] edX subtitles (error:%s)' % e.message)\n return None","def play_movie_with_subs(self, filmid):\n self.logger.debug('play_movie_with_subs')\n start = time.time()\n #\n film = self.database.retrieve_film_info(filmid)\n if film is None:\n self.logger.error(\"no film for download \" + self.plugin.language(30991))\n self.notifier.show_error(30990, self.plugin.language(30991))\n return\n ttmname = os.path.join(self.settings.getDatapath(), 'subtitle.ttml')\n srtname = os.path.join(self.settings.getDatapath(), 'subtitle.srt')\n subs = []\n if self.download_subtitle(film, ttmname, srtname, 'subtitle'):\n subs.append(srtname)\n # (_, listitem) = FilmUI(self.plugin).get_list_item(None, film)\n (_, listitem) = FilmlistUi(self.plugin)._generateListItem(film)\n self.logger.debug('SUBTITLE FOUND {} from url {}' , subs, film.url_sub)\n if listitem:\n if subs:\n listitem.setSubtitles(subs)\n self.plugin.set_resolved_url(True, listitem)\n self.logger.debug('play_movie_with_subs processed: {} sec', time.time() - start)","def load_top_video(self):\n\n if self.general_parser is None or \\\n self.specific_parser is None or \\\n ((self.video_parser is None) and (self.video_data_parser is None)):\n self.missing_files_label.grid(row=13, column=5)\n raise Exception(\"you need to load the general, month-specific, and video words first\")\n else:\n self.missing_files_label.grid_remove()\n\n if self.month_selected is None:\n self.no_month_selected_label.grid(row=14, column=5, columnspan=1)\n else:\n self.no_month_selected_label.grid_remove()\n\n self.top_unique_video = self.find_top_unique(self.video_entries,\n int(self.top_unique_video_entry.get()))\n\n self.top_unique_video_box.delete(0, END)\n\n box_count = 0\n for rank, words in enumerate(self.top_unique_video):\n for index, word in enumerate(words):\n self.top_unique_video_box.insert(box_count,\n str(word.rank)+ \". \" +\n word.word +\n \" - \" + str(word.count))\n box_count += 1\n\n self.unique_video_found = True","def get_subtitles(self, index: int):\n\n match = self.re_subs[index - 1]\n start = convert_subs_time(match[1])\n end = convert_subs_time(match[2])\n subtitles = match[3]\n subtitles = clean_text(subtitles)\n\n return (subtitles, start, end)","def top_controversial(self, n):\n return top_movies","def extract_movie_titles(dictionary):\n results = dictionary['Similar']['Results']\n lstmt = [d['Name'] for d in results]\n return lstmt","def get_movie_longest_runtime(movies: list) -> str:\n pass","def download_subtitle(self, film, ttmname, srtname, filename):\n self.logger.debug('download_subtitle')\n ret = False\n if film.url_sub:\n progress = KodiProgressDialog()\n progress.create(30978, filename + u'.ttml')\n # pylint: disable=broad-except\n try:\n progress.update(0)\n mvutils.url_retrieve_vfs(\n film.url_sub, ttmname, progress.url_retrieve_hook)\n try:\n ttml2srtConverter = ttml2srt()\n ttml2srtConverter.do(xbmcvfs.File(ttmname, 'r'),\n xbmcvfs.File(srtname, 'w'))\n ret = True\n except Exception as err:\n self.logger.error('Failed to convert to srt: {}', err)\n progress.close()\n except Exception as err:\n progress.close()\n self.logger.error(\n 'Failure downloading {}: {}', film.url_sub, err)\n return ret","def get_matched_game_ranking_info_for_movie(movie_id: str) -> Dict[str, int]:\n query_res = Movie.query.filter_by(link_id=movie_id).all()\n if query_res:\n return eval(query_res[0].games_title_match)\n return dict()","def get_time_intervals(subtitle, regex=r\"\\S+\"):\n # module webvtt only gets the line-captions, not individual words, so it's time for some regex!\n # The time corresponding to a word is when that word *starts*\n # words = (match.group(\"word\") for match in WORD_REGEX.finditer(subtitle))\n time_words = [\n (m.group(\"time1\") or m.group(\"time2\"), m.group(\"word1\") or m.group(\"word2\"))\n for m in TIME_WORD_REGEX.finditer(subtitle)\n ]\n # Incorrect format, which would lead to trouble zipping\n if len(time_words) == 0:\n return []\n times, words = zip(*time_words)\n # Quickly search lines starting from the end\n final_time = next(match.group(\"time\") for line in reversed(subtitle.split(\"\\n\")) for match in [re.search(FINAL_TIME_REGEX, line)] if match)\n # timestamps[i] is the time the word starts at if i is the index of the start of a word\n timestamps = {}\n word_indices = {}\n # Build search_str while computing time_stamps by adding one word and one space at a time\n search_str = ''\n words = list(words)\n last_time = 0\n for j, (word, time) in enumerate(zip(words, times)):\n i = len(search_str)\n time = parse_time(time)\n timestamps[i] = time\n if time - last_time > 10:\n search_str += '[ … ] '\n last_time = time\n word_indices[i] = j\n search_str += word + ' '\n i = len(search_str)\n timestamps[i] = final_time\n word_indices[i] = len(words)\n # Trim off the final space\n # Inconsistent capitalization, so just lowercase\n search_str = search_str[:-1].lower()\n for match in re.finditer(regex, search_str):\n start, end = match.span()\n start_index = max(i for i in timestamps if i<=start)\n end_index = min(i for i in timestamps if i>end)\n yield Interval(\n timestamps[start_index],\n timestamps[end_index],\n word_indices[start_index],\n word_indices[end_index],\n match.group(0)\n )","def _best_song_match(songs, title, duration):\n # pylint: disable=R0914\n seqmatch = difflib.SequenceMatcher\n\n def variance(a, b):\n \"\"\" Return difference ratio. \"\"\"\n return float(abs(a - b)) / max(a, b)\n\n candidates = []\n\n ignore = \"music video lyrics new lyrics video audio\".split()\n extra = \"official original vevo\".split()\n\n for song in songs:\n dur, tit = int(song.length), song.title\n dbg(\"Title: %s, Duration: %s\", tit, dur)\n\n for word in extra:\n if word in tit.lower() and word not in title.lower():\n pattern = re.compile(word, re.I)\n tit = pattern.sub(\"\", tit)\n\n for word in ignore:\n if word in tit.lower() and word not in title.lower():\n pattern = re.compile(word, re.I)\n tit = pattern.sub(\"\", tit)\n\n replacechars = re.compile(r\"[\\]\\[\\)\\(\\-]\")\n tit = replacechars.sub(\" \", tit)\n multiple_spaces = re.compile(r\"(\\s)(\\s*)\")\n tit = multiple_spaces.sub(r\"\\1\", tit)\n\n title_score = seqmatch(None, title.lower(), tit.lower()).ratio()\n duration_score = 1 - variance(duration, dur)\n dbg(\"Title score: %s, Duration score: %s\", title_score,\n duration_score)\n\n # apply weightings\n score = duration_score * .5 + title_score * .5\n candidates.append((score, song))\n\n best_score, best_song = max(candidates, key=lambda x: x[0])\n percent_score = int(100 * best_score)\n return best_song, percent_score","def get_subjects(cur, table):\n cur.execute('SELECT subj FROM {}'.format(table))\n d = cur.fetchall()\n\n subj = []\n for sub in d:\n subj.append(str(sub[0]))\n subj.sort()\n\n return subj","def extract_subtitle_track(path_to_mkv):\n handler = SubtitleHandler()\n with open(path_to_mkv, \"rb\") as fp:\n mkvparse.mkvparse(fp, handler)\n\n return handler.subs","def read_table(self):\n\n db = self.connection(database=\"imdb\")\n\n try:\n cur = db.cursor()\n sql = \"SELECT title FROM film;\"\n cur.execute(sql)\n return cur.fetchall()\n except:\n print(\"Cannot read from table!\")\n\n db.close()","def make_movie(processed_files_directory='files/', WITH_SUBTITLES=False, WITH_AUDIO=False):\r\n # Declare the text for sub-titles\r\n\r\n if WITH_SUBTITLES: # if the user is willing to have subtitles in the movie\r\n with open(processed_files_directory+'subtitles.txt', 'r', encoding='utf8') as f:\r\n txt = f.read() # read the subtitles file\r\n # Split text to lines.\r\n subtitles = txt.split('\\n')\r\n # Declare VideoFileClip from the movie that I already have.\r\n clip = VideoFileClip(processed_files_directory + \"initial.avi\")\r\n # Declare duration of one sub-title as total duration of the video divided by number of lines.\r\n duration = clip.duration/len(subtitles)\r\n # Set start to zero.\r\n start=0\r\n # Set container for the clips.\r\n videos=[]\r\n # Loop all sub-titles\r\n for line in subtitles:\r\n # Make text clip from the reversed Hebrew text\r\n txt_clip = TextClip(line[::-1], fontsize=30, color='yellow', font='Calibri')\r\n # Set position to the bottom of screen.\r\n txt_clip = txt_clip.set_position('bottom').set_duration(duration)\r\n # Make sub clip of the movie with same duration as text clip.\r\n sub_clip = clip.subclip(start,start+duration)\r\n # Set CompositeVideoClip from the text clip and sub clip.\r\n video = CompositeVideoClip([sub_clip, txt_clip])\r\n # Insert the video to the clips container\r\n videos.append(video)\r\n # Set start time for next sub-title.\r\n start+=duration\r\n # Concatenate all clips of the container.\r\n res = concatenate_videoclips(videos)\r\n clip = res # now the clip is res\r\n else:\r\n clip = VideoFileClip(processed_files_directory+ \"initial.avi\") # the clip won't have subtitles\r\n\r\n\r\n # Set audio clip from mp3 file.\r\n if WITH_AUDIO: # if the user has chosen to include soundtrack in the movie\r\n f = 'audio.mp3' # change to mp3 soundtrack file of the movie\r\n # set the duration of the audioclip to max(duration of clip), even if the audioclip is longer\r\n audioclip = AudioFileClip(processed_files_directory+f)\r\n\r\n # check if the clip length is bigger than the\r\n if clip.duration > audioclip.duration:\r\n number_of_duplicated = int(np.ceil(clip.duration/audioclip.duration))\r\n # duplicate the audioclip in order to later fit the movie's duration\r\n audioclip = concatenate_audioclips([AudioFileClip(processed_files_directory+f) for i in range(number_of_duplicated)])\r\n\r\n # Now fit the audioclip duration to the movie's\r\n audioclip = audioclip.set_duration(clip.duration)\r\n\r\n # Set audio for the container.\r\n if not WITH_SUBTITLES: # if the user wanted to have audio included without subtitles\r\n videoclip = clip.set_audio(audioclip)\r\n else: # if the user wanted to have both audio and subtitles\r\n videoclip = res.set_audio(audioclip)\r\n else:\r\n videoclip = clip # if the user didn't want audio in the movie\r\n\r\n # Write the video file.\r\n f = 'final_movie.mp4' # change to the desired movie filename\r\n videoclip.write_videofile(processed_files_directory+f)","def getSubtitleTable(date) -> str:\n return \"\"\"| Start of the day | Weeks until NIMCET |\n| ---------------- | -----------------: |\n| {time} | {weeks} weeks |\"\"\".format(time=formattedTimeNow(), weeks=round((datetime(2021, 5, 21) - date).days/7, 1))","def findtable(self, title_pattern, index=0):\n return find_table_by_title(self.__tables, title_pattern, index)","def findtable(self, title_pattern, index=0):\n return find_table_by_title(self.__tables, title_pattern, index)","def get_words_with_end_times(subtitle_file_path):\n\n with open(subtitle_file_path) as subtitle_file:\n\n # Remove first 4 lines (containing meta information)\n for j in range(0, 4):\n subtitle_file.readline()\n\n text = subtitle_file.read()\n\n # Check if the subtitle file supports individual word times\n if text.find(\"<c>\") == -1:\n print(\"Individual word times are not supported for file: \" + subtitle_file_path)\n return None, None\n\n chunks = text.split(\" \\n\\n\") # split into chunks for easier data processing\n\n words = list()\n word_end_times = list()\n\n for chunk in chunks:\n chunk_lines = chunk.split(\"\\n\")\n words_line = chunk_lines[2]\n\n words_in_chunk = []\n word_end_times_in_chunk = []\n\n first_word_end_index = words_line.find(\"<\")\n if first_word_end_index != -1:\n first_word = words_line[\n 0:first_word_end_index] # get the first word (can't be found using method below)\n\n words_in_chunk = re.findall(\"<c> [\\S]*</c>\", words_line) # get all words\n words_in_chunk = [w[4:-4] for w in words_in_chunk] # strip <c> and <c/>\n\n word_end_times_in_chunk = re.findall(\"<\\d\\d:\\d\\d:\\d\\d.\\d\\d\\d>\", words_line) # get all word end times\n word_end_times_in_chunk = [t[1:-1] for t in word_end_times_in_chunk] # strip < and >\n else:\n # Only one word\n first_word = words_line\n\n last_time = chunk_lines[4][17:29] # end time for the last word\n\n words_in_chunk.insert(0, first_word)\n word_end_times_in_chunk.append(last_time)\n\n words.extend(words_in_chunk)\n word_end_times.extend(word_end_times_in_chunk)\n\n # For the last chunk we have to get the word end time from somewhere else\n first_line_in_last_chunk = chunks[-1].split(\"\\n\")[0]\n last_time = first_line_in_last_chunk[17:29]\n word_end_times.pop()\n word_end_times.append(last_time)\n\n if len(words) != len(word_end_times):\n print(\"Warning: word count does not match times count\")\n\n return words, word_end_times","def mostlikelycodeword(self):\n\n # Add your code here\n stoping_int = None # Replace\n best, first_index, last_index = None, None, None # Replace all three with an integer\n for i in range(stoping_int):\n for j in range(None, stoping_int): # Replace None. \n current = self.quality(None, None)\n if None > None # Replace both Nones\n best, first_index, last_index = current, i, j\n return self.preamble[None:None]","def get_movie_longest_runtime():\n tree = get_tree()\n movie_runtimes = [(movie.get(\"title\"), movie.get(\"runtime\")) for movie in tree.getroot().findall(\"movie\")]\n\n # one way\n result = sorted(movie_runtimes, key=lambda movie_runtimes: movie_runtimes[1], reverse = True)[0][0]\n return result\n \n # another way\n # result = max(movie_runtimes, key=lambda movie_runtimes: movie_runtimes[1])[0]\n # return result","def get_frames_and_titles(video_label):\n\n frames = []\n titles = []\n cap = cv2.VideoCapture(video_label)\n frameRate = cap.get(5) # frame rate\n numero = 29\n index = 0\n while (cap.isOpened()):\n frameId = cap.get(1) # current frame number\n ret, frame = cap.read()\n # Apply template Matching\n if (ret != True):\n break\n if (frameId % math.floor(frameRate) == 0):\n frames.append(frame)\n index = index\n titles.append(\"Frame {}\".format(int(index / 30)))\n\n if numero > 30:\n break\n index = index + 1\n cap.release()\n\n return frames, titles","def get_subtitles(self, title):\n return library.subtitles.get_subtitle_url(title)","def _get_info(self, id, score=None):\n try:\n info_query = f\"\"\"\n SELECT m.primary_title, m.start_year, r.average_rating, r.num_votes\n FROM movies m\n JOIN ratings r ON m.movie_id = r.movie_id\n WHERE m.movie_id = '{id}'\"\"\"\n self.cursor_dog.execute(info_query)\n except Exception as e:\n return tuple([f\"Movie title unknown. ID:{id}\", None, None, None, None, None, None, id])\n\n t = self.cursor_dog.fetchone()\n if t:\n title = tuple([t[0], t[1], f\"https://www.imdb.com/title/tt{id}/\",\n f\"https://www.letterboxd.com/imdb/tt{id}/\", t[2], t[3], score, id])\n return title\n else:\n return tuple([f\"Movie title not retrieved. ID:{id}\", None, None, None, None, None, None, id])","def dp_match(phrase, songs=None):\n scores = [score_match(phrase, song) for song in songs]\n i = scores.index(max(scores))\n return scores[i], [phrase], [songs[i]]","def recognition(database, testSong, plot=True, info=True, latextable=False):\n #Score for every song in database with respect to testsong\n \n if latextable == True:\n print(testSong[\"name\"])\n print(\"\"\"\\\\begin{table}[H]\n \\centering\n \\\\begin{tabular}{|l|l|}\n \\hline\n Artist and Title & Score value\\\\\\\\\n \\hline\n \"\"\")\n for i in range(len(database)):\n scores = []\n for j in range(testSong[\"spectrogram\"].shape[1]): #every frame of STFT\n #Score is calculated\n u = np.transpose(database[i][\"eigen\"]) @ (testSong[\"spectrogram\"][:, j] - database[i][\"mean\"])\n scores.append(LA.norm(u - database[i][\"weights\"][:, j]))\n #mean value of the scores\n database[i][\"score\"] = sum(scores)/len(scores)\n if latextable == True:\n print(f'{database[i][\"name\"]} & {database[i][\"score\"]:0.7} \\\\\\\\')\n if info == True and latextable != True:\n print(f\"{database[i]['name']} has a score of {database[i]['score']}\")\n if plot == True:\n plt.plot(scores)\n plt.title(f\"{database[i]['name'].split('.w')[0]}\\n testsong: {testSong['name'].split('/')[1].split('(o')[0]}\")\n plt.show()\n\n #The lowest score is found and is the most alike to testSong\n lowsScore = database[0]\n for song in database[1:]:\n if lowsScore[\"score\"] > song[\"score\"]:\n lowsScore = song\n if info == True and latextable != True: \n print(\" \")\n print(f\"The song with the lowest score is {lowsScore['name']} with a score of {lowsScore['score']}\")\n \n if latextable == True:\n print(\"\"\"\\hline\n\\end{tabular}\n\\caption{Recognition of a recorded version of \"\"\" + testSong[\"name\"] + \"\"\" and the coherent score value.}\n\\label{tab: }\n\\end{table}\"\"\")\n print(\" \")\n return lowsScore['name'], lowsScore['score']","def update_storyline(self):\n search_title = self.video_title.replace(\" \", \"+\")\n api_response = urllib.urlopen(\"https://api.themoviedb.org/3/search/\"+\n \"movie?api_key=0bf3188c8eacc47d41ae97\"+\n \"d1d6dd2cfc&query=\"+\n search_title)\n movie_data = api_response.read()\n api_response.close()\n if '\"overview\":\"' in movie_data:\n #finding first position of storyline from API data\n apos = movie_data.find('\"overview\":\"') + 12\n #finding last position of storyline\n bpos = movie_data.find('\",', apos)\n return movie_data[apos:bpos]\n else:\n return","def convert_to_tvr_subtitle(df: pd.DataFrame) -> pd.DataFrame:\n\tpass","def get_by_title(title):\n query = Session.query(Movie.title)\n result = query.all()\n title_list = [title for title, in result]\n one_item = process.extractOne(title, title_list)\n if one_item:\n result_title, ratio = one_item\n else:\n return None\n if ratio > 60:\n return result_title\n else:\n return None","def most_similar_actors_lda(self, moviename):\n data_frame = self.data_extractor.get_mlmovies_data()\n tag_data_frame = self.data_extractor.get_genome_tags_data()\n movie_data_frame = self.data_extractor.get_mltags_data()\n movie_tag_data_frame = movie_data_frame.merge(tag_data_frame, how=\"left\", left_on=\"tagid\", right_on=\"tagId\")\n movie_tag_data_frame = movie_tag_data_frame.merge(data_frame, how=\"left\", left_on=\"movieid\", right_on=\"movieid\")\n tag_df = movie_tag_data_frame.groupby(['movieid'])['tag'].apply(list).reset_index()\n\n tag_df = tag_df.sort_values('movieid')\n movies = tag_df.movieid.tolist()\n tag_df = list(tag_df.iloc[:, 1])\n\n input_movieid = self.util.get_movie_id(moviename)\n\n (U, Vh) = self.util.LDA(tag_df, num_topics=5, num_features=1000)\n\n movie_topic_matrix = self.util.get_doc_topic_matrix(U, num_docs=len(movies), num_topics=5)\n topic_movie_matrix = movie_topic_matrix.transpose()\n movie_movie_matrix = numpy.dot(movie_topic_matrix, topic_movie_matrix)\n\n index_movie = None\n for i, j in enumerate(movies):\n if j == input_movieid:\n index_movie = i\n break\n\n if index_movie == None:\n print(\"Movie Id not found.\")\n return None\n\n movie_row = movie_movie_matrix[index_movie].tolist()\n movie_movie_dict = dict(zip(movies, movie_row))\n del movie_movie_dict[input_movieid]\n\n for key in movie_movie_dict.keys():\n movie_movie_dict[key] = abs(movie_movie_dict[key])\n\n movie_movie_dict = sorted(movie_movie_dict.items(), key=operator.itemgetter(1), reverse=True)\n\n if movie_movie_dict == None:\n return None\n actors = []\n for (movie, val) in movie_movie_dict:\n if val <= 0:\n break\n actors = actors + self.sim_act_diff_mov_tf.get_actors_of_movie(self.util.get_movie_name_for_id(movie))\n if len(actors) >= 10:\n break\n\n actors_of_given_movie = self.sim_act_diff_mov_tf.get_actors_of_movie(moviename)\n\n actorsFinal = [x for x in actors if x not in actors_of_given_movie]\n\n actornames = []\n for actorid in actorsFinal:\n actor = self.util.get_actor_name_for_id(actorid)\n actornames.append(actor)\n\n return actornames","def test_get_subtitles(self):\n\n (subtitles, start, end) = self.sp.get_subtitles(INDEX)\n self.assertEqual(subtitles, INDEX_SUBTITLES, 'Check get_subtitles.')","def get_best_candidate(self):\n if not self.scores:\n return None\n return self.te_list[self.scores.index(max(self.scores))]","def display_get_most_played():\n title_game = reports.get_most_played(filename)\n print(\"Title of most played game in {}: {}\\n\".format(filename, title_game))","def get_related_titles(lstmt):\n lst = []\n for mtitle in lstmt:\n dtitle = get_movies_from_tastedive(mtitle)\n mlst = extract_movie_titles(dtitle)\n for movie in mlst:\n if movie not in lst:\n lst.append(movie)\n return lst","def get(self):\n parser.add_argument('title-word', required=True, help='cannot be blank')\n return find_movie_by_title(parser.parse_args()['title-word'])","def find_best_match(filename, e):\n best_matches = {}\n with open(filename) as f:\n for record in NCBIXML.parse(f):\n best = e\n best_name = \"\"\n if record.alignments:\n for alignment in record.alignments:\n locus = alignment.definition.split(\" \")[0].split(\"|\")[1]\n for hsp in alignment.hsps:\n if hsp.expect < best:\n best_name = name\n best = hsp.expect\n\n if best < e:\n iden = record.query.split(\" \")[0]\n best_matches[iden] = a_best_ma\n\n return transcription_factors","def find_movie_by_title(title):\n return Movie.objects.filter(title=title).first()","def get_subtitle_print(subs: List[Track]) -> List[str]:\n data = []\n if not subs:\n data.append(\"--\")\n for sub in subs:\n line_items = []\n\n # following sub.title tree checks and supports three different language and title scenarios\n # The second scenario is the recommended option to choose if you are open to choosing any\n # The third scenario should be used if you have nothing unique to state about the track\n # | Language | Track Title | Output |\n # | ------------ | ----------------------------- | --------------------------------------------- |\n # | es / Spanish | Spanish (Latin American, SDH) | - Spanish (Latin American, SDH), SubRip (SRT) |\n # | es / Spanish | Latin American (SDH) | - Spanish, Latin American (SDH), SubRip (SRT) |\n # | es / Spanish | None | - Spanish, SubRip (SRT) |\n language = pycountry.languages.get(alpha_2=sub.language).name\n if sub.title:\n if language.lower() in sub.title.lower():\n line_items.append(sub.title)\n else:\n line_items.append(f\"{language}, {sub.title}\")\n else:\n line_items.append(language)\n\n line_items.append(sub.format.replace(\"UTF-8\", \"SubRip (SRT)\"))\n\n line = \"- \" + \", \".join(line_items)\n data += [\n (\" \" + x if i > 0 else x)\n for i, x in enumerate(textwrap.wrap(line, 64))\n ]\n return data","def get_cheapest_price(self, movie_title):\n self.get_all_movies()\n movie_list = self.title_map.get(movie_title.strip().lower(), [])\n\n if movie_list is None:\n return None\n\n pick_list = []\n for movie_info in movie_list:\n try:\n movie_id = movie_info['ID']\n movie_world = movie_info['world']\n except KeyError as e:\n print(\"Price is not available for {}\".format(movie_title))\n continue\n pick_list.append({'id': movie_id, 'world': movie_world})\n\n if pick_list is None:\n return None\n\n pool = Pool(2)\n movies_list = pool.map(self.get_movie_from_id, pick_list)\n pool.close()\n pool.join()\n\n # Set price as maximum float value in start to find minimum value\n price = sys.float_info.max\n print(\"\\nMovie info from different worlds:\\n\")\n for movie in movies_list:\n if movie is None:\n continue\n print(\"[{}]\".format(movie['world']))\n for key, value in movie.items():\n print(\" {} = {}\".format(key, value))\n print(\"\\n\")\n try:\n movie_price = float(movie['Price'])\n except KeyError as e:\n print(\"Price is not available for {}\".format(movie_title))\n continue\n if movie_price < price:\n price = movie_price\n\n if price == sys.float_info.max:\n return None\n\n return str(price)","def get_movie_most_nominations(movies: list) -> str:\n pass","def return_movie_list(url: str) -> (bs4.element.NavigableString, list, list):\n soup = return_beautiful_soup_object(url)\n cell_data_list = soup.find('body').find('div', {'class': 'col-left-center'}).find('table').find_all('td')\n span_rating_list = list([cell.find_all('span', {'class': 'tMeterScore'}) for cell in cell_data_list])\n rating_list = list([span[0].text.strip() for span in span_rating_list if span != []])\n movies = list(movie[0].text.strip() for movie in list([cell.find_all('a') for cell in cell_data_list])\n if movie != [])\n return soup.title.contents[0], movies, rating_list","def _match_movie_titles(self, cinema_schedule_data):\n matcher = MovieIDMatcher()\n invalid_titles = []\n for title, content in cinema_schedule_data.items():\n\n logging.warning(\"Matching movie: \" + title)\n\n imdb_id = matcher.match_imdb_id_from_title_recent(title)\n if imdb_id is None:\n logging.error(\"IMDb ID matched is invalid!\")\n invalid_titles.append(title)\n continue\n\n cinema_schedule_data[title] = {\n 'imdb_id': imdb_id,\n 'content': content\n }\n self.update_single_movie_data(imdb_id)\n logging.warning(\"matching successful!\")\n\n for invalid_title in invalid_titles:\n cinema_schedule_data.pop(invalid_title)","def select_best_match(self, normalized_texts: List[str], transcript: str, verbose: bool = False):\n normalized_texts = calculate_cer(normalized_texts, transcript)\n normalized_texts = sorted(normalized_texts, key=lambda x: x[1])\n normalized_text, cer = normalized_texts[0]\n\n if verbose:\n print('-' * 30)\n for option in normalized_texts:\n print(option)\n print('-' * 30)\n return normalized_text, cer","def get_top_words(self, label, n):\n score_list = []\n if('sod' in label):\n for term in self.vocab:\n score = self.cond_prob_sod[term] / self.cond_prob_pop[term]\n score_list.append((score,term)) \n else:\n for term in self.vocab:\n score = self.cond_prob_pop[term] / self.cond_prob_sod[term]\n score_list.append((score,term))\n score_list = sorted(score_list, key=lambda x:x[0],reverse=True)[:n]\n return score_list \n pass","def get_best(self):\n scores, ids = self.sort_best()\n return scores[1], ids[1]","def generate_subtitles(\n source_path,\n output=None,\n dst_language=DEFAULT_DST_LANGUAGE,\n debug=False,\n cloud=False,\n disable_time=False,\n min_height=80,\n max_height=100,\n l_v=240\n ):\n # Opens the Video file\n print(f\"starting: using cloud {cloud}, source_path {source_path}\")\n if not cloud:\n ocr = PaddleOCR(lang='ch', use_gpu=False,\n rec_model_dir=r\"C:\\autosub_models\\rec\",\n cls_model_dir=r\"C:\\autosub_models\\cls\",\n det_model_dir=r\"C:\\autosub_models\\det\",\n use_angle_cls=True,\n rec_char_type='ch',\n drop_score=0.8,\n det_db_box_thresh=0.3,\n cls=True)\n\n cap = cv2.VideoCapture(source_path)\n # cap.set(3, 1280)\n # cap.set(4, 720)\n # cv2.createTrackbar(\"L - V\", \"Trackbars\", 0, 100, nothing)\n # cv2.createTrackbar(\"Min height\", \"Trackbars\", 80, 100, nothing)\n # cv2.createTrackbar(\"Max Height\", \"Trackbars\", 100, 100, nothing)\n fps = cap.get(cv2.CAP_PROP_FPS)\n print(f\"fps {fps}\")\n time_per_frame = 1 / fps\n i = 0\n div_frame = 6 # 5 frame /s\n sub_idx = 1\n list_srt = []\n old_des = \"\"\n prev_time = 0\n current_time = 0\n file_name = os.path.basename(source_path)\n extenstion = \".srt\" if not disable_time else \".txt\"\n filesub = f\"{os.path.splitext(file_name)[0]}{extenstion}\"\n if os.path.isfile(filesub):\n os.remove(filesub)\n while (cap.isOpened()):\n ret, frame = cap.read()\n if ret == False:\n break\n\n # min_height = cv2.getTrackbarPos(\"Min height\", \"Trackbars\")\n # max_height = cv2.getTrackbarPos(\"Max Height\", \"Trackbars\")\n # if max_height < min_height:\n # max_height = min_height + 10\n\n # l_v = cv2.getTrackbarPos(\"L - V\", \"Trackbars\")\n\n if i % div_frame == 0:\n prev_time_ts = datetime.utcfromtimestamp(prev_time).strftime('%H:%M:%S,%f')[:-4]\n current_time_ts = datetime.utcfromtimestamp(current_time).strftime('%H:%M:%S,%f')[:-4]\n h, w, c = frame.shape\n crop_img = frame[int(h * min_height/100):int(h * max_height/100), 0:w]\n hsv = cv2.cvtColor(crop_img, cv2.COLOR_BGR2HSV)\n\n # define range of white color in HSV\n # change it according to your need !\n lower_white = np.array([0, 0, 246], dtype=np.uint8)\n upper_white = np.array([157, 21, 255], dtype=np.uint8)\n\n # Threshold the HSV image to get only white colors\n mask = cv2.inRange(hsv, lower_white, upper_white)\n # Bitwise-AND mask and original image\n crop_img = cv2.bitwise_and(crop_img, crop_img, mask=mask)\n # crop_img = cv2.cvtColor(crop_img, cv2.COLOR_HSV2RGB)\n # crop_img = cv2.cvtColor(crop_img, cv2.COLOR_RGB2GRAY)\n\n description = \"\"\n if cloud:\n success, encoded_image = cv2.imencode('.jpg', crop_img)\n description = detect_texts_google_cloud(encoded_image.tobytes())\n else:\n # dst = cv2.fastNlMeansDenoisingColored(crop_img,None,10,10,7,21)\n # stacked = np.hstack((dst, crop_img))\n if debug:\n # cv2.imshow('dst', dst)\n cv2.imshow('crop_img', crop_img)\n cv2.imshow('frame', frame)\n cv2.waitKey(1)\n\n result = ocr.ocr(crop_img, det=False, rec=True, cls=False)\n for line in result:\n # print(current_time_ts, line)\n if line[1] > 0.7:\n description = html.unescape(line[0].strip().replace('，', '').replace('、', '').replace('．', ''))\n break\n\n description = \"\" if len(description) < 6 else description\n prev_des = \"\"\n ratio = fuzz.ratio(description.lower(), old_des.lower())\n if len(list_srt) > 0:\n prev_des = list_srt[-1]['description']\n\n print(current_time_ts, description, ratio)\n if (old_des != \"\" or description == \"\") and (ratio < 70) and current_time - prev_time > 0.5:\n list_srt.append({\n \"description\": old_des,\n \"translate\": translate_text(dst_language, old_des),\n \"first_time\": prev_time_ts,\n \"last_time\": current_time_ts,\n \"sub_idx\": sub_idx\n })\n # with open(f\"{os.path.splitext(file_name)[0]}_raw.srt\", \"a\", encoding=\"utf-8\") as myfile:\n # myfile.write(f\"{list_srt[-1]['sub_idx']}\\n\")\n # myfile.write(f\"{list_srt[-1]['first_time']} --> {list_srt[-1]['last_time']}\\n\")\n # myfile.write(f\"{list_srt[-1]['description']}\\n\")\n # myfile.write('\\n')\n # myfile.close()\n\n with open(filesub, \"a\", encoding=\"utf-8\") as myfile_vi:\n if not disable_time:\n myfile_vi.write(f\"{list_srt[-1]['sub_idx']}\\n\")\n myfile_vi.write(f\"{list_srt[-1]['first_time']} --> {list_srt[-1]['last_time']}\\n\")\n myfile_vi.write(f\"{list_srt[-1]['translate']}\\n\")\n myfile_vi.write('\\n')\n myfile_vi.close()\n\n print(f\"{list_srt[-1]['sub_idx']}\\n\")\n print(f\"{list_srt[-1]['first_time']} --> {list_srt[-1]['last_time']}\\n\")\n print(f\"{list_srt[-1]['description']}\\n\")\n print(f\"{list_srt[-1]['translate']}\\n\")\n print(f\"Similarity{ratio}\\n\")\n print('\\n')\n\n sub_idx += 1\n prev_time = current_time\n\n if description == \"\":\n prev_time = current_time\n\n old_des = description\n current_time += time_per_frame * div_frame\n\n i += 1\n\n cap.release()\n return output","def get_movie(self, identifier: int) -> Movie:\n result = list(filter(lambda x: x.identifier == identifier, self.items))\n if result:\n return result[0]\n\n return None","def find_match(second_file, title):\r\n # Initialize variables/ open files\r\n seq2 = \"\"\r\n header2 = \"\"\r\n match_fh = open(second_file, \"r\")\r\n # parse through lines of file\r\n for lines in match_fh:\r\n # If > found assume its header\r\n if lines[0] == \">\":\r\n # header2 = lines\r\n # If a header has been found, pull strain name, orgainism and subtype for new header\r\n if len(header2) > 0:\r\n matches2 = re.findall(\"(Strain Name:[AB]\\/[\\/A-Za-z 0-9()\\\\-_'.]+)\", header2)\r\n subtype_match2 = re.findall(\"(Subtype:[A-Za-z0-9]+)\", header2)\r\n organ2 = re.findall(\"(Organism:[\\/A-Za-z 0-9()\\\\-_'.]+)\", header2)\r\n header2 = \">\" + organ2[0] + \"|\" + matches2[0] + \"|\" + subtype_match2[0]\r\n # if new header equals input header then return it and the sequence\r\n if header2 == title:\r\n match_fh.close()\r\n print(\"match\")\r\n return header2, seq2\r\n # Reset the header and seq\r\n header2 = lines\r\n seq2 = \"\"\r\n\r\n else:\r\n # if it is part of the sequence\r\n seq2 = seq2 + lines\r\n\r\n # to return the last entry in the file, since loop won't be able to return it\r\n matches2 = re.findall(\"(Strain Name:[AB]\\/[\\/A-Za-z 0-9()\\\\-_'.]+)\", header2)\r\n subtype_match2 = re.findall(\"(Subtype:[A-Za-z0-9]+)\", header2)\r\n organ2 = re.findall(\"(Organism:[\\/A-Za-z 0-9()\\\\-_'.]+)\", header2)\r\n header2 = \">\" + organ2[0] + \"|\" + matches2[0] + \"|\" + subtype_match2[0]\r\n match_fh.close()\r\n return header2, seq2","def fetch_trailer(self, movie_id):\n movie = tmdbsimple.Movies(movie_id)\n request = movie.videos()\n trailer = movie.results[0]['key']\n\n return trailer","def get_recommendations(df,song_title, similarity_score, num_recommends = 5):\r\n indices = pd.Series(df.index, index = df['track_name']).drop_duplicates()\r\n idx = indices[song_title]\r\n sim_scores = list(enumerate(similarity_score[idx]))\r\n sim_scores = sorted(sim_scores, key = lambda x: x[1],reverse = True)\r\n top_scores = sim_scores[1:num_recommends+1]\r\n song_indices = [i[0] for i in top_scores]\r\n return df[\"track_name\"].iloc[song_indices]","def tmdb_info(title):\n result = False\n search_result = tmdb.Movies(title, limit=True)\n for movie in search_result.iter_results():\n result = movie\n break\n return result","def parse_infotable_movie(soup, pageurl):\n\t# find the infobox (right of screen)\n\tinfo_table = soup.findAll('table', {'class': 'infobox vevent'})\n\t# if info_table doesn't exist, cannot find year and gross\n\tif len(info_table) == 0:\n\t\treturn None, None\n\tgross = None\n\tyear = None\n\t# search each row of the info_table\n\tfor row in info_table[0].findAll('tr'):\n\t\theader = row.find('th')\n\t\t# check for header for year row\n\t\tif header != None and header.find('div') != None and header.find('div').get_text() == 'Release date':\n\t\t\tdate = row.find('td')\n\t\t\tif date.find('div') != None and date.find('div').find('ul') != None:\n\t\t\t\tdate = date.find('div').find('ul').find('li').find('span')\n\t\t\t# clean the date and extract year before returning\n\t\t\tyear = parse_year_movie(date.get_text(), pageurl)\n\t\t# check for header for gross row\n\t\tif header != None and header.get_text() == 'Box office':\n\t\t\tgross = row.find('td').get_text()\n\t\t\tif gross == None:\n\t\t\t\treturn None\n\t\t\t# clean the gross number to return as int\n\t\t\tgross = parse_gross_movie(gross, pageurl)\n\treturn year, gross","def find_top_and_topic(self, index, trs):\n\n top_result = \"kein_TOP\" \n topic_result = \"kein_TOPIC\" \n\n while index > 0:\n tree = html.fromstring(trs[index].get())\n top = tree.xpath('//tr/td[contains(@class, \"smc_tophn\")]/text()') \n topic = tree.xpath('//tr/td/a[contains(@class, \"smc_doc smc_field_voname smc_datatype_vo\")]/text()') \n\n if top != [] and top_result == \"kein_TOP\":\n top_result = top[0]\n if topic != [] and topic_result == \"kein_TOPIC\":\n topic_result = topic[0]\n\n index -= 1\n\n return top_result, topic_result","def get_best_speaker(self):\n max_val = -33.0\n try:\n self.value = max(self.speakers.values())\n except ValueError:\n self.value = -100\n _speaker = 'unknown'\n distance = self.get_distance()\n \n if len(self.speakers.values()) >1:\n mean_distance = self.get_m_distance()\n else:\n mean_distance = .5\n \n thres = 0\n \n if distance > -1:\n thres = max_val - distance\n else: thres = max_val\n \n if self.value >= thres and mean_distance > .49:\n for spk in self.speakers:\n if self.speakers[spk] == self.value:\n _speaker = spk\n break\n \n if distance > -1 and distance < .07:\n _speaker = 'unknown'\n \n return _speaker","def get_title_by_id_from_table(table, id):\n\n for line in sales_data:\n if line[ID] == id:\n return line[TITLE]\n return None","def get_oscars_best_picture_list():\n list_file = 'oscar_best_picture_list.txt'\n f = open(list_file, 'r')\n film_list = []\n\n for line in f:\n words = line.split('-')\n film = {\n 'year': words[0][:-1],\n 'name': words[1][2:-2]\n }\n film_list.append(film)\n f.close()\n # Reverse as we want newest first not last\n film_list.reverse()\n return film_list","def search_for_title(session, search_term):\n try:\n s_result = session.search_movie(search_term)\n shows = {}\n\n # made the keys of the namedtuple a digit for ease of selecting the correct one later\n for count, result in enumerate(s_result):\n show_id = count\n movie_id = result.movieID\n title = result['long imdb canonical title']\n url = f'http://www.imdb.com/title/tt{movie_id}/parentalguide'\n shows[count] = Show(show_id, movie_id, title, url)\n return shows\n except imdb._exceptions.IMDbDataAccessError:\n display_error()","def ratings_best(Y, titles):\n ratings_lists = data_proc.ratings_for_movies(Y)\n\n # Possible rating values\n rating_values = list(range(1, 6))\n\n # avg_ratings[i] = average rating of movie i\n # avg_ratings = [float(sum(ratings_list)) / len(ratings_list)\n # for ratings_list in ratings_lists]\n # Disfavor highly rated movies with few ratings:\n # http://stats.stackexchange.com/a/6361\n avg_ratings = [float(sum(ratings_list) + sum(rating_values))\n / (len(ratings_list) + len(rating_values))\n for ratings_list in ratings_lists]\n best_ids = data_proc.top_indices(avg_ratings, 10)\n best_titles = [titles[id] for id in best_ids]\n\n # ratings_table[i][j] is the number of rating_values[j] ratings for\n # movie with id i\n ratings_table = \\\n [[sum([rating_list[1] == id and rating_list[2] == rating_val\n for rating_list in Y])\n for rating_val in rating_values]\n for id in best_ids]\n\n sns.heatmap(ratings_table,\n annot=True, fmt='d', # Annotate data values\n yticklabels=best_titles, xticklabels=rating_values)\n plt.yticks(rotation=0) # Rotate yticks horizontally\n plt.xlabel('Rating')\n plt.title('Ratings of highest rated movies')\n plt.tight_layout() # Make room for long ytick labels\n plt.show()","def find_table(self):\n tables = self.document.tables\n header = []\n for table in tables:\n for row in table.rows:\n header[:] = []\n for cell in row.cells:\n for para in cell.paragraphs:\n header.append(para.text.strip(' '))\n # new versions of final CAPA's keep project information in a table\n if 'Project Information' in header:\n self.read_new_format(table)\n # check if elements in findings is also in header\n cond = len(header) == 5 and header[4] == 'Rating'\n if cond or [x for x in self.findings for y in header if x in y] == self.findings:\n self.table = table\n return","def closest_match(episodeplot, seriesname):\n LOG.debug(\"Calling closest_match() with the following arguments:\")\n LOG.debug(\"episodeplot= %s\"%episodeplot)\n LOG.debug(\"seriesname= %s\"%seriesname)\n #Doc2Vec.most_similar(positive=[], negative=[], topn=1, restrict_vocab=None)\n #If topn is False, most_similar returns the vector of similarity scores.\n\n return bestmatch, quality","def select_best_match(\n self, normalized_texts: List[str], transcript: str, verbose: bool = False, remove_punct: bool = False\n ):\n normalized_texts = calculate_cer(normalized_texts, transcript, remove_punct)\n normalized_texts = sorted(normalized_texts, key=lambda x: x[1])\n normalized_text, cer = normalized_texts[0]\n\n if verbose:\n print('-' * 30)\n for option in normalized_texts:\n print(option)\n print('-' * 30)\n return normalized_text, cer","def print_movie_table(self):\n self = self\n headers = [\"Votes\", \"Rank\", \"Year\", \"Title\"]\n self.handler.header(headers)\n\n for movie in self.movie_list:\n self.handler.row([str(movie.get_votes()), str(movie.get_rank()),\n str(movie.get_year()), str(movie.get_title())])\n\n self.handler.footer()","def get_summary(filename=video_file, subtitles=srt_filename, duration = 300):\n regions = find_summary_regions(subtitles, duration, \"english\")\n summary = create_summary(filename, regions)\n base, ext = os.path.splitext(filename)\n output = \"{0}_summary.mp4\".format(base)\n summary.to_videofile(\n output,\n codec=\"libx264\",\n temp_audiofile=\"temp.m4a\", remove_temp=True, audio_codec=\"aac\")\n return True","def find_tables_by_title(table_list, title_pattern):\n\n rtitle = re.compile(title_pattern)\n rtable_list = []\n for table in table_list:\n if rtitle.match(table.title()):\n rtable_list.append(table)\n return rtable_list","def find_best_match_jobs(self,candidate_matrix):\n\n \"\"\"\n Example format for input:\n candidate_matrix =\n {\n 0: {\"This is a skill description\": 10, \"This is another skill description\": 7},\n 1: {\"This is a knowledge description\" : 8, \"This is another knowledge description\": 6}\n }\n \"\"\"\n\n\n\n\n\n\n # Get a list of all job codes to begin importing details for\n cursor = self.conn.execute(\"SELECT job_code FROM job\")\n\n # Get python list of all job codes\n job_codes = cursor.fetchall()\n\n\n job_score = {}\n\n for job_code in job_codes:\n job_code = job_code[0]\n job_importance_matrix = self.generate_job_importance_matrix(job_code)\n\n\n job_score[job_code] = self.calculate_job_score(candidate_matrix, job_importance_matrix)\n\n\n # Sort by job scores!\n sorted_jobs = sorted(job_score.iteritems(), key=operator.itemgetter(1))\n\n # Get in descending order\n sorted_jobs.reverse()\n\n # Return the jobs with the top 5 job scores for the candidate\n return sorted_jobs[:5]","def get_all_movies(self):\n cinemaworld_movies, filmworld_movies = self.get_movies()\n\n if cinemaworld_movies is not None:\n self.get_title_map(cinemaworld_movies, \"cinemaworld\")\n if filmworld_movies is not None:\n self.get_title_map(filmworld_movies, \"filmworld\")\n\n return self.title_map","def full_text_search_title(self, term: str):\n if not self.client:\n self.connect()\n query = templates.full_text_search_title(term)\n return self.client.moviebuff.engtitles.aggregate(query)","def calculate_needed_subtitle_height(annotation, seen_annotations, video_clip):\n width = video_clip.w\n text = annotation[\"text\"].encode('utf-8')\n if len(text) > width / 40:\n text, lines_inserted = newlinify_string(text, int(width / 40))\n add_to_subtitle_offset(annotation, seen_annotations, lines_inserted - 1)\n\n return text","def get_top_movies(genre: Genre) -> List[Movie]:\n\n html = download_top_movies(genre)\n soup = parse_top_movies(html)\n return [extract_movie(result) for result in soup]","def get_matching_names(understat_names, fpl_names): \n understat_names, fpl_names = understat_names['player_name'].unique(), fpl_names['player_name'].unique()\n seq = difflib.SequenceMatcher()\n understat_similar = []\n fpl_similar = []\n ratio = []\n for i in range(len(understat_names)):\n for j in range(len(fpl_names)):\n seq.set_seqs(understat_names[i].lower(), fpl_names[j].lower())\n ratio_similar = seq.ratio()\n understat_similar.append(understat_names[i])\n fpl_similar.append(fpl_names[j])\n ratio.append(ratio_similar)\n similarity_matched_df = pd.DataFrame({'understat':understat_similar, 'fpl':fpl_similar, 'similarity': ratio}).copy()\n similarity_matched_df_final = similarity_matched_df.loc[similarity_matched_df.groupby('understat')['similarity'].idxmax()].copy()\n # print(similarity_matched_df_final.sort_values('similarity',ascending=False).to_latex())\n return similarity_matched_df_final","def most_stable():\n \n \n \n \n return Z","def get_subtitleinfo(fileFullName):\n sys.stdout.write(\"Requesting subtitle info...\\n\")\n\n #接口获取字幕信息\n response = requests.post(\n \"https://www.shooter.cn/api/subapi.php\",\n verify=False,\n params= {\n 'filehash': ComputeFileHash(fileFullName),\n 'pathinfo': os.path.realpath(fileFullName),\n 'format': 'json',\n 'lang': \"Chn\",\n },\n )\n #未找到字幕处理\n if response.text == u'\\xff':\n sys.stderr.write(\"Subtitle not found.\\n\")\n sys.exit(1)\n return response","def second_lowest():\n copy = movies.copy()\n name = copy.sort_values(['Total Gross']).reset_index(drop = True)['#1 Movie'].loc[1]\n return ('second_lowest', name)","def get_title_by_id_from_table(table, id):\n\n # your code","def get_table_by_text(text: str) -> Dict[str, str]:\n for morse_table in MORSE_TABLES:\n letter_to_check = _get_first_letter_in_text(text)\n if letter_to_check.upper() in morse_table.keys():\n return morse_table\n if letter_to_check in morse_table.values():\n return MORSE_EN_CODE_DICT\n raise LanguageDoseNotSupported","def transcribe_table_data(text_table, match_time=-1):\n\n\tprocessed_data = []\n\n\tfor text in text_table:\n\t\tif len(text) == 0:\n\t\t\tcontinue\n\t\thash_id = md5(text.encode('utf-8')).hexdigest()\n\t\tteam_1, score, team_2, tournament, matchtype = text.split('\\n')\n\t\tteam_1_score, team_2_score = score.split(' - ')\n\t\tmatch_summary = (hash_id, team_1, team_2, int(team_1_score), int(team_2_score), tournament, matchtype, match_time)\n\t\tprocessed_data.append(match_summary)\n\n\treturn processed_data","def compute_sentences_ranking(video_captions):\n sentences_global_ranking = []\n\n if config.experiment == 'experiment1':\n bfs = True\n embeddings = []\n labels = []\n for sentence in video_captions.sentences:\n sentence_embedding = sentence.get_sentence_embedding(bfs)\n if len(sentence_embedding) > 0: # there are sentences without senses (i.e. 'its a t') --> no embedding!\n embeddings.append(sentence_embedding)\n labels.append(sentence.sentence)\n\n embeddings_mean = np.mean(embeddings, axis=0)\n distances = [scipy.spatial.distance.cosine(embedding, embeddings_mean) for embedding in embeddings]\n for i, distance in enumerate(distances):\n sentences_global_ranking.append((video_captions.sentences[i].sentence, distance))\n\n elif config.experiment == 'experiment5':\n chencherry = SmoothingFunction()\n for i, sentence1 in enumerate(video_captions.sentences):\n scores = [bleu_score.sentence_bleu([sentence2.sentence.split(' ')], sentence1.sentence.split(' '), smoothing_function=chencherry.method4) for j, sentence2 in enumerate(video_captions.sentences)] # if i != j] # if we add 1 to all, result shouldn't change\n score = sum(scores) / len(scores)\n sentences_global_ranking.append((sentence1.sentence, score))\n\n else:\n result = np.zeros([20, 20])\n for i, sentence1 in enumerate(video_captions.sentences):\n for j, sentence2 in enumerate(video_captions.sentences):\n similarities = []\n for token1_id in sentence1.tokens_id_list:\n\n # find most similar token to sentence1.token1 in sentence2.tokens\n most_similar_token_in_sentence = (None, float('-inf'))\n for token2_id in sentence2.tokens_id_list:\n if (token1_id, token2_id) in config.tokens_set.tokens_similarities_closest:\n similarity = config.tokens_set.tokens_similarities_closest[(token1_id, token2_id)]\n if similarity > most_similar_token_in_sentence[1]:\n most_similar_token_in_sentence = (token2_id, similarity)\n\n # store token similarity (depending on the experiments we check if it is over threshold)\n if most_similar_token_in_sentence[0] is not None:\n if config.experiment in ['experiment4', 'experiment4symmetrical']:\n if most_similar_token_in_sentence[1] > config.th1:\n similarities.append((most_similar_token_in_sentence[0], 1.0)) # for each token we add 1 instead of similarity\n else:\n similarities.append((None, 0))\n elif config.experiment == 'experiment3':\n if most_similar_token_in_sentence[1] > config.th1:\n similarities.append(most_similar_token_in_sentence)\n else:\n similarities.append((None, 0))\n elif config.experiment == 'experiment2':\n similarities.append(most_similar_token_in_sentence)\n\n # compute and store similarity between sentence1 and sentence2\n if len(similarities) > 0:\n sentences_similarity = float(sum([a[1] for a in similarities])) / len(similarities)\n else:\n sentences_similarity = 0\n\n result[i, j] = sentences_similarity\n\n # we make the similarities symmetrical\n if config.experiment == 'experiment4symmetrical':\n for i in range(0, len(result)):\n for j in range(0, len(result)):\n symmetric_similarity = 0\n if result[i, j] + result[j, i] != 0:\n symmetric_similarity = (result[i, j] + result[j, i]) / 2\n result[i, j] = symmetric_similarity\n result[j, i] = symmetric_similarity\n\n # compute sentences similarity to all others (array of size 20)\n sentences_similarities = (np.sum(result, axis=1)) / result.shape[1] # sentences similarities normalized between 0 and 1\n for i, similarity in enumerate(sentences_similarities):\n sentences_global_ranking.append((video_captions.sentences[i].sentence, similarity))\n\n return sentences_global_ranking","def select_best_th(metrics_dict: Dict, metric: str):\n max_metric_ix = np.argmax(metrics_dict[metric])\n return metrics_dict['metrics_ths'][max_metric_ix]","def topseq(filename):\n\n\tdic = {0:\"A\",1:\"C\",2:\"G\",3:\"T\"} # dictionary of indexes of each nucleotide for matrices\n\ttf1 = np.loadtxt(filename, skiprows=1)\n\ttf2 = tf1[:,1:].transpose()\n\tindexes = np.argmax(tf2,axis=0).tolist() #generates a list of indexes of the highest probability base per position. \n\tseqstring = \"\"\n\tfor i in indexes: #generates a string nucleotide sequence corresponding top nucleotide for each position\n\t\tseqstring += dic[i]\n\treturn seqstring # returns the top motif","def get_table(image):\n bounds = {}\n for pocket in ['tl', 'tr', 'bl', 'br']:\n\n matchmap = matchTemplate(image, pocket_templates[pocket])\n minval, maxval, minloc, maxloc = cvMinMaxLoc(matchmap)\n\n #print(\"Pocket %s value = %d\" % (pocket, minval))\n\n if minval < POCKET_TRESHOLD:\n # Found a possible match\n bounds[pocket] = cvPoint(minloc.x + pocket_markers[pocket].x, minloc.y + pocket_markers[pocket].y)\n else:\n # If the best match for a pocket is above the treshold, then we can discard\n # the whole thing\n return None\n\n if DEBUG: print(\"Possible table bounds %s\" % bounds)\n\n # Sanity check\n\n if bounds['tl'].x >= bounds['tr'].x or bounds['bl'].x >= bounds['br'].x:\n return None\n if bounds['tl'].x <= bounds['bl'].x or bounds['tr'].x >= bounds['br'].x:\n return None\n if bounds['bl'].y <= bounds['tl'].y:\n return None\n\n # Make sure top and bottom edges are straight\n if abs( bounds['tl'].y - bounds['tr'].y ) > image.height / 80:\n return None\n if abs( bounds['bl'].y - bounds['br'].y ) > image.height / 80:\n return None\n\n # Make sure table is more or less symmetrical\n if math.fabs((bounds['tl'].x-bounds['bl'].x)-(bounds['br'].x-bounds['tr'].x)) > image.width / 100:\n return None\n\n return bounds","def textrank(self, sentences, n_top=2, stopwords=None):\n S = self.build_similarity_matrix(sentences, stopwords) \n sentence_ranks = self.pagerank(S)\n \n # Sort the sentence ranks\n ranked_sentence_indexes = [item[0] for item in sorted(enumerate(sentence_ranks), key=lambda item: -item[1])]\n #print(ranked_sentence_indexes)\n selected_sentences = sorted(ranked_sentence_indexes[:n_top])\n summary = itemgetter(*selected_sentences)(sentences)\n return summary","def search_videos(self, search_term):\n recommendations = []\n for video in self.videos_dict:\n if not video.flagged and search_term in self.videos_dict[video]:\n recommendations.append(self.videos_dict[video])\n \n recommendations.sort()\n n = len(recommendations)\n\n\n if n == 0:\n print(f\"No search results for {search_term}\")\n else:\n print(f\"Here are the results for {search_term}:\")\n for i in range(n):\n print(f\"{i+1}) {recommendations[i]}\")\n print(\"Would you like to play any of the above? If yes, specify the number of the video.\")\n print(\"If your answer is not a valid number, we will assume it's a no.\")\n\n try:\n response = int(input())\n if response in range(1,n+1):\n wanted_video_info = recommendations[response-1]\n #print(wanted_video_info)\n s = wanted_video_info\n result = re.search(r\"\\(([A-Za-z0-9_]+)\\)\", s)\n #print(result.group(1))\n self.play_video(result.group(1))\n except ValueError:\n pass","def get_tfidf(self, movie):\n return self.tf[movie] * self.idf","def table_dictionary_time(max_time):\n\n b = [1, 27183, 250726]\n tablesize = [250727, 402221, 1000081]\n dic = [\"english_small.txt\",\"english_large.txt\",\"french.txt\"]\n\n with open('output_task2.csv', 'w') as openFile: # create csv file\n\n writer = csv.writer(openFile)\n writer.writerow(['Dic','Tablesize', 'b', 'No. of words', 'time taken'])\n\n for i in range((len(dic))):\n counter = 0\n counter2 = 0\n for k in range(len(b)*len(tablesize)):\n base = b[counter2]\n table_Size = tablesize[counter]\n print(base, table_Size)\n word_n_time = load_dictionary_time(base, table_Size, dic[i], max_time)\n counter += 1\n\n if counter == 3:\n counter = 0\n print(word_n_time)\n\n if word_n_time[1] is None:\n writer.writerow([dic[i], table_Size, base, word_n_time[0],(max_time+10)])\n else:\n writer.writerow([dic[i], table_Size, base, word_n_time[0], word_n_time[1]])\n\n if counter == 0:\n counter2 += 1"],"string":"[\n \"def _best_matching_movie(movie):\\n return (Levenshtein.distance(movie_name, movie.get('title').lower()),\\n (0 - movie.get('votes', 0)),\\n )\",\n \"def download_subtitle(search, results, filename, min_match=0,\\n force=0, debug=0):\\n s = Subseek()\\n subtitleurl = False\\n for result in s.order_match(search, results):\\n match_text = s.clean_text(s.clean_html(result['text']),False,\\n s.detect_encoding(s.clean_html(result['text']))\\n ) + \\\" \\\" + s.clean_text(s.clean_html(result['description']),False,\\n s.detect_encoding(s.clean_html(result['description'])))\\n subtitleurl = result['link']\\n rating_weight = s.text_weight(search, match_text)\\n max_weight = s.text_weight(search)\\n rating_match = rating_weight/max_weight*100\\n if debug == 1:\\n print \\\"Subtitle File URL: \\\" + subtitleurl\\n print \\\" Text To Search: \\\" + search\\n print \\\" Text To Match: \\\" + match_text\\n print \\\" Text Match (%): \\\" + str(round(rating_match,2)) + \\\"%\\\"\\n # check minimal match to use\\n if rating_match >= min_match:\\n downloaded = s.download(subtitleurl, filename + '.tmp')\\n if downloaded == False:\\n if debug == 1:\\n print \\\"Error: connection or file creation failed\\\"\\n subtitleurl = False\\n else:\\n if debug == 1:\\n print \\\"File downloaded\\\"\\n # unrar, unzip or get srt file\\n typefile = s.get_sub_file_from_file(filename + '.tmp',\\n search, force)\\n if typefile == False:\\n if debug == 1:\\n print \\\"Subtitle file not found\\\"\\n subtitleurl = False\\n else:\\n if debug == 1:\\n print \\\"Subtitle file found in \\\" + typefile\\n subtitleurl = True\\n break\\n else:\\n if debug == 1:\\n print \\\"Error: match less than \\\" + str(round(min_match,2))+ \\\"%\\\"\\n subtitleurl = False\\n break\\n\\n return subtitleurl\",\n \"def best_subtitle_url(search, full_search, path_file_name,\\n min_match=0, force=0, deep=0, debug=0):\\n # first search in subtitle search engines\\n links = subtitle_search_engines_links(search, deep, debug)\\n subtitle_url = download_best_subtitle(links,\\n full_search,\\n path_file_name,\\n min_match, force, debug)\\n # if not found use the external search engines\\n if not subtitle_url:\\n links = external_search_engines_links(search, deep, debug)\\n subtitle_url = download_best_subtitle(links,\\n full_search,\\n path_file_name,\\n min_match, force, debug)\\n\\n return subtitle_url\",\n \"def get_title_similarity(self):\\n title_words = []\\n ignore_words = ['the', 'and', 'or', 'to', 'at', 'on', 'of']\\n for w in self.target_movie.title.split(' '):\\n w = w.strip('- ,:(){}[]')\\n if w.lower() not in ignore_words:\\n title_words.append(w)\\n\\n # if last word is a number then it's an year and should be ignored.\\n if len(title_words) > 1 and title_words[-1].isdigit():\\n title_words = title_words[:-1]\\n\\n print(title_words)\\n res = self.db.query(Movie).filter(\\n Movie.movie_id != self.target_movie.movie_id).filter(or_(\\n Movie.title.ilike(r'%' + tw + r'%') for tw in title_words\\n )).all()\\n\\n target_clean_title = string_cleanup(self.target_movie.title)\\n\\n print(\\\"%i records from partial title match\\\" % len(res))\\n TSW = self.TITLE_SIMILARITY_WEIGHT\\n for rec in res:\\n mc_title = string_cleanup(rec.title)\\n smid = rec.movie_id\\n if smid not in self.recommendation_pool:\\n self.recommendation_pool[smid] = {\\n 'movie_obj': rec,\\n 'title_similarity': jaccard_index(\\n target_clean_title, mc_title, ' ') * TSW\\n }\\n\\n else:\\n self.recommendation_pool[smid]['title_similarity'] = \\\\\\n jaccard_index(\\n target_clean_title, mc_title, ' ') * TSW\",\n \"def download_best_subtitle(links, full_search, path_file_name,\\n min_match=0, force=0, debug=0):\\n s = Subseek()\\n if not links or len(links) == 0:\\n return False\\n else:\\n results = []\\n for link in links:\\n if debug == 1:\\n print \\\"Searching in \\\" + link['link']\\n for provider in SUBTITLE_PROVIDERS:\\n results_aux = s.get_subtitles_links(link['link'],\\n provider)\\n if results_aux is False or len(results_aux) == 0:\\n if debug == 1:\\n print \\\"No subtitles with '%s'\\\" % provider['name']\\n else:\\n if debug == 1:\\n print \\\"%s subtitles with '%s'\\\" % (len(results_aux),\\n provider['name'])\\n results = results + results_aux\\n # download the best subtitle of the entire list\\n return download_subtitle(full_search,\\n results,\\n path_file_name,\\n min_match,\\n force,\\n debug)\",\n \"def content_model(movie_list,top_n):\\r\\n # Vectorise content for each movie in list_title\\r\\n input_matrix = vectoriser.transform(movies[movies['title'].isin(movie_list)].content)\\r\\n \\r\\n # Initiate list to store indeces of input movies\\r\\n m_idx = []\\r\\n \\r\\n for title in movie_list:\\r\\n for id in movies.movieId[movies['title']==title]:\\r\\n m_idx.append(indices[id])\\r\\n \\r\\n # Create list of similarities between each input movie and every other movie in the dataset \\r\\n sim = list(enumerate(cosine_similarity(content_matrix,\\r\\n input_matrix))) \\r\\n\\r\\n # Sort the list by the average similarity of the movies\\r\\n sim_scores = sorted(sim, key=lambda x: x[1].mean(), reverse=True)\\r\\n \\r\\n # Select the top-k values for recommendation\\r\\n sim_scores = sim_scores[0:20]\\r\\n\\r\\n # Select the indices of the top-k movies\\r\\n movie_indices = [i[0] for i in sim_scores if i[0] not in m_idx]\\r\\n \\r\\n # Return a list of the movie titles\\r\\n return movies.iloc[movie_indices].title[:top_n]\",\n \"def get_most_similar_title(self, id, id_list):\\n clf = self._get_model()\\n vocab = clf.wv.vocab\\n if id not in vocab:\\n return \\\"\\\"\\n id_list = [id for id in id_list if id in vocab] # ensure all in vocab\\n id_book = self.id_book\\n match = clf.wv.most_similar_to_given(id, id_list)\\n return id_book['primaryTitle'].loc[id_book['tconst'] == int(match)].values[0]\",\n \"def edx_get_subtitle(url, headers):\\n \\\"\\\"\\\" or None if no subtitles are available \\\"\\\"\\\"\\n try:\\n jsonString = get_page_contents(url, headers)\\n jsonObject = json.loads(jsonString)\\n return edx_json2srt(jsonObject)\\n except URLError as e:\\n print('[warning] edX subtitles (error:%s)' % e.reason)\\n return None\\n except ValueError as e:\\n print('[warning] edX subtitles (error:%s)' % e.message)\\n return None\",\n \"def getSubtitleURL(self):\\n\\n # If it is a movie, we use this methodology -\\n try:\\n IndexingParameters = [\\\"subtitleUrls\\\", 0, \\\"url\\\"]\\n TitleParamters = [\\n \\\"catalogMetadata\\\", \\\"catalog\\\", \\\"title\\\", \\\"episodeNumber\\\"]\\n subRequestObject = requests.get(self.subtitleURLContainer)\\n\\n parsedJsonObject = json.loads(str(subRequestObject.text))\\n SubsURL = parsedJsonObject[IndexingParameters[0]][\\n IndexingParameters[1]][IndexingParameters[2]]\\n if self.title == \\\"Amazonsubtitles\\\":\\n try:\\n self.title = parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[2]] + \\\"_\\\" + str(\\n parsedJsonObject[TitleParamters[0]][TitleParamters[1]][TitleParamters[3]])\\n except:\\n pass\\n\\n return SubsURL\\n\\n except:\\n pass\\n pass\",\n \"def stat_subtitle(self, release_name, movie_dir):\\n ret = {}\\n for root_dir, child_folders, file_names in os.walk(movie_dir):\\n for file_name in file_names:\\n if not file_name.startswith(release_name):\\n continue\\n\\n subtitle_info = get_subtitle_info(file_name)\\n if not subtitle_info:\\n continue\\n\\n if 'lang' not in subtitle_info:\\n continue\\n\\n lang = subtitle_info['lang']\\n if lang not in ret:\\n ret[lang] = []\\n\\n ret[lang].append(file_name)\\n\\n # Sort result\\n for lang in ret:\\n ret[lang] = sorted(ret[lang])\\n\\n return ret\",\n \"def tabler(subcorpus_names, list_of_dicts, num_rows):\\n import pandas as pd\\n cols = []\\n for subcorp, data in zip(subcorpus_names, list_of_dicts):\\n col = pd.Series([w for w, v in data.most_common(num_rows)], name = subcorp)\\n cols.append(col)\\n word_table = pd.concat(cols, axis = 1)\\n return word_table\",\n \"def content_model(movie_list,top_n=10):\\n # Initializing the empty list of recommended movies\\n recommended_movies = []\\n data = data_preprocessing(27000)\\n # Instantiating and generating the count matrix\\n count_vec = CountVectorizer()\\n count_matrix = count_vec.fit_transform(data['keyWords'])\\n indices = pd.Series(data['title'])\\n cosine_sim = cosine_similarity(count_matrix, count_matrix)\\n # Getting the index of the movie that matches the title\\n idx_1 = indices[indices == movie_list[0]].index[0]\\n idx_2 = indices[indices == movie_list[1]].index[0]\\n idx_3 = indices[indices == movie_list[2]].index[0]\\n # Creating a Series with the similarity scores in descending order\\n rank_1 = cosine_sim[idx_1]\\n rank_2 = cosine_sim[idx_2]\\n rank_3 = cosine_sim[idx_3]\\n # Calculating the scores\\n score_series_1 = pd.Series(rank_1).sort_values(ascending = False)\\n score_series_2 = pd.Series(rank_2).sort_values(ascending = False)\\n score_series_3 = pd.Series(rank_3).sort_values(ascending = False)\\n # Getting the indexes of the 10 most similar movies\\n listings = score_series_1.append(score_series_1).append(score_series_3).sort_values(ascending = False)\\n\\n # Store movie names\\n recommended_movies = []\\n # Appending the names of movies\\n top_50_indexes = list(listings.iloc[1:50].index)\\n # Removing chosen movies\\n top_indexes = np.setdiff1d(top_50_indexes,[idx_1,idx_2,idx_3])\\n for i in top_indexes[:top_n]:\\n recommended_movies.append(list(movies['title'])[i])\\n return recommended_movies\",\n \"def find_table_by_title(table_list, title_pattern, index=0):\\n\\n rtable_list = find_tables_by_title(table_list, title_pattern)\\n try:\\n return rtable_list[index]\\n except Exception:\\n return None\",\n \"def get_subtitle(annotation, sub_duration, video_clip, seen_annotations):\\n if len(annotation[\\\"text\\\"]) == 0:\\n return None\\n\\n annotation_txt = calculate_needed_subtitle_height(annotation, seen_annotations, video_clip)\\n\\n txt_clip = TextClip(annotation_txt, color=\\\"white\\\", fontsize=70, font='Sans Serif')\\n txt_clip = txt_clip.set_position((\\\"center\\\", get_subtitle_offset(annotation, seen_annotations, video_clip)))\\n txt_clip = txt_clip.set_start(float(annotation[\\\"time\\\"]) / 1000.0)\\n txt_clip = txt_clip.set_duration(sub_duration)\\n\\n return txt_clip\",\n \"def get_top_games_from_title_for_movie(mov_tmt_path: str,\\n candidate_games: List[str],\\n threshold=0.5) -> List[Dict]:\\n if not mov_tmt_path or not candidate_games:\\n return []\\n ranking_info = get_matched_game_ranking_info_for_movie(\\n movie_id=mov_tmt_path)\\n res = []\\n for app_id, score in ranking_info.items():\\n if score >= threshold and app_id in candidate_games:\\n game_obj: Game = Game.query.filter_by(app_id=app_id).all()[0]\\n game_info = {\\n 'app_id': app_id,\\n 'name': game_obj.name,\\n 'developer': \\\", \\\".join(json.loads(game_obj.developer)),\\n 'publisher': \\\", \\\".join(json.loads(game_obj.publisher)),\\n 'tags': json.loads(game_obj.tags),\\n 'genre': json.loads(game_obj.genre),\\n 'single_player': game_obj.single_player,\\n 'multi_player': game_obj.multi_player,\\n 'rating': game_obj.rating,\\n 'mature_content': game_obj.mature_content,\\n 'title_match_score': score}\\n res.append(game_info)\\n return res\",\n \"def find_movie(imdb_file, title_regex):\\n\\n process = subprocess.run([\\n \\\"grep\\\",\\n \\\"-i\\\", # Case insensitive\\n f'movie\\\\t[^\\\\t]*{title_regex}', # Only match movies\\n imdb_file\\n ], stdout=subprocess.PIPE)\\n hits = [dict(zip(COLUMNS, hit.decode(\\\"utf-8\\\").split(\\\"\\\\t\\\")))\\n for hit in process.stdout.split(b\\\"\\\\n\\\")[:-1]]\\n # Try to filter out irrelevant hits, e.g. that don't yet exist or are porn\\n legitimate_hits = [hit for hit in hits\\n if hit[\\\"startYear\\\"] != \\\"\\\\\\\\N\\\" and\\n hit[\\\"isAdult\\\"] == \\\"0\\\"]\\n return legitimate_hits\",\n \"def edx_get_subtitle(url, headers):\\n try:\\n json_object = get_page_contents_as_json(url, headers)\\n return edx_json2srt(json_object)\\n except URLError as e:\\n _print('[warning] edX subtitles (error:%s)' % e.reason)\\n return None\\n except ValueError as e:\\n _print('[warning] edX subtitles (error:%s)' % e.message)\\n return None\",\n \"def play_movie_with_subs(self, filmid):\\n self.logger.debug('play_movie_with_subs')\\n start = time.time()\\n #\\n film = self.database.retrieve_film_info(filmid)\\n if film is None:\\n self.logger.error(\\\"no film for download \\\" + self.plugin.language(30991))\\n self.notifier.show_error(30990, self.plugin.language(30991))\\n return\\n ttmname = os.path.join(self.settings.getDatapath(), 'subtitle.ttml')\\n srtname = os.path.join(self.settings.getDatapath(), 'subtitle.srt')\\n subs = []\\n if self.download_subtitle(film, ttmname, srtname, 'subtitle'):\\n subs.append(srtname)\\n # (_, listitem) = FilmUI(self.plugin).get_list_item(None, film)\\n (_, listitem) = FilmlistUi(self.plugin)._generateListItem(film)\\n self.logger.debug('SUBTITLE FOUND {} from url {}' , subs, film.url_sub)\\n if listitem:\\n if subs:\\n listitem.setSubtitles(subs)\\n self.plugin.set_resolved_url(True, listitem)\\n self.logger.debug('play_movie_with_subs processed: {} sec', time.time() - start)\",\n \"def load_top_video(self):\\n\\n if self.general_parser is None or \\\\\\n self.specific_parser is None or \\\\\\n ((self.video_parser is None) and (self.video_data_parser is None)):\\n self.missing_files_label.grid(row=13, column=5)\\n raise Exception(\\\"you need to load the general, month-specific, and video words first\\\")\\n else:\\n self.missing_files_label.grid_remove()\\n\\n if self.month_selected is None:\\n self.no_month_selected_label.grid(row=14, column=5, columnspan=1)\\n else:\\n self.no_month_selected_label.grid_remove()\\n\\n self.top_unique_video = self.find_top_unique(self.video_entries,\\n int(self.top_unique_video_entry.get()))\\n\\n self.top_unique_video_box.delete(0, END)\\n\\n box_count = 0\\n for rank, words in enumerate(self.top_unique_video):\\n for index, word in enumerate(words):\\n self.top_unique_video_box.insert(box_count,\\n str(word.rank)+ \\\". \\\" +\\n word.word +\\n \\\" - \\\" + str(word.count))\\n box_count += 1\\n\\n self.unique_video_found = True\",\n \"def get_subtitles(self, index: int):\\n\\n match = self.re_subs[index - 1]\\n start = convert_subs_time(match[1])\\n end = convert_subs_time(match[2])\\n subtitles = match[3]\\n subtitles = clean_text(subtitles)\\n\\n return (subtitles, start, end)\",\n \"def top_controversial(self, n):\\n return top_movies\",\n \"def extract_movie_titles(dictionary):\\n results = dictionary['Similar']['Results']\\n lstmt = [d['Name'] for d in results]\\n return lstmt\",\n \"def get_movie_longest_runtime(movies: list) -> str:\\n pass\",\n \"def download_subtitle(self, film, ttmname, srtname, filename):\\n self.logger.debug('download_subtitle')\\n ret = False\\n if film.url_sub:\\n progress = KodiProgressDialog()\\n progress.create(30978, filename + u'.ttml')\\n # pylint: disable=broad-except\\n try:\\n progress.update(0)\\n mvutils.url_retrieve_vfs(\\n film.url_sub, ttmname, progress.url_retrieve_hook)\\n try:\\n ttml2srtConverter = ttml2srt()\\n ttml2srtConverter.do(xbmcvfs.File(ttmname, 'r'),\\n xbmcvfs.File(srtname, 'w'))\\n ret = True\\n except Exception as err:\\n self.logger.error('Failed to convert to srt: {}', err)\\n progress.close()\\n except Exception as err:\\n progress.close()\\n self.logger.error(\\n 'Failure downloading {}: {}', film.url_sub, err)\\n return ret\",\n \"def get_matched_game_ranking_info_for_movie(movie_id: str) -> Dict[str, int]:\\n query_res = Movie.query.filter_by(link_id=movie_id).all()\\n if query_res:\\n return eval(query_res[0].games_title_match)\\n return dict()\",\n \"def get_time_intervals(subtitle, regex=r\\\"\\\\S+\\\"):\\n # module webvtt only gets the line-captions, not individual words, so it's time for some regex!\\n # The time corresponding to a word is when that word *starts*\\n # words = (match.group(\\\"word\\\") for match in WORD_REGEX.finditer(subtitle))\\n time_words = [\\n (m.group(\\\"time1\\\") or m.group(\\\"time2\\\"), m.group(\\\"word1\\\") or m.group(\\\"word2\\\"))\\n for m in TIME_WORD_REGEX.finditer(subtitle)\\n ]\\n # Incorrect format, which would lead to trouble zipping\\n if len(time_words) == 0:\\n return []\\n times, words = zip(*time_words)\\n # Quickly search lines starting from the end\\n final_time = next(match.group(\\\"time\\\") for line in reversed(subtitle.split(\\\"\\\\n\\\")) for match in [re.search(FINAL_TIME_REGEX, line)] if match)\\n # timestamps[i] is the time the word starts at if i is the index of the start of a word\\n timestamps = {}\\n word_indices = {}\\n # Build search_str while computing time_stamps by adding one word and one space at a time\\n search_str = ''\\n words = list(words)\\n last_time = 0\\n for j, (word, time) in enumerate(zip(words, times)):\\n i = len(search_str)\\n time = parse_time(time)\\n timestamps[i] = time\\n if time - last_time > 10:\\n search_str += '[ … ] '\\n last_time = time\\n word_indices[i] = j\\n search_str += word + ' '\\n i = len(search_str)\\n timestamps[i] = final_time\\n word_indices[i] = len(words)\\n # Trim off the final space\\n # Inconsistent capitalization, so just lowercase\\n search_str = search_str[:-1].lower()\\n for match in re.finditer(regex, search_str):\\n start, end = match.span()\\n start_index = max(i for i in timestamps if i<=start)\\n end_index = min(i for i in timestamps if i>end)\\n yield Interval(\\n timestamps[start_index],\\n timestamps[end_index],\\n word_indices[start_index],\\n word_indices[end_index],\\n match.group(0)\\n )\",\n \"def _best_song_match(songs, title, duration):\\n # pylint: disable=R0914\\n seqmatch = difflib.SequenceMatcher\\n\\n def variance(a, b):\\n \\\"\\\"\\\" Return difference ratio. \\\"\\\"\\\"\\n return float(abs(a - b)) / max(a, b)\\n\\n candidates = []\\n\\n ignore = \\\"music video lyrics new lyrics video audio\\\".split()\\n extra = \\\"official original vevo\\\".split()\\n\\n for song in songs:\\n dur, tit = int(song.length), song.title\\n dbg(\\\"Title: %s, Duration: %s\\\", tit, dur)\\n\\n for word in extra:\\n if word in tit.lower() and word not in title.lower():\\n pattern = re.compile(word, re.I)\\n tit = pattern.sub(\\\"\\\", tit)\\n\\n for word in ignore:\\n if word in tit.lower() and word not in title.lower():\\n pattern = re.compile(word, re.I)\\n tit = pattern.sub(\\\"\\\", tit)\\n\\n replacechars = re.compile(r\\\"[\\\\]\\\\[\\\\)\\\\(\\\\-]\\\")\\n tit = replacechars.sub(\\\" \\\", tit)\\n multiple_spaces = re.compile(r\\\"(\\\\s)(\\\\s*)\\\")\\n tit = multiple_spaces.sub(r\\\"\\\\1\\\", tit)\\n\\n title_score = seqmatch(None, title.lower(), tit.lower()).ratio()\\n duration_score = 1 - variance(duration, dur)\\n dbg(\\\"Title score: %s, Duration score: %s\\\", title_score,\\n duration_score)\\n\\n # apply weightings\\n score = duration_score * .5 + title_score * .5\\n candidates.append((score, song))\\n\\n best_score, best_song = max(candidates, key=lambda x: x[0])\\n percent_score = int(100 * best_score)\\n return best_song, percent_score\",\n \"def get_subjects(cur, table):\\n cur.execute('SELECT subj FROM {}'.format(table))\\n d = cur.fetchall()\\n\\n subj = []\\n for sub in d:\\n subj.append(str(sub[0]))\\n subj.sort()\\n\\n return subj\",\n \"def extract_subtitle_track(path_to_mkv):\\n handler = SubtitleHandler()\\n with open(path_to_mkv, \\\"rb\\\") as fp:\\n mkvparse.mkvparse(fp, handler)\\n\\n return handler.subs\",\n \"def read_table(self):\\n\\n db = self.connection(database=\\\"imdb\\\")\\n\\n try:\\n cur = db.cursor()\\n sql = \\\"SELECT title FROM film;\\\"\\n cur.execute(sql)\\n return cur.fetchall()\\n except:\\n print(\\\"Cannot read from table!\\\")\\n\\n db.close()\",\n \"def make_movie(processed_files_directory='files/', WITH_SUBTITLES=False, WITH_AUDIO=False):\\r\\n # Declare the text for sub-titles\\r\\n\\r\\n if WITH_SUBTITLES: # if the user is willing to have subtitles in the movie\\r\\n with open(processed_files_directory+'subtitles.txt', 'r', encoding='utf8') as f:\\r\\n txt = f.read() # read the subtitles file\\r\\n # Split text to lines.\\r\\n subtitles = txt.split('\\\\n')\\r\\n # Declare VideoFileClip from the movie that I already have.\\r\\n clip = VideoFileClip(processed_files_directory + \\\"initial.avi\\\")\\r\\n # Declare duration of one sub-title as total duration of the video divided by number of lines.\\r\\n duration = clip.duration/len(subtitles)\\r\\n # Set start to zero.\\r\\n start=0\\r\\n # Set container for the clips.\\r\\n videos=[]\\r\\n # Loop all sub-titles\\r\\n for line in subtitles:\\r\\n # Make text clip from the reversed Hebrew text\\r\\n txt_clip = TextClip(line[::-1], fontsize=30, color='yellow', font='Calibri')\\r\\n # Set position to the bottom of screen.\\r\\n txt_clip = txt_clip.set_position('bottom').set_duration(duration)\\r\\n # Make sub clip of the movie with same duration as text clip.\\r\\n sub_clip = clip.subclip(start,start+duration)\\r\\n # Set CompositeVideoClip from the text clip and sub clip.\\r\\n video = CompositeVideoClip([sub_clip, txt_clip])\\r\\n # Insert the video to the clips container\\r\\n videos.append(video)\\r\\n # Set start time for next sub-title.\\r\\n start+=duration\\r\\n # Concatenate all clips of the container.\\r\\n res = concatenate_videoclips(videos)\\r\\n clip = res # now the clip is res\\r\\n else:\\r\\n clip = VideoFileClip(processed_files_directory+ \\\"initial.avi\\\") # the clip won't have subtitles\\r\\n\\r\\n\\r\\n # Set audio clip from mp3 file.\\r\\n if WITH_AUDIO: # if the user has chosen to include soundtrack in the movie\\r\\n f = 'audio.mp3' # change to mp3 soundtrack file of the movie\\r\\n # set the duration of the audioclip to max(duration of clip), even if the audioclip is longer\\r\\n audioclip = AudioFileClip(processed_files_directory+f)\\r\\n\\r\\n # check if the clip length is bigger than the\\r\\n if clip.duration > audioclip.duration:\\r\\n number_of_duplicated = int(np.ceil(clip.duration/audioclip.duration))\\r\\n # duplicate the audioclip in order to later fit the movie's duration\\r\\n audioclip = concatenate_audioclips([AudioFileClip(processed_files_directory+f) for i in range(number_of_duplicated)])\\r\\n\\r\\n # Now fit the audioclip duration to the movie's\\r\\n audioclip = audioclip.set_duration(clip.duration)\\r\\n\\r\\n # Set audio for the container.\\r\\n if not WITH_SUBTITLES: # if the user wanted to have audio included without subtitles\\r\\n videoclip = clip.set_audio(audioclip)\\r\\n else: # if the user wanted to have both audio and subtitles\\r\\n videoclip = res.set_audio(audioclip)\\r\\n else:\\r\\n videoclip = clip # if the user didn't want audio in the movie\\r\\n\\r\\n # Write the video file.\\r\\n f = 'final_movie.mp4' # change to the desired movie filename\\r\\n videoclip.write_videofile(processed_files_directory+f)\",\n \"def getSubtitleTable(date) -> str:\\n return \\\"\\\"\\\"| Start of the day | Weeks until NIMCET |\\n| ---------------- | -----------------: |\\n| {time} | {weeks} weeks |\\\"\\\"\\\".format(time=formattedTimeNow(), weeks=round((datetime(2021, 5, 21) - date).days/7, 1))\",\n \"def findtable(self, title_pattern, index=0):\\n return find_table_by_title(self.__tables, title_pattern, index)\",\n \"def findtable(self, title_pattern, index=0):\\n return find_table_by_title(self.__tables, title_pattern, index)\",\n \"def get_words_with_end_times(subtitle_file_path):\\n\\n with open(subtitle_file_path) as subtitle_file:\\n\\n # Remove first 4 lines (containing meta information)\\n for j in range(0, 4):\\n subtitle_file.readline()\\n\\n text = subtitle_file.read()\\n\\n # Check if the subtitle file supports individual word times\\n if text.find(\\\"<c>\\\") == -1:\\n print(\\\"Individual word times are not supported for file: \\\" + subtitle_file_path)\\n return None, None\\n\\n chunks = text.split(\\\" \\\\n\\\\n\\\") # split into chunks for easier data processing\\n\\n words = list()\\n word_end_times = list()\\n\\n for chunk in chunks:\\n chunk_lines = chunk.split(\\\"\\\\n\\\")\\n words_line = chunk_lines[2]\\n\\n words_in_chunk = []\\n word_end_times_in_chunk = []\\n\\n first_word_end_index = words_line.find(\\\"<\\\")\\n if first_word_end_index != -1:\\n first_word = words_line[\\n 0:first_word_end_index] # get the first word (can't be found using method below)\\n\\n words_in_chunk = re.findall(\\\"<c> [\\\\S]*</c>\\\", words_line) # get all words\\n words_in_chunk = [w[4:-4] for w in words_in_chunk] # strip <c> and <c/>\\n\\n word_end_times_in_chunk = re.findall(\\\"<\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d.\\\\d\\\\d\\\\d>\\\", words_line) # get all word end times\\n word_end_times_in_chunk = [t[1:-1] for t in word_end_times_in_chunk] # strip < and >\\n else:\\n # Only one word\\n first_word = words_line\\n\\n last_time = chunk_lines[4][17:29] # end time for the last word\\n\\n words_in_chunk.insert(0, first_word)\\n word_end_times_in_chunk.append(last_time)\\n\\n words.extend(words_in_chunk)\\n word_end_times.extend(word_end_times_in_chunk)\\n\\n # For the last chunk we have to get the word end time from somewhere else\\n first_line_in_last_chunk = chunks[-1].split(\\\"\\\\n\\\")[0]\\n last_time = first_line_in_last_chunk[17:29]\\n word_end_times.pop()\\n word_end_times.append(last_time)\\n\\n if len(words) != len(word_end_times):\\n print(\\\"Warning: word count does not match times count\\\")\\n\\n return words, word_end_times\",\n \"def mostlikelycodeword(self):\\n\\n # Add your code here\\n stoping_int = None # Replace\\n best, first_index, last_index = None, None, None # Replace all three with an integer\\n for i in range(stoping_int):\\n for j in range(None, stoping_int): # Replace None. \\n current = self.quality(None, None)\\n if None > None # Replace both Nones\\n best, first_index, last_index = current, i, j\\n return self.preamble[None:None]\",\n \"def get_movie_longest_runtime():\\n tree = get_tree()\\n movie_runtimes = [(movie.get(\\\"title\\\"), movie.get(\\\"runtime\\\")) for movie in tree.getroot().findall(\\\"movie\\\")]\\n\\n # one way\\n result = sorted(movie_runtimes, key=lambda movie_runtimes: movie_runtimes[1], reverse = True)[0][0]\\n return result\\n \\n # another way\\n # result = max(movie_runtimes, key=lambda movie_runtimes: movie_runtimes[1])[0]\\n # return result\",\n \"def get_frames_and_titles(video_label):\\n\\n frames = []\\n titles = []\\n cap = cv2.VideoCapture(video_label)\\n frameRate = cap.get(5) # frame rate\\n numero = 29\\n index = 0\\n while (cap.isOpened()):\\n frameId = cap.get(1) # current frame number\\n ret, frame = cap.read()\\n # Apply template Matching\\n if (ret != True):\\n break\\n if (frameId % math.floor(frameRate) == 0):\\n frames.append(frame)\\n index = index\\n titles.append(\\\"Frame {}\\\".format(int(index / 30)))\\n\\n if numero > 30:\\n break\\n index = index + 1\\n cap.release()\\n\\n return frames, titles\",\n \"def get_subtitles(self, title):\\n return library.subtitles.get_subtitle_url(title)\",\n \"def _get_info(self, id, score=None):\\n try:\\n info_query = f\\\"\\\"\\\"\\n SELECT m.primary_title, m.start_year, r.average_rating, r.num_votes\\n FROM movies m\\n JOIN ratings r ON m.movie_id = r.movie_id\\n WHERE m.movie_id = '{id}'\\\"\\\"\\\"\\n self.cursor_dog.execute(info_query)\\n except Exception as e:\\n return tuple([f\\\"Movie title unknown. ID:{id}\\\", None, None, None, None, None, None, id])\\n\\n t = self.cursor_dog.fetchone()\\n if t:\\n title = tuple([t[0], t[1], f\\\"https://www.imdb.com/title/tt{id}/\\\",\\n f\\\"https://www.letterboxd.com/imdb/tt{id}/\\\", t[2], t[3], score, id])\\n return title\\n else:\\n return tuple([f\\\"Movie title not retrieved. ID:{id}\\\", None, None, None, None, None, None, id])\",\n \"def dp_match(phrase, songs=None):\\n scores = [score_match(phrase, song) for song in songs]\\n i = scores.index(max(scores))\\n return scores[i], [phrase], [songs[i]]\",\n \"def recognition(database, testSong, plot=True, info=True, latextable=False):\\n #Score for every song in database with respect to testsong\\n \\n if latextable == True:\\n print(testSong[\\\"name\\\"])\\n print(\\\"\\\"\\\"\\\\\\\\begin{table}[H]\\n \\\\centering\\n \\\\\\\\begin{tabular}{|l|l|}\\n \\\\hline\\n Artist and Title & Score value\\\\\\\\\\\\\\\\\\n \\\\hline\\n \\\"\\\"\\\")\\n for i in range(len(database)):\\n scores = []\\n for j in range(testSong[\\\"spectrogram\\\"].shape[1]): #every frame of STFT\\n #Score is calculated\\n u = np.transpose(database[i][\\\"eigen\\\"]) @ (testSong[\\\"spectrogram\\\"][:, j] - database[i][\\\"mean\\\"])\\n scores.append(LA.norm(u - database[i][\\\"weights\\\"][:, j]))\\n #mean value of the scores\\n database[i][\\\"score\\\"] = sum(scores)/len(scores)\\n if latextable == True:\\n print(f'{database[i][\\\"name\\\"]} & {database[i][\\\"score\\\"]:0.7} \\\\\\\\\\\\\\\\')\\n if info == True and latextable != True:\\n print(f\\\"{database[i]['name']} has a score of {database[i]['score']}\\\")\\n if plot == True:\\n plt.plot(scores)\\n plt.title(f\\\"{database[i]['name'].split('.w')[0]}\\\\n testsong: {testSong['name'].split('/')[1].split('(o')[0]}\\\")\\n plt.show()\\n\\n #The lowest score is found and is the most alike to testSong\\n lowsScore = database[0]\\n for song in database[1:]:\\n if lowsScore[\\\"score\\\"] > song[\\\"score\\\"]:\\n lowsScore = song\\n if info == True and latextable != True: \\n print(\\\" \\\")\\n print(f\\\"The song with the lowest score is {lowsScore['name']} with a score of {lowsScore['score']}\\\")\\n \\n if latextable == True:\\n print(\\\"\\\"\\\"\\\\hline\\n\\\\end{tabular}\\n\\\\caption{Recognition of a recorded version of \\\"\\\"\\\" + testSong[\\\"name\\\"] + \\\"\\\"\\\" and the coherent score value.}\\n\\\\label{tab: }\\n\\\\end{table}\\\"\\\"\\\")\\n print(\\\" \\\")\\n return lowsScore['name'], lowsScore['score']\",\n \"def update_storyline(self):\\n search_title = self.video_title.replace(\\\" \\\", \\\"+\\\")\\n api_response = urllib.urlopen(\\\"https://api.themoviedb.org/3/search/\\\"+\\n \\\"movie?api_key=0bf3188c8eacc47d41ae97\\\"+\\n \\\"d1d6dd2cfc&query=\\\"+\\n search_title)\\n movie_data = api_response.read()\\n api_response.close()\\n if '\\\"overview\\\":\\\"' in movie_data:\\n #finding first position of storyline from API data\\n apos = movie_data.find('\\\"overview\\\":\\\"') + 12\\n #finding last position of storyline\\n bpos = movie_data.find('\\\",', apos)\\n return movie_data[apos:bpos]\\n else:\\n return\",\n \"def convert_to_tvr_subtitle(df: pd.DataFrame) -> pd.DataFrame:\\n\\tpass\",\n \"def get_by_title(title):\\n query = Session.query(Movie.title)\\n result = query.all()\\n title_list = [title for title, in result]\\n one_item = process.extractOne(title, title_list)\\n if one_item:\\n result_title, ratio = one_item\\n else:\\n return None\\n if ratio > 60:\\n return result_title\\n else:\\n return None\",\n \"def most_similar_actors_lda(self, moviename):\\n data_frame = self.data_extractor.get_mlmovies_data()\\n tag_data_frame = self.data_extractor.get_genome_tags_data()\\n movie_data_frame = self.data_extractor.get_mltags_data()\\n movie_tag_data_frame = movie_data_frame.merge(tag_data_frame, how=\\\"left\\\", left_on=\\\"tagid\\\", right_on=\\\"tagId\\\")\\n movie_tag_data_frame = movie_tag_data_frame.merge(data_frame, how=\\\"left\\\", left_on=\\\"movieid\\\", right_on=\\\"movieid\\\")\\n tag_df = movie_tag_data_frame.groupby(['movieid'])['tag'].apply(list).reset_index()\\n\\n tag_df = tag_df.sort_values('movieid')\\n movies = tag_df.movieid.tolist()\\n tag_df = list(tag_df.iloc[:, 1])\\n\\n input_movieid = self.util.get_movie_id(moviename)\\n\\n (U, Vh) = self.util.LDA(tag_df, num_topics=5, num_features=1000)\\n\\n movie_topic_matrix = self.util.get_doc_topic_matrix(U, num_docs=len(movies), num_topics=5)\\n topic_movie_matrix = movie_topic_matrix.transpose()\\n movie_movie_matrix = numpy.dot(movie_topic_matrix, topic_movie_matrix)\\n\\n index_movie = None\\n for i, j in enumerate(movies):\\n if j == input_movieid:\\n index_movie = i\\n break\\n\\n if index_movie == None:\\n print(\\\"Movie Id not found.\\\")\\n return None\\n\\n movie_row = movie_movie_matrix[index_movie].tolist()\\n movie_movie_dict = dict(zip(movies, movie_row))\\n del movie_movie_dict[input_movieid]\\n\\n for key in movie_movie_dict.keys():\\n movie_movie_dict[key] = abs(movie_movie_dict[key])\\n\\n movie_movie_dict = sorted(movie_movie_dict.items(), key=operator.itemgetter(1), reverse=True)\\n\\n if movie_movie_dict == None:\\n return None\\n actors = []\\n for (movie, val) in movie_movie_dict:\\n if val <= 0:\\n break\\n actors = actors + self.sim_act_diff_mov_tf.get_actors_of_movie(self.util.get_movie_name_for_id(movie))\\n if len(actors) >= 10:\\n break\\n\\n actors_of_given_movie = self.sim_act_diff_mov_tf.get_actors_of_movie(moviename)\\n\\n actorsFinal = [x for x in actors if x not in actors_of_given_movie]\\n\\n actornames = []\\n for actorid in actorsFinal:\\n actor = self.util.get_actor_name_for_id(actorid)\\n actornames.append(actor)\\n\\n return actornames\",\n \"def test_get_subtitles(self):\\n\\n (subtitles, start, end) = self.sp.get_subtitles(INDEX)\\n self.assertEqual(subtitles, INDEX_SUBTITLES, 'Check get_subtitles.')\",\n \"def get_best_candidate(self):\\n if not self.scores:\\n return None\\n return self.te_list[self.scores.index(max(self.scores))]\",\n \"def display_get_most_played():\\n title_game = reports.get_most_played(filename)\\n print(\\\"Title of most played game in {}: {}\\\\n\\\".format(filename, title_game))\",\n \"def get_related_titles(lstmt):\\n lst = []\\n for mtitle in lstmt:\\n dtitle = get_movies_from_tastedive(mtitle)\\n mlst = extract_movie_titles(dtitle)\\n for movie in mlst:\\n if movie not in lst:\\n lst.append(movie)\\n return lst\",\n \"def get(self):\\n parser.add_argument('title-word', required=True, help='cannot be blank')\\n return find_movie_by_title(parser.parse_args()['title-word'])\",\n \"def find_best_match(filename, e):\\n best_matches = {}\\n with open(filename) as f:\\n for record in NCBIXML.parse(f):\\n best = e\\n best_name = \\\"\\\"\\n if record.alignments:\\n for alignment in record.alignments:\\n locus = alignment.definition.split(\\\" \\\")[0].split(\\\"|\\\")[1]\\n for hsp in alignment.hsps:\\n if hsp.expect < best:\\n best_name = name\\n best = hsp.expect\\n\\n if best < e:\\n iden = record.query.split(\\\" \\\")[0]\\n best_matches[iden] = a_best_ma\\n\\n return transcription_factors\",\n \"def find_movie_by_title(title):\\n return Movie.objects.filter(title=title).first()\",\n \"def get_subtitle_print(subs: List[Track]) -> List[str]:\\n data = []\\n if not subs:\\n data.append(\\\"--\\\")\\n for sub in subs:\\n line_items = []\\n\\n # following sub.title tree checks and supports three different language and title scenarios\\n # The second scenario is the recommended option to choose if you are open to choosing any\\n # The third scenario should be used if you have nothing unique to state about the track\\n # | Language | Track Title | Output |\\n # | ------------ | ----------------------------- | --------------------------------------------- |\\n # | es / Spanish | Spanish (Latin American, SDH) | - Spanish (Latin American, SDH), SubRip (SRT) |\\n # | es / Spanish | Latin American (SDH) | - Spanish, Latin American (SDH), SubRip (SRT) |\\n # | es / Spanish | None | - Spanish, SubRip (SRT) |\\n language = pycountry.languages.get(alpha_2=sub.language).name\\n if sub.title:\\n if language.lower() in sub.title.lower():\\n line_items.append(sub.title)\\n else:\\n line_items.append(f\\\"{language}, {sub.title}\\\")\\n else:\\n line_items.append(language)\\n\\n line_items.append(sub.format.replace(\\\"UTF-8\\\", \\\"SubRip (SRT)\\\"))\\n\\n line = \\\"- \\\" + \\\", \\\".join(line_items)\\n data += [\\n (\\\" \\\" + x if i > 0 else x)\\n for i, x in enumerate(textwrap.wrap(line, 64))\\n ]\\n return data\",\n \"def get_cheapest_price(self, movie_title):\\n self.get_all_movies()\\n movie_list = self.title_map.get(movie_title.strip().lower(), [])\\n\\n if movie_list is None:\\n return None\\n\\n pick_list = []\\n for movie_info in movie_list:\\n try:\\n movie_id = movie_info['ID']\\n movie_world = movie_info['world']\\n except KeyError as e:\\n print(\\\"Price is not available for {}\\\".format(movie_title))\\n continue\\n pick_list.append({'id': movie_id, 'world': movie_world})\\n\\n if pick_list is None:\\n return None\\n\\n pool = Pool(2)\\n movies_list = pool.map(self.get_movie_from_id, pick_list)\\n pool.close()\\n pool.join()\\n\\n # Set price as maximum float value in start to find minimum value\\n price = sys.float_info.max\\n print(\\\"\\\\nMovie info from different worlds:\\\\n\\\")\\n for movie in movies_list:\\n if movie is None:\\n continue\\n print(\\\"[{}]\\\".format(movie['world']))\\n for key, value in movie.items():\\n print(\\\" {} = {}\\\".format(key, value))\\n print(\\\"\\\\n\\\")\\n try:\\n movie_price = float(movie['Price'])\\n except KeyError as e:\\n print(\\\"Price is not available for {}\\\".format(movie_title))\\n continue\\n if movie_price < price:\\n price = movie_price\\n\\n if price == sys.float_info.max:\\n return None\\n\\n return str(price)\",\n \"def get_movie_most_nominations(movies: list) -> str:\\n pass\",\n \"def return_movie_list(url: str) -> (bs4.element.NavigableString, list, list):\\n soup = return_beautiful_soup_object(url)\\n cell_data_list = soup.find('body').find('div', {'class': 'col-left-center'}).find('table').find_all('td')\\n span_rating_list = list([cell.find_all('span', {'class': 'tMeterScore'}) for cell in cell_data_list])\\n rating_list = list([span[0].text.strip() for span in span_rating_list if span != []])\\n movies = list(movie[0].text.strip() for movie in list([cell.find_all('a') for cell in cell_data_list])\\n if movie != [])\\n return soup.title.contents[0], movies, rating_list\",\n \"def _match_movie_titles(self, cinema_schedule_data):\\n matcher = MovieIDMatcher()\\n invalid_titles = []\\n for title, content in cinema_schedule_data.items():\\n\\n logging.warning(\\\"Matching movie: \\\" + title)\\n\\n imdb_id = matcher.match_imdb_id_from_title_recent(title)\\n if imdb_id is None:\\n logging.error(\\\"IMDb ID matched is invalid!\\\")\\n invalid_titles.append(title)\\n continue\\n\\n cinema_schedule_data[title] = {\\n 'imdb_id': imdb_id,\\n 'content': content\\n }\\n self.update_single_movie_data(imdb_id)\\n logging.warning(\\\"matching successful!\\\")\\n\\n for invalid_title in invalid_titles:\\n cinema_schedule_data.pop(invalid_title)\",\n \"def select_best_match(self, normalized_texts: List[str], transcript: str, verbose: bool = False):\\n normalized_texts = calculate_cer(normalized_texts, transcript)\\n normalized_texts = sorted(normalized_texts, key=lambda x: x[1])\\n normalized_text, cer = normalized_texts[0]\\n\\n if verbose:\\n print('-' * 30)\\n for option in normalized_texts:\\n print(option)\\n print('-' * 30)\\n return normalized_text, cer\",\n \"def get_top_words(self, label, n):\\n score_list = []\\n if('sod' in label):\\n for term in self.vocab:\\n score = self.cond_prob_sod[term] / self.cond_prob_pop[term]\\n score_list.append((score,term)) \\n else:\\n for term in self.vocab:\\n score = self.cond_prob_pop[term] / self.cond_prob_sod[term]\\n score_list.append((score,term))\\n score_list = sorted(score_list, key=lambda x:x[0],reverse=True)[:n]\\n return score_list \\n pass\",\n \"def get_best(self):\\n scores, ids = self.sort_best()\\n return scores[1], ids[1]\",\n \"def generate_subtitles(\\n source_path,\\n output=None,\\n dst_language=DEFAULT_DST_LANGUAGE,\\n debug=False,\\n cloud=False,\\n disable_time=False,\\n min_height=80,\\n max_height=100,\\n l_v=240\\n ):\\n # Opens the Video file\\n print(f\\\"starting: using cloud {cloud}, source_path {source_path}\\\")\\n if not cloud:\\n ocr = PaddleOCR(lang='ch', use_gpu=False,\\n rec_model_dir=r\\\"C:\\\\autosub_models\\\\rec\\\",\\n cls_model_dir=r\\\"C:\\\\autosub_models\\\\cls\\\",\\n det_model_dir=r\\\"C:\\\\autosub_models\\\\det\\\",\\n use_angle_cls=True,\\n rec_char_type='ch',\\n drop_score=0.8,\\n det_db_box_thresh=0.3,\\n cls=True)\\n\\n cap = cv2.VideoCapture(source_path)\\n # cap.set(3, 1280)\\n # cap.set(4, 720)\\n # cv2.createTrackbar(\\\"L - V\\\", \\\"Trackbars\\\", 0, 100, nothing)\\n # cv2.createTrackbar(\\\"Min height\\\", \\\"Trackbars\\\", 80, 100, nothing)\\n # cv2.createTrackbar(\\\"Max Height\\\", \\\"Trackbars\\\", 100, 100, nothing)\\n fps = cap.get(cv2.CAP_PROP_FPS)\\n print(f\\\"fps {fps}\\\")\\n time_per_frame = 1 / fps\\n i = 0\\n div_frame = 6 # 5 frame /s\\n sub_idx = 1\\n list_srt = []\\n old_des = \\\"\\\"\\n prev_time = 0\\n current_time = 0\\n file_name = os.path.basename(source_path)\\n extenstion = \\\".srt\\\" if not disable_time else \\\".txt\\\"\\n filesub = f\\\"{os.path.splitext(file_name)[0]}{extenstion}\\\"\\n if os.path.isfile(filesub):\\n os.remove(filesub)\\n while (cap.isOpened()):\\n ret, frame = cap.read()\\n if ret == False:\\n break\\n\\n # min_height = cv2.getTrackbarPos(\\\"Min height\\\", \\\"Trackbars\\\")\\n # max_height = cv2.getTrackbarPos(\\\"Max Height\\\", \\\"Trackbars\\\")\\n # if max_height < min_height:\\n # max_height = min_height + 10\\n\\n # l_v = cv2.getTrackbarPos(\\\"L - V\\\", \\\"Trackbars\\\")\\n\\n if i % div_frame == 0:\\n prev_time_ts = datetime.utcfromtimestamp(prev_time).strftime('%H:%M:%S,%f')[:-4]\\n current_time_ts = datetime.utcfromtimestamp(current_time).strftime('%H:%M:%S,%f')[:-4]\\n h, w, c = frame.shape\\n crop_img = frame[int(h * min_height/100):int(h * max_height/100), 0:w]\\n hsv = cv2.cvtColor(crop_img, cv2.COLOR_BGR2HSV)\\n\\n # define range of white color in HSV\\n # change it according to your need !\\n lower_white = np.array([0, 0, 246], dtype=np.uint8)\\n upper_white = np.array([157, 21, 255], dtype=np.uint8)\\n\\n # Threshold the HSV image to get only white colors\\n mask = cv2.inRange(hsv, lower_white, upper_white)\\n # Bitwise-AND mask and original image\\n crop_img = cv2.bitwise_and(crop_img, crop_img, mask=mask)\\n # crop_img = cv2.cvtColor(crop_img, cv2.COLOR_HSV2RGB)\\n # crop_img = cv2.cvtColor(crop_img, cv2.COLOR_RGB2GRAY)\\n\\n description = \\\"\\\"\\n if cloud:\\n success, encoded_image = cv2.imencode('.jpg', crop_img)\\n description = detect_texts_google_cloud(encoded_image.tobytes())\\n else:\\n # dst = cv2.fastNlMeansDenoisingColored(crop_img,None,10,10,7,21)\\n # stacked = np.hstack((dst, crop_img))\\n if debug:\\n # cv2.imshow('dst', dst)\\n cv2.imshow('crop_img', crop_img)\\n cv2.imshow('frame', frame)\\n cv2.waitKey(1)\\n\\n result = ocr.ocr(crop_img, det=False, rec=True, cls=False)\\n for line in result:\\n # print(current_time_ts, line)\\n if line[1] > 0.7:\\n description = html.unescape(line[0].strip().replace('，', '').replace('、', '').replace('．', ''))\\n break\\n\\n description = \\\"\\\" if len(description) < 6 else description\\n prev_des = \\\"\\\"\\n ratio = fuzz.ratio(description.lower(), old_des.lower())\\n if len(list_srt) > 0:\\n prev_des = list_srt[-1]['description']\\n\\n print(current_time_ts, description, ratio)\\n if (old_des != \\\"\\\" or description == \\\"\\\") and (ratio < 70) and current_time - prev_time > 0.5:\\n list_srt.append({\\n \\\"description\\\": old_des,\\n \\\"translate\\\": translate_text(dst_language, old_des),\\n \\\"first_time\\\": prev_time_ts,\\n \\\"last_time\\\": current_time_ts,\\n \\\"sub_idx\\\": sub_idx\\n })\\n # with open(f\\\"{os.path.splitext(file_name)[0]}_raw.srt\\\", \\\"a\\\", encoding=\\\"utf-8\\\") as myfile:\\n # myfile.write(f\\\"{list_srt[-1]['sub_idx']}\\\\n\\\")\\n # myfile.write(f\\\"{list_srt[-1]['first_time']} --> {list_srt[-1]['last_time']}\\\\n\\\")\\n # myfile.write(f\\\"{list_srt[-1]['description']}\\\\n\\\")\\n # myfile.write('\\\\n')\\n # myfile.close()\\n\\n with open(filesub, \\\"a\\\", encoding=\\\"utf-8\\\") as myfile_vi:\\n if not disable_time:\\n myfile_vi.write(f\\\"{list_srt[-1]['sub_idx']}\\\\n\\\")\\n myfile_vi.write(f\\\"{list_srt[-1]['first_time']} --> {list_srt[-1]['last_time']}\\\\n\\\")\\n myfile_vi.write(f\\\"{list_srt[-1]['translate']}\\\\n\\\")\\n myfile_vi.write('\\\\n')\\n myfile_vi.close()\\n\\n print(f\\\"{list_srt[-1]['sub_idx']}\\\\n\\\")\\n print(f\\\"{list_srt[-1]['first_time']} --> {list_srt[-1]['last_time']}\\\\n\\\")\\n print(f\\\"{list_srt[-1]['description']}\\\\n\\\")\\n print(f\\\"{list_srt[-1]['translate']}\\\\n\\\")\\n print(f\\\"Similarity{ratio}\\\\n\\\")\\n print('\\\\n')\\n\\n sub_idx += 1\\n prev_time = current_time\\n\\n if description == \\\"\\\":\\n prev_time = current_time\\n\\n old_des = description\\n current_time += time_per_frame * div_frame\\n\\n i += 1\\n\\n cap.release()\\n return output\",\n \"def get_movie(self, identifier: int) -> Movie:\\n result = list(filter(lambda x: x.identifier == identifier, self.items))\\n if result:\\n return result[0]\\n\\n return None\",\n \"def find_match(second_file, title):\\r\\n # Initialize variables/ open files\\r\\n seq2 = \\\"\\\"\\r\\n header2 = \\\"\\\"\\r\\n match_fh = open(second_file, \\\"r\\\")\\r\\n # parse through lines of file\\r\\n for lines in match_fh:\\r\\n # If > found assume its header\\r\\n if lines[0] == \\\">\\\":\\r\\n # header2 = lines\\r\\n # If a header has been found, pull strain name, orgainism and subtype for new header\\r\\n if len(header2) > 0:\\r\\n matches2 = re.findall(\\\"(Strain Name:[AB]\\\\/[\\\\/A-Za-z 0-9()\\\\\\\\-_'.]+)\\\", header2)\\r\\n subtype_match2 = re.findall(\\\"(Subtype:[A-Za-z0-9]+)\\\", header2)\\r\\n organ2 = re.findall(\\\"(Organism:[\\\\/A-Za-z 0-9()\\\\\\\\-_'.]+)\\\", header2)\\r\\n header2 = \\\">\\\" + organ2[0] + \\\"|\\\" + matches2[0] + \\\"|\\\" + subtype_match2[0]\\r\\n # if new header equals input header then return it and the sequence\\r\\n if header2 == title:\\r\\n match_fh.close()\\r\\n print(\\\"match\\\")\\r\\n return header2, seq2\\r\\n # Reset the header and seq\\r\\n header2 = lines\\r\\n seq2 = \\\"\\\"\\r\\n\\r\\n else:\\r\\n # if it is part of the sequence\\r\\n seq2 = seq2 + lines\\r\\n\\r\\n # to return the last entry in the file, since loop won't be able to return it\\r\\n matches2 = re.findall(\\\"(Strain Name:[AB]\\\\/[\\\\/A-Za-z 0-9()\\\\\\\\-_'.]+)\\\", header2)\\r\\n subtype_match2 = re.findall(\\\"(Subtype:[A-Za-z0-9]+)\\\", header2)\\r\\n organ2 = re.findall(\\\"(Organism:[\\\\/A-Za-z 0-9()\\\\\\\\-_'.]+)\\\", header2)\\r\\n header2 = \\\">\\\" + organ2[0] + \\\"|\\\" + matches2[0] + \\\"|\\\" + subtype_match2[0]\\r\\n match_fh.close()\\r\\n return header2, seq2\",\n \"def fetch_trailer(self, movie_id):\\n movie = tmdbsimple.Movies(movie_id)\\n request = movie.videos()\\n trailer = movie.results[0]['key']\\n\\n return trailer\",\n \"def get_recommendations(df,song_title, similarity_score, num_recommends = 5):\\r\\n indices = pd.Series(df.index, index = df['track_name']).drop_duplicates()\\r\\n idx = indices[song_title]\\r\\n sim_scores = list(enumerate(similarity_score[idx]))\\r\\n sim_scores = sorted(sim_scores, key = lambda x: x[1],reverse = True)\\r\\n top_scores = sim_scores[1:num_recommends+1]\\r\\n song_indices = [i[0] for i in top_scores]\\r\\n return df[\\\"track_name\\\"].iloc[song_indices]\",\n \"def tmdb_info(title):\\n result = False\\n search_result = tmdb.Movies(title, limit=True)\\n for movie in search_result.iter_results():\\n result = movie\\n break\\n return result\",\n \"def parse_infotable_movie(soup, pageurl):\\n\\t# find the infobox (right of screen)\\n\\tinfo_table = soup.findAll('table', {'class': 'infobox vevent'})\\n\\t# if info_table doesn't exist, cannot find year and gross\\n\\tif len(info_table) == 0:\\n\\t\\treturn None, None\\n\\tgross = None\\n\\tyear = None\\n\\t# search each row of the info_table\\n\\tfor row in info_table[0].findAll('tr'):\\n\\t\\theader = row.find('th')\\n\\t\\t# check for header for year row\\n\\t\\tif header != None and header.find('div') != None and header.find('div').get_text() == 'Release date':\\n\\t\\t\\tdate = row.find('td')\\n\\t\\t\\tif date.find('div') != None and date.find('div').find('ul') != None:\\n\\t\\t\\t\\tdate = date.find('div').find('ul').find('li').find('span')\\n\\t\\t\\t# clean the date and extract year before returning\\n\\t\\t\\tyear = parse_year_movie(date.get_text(), pageurl)\\n\\t\\t# check for header for gross row\\n\\t\\tif header != None and header.get_text() == 'Box office':\\n\\t\\t\\tgross = row.find('td').get_text()\\n\\t\\t\\tif gross == None:\\n\\t\\t\\t\\treturn None\\n\\t\\t\\t# clean the gross number to return as int\\n\\t\\t\\tgross = parse_gross_movie(gross, pageurl)\\n\\treturn year, gross\",\n \"def find_top_and_topic(self, index, trs):\\n\\n top_result = \\\"kein_TOP\\\" \\n topic_result = \\\"kein_TOPIC\\\" \\n\\n while index > 0:\\n tree = html.fromstring(trs[index].get())\\n top = tree.xpath('//tr/td[contains(@class, \\\"smc_tophn\\\")]/text()') \\n topic = tree.xpath('//tr/td/a[contains(@class, \\\"smc_doc smc_field_voname smc_datatype_vo\\\")]/text()') \\n\\n if top != [] and top_result == \\\"kein_TOP\\\":\\n top_result = top[0]\\n if topic != [] and topic_result == \\\"kein_TOPIC\\\":\\n topic_result = topic[0]\\n\\n index -= 1\\n\\n return top_result, topic_result\",\n \"def get_best_speaker(self):\\n max_val = -33.0\\n try:\\n self.value = max(self.speakers.values())\\n except ValueError:\\n self.value = -100\\n _speaker = 'unknown'\\n distance = self.get_distance()\\n \\n if len(self.speakers.values()) >1:\\n mean_distance = self.get_m_distance()\\n else:\\n mean_distance = .5\\n \\n thres = 0\\n \\n if distance > -1:\\n thres = max_val - distance\\n else: thres = max_val\\n \\n if self.value >= thres and mean_distance > .49:\\n for spk in self.speakers:\\n if self.speakers[spk] == self.value:\\n _speaker = spk\\n break\\n \\n if distance > -1 and distance < .07:\\n _speaker = 'unknown'\\n \\n return _speaker\",\n \"def get_title_by_id_from_table(table, id):\\n\\n for line in sales_data:\\n if line[ID] == id:\\n return line[TITLE]\\n return None\",\n \"def get_oscars_best_picture_list():\\n list_file = 'oscar_best_picture_list.txt'\\n f = open(list_file, 'r')\\n film_list = []\\n\\n for line in f:\\n words = line.split('-')\\n film = {\\n 'year': words[0][:-1],\\n 'name': words[1][2:-2]\\n }\\n film_list.append(film)\\n f.close()\\n # Reverse as we want newest first not last\\n film_list.reverse()\\n return film_list\",\n \"def search_for_title(session, search_term):\\n try:\\n s_result = session.search_movie(search_term)\\n shows = {}\\n\\n # made the keys of the namedtuple a digit for ease of selecting the correct one later\\n for count, result in enumerate(s_result):\\n show_id = count\\n movie_id = result.movieID\\n title = result['long imdb canonical title']\\n url = f'http://www.imdb.com/title/tt{movie_id}/parentalguide'\\n shows[count] = Show(show_id, movie_id, title, url)\\n return shows\\n except imdb._exceptions.IMDbDataAccessError:\\n display_error()\",\n \"def ratings_best(Y, titles):\\n ratings_lists = data_proc.ratings_for_movies(Y)\\n\\n # Possible rating values\\n rating_values = list(range(1, 6))\\n\\n # avg_ratings[i] = average rating of movie i\\n # avg_ratings = [float(sum(ratings_list)) / len(ratings_list)\\n # for ratings_list in ratings_lists]\\n # Disfavor highly rated movies with few ratings:\\n # http://stats.stackexchange.com/a/6361\\n avg_ratings = [float(sum(ratings_list) + sum(rating_values))\\n / (len(ratings_list) + len(rating_values))\\n for ratings_list in ratings_lists]\\n best_ids = data_proc.top_indices(avg_ratings, 10)\\n best_titles = [titles[id] for id in best_ids]\\n\\n # ratings_table[i][j] is the number of rating_values[j] ratings for\\n # movie with id i\\n ratings_table = \\\\\\n [[sum([rating_list[1] == id and rating_list[2] == rating_val\\n for rating_list in Y])\\n for rating_val in rating_values]\\n for id in best_ids]\\n\\n sns.heatmap(ratings_table,\\n annot=True, fmt='d', # Annotate data values\\n yticklabels=best_titles, xticklabels=rating_values)\\n plt.yticks(rotation=0) # Rotate yticks horizontally\\n plt.xlabel('Rating')\\n plt.title('Ratings of highest rated movies')\\n plt.tight_layout() # Make room for long ytick labels\\n plt.show()\",\n \"def find_table(self):\\n tables = self.document.tables\\n header = []\\n for table in tables:\\n for row in table.rows:\\n header[:] = []\\n for cell in row.cells:\\n for para in cell.paragraphs:\\n header.append(para.text.strip(' '))\\n # new versions of final CAPA's keep project information in a table\\n if 'Project Information' in header:\\n self.read_new_format(table)\\n # check if elements in findings is also in header\\n cond = len(header) == 5 and header[4] == 'Rating'\\n if cond or [x for x in self.findings for y in header if x in y] == self.findings:\\n self.table = table\\n return\",\n \"def closest_match(episodeplot, seriesname):\\n LOG.debug(\\\"Calling closest_match() with the following arguments:\\\")\\n LOG.debug(\\\"episodeplot= %s\\\"%episodeplot)\\n LOG.debug(\\\"seriesname= %s\\\"%seriesname)\\n #Doc2Vec.most_similar(positive=[], negative=[], topn=1, restrict_vocab=None)\\n #If topn is False, most_similar returns the vector of similarity scores.\\n\\n return bestmatch, quality\",\n \"def select_best_match(\\n self, normalized_texts: List[str], transcript: str, verbose: bool = False, remove_punct: bool = False\\n ):\\n normalized_texts = calculate_cer(normalized_texts, transcript, remove_punct)\\n normalized_texts = sorted(normalized_texts, key=lambda x: x[1])\\n normalized_text, cer = normalized_texts[0]\\n\\n if verbose:\\n print('-' * 30)\\n for option in normalized_texts:\\n print(option)\\n print('-' * 30)\\n return normalized_text, cer\",\n \"def print_movie_table(self):\\n self = self\\n headers = [\\\"Votes\\\", \\\"Rank\\\", \\\"Year\\\", \\\"Title\\\"]\\n self.handler.header(headers)\\n\\n for movie in self.movie_list:\\n self.handler.row([str(movie.get_votes()), str(movie.get_rank()),\\n str(movie.get_year()), str(movie.get_title())])\\n\\n self.handler.footer()\",\n \"def get_summary(filename=video_file, subtitles=srt_filename, duration = 300):\\n regions = find_summary_regions(subtitles, duration, \\\"english\\\")\\n summary = create_summary(filename, regions)\\n base, ext = os.path.splitext(filename)\\n output = \\\"{0}_summary.mp4\\\".format(base)\\n summary.to_videofile(\\n output,\\n codec=\\\"libx264\\\",\\n temp_audiofile=\\\"temp.m4a\\\", remove_temp=True, audio_codec=\\\"aac\\\")\\n return True\",\n \"def find_tables_by_title(table_list, title_pattern):\\n\\n rtitle = re.compile(title_pattern)\\n rtable_list = []\\n for table in table_list:\\n if rtitle.match(table.title()):\\n rtable_list.append(table)\\n return rtable_list\",\n \"def find_best_match_jobs(self,candidate_matrix):\\n\\n \\\"\\\"\\\"\\n Example format for input:\\n candidate_matrix =\\n {\\n 0: {\\\"This is a skill description\\\": 10, \\\"This is another skill description\\\": 7},\\n 1: {\\\"This is a knowledge description\\\" : 8, \\\"This is another knowledge description\\\": 6}\\n }\\n \\\"\\\"\\\"\\n\\n\\n\\n\\n\\n\\n # Get a list of all job codes to begin importing details for\\n cursor = self.conn.execute(\\\"SELECT job_code FROM job\\\")\\n\\n # Get python list of all job codes\\n job_codes = cursor.fetchall()\\n\\n\\n job_score = {}\\n\\n for job_code in job_codes:\\n job_code = job_code[0]\\n job_importance_matrix = self.generate_job_importance_matrix(job_code)\\n\\n\\n job_score[job_code] = self.calculate_job_score(candidate_matrix, job_importance_matrix)\\n\\n\\n # Sort by job scores!\\n sorted_jobs = sorted(job_score.iteritems(), key=operator.itemgetter(1))\\n\\n # Get in descending order\\n sorted_jobs.reverse()\\n\\n # Return the jobs with the top 5 job scores for the candidate\\n return sorted_jobs[:5]\",\n \"def get_all_movies(self):\\n cinemaworld_movies, filmworld_movies = self.get_movies()\\n\\n if cinemaworld_movies is not None:\\n self.get_title_map(cinemaworld_movies, \\\"cinemaworld\\\")\\n if filmworld_movies is not None:\\n self.get_title_map(filmworld_movies, \\\"filmworld\\\")\\n\\n return self.title_map\",\n \"def full_text_search_title(self, term: str):\\n if not self.client:\\n self.connect()\\n query = templates.full_text_search_title(term)\\n return self.client.moviebuff.engtitles.aggregate(query)\",\n \"def calculate_needed_subtitle_height(annotation, seen_annotations, video_clip):\\n width = video_clip.w\\n text = annotation[\\\"text\\\"].encode('utf-8')\\n if len(text) > width / 40:\\n text, lines_inserted = newlinify_string(text, int(width / 40))\\n add_to_subtitle_offset(annotation, seen_annotations, lines_inserted - 1)\\n\\n return text\",\n \"def get_top_movies(genre: Genre) -> List[Movie]:\\n\\n html = download_top_movies(genre)\\n soup = parse_top_movies(html)\\n return [extract_movie(result) for result in soup]\",\n \"def get_matching_names(understat_names, fpl_names): \\n understat_names, fpl_names = understat_names['player_name'].unique(), fpl_names['player_name'].unique()\\n seq = difflib.SequenceMatcher()\\n understat_similar = []\\n fpl_similar = []\\n ratio = []\\n for i in range(len(understat_names)):\\n for j in range(len(fpl_names)):\\n seq.set_seqs(understat_names[i].lower(), fpl_names[j].lower())\\n ratio_similar = seq.ratio()\\n understat_similar.append(understat_names[i])\\n fpl_similar.append(fpl_names[j])\\n ratio.append(ratio_similar)\\n similarity_matched_df = pd.DataFrame({'understat':understat_similar, 'fpl':fpl_similar, 'similarity': ratio}).copy()\\n similarity_matched_df_final = similarity_matched_df.loc[similarity_matched_df.groupby('understat')['similarity'].idxmax()].copy()\\n # print(similarity_matched_df_final.sort_values('similarity',ascending=False).to_latex())\\n return similarity_matched_df_final\",\n \"def most_stable():\\n \\n \\n \\n \\n return Z\",\n \"def get_subtitleinfo(fileFullName):\\n sys.stdout.write(\\\"Requesting subtitle info...\\\\n\\\")\\n\\n #接口获取字幕信息\\n response = requests.post(\\n \\\"https://www.shooter.cn/api/subapi.php\\\",\\n verify=False,\\n params= {\\n 'filehash': ComputeFileHash(fileFullName),\\n 'pathinfo': os.path.realpath(fileFullName),\\n 'format': 'json',\\n 'lang': \\\"Chn\\\",\\n },\\n )\\n #未找到字幕处理\\n if response.text == u'\\\\xff':\\n sys.stderr.write(\\\"Subtitle not found.\\\\n\\\")\\n sys.exit(1)\\n return response\",\n \"def second_lowest():\\n copy = movies.copy()\\n name = copy.sort_values(['Total Gross']).reset_index(drop = True)['#1 Movie'].loc[1]\\n return ('second_lowest', name)\",\n \"def get_title_by_id_from_table(table, id):\\n\\n # your code\",\n \"def get_table_by_text(text: str) -> Dict[str, str]:\\n for morse_table in MORSE_TABLES:\\n letter_to_check = _get_first_letter_in_text(text)\\n if letter_to_check.upper() in morse_table.keys():\\n return morse_table\\n if letter_to_check in morse_table.values():\\n return MORSE_EN_CODE_DICT\\n raise LanguageDoseNotSupported\",\n \"def transcribe_table_data(text_table, match_time=-1):\\n\\n\\tprocessed_data = []\\n\\n\\tfor text in text_table:\\n\\t\\tif len(text) == 0:\\n\\t\\t\\tcontinue\\n\\t\\thash_id = md5(text.encode('utf-8')).hexdigest()\\n\\t\\tteam_1, score, team_2, tournament, matchtype = text.split('\\\\n')\\n\\t\\tteam_1_score, team_2_score = score.split(' - ')\\n\\t\\tmatch_summary = (hash_id, team_1, team_2, int(team_1_score), int(team_2_score), tournament, matchtype, match_time)\\n\\t\\tprocessed_data.append(match_summary)\\n\\n\\treturn processed_data\",\n \"def compute_sentences_ranking(video_captions):\\n sentences_global_ranking = []\\n\\n if config.experiment == 'experiment1':\\n bfs = True\\n embeddings = []\\n labels = []\\n for sentence in video_captions.sentences:\\n sentence_embedding = sentence.get_sentence_embedding(bfs)\\n if len(sentence_embedding) > 0: # there are sentences without senses (i.e. 'its a t') --> no embedding!\\n embeddings.append(sentence_embedding)\\n labels.append(sentence.sentence)\\n\\n embeddings_mean = np.mean(embeddings, axis=0)\\n distances = [scipy.spatial.distance.cosine(embedding, embeddings_mean) for embedding in embeddings]\\n for i, distance in enumerate(distances):\\n sentences_global_ranking.append((video_captions.sentences[i].sentence, distance))\\n\\n elif config.experiment == 'experiment5':\\n chencherry = SmoothingFunction()\\n for i, sentence1 in enumerate(video_captions.sentences):\\n scores = [bleu_score.sentence_bleu([sentence2.sentence.split(' ')], sentence1.sentence.split(' '), smoothing_function=chencherry.method4) for j, sentence2 in enumerate(video_captions.sentences)] # if i != j] # if we add 1 to all, result shouldn't change\\n score = sum(scores) / len(scores)\\n sentences_global_ranking.append((sentence1.sentence, score))\\n\\n else:\\n result = np.zeros([20, 20])\\n for i, sentence1 in enumerate(video_captions.sentences):\\n for j, sentence2 in enumerate(video_captions.sentences):\\n similarities = []\\n for token1_id in sentence1.tokens_id_list:\\n\\n # find most similar token to sentence1.token1 in sentence2.tokens\\n most_similar_token_in_sentence = (None, float('-inf'))\\n for token2_id in sentence2.tokens_id_list:\\n if (token1_id, token2_id) in config.tokens_set.tokens_similarities_closest:\\n similarity = config.tokens_set.tokens_similarities_closest[(token1_id, token2_id)]\\n if similarity > most_similar_token_in_sentence[1]:\\n most_similar_token_in_sentence = (token2_id, similarity)\\n\\n # store token similarity (depending on the experiments we check if it is over threshold)\\n if most_similar_token_in_sentence[0] is not None:\\n if config.experiment in ['experiment4', 'experiment4symmetrical']:\\n if most_similar_token_in_sentence[1] > config.th1:\\n similarities.append((most_similar_token_in_sentence[0], 1.0)) # for each token we add 1 instead of similarity\\n else:\\n similarities.append((None, 0))\\n elif config.experiment == 'experiment3':\\n if most_similar_token_in_sentence[1] > config.th1:\\n similarities.append(most_similar_token_in_sentence)\\n else:\\n similarities.append((None, 0))\\n elif config.experiment == 'experiment2':\\n similarities.append(most_similar_token_in_sentence)\\n\\n # compute and store similarity between sentence1 and sentence2\\n if len(similarities) > 0:\\n sentences_similarity = float(sum([a[1] for a in similarities])) / len(similarities)\\n else:\\n sentences_similarity = 0\\n\\n result[i, j] = sentences_similarity\\n\\n # we make the similarities symmetrical\\n if config.experiment == 'experiment4symmetrical':\\n for i in range(0, len(result)):\\n for j in range(0, len(result)):\\n symmetric_similarity = 0\\n if result[i, j] + result[j, i] != 0:\\n symmetric_similarity = (result[i, j] + result[j, i]) / 2\\n result[i, j] = symmetric_similarity\\n result[j, i] = symmetric_similarity\\n\\n # compute sentences similarity to all others (array of size 20)\\n sentences_similarities = (np.sum(result, axis=1)) / result.shape[1] # sentences similarities normalized between 0 and 1\\n for i, similarity in enumerate(sentences_similarities):\\n sentences_global_ranking.append((video_captions.sentences[i].sentence, similarity))\\n\\n return sentences_global_ranking\",\n \"def select_best_th(metrics_dict: Dict, metric: str):\\n max_metric_ix = np.argmax(metrics_dict[metric])\\n return metrics_dict['metrics_ths'][max_metric_ix]\",\n \"def topseq(filename):\\n\\n\\tdic = {0:\\\"A\\\",1:\\\"C\\\",2:\\\"G\\\",3:\\\"T\\\"} # dictionary of indexes of each nucleotide for matrices\\n\\ttf1 = np.loadtxt(filename, skiprows=1)\\n\\ttf2 = tf1[:,1:].transpose()\\n\\tindexes = np.argmax(tf2,axis=0).tolist() #generates a list of indexes of the highest probability base per position. \\n\\tseqstring = \\\"\\\"\\n\\tfor i in indexes: #generates a string nucleotide sequence corresponding top nucleotide for each position\\n\\t\\tseqstring += dic[i]\\n\\treturn seqstring # returns the top motif\",\n \"def get_table(image):\\n bounds = {}\\n for pocket in ['tl', 'tr', 'bl', 'br']:\\n\\n matchmap = matchTemplate(image, pocket_templates[pocket])\\n minval, maxval, minloc, maxloc = cvMinMaxLoc(matchmap)\\n\\n #print(\\\"Pocket %s value = %d\\\" % (pocket, minval))\\n\\n if minval < POCKET_TRESHOLD:\\n # Found a possible match\\n bounds[pocket] = cvPoint(minloc.x + pocket_markers[pocket].x, minloc.y + pocket_markers[pocket].y)\\n else:\\n # If the best match for a pocket is above the treshold, then we can discard\\n # the whole thing\\n return None\\n\\n if DEBUG: print(\\\"Possible table bounds %s\\\" % bounds)\\n\\n # Sanity check\\n\\n if bounds['tl'].x >= bounds['tr'].x or bounds['bl'].x >= bounds['br'].x:\\n return None\\n if bounds['tl'].x <= bounds['bl'].x or bounds['tr'].x >= bounds['br'].x:\\n return None\\n if bounds['bl'].y <= bounds['tl'].y:\\n return None\\n\\n # Make sure top and bottom edges are straight\\n if abs( bounds['tl'].y - bounds['tr'].y ) > image.height / 80:\\n return None\\n if abs( bounds['bl'].y - bounds['br'].y ) > image.height / 80:\\n return None\\n\\n # Make sure table is more or less symmetrical\\n if math.fabs((bounds['tl'].x-bounds['bl'].x)-(bounds['br'].x-bounds['tr'].x)) > image.width / 100:\\n return None\\n\\n return bounds\",\n \"def textrank(self, sentences, n_top=2, stopwords=None):\\n S = self.build_similarity_matrix(sentences, stopwords) \\n sentence_ranks = self.pagerank(S)\\n \\n # Sort the sentence ranks\\n ranked_sentence_indexes = [item[0] for item in sorted(enumerate(sentence_ranks), key=lambda item: -item[1])]\\n #print(ranked_sentence_indexes)\\n selected_sentences = sorted(ranked_sentence_indexes[:n_top])\\n summary = itemgetter(*selected_sentences)(sentences)\\n return summary\",\n \"def search_videos(self, search_term):\\n recommendations = []\\n for video in self.videos_dict:\\n if not video.flagged and search_term in self.videos_dict[video]:\\n recommendations.append(self.videos_dict[video])\\n \\n recommendations.sort()\\n n = len(recommendations)\\n\\n\\n if n == 0:\\n print(f\\\"No search results for {search_term}\\\")\\n else:\\n print(f\\\"Here are the results for {search_term}:\\\")\\n for i in range(n):\\n print(f\\\"{i+1}) {recommendations[i]}\\\")\\n print(\\\"Would you like to play any of the above? If yes, specify the number of the video.\\\")\\n print(\\\"If your answer is not a valid number, we will assume it's a no.\\\")\\n\\n try:\\n response = int(input())\\n if response in range(1,n+1):\\n wanted_video_info = recommendations[response-1]\\n #print(wanted_video_info)\\n s = wanted_video_info\\n result = re.search(r\\\"\\\\(([A-Za-z0-9_]+)\\\\)\\\", s)\\n #print(result.group(1))\\n self.play_video(result.group(1))\\n except ValueError:\\n pass\",\n \"def get_tfidf(self, movie):\\n return self.tf[movie] * self.idf\",\n \"def table_dictionary_time(max_time):\\n\\n b = [1, 27183, 250726]\\n tablesize = [250727, 402221, 1000081]\\n dic = [\\\"english_small.txt\\\",\\\"english_large.txt\\\",\\\"french.txt\\\"]\\n\\n with open('output_task2.csv', 'w') as openFile: # create csv file\\n\\n writer = csv.writer(openFile)\\n writer.writerow(['Dic','Tablesize', 'b', 'No. of words', 'time taken'])\\n\\n for i in range((len(dic))):\\n counter = 0\\n counter2 = 0\\n for k in range(len(b)*len(tablesize)):\\n base = b[counter2]\\n table_Size = tablesize[counter]\\n print(base, table_Size)\\n word_n_time = load_dictionary_time(base, table_Size, dic[i], max_time)\\n counter += 1\\n\\n if counter == 3:\\n counter = 0\\n print(word_n_time)\\n\\n if word_n_time[1] is None:\\n writer.writerow([dic[i], table_Size, base, word_n_time[0],(max_time+10)])\\n else:\\n writer.writerow([dic[i], table_Size, base, word_n_time[0], word_n_time[1]])\\n\\n if counter == 0:\\n counter2 += 1\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.618252","0.5965921","0.57754785","0.5734618","0.57143825","0.5659548","0.5541539","0.5518001","0.5478379","0.5466522","0.543087","0.53836876","0.5375327","0.52907383","0.52813095","0.5275028","0.52749276","0.52622724","0.5237285","0.5202462","0.5175123","0.5173618","0.51668274","0.5139571","0.5131304","0.5099078","0.5094993","0.5065269","0.5028155","0.5025415","0.50192606","0.50082844","0.4996621","0.4996621","0.49902168","0.49617994","0.49574625","0.49536955","0.49496618","0.49474823","0.4935896","0.4901887","0.48997942","0.4887643","0.48823574","0.48753387","0.48521185","0.48483363","0.48480487","0.48476347","0.4835774","0.4833485","0.48327097","0.48300594","0.48237428","0.48173475","0.48099634","0.48068604","0.4798049","0.47941685","0.4770194","0.47649354","0.4761148","0.47532126","0.47280967","0.47235212","0.47188717","0.47138602","0.47118145","0.47110114","0.47097498","0.4707948","0.46996674","0.46971205","0.46958372","0.4694224","0.46731344","0.46700504","0.46580684","0.46559817","0.46546057","0.46511024","0.46414965","0.4639983","0.46381736","0.46365154","0.46365148","0.46333405","0.46264312","0.4625376","0.4623867","0.4621596","0.46196574","0.46177623","0.46166566","0.461645","0.46126944","0.46110648","0.4609673","0.46091872"],"string":"[\n \"0.618252\",\n \"0.5965921\",\n \"0.57754785\",\n \"0.5734618\",\n \"0.57143825\",\n \"0.5659548\",\n \"0.5541539\",\n \"0.5518001\",\n \"0.5478379\",\n \"0.5466522\",\n \"0.543087\",\n \"0.53836876\",\n \"0.5375327\",\n \"0.52907383\",\n \"0.52813095\",\n \"0.5275028\",\n \"0.52749276\",\n \"0.52622724\",\n \"0.5237285\",\n \"0.5202462\",\n \"0.5175123\",\n \"0.5173618\",\n \"0.51668274\",\n \"0.5139571\",\n \"0.5131304\",\n \"0.5099078\",\n \"0.5094993\",\n \"0.5065269\",\n \"0.5028155\",\n \"0.5025415\",\n \"0.50192606\",\n \"0.50082844\",\n \"0.4996621\",\n \"0.4996621\",\n \"0.49902168\",\n \"0.49617994\",\n \"0.49574625\",\n \"0.49536955\",\n \"0.49496618\",\n \"0.49474823\",\n \"0.4935896\",\n \"0.4901887\",\n \"0.48997942\",\n \"0.4887643\",\n \"0.48823574\",\n \"0.48753387\",\n \"0.48521185\",\n \"0.48483363\",\n \"0.48480487\",\n \"0.48476347\",\n \"0.4835774\",\n \"0.4833485\",\n \"0.48327097\",\n \"0.48300594\",\n \"0.48237428\",\n \"0.48173475\",\n \"0.48099634\",\n \"0.48068604\",\n \"0.4798049\",\n \"0.47941685\",\n \"0.4770194\",\n \"0.47649354\",\n \"0.4761148\",\n \"0.47532126\",\n \"0.47280967\",\n \"0.47235212\",\n \"0.47188717\",\n \"0.47138602\",\n \"0.47118145\",\n \"0.47110114\",\n \"0.47097498\",\n \"0.4707948\",\n \"0.46996674\",\n \"0.46971205\",\n \"0.46958372\",\n \"0.4694224\",\n \"0.46731344\",\n \"0.46700504\",\n \"0.46580684\",\n \"0.46559817\",\n \"0.46546057\",\n \"0.46511024\",\n \"0.46414965\",\n \"0.4639983\",\n \"0.46381736\",\n \"0.46365154\",\n \"0.46365148\",\n \"0.46333405\",\n \"0.46264312\",\n \"0.4625376\",\n \"0.4623867\",\n \"0.4621596\",\n \"0.46196574\",\n \"0.46177623\",\n \"0.46166566\",\n \"0.461645\",\n \"0.46126944\",\n \"0.46110648\",\n \"0.4609673\",\n \"0.46091872\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.65964955"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":92987,"cells":{"query":{"kind":"string","value":"Generate a .tgz archive from the contents of the web_static."},"document":{"kind":"string","value":"def do_pack():\n\n now = datetime.now()\n # format the name of the file with the timestamps\n now_year = now.year\n now_month = now.month\n now_day = now.day\n now_hour = now.hour\n now_minute = now.minute\n now_second = now.second\n # apply the format\n file_name = 'versions/web_static_{}{}{}{}{}{}.tgz'.format(\n now_year, now_month, now_day, now_hour, now_minute, now_second\n )\n # All archives must be stored in the folder versions\n local('mkdir -p versions')\n # execute locally the compression of the folder\n command = local(\"tar -cvzf \" + file_name + \" ./web_static/\")\n # return the archive path if the archive has been correctly generated\n if command.succeeded:\n return file_name\n else:\n return None"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def do_pack():\n now = datetime.datetime.now()\n path = 'versions/web_static_' +\\\n '{}{}{}{}{}{}'.format(now.year, now.month,\n now.day, now.hour,\n now.minute, now.second) + '.tgz'\n\n local('mkdir -p versions')\n success = local('tar -cvzf {:s} web_static'.format(path), capture=True)\n if success.return_code == 0:\n return path","def do_pack():\n try:\n if isdir('versions') is False:\n local(\"mkdir versions\")\n tgz_file = \"versions/web_static_{}.tgz\".format(\n time.strftime(\"%Y%m%d%H%M%S\"))\n local(\"tar -cvzf {} web_static\".format(tgz_file))\n return tgz_file\n except:\n return None","def do_pack():\n local(\"sudo mkdir -p versions\")\n date_time = datetime.now().strftime(\"%Y%m%d%H%M%S\")\n name_file = \"versions/web_static{}.tgz\".format(date_time)\n local(\"sudo tar -cvzf {} web_static\".format(name_file))\n return name_file","def do_pack():\n\n sd = '{0:%Y%m%d%H%M%S}'.format(datetime.now())\n fname = 'versions/web_static_' + sd + '.tgz'\n local('mkdir -p versions')\n rs = local('tar -cvzf ' + fname + ' web_static')\n\n if rs.succeeded:\n return fname\n return None","def do_pack():\n from os import mkdir, path\n\n filename = \"web_static_{}.tgz\".format(now.strftime(\"%Y%m%d%H%M%S\"))\n filepath = \"versions/{}\".format(filename)\n\n try:\n mkdir('./versions')\n except FileExistsError:\n pass\n\n print(\"Packing web_static to {}\".format(filepath))\n cmd = local('tar -cvzf {} web_static'.format(filepath))\n if (cmd.return_code == 0):\n filesize = path.getsize(filepath)\n print(\"web_static packed: {} -> {}Bytes\".format(filepath, filesize))\n return filepath\n return None","def do_pack():\n date = datetime.datetime.now()\n archive = 'versions/web_static_{}{}{}{}{}{}.tgz'.format(date.year,\n date.month,\n date.day,\n date.hour,\n date.minute,\n date.second)\n local('mkdir -p versions')\n check = local('tar -cvzf {} web_static'.format(archive))\n if check.failed:\n return None\n else:\n return archive","def do_pack():\n a = datetime.now()\n file_name = \"versions/web_static_{}{}{}{}{}{}.tgz\".format(a.year,\n a.month,\n a.day,\n a.hour,\n a.minute,\n a.second)\n try:\n print(\"Packing web_static to \" + file_name)\n local(\"mkdir -p versions\")\n\n local(\"tar -cvzf \" + file_name + \" web_static\")\n return file_name\n except:\n return None","def do_pack():\n time = datetime.utcnow().strftime('%Y%m%d%H%M%S')\n file_name = \"versions/web_static_{}.tgz\".format(time)\n try:\n local(\"mkdir -p ./versions\")\n local(\"tar --create --verbose -z --file={} ./web_static\"\n .format(file_name))\n return file_name\n except:\n return None","def do_pack():\n files = 'versions/web_static_{}{}{}{}{}{}.tgz'\\\n .format(T.year, T.month, T.day, T.hour, T.minute, T.second)\n local('mkdir -p versions')\n execute = local(\"tar -cvzf \" + files + \" ./web_static/\")\n if execute.succeeded:\n return files\n return None","def do_pack():\n try:\n date = datetime.now().strftime(\"%Y%m%d%H%M%S\")\n if isdir(\"versions\") is False:\n local(\"mkdir versions\")\n file_name = \"versions/web_static_{}.tgz\".format(date)\n local(\"tar -cvzf {} web_static\".format(file_name))\n return file_name\n except BaseException:\n return None","def do_pack():\n d = datetime.now()\n local(\"mkdir -p versions\")\n file_name = 'versions/web_static_{}{}{}{}{}{}.tgz\\\n'.format(d.year, d.month, d.day, d.hour, d.minute, d.second)\n status = local(\"tar -cvzf\" + file_name + \" ./web_static/\", capture=True)\n if status.succeeded:\n return file_name\n return None","def do_pack():\n\n now = datetime.now()\n time_now = now.strftime(\"%Y%m%d%H%M%S\")\n archive_name = \"versions/web_static_\" + time_now + \".tgz\"\n local('mkdir -p versions')\n archive_command = local(\"tar -zcvf \" + archive_name + \" web_static\")\n\n if archive_command.succeeded:\n return archive_name\n\n return None","def do_pack():\n a = datetime.now()\n file_name = \"versions/web_static_{}{}{}{}{}{}.tgz\\\n\".format(a.year if a.year > 999 else \"0\" + str(a.year),\n a.month if a.month > 9 else \"0\" + str(a.month),\n a.day if a.day > 9 else \"0\" + str(a.day),\n a.hour if a.hour > 9 else \"0\" + str(a.hour),\n a.minute if a.minute > 9 else \"0\" + str(a.minute),\n a.second if a.second > 9 else \"0\" + str(a.second))\n try:\n print(\"Packing web_static to \" + file_name)\n local(\"mkdir -p versions\")\n\n local(\"tar -cvzf \" + file_name + \" web_static\")\n return file_name\n except:\n return None","def do_pack():\n time = datetime.now()\n file = 'versions/web_static_{}{}{}{}{}{}.tgz'.format(\n time.year,\n time.month,\n time.day,\n time.hour,\n time.minute,\n time.second\n )\n local('mkdir -p versions')\n if local('tar -cvzf ' + file + ' web_static').succeeded:\n return file\n return None","def do_pack():\n try:\n if os.path.isdir(\"versions\") is False:\n os.mkdir(\"versions\")\n time = datetime.datetime.now().strftime(\"%Y%m%d%H%M%S\")\n packed = 'versions/web_static_' + time + '.tgz'\n fabric.api.local(\"tar -cvzf {} web_static\".format(packed))\n return packed\n except:\n return None","def do_pack():\n with api.settings(warn_only=True):\n isdir = os.path.isdir(\"versions\")\n if not isdir:\n mkdir = api.local(\"mkdir versions\")\n if mkdir.failed:\n return None\n sfx = datetime.now().strftime(\"%Y%m%d%M%S\")\n path = \"versions/web_static_{:s}.tgz\".format(sfx)\n tar = api.local(\"tar -cvzf {:s} web_static\".format(path))\n if tar.failed:\n return None\n size = os.stat(path).st_size\n print(\"wb_static packed: {} -> {}Bytes\".format(path, size))\n return path","def do_pack():\n try:\n now = time.strftime(\"%Y%m%d%H%M%S\")\n local('mkdir -p ./versions')\n local('tar -cvzf versions/web_static_{}.tgz web_static'.format(now))\n return(\"versions/web_static_{}.tgz\".format(now))\n except:\n return None","def do_pack():\n date = (datetime.strftime(datetime.now(), \"%Y%m%d%H%M%S\"))\n name = \"versions/web_static_{}.tgz\".format(date)\n\n if not os.path.exists(\"./versions/\"):\n os.makedirs(\"./versions/\")\n try:\n local(\"tar -cvzf {} web_static\".format(name))\n return (name)\n except:\n return (None)","def do_pack():\n makedirs('versions', exist_ok=True)\n date = 'versions/web_static_{}{}{}{}{}{}.tgz'.format(\n time.year, time.month, time.day, time.minute, time.second)\n check = local(\"tar -cvzf \" + date + \" ./web_static/\")\n if check.succeeded:\n return date\n return None","def do_pack():\n time_test = datetime.now().strftime(\"%Y%m%d%H%M%S\")\n file_name = \"versions/web_static_\" + time_test + \".tgz\"\n command1 = \"mkdir -p versions\"\n command2 = \"tar -czvf \" + file_name + \" web_static\"\n local(command1)\n com = local(command2)\n if com.return_code == 0:\n return file_name\n else:\n return None","def do_pack():\n time_f = '%Y%m%d%H%M%S'\n try:\n if not os.path.exists('versions'):\n local('mkdir versions')\n to = 'versions/web_static_{}.tgz'.format(\n datetime.now().strftime(time_f))\n\n local('tar -cvzf {} web_static'.format(to))\n return(to)\n except:\n return (None)","def do_pack():\n with api.settings(warn_only=True):\n isdir = os.path.isdir('versions')\n if not isdir:\n mkdir = api.local('mkdir versions')\n if mkdir.failed:\n return False\n suffix = datetime.now().strftime('%Y%m%d%M%S')\n path = 'versions/web_static_{}.tgz'.format(suffix)\n tar = api.local('tar -cvzf {} web_static'.format(path))\n if tar.failed:\n return False\n size = os.stat(path).st_size\n print('web_static packed: {} -> {}Bytes'.format(path, size))\n return path","def do_pack():\n now = datetime.now().strftime(\"%Y%m%d%H%M%S\")\n local('mkdir -p versions')\n result = local('tar -czvf versions/web_static_{}.tgz web_static'\n .format(now))\n if result.failed:\n return None\n else:\n return result","def do_pack():\n local(\"mkdir -p versions\")\n time = datetime.datetime.now().strftime(\"%Y%m%d%H%M%S\")\n file = local(\"tar -czvf versions/web_static_%s.tgz web_static\" % time)\n if file:\n return \"versions/web_static_{}.tgz\".format(time)\n else:\n return None","def do_pack():\n with settings(warn_only=True):\n res = local(\"mkdir -p versions\")\n date = dt.now()\n pathname = \"versions/web_static_\"\n pathname += str(date.year)\n pathname += str(date.month)\n pathname += str(date.day)\n pathname += str(date.hour)\n pathname += str(date.minute)\n pathname += str(date.second)\n pathname += \".tgz\"\n res2 = local(\"tar -cvzf \" + pathname + \" web_static\")\n if res2.return_code == 0:\n return pathname","def do_pack():\n\n local('mkdir -p versions')\n\n time = datetime.now().strftime(\"%Y%m%d%H%M%S\")\n file_time = 'versions/web_static_{}.tgz'.format(time)\n\n compressed = local(\"tar -cvzf \" + file_time + \" web_static/\")\n\n if compressed.succeeded:\n return file_time\n return None","def do_pack():\n local(\"mkdir -p versions\", capture=True)\n time = datetime.now()\n date = time.strftime(\"%Y%m%d%H%M%S\")\n path = \"versions/web_static_{}.tgz\".format(date)\n if local(\"tar -czvf {} web_static/\".format(path), capture=False):\n return path\n else:\n return None","def do_pack():\n now = datetime.now()\n file_name = \"web_static_{}{}{}{}{}{}.tgz\".format(\n now.year,\n now.month,\n now.day,\n now.hour,\n now.minute,\n now.second\n )\n try:\n local(\"sudo tar -cvzf {} ./web_static\".format(file_name))\n local(\"sudo mkdir -p versions\")\n local(\"sudo mv ./{} versions/\".format(file_name))\n except:\n return (None)\n return (\"versions/{}\".format(file_name))","def do_pack():\n try:\n if not os.path.exists(\"versions\"):\n local(\"mkdir versions\")\n date = datetime.now()\n date = date.strftime(\"%Y%m%d%H%M%S\")\n new_versions = \"versions/web_static_{}.tgz\".format(date)\n local(\"tar -cvzf {} web_static\".format(new_versions))\n return new_versions\n except:\n return None","def do_pack():\n\n local(\"mkdir -p versions\")\n current = dt.now()\n current = current.now()\n tgz = \"web_static_{}.tgz\".format(current.strftime(\"%Y%m%d%H%M%S\"))\n working = local(\"tar -cavf versions/{} web_static\".format(tgz))\n\n if working.failed:\n return None\n else:\n return \"versions/{}\".format(tgz)","def do_pack():\n\n datenow = datetime.now()\n full_date = datenow.strftime(\"%Y%m%d%H%M%S\")\n\n try:\n if not os.path.isdir(\"versions\"):\n local(\"mkdir versions\")\n local_command = local(\"tar -cvzf versions/web_static_{}.tgz web_static\"\n .format(full_date))\n return local_command\n except Exception:\n return None","def create_tar(self):\n with tarfile.open(self.tgzfile, \"w:gz\") as tar_handle:\n for root, _, files in os.walk(self.dirname):\n for file in files:\n tar_handle.add(os.path.join(root, file))","def statics(file, type='img'):\n return bottle.static_file(file, root=HOME+STATIC_PATH+'/'+type)","def static(self, filepath):\n tar = tarfile.open(tarball_path)\n fileobj = tar.extractfile(filepath)\n f, extension = os.path.splitext(filepath)\n if extension == '.css': # It seems CherryPy can't always figure out what mime types are inside tarballs\n cherrypy.response.headers['Content-Type'] = \"text/css\"\n filedata = fileobj.read()\n return filedata","def gen_static(self, output_folder):\n files = []\n for l in self.file_listers:\n files += l()\n for f in files:\n _logger.info(\"generating %s\" % f)\n content = self.get(f)\n loc = os.path.join(output_folder, f)\n d = os.path.dirname(loc)\n if not os.path.exists(d):\n os.makedirs(d)\n with open(loc, \"wb\") as file_:\n file_.write(content)","def gzip_assets():\n run('cd %(repo_path)s; python gzip_assets.py' % env)","def compress_data():\r\n os.chdir(PATH_CSV)\r\n z = zipfile.ZipFile(SITE_NAME + \"_\" + DATE + \"_csv.zip\", \"a\")\r\n z.write(SITE_NAME + \"_\" + DATE + \".csv\")\r\n os.remove(SITE_NAME + \"_\" + DATE + \".csv\")\r\n\r\n os.chdir(PATH_HTML)\r\n z = zipfile.ZipFile(SITE_NAME + \"_\" + DATE + \"_html.zip\", \"a\")\r\n for file in glob.glob(\"*.html\"):\r\n z.write(file)\r\n os.remove(file)","def pack():\n clean_local()\n build()\n copy_json()\n optimize()\n tarball()","def compress_html():\n if not os.path.exists(PATH_HTML):\n os.makedirs(PATH_HTML)\n os.chdir(PATH_HTML)\n try:\n zip_csv = ZipFile(SITE_NAME + '_' + DATE + '_html.zip', 'a')\n for file in glob.glob(\"*\" + DATE + \"*\" + \"html\"):\n zip_csv.write(file)\n os.remove(file)\n log.info(\"Compressing HTML files\")\n except Exception as e:\n log.error('Error when compressing html')\n log.info(type(e).__name__ + str(e))\n os.chdir(PROJECT_PATH)","def deploy_to_s3():\n env.gzip_path = '%(path)s/repository/gzip/assets/' % env\n run(('s3cmd -P --add-header=Content-encoding:gzip --guess-mime-type --rexclude-from=%(path)s/repository/s3exclude sync %(gzip_path)s s3://%(s3_bucket)s/%(project_name)s/') % env)","def static(path):\n return bottle.static_file(path, root='static/')","def static(path):\n return bottle.static_file(path, root='static/')","def static(path):\n return bottle.static_file(path, root='static/')","def static(path):\n return bottle.static_file(path, root='static/')","def _outside_tar(self):\r\n outside_tar = self.unsafe_common_dir / \"unsafe_file.tar.gz\"\r\n with tarfile.open(outside_tar, \"w:gz\") as tar:\r\n tar.addfile(tarfile.TarInfo(str(self.content_dir / \"a_file\")))\r\n\r\n return outside_tar","def index(self):\n\n # 'html/index.html' is the path WITHIN the tarball.\n return self.static('html/index.html')","def static_text_files():\n return send_from_directory(\"static/\", request.path[1:])","def download():\n\n if request.method == 'GET':\n return f\"The URL /download was accessed directly. Try going to '/' to submit the URL first.\"\n if request.method == 'POST':\n # get the URL submited\n form_data = request.form\n url = form_data[\"URL\"]\n quality = int(form_data[\"Quality\"])\n\n # get the information about the website. a list of dictionaries\n # form: {url: , width: , height:}\n images_info = image_scrapper.get_images(url)\n # this will be sent to the html file to be displayed \n\n # generate the directory to save the compressed images\n image_scrapper.gen_directory(static_dir)\n\n # compess and save the images. You can use uncompress to see which ones weren't in a format that could be compressed.\n # the names of the images that are compressed are saved to images_info dict\n uncompressed = image_scrapper.compress_images(images_info, static_dir, quality)\n # note that the images that can't be compressed are named 'x' which was dealt with in the template\n \n # get the names of the images\n dirs = os.listdir(static_dir)\n\n # probably could do some checks here but depends on how you want to implement it.\n return render_template('download.html', \n form_data = form_data,\n image_info = images_info,\n image_names = dirs)","def deploy_static(): \n from fabdeploy.django import collectstatic as django_collectstatic\n# run(\"rm -rf %(root_path)s%(project_name)s/static/*\" % env) # call again git_add_commit_pull\n django_collectstatic()","def compress():\n run_manage_cmd('compress_assets')","def _make_tar_gz_file(output_filename, source_dir):\n with tarfile.open(output_filename, \"w:gz\") as tar:\n for f in os.listdir(source_dir):\n tar.add(os.path.join(source_dir, f), arcname=f)","def write_tarball(args, tarfilename, archivefiles=[]):\n if not archivefiles:\n return None\n \n manifest_filename, manifest_uuid = render_manifest(args, archivefiles)\n try:\n with tarfile.open(tarfilename, f\"{FILE_FLAG}:gz\") as tarball:\n file_count = 0\n for fname in archivefiles:\n LOG.debug(f\"Adding {fname} to {tarfilename}: \")\n if fname.endswith(\".csv\"):\n upload_name = f\"{manifest_uuid}_openshift_usage_report.{file_count}.csv\"\n tarball.add(fname, arcname=upload_name)\n file_count += 1\n tarball.add(manifest_filename, arcname=\"manifest.json\")\n except FileExistsError as exc:\n LOG.critical(exc)\n sys.exit(2)\n LOG.info(f\"Wrote: {tarfilename}\")\n return f\"{tarfilename}\"","def make_static_assets(opts):\n\n css_filename = do_css(opts['css_source_dir'], opts['out_dir'])\n js_filename = do_js(opts['js_source_dir'], opts['out_dir'])\n return {\n 'primary_css': css_filename,\n 'js': js_filename\n }","def do_deploy(archive_path):\n if os.path.isfile('{}'.format(archive_path)) is False:\n return False\n tgz_file = archive_path.split('/')[-1]\n storage_location = '/tmp/'\n new_location = '/data/web_static/releases/'\n upload = put('{}'.format(archive_path), storage_location)\n if upload is False:\n return False\n create_dir = run('mkdir -p {}'.format(new_location +\n tgz_file.replace('.tgz', '')))\n if create_dir is False:\n return False\n uncompress = run('tar -xzvf {} -C {}'.format(storage_location +\n tgz_file, new_location +\n tgz_file.replace('.tgz', '')))\n if uncompress is False:\n return False\n delete_file = run('rm -f {}'.format(storage_location + tgz_file))\n if delete_file is False:\n return False\n new_route = \"{}\".format(new_location + tgz_file.replace('.tgz', ''))\n move_files = run('mv {}/web_static/* {}'.format(new_route, new_route))\n if move_files is False:\n return False\n delete_folder = run('rm -rf {}/web_static'.format(new_route))\n if delete_folder is False:\n return False\n sym_link_name = '/data/web_static/current'\n delete_sym = run('rm -f {}'.format(sym_link_name))\n if delete_sym is False:\n return False\n create_sym = run('ln -sT {} {}'.format(new_location +\n tgz_file.replace('.tgz', ''),\n sym_link_name))\n if create_sym is False:\n return False\n return True","def static(filename):\n return href.static(file=filename)","def _outside_tar2(self):\r\n outside_tar = self.unsafe_common_dir / \"unsafe_file.tar.gz\"\r\n with tarfile.open(outside_tar, \"w:gz\") as tar:\r\n tar.addfile(tarfile.TarInfo(str(self.unsafe_common_dir / \"../a_file\")))\r\n\r\n return outside_tar","def create_zip_file():\n shutil.make_archive(os.path.join(DIST_DIR, \"build\"), \"zip\", BUILD_DIR)","def create_archive(filelist):\n\t\n\n\ttmp = tempfile.NamedTemporaryFile()\n\t# with tempfile.SpooledTemporaryFile() as tmp:\n\twith zipfile.ZipFile(tmp, 'w', zipfile.ZIP_DEFLATED) as archive:\n\t\tarcname = './docs/'\n\t\tfor x in filelist:\n\t\t\tfilename = os.path.basename(x[1])\n\t\t\t_file = x[0]\n\t\t\t# make sure we're at the start...\n\t\t\t_file.seek(0)\n\t\t\tarchive.write(_file.name, arcname=os.path.join(arcname, filename))\n\n\t# Reset file pointer\n\ttmp.seek(0)\n\n\treturn tmp\n\n\t\t# Write file data to response\n\t\t# return HttpResponse(tmp.read(), content_type='application/x-zip-compressed')","def unpack(uri):\n conn = boto.connect_s3(anon=True, host='s3.amazonaws.com')\n bucket = conn.get_bucket('commoncrawl')\n key_ = Key(bucket, uri)\n file_ = warc.WARCFile(fileobj=GzipStreamFile(key_))\n return file_","def create_tarball(fileobj, path, callback=None, compression_level=None):\n tar_cmd = [\"tar\", \"-zc\", \"--directory=%s\" % path, \".\"]\n env = os.environ.copy()\n if compression_level and 1 <= compression_level <= 9:\n env[\"GZIP\"] = \"-%d\" % compression_level\n tar_proc = make_subprocess(tar_cmd, stdout=True, stderr=True, env=env)\n\n try:\n while True:\n chunk = tar_proc.stdout.read(CHUNK_SIZE)\n if chunk == '':\n break\n\n if callback:\n callback(chunk)\n\n if fileobj:\n fileobj.write(chunk)\n except Exception:\n try_kill_process(tar_proc)\n raise\n\n finish_subprocess(tar_proc, tar_cmd)","def download(request):\n \n\n def make_archive(source, destination):\n print(source, destination)\n base = os.path.basename(destination)\n name = base.split('.')[0]\n format = base.split('.')[1]\n archive_from = os.path.dirname(source)\n archive_to = os.path.basename(source.strip(os.sep))\n print(source, destination, archive_from, archive_to)\n shutil.make_archive(name, format, archive_from, archive_to)\n shutil.move('%s.%s' % (name, format), destination)\n\n user_id = request.session['user_id']\n user_root = request.session['user_root']\n search_id = request.session['search_id']\n logger = Logger(user_root,user_id)\n logger.write(\"start compressing images..\")\n t_start_zip=time.time()\n zip_target = os.path.join(user_root, search_id)\n zip_path = os.path.join(user_root, search_id, \"Color_images.zip\")\n make_archive(zip_target, zip_path)\n print(\"finish zip.\")\n zip_file = open(zip_path, '+rb')\n response = HttpResponse(zip_file, content_type='application/zip')\n response[\n 'Content-Disposition'] = 'attachment; filename=%s' % \"dataset.zip\"\n response['Content-Length'] = os.path.getsize(zip_path)\n zip_file.close()\n logger.write(\"compressing images finished (\"+convert_duration_time(time.time(),t_start_zip)+\"s)\")\n\n return response","async def create_tarball(output_path: str) -> bytes:\n file_paths = []\n for root, _, filenames in os.walk(output_path):\n for filename in filenames:\n file_path = os.path.join(root, filename)\n log.info(f'Adding {file_path} to tarball.')\n file_paths.append(file_path)\n\n with ByteStream() as stream:\n with tarfile.TarFile.open(fileobj=stream, mode='w:gz',\n compresslevel=1) as tar:\n for file_path in file_paths:\n tar_info = tar.gettarinfo(name=file_path)\n tar.addfile(tar_info)\n # Yield the header for the tarinfo file.\n yield stream.pop()\n\n with open(file_path, 'rb') as in_fp:\n # Read the input file in chunks of stream.block_size bytes.\n while True:\n data = in_fp.read(stream.block_size)\n if len(data) > 0:\n # Write the data to the buffer.\n tar.fileobj.write(data)\n # Yield a compressed file chunk so the client can receive it.\n yield stream.pop()\n # Write padding if necessary.\n if len(data) < stream.block_size:\n blocks, remainder = divmod(tar_info.size, tarfile.BLOCKSIZE)\n if remainder > 0:\n tar.fileobj.write(tarfile.NUL * (tarfile.BLOCKSIZE - remainder))\n yield stream.pop()\n blocks += 1\n tar.offset += blocks * tarfile.BLOCKSIZE\n break\n\n # Yield end-of-archive marker.\n yield stream.pop()","def make_static(outpath, data, types=(\"inflated\",), recache=False, cmap=\"RdBu_r\",\n template=\"static.html\", layout=None, anonymize=False, overlays_available=None,\n html_embed=True, overlays_visible=('rois', 'sulci'), labels_visible=('rois', ),\n overlay_file=None, copy_ctmfiles=True, title='Brain', **kwargs):\n\n outpath = os.path.abspath(os.path.expanduser(outpath)) # To handle ~ expansion\n if not os.path.exists(outpath):\n os.makedirs(outpath)\n if not os.path.exists(os.path.join(outpath, 'data')):\n # Don't lump together w/ outpath, because of edge cases\n # for which outpath exists but not sub-folder `data`\n os.makedirs(os.path.join(outpath, \"data\"))\n\n data = dataset.normalize(data)\n if not isinstance(data, dataset.Dataset):\n data = dataset.Dataset(data=data)\n\n db.auxfile = data\n\n package = Package(data)\n subjects = list(package.subjects)\n\n ctmargs = dict(method='mg2', level=9, recache=recache, external_svg=overlay_file,\n overlays_available=overlays_available)\n ctms = dict((subj, utils.get_ctmpack(subj, types, **ctmargs))\n for subj in subjects)\n package.reorder(ctms)\n\n db.auxfile = None\n if layout is None:\n layout = [None, (1, 1), (2, 1), (3, 1), (2, 2), (3, 2), (3, 2), (3, 3), (3, 3), (3, 3)][len(subjects)]\n\n ## Rename files to anonymize\n submap = dict()\n for i, (subj, ctmfile) in enumerate(ctms.items()):\n oldpath, fname = os.path.split(ctmfile)\n fname, ext = os.path.splitext(fname)\n if anonymize:\n newfname = \"S%d\"%i\n submap[subj] = newfname\n else:\n newfname = fname\n ctms[subj] = newfname+\".json\"\n\n for ext in ['json', 'ctm', 'svg']:\n srcfile = os.path.join(oldpath, \"%s.%s\"%(fname, ext))\n newfile = os.path.join(outpath, \"%s.%s\"%(newfname, ext))\n if os.path.exists(newfile):\n os.unlink(newfile)\n\n if os.path.exists(srcfile) and copy_ctmfiles:\n shutil.copy2(srcfile, newfile)\n\n if ext == \"json\" and anonymize:\n ## change filenames in json\n nfh = open(newfile)\n jsoncontents = nfh.read()\n nfh.close()\n\n ofh = open(newfile, \"w\")\n ofh.write(jsoncontents.replace(fname, newfname))\n ofh.close()\n if anonymize:\n old_subjects = sorted(list(ctms.keys()))\n ctms = dict(('S%d'%i, ctms[k]) for i, k in enumerate(old_subjects))\n if len(submap) == 0:\n submap = None\n\n #Process the data\n metadata = package.metadata(fmt=\"data/{name}_{frame}.png\", submap=submap)\n images = package.images\n #Write out the PNGs\n for name, imgs in images.items():\n impath = os.path.join(outpath, \"data\", \"{name}_{frame}.png\")\n for i, img in enumerate(imgs):\n with open(impath.format(name=name, frame=i), \"wb\") as binfile:\n binfile.write(img)\n\n #Copy any stimulus files\n stimpath = os.path.join(outpath, \"stim\")\n for name, view in data:\n if 'stim' in view.attrs and os.path.exists(view.attrs['stim']):\n if not os.path.exists(stimpath):\n os.makedirs(stimpath)\n shutil.copy2(view.attrs['stim'], stimpath)\n\n #Parse the html file and paste all the js and css files directly into the html\n from . import htmlembed\n if os.path.exists(template):\n ## Load locally\n templatedir, templatefile = os.path.split(os.path.abspath(template))\n rootdirs = [templatedir, serve.cwd]\n else:\n ## Load system templates\n templatefile = template\n rootdirs = [serve.cwd]\n loader = FallbackLoader(rootdirs)\n tpl = loader.load(templatefile)\n\n # Put together all view options\n my_viewopts = dict(options.config.items('webgl_viewopts'))\n my_viewopts['overlays_visible'] = overlays_visible\n my_viewopts['labels_visible'] = labels_visible\n my_viewopts['brightness'] = options.config.get('curvature', 'brightness')\n my_viewopts['smoothness'] = options.config.get('curvature', 'webgl_smooth')\n my_viewopts['contrast'] = options.config.get('curvature', 'contrast')\n\n for sec in options.config.sections():\n if 'paths' in sec or 'labels' in sec:\n my_viewopts[sec] = dict(options.config.items(sec))\n\n html = tpl.generate(data=json.dumps(metadata),\n colormaps=colormaps,\n default_cmap=cmap,\n python_interface=False,\n leapmotion=True,\n layout=layout,\n subjects=json.dumps(ctms),\n viewopts=json.dumps(my_viewopts),\n title=title,\n **kwargs)\n desthtml = os.path.join(outpath, \"index.html\")\n if html_embed:\n htmlembed.embed(html, desthtml, rootdirs)\n else:\n with open(desthtml, \"w\") as htmlfile:\n htmlfile.write(html)","def wrapped_tarball(export_context, context):\n result = export_result_dict(export_context)\n RESPONSE = context.REQUEST.RESPONSE\n RESPONSE.setHeader('Content-type', 'application/x-gzip')\n RESPONSE.setHeader('Content-disposition',\n 'attachment; filename=%s' % result['filename'])\n return result['tarball']","def package(notes, version):\n print('creating tarball')\n archive_name = '{}.tgz'.format(version.replace('.', '-'))\n run('tar --exclude=\".git\"'\n ' --exclude=\"{}/wp-content/themes/tmp\"'\n ' --exclude=\"{}/wp-content/uploads\" -zcf ../tmp/{} *'\n .format(DOC_ROOT, DOC_ROOT, archive_name))\n os.chdir(previous_dir)\n return archive_name","def deploy():\n\n project_dir = '/home/gastosabertos/gastos_abertos_website'\n with cd(project_dir):\n local('tar -cvzf build.tar.gz build')\n run('cp -r build build-old')\n put('build.tar.gz', '.')\n run('tar -xvf build.tar.gz')","def mk_license_tarball(work_dir, license_dir):\n #print 'license_dir=%s' % license_dir\n \n # create tar file\n tar_file = tarfile.open(work_dir + '/pentaho-licenses.tar.gz', 'w:gz')\n\n # list all lic files\n files = glob.glob(license_dir + '/*.lic')\n for f in files:\n tar_file.add(f, arcname=os.path.basename(f))\n \n tar_file.close()\n return tar_file.name","def npmfile_containing(file_contents: Sequence[Tuple[str, str]]):\n with tempfile.NamedTemporaryFile(suffix='.tgz') as temp_file:\n with tarfile.open(fileobj=temp_file, mode='w:gz') as tar_file:\n for file_name, contents in file_contents:\n # NPM package contents live in the package/ directory.\n info = tarfile.TarInfo(name=f'package/{file_name}')\n info.size = len(contents)\n tar_file.addfile(\n tarinfo=info, fileobj=io.BytesIO(contents.encode('utf-8'))\n )\n temp_file.flush()\n yield temp_file","def do_deploy(archive_path):\n if path.exists(archive_path):\n\n # File name without .tgz\n file_ext = archive_path.split('/')[1]\n file_alone = file_ext.split(\".\")[0]\n curr_release = \"/data/web_static/releases/\" + file_alone + '/'\n\n result = True\n\n # Deploy compressed file to the server /tmp/ directory\n upload = put(archive_path, \"/tmp/\")\n if upload.failed:\n result = False\n\n # Make dir to store the release\n dir_release = run(\"sudo mkdir -p \" + curr_release)\n if dir_release.failed:\n result = False\n\n # Uncompress file inside the folder created\n uncompress = run(\"sudo tar -xzf \" + \"/tmp/\\\n\" + file_ext + \" -C \" + curr_release)\n if uncompress.failed:\n result = False\n\n # Move all files from web_static to folder release\n move_info = run(\"sudo mv \" + curr_release + \"\\\nweb_static/* \" + curr_release)\n if move_info.failed:\n result = False\n\n # Remove empty web_static directory\n rm_empty = run(\"sudo rm -rf \" + curr_release + \"\\\nweb_static/\")\n if rm_empty.failed:\n result = False\n\n # Remove symbolic link current\n rm_link = run(\"sudo rm -rf /data/\\\nweb_static/current\")\n if rm_link.failed:\n result = False\n\n # Make new symbolic link\n new_link = run(\"sudo ln -s \" + curr_release + \" /data/\\\nweb_static/current\")\n if new_link.failed:\n result = False\n\n return result\n else:\n return False","def compress(roles='webapp_servers'):\n if _current_host_has_role(roles):\n print(\"=== COMPRESSING STATIC MEDIA ===\")\n with cd(env.REMOTE_CODEBASE_PATH):\n run(\"workon %s && ./manage.py compress --force\" % env.REMOTE_VIRTUALENV_NAME)","def _create_manifest(self, templates_dir, static_dir):\n return \"\"\"\n graft %(templates_dir)s\n graft %(static_dir)s\n\n include COPYING\n include INSTALL\n include README.md\n include *-requirements.txt\n\n global-exclude .*.sw[op] *.py[co] __pycache__ .DS_Store .noseids\n \"\"\" % {\n 'templates_dir': templates_dir,\n 'static_dir': static_dir,\n }","def create_assets():\n assets = {}\n\n # Load all static files\n for root, dirs, files in os.walk(STATIC_DIR):\n for fname in files:\n filename = os.path.join(root, fname)\n with open(filename, \"rb\") as f:\n assets[os.path.relpath(filename, STATIC_DIR)] = f.read()\n\n # Collect pages\n pages = {}\n for fname in os.listdir(PAGES_DIR):\n if fname.lower().endswith(\".md\"):\n name = fname.split(\".\")[0].lower()\n with open(os.path.join(PAGES_DIR, fname), \"rb\") as f:\n md = f.read().decode()\n pages[name] = Page(name, md)\n\n # todo: Collect blog posts\n\n # Get template\n with open(os.path.join(THIS_DIR, \"template.html\"), \"rb\") as f:\n html_template = f.read().decode()\n\n with open(os.path.join(THIS_DIR, \"style.css\"), \"rb\") as f:\n css = f.read().decode()\n css += \"/* Pygments CSS */\\n\" + HtmlFormatter(style=\"vs\").get_style_defs(\n \".highlight\"\n )\n\n # Generate pages\n year = datetime.now().year\n for page in pages.values():\n page.prepare(pages.keys())\n title = TITLE if page.name == \"index\" else TITLE + \" - \" + page.name\n menu = create_menu(page)\n html = html_template.format(\n title=title, style=css, body=page.to_html(), menu=menu, year=year\n )\n print(\"generating\", page.name + \".html\")\n assets[page.name + \".html\"] = html.encode()\n\n # Fix backslashes on Windows\n for key in list(assets.keys()):\n if \"\\\\\" in key:\n assets[key.replace(\"\\\\\", \"/\")] = assets.pop(key)\n\n return assets","def tarball(request):\n\n patches = (models.Patch\n .query(models.Patch.patchset_key == request.patchset.key)\n .order(models.Patch.filename)\n .fetch(1000))\n\n temp = tempfile.TemporaryFile()\n tar = tarfile.open(mode=\"w|bz2\", fileobj=temp)\n\n def add_entry(prefix, content):\n data = content.data\n if data is None:\n data = content.text\n if isinstance(data, unicode):\n data = data.encode(\"utf-8\", \"replace\")\n if data is None:\n return\n info = tarfile.TarInfo(prefix + patch.filename)\n info.size = len(data)\n # TODO(adonovan): set SYMTYPE/0755 when Rietveld supports symlinks.\n info.type = tarfile.REGTYPE\n info.mode = 0644\n # datetime->time_t\n delta = request.patchset.modified - datetime.datetime(1970, 1, 1)\n info.mtime = int(delta.days * 86400 + delta.seconds)\n tar.addfile(info, fileobj=StringIO(data))\n\n for patch in patches:\n if not patch.no_base_file:\n try:\n add_entry('a/', patch.get_content()) # before\n except FetchError: # I/O problem?\n logging.exception('tarball: patch(%s, %s).get_content failed' %\n (patch.key.id(), patch.filename))\n try:\n add_entry('b/', patch.get_patched_content()) # after\n except FetchError: # file deletion? I/O problem?\n logging.exception('tarball: patch(%s, %s).get_patched_content failed' %\n (patch.key.id(), patch.filename))\n\n tar.close()\n temp.flush()\n\n wrapper = FileWrapper(temp)\n response = HttpResponse(wrapper, mimetype='application/x-gtar')\n response['Content-Disposition'] = (\n 'attachment; filename=patch%s_%s.tar.bz2' % (request.issue.key.id(),\n request.patchset.key.id()))\n response['Content-Length'] = temp.tell()\n temp.seek(0)\n return response","def extract_web_archive(url, apath, ffilter=[]):\n\n download(url, apath)\n output_files = extract(apath, ffilter=ffilter)\n\n return output_files","def zipped_tarball(this_tmp_dir):\n tgz_name = \"%s.tar.gz\" % this_tmp_dir\n\n tar = tarfile.open(tgz_name, \"w:gz\")\n\n tar.add(this_tmp_dir)\n\n tar.close()\n\n return tgz_name","def convert_to_web(base_path, files):\n for i, f in enumerate(files):\n imagetype = get_imagetype_from_filename(f)\n cmd = ('rsync '\n '{base_path}/qc/phantom/{imagetype}/{f} '\n '{base_path}/website/assets/{output}'.format(\n base_path=base_path, imagetype=imagetype, \n f=f, output=f[9:]))\n os.system(cmd)","def zip_html(self):\n zip_fname = os.path.join(BUILD_PATH, \"html\", \"pandas.zip\")\n if os.path.exists(zip_fname):\n os.remove(zip_fname)\n dirname = os.path.join(BUILD_PATH, \"html\")\n fnames = os.listdir(dirname)\n os.chdir(dirname)\n self._run_os(\"zip\", zip_fname, \"-r\", \"-q\", *fnames)","def zip_html(self):\n zip_fname = os.path.join(BUILD_PATH, \"html\", \"pandas.zip\")\n if os.path.exists(zip_fname):\n os.remove(zip_fname)\n dirname = os.path.join(BUILD_PATH, \"html\")\n fnames = os.listdir(dirname)\n os.chdir(dirname)\n self._run_os(\"zip\", zip_fname, \"-r\", \"-q\", *fnames)","def tar(self, out=sys.stdout, config=None, *args, **kw):\r\n if config is not None:\r\n config = self.manifest.config_schema.validate(config)\r\n if self.manifest.get(\"templates\"):\r\n templates_dir = self.copy(templates=True)\r\n for template in self.find(templates=True):\r\n EJSTemplate(templates_dir + template).apply(templates_dir + template, config)\r\n tar = tarfile.open(\"\", mode=\"w|\", fileobj=out)\r\n templates = self.manifest.get(\"templates\")\r\n for path in self.find(*args, **kw):\r\n if config and path in templates:\r\n real_path = templates_dir + path\r\n EJSTemplate(real_path).apply(real_path, config)\r\n else:\r\n real_path = self.unchroot_path(path)\r\n tar.add(real_path, path, recursive=False)\r\n tar.close()","def server_static(filename):\n return static_file(filename, root='static/stats')","def extract_web_archive(cls, url, apath, ffilter=[]):\n\n if apath not in cls._archives.keys():\n download(url, apath)\n\n _files = extract(apath, ffilter=ffilter)\n\n return _files","def gz_tar(full_prefix):\n tarfile = os.path.join(outputdir, full_prefix + '.tar')\n try:\n with open(tarfile, 'rb') as f_in, gzip.open(tarfile + '.gz', 'wb') as f_out:\n shutil.copyfileobj(f_in, f_out)\n os.remove(tarfile)\n except Exception as e:\n log.error(\"Tarfile {0} was not generated. Module(s) run collected no info?\".format(tarfile))\n log.error(e)\n\n return tarfile + '.gz'","def generate_static_site(self, output_root=None, extra_context=None):\n self.app.config['BUILD_PATH'] = output_root\n\n # use this hook for registering URLs to freeze\n self.call_hook(\"generate\", self, output_root, extra_context)\n\n if output_root is not None:\n # realpath or this gets generated relative to the tarbell package\n self.app.config['FREEZER_DESTINATION'] = os.path.realpath(output_root)\n\n self.freezer.freeze()","def _download_from_web(*, ds_name: str, ds_path: Path):\n import cgi\n import zipfile\n import httpx\n from tqdm import tqdm\n\n url = DATASET_OPTIONS[ds_name]['web']\n if ds_path.exists():\n print('Dataset directory already exists; remove it if you wish to '\n 're-download the dataset')\n return\n\n ds_path.mkdir(parents=True, exist_ok=True)\n\n with httpx.Client() as client:\n with client.stream('GET', url=url) as response:\n if not response.is_error:\n pass # All good!\n else:\n raise RuntimeError(\n f'Error {response.status_code} when trying '\n f'to download {url}')\n\n\n header = response.headers['content-disposition']\n _, params = cgi.parse_header(header)\n # where to store the archive\n outfile = ds_path / params['filename']\n remote_file_size = int(response.headers['content-length'])\n\n with open(outfile, mode='wb') as f:\n with tqdm(desc=params['filename'], initial=0,\n total=remote_file_size, unit='B',\n unit_scale=True, unit_divisor=1024,\n leave=False) as progress:\n num_bytes_downloaded = response.num_bytes_downloaded\n\n for chunk in response.iter_bytes():\n f.write(chunk)\n progress.update(response.num_bytes_downloaded -\n num_bytes_downloaded)\n num_bytes_downloaded = (response\n .num_bytes_downloaded)\n\n assert outfile.suffix == '.zip'\n\n with zipfile.ZipFile(outfile) as zip:\n for zip_info in zip.infolist():\n path_in_zip = Path(zip_info.filename)\n # omit top-level directory from Zip archive\n target_path = str(Path(*path_in_zip.parts[1:]))\n if str(target_path) in ('.', '..'):\n continue\n if zip_info.filename.endswith('/'):\n (ds_path / target_path).mkdir(parents=True, exist_ok=True)\n continue\n zip_info.filename = target_path\n print(f'Extracting: {target_path}')\n zip.extract(zip_info, ds_path)\n\n outfile.unlink()","def server_static(filepath):\n return bottle.static_file(filepath, root=STATIC_ROOT)","def tarball(request):\n\n patches = (models.Patch\n .query(ancestor=request.patchset.key)\n .order(models.Patch.filename)\n .fetch(1000))\n\n temp = tempfile.TemporaryFile()\n tar = tarfile.open(mode=\"w|bz2\", fileobj=temp)\n\n def add_entry(prefix, content, patch):\n data = content.data\n if data is None:\n data = content.text\n if isinstance(data, unicode):\n data = data.encode(\"utf-8\", \"replace\")\n if data is None:\n return\n info = tarfile.TarInfo(prefix + patch.filename)\n info.size = len(data)\n # TODO(adonovan): set SYMTYPE/0755 when Rietveld supports symlinks.\n info.type = tarfile.REGTYPE\n info.mode = 0644\n # datetime->time_t\n delta = request.patchset.modified - datetime.datetime(1970, 1, 1)\n info.mtime = int(delta.days * 86400 + delta.seconds)\n tar.addfile(info, fileobj=StringIO(data))\n\n for patch in patches:\n if not patch.no_base_file:\n try:\n add_entry('a/', patch.get_content(), patch) # before\n except FetchError: # I/O problem?\n logging.exception('tarball: patch(%s, %s).get_content failed' %\n (patch.key.id(), patch.filename))\n try:\n add_entry('b/', patch.get_patched_content(), patch) # after\n except FetchError: # file deletion? I/O problem?\n logging.exception('tarball: patch(%s, %s).get_patched_content failed' %\n (patch.key.id(), patch.filename))\n\n tar.close()\n temp.flush()\n\n wrapper = FileWrapper(temp)\n response = HttpResponse(wrapper, mimetype='application/x-gtar')\n response['Content-Disposition'] = (\n 'attachment; filename=patch%s_%s.tar.bz2' % (request.issue.key.id(),\n request.patchset.key.id()))\n response['Content-Length'] = temp.tell()\n temp.seek(0)\n return response","def download_and_expand_tgz(url):\n with TemporaryDirectory(prefix=\"cot_helper\") as directory:\n logger.debug(\"Temporary directory is %s\", directory)\n logger.verbose(\"Downloading and extracting %s\", url)\n response = requests.get(url, stream=True)\n tgz = os.path.join(directory, 'helper.tgz')\n with open(tgz, 'wb') as fileobj:\n shutil.copyfileobj(response.raw, fileobj)\n del response\n logger.debug(\"Extracting %s\", tgz)\n with tarfile.open(tgz, \"r:gz\") as tarf:\n tarf.extractall(path=directory)\n try:\n yield directory\n finally:\n logger.debug(\"Cleaning up temporary directory %s\", directory)","def _download_untar(self, dep):\n tar = sh.Command(\"tar\")\n download_url = self.dependency_dict[dep][\"tarball\"]\n dlname = download_url.split(\"/\")[-1]\n download_path = Path(\".\") / dlname\n logger.debug(f\"downloading {dep} at {download_url} to {dlname}\")\n if self.quiet:\n trackers = ()\n else:\n trackers = (ProgressTracker(DataTransferBar()),)\n request_download(download_url, download_path, trackers=trackers)\n logger.debug(\n f\"downloaded file {download_path}, size\"\n f\" {download_path.stat().st_size}\"\n )\n try:\n tar(\"xvf\", download_path, **self.output_kwargs)\n except:\n logger.error(f\"untar of {download_path} failed\")\n sys.exit(1)","def main():\n # Create / clean output dir\n if os.path.isdir(OUT_DIR):\n shutil.rmtree(OUT_DIR)\n os.mkdir(OUT_DIR)\n\n # Write all assets to the directory\n for fname, bb in create_assets().items():\n filename = os.path.join(OUT_DIR, fname)\n dirname = os.path.dirname(filename)\n if not os.path.isdir(dirname):\n os.makedirs(dirname)\n with open(filename, \"wb\") as f:\n f.write(bb)","def download_archive(self):\n\n def time_convert(structure):\n \"\"\"\n :param structure: tuple representation of time\n :return: GitHub archive time\n \"\"\"\n \n \n join_number_to_zero = lambda number: (\"\" if number > 9 else \"0\") + str(number)\n\n return \"%s-%s-%s-%s\" % (\n structure.tm_year, join_number_to_zero(structure.tm_mon), join_number_to_zero(structure.tm_mday),\n structure.tm_hour)\n\n current_time = self.get_time()\n self.logger.debug(__name__ + \": \" + \"current time: \" + str(gmtime(current_time)))\n\n difference = -25200\n #timezone difference in seconds between GMT and west coast of USA\n\n downloading_time = int(timegm(self.config[\"last_connection_time\"])) + 3600\n self.logger.debug(__name__ + \": \" + \"downloading time: \" + str(gmtime(downloading_time)))\n\n if downloading_time > current_time - 7200:\n self.logger.info(__name__ + \": \" + \"unable to download file (time limiting).\")\n return\n\n downloading_time += difference\n\n json_file_name = self.download_file(time_convert(gmtime(downloading_time)))\n\n self.config[\"last_connection_time\"] = gmtime(downloading_time - difference)\n self.logger.debug(__name__ + \": \" + \"last_connection_time: \" + str(self.config[\"last_connection_time\"]))\n\n return json_file_name","def write_to_gzip(fname, html_body):\n dir_path = os.path.dirname(fname)\n ensure_dir_exists(dir_path)\n\n with gzip.open(fname, 'wb') as html_file:\n html_file.write(html_body)","def make_zip_file(self, post_content):\n file_path, file_url = self.save_file(post_content['shortcode'] + '.zip', self.make_empty_zip())\n with ZipFile(file_path, 'w') as zipf:\n if post_content['igtv'] is True:\n zipf.writestr('igtv_link.txt', post_content['urls'][0][2])\n else:\n for url in post_content['urls']:\n zipf.writestr(self.get_content_name(url[2]), requests.get(url[2]).content)\n\n if 'text' in post_content:\n zipf.writestr('caption.txt', post_content['text'])\n return file_url","def server_static (filename):\n return static_file(filename, root=\"./static\")","def copy_static(self, outdir):\n pass","def archive(mongo_backup_file):\r\n filename = get_archive_filename()\r\n tar = tarfile.open(filename, \"w|gz\")\r\n tar.add(mongo_backup_file)\r\n tar.close()\r\n\r\n return filename","def restricted_download():\n aaa.require(fail_redirect='/login')\n return bottle.static_file('static_file', root='.')","def generate(self):\n xml = self.template()\n fp = BytesIO()\n gzip = GzipFile(self.filename, \"wb\", 9, fp)\n if isinstance(xml, str):\n xml = xml.encode(\"utf8\")\n gzip.write(xml)\n gzip.close()\n data = fp.getvalue()\n fp.close()\n return data","async def download_directory_as_archive(\n request: web.Request,\n file_path: Path,\n zip_filename: str = None,\n) -> web.StreamResponse:\n\n def _iter2aiter(iter):\n \"\"\"Iterable to async iterable\"\"\"\n\n def _consume(loop, iter, q):\n for item in iter:\n q.put(item)\n q.put(SENTINEL)\n\n async def _aiter():\n loop = asyncio.get_running_loop()\n q = janus.Queue(maxsize=DEFAULT_INFLIGHT_CHUNKS)\n try:\n fut = loop.run_in_executor(None, lambda: _consume(loop, iter, q.sync_q))\n while True:\n item = await q.async_q.get()\n if item is SENTINEL:\n break\n yield item\n q.async_q.task_done()\n await fut\n finally:\n q.close()\n await q.wait_closed()\n\n return _aiter()\n\n if zip_filename is None:\n zip_filename = file_path.name + \".zip\"\n zf = zipstream.ZipFile(compression=zipstream.ZIP_DEFLATED)\n async for root, dirs, files in _iter2aiter(os.walk(file_path)):\n for file in files:\n zf.write(Path(root) / file, Path(root).relative_to(file_path) / file)\n if len(dirs) == 0 and len(files) == 0:\n # Include an empty directory in the archive as well.\n zf.write(root, Path(root).relative_to(file_path))\n ascii_filename = (\n zip_filename.encode(\"ascii\", errors=\"ignore\")\n .decode(\"ascii\")\n .replace('\"', r\"\\\"\")\n )\n encoded_filename = urllib.parse.quote(zip_filename, encoding=\"utf-8\")\n response = web.StreamResponse(\n headers={\n hdrs.CONTENT_TYPE: \"application/zip\",\n hdrs.CONTENT_DISPOSITION: \" \".join(\n [\n \"attachment;\" f'filename=\"{ascii_filename}\";', # RFC-2616 sec2.2\n f\"filename*=UTF-8''{encoded_filename}\", # RFC-5987\n ]\n ),\n }\n )\n await response.prepare(request)\n async for chunk in _iter2aiter(zf):\n await response.write(chunk)\n return response","def make_tar(self, package, input_dir, build_dir, add_args=None):\n tar = self.options.tar_command\n\n # Generate the .tar.gz file\n filename = package + '.tar.gz'\n out_file = open(os.path.join(build_dir, filename), \"w\")\n args = [tar, '--format=gnu', '--exclude-vcs', '-C', build_dir]\n if self.config.get('tar', {}).get('ignore', []):\n for patt in self.config['tar']['ignore']:\n args += ['--exclude', patt]\n if add_args:\n args += add_args\n args += ['-c', input_dir]\n logging.debug(\"Creating %s\", filename)\n tar_proc = subprocess.Popen(args, stdout=subprocess.PIPE)\n gzip_proc = subprocess.Popen(['gzip', '-9'], stdin=tar_proc.stdout,\n stdout=out_file)\n\n if tar_proc.wait() != 0 or gzip_proc.wait() != 0:\n logging.error(\"tar/gzip failed, exiting\")\n sys.exit(1)\n out_file.close()\n logging.info('%s written', filename)\n return filename","def setup_output_path(self):\n self.logger.info('setting up output path')\n try:\n self.output_path.mkdir()\n except FileExistsError:\n pass\n try:\n (self.output_path / 'simple').mkdir()\n except FileExistsError:\n pass\n for filename in resource_listdir(__name__, 'static'):\n if filename == 'index.html':\n # Skip template\n continue\n with (self.output_path / filename).open('wb') as f:\n source = resource_stream(__name__, 'static/' + filename)\n f.write(source.read())\n source.close()"],"string":"[\n \"def do_pack():\\n now = datetime.datetime.now()\\n path = 'versions/web_static_' +\\\\\\n '{}{}{}{}{}{}'.format(now.year, now.month,\\n now.day, now.hour,\\n now.minute, now.second) + '.tgz'\\n\\n local('mkdir -p versions')\\n success = local('tar -cvzf {:s} web_static'.format(path), capture=True)\\n if success.return_code == 0:\\n return path\",\n \"def do_pack():\\n try:\\n if isdir('versions') is False:\\n local(\\\"mkdir versions\\\")\\n tgz_file = \\\"versions/web_static_{}.tgz\\\".format(\\n time.strftime(\\\"%Y%m%d%H%M%S\\\"))\\n local(\\\"tar -cvzf {} web_static\\\".format(tgz_file))\\n return tgz_file\\n except:\\n return None\",\n \"def do_pack():\\n local(\\\"sudo mkdir -p versions\\\")\\n date_time = datetime.now().strftime(\\\"%Y%m%d%H%M%S\\\")\\n name_file = \\\"versions/web_static{}.tgz\\\".format(date_time)\\n local(\\\"sudo tar -cvzf {} web_static\\\".format(name_file))\\n return name_file\",\n \"def do_pack():\\n\\n sd = '{0:%Y%m%d%H%M%S}'.format(datetime.now())\\n fname = 'versions/web_static_' + sd + '.tgz'\\n local('mkdir -p versions')\\n rs = local('tar -cvzf ' + fname + ' web_static')\\n\\n if rs.succeeded:\\n return fname\\n return None\",\n \"def do_pack():\\n from os import mkdir, path\\n\\n filename = \\\"web_static_{}.tgz\\\".format(now.strftime(\\\"%Y%m%d%H%M%S\\\"))\\n filepath = \\\"versions/{}\\\".format(filename)\\n\\n try:\\n mkdir('./versions')\\n except FileExistsError:\\n pass\\n\\n print(\\\"Packing web_static to {}\\\".format(filepath))\\n cmd = local('tar -cvzf {} web_static'.format(filepath))\\n if (cmd.return_code == 0):\\n filesize = path.getsize(filepath)\\n print(\\\"web_static packed: {} -> {}Bytes\\\".format(filepath, filesize))\\n return filepath\\n return None\",\n \"def do_pack():\\n date = datetime.datetime.now()\\n archive = 'versions/web_static_{}{}{}{}{}{}.tgz'.format(date.year,\\n date.month,\\n date.day,\\n date.hour,\\n date.minute,\\n date.second)\\n local('mkdir -p versions')\\n check = local('tar -cvzf {} web_static'.format(archive))\\n if check.failed:\\n return None\\n else:\\n return archive\",\n \"def do_pack():\\n a = datetime.now()\\n file_name = \\\"versions/web_static_{}{}{}{}{}{}.tgz\\\".format(a.year,\\n a.month,\\n a.day,\\n a.hour,\\n a.minute,\\n a.second)\\n try:\\n print(\\\"Packing web_static to \\\" + file_name)\\n local(\\\"mkdir -p versions\\\")\\n\\n local(\\\"tar -cvzf \\\" + file_name + \\\" web_static\\\")\\n return file_name\\n except:\\n return None\",\n \"def do_pack():\\n time = datetime.utcnow().strftime('%Y%m%d%H%M%S')\\n file_name = \\\"versions/web_static_{}.tgz\\\".format(time)\\n try:\\n local(\\\"mkdir -p ./versions\\\")\\n local(\\\"tar --create --verbose -z --file={} ./web_static\\\"\\n .format(file_name))\\n return file_name\\n except:\\n return None\",\n \"def do_pack():\\n files = 'versions/web_static_{}{}{}{}{}{}.tgz'\\\\\\n .format(T.year, T.month, T.day, T.hour, T.minute, T.second)\\n local('mkdir -p versions')\\n execute = local(\\\"tar -cvzf \\\" + files + \\\" ./web_static/\\\")\\n if execute.succeeded:\\n return files\\n return None\",\n \"def do_pack():\\n try:\\n date = datetime.now().strftime(\\\"%Y%m%d%H%M%S\\\")\\n if isdir(\\\"versions\\\") is False:\\n local(\\\"mkdir versions\\\")\\n file_name = \\\"versions/web_static_{}.tgz\\\".format(date)\\n local(\\\"tar -cvzf {} web_static\\\".format(file_name))\\n return file_name\\n except BaseException:\\n return None\",\n \"def do_pack():\\n d = datetime.now()\\n local(\\\"mkdir -p versions\\\")\\n file_name = 'versions/web_static_{}{}{}{}{}{}.tgz\\\\\\n'.format(d.year, d.month, d.day, d.hour, d.minute, d.second)\\n status = local(\\\"tar -cvzf\\\" + file_name + \\\" ./web_static/\\\", capture=True)\\n if status.succeeded:\\n return file_name\\n return None\",\n \"def do_pack():\\n\\n now = datetime.now()\\n time_now = now.strftime(\\\"%Y%m%d%H%M%S\\\")\\n archive_name = \\\"versions/web_static_\\\" + time_now + \\\".tgz\\\"\\n local('mkdir -p versions')\\n archive_command = local(\\\"tar -zcvf \\\" + archive_name + \\\" web_static\\\")\\n\\n if archive_command.succeeded:\\n return archive_name\\n\\n return None\",\n \"def do_pack():\\n a = datetime.now()\\n file_name = \\\"versions/web_static_{}{}{}{}{}{}.tgz\\\\\\n\\\".format(a.year if a.year > 999 else \\\"0\\\" + str(a.year),\\n a.month if a.month > 9 else \\\"0\\\" + str(a.month),\\n a.day if a.day > 9 else \\\"0\\\" + str(a.day),\\n a.hour if a.hour > 9 else \\\"0\\\" + str(a.hour),\\n a.minute if a.minute > 9 else \\\"0\\\" + str(a.minute),\\n a.second if a.second > 9 else \\\"0\\\" + str(a.second))\\n try:\\n print(\\\"Packing web_static to \\\" + file_name)\\n local(\\\"mkdir -p versions\\\")\\n\\n local(\\\"tar -cvzf \\\" + file_name + \\\" web_static\\\")\\n return file_name\\n except:\\n return None\",\n \"def do_pack():\\n time = datetime.now()\\n file = 'versions/web_static_{}{}{}{}{}{}.tgz'.format(\\n time.year,\\n time.month,\\n time.day,\\n time.hour,\\n time.minute,\\n time.second\\n )\\n local('mkdir -p versions')\\n if local('tar -cvzf ' + file + ' web_static').succeeded:\\n return file\\n return None\",\n \"def do_pack():\\n try:\\n if os.path.isdir(\\\"versions\\\") is False:\\n os.mkdir(\\\"versions\\\")\\n time = datetime.datetime.now().strftime(\\\"%Y%m%d%H%M%S\\\")\\n packed = 'versions/web_static_' + time + '.tgz'\\n fabric.api.local(\\\"tar -cvzf {} web_static\\\".format(packed))\\n return packed\\n except:\\n return None\",\n \"def do_pack():\\n with api.settings(warn_only=True):\\n isdir = os.path.isdir(\\\"versions\\\")\\n if not isdir:\\n mkdir = api.local(\\\"mkdir versions\\\")\\n if mkdir.failed:\\n return None\\n sfx = datetime.now().strftime(\\\"%Y%m%d%M%S\\\")\\n path = \\\"versions/web_static_{:s}.tgz\\\".format(sfx)\\n tar = api.local(\\\"tar -cvzf {:s} web_static\\\".format(path))\\n if tar.failed:\\n return None\\n size = os.stat(path).st_size\\n print(\\\"wb_static packed: {} -> {}Bytes\\\".format(path, size))\\n return path\",\n \"def do_pack():\\n try:\\n now = time.strftime(\\\"%Y%m%d%H%M%S\\\")\\n local('mkdir -p ./versions')\\n local('tar -cvzf versions/web_static_{}.tgz web_static'.format(now))\\n return(\\\"versions/web_static_{}.tgz\\\".format(now))\\n except:\\n return None\",\n \"def do_pack():\\n date = (datetime.strftime(datetime.now(), \\\"%Y%m%d%H%M%S\\\"))\\n name = \\\"versions/web_static_{}.tgz\\\".format(date)\\n\\n if not os.path.exists(\\\"./versions/\\\"):\\n os.makedirs(\\\"./versions/\\\")\\n try:\\n local(\\\"tar -cvzf {} web_static\\\".format(name))\\n return (name)\\n except:\\n return (None)\",\n \"def do_pack():\\n makedirs('versions', exist_ok=True)\\n date = 'versions/web_static_{}{}{}{}{}{}.tgz'.format(\\n time.year, time.month, time.day, time.minute, time.second)\\n check = local(\\\"tar -cvzf \\\" + date + \\\" ./web_static/\\\")\\n if check.succeeded:\\n return date\\n return None\",\n \"def do_pack():\\n time_test = datetime.now().strftime(\\\"%Y%m%d%H%M%S\\\")\\n file_name = \\\"versions/web_static_\\\" + time_test + \\\".tgz\\\"\\n command1 = \\\"mkdir -p versions\\\"\\n command2 = \\\"tar -czvf \\\" + file_name + \\\" web_static\\\"\\n local(command1)\\n com = local(command2)\\n if com.return_code == 0:\\n return file_name\\n else:\\n return None\",\n \"def do_pack():\\n time_f = '%Y%m%d%H%M%S'\\n try:\\n if not os.path.exists('versions'):\\n local('mkdir versions')\\n to = 'versions/web_static_{}.tgz'.format(\\n datetime.now().strftime(time_f))\\n\\n local('tar -cvzf {} web_static'.format(to))\\n return(to)\\n except:\\n return (None)\",\n \"def do_pack():\\n with api.settings(warn_only=True):\\n isdir = os.path.isdir('versions')\\n if not isdir:\\n mkdir = api.local('mkdir versions')\\n if mkdir.failed:\\n return False\\n suffix = datetime.now().strftime('%Y%m%d%M%S')\\n path = 'versions/web_static_{}.tgz'.format(suffix)\\n tar = api.local('tar -cvzf {} web_static'.format(path))\\n if tar.failed:\\n return False\\n size = os.stat(path).st_size\\n print('web_static packed: {} -> {}Bytes'.format(path, size))\\n return path\",\n \"def do_pack():\\n now = datetime.now().strftime(\\\"%Y%m%d%H%M%S\\\")\\n local('mkdir -p versions')\\n result = local('tar -czvf versions/web_static_{}.tgz web_static'\\n .format(now))\\n if result.failed:\\n return None\\n else:\\n return result\",\n \"def do_pack():\\n local(\\\"mkdir -p versions\\\")\\n time = datetime.datetime.now().strftime(\\\"%Y%m%d%H%M%S\\\")\\n file = local(\\\"tar -czvf versions/web_static_%s.tgz web_static\\\" % time)\\n if file:\\n return \\\"versions/web_static_{}.tgz\\\".format(time)\\n else:\\n return None\",\n \"def do_pack():\\n with settings(warn_only=True):\\n res = local(\\\"mkdir -p versions\\\")\\n date = dt.now()\\n pathname = \\\"versions/web_static_\\\"\\n pathname += str(date.year)\\n pathname += str(date.month)\\n pathname += str(date.day)\\n pathname += str(date.hour)\\n pathname += str(date.minute)\\n pathname += str(date.second)\\n pathname += \\\".tgz\\\"\\n res2 = local(\\\"tar -cvzf \\\" + pathname + \\\" web_static\\\")\\n if res2.return_code == 0:\\n return pathname\",\n \"def do_pack():\\n\\n local('mkdir -p versions')\\n\\n time = datetime.now().strftime(\\\"%Y%m%d%H%M%S\\\")\\n file_time = 'versions/web_static_{}.tgz'.format(time)\\n\\n compressed = local(\\\"tar -cvzf \\\" + file_time + \\\" web_static/\\\")\\n\\n if compressed.succeeded:\\n return file_time\\n return None\",\n \"def do_pack():\\n local(\\\"mkdir -p versions\\\", capture=True)\\n time = datetime.now()\\n date = time.strftime(\\\"%Y%m%d%H%M%S\\\")\\n path = \\\"versions/web_static_{}.tgz\\\".format(date)\\n if local(\\\"tar -czvf {} web_static/\\\".format(path), capture=False):\\n return path\\n else:\\n return None\",\n \"def do_pack():\\n now = datetime.now()\\n file_name = \\\"web_static_{}{}{}{}{}{}.tgz\\\".format(\\n now.year,\\n now.month,\\n now.day,\\n now.hour,\\n now.minute,\\n now.second\\n )\\n try:\\n local(\\\"sudo tar -cvzf {} ./web_static\\\".format(file_name))\\n local(\\\"sudo mkdir -p versions\\\")\\n local(\\\"sudo mv ./{} versions/\\\".format(file_name))\\n except:\\n return (None)\\n return (\\\"versions/{}\\\".format(file_name))\",\n \"def do_pack():\\n try:\\n if not os.path.exists(\\\"versions\\\"):\\n local(\\\"mkdir versions\\\")\\n date = datetime.now()\\n date = date.strftime(\\\"%Y%m%d%H%M%S\\\")\\n new_versions = \\\"versions/web_static_{}.tgz\\\".format(date)\\n local(\\\"tar -cvzf {} web_static\\\".format(new_versions))\\n return new_versions\\n except:\\n return None\",\n \"def do_pack():\\n\\n local(\\\"mkdir -p versions\\\")\\n current = dt.now()\\n current = current.now()\\n tgz = \\\"web_static_{}.tgz\\\".format(current.strftime(\\\"%Y%m%d%H%M%S\\\"))\\n working = local(\\\"tar -cavf versions/{} web_static\\\".format(tgz))\\n\\n if working.failed:\\n return None\\n else:\\n return \\\"versions/{}\\\".format(tgz)\",\n \"def do_pack():\\n\\n datenow = datetime.now()\\n full_date = datenow.strftime(\\\"%Y%m%d%H%M%S\\\")\\n\\n try:\\n if not os.path.isdir(\\\"versions\\\"):\\n local(\\\"mkdir versions\\\")\\n local_command = local(\\\"tar -cvzf versions/web_static_{}.tgz web_static\\\"\\n .format(full_date))\\n return local_command\\n except Exception:\\n return None\",\n \"def create_tar(self):\\n with tarfile.open(self.tgzfile, \\\"w:gz\\\") as tar_handle:\\n for root, _, files in os.walk(self.dirname):\\n for file in files:\\n tar_handle.add(os.path.join(root, file))\",\n \"def statics(file, type='img'):\\n return bottle.static_file(file, root=HOME+STATIC_PATH+'/'+type)\",\n \"def static(self, filepath):\\n tar = tarfile.open(tarball_path)\\n fileobj = tar.extractfile(filepath)\\n f, extension = os.path.splitext(filepath)\\n if extension == '.css': # It seems CherryPy can't always figure out what mime types are inside tarballs\\n cherrypy.response.headers['Content-Type'] = \\\"text/css\\\"\\n filedata = fileobj.read()\\n return filedata\",\n \"def gen_static(self, output_folder):\\n files = []\\n for l in self.file_listers:\\n files += l()\\n for f in files:\\n _logger.info(\\\"generating %s\\\" % f)\\n content = self.get(f)\\n loc = os.path.join(output_folder, f)\\n d = os.path.dirname(loc)\\n if not os.path.exists(d):\\n os.makedirs(d)\\n with open(loc, \\\"wb\\\") as file_:\\n file_.write(content)\",\n \"def gzip_assets():\\n run('cd %(repo_path)s; python gzip_assets.py' % env)\",\n \"def compress_data():\\r\\n os.chdir(PATH_CSV)\\r\\n z = zipfile.ZipFile(SITE_NAME + \\\"_\\\" + DATE + \\\"_csv.zip\\\", \\\"a\\\")\\r\\n z.write(SITE_NAME + \\\"_\\\" + DATE + \\\".csv\\\")\\r\\n os.remove(SITE_NAME + \\\"_\\\" + DATE + \\\".csv\\\")\\r\\n\\r\\n os.chdir(PATH_HTML)\\r\\n z = zipfile.ZipFile(SITE_NAME + \\\"_\\\" + DATE + \\\"_html.zip\\\", \\\"a\\\")\\r\\n for file in glob.glob(\\\"*.html\\\"):\\r\\n z.write(file)\\r\\n os.remove(file)\",\n \"def pack():\\n clean_local()\\n build()\\n copy_json()\\n optimize()\\n tarball()\",\n \"def compress_html():\\n if not os.path.exists(PATH_HTML):\\n os.makedirs(PATH_HTML)\\n os.chdir(PATH_HTML)\\n try:\\n zip_csv = ZipFile(SITE_NAME + '_' + DATE + '_html.zip', 'a')\\n for file in glob.glob(\\\"*\\\" + DATE + \\\"*\\\" + \\\"html\\\"):\\n zip_csv.write(file)\\n os.remove(file)\\n log.info(\\\"Compressing HTML files\\\")\\n except Exception as e:\\n log.error('Error when compressing html')\\n log.info(type(e).__name__ + str(e))\\n os.chdir(PROJECT_PATH)\",\n \"def deploy_to_s3():\\n env.gzip_path = '%(path)s/repository/gzip/assets/' % env\\n run(('s3cmd -P --add-header=Content-encoding:gzip --guess-mime-type --rexclude-from=%(path)s/repository/s3exclude sync %(gzip_path)s s3://%(s3_bucket)s/%(project_name)s/') % env)\",\n \"def static(path):\\n return bottle.static_file(path, root='static/')\",\n \"def static(path):\\n return bottle.static_file(path, root='static/')\",\n \"def static(path):\\n return bottle.static_file(path, root='static/')\",\n \"def static(path):\\n return bottle.static_file(path, root='static/')\",\n \"def _outside_tar(self):\\r\\n outside_tar = self.unsafe_common_dir / \\\"unsafe_file.tar.gz\\\"\\r\\n with tarfile.open(outside_tar, \\\"w:gz\\\") as tar:\\r\\n tar.addfile(tarfile.TarInfo(str(self.content_dir / \\\"a_file\\\")))\\r\\n\\r\\n return outside_tar\",\n \"def index(self):\\n\\n # 'html/index.html' is the path WITHIN the tarball.\\n return self.static('html/index.html')\",\n \"def static_text_files():\\n return send_from_directory(\\\"static/\\\", request.path[1:])\",\n \"def download():\\n\\n if request.method == 'GET':\\n return f\\\"The URL /download was accessed directly. Try going to '/' to submit the URL first.\\\"\\n if request.method == 'POST':\\n # get the URL submited\\n form_data = request.form\\n url = form_data[\\\"URL\\\"]\\n quality = int(form_data[\\\"Quality\\\"])\\n\\n # get the information about the website. a list of dictionaries\\n # form: {url: , width: , height:}\\n images_info = image_scrapper.get_images(url)\\n # this will be sent to the html file to be displayed \\n\\n # generate the directory to save the compressed images\\n image_scrapper.gen_directory(static_dir)\\n\\n # compess and save the images. You can use uncompress to see which ones weren't in a format that could be compressed.\\n # the names of the images that are compressed are saved to images_info dict\\n uncompressed = image_scrapper.compress_images(images_info, static_dir, quality)\\n # note that the images that can't be compressed are named 'x' which was dealt with in the template\\n \\n # get the names of the images\\n dirs = os.listdir(static_dir)\\n\\n # probably could do some checks here but depends on how you want to implement it.\\n return render_template('download.html', \\n form_data = form_data,\\n image_info = images_info,\\n image_names = dirs)\",\n \"def deploy_static(): \\n from fabdeploy.django import collectstatic as django_collectstatic\\n# run(\\\"rm -rf %(root_path)s%(project_name)s/static/*\\\" % env) # call again git_add_commit_pull\\n django_collectstatic()\",\n \"def compress():\\n run_manage_cmd('compress_assets')\",\n \"def _make_tar_gz_file(output_filename, source_dir):\\n with tarfile.open(output_filename, \\\"w:gz\\\") as tar:\\n for f in os.listdir(source_dir):\\n tar.add(os.path.join(source_dir, f), arcname=f)\",\n \"def write_tarball(args, tarfilename, archivefiles=[]):\\n if not archivefiles:\\n return None\\n \\n manifest_filename, manifest_uuid = render_manifest(args, archivefiles)\\n try:\\n with tarfile.open(tarfilename, f\\\"{FILE_FLAG}:gz\\\") as tarball:\\n file_count = 0\\n for fname in archivefiles:\\n LOG.debug(f\\\"Adding {fname} to {tarfilename}: \\\")\\n if fname.endswith(\\\".csv\\\"):\\n upload_name = f\\\"{manifest_uuid}_openshift_usage_report.{file_count}.csv\\\"\\n tarball.add(fname, arcname=upload_name)\\n file_count += 1\\n tarball.add(manifest_filename, arcname=\\\"manifest.json\\\")\\n except FileExistsError as exc:\\n LOG.critical(exc)\\n sys.exit(2)\\n LOG.info(f\\\"Wrote: {tarfilename}\\\")\\n return f\\\"{tarfilename}\\\"\",\n \"def make_static_assets(opts):\\n\\n css_filename = do_css(opts['css_source_dir'], opts['out_dir'])\\n js_filename = do_js(opts['js_source_dir'], opts['out_dir'])\\n return {\\n 'primary_css': css_filename,\\n 'js': js_filename\\n }\",\n \"def do_deploy(archive_path):\\n if os.path.isfile('{}'.format(archive_path)) is False:\\n return False\\n tgz_file = archive_path.split('/')[-1]\\n storage_location = '/tmp/'\\n new_location = '/data/web_static/releases/'\\n upload = put('{}'.format(archive_path), storage_location)\\n if upload is False:\\n return False\\n create_dir = run('mkdir -p {}'.format(new_location +\\n tgz_file.replace('.tgz', '')))\\n if create_dir is False:\\n return False\\n uncompress = run('tar -xzvf {} -C {}'.format(storage_location +\\n tgz_file, new_location +\\n tgz_file.replace('.tgz', '')))\\n if uncompress is False:\\n return False\\n delete_file = run('rm -f {}'.format(storage_location + tgz_file))\\n if delete_file is False:\\n return False\\n new_route = \\\"{}\\\".format(new_location + tgz_file.replace('.tgz', ''))\\n move_files = run('mv {}/web_static/* {}'.format(new_route, new_route))\\n if move_files is False:\\n return False\\n delete_folder = run('rm -rf {}/web_static'.format(new_route))\\n if delete_folder is False:\\n return False\\n sym_link_name = '/data/web_static/current'\\n delete_sym = run('rm -f {}'.format(sym_link_name))\\n if delete_sym is False:\\n return False\\n create_sym = run('ln -sT {} {}'.format(new_location +\\n tgz_file.replace('.tgz', ''),\\n sym_link_name))\\n if create_sym is False:\\n return False\\n return True\",\n \"def static(filename):\\n return href.static(file=filename)\",\n \"def _outside_tar2(self):\\r\\n outside_tar = self.unsafe_common_dir / \\\"unsafe_file.tar.gz\\\"\\r\\n with tarfile.open(outside_tar, \\\"w:gz\\\") as tar:\\r\\n tar.addfile(tarfile.TarInfo(str(self.unsafe_common_dir / \\\"../a_file\\\")))\\r\\n\\r\\n return outside_tar\",\n \"def create_zip_file():\\n shutil.make_archive(os.path.join(DIST_DIR, \\\"build\\\"), \\\"zip\\\", BUILD_DIR)\",\n \"def create_archive(filelist):\\n\\t\\n\\n\\ttmp = tempfile.NamedTemporaryFile()\\n\\t# with tempfile.SpooledTemporaryFile() as tmp:\\n\\twith zipfile.ZipFile(tmp, 'w', zipfile.ZIP_DEFLATED) as archive:\\n\\t\\tarcname = './docs/'\\n\\t\\tfor x in filelist:\\n\\t\\t\\tfilename = os.path.basename(x[1])\\n\\t\\t\\t_file = x[0]\\n\\t\\t\\t# make sure we're at the start...\\n\\t\\t\\t_file.seek(0)\\n\\t\\t\\tarchive.write(_file.name, arcname=os.path.join(arcname, filename))\\n\\n\\t# Reset file pointer\\n\\ttmp.seek(0)\\n\\n\\treturn tmp\\n\\n\\t\\t# Write file data to response\\n\\t\\t# return HttpResponse(tmp.read(), content_type='application/x-zip-compressed')\",\n \"def unpack(uri):\\n conn = boto.connect_s3(anon=True, host='s3.amazonaws.com')\\n bucket = conn.get_bucket('commoncrawl')\\n key_ = Key(bucket, uri)\\n file_ = warc.WARCFile(fileobj=GzipStreamFile(key_))\\n return file_\",\n \"def create_tarball(fileobj, path, callback=None, compression_level=None):\\n tar_cmd = [\\\"tar\\\", \\\"-zc\\\", \\\"--directory=%s\\\" % path, \\\".\\\"]\\n env = os.environ.copy()\\n if compression_level and 1 <= compression_level <= 9:\\n env[\\\"GZIP\\\"] = \\\"-%d\\\" % compression_level\\n tar_proc = make_subprocess(tar_cmd, stdout=True, stderr=True, env=env)\\n\\n try:\\n while True:\\n chunk = tar_proc.stdout.read(CHUNK_SIZE)\\n if chunk == '':\\n break\\n\\n if callback:\\n callback(chunk)\\n\\n if fileobj:\\n fileobj.write(chunk)\\n except Exception:\\n try_kill_process(tar_proc)\\n raise\\n\\n finish_subprocess(tar_proc, tar_cmd)\",\n \"def download(request):\\n \\n\\n def make_archive(source, destination):\\n print(source, destination)\\n base = os.path.basename(destination)\\n name = base.split('.')[0]\\n format = base.split('.')[1]\\n archive_from = os.path.dirname(source)\\n archive_to = os.path.basename(source.strip(os.sep))\\n print(source, destination, archive_from, archive_to)\\n shutil.make_archive(name, format, archive_from, archive_to)\\n shutil.move('%s.%s' % (name, format), destination)\\n\\n user_id = request.session['user_id']\\n user_root = request.session['user_root']\\n search_id = request.session['search_id']\\n logger = Logger(user_root,user_id)\\n logger.write(\\\"start compressing images..\\\")\\n t_start_zip=time.time()\\n zip_target = os.path.join(user_root, search_id)\\n zip_path = os.path.join(user_root, search_id, \\\"Color_images.zip\\\")\\n make_archive(zip_target, zip_path)\\n print(\\\"finish zip.\\\")\\n zip_file = open(zip_path, '+rb')\\n response = HttpResponse(zip_file, content_type='application/zip')\\n response[\\n 'Content-Disposition'] = 'attachment; filename=%s' % \\\"dataset.zip\\\"\\n response['Content-Length'] = os.path.getsize(zip_path)\\n zip_file.close()\\n logger.write(\\\"compressing images finished (\\\"+convert_duration_time(time.time(),t_start_zip)+\\\"s)\\\")\\n\\n return response\",\n \"async def create_tarball(output_path: str) -> bytes:\\n file_paths = []\\n for root, _, filenames in os.walk(output_path):\\n for filename in filenames:\\n file_path = os.path.join(root, filename)\\n log.info(f'Adding {file_path} to tarball.')\\n file_paths.append(file_path)\\n\\n with ByteStream() as stream:\\n with tarfile.TarFile.open(fileobj=stream, mode='w:gz',\\n compresslevel=1) as tar:\\n for file_path in file_paths:\\n tar_info = tar.gettarinfo(name=file_path)\\n tar.addfile(tar_info)\\n # Yield the header for the tarinfo file.\\n yield stream.pop()\\n\\n with open(file_path, 'rb') as in_fp:\\n # Read the input file in chunks of stream.block_size bytes.\\n while True:\\n data = in_fp.read(stream.block_size)\\n if len(data) > 0:\\n # Write the data to the buffer.\\n tar.fileobj.write(data)\\n # Yield a compressed file chunk so the client can receive it.\\n yield stream.pop()\\n # Write padding if necessary.\\n if len(data) < stream.block_size:\\n blocks, remainder = divmod(tar_info.size, tarfile.BLOCKSIZE)\\n if remainder > 0:\\n tar.fileobj.write(tarfile.NUL * (tarfile.BLOCKSIZE - remainder))\\n yield stream.pop()\\n blocks += 1\\n tar.offset += blocks * tarfile.BLOCKSIZE\\n break\\n\\n # Yield end-of-archive marker.\\n yield stream.pop()\",\n \"def make_static(outpath, data, types=(\\\"inflated\\\",), recache=False, cmap=\\\"RdBu_r\\\",\\n template=\\\"static.html\\\", layout=None, anonymize=False, overlays_available=None,\\n html_embed=True, overlays_visible=('rois', 'sulci'), labels_visible=('rois', ),\\n overlay_file=None, copy_ctmfiles=True, title='Brain', **kwargs):\\n\\n outpath = os.path.abspath(os.path.expanduser(outpath)) # To handle ~ expansion\\n if not os.path.exists(outpath):\\n os.makedirs(outpath)\\n if not os.path.exists(os.path.join(outpath, 'data')):\\n # Don't lump together w/ outpath, because of edge cases\\n # for which outpath exists but not sub-folder `data`\\n os.makedirs(os.path.join(outpath, \\\"data\\\"))\\n\\n data = dataset.normalize(data)\\n if not isinstance(data, dataset.Dataset):\\n data = dataset.Dataset(data=data)\\n\\n db.auxfile = data\\n\\n package = Package(data)\\n subjects = list(package.subjects)\\n\\n ctmargs = dict(method='mg2', level=9, recache=recache, external_svg=overlay_file,\\n overlays_available=overlays_available)\\n ctms = dict((subj, utils.get_ctmpack(subj, types, **ctmargs))\\n for subj in subjects)\\n package.reorder(ctms)\\n\\n db.auxfile = None\\n if layout is None:\\n layout = [None, (1, 1), (2, 1), (3, 1), (2, 2), (3, 2), (3, 2), (3, 3), (3, 3), (3, 3)][len(subjects)]\\n\\n ## Rename files to anonymize\\n submap = dict()\\n for i, (subj, ctmfile) in enumerate(ctms.items()):\\n oldpath, fname = os.path.split(ctmfile)\\n fname, ext = os.path.splitext(fname)\\n if anonymize:\\n newfname = \\\"S%d\\\"%i\\n submap[subj] = newfname\\n else:\\n newfname = fname\\n ctms[subj] = newfname+\\\".json\\\"\\n\\n for ext in ['json', 'ctm', 'svg']:\\n srcfile = os.path.join(oldpath, \\\"%s.%s\\\"%(fname, ext))\\n newfile = os.path.join(outpath, \\\"%s.%s\\\"%(newfname, ext))\\n if os.path.exists(newfile):\\n os.unlink(newfile)\\n\\n if os.path.exists(srcfile) and copy_ctmfiles:\\n shutil.copy2(srcfile, newfile)\\n\\n if ext == \\\"json\\\" and anonymize:\\n ## change filenames in json\\n nfh = open(newfile)\\n jsoncontents = nfh.read()\\n nfh.close()\\n\\n ofh = open(newfile, \\\"w\\\")\\n ofh.write(jsoncontents.replace(fname, newfname))\\n ofh.close()\\n if anonymize:\\n old_subjects = sorted(list(ctms.keys()))\\n ctms = dict(('S%d'%i, ctms[k]) for i, k in enumerate(old_subjects))\\n if len(submap) == 0:\\n submap = None\\n\\n #Process the data\\n metadata = package.metadata(fmt=\\\"data/{name}_{frame}.png\\\", submap=submap)\\n images = package.images\\n #Write out the PNGs\\n for name, imgs in images.items():\\n impath = os.path.join(outpath, \\\"data\\\", \\\"{name}_{frame}.png\\\")\\n for i, img in enumerate(imgs):\\n with open(impath.format(name=name, frame=i), \\\"wb\\\") as binfile:\\n binfile.write(img)\\n\\n #Copy any stimulus files\\n stimpath = os.path.join(outpath, \\\"stim\\\")\\n for name, view in data:\\n if 'stim' in view.attrs and os.path.exists(view.attrs['stim']):\\n if not os.path.exists(stimpath):\\n os.makedirs(stimpath)\\n shutil.copy2(view.attrs['stim'], stimpath)\\n\\n #Parse the html file and paste all the js and css files directly into the html\\n from . import htmlembed\\n if os.path.exists(template):\\n ## Load locally\\n templatedir, templatefile = os.path.split(os.path.abspath(template))\\n rootdirs = [templatedir, serve.cwd]\\n else:\\n ## Load system templates\\n templatefile = template\\n rootdirs = [serve.cwd]\\n loader = FallbackLoader(rootdirs)\\n tpl = loader.load(templatefile)\\n\\n # Put together all view options\\n my_viewopts = dict(options.config.items('webgl_viewopts'))\\n my_viewopts['overlays_visible'] = overlays_visible\\n my_viewopts['labels_visible'] = labels_visible\\n my_viewopts['brightness'] = options.config.get('curvature', 'brightness')\\n my_viewopts['smoothness'] = options.config.get('curvature', 'webgl_smooth')\\n my_viewopts['contrast'] = options.config.get('curvature', 'contrast')\\n\\n for sec in options.config.sections():\\n if 'paths' in sec or 'labels' in sec:\\n my_viewopts[sec] = dict(options.config.items(sec))\\n\\n html = tpl.generate(data=json.dumps(metadata),\\n colormaps=colormaps,\\n default_cmap=cmap,\\n python_interface=False,\\n leapmotion=True,\\n layout=layout,\\n subjects=json.dumps(ctms),\\n viewopts=json.dumps(my_viewopts),\\n title=title,\\n **kwargs)\\n desthtml = os.path.join(outpath, \\\"index.html\\\")\\n if html_embed:\\n htmlembed.embed(html, desthtml, rootdirs)\\n else:\\n with open(desthtml, \\\"w\\\") as htmlfile:\\n htmlfile.write(html)\",\n \"def wrapped_tarball(export_context, context):\\n result = export_result_dict(export_context)\\n RESPONSE = context.REQUEST.RESPONSE\\n RESPONSE.setHeader('Content-type', 'application/x-gzip')\\n RESPONSE.setHeader('Content-disposition',\\n 'attachment; filename=%s' % result['filename'])\\n return result['tarball']\",\n \"def package(notes, version):\\n print('creating tarball')\\n archive_name = '{}.tgz'.format(version.replace('.', '-'))\\n run('tar --exclude=\\\".git\\\"'\\n ' --exclude=\\\"{}/wp-content/themes/tmp\\\"'\\n ' --exclude=\\\"{}/wp-content/uploads\\\" -zcf ../tmp/{} *'\\n .format(DOC_ROOT, DOC_ROOT, archive_name))\\n os.chdir(previous_dir)\\n return archive_name\",\n \"def deploy():\\n\\n project_dir = '/home/gastosabertos/gastos_abertos_website'\\n with cd(project_dir):\\n local('tar -cvzf build.tar.gz build')\\n run('cp -r build build-old')\\n put('build.tar.gz', '.')\\n run('tar -xvf build.tar.gz')\",\n \"def mk_license_tarball(work_dir, license_dir):\\n #print 'license_dir=%s' % license_dir\\n \\n # create tar file\\n tar_file = tarfile.open(work_dir + '/pentaho-licenses.tar.gz', 'w:gz')\\n\\n # list all lic files\\n files = glob.glob(license_dir + '/*.lic')\\n for f in files:\\n tar_file.add(f, arcname=os.path.basename(f))\\n \\n tar_file.close()\\n return tar_file.name\",\n \"def npmfile_containing(file_contents: Sequence[Tuple[str, str]]):\\n with tempfile.NamedTemporaryFile(suffix='.tgz') as temp_file:\\n with tarfile.open(fileobj=temp_file, mode='w:gz') as tar_file:\\n for file_name, contents in file_contents:\\n # NPM package contents live in the package/ directory.\\n info = tarfile.TarInfo(name=f'package/{file_name}')\\n info.size = len(contents)\\n tar_file.addfile(\\n tarinfo=info, fileobj=io.BytesIO(contents.encode('utf-8'))\\n )\\n temp_file.flush()\\n yield temp_file\",\n \"def do_deploy(archive_path):\\n if path.exists(archive_path):\\n\\n # File name without .tgz\\n file_ext = archive_path.split('/')[1]\\n file_alone = file_ext.split(\\\".\\\")[0]\\n curr_release = \\\"/data/web_static/releases/\\\" + file_alone + '/'\\n\\n result = True\\n\\n # Deploy compressed file to the server /tmp/ directory\\n upload = put(archive_path, \\\"/tmp/\\\")\\n if upload.failed:\\n result = False\\n\\n # Make dir to store the release\\n dir_release = run(\\\"sudo mkdir -p \\\" + curr_release)\\n if dir_release.failed:\\n result = False\\n\\n # Uncompress file inside the folder created\\n uncompress = run(\\\"sudo tar -xzf \\\" + \\\"/tmp/\\\\\\n\\\" + file_ext + \\\" -C \\\" + curr_release)\\n if uncompress.failed:\\n result = False\\n\\n # Move all files from web_static to folder release\\n move_info = run(\\\"sudo mv \\\" + curr_release + \\\"\\\\\\nweb_static/* \\\" + curr_release)\\n if move_info.failed:\\n result = False\\n\\n # Remove empty web_static directory\\n rm_empty = run(\\\"sudo rm -rf \\\" + curr_release + \\\"\\\\\\nweb_static/\\\")\\n if rm_empty.failed:\\n result = False\\n\\n # Remove symbolic link current\\n rm_link = run(\\\"sudo rm -rf /data/\\\\\\nweb_static/current\\\")\\n if rm_link.failed:\\n result = False\\n\\n # Make new symbolic link\\n new_link = run(\\\"sudo ln -s \\\" + curr_release + \\\" /data/\\\\\\nweb_static/current\\\")\\n if new_link.failed:\\n result = False\\n\\n return result\\n else:\\n return False\",\n \"def compress(roles='webapp_servers'):\\n if _current_host_has_role(roles):\\n print(\\\"=== COMPRESSING STATIC MEDIA ===\\\")\\n with cd(env.REMOTE_CODEBASE_PATH):\\n run(\\\"workon %s && ./manage.py compress --force\\\" % env.REMOTE_VIRTUALENV_NAME)\",\n \"def _create_manifest(self, templates_dir, static_dir):\\n return \\\"\\\"\\\"\\n graft %(templates_dir)s\\n graft %(static_dir)s\\n\\n include COPYING\\n include INSTALL\\n include README.md\\n include *-requirements.txt\\n\\n global-exclude .*.sw[op] *.py[co] __pycache__ .DS_Store .noseids\\n \\\"\\\"\\\" % {\\n 'templates_dir': templates_dir,\\n 'static_dir': static_dir,\\n }\",\n \"def create_assets():\\n assets = {}\\n\\n # Load all static files\\n for root, dirs, files in os.walk(STATIC_DIR):\\n for fname in files:\\n filename = os.path.join(root, fname)\\n with open(filename, \\\"rb\\\") as f:\\n assets[os.path.relpath(filename, STATIC_DIR)] = f.read()\\n\\n # Collect pages\\n pages = {}\\n for fname in os.listdir(PAGES_DIR):\\n if fname.lower().endswith(\\\".md\\\"):\\n name = fname.split(\\\".\\\")[0].lower()\\n with open(os.path.join(PAGES_DIR, fname), \\\"rb\\\") as f:\\n md = f.read().decode()\\n pages[name] = Page(name, md)\\n\\n # todo: Collect blog posts\\n\\n # Get template\\n with open(os.path.join(THIS_DIR, \\\"template.html\\\"), \\\"rb\\\") as f:\\n html_template = f.read().decode()\\n\\n with open(os.path.join(THIS_DIR, \\\"style.css\\\"), \\\"rb\\\") as f:\\n css = f.read().decode()\\n css += \\\"/* Pygments CSS */\\\\n\\\" + HtmlFormatter(style=\\\"vs\\\").get_style_defs(\\n \\\".highlight\\\"\\n )\\n\\n # Generate pages\\n year = datetime.now().year\\n for page in pages.values():\\n page.prepare(pages.keys())\\n title = TITLE if page.name == \\\"index\\\" else TITLE + \\\" - \\\" + page.name\\n menu = create_menu(page)\\n html = html_template.format(\\n title=title, style=css, body=page.to_html(), menu=menu, year=year\\n )\\n print(\\\"generating\\\", page.name + \\\".html\\\")\\n assets[page.name + \\\".html\\\"] = html.encode()\\n\\n # Fix backslashes on Windows\\n for key in list(assets.keys()):\\n if \\\"\\\\\\\\\\\" in key:\\n assets[key.replace(\\\"\\\\\\\\\\\", \\\"/\\\")] = assets.pop(key)\\n\\n return assets\",\n \"def tarball(request):\\n\\n patches = (models.Patch\\n .query(models.Patch.patchset_key == request.patchset.key)\\n .order(models.Patch.filename)\\n .fetch(1000))\\n\\n temp = tempfile.TemporaryFile()\\n tar = tarfile.open(mode=\\\"w|bz2\\\", fileobj=temp)\\n\\n def add_entry(prefix, content):\\n data = content.data\\n if data is None:\\n data = content.text\\n if isinstance(data, unicode):\\n data = data.encode(\\\"utf-8\\\", \\\"replace\\\")\\n if data is None:\\n return\\n info = tarfile.TarInfo(prefix + patch.filename)\\n info.size = len(data)\\n # TODO(adonovan): set SYMTYPE/0755 when Rietveld supports symlinks.\\n info.type = tarfile.REGTYPE\\n info.mode = 0644\\n # datetime->time_t\\n delta = request.patchset.modified - datetime.datetime(1970, 1, 1)\\n info.mtime = int(delta.days * 86400 + delta.seconds)\\n tar.addfile(info, fileobj=StringIO(data))\\n\\n for patch in patches:\\n if not patch.no_base_file:\\n try:\\n add_entry('a/', patch.get_content()) # before\\n except FetchError: # I/O problem?\\n logging.exception('tarball: patch(%s, %s).get_content failed' %\\n (patch.key.id(), patch.filename))\\n try:\\n add_entry('b/', patch.get_patched_content()) # after\\n except FetchError: # file deletion? I/O problem?\\n logging.exception('tarball: patch(%s, %s).get_patched_content failed' %\\n (patch.key.id(), patch.filename))\\n\\n tar.close()\\n temp.flush()\\n\\n wrapper = FileWrapper(temp)\\n response = HttpResponse(wrapper, mimetype='application/x-gtar')\\n response['Content-Disposition'] = (\\n 'attachment; filename=patch%s_%s.tar.bz2' % (request.issue.key.id(),\\n request.patchset.key.id()))\\n response['Content-Length'] = temp.tell()\\n temp.seek(0)\\n return response\",\n \"def extract_web_archive(url, apath, ffilter=[]):\\n\\n download(url, apath)\\n output_files = extract(apath, ffilter=ffilter)\\n\\n return output_files\",\n \"def zipped_tarball(this_tmp_dir):\\n tgz_name = \\\"%s.tar.gz\\\" % this_tmp_dir\\n\\n tar = tarfile.open(tgz_name, \\\"w:gz\\\")\\n\\n tar.add(this_tmp_dir)\\n\\n tar.close()\\n\\n return tgz_name\",\n \"def convert_to_web(base_path, files):\\n for i, f in enumerate(files):\\n imagetype = get_imagetype_from_filename(f)\\n cmd = ('rsync '\\n '{base_path}/qc/phantom/{imagetype}/{f} '\\n '{base_path}/website/assets/{output}'.format(\\n base_path=base_path, imagetype=imagetype, \\n f=f, output=f[9:]))\\n os.system(cmd)\",\n \"def zip_html(self):\\n zip_fname = os.path.join(BUILD_PATH, \\\"html\\\", \\\"pandas.zip\\\")\\n if os.path.exists(zip_fname):\\n os.remove(zip_fname)\\n dirname = os.path.join(BUILD_PATH, \\\"html\\\")\\n fnames = os.listdir(dirname)\\n os.chdir(dirname)\\n self._run_os(\\\"zip\\\", zip_fname, \\\"-r\\\", \\\"-q\\\", *fnames)\",\n \"def zip_html(self):\\n zip_fname = os.path.join(BUILD_PATH, \\\"html\\\", \\\"pandas.zip\\\")\\n if os.path.exists(zip_fname):\\n os.remove(zip_fname)\\n dirname = os.path.join(BUILD_PATH, \\\"html\\\")\\n fnames = os.listdir(dirname)\\n os.chdir(dirname)\\n self._run_os(\\\"zip\\\", zip_fname, \\\"-r\\\", \\\"-q\\\", *fnames)\",\n \"def tar(self, out=sys.stdout, config=None, *args, **kw):\\r\\n if config is not None:\\r\\n config = self.manifest.config_schema.validate(config)\\r\\n if self.manifest.get(\\\"templates\\\"):\\r\\n templates_dir = self.copy(templates=True)\\r\\n for template in self.find(templates=True):\\r\\n EJSTemplate(templates_dir + template).apply(templates_dir + template, config)\\r\\n tar = tarfile.open(\\\"\\\", mode=\\\"w|\\\", fileobj=out)\\r\\n templates = self.manifest.get(\\\"templates\\\")\\r\\n for path in self.find(*args, **kw):\\r\\n if config and path in templates:\\r\\n real_path = templates_dir + path\\r\\n EJSTemplate(real_path).apply(real_path, config)\\r\\n else:\\r\\n real_path = self.unchroot_path(path)\\r\\n tar.add(real_path, path, recursive=False)\\r\\n tar.close()\",\n \"def server_static(filename):\\n return static_file(filename, root='static/stats')\",\n \"def extract_web_archive(cls, url, apath, ffilter=[]):\\n\\n if apath not in cls._archives.keys():\\n download(url, apath)\\n\\n _files = extract(apath, ffilter=ffilter)\\n\\n return _files\",\n \"def gz_tar(full_prefix):\\n tarfile = os.path.join(outputdir, full_prefix + '.tar')\\n try:\\n with open(tarfile, 'rb') as f_in, gzip.open(tarfile + '.gz', 'wb') as f_out:\\n shutil.copyfileobj(f_in, f_out)\\n os.remove(tarfile)\\n except Exception as e:\\n log.error(\\\"Tarfile {0} was not generated. Module(s) run collected no info?\\\".format(tarfile))\\n log.error(e)\\n\\n return tarfile + '.gz'\",\n \"def generate_static_site(self, output_root=None, extra_context=None):\\n self.app.config['BUILD_PATH'] = output_root\\n\\n # use this hook for registering URLs to freeze\\n self.call_hook(\\\"generate\\\", self, output_root, extra_context)\\n\\n if output_root is not None:\\n # realpath or this gets generated relative to the tarbell package\\n self.app.config['FREEZER_DESTINATION'] = os.path.realpath(output_root)\\n\\n self.freezer.freeze()\",\n \"def _download_from_web(*, ds_name: str, ds_path: Path):\\n import cgi\\n import zipfile\\n import httpx\\n from tqdm import tqdm\\n\\n url = DATASET_OPTIONS[ds_name]['web']\\n if ds_path.exists():\\n print('Dataset directory already exists; remove it if you wish to '\\n 're-download the dataset')\\n return\\n\\n ds_path.mkdir(parents=True, exist_ok=True)\\n\\n with httpx.Client() as client:\\n with client.stream('GET', url=url) as response:\\n if not response.is_error:\\n pass # All good!\\n else:\\n raise RuntimeError(\\n f'Error {response.status_code} when trying '\\n f'to download {url}')\\n\\n\\n header = response.headers['content-disposition']\\n _, params = cgi.parse_header(header)\\n # where to store the archive\\n outfile = ds_path / params['filename']\\n remote_file_size = int(response.headers['content-length'])\\n\\n with open(outfile, mode='wb') as f:\\n with tqdm(desc=params['filename'], initial=0,\\n total=remote_file_size, unit='B',\\n unit_scale=True, unit_divisor=1024,\\n leave=False) as progress:\\n num_bytes_downloaded = response.num_bytes_downloaded\\n\\n for chunk in response.iter_bytes():\\n f.write(chunk)\\n progress.update(response.num_bytes_downloaded -\\n num_bytes_downloaded)\\n num_bytes_downloaded = (response\\n .num_bytes_downloaded)\\n\\n assert outfile.suffix == '.zip'\\n\\n with zipfile.ZipFile(outfile) as zip:\\n for zip_info in zip.infolist():\\n path_in_zip = Path(zip_info.filename)\\n # omit top-level directory from Zip archive\\n target_path = str(Path(*path_in_zip.parts[1:]))\\n if str(target_path) in ('.', '..'):\\n continue\\n if zip_info.filename.endswith('/'):\\n (ds_path / target_path).mkdir(parents=True, exist_ok=True)\\n continue\\n zip_info.filename = target_path\\n print(f'Extracting: {target_path}')\\n zip.extract(zip_info, ds_path)\\n\\n outfile.unlink()\",\n \"def server_static(filepath):\\n return bottle.static_file(filepath, root=STATIC_ROOT)\",\n \"def tarball(request):\\n\\n patches = (models.Patch\\n .query(ancestor=request.patchset.key)\\n .order(models.Patch.filename)\\n .fetch(1000))\\n\\n temp = tempfile.TemporaryFile()\\n tar = tarfile.open(mode=\\\"w|bz2\\\", fileobj=temp)\\n\\n def add_entry(prefix, content, patch):\\n data = content.data\\n if data is None:\\n data = content.text\\n if isinstance(data, unicode):\\n data = data.encode(\\\"utf-8\\\", \\\"replace\\\")\\n if data is None:\\n return\\n info = tarfile.TarInfo(prefix + patch.filename)\\n info.size = len(data)\\n # TODO(adonovan): set SYMTYPE/0755 when Rietveld supports symlinks.\\n info.type = tarfile.REGTYPE\\n info.mode = 0644\\n # datetime->time_t\\n delta = request.patchset.modified - datetime.datetime(1970, 1, 1)\\n info.mtime = int(delta.days * 86400 + delta.seconds)\\n tar.addfile(info, fileobj=StringIO(data))\\n\\n for patch in patches:\\n if not patch.no_base_file:\\n try:\\n add_entry('a/', patch.get_content(), patch) # before\\n except FetchError: # I/O problem?\\n logging.exception('tarball: patch(%s, %s).get_content failed' %\\n (patch.key.id(), patch.filename))\\n try:\\n add_entry('b/', patch.get_patched_content(), patch) # after\\n except FetchError: # file deletion? I/O problem?\\n logging.exception('tarball: patch(%s, %s).get_patched_content failed' %\\n (patch.key.id(), patch.filename))\\n\\n tar.close()\\n temp.flush()\\n\\n wrapper = FileWrapper(temp)\\n response = HttpResponse(wrapper, mimetype='application/x-gtar')\\n response['Content-Disposition'] = (\\n 'attachment; filename=patch%s_%s.tar.bz2' % (request.issue.key.id(),\\n request.patchset.key.id()))\\n response['Content-Length'] = temp.tell()\\n temp.seek(0)\\n return response\",\n \"def download_and_expand_tgz(url):\\n with TemporaryDirectory(prefix=\\\"cot_helper\\\") as directory:\\n logger.debug(\\\"Temporary directory is %s\\\", directory)\\n logger.verbose(\\\"Downloading and extracting %s\\\", url)\\n response = requests.get(url, stream=True)\\n tgz = os.path.join(directory, 'helper.tgz')\\n with open(tgz, 'wb') as fileobj:\\n shutil.copyfileobj(response.raw, fileobj)\\n del response\\n logger.debug(\\\"Extracting %s\\\", tgz)\\n with tarfile.open(tgz, \\\"r:gz\\\") as tarf:\\n tarf.extractall(path=directory)\\n try:\\n yield directory\\n finally:\\n logger.debug(\\\"Cleaning up temporary directory %s\\\", directory)\",\n \"def _download_untar(self, dep):\\n tar = sh.Command(\\\"tar\\\")\\n download_url = self.dependency_dict[dep][\\\"tarball\\\"]\\n dlname = download_url.split(\\\"/\\\")[-1]\\n download_path = Path(\\\".\\\") / dlname\\n logger.debug(f\\\"downloading {dep} at {download_url} to {dlname}\\\")\\n if self.quiet:\\n trackers = ()\\n else:\\n trackers = (ProgressTracker(DataTransferBar()),)\\n request_download(download_url, download_path, trackers=trackers)\\n logger.debug(\\n f\\\"downloaded file {download_path}, size\\\"\\n f\\\" {download_path.stat().st_size}\\\"\\n )\\n try:\\n tar(\\\"xvf\\\", download_path, **self.output_kwargs)\\n except:\\n logger.error(f\\\"untar of {download_path} failed\\\")\\n sys.exit(1)\",\n \"def main():\\n # Create / clean output dir\\n if os.path.isdir(OUT_DIR):\\n shutil.rmtree(OUT_DIR)\\n os.mkdir(OUT_DIR)\\n\\n # Write all assets to the directory\\n for fname, bb in create_assets().items():\\n filename = os.path.join(OUT_DIR, fname)\\n dirname = os.path.dirname(filename)\\n if not os.path.isdir(dirname):\\n os.makedirs(dirname)\\n with open(filename, \\\"wb\\\") as f:\\n f.write(bb)\",\n \"def download_archive(self):\\n\\n def time_convert(structure):\\n \\\"\\\"\\\"\\n :param structure: tuple representation of time\\n :return: GitHub archive time\\n \\\"\\\"\\\"\\n \\n \\n join_number_to_zero = lambda number: (\\\"\\\" if number > 9 else \\\"0\\\") + str(number)\\n\\n return \\\"%s-%s-%s-%s\\\" % (\\n structure.tm_year, join_number_to_zero(structure.tm_mon), join_number_to_zero(structure.tm_mday),\\n structure.tm_hour)\\n\\n current_time = self.get_time()\\n self.logger.debug(__name__ + \\\": \\\" + \\\"current time: \\\" + str(gmtime(current_time)))\\n\\n difference = -25200\\n #timezone difference in seconds between GMT and west coast of USA\\n\\n downloading_time = int(timegm(self.config[\\\"last_connection_time\\\"])) + 3600\\n self.logger.debug(__name__ + \\\": \\\" + \\\"downloading time: \\\" + str(gmtime(downloading_time)))\\n\\n if downloading_time > current_time - 7200:\\n self.logger.info(__name__ + \\\": \\\" + \\\"unable to download file (time limiting).\\\")\\n return\\n\\n downloading_time += difference\\n\\n json_file_name = self.download_file(time_convert(gmtime(downloading_time)))\\n\\n self.config[\\\"last_connection_time\\\"] = gmtime(downloading_time - difference)\\n self.logger.debug(__name__ + \\\": \\\" + \\\"last_connection_time: \\\" + str(self.config[\\\"last_connection_time\\\"]))\\n\\n return json_file_name\",\n \"def write_to_gzip(fname, html_body):\\n dir_path = os.path.dirname(fname)\\n ensure_dir_exists(dir_path)\\n\\n with gzip.open(fname, 'wb') as html_file:\\n html_file.write(html_body)\",\n \"def make_zip_file(self, post_content):\\n file_path, file_url = self.save_file(post_content['shortcode'] + '.zip', self.make_empty_zip())\\n with ZipFile(file_path, 'w') as zipf:\\n if post_content['igtv'] is True:\\n zipf.writestr('igtv_link.txt', post_content['urls'][0][2])\\n else:\\n for url in post_content['urls']:\\n zipf.writestr(self.get_content_name(url[2]), requests.get(url[2]).content)\\n\\n if 'text' in post_content:\\n zipf.writestr('caption.txt', post_content['text'])\\n return file_url\",\n \"def server_static (filename):\\n return static_file(filename, root=\\\"./static\\\")\",\n \"def copy_static(self, outdir):\\n pass\",\n \"def archive(mongo_backup_file):\\r\\n filename = get_archive_filename()\\r\\n tar = tarfile.open(filename, \\\"w|gz\\\")\\r\\n tar.add(mongo_backup_file)\\r\\n tar.close()\\r\\n\\r\\n return filename\",\n \"def restricted_download():\\n aaa.require(fail_redirect='/login')\\n return bottle.static_file('static_file', root='.')\",\n \"def generate(self):\\n xml = self.template()\\n fp = BytesIO()\\n gzip = GzipFile(self.filename, \\\"wb\\\", 9, fp)\\n if isinstance(xml, str):\\n xml = xml.encode(\\\"utf8\\\")\\n gzip.write(xml)\\n gzip.close()\\n data = fp.getvalue()\\n fp.close()\\n return data\",\n \"async def download_directory_as_archive(\\n request: web.Request,\\n file_path: Path,\\n zip_filename: str = None,\\n) -> web.StreamResponse:\\n\\n def _iter2aiter(iter):\\n \\\"\\\"\\\"Iterable to async iterable\\\"\\\"\\\"\\n\\n def _consume(loop, iter, q):\\n for item in iter:\\n q.put(item)\\n q.put(SENTINEL)\\n\\n async def _aiter():\\n loop = asyncio.get_running_loop()\\n q = janus.Queue(maxsize=DEFAULT_INFLIGHT_CHUNKS)\\n try:\\n fut = loop.run_in_executor(None, lambda: _consume(loop, iter, q.sync_q))\\n while True:\\n item = await q.async_q.get()\\n if item is SENTINEL:\\n break\\n yield item\\n q.async_q.task_done()\\n await fut\\n finally:\\n q.close()\\n await q.wait_closed()\\n\\n return _aiter()\\n\\n if zip_filename is None:\\n zip_filename = file_path.name + \\\".zip\\\"\\n zf = zipstream.ZipFile(compression=zipstream.ZIP_DEFLATED)\\n async for root, dirs, files in _iter2aiter(os.walk(file_path)):\\n for file in files:\\n zf.write(Path(root) / file, Path(root).relative_to(file_path) / file)\\n if len(dirs) == 0 and len(files) == 0:\\n # Include an empty directory in the archive as well.\\n zf.write(root, Path(root).relative_to(file_path))\\n ascii_filename = (\\n zip_filename.encode(\\\"ascii\\\", errors=\\\"ignore\\\")\\n .decode(\\\"ascii\\\")\\n .replace('\\\"', r\\\"\\\\\\\"\\\")\\n )\\n encoded_filename = urllib.parse.quote(zip_filename, encoding=\\\"utf-8\\\")\\n response = web.StreamResponse(\\n headers={\\n hdrs.CONTENT_TYPE: \\\"application/zip\\\",\\n hdrs.CONTENT_DISPOSITION: \\\" \\\".join(\\n [\\n \\\"attachment;\\\" f'filename=\\\"{ascii_filename}\\\";', # RFC-2616 sec2.2\\n f\\\"filename*=UTF-8''{encoded_filename}\\\", # RFC-5987\\n ]\\n ),\\n }\\n )\\n await response.prepare(request)\\n async for chunk in _iter2aiter(zf):\\n await response.write(chunk)\\n return response\",\n \"def make_tar(self, package, input_dir, build_dir, add_args=None):\\n tar = self.options.tar_command\\n\\n # Generate the .tar.gz file\\n filename = package + '.tar.gz'\\n out_file = open(os.path.join(build_dir, filename), \\\"w\\\")\\n args = [tar, '--format=gnu', '--exclude-vcs', '-C', build_dir]\\n if self.config.get('tar', {}).get('ignore', []):\\n for patt in self.config['tar']['ignore']:\\n args += ['--exclude', patt]\\n if add_args:\\n args += add_args\\n args += ['-c', input_dir]\\n logging.debug(\\\"Creating %s\\\", filename)\\n tar_proc = subprocess.Popen(args, stdout=subprocess.PIPE)\\n gzip_proc = subprocess.Popen(['gzip', '-9'], stdin=tar_proc.stdout,\\n stdout=out_file)\\n\\n if tar_proc.wait() != 0 or gzip_proc.wait() != 0:\\n logging.error(\\\"tar/gzip failed, exiting\\\")\\n sys.exit(1)\\n out_file.close()\\n logging.info('%s written', filename)\\n return filename\",\n \"def setup_output_path(self):\\n self.logger.info('setting up output path')\\n try:\\n self.output_path.mkdir()\\n except FileExistsError:\\n pass\\n try:\\n (self.output_path / 'simple').mkdir()\\n except FileExistsError:\\n pass\\n for filename in resource_listdir(__name__, 'static'):\\n if filename == 'index.html':\\n # Skip template\\n continue\\n with (self.output_path / filename).open('wb') as f:\\n source = resource_stream(__name__, 'static/' + filename)\\n f.write(source.read())\\n source.close()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7631921","0.75582755","0.75560766","0.75341463","0.7505679","0.7504223","0.7474274","0.74703455","0.74594927","0.7432596","0.74290574","0.7389648","0.7334055","0.7259239","0.72502697","0.72062916","0.72048455","0.71769315","0.71692425","0.7156065","0.71461654","0.708","0.7069954","0.70512563","0.7048458","0.7017238","0.69439197","0.69110185","0.6802071","0.6788425","0.6442844","0.5993682","0.59668136","0.5951712","0.57428193","0.57405037","0.56939083","0.5689376","0.5670903","0.55482167","0.5530465","0.5530465","0.5530465","0.5530465","0.55288714","0.5490971","0.54467785","0.5435327","0.5433396","0.5422269","0.54203796","0.5407931","0.5405615","0.53790736","0.53678644","0.53625804","0.5357676","0.53439355","0.5339509","0.53334755","0.5332622","0.5304029","0.52814937","0.5277477","0.5228327","0.52233493","0.5217847","0.52167165","0.52023244","0.51905817","0.51861566","0.517582","0.51739955","0.51714534","0.5166573","0.5164711","0.5158821","0.5158821","0.5150499","0.514092","0.51396227","0.51319736","0.51245826","0.5119584","0.5111016","0.50998193","0.5095516","0.5094749","0.5094728","0.50941616","0.5094119","0.5089665","0.50889987","0.5087652","0.5078233","0.50746214","0.50637716","0.5063733","0.5061513","0.5047063"],"string":"[\n \"0.7631921\",\n \"0.75582755\",\n \"0.75560766\",\n \"0.75341463\",\n \"0.7505679\",\n \"0.7504223\",\n \"0.7474274\",\n \"0.74703455\",\n \"0.74594927\",\n \"0.7432596\",\n \"0.74290574\",\n \"0.7389648\",\n \"0.7334055\",\n \"0.7259239\",\n \"0.72502697\",\n \"0.72062916\",\n \"0.72048455\",\n \"0.71769315\",\n \"0.71692425\",\n \"0.7156065\",\n \"0.71461654\",\n \"0.708\",\n \"0.7069954\",\n \"0.70512563\",\n \"0.7048458\",\n \"0.7017238\",\n \"0.69439197\",\n \"0.69110185\",\n \"0.6802071\",\n \"0.6788425\",\n \"0.6442844\",\n \"0.5993682\",\n \"0.59668136\",\n \"0.5951712\",\n \"0.57428193\",\n \"0.57405037\",\n \"0.56939083\",\n \"0.5689376\",\n \"0.5670903\",\n \"0.55482167\",\n \"0.5530465\",\n \"0.5530465\",\n \"0.5530465\",\n \"0.5530465\",\n \"0.55288714\",\n \"0.5490971\",\n \"0.54467785\",\n \"0.5435327\",\n \"0.5433396\",\n \"0.5422269\",\n \"0.54203796\",\n \"0.5407931\",\n \"0.5405615\",\n \"0.53790736\",\n \"0.53678644\",\n \"0.53625804\",\n \"0.5357676\",\n \"0.53439355\",\n \"0.5339509\",\n \"0.53334755\",\n \"0.5332622\",\n \"0.5304029\",\n \"0.52814937\",\n \"0.5277477\",\n \"0.5228327\",\n \"0.52233493\",\n \"0.5217847\",\n \"0.52167165\",\n \"0.52023244\",\n \"0.51905817\",\n \"0.51861566\",\n \"0.517582\",\n \"0.51739955\",\n \"0.51714534\",\n \"0.5166573\",\n \"0.5164711\",\n \"0.5158821\",\n \"0.5158821\",\n \"0.5150499\",\n \"0.514092\",\n \"0.51396227\",\n \"0.51319736\",\n \"0.51245826\",\n \"0.5119584\",\n \"0.5111016\",\n \"0.50998193\",\n \"0.5095516\",\n \"0.5094749\",\n \"0.5094728\",\n \"0.50941616\",\n \"0.5094119\",\n \"0.5089665\",\n \"0.50889987\",\n \"0.5087652\",\n \"0.5078233\",\n \"0.50746214\",\n \"0.50637716\",\n \"0.5063733\",\n \"0.5061513\",\n \"0.5047063\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.73877853"},"document_rank":{"kind":"string","value":"12"}}},{"rowIdx":92988,"cells":{"query":{"kind":"string","value":"check the previous day for viable departures"},"document":{"kind":"string","value":"def test_check_yesterday(self):\n \n # the service calendar has two weekdays, back to back\n sc = ServiceCalendar()\n sc.add_period( 0, 3600*24, [\"WKDY\"] )\n sc.add_period( 3600*24, 2*3600*24, [\"WKDY\"] )\n \n # the timezone lasts for two days and has no offset\n # this is just boilerplate\n tz = Timezone()\n tz.add_period( TimezonePeriod(0, 2*3600*24, 0) )\n \n # tripboard runs on weekdays for agency 0\n al = TripAlight( \"WKDY\", sc, tz, 0 )\n \n # one alighting - one second before midnight\n al.add_alighting( \"1\", 86400-1, 0 )\n \n # our starting state is midnight between the two days\n s0 = State(1, 86400)\n \n # it should be one second after the last alighting \n s1 = al.walk_back( s0, WalkOptions() )\n self.assertEquals( s1.time, 86399 )"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def check_if_up_to_date():\n last_daily = get_latest_dl_date()\n last_trading_day = get_last_open_trading_day()","def check_absent_pre_date(self, cr, uid, att, context=None):\n if att:\n # check employee absent pre date\n pre_att_ids = self.search(cr, uid, [('employee_id', '=', att.employee_id.id), \n ('name', '<', att.name), \n ('action', 'in', ('sign_in', 'sign_out'))], \n limit=1)\n param_obj = self.pool.get('ir.config_parameter')\n working_hour_obj = self.pool.get('hr.payroll.working.hour')\n max_early = param_obj.get_param(cr, uid, 'maximum_early_minutes', default=60)\n max_late = param_obj.get_param(cr, uid, 'maximum_late_minutes', default=60)\n trobz_base_obj = self.pool.get('trobz.base')\n att_name = datetime.strptime(att.name_tz, DEFAULT_SERVER_DATETIME_FORMAT)\n try:\n max_early = int (max_early)\n max_late = int (max_late)\n except:\n raise except_osv(_(\"Warning !\"),_(\"maximum_early_minutes or maximum_late_minutes in config parameter is incorrect\"))\n \n time_late = att_name - timedelta(minutes = max_late)\n \n working_hour_ids=[] #Payroll Working Hours (Only read working PWH, Not Leave or Overtime PWH) \n if not pre_att_ids:\n working_hour_ids = working_hour_obj.search(cr, uid, [('employee_id', '=', att.employee_id.id),\n ('expected_end', '<', time_late.strftime(DEFAULT_SERVER_DATETIME_FORMAT)),\n ('plan_line_id', '!=', False)\n ], \n context=context)\n else:\n pre_time_early = self.read(cr, uid, pre_att_ids[0], ['name_tz'], context=context)['name_tz']\n time_start_early = datetime.strptime(pre_time_early, DEFAULT_SERVER_DATETIME_FORMAT) + timedelta(minutes = max_early)\n working_hour_ids = working_hour_obj.search(cr, uid, [('employee_id', '=', att.employee_id.id),\n ('expected_start', '>', time_start_early.strftime(DEFAULT_SERVER_DATETIME_FORMAT)),\n ('expected_end', '<', time_late.strftime(DEFAULT_SERVER_DATETIME_FORMAT)),\n ('plan_line_id', '!=', False)\n ], context=context, order='date DESC')\n if not working_hour_ids:\n return False\n else:\n for working in working_hour_obj.browse(cr, uid, working_hour_ids, context=context):\n # check public holiday\n holiday_ids = self.pool.get('trobz.hr.public.holidays').search(cr, uid, [('date','=', working.date)], context=context) \n if holiday_ids:\n return False\n # full\n sql = '''\n SELECT line.id\n FROM hr_holidays_line line JOIN hr_holidays h ON line.holiday_id = h.id\n WHERE h.employee_id = %d\n AND line.first_date < '%s' AND line.last_date > '%s'\n AND h.state = 'validate'\n '''% (working.employee_id.id, working.date, working.date)\n cr.execute(sql)\n if cr.fetchall():\n continue\n else:\n sql = False\n expected_start = trobz_base_obj.convert_from_utc_to_current_timezone(cr, uid, working.expected_start, False, DEFAULT_SERVER_DATETIME_FORMAT, False, context=context)\n time_start = expected_start.hour\n expected_end = trobz_base_obj.convert_from_utc_to_current_timezone(cr, uid, working.expected_end, False, DEFAULT_SERVER_DATETIME_FORMAT, False, context=context)\n time_end = expected_end.hour\n # wh afternoon\n if time_start >= 12 and time_end >=12:\n sql = '''\n SELECT line.id\n FROM hr_holidays_line line JOIN hr_holidays h ON line.holiday_id = h.id\n WHERE h.employee_id = %d\n AND (line.first_date = '%s' OR line.last_date = '%s')\n AND h.state = 'validate'\n AND (line.last_date_type = 'afternoon' OR line.first_date_type = 'afternoon')\n '''% (working.employee_id.id, working.date, working.date)\n # wh morning\n elif time_start < 12 and time_end <= 12:\n sql = '''\n SELECT line.id\n FROM hr_holidays_line line JOIN hr_holidays h ON line.holiday_id = h.id\n WHERE h.employee_id = %d\n AND (line.first_date = '%s' OR line.last_date = '%s')\n AND h.state = 'validate'\n AND (line.last_date_type = 'morning' OR line.first_date_type = 'morning')\n '''% (working.employee_id.id, working.date, working.date)\n \n if sql:\n cr.execute(sql)\n if cr.fetchall():\n continue\n # wh full\n sql = '''\n SELECT line.id\n FROM hr_holidays_line line JOIN hr_holidays h ON line.holiday_id = h.id\n WHERE h.employee_id = %d\n AND (line.first_date = '%s' OR line.last_date = '%s')\n AND h.state = 'validate'\n AND (line.last_date_type = 'full' OR line.first_date_type = 'full')\n '''% (working.employee_id.id, working.date, working.date)\n cr.execute(sql)\n res = cr.fetchall()\n if res or (time_late >= expected_start and time_late <= expected_end):\n continue\n return True\n return False","def Daysleftverification():\n pass","def check_day_advance(self):\n days_ago = datetime.now().toordinal() - self.start_time.toordinal()\n if days_ago:\n # New day. Save data for the old day.\n self.save(days_ago = days_ago)\n self.start_time = datetime.now()\n # Reset all counters back to 0:00:00.\n for rd in self.row_detail_list:\n rd.time = '0:00:00'\n self.refresh_display()","def service_recently_down(self):\n\n outage_history_start = self.local_tz.localize(datetime.now()) - timedelta(hours=3)\n\n return outage_history_start <= self.start_time <= self.local_tz.localize(datetime.now())","def test_get_remaining_event_dates(self):\n date = EventDate.objects.create(\n event=self.event_show2,\n date=(timezone.now() - timedelta(days=10))\n )\n dates = list(get_remaining_event_dates(self.event_show2))\n self.assertFalse(date in dates)\n self.assertTrue(self.future_date in dates)\n self.assertFalse(self.past_date in dates)","def validate_current_time(self,data):\n # cuando la fecha actual esta adelnta de la fecha de inicio eso significa que el viaje ya inicio\n # si ya inicio todo esta bien \n ride = self.context['view'].get_object()\n if data <= ride.departure_date:\n raise serializers.ValidationError('Ride has not started yet')\n\n return data","def datesBeforeCurrentDate(individual):\n birthdate = individual.get_birth_data()[0]\n deathdate = individual.get_death_data()[0]\n marriageDates = gedcom_parser.get_marriages(individual)\n\n fams = gedcom_parser.get_families(individual)\n childElements = [(fam.get_child_elements()) for fam in fams]\n\n divorceDates = []\n for elements in childElements:\n for element in elements:\n if element.get_tag() == \"DIV\":\n divorceDates.append(element.get_child_elements()[0].get_value())\n\n\n latestDivorceDate = max(convertGedcomDate(date)\n for date in divorceDates) if divorceDates else None\n latestMarriageDate = max(convertGedcomDate(\n date[0]) for date in marriageDates) if marriageDates else None\n birthdate = convertGedcomDate(birthdate) if birthdate else None\n deathdate = convertGedcomDate(deathdate) if deathdate else None\n\n comparisonDates = [birthdate, deathdate,\n latestMarriageDate, latestDivorceDate]\n\n if any(day > dt.now() for day in comparisonDates if day):\n print(\n f\"Error US05: Date associated with {individual.get_name()[0]} {individual.get_name()[1]} ({individual.get_pointer()}) occurs after current date\")\n return False\n else:\n return True","def has_previous_day(self):\n\n today = datetime.now()\n start = self.file_date\n if not start:\n return False\n return start.day != today.day or start.month != today.month","def departure(self, when: datetime.date):\n if self._departure:\n logging.warning(\n f'Overwriting departure date of {self._departure.isoformat()} '\n f'for pet {self.animal_id} with {when.isoformat()}'\n )\n\n self._departure = when\n if self.intake_date and self.intake_date != \"NULL\" and self._departure != \"NULL\":\n self._adoption_time = self._departure - self.intake_date","def _check_date(self):\n\n limit_hours = self.env.user.company_id.product_rejected_limit_hours\n if limit_hours > 0:\n\n for record in self:\n\n if record.partner_id:\n last_record = self.search([\n ('id', '!=', record.id),\n ('product_id', '=', record.product_id.id),\n ('partner_id', '=', record.partner_id.id),\n ('company_id', '=', self.env.user.company_id.id),\n ], order='date')\n\n if last_record:\n last_record_date = last_record[-1].date\n last_record_datetime = datetime.strptime(\n last_record_date, '%Y-%m-%d %H:%M:%S')\n record_date = datetime.strptime(\n record.date, '%Y-%m-%d %H:%M:%S')\n\n diff = record_date - last_record_datetime\n hours_diff = (diff.seconds / 60.0) / 60\n\n if hours_diff <= limit_hours:\n raise ValidationError(\n _('This product rejected has already been registered for this same partner in the last %s hours.' % limit_hours)\n )","def _check_data_continuity(self):\n dates = list(self.data.open_date.unique())\n dates.sort()\n\n f = lambda x : tb.DateConvert(x).datetime\n dates = list(map(f, dates))\n\n delta = []\n for i, _ in enumerate(dates, start=1):\n if i < len(dates):\n delta.append(dates[i]-dates[i-1])\n\n if len(pd.unique(delta)) > 1:\n raise DiscontinuousError(\n 'There appear to be missing dates in the market data.'\n )","def _checkstate(self, queryset):\n for presup in queryset.filter(estado='borrador').exclude(fecha_realizado=None):\n if ((presup.fecha_realizado + timedelta(days=21) < datetime.now().date() and presup.tipo != 'asistencia') or\n (presup.fecha_realizado + timedelta(days=60) < datetime.now().date() and presup.tipo == 'asistencia')):\n presup._toState_cancelado(obs=\"Registro automático: Presupuesto vencido\")","def is_before(self,other_date):","def __data_set_is_payday_negative_16_17_18(cls):\n _pay_cycle_object = pay_cycle_object()\n date_to_check = date_class(2019,1,24) # The day before first payday\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\n\n date_to_check = date_class(2018,12,27)\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\n\n date_to_check = date_class(2018,2,28)\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))","def in_past(self):\n return self.election_date < datetime.date.today()","def doAdjustmentBeforeForecast(startDate : dt.datetime, endDate :dt.datetime, configDict:dict)->bool:\n conString:str = configDict['con_string_mis_warehouse']\n isAdjustmentSuccesscount = 0\n currDate = startDate\n #create object of class Adjustment\n obj_adjustment = Adjustment(conString)\n\n while currDate <= endDate:\n isAdjustmentSuccess = obj_adjustment.doAdjustment(currDate)\n if isAdjustmentSuccess:\n isAdjustmentSuccesscount = isAdjustmentSuccesscount + 1\n currDate += dt.timedelta(days=1)\n\n numOfDays = (endDate-startDate).days\n if isAdjustmentSuccesscount == numOfDays +1 :\n return True\n else:\n return False","def periodCheck(data):","def conference_departure_at(self, date_time: datetime.datetime):\n self.add_not_available(start=date_time)","def _set_days_until_triage(self):\n if self.sla_triaged_at:\n btd = dates.businesstimedelta(self.created_at, self.sla_triaged_at)\n self.days_until_triage = btd.days\n else:\n self.days_until_triage = None","def checkValidDate(self, nextDate, startDate):\n\t\tcurrentDay = nextDate.day\n\t\tcurrentMonth = nextDate.month\n\t\tcurrentYear = nextDate.year\n\t\t\n\t\tstartDay = startDate.day\n\t\tcurrentDate = datetime.datetime(currentYear, currentMonth, startDay)\n\t\t\n\t\tminDaysDiff = 99\n\t\tresult = None\n\t\t\n\t\tfor dataPoint in self.dataPoints:\n\t\t\tdataPointDate = dataPoint.getDate()\n\t\t\tdaysDiff = (dataPointDate - currentDate).days\n\t\t\t\t\t\t\n\t\t\tif daysDiff == 0:\n\t\t\t\treturn dataPointDate\n\t\t\telif daysDiff >= 0 and daysDiff < minDaysDiff:\n\t\t\t\tminDaysDiff = daysDiff\n\t\t\t\tresult = dataPointDate\n\t\treturn result","def _recompute(self):\n current_date = self.start_date\n self.quarterly_date_list = []\n self.daily_date_list = []\n while current_date <= self.end_date:\n current_quarter = get_quarter(current_date)\n current_year = current_date.year\n next_year, next_quarter = add_quarter(current_year, current_quarter)\n next_start_quarter_date = date(next_year, get_month(next_quarter),\n 1)\n\n days_till_next_quarter = (next_start_quarter_date -\n current_date).days\n days_till_end = (self.end_date - current_date).days\n if days_till_next_quarter <= days_till_end:\n current_start_quarter_date = date(current_year,\n get_month(current_quarter), 1)\n if current_start_quarter_date == current_date:\n self.quarterly_date_list.append(\n (current_year, current_quarter, lambda x: True))\n current_date = next_start_quarter_date\n elif days_till_next_quarter > self.balancing_point:\n self.quarterly_date_list.append(\n (current_year, current_quarter,\n lambda x: date(x['date_filed']) >= self.start_date))\n current_date = next_start_quarter_date\n else:\n while current_date < next_start_quarter_date:\n self.daily_date_list.append(current_date)\n current_date += timedelta(days=1)\n else:\n if days_till_end > self.balancing_point:\n if days_till_next_quarter - 1 == days_till_end:\n self.quarterly_date_list.append(\n (current_year, current_quarter, lambda x: True))\n current_date = next_start_quarter_date\n else:\n self.quarterly_date_list.append(\n (current_year, current_quarter,\n lambda x: date(x['date_filed']) <= self.end_date))\n current_date = self.end_date\n else:\n while current_date <= self.end_date:\n self.daily_date_list.append(current_date)\n current_date += timedelta(days=1)","def filter_according_to_travel_day(self,day):\n \"\"\"First check it the data has any mising values\"\"\"\n dataset = os.path.abspath('./dataset/train_revised.csv')\n if not self.check_for_missing_values(dataset):\n #Understand the dataset\n # self.understand_the_data(self.df)\n # Transform the travel date column to date time values to be accessedby dt\n self.df['travel_date'] = pd.to_datetime(self.df['travel_date'])\n # Get the respective day of the week and store it in a new column\n self.df['day_of_week'] = self.df['travel_date'].dt.day_name()\n # Drop all rows where the day was not the day passed:Sunday\n self.df.drop(self.df[self.df['day_of_week'] != day].index, axis=0, inplace=True)\n return self.df","def validate_departure_date(self,data):\n print(data)\n min_date = timezone.now()+ timedelta(minutes=10)\n if data <=min_date:\n raise serializers.ValidationError(\n 'Departure time must be at least pass the next 20 minutes window'\n )\n return data","def test_is_payday_negative1(self):\n date_to_check = date_class(2020,12,25)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == False\n\n date_to_check = date_class(2021,12,24)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == False\n\n date_to_check = date_class(2022,11,11)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == False","def check_dataset_dates(self):\n # TODO: graph traverse and date checking\n pass","def getMaximumPreviousPrice(self, departureDate, state, datas):\n specificDatas = []\n specificDatas = [data for data in datas if data[\"Date\"]==departureDate]\n\n maximumPreviousPrice = util.getPrice(specificDatas[0][\"MinimumPrice\"])\n for data in specificDatas:\n if util.getPrice(data[\"MinimumPrice\"]) > maximumPreviousPrice and data[\"State\"]>=state:\n maximumPreviousPrice = util.getPrice(data[\"MinimumPrice\"])\n\n return maximumPreviousPrice","def ElectionAfterStart(obj):\n if obj.election_date >= obj.start_date:\n raise interface.Invalid(\n _(\"A parliament has to be elected before it can be sworn in\"), \n \"election_date\", \n \"start_date\")","def is_outdated(self):\n today = datetime.datetime.today()\n day = datetime.datetime.combine(self.date, self.start_time)\n return day <= today","def getMinimumPreviousPrice(self, departureDate, state, datas):\n specificDatas = []\n specificDatas = [data for data in datas if data[\"Date\"]==departureDate]\n\n minimumPreviousPrice = util.getPrice(specificDatas[0][\"MinimumPrice\"])\n for data in specificDatas:\n if util.getPrice(data[\"MinimumPrice\"]) < minimumPreviousPrice and data[\"State\"]>=state:\n minimumPreviousPrice = util.getPrice(data[\"MinimumPrice\"])\n\n return minimumPreviousPrice","def enough_days(self, cur, username, start_date, end_date):\n cur.execute('SELECT days_free FROM users WHERE username = ?', (username,))\n days_free = cur.fetchone()[0]\n days_between = abs(self.days_difference(start_date, end_date))\n return days_free >= days_between","def _check_day_data(self, datetime):\n if self.curr_day_data is None or self.compare_dates(self.curr_day_data.index[0], datetime) is False:\n date = dt.datetime(year=datetime.year, month=datetime.month, day=datetime.day)\n symbols = [product.symbol for product in self.products]\n self.curr_day_data = get_data_multi(symbols, date, second_bars=self.second_bars)\n self.clear_resting_orders()","def test_is_payday_negative2(self):\n date_to_check = date_class(2018,11,23)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == False\n\n date_to_check = date_class(2019,1,18)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == False\n\n date_to_check = date_class(2021,12,17)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == False","def _first_good_date(self, day):\n count = 0\n while True:\n try:\n self.data.loc[day - timedelta(count)]\n return day - timedelta(count)\n except KeyError:\n count += 1","def _check_date_not_in_future(self, date):\n if date is None:\n pass\n else:\n assert (\n date <= datetime.datetime.now()\n ), \"Provided date cannot be in the future\"","def new_day(self):\n self.previous_days.append(self.energy_debt)\n self.energy_debt = defaultdict(lambda: 0.0)\n\n #TODO: add the settelement mechanism here","def test_new_items_have_equal_higher_dates(self):\n input_ = [\n self.indicator_record(date=datetime.date(2014, 2, 24),\n end_date=datetime.date(2014, 3, 24),\n value=0.0000),\n self.indicator_record(date=datetime.date(2014, 2, 25),\n end_date=datetime.date(2014, 3, 25),\n value=0.0007),\n ]\n records = self.expander._daily_three_field_indicator_expander(input_)\n increasing_days = [records[index_].date <= record.date and\n records[index_].end_date <= record.end_date\n for index_, record in enumerate(records[1:])]\n\n self.assertTrue(all(increasing_days))","def service_currently_down(self):\n\n return self.end_time and self.start_time <= self.local_tz.localize(datetime.now()) <= self.end_time","def prior_determination_date(ddates,clo_idx):\n dd = ddates.loc[ddates['Fund']==clo_idx,'Determination Date']\n prior_ddate = max(dd.loc[dd<pd.Timestamp.today()], key=lambda s: (s-pd.Timestamp.today()))\n return prior_ddate","def get_today():\n global endDate\n check_today=date_trans_x(time.strftime(\"%Y.%m.%d\"))\n if(get_article_ammount(check_today,True)>0): \n diff=datetime.strptime(check_today,'%Y.%m.%d')-datetime.strptime(endDate,'%Y.%m.%d')\n if(diff.total_seconds()>=0):\n endDate=check_today\n print \"get_today : \"+ check_today\n return check_today\n else:\n print \"get_today : \"+ endDate\n return endDate","def _is_eruption_in(self, days, from_time):\n for te in self.tes:\n if 0 < (te-from_time).total_seconds()/(3600*24) < days:\n return 1.\n return 0.","def is_upcoming(self):\n\n return timezone.now() < self.start < timezone.now() + timedelta(days=1)","def test_07_no_future_records(self):\n bad_date = timezone.now() + timedelta(days=1)\n record = SwimRecord(record_date=bad_date)\n try:\n record.full_clean()\n except ValidationError as e:\n self.assertTrue(\"Can't set record in the future.\" in e.message_dict['record_date'])","def _checkDT(self):\r\n dt = np.diff(self.tsec)\r\n \r\n dt_unique = np.unique(dt)\r\n \r\n if np.size(dt_unique) == 1:\r\n self.isequal = True\r\n else:\r\n self.isequal = False\r\n \r\n try:\r\n self.dt = dt[1]\r\n except:\r\n self.dt = 0.0","def _onchange_date_from(self):\n\t\tdate_from = self.date_from\n\t\tdate_to = self.date_to\n\t\tself.compute_valid_leaves_for_employee(date_from, date_to)\n\n\t\t# policy_id = self.env['leaves.policy'].sudo().search(\n\t\t# \t[('leave_type', '=', self.holiday_status_id.id), ('company_id', '=', self.env.user.company_id.id)])\n\t\t# if date_from and not date_to:\n\t\t# \tdate_to_with_delta = fields.Datetime.from_string(date_from) + timedelta(hours=8)\n\t\t# \tself.date_to = str(date_to_with_delta)\n\t\t# \tnumber_of_day = (datetime.strptime(self.date_to, DEFAULT_SERVER_DATETIME_FORMAT) - datetime.strptime(date_from, DEFAULT_SERVER_DATETIME_FORMAT)).total_seconds()/(24*3600)\n\t\t# \tself.number_of_days_temp = number_of_day\n\t\t# # Compute and update the number of days\n\t\t# if (date_to and date_from) and (date_from <= date_to):\n\t\t# \tif policy_id:\n\t\t# \t\tfor val in policy_id:\n\t\t# \t\t\tnumber_of_days = 0\n\t\t# \t\t\tif val.weekends_leave_period == 'dont_count':\n\t\t# \t\t\t\tnum_days = self._get_number_of_days(date_from, date_to, self.employee_id.id)\n\t\t# \t\t\t\tdate_to1 = datetime.strptime(date_to, '%Y-%m-%d %H:%M:%S')\n\t\t# \t\t\t\tdate_from1 = datetime.strptime(date_from, '%Y-%m-%d %H:%M:%S')\n\t\t#\n\t\t# \t\t\t\t# Logic of Public Holidays when week offs count as holidays is True 2019-11-19\n\t\t# \t\t\t\temp_shift = self.employee_id.resource_calendar_ids\n\t\t# \t\t\t\tglobal_leaves = emp_shift.global_leave_ids\n\t\t# \t\t\t\t# List to store the global leaves\n\t\t# \t\t\t\tpublic_holidays = []\n\t\t# \t\t\t\tfor holiday in global_leaves:\n\t\t# \t\t\t\t\tpublic_holidays.append((holiday.date_from, holiday.date_to))\n\t\t#\n\t\t# \t\t\t\t# Public holidays between leave period\n\t\t# \t\t\t\tleave_period_dates = []\n\t\t# \t\t\t\tstart_date = date_from1.date()\n\t\t# \t\t\t\tend_date = date_to1.date()\n\t\t# \t\t\t\tdelta = end_date - start_date\n\t\t# \t\t\t\tfor i in range(delta.days + 1):\n\t\t# \t\t\t\t\tday = start_date + timedelta(days=i)\n\t\t# \t\t\t\t\tleave_period_dates.append(day)\n\t\t# \t\t\t\tcount = 0\n\t\t# \t\t\t\tfor date in public_holidays:\n\t\t# \t\t\t\t\tif datetime.strptime(date[0], '%Y-%m-%d %H:%M:%S').date() in leave_period_dates:\n\t\t# \t\t\t\t\t\tcount += 1\n\t\t# \t\t\t# End of Public Holidays logic\n\t\t#\n\t\t# \t\t\t\tself.number_of_days_temp = num_days - count\n\t\t# \t\t\telse:\n\t\t# \t\t\t\tnumber_of_days = self._get_number_of_days(date_from, date_to, self.employee_id.id)\n\t\t# \t\t\t\tdate_to1 = datetime.strptime(date_to, '%Y-%m-%d %H:%M:%S')\n\t\t# \t\t\t\tdate_from1 = datetime.strptime(date_from, '%Y-%m-%d %H:%M:%S')\n\t\t# \t\t\t\tif val.dur_full and not val.dur_half:\n\t\t# \t\t\t\t\ttotal_days = (date_to1 - date_from1).days\n\t\t# \t\t\t\telse:\n\t\t# \t\t\t\t\ttotal_seconds = (date_to1 - date_from1).seconds\n\t\t# \t\t\t\t\ttotal_days = total_seconds / (24 * 3600)\n\t\t#\n\t\t# \t\t\t\tweek_offs = total_days - number_of_days\n\t\t# \t\t\t\tself.number_of_days_temp = number_of_days + week_offs\n\t\t# \telse:\n\t\t# \t\t# self.number_of_days_temp = self._get_number_of_days(date_from, date_to, self.employee_id.id)\n\t\t# \t\tnumber_of_day = (datetime.strptime(self.date_to, DEFAULT_SERVER_DATETIME_FORMAT) - datetime.strptime(\n\t\t# \t\t\tdate_from, DEFAULT_SERVER_DATETIME_FORMAT)).total_seconds() / (24 * 3600)\n\t\t# \t\tself.number_of_days_temp = number_of_day\n\t\t#\n\t\t# elif (date_to and date_from) and (date_from > date_to):\n\t\t# \traise ValidationError(\"From Date cannot be greater then To Date\")\n\t\t# else:\n\t\t# \tself.number_of_days_temp = 0","def check_market_status():\n # today = datetime.datetime.now(pytz.timezone('America/New_York')).date()\n today_utc = pd.to_datetime('now').date()\n ndq = mcal.get_calendar('NASDAQ')\n open_days = ndq.schedule(start_date=today_utc - pd.Timedelta('10 days'), end_date=today_utc)\n if today_utc in open_days.index:\n return open_days\n else:\n return None","def test_is_payday_positive_25(self):\n expected_count = 3\n expected_paydays = [\n date_class(2020,10,2), \n date_class(2020,10,16), \n date_class(2020,10,30)\n ]\n\n curr_date = date_class(2020,10,1)\n end_date = date_class(2020,10,31)\n paydays = []\n\n while curr_date <= end_date:\n is_payday = pay_cycle_object().is_payday(curr_date)\n if is_payday: \n paydays.append(curr_date)\n curr_date += timedelta(days=1)\n\n assert len(paydays) == expected_count, \\\n f'Got {len(paydays)}, expected {expected_count}'\n assert paydays == expected_paydays, \\\n f'Got {paydays}, expected {expected_paydays}'","def __data_set_is_payday_negative_22_23_24(cls):\n _pay_cycle_object = pay_cycle_object()\n date_to_check = date_class(2018,11,23)\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\n\n date_to_check = date_class(2019,1,18)\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\n\n date_to_check = date_class(2021,12,17)\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))","def compute_prev_fy_performance(self):\n PrevFY = self.env['%s.prev.fy.view' % self._name]\n PrevFY._fill_prev_fy_performance(self) # self = plans","def test_is_payday_negative0(self):\n date_to_check = date_class(2019,1,24)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == False\n\n date_to_check = date_class(2018,12,27)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == False\n\n date_to_check = date_class(2018,2,28)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == False","def change_possible(self, departure_time):\r\n if (departure_time >= self.min_departure_time) and (departure_time <= self.max_departure_time):\r\n return True\r\n\r\n return False","def good_standing(self):\n # Date of last AR or founding date if they haven't yet filed one\n last_ar_date = self.last_ar_date or self.founding_date\n # Good standing is if last AR was filed within the past 1 year, 2 months and 1 day\n return last_ar_date + datedelta.datedelta(years=1, months=2, days=1) > datetime.utcnow()","def DissolutionAfterReinstatement(obj):\n if (obj.dissolution_date is None) or (obj.reinstatement_date is None): \n return\n if obj.dissolution_date > obj.reinstatement_date:\n raise interface.Invalid(\n _(\"A committee must be disolved before it can be reinstated\"), \n \"dissolution_date\", \n \"reinstatement_date\")","def _check_dates(self):\n for record in self:\n if record.end_date and record.end_date < record.start_date:\n raise exceptions.Warning(\n _('Agreement end date must be greater than start date'))","def _check_dates(self, cr, uid, ids, context=None):\n for act in self.browse(cr, uid, ids, context):\n date_from = self.get_date(act.date_from)\n date_to = self.get_date(act.date_to)\n previous_ids = self.search(cr, uid, [('id','!=',act.id), ('alternative_setting_id','=',act.alternative_setting_id.id)],context=context)\n dates = self.read(cr, uid, previous_ids, ['date_from','date_to'], context=context)\n\n dates = [{'date_from':self.get_date(x['date_from']),'date_to':self.get_date(x['date_to'])} for x in dates]\n for date in dates:\n case0 = date['date_from'] >= date_from and date['date_to'] <= date_to\n\n case1 = date['date_from'] <= date_from and date['date_to'] >= date_to\n\n case2 = date['date_from'] <= date_from and date_from <= date['date_to'] \n\n case3 = date_from <= date['date_from'] and date['date_from'] <= date_to\n \n if case0 or case1 or case2 or case3:\n raise osv.except_osv(_('Error'), _(\"THIS RANGE OF DATE HAVE BEEN FETCHED BEFORE\"))\n return True","def test_holidays():\n\n assert not datetime.datetime(2003, 12, 25) in TRADING_DATES\n assert not datetime.datetime(2003, 5, 26) in TRADING_DATES # memorial day","def test_date_accept_yesterday(self):\n import dateutil.relativedelta\n spi_search = \"find date yesterday\"\n inv_search = \"year:\" + datetime.datetime.strftime(datetime.datetime.today()+dateutil.relativedelta.relativedelta(days=-1), '%Y-%m-%d')\n self._compare_searches(inv_search, spi_search)","def period_check(init_dates, fcst_dates):\n check_dates(init_dates)\n check_dates(fcst_dates)\n \n if max(init_dates) > min(fcst_dates):\n raise ValueError('Forecast date, %s comes before initialisation '\\\n 'date, %s.' % (min(fcst_dates), max(init_dates)))\n\n fcst_dates = change_zeroth_hour(fcst_dates)\n return init_dates, fcst_dates","def check_changes(yield_curve, forecast):\r\n df = pd.read_csv('data/diff_df.csv').set_index('DATE')\r\n if list(df.index)[-1] != list(yield_curve.index)[-1]:\r\n forecast = pd.read_csv('data/forecast.csv')\r\n yield_curve = df","def test_fall_back(self):\n # Exact crossover time:\n # datetime.datetime(2011, 11, 6, 2, 0, 0, tzinfo=pytz.utc)\n # This test will use times on either side of it.\n\n # From the PDT vantage point, the run time is 24.2 and 48.2 hours away:\n s1a, s1b = self.hours_to_job_at_datetime(\n 'tz_test_job', 2011, 11, 6, 0, 50, 0)\n\n # From the PST vantage point, the run time is 21.8 and 45.8 hours away:\n s2a, s2b = self.hours_to_job_at_datetime(\n 'tz_test_job', 2011, 11, 6, 2, 10, 0)\n\n # Make sure the measurements are consistent for each vantage point,\n # meaning that each run is 24 hours apart no matter where you measure\n # from, even if the start time appears different for each vantage\n # point.\n self._assert_range(s1b - s1a, 23.99, 24.01)\n self._assert_range(s2b - s2a, 23.99, 24.01)\n\n # Start times should differ by 2.4 hours.\n self._assert_range(s1a - s2a, 2.39, 2.41)","def _check_dates_tarea_start(self, cr, uid, ids, context=None):\n for leave in self.read(cr, uid, ids, ['date_start_tarea', 'date_start_proyecto'], context=context):\n if leave['date_start_tarea'] and leave['date_start_proyecto']:\n if leave['date_start_tarea'] < leave['date_start_proyecto']:\n return False\n return True","def check(self):\n validity_year = int(self.date[0:4])\n validity_month = int(self.date[5:7])\n validity_day = int(self.date[8:10])\n if datetime.today().year > validity_year:\n self.flag = False\n elif datetime.today().year == validity_year:\n if datetime.today().month > validity_month:\n self.flag = False\n elif datetime.today().month == validity_month:\n if datetime.today().day > validity_day:\n self.flag = False\n else:\n self.flag = True\n else:\n self.flag = True\n else:\n self.flag = True","def clean(self):\n\t\tlogging.info(\"Checking week for old days\")\n\t\ttoday = datetime.now().date()\n\t\tfor i,d in enumerate(self.days):\n\t\t\tif d is not None and today-d.date > timedelta(7):\n\t\t\t\tself.days[i] = None\n\t\t\t\tlogging.info(\"Deleting old workday from %d/%d in slot %d\" \\\n\t\t\t\t\t% (d.date.month, d.date.day, i)\n\t\t\t\t\t)","def test_is_payday_positive2(self):\n date_to_check = date_class(2019,11,1)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == True\n\n date_to_check = date_class(2019,11,29)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == True\n\n date_to_check = date_class(2019,12,13)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == True","def check_sequence_for_days(self):\n # delta = (max(self.giorni) - min(self.giorni)).days + 1 # the difference returns a timedelta\n try:\n delta = abs(max(self.giorni).daysTo(min(self.giorni))) + 1\n if delta != len(self.giorni):\n raise ValidationError('dates need to be in sequence')\n except ValueError as e:\n return print(e)","def is_before_eof_finals_week(now, request):\n logger.debug(\"{} is_before_eof_finals_week {} ==> {}\".format(\n now, get_eod_current_term_last_final_exam(request),\n now < get_eod_current_term_last_final_exam(request)))\n return now < get_eod_current_term_last_final_exam(request)","def _check_dates(self, cr, uid, ids, context=None):\n for act in self.browse(cr, uid, ids, context):\n date_from = self.get_date(act.date_from)\n date_to = self.get_date(act.date_to)\n previous_ids = self.search(cr, uid, [('id','!=',act.id)],context=context)\n dates = self.read(cr, uid, previous_ids, ['date_from','date_to'], context=context)\n\n dates = [{'date_from':self.get_date(x['date_from']),'date_to':self.get_date(x['date_to'])} for x in dates]\n for date in dates:\n case0 = date['date_from'] >= date_from and date['date_to'] <= date_to\n\n case1 = date['date_from'] <= date_from and date['date_to'] >= date_to\n\n case2 = date['date_from'] <= date_from and date_from <= date['date_to'] \n\n case3 = date_from <= date['date_from'] and date['date_from'] <= date_to\n \n if case0 or case1 or case2 or case3:\n raise osv.except_osv(_('Error'), _(\"THIS RANGE OF DATE HAVE BEEN FETCHED BEFORE\"))\n return True","def test_check_date_tour(self):\n date_start = timezone.now()\n date_end = timezone.now() - timedelta(days=5)\n new_tour = Tournament(date_start=date_start, date_end=date_end)\n\n self.assertEqual(new_tour.check_date(), False)","def __data_set_is_payday_negative_19_20_21(cls):\n _pay_cycle_object = pay_cycle_object()\n date_to_check = date_class(2020,12,25) # Christmas\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\n\n date_to_check = date_class(2021,12,24)\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\n\n date_to_check = date_class(2022,11,11)\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))","def previous_date(date):\n #This function is basically the same as the next_date function, except I subtracted 1 instead of adding 1.\n #The main difference was figuring out what to do when transitioning to a different month with a different amount of days.\n #This is why August, for example, is in it's own if else statement; most 31 day months go backwards into a 30 day month.\n #August, however, transitions into July, which is another 31 day month. Because of this, I needed to create a case just for August.\n #I used the same thought process for the other monthly transitions, as well as the year transition (1-1-XXXX -> 12-31-XXX(X-1))\n if date[0] == 5 or date[0] == 7 or date[0] == 10 or date[0] == 12:\n if date[1] > 1:\n prevday = (date[0], date[1] - 1, date[2])\n return prevday\n elif date[1] == 1:\n prevday = (date[0] - 1, 30, date[2])\n return prevday\n elif date[0] == 8:\n if date[1] > 1:\n prevday = (date[0], date[1] - 1, date[2])\n return prevday\n elif date[1] == 1:\n prevday = (date[0] - 1, 31, date[2])\n return prevday\n elif date[0] == 1:\n if date[1] > 1:\n prevday = (date[0], date[1] - 1, date[2])\n return prevday\n elif date[1] == 1:\n prevday = (12, 31, date[2] - 1)\n return prevday\n elif date[0] == 4 or date[0] == 6 or date[0] == 9 or date[0] == 11:\n if date[1] > 1:\n prevday = (date[0], date[1] - 1, date[2])\n return prevday\n elif date[1] == 1:\n prevday = (date[0] - 1, 31, date[2])\n return prevday\n elif date[0] == 3:\n if date[2] % 4 == 0 or date[2] % 1000 == 0:\n if date[1] > 1:\n prevday = (date[0], date[1] - 1, date[2])\n return prevday\n elif date[1] == 1:\n prevday = (2, 29, date[2])\n return prevday\n elif date[1] > 1:\n prevday = (date[0], date[1] - 1, date[2])\n return prevday\n elif date[1] == 1:\n prevday = (date[0] - 1, 28, date[2])\n return prevday\n elif date[0] == 2:\n if date[1] > 1:\n prevday = (date[0], date[1] - 1, date[2])\n return prevday\n elif date[1] == 1:\n prevday = (date[0] - 1, 31, date[2])\n return prevday","def check_market_status():\n today_ny = datetime.datetime.now(pytz.timezone('America/New_York'))\n ndq = mcal.get_calendar('NASDAQ')\n open_days = ndq.schedule(start_date=today_ny - pd.Timedelta('10 days'), end_date=today_ny)\n if today_ny.date() in open_days.index:\n return open_days\n else:\n return None","def test_is_payday_positive3(self):\n date_to_check = date_class(2020,1,10)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == True\n\n date_to_check = date_class(2020,1,24)\n is_payday = self.pay_cycle.is_payday(date_to_check)\n assert is_payday == True","def get_next_departure(self,day,link,current_time): \n if link not in self.data[day]:\n return None\n import numpy as np\n index=[np.searchsorted(self.data[day][link][0:,0],current_time)]\n print(len(self.data[day][link]))\n print(index) \n if index[0] < len(self.data[day][link]):\n return self.data[day][link][index[0]]\n else:\n return None","async def test_source_up_to_dateness(self):\n self.set_source_parameter(\"date\", \"2019-06-01\")\n response = await self.collect()\n self.assert_measurement(response, value=str((datetime.now() - datetime(2019, 6, 1)).days))","def yesterday(self):\n if self.isLeapYear():\n fdays = 29\n else:\n fdays = 28\n\n DIM = [0, 31, fdays, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]\n\n currentDay = self.day\n firstMonth = 1\n firstDay = 1\n\n if currentDay == firstDay and self.month == firstMonth:\n self.year -= 1\n self.month = 12\n self.day = 31\n elif currentDay == firstDay:\n self.month -= 1\n self.day = DIM[self.month]\n else:\n self.day -= 1","def trade_position_effective_date_valid(record):\n knowledge_date = record['knowledge_date']\n effective_date = record['effective_date']\n assert effective_date == knowledge_date + timedelta(days=2)","def date_in_past(date: dt.datetime) -> bool:\n return date < dt.datetime.now()","def _departure_on_duty(self) -> bool:\n return self._get_departure_shift().is_on_duty()","def __find_previous_cf_element(self) -> LineElement:\n index = (self.current_time_in_eighths - 1) // N_EIGHTHS_PER_MEASURE\n result = self.cantus_firmus[index]\n return result","def condition(self, year, month, day, lastday, leapday):\n try:\n if len(day) == 0 or int(day) > int(lastday):\n if int(month) == 2 and day == leapday:\n Input.change_display(self, self.entries[4],\n 'Not a leap year')\n else:\n Input.change_display(self, self.entries[4],\n 'Enter day between 1-' + lastday)\n elif int(day) <= int(lastday):\n Input.change_display(self, self.entries[3], #Weekday message\n Output.message(self, year, month, day))\n except:\n Input.change_display(self, self.entries[4],\n 'Enter day between 1-' + lastday)","def test_form_invalid_date_in_past(self):\n login = self.client.login(\n username='testuser2',\n password='2HJ1vRV0Z&3iD')\n past_date = datetime.date.today() - datetime.timedelta(days=1)\n response = self.client.post(\n reverse('librarian-renew-book',\n kwargs={'pk': self.test_bookinstance2.pk}),\n {'due_back': past_date})\n self.assertEqual(response.status_code, 200)\n self.assertFormError(response,\n 'form',\n 'due_back',\n 'Invalid date - renewal in the past')","def one_day(self):\n return self.end.date() == self.date","def CheckIfEarliestDeparture(ConnectionInfo, PathInfo):\r\n\tif not hasattr(CheckIfEarliestDeparture, \"DepartureTimeDic\"):\r\n\t\tCheckIfEarliestDeparture.DepartureTimeDic = {}\r\n\r\n\t# return True\r\n\r\n\tcurr_station = ConnectionInfo[ConnInfoInd['station_from']]\r\n\tnext_station = ConnectionInfo[ConnInfoInd['station_to']]\r\n\r\n\tline_id = ConnectionInfo[ConnInfoInd['line_id']]\r\n\t\r\n\tNextLine = (curr_station, next_station, line_id)\r\n\tdeparture_next_station = ConnectionInfo[ConnInfoInd['arrival_hour']]*60 + ConnectionInfo[ConnInfoInd['arrival_min']]\r\n\r\n\tif CheckIfEarliestDeparture.DepartureTimeDic.has_key(next_station):\r\n\t\tearliest_departure = CheckIfEarliestDeparture.DepartureTimeDic[NextLine]\r\n\r\n\t\tif departure_next_station < earliest_departure:\r\n\t\t\tCheckIfEarliestDeparture.DepartureTimeDic[NextLine] = departure_next_station\r\n\t\t\tprint \"CheckIfEarliestDeparture: True\"\r\n\t\t\treturn True\r\n\t\telse:\r\n\t\t\tprint \"CheckIfEarliestDeparture: False\"\r\n\t\t\treturn False\r\n\telse:\r\n\t\tCheckIfEarliestDeparture.DepartureTimeDic[NextLine] = departure_next_station\r\n\t\treturn True","def test_date_accept_date_minus_many_days(self):\n spi_search = \"find date 2011-02-24 - 946\"\n inv_search = \"year:2008-07-23\"\n self._compare_searches(inv_search, spi_search)","def get_days_delta(query):\n # the format of delta: 18 days, 0:00:00\n\n try:\n delta_string = str(get_date() - get_start_date(query)).split(' ')[0]\n delta = int(delta_string)\n\n except TypeError as err:\n \"\"\"\n could get_start_date of contact because it hasn't been initialized.\n \"\"\"\n # print(\"the contact hasn't initialize the evaluation: \", err)\n return None, err\n\n except ValueError as err:\n \"\"\"\n this exception is used to handle the first day record error.\n minus the same dates will get \"0:00:00\".\n \"\"\"\n if delta_string == \"0:00:00\":\n delta = 0\n else:\n # print(\"the date has some problem: \", err)\n return None, err\n return delta","def prev(self):\n return self.from_date(self.date_a - datetime.timedelta(1))","def testPrevDayOfMonthWithCrossing(self):\n base = datetime(2012, 3, 15, 0, 0)\n itr = croniter('0 0 22 * *', base)\n prev = itr.get_prev(datetime)\n self.assertEqual(prev.year, 2012)\n self.assertEqual(prev.month, 2)\n self.assertEqual(prev.day, 22)\n self.assertEqual(prev.hour, 0)\n self.assertEqual(prev.minute, 0)","def test_before():\n date = datetime.datetime\n\n #july forth is this week\n assert CALENDAR.nth_trading_day_before(3, date(2006, 7, 7)) == date(2006, 7, 3)\n assert CALENDAR.nth_trading_day_before(0, date(2006, 7, 7)) == date(2006, 7, 7)\n assert CALENDAR.nth_trading_day_before(0, date(2006, 7, 8)) == date(2006, 7, 7)","def isOutOfDate(self):\n cert = self.getLatestValidCertification()\n today = date.today()\n if cert and cert.getValidTo():\n validto = cert.getValidTo().asdatetime().date();\n if validto > today:\n return False\n return True","def test_looking_back_to_prior_state(self):\n schedule = parser.parse_schedule(SCHEDULE)\n self.assertIsNone(schedule.get_latest_event(\n dt(saturday, '09:30'), lookback=False))\n self.assertEqual((dt(friday, '11:00'), \"c\"),\n schedule.get_latest_event(dt(saturday, '09:30')))","def test_date_accept_date_minus_days(self):\n spi_search = \"find date 2011-01-03 - 2\"\n inv_search = \"year:2011-01\"\n self._compare_searches(inv_search, spi_search)","def prev_quarter_boundaries(now):\n first_of_month = datetime.datetime(now.year, now.month, 1)\n\n # 75 days before the 1st is always in the previous quarter\n date_in_prev_q = first_of_month - datetime.timedelta(days=75)\n\n q_y = date_in_prev_q.year\n q_start_m = int((date_in_prev_q.month-1) / 3)*3 + 1\n q_end_m = q_start_m + 2\n q_end_d = calendar.monthrange(q_y, q_end_m)[1]\n\n s_d = datetime.datetime(q_y, q_start_m, 1)\n e_d = datetime.datetime(q_y, q_end_m, q_end_d)\n\n return s_d, e_d","def previous(self):\n try:\n return self.filter(end_date__lt=self.current().start_date).latest()\n except self.model.DoesNotExist:\n return None","def flag_day_if_not_enough_consecutive_days(self, min_number_days: int):\n\n for wearable in self.wearables.values():\n\n days = self.get_valid_days(wearable.get_pid())[wearable.get_pid()]\n\n if len(days) == 0:\n continue\n\n s = sorted(days)\n\n consecutive = 1\n last_value = s[0]\n saved_so_far = [last_value]\n okay = []\n\n for actual in s[1:]:\n if actual == last_value + 1:\n consecutive += 1\n last_value = actual\n saved_so_far.append(last_value)\n\n else:\n # Ops! We found a gap in the sequence.\n # First we check if we already have enough days:\n if len(saved_so_far) >= min_number_days:\n okay.extend(saved_so_far) # Cool! We have enough days.\n\n else: # Otherwise we start over\n consecutive = 1\n last_value = actual\n saved_so_far = [last_value]\n\n if len(saved_so_far) >= min_number_days:\n okay.extend(saved_so_far)\n\n # In the okay set, we have all days that we can keep.\n new_invalid = set(days) - set(okay)\n if new_invalid:\n print(\"Flagging the following days as invalid for pid %s: %s\" % (\n wearable.get_pid(), ','.join(map(str, new_invalid))))\n\n wearable.data.loc[wearable.data[wearable.get_experiment_day_col()].isin(\n new_invalid), self.invalid_col] |= InvCode.FLAG_DAY_NOT_ENOUGH_CONSECUTIVE_DAYS","def _deadline_same_day(self) -> pd.Timestamp:\n # Get the workshift on the deadline\n workshift = self._get_departure_shift()\n\n # Departure was on duty, see if there is enough time to meet deadline\n if (\n self._departure_on_duty()\n and self.compare_shift(workshift, self._lt_sec()) > 0\n ):\n # There is enough time to schedule the loading on same workshift\n return workshift.end_time - self.loading_time\n elif self.compare_shift(workshift.rollback(1), self._lt_sec()) > 0:\n # Not enough time to schedule loading same day so get previous on duty workshift\n return workshift.rollback(1).end_time - self.loading_time\n else:\n # Departure was not on duty so get closest workshift\n raise InvalidScheduleException(workshift.duration, self.loading_time)","def revise_agreements_expirations_planned(self):\n for agreement in self.search([('prolong', '=', 'unlimited')]):\n if agreement.next_expiration_date <= fields.Date.today():\n # force recalculate next_expiration_date\n agreement.write({'prolong': 'unlimited'})\n return True","def test_new_items_have_increasing_dates(self):\n input_ = [\n self.indicator_record(date=datetime.date(2004, 11, 1), value=0.69),\n self.indicator_record(date=datetime.date(2004, 12, 1), value=0.86),\n self.indicator_record(date=datetime.date(2005, 1, 1), value=0.58),\n ]\n records = self.expander._ipca_from_15_expander(input_)\n\n self.assertTrue(records[-1].date > input_[-1].date)","def check_day(self, day_of_week):\n\n day_of_week -= 1\n if (day_of_week == -1):\n self.day_of_week = 6\n else:\n self.day_of_week = day_of_week","def createDayAheadForecast(startDate:dt.datetime ,endDate: dt.datetime, configDict:dict)->bool: \n\n \n conString:str = configDict['con_string_mis_warehouse']\n demandInsertionSuccessCount = 0\n r0InsertionSuccessCount = 0\n\n #creating instance of classes\n obj_demandFetchForAlgo = DemandFetchForAlgoRepo(conString)\n obj_dayAheadDemandForecastInsertion = DayAheadDemandForecastInsertion(conString)\n obj_r0ForecastInsertion = R0RevisionInsertion(conString)\n \n currDate = startDate\n \n # Iterating through each day and inserting day ahead forecasted demand of all entities \n while currDate <= endDate:\n\n resultDict : IResultDict = obj_demandFetchForAlgo.fetchBlockwiseDemandForAlgo(currDate)\n # print(data)\n isForecastedDemandInsSuccess = obj_dayAheadDemandForecastInsertion.insertDayAheadDemandForecast(resultDict['demandData'])\n if isForecastedDemandInsSuccess:\n demandInsertionSuccessCount = demandInsertionSuccessCount + 1\n \n isR0InsertionSuccess = obj_r0ForecastInsertion.insertR0DemandForecast(resultDict['r0AData'])\n if isR0InsertionSuccess:\n r0InsertionSuccessCount += 1\n\n currDate += dt.timedelta(days=1)\n \n numOfDays = (endDate-startDate).days\n\n #checking whether data is inserted for each day or not\n if demandInsertionSuccessCount == numOfDays +1 and r0InsertionSuccessCount == numOfDays +1:\n return True\n else:\n return False","def judge_today_point_give(self,uid,pid,gid=0):\n early_night_timestamp = self.get_early_night_timestamp()\n return self.find_db_sum('fs_point_from',uid=uid,pid=pid,gid=gid,time={'rule':'>','value':early_night_timestamp})"],"string":"[\n \"def check_if_up_to_date():\\n last_daily = get_latest_dl_date()\\n last_trading_day = get_last_open_trading_day()\",\n \"def check_absent_pre_date(self, cr, uid, att, context=None):\\n if att:\\n # check employee absent pre date\\n pre_att_ids = self.search(cr, uid, [('employee_id', '=', att.employee_id.id), \\n ('name', '<', att.name), \\n ('action', 'in', ('sign_in', 'sign_out'))], \\n limit=1)\\n param_obj = self.pool.get('ir.config_parameter')\\n working_hour_obj = self.pool.get('hr.payroll.working.hour')\\n max_early = param_obj.get_param(cr, uid, 'maximum_early_minutes', default=60)\\n max_late = param_obj.get_param(cr, uid, 'maximum_late_minutes', default=60)\\n trobz_base_obj = self.pool.get('trobz.base')\\n att_name = datetime.strptime(att.name_tz, DEFAULT_SERVER_DATETIME_FORMAT)\\n try:\\n max_early = int (max_early)\\n max_late = int (max_late)\\n except:\\n raise except_osv(_(\\\"Warning !\\\"),_(\\\"maximum_early_minutes or maximum_late_minutes in config parameter is incorrect\\\"))\\n \\n time_late = att_name - timedelta(minutes = max_late)\\n \\n working_hour_ids=[] #Payroll Working Hours (Only read working PWH, Not Leave or Overtime PWH) \\n if not pre_att_ids:\\n working_hour_ids = working_hour_obj.search(cr, uid, [('employee_id', '=', att.employee_id.id),\\n ('expected_end', '<', time_late.strftime(DEFAULT_SERVER_DATETIME_FORMAT)),\\n ('plan_line_id', '!=', False)\\n ], \\n context=context)\\n else:\\n pre_time_early = self.read(cr, uid, pre_att_ids[0], ['name_tz'], context=context)['name_tz']\\n time_start_early = datetime.strptime(pre_time_early, DEFAULT_SERVER_DATETIME_FORMAT) + timedelta(minutes = max_early)\\n working_hour_ids = working_hour_obj.search(cr, uid, [('employee_id', '=', att.employee_id.id),\\n ('expected_start', '>', time_start_early.strftime(DEFAULT_SERVER_DATETIME_FORMAT)),\\n ('expected_end', '<', time_late.strftime(DEFAULT_SERVER_DATETIME_FORMAT)),\\n ('plan_line_id', '!=', False)\\n ], context=context, order='date DESC')\\n if not working_hour_ids:\\n return False\\n else:\\n for working in working_hour_obj.browse(cr, uid, working_hour_ids, context=context):\\n # check public holiday\\n holiday_ids = self.pool.get('trobz.hr.public.holidays').search(cr, uid, [('date','=', working.date)], context=context) \\n if holiday_ids:\\n return False\\n # full\\n sql = '''\\n SELECT line.id\\n FROM hr_holidays_line line JOIN hr_holidays h ON line.holiday_id = h.id\\n WHERE h.employee_id = %d\\n AND line.first_date < '%s' AND line.last_date > '%s'\\n AND h.state = 'validate'\\n '''% (working.employee_id.id, working.date, working.date)\\n cr.execute(sql)\\n if cr.fetchall():\\n continue\\n else:\\n sql = False\\n expected_start = trobz_base_obj.convert_from_utc_to_current_timezone(cr, uid, working.expected_start, False, DEFAULT_SERVER_DATETIME_FORMAT, False, context=context)\\n time_start = expected_start.hour\\n expected_end = trobz_base_obj.convert_from_utc_to_current_timezone(cr, uid, working.expected_end, False, DEFAULT_SERVER_DATETIME_FORMAT, False, context=context)\\n time_end = expected_end.hour\\n # wh afternoon\\n if time_start >= 12 and time_end >=12:\\n sql = '''\\n SELECT line.id\\n FROM hr_holidays_line line JOIN hr_holidays h ON line.holiday_id = h.id\\n WHERE h.employee_id = %d\\n AND (line.first_date = '%s' OR line.last_date = '%s')\\n AND h.state = 'validate'\\n AND (line.last_date_type = 'afternoon' OR line.first_date_type = 'afternoon')\\n '''% (working.employee_id.id, working.date, working.date)\\n # wh morning\\n elif time_start < 12 and time_end <= 12:\\n sql = '''\\n SELECT line.id\\n FROM hr_holidays_line line JOIN hr_holidays h ON line.holiday_id = h.id\\n WHERE h.employee_id = %d\\n AND (line.first_date = '%s' OR line.last_date = '%s')\\n AND h.state = 'validate'\\n AND (line.last_date_type = 'morning' OR line.first_date_type = 'morning')\\n '''% (working.employee_id.id, working.date, working.date)\\n \\n if sql:\\n cr.execute(sql)\\n if cr.fetchall():\\n continue\\n # wh full\\n sql = '''\\n SELECT line.id\\n FROM hr_holidays_line line JOIN hr_holidays h ON line.holiday_id = h.id\\n WHERE h.employee_id = %d\\n AND (line.first_date = '%s' OR line.last_date = '%s')\\n AND h.state = 'validate'\\n AND (line.last_date_type = 'full' OR line.first_date_type = 'full')\\n '''% (working.employee_id.id, working.date, working.date)\\n cr.execute(sql)\\n res = cr.fetchall()\\n if res or (time_late >= expected_start and time_late <= expected_end):\\n continue\\n return True\\n return False\",\n \"def Daysleftverification():\\n pass\",\n \"def check_day_advance(self):\\n days_ago = datetime.now().toordinal() - self.start_time.toordinal()\\n if days_ago:\\n # New day. Save data for the old day.\\n self.save(days_ago = days_ago)\\n self.start_time = datetime.now()\\n # Reset all counters back to 0:00:00.\\n for rd in self.row_detail_list:\\n rd.time = '0:00:00'\\n self.refresh_display()\",\n \"def service_recently_down(self):\\n\\n outage_history_start = self.local_tz.localize(datetime.now()) - timedelta(hours=3)\\n\\n return outage_history_start <= self.start_time <= self.local_tz.localize(datetime.now())\",\n \"def test_get_remaining_event_dates(self):\\n date = EventDate.objects.create(\\n event=self.event_show2,\\n date=(timezone.now() - timedelta(days=10))\\n )\\n dates = list(get_remaining_event_dates(self.event_show2))\\n self.assertFalse(date in dates)\\n self.assertTrue(self.future_date in dates)\\n self.assertFalse(self.past_date in dates)\",\n \"def validate_current_time(self,data):\\n # cuando la fecha actual esta adelnta de la fecha de inicio eso significa que el viaje ya inicio\\n # si ya inicio todo esta bien \\n ride = self.context['view'].get_object()\\n if data <= ride.departure_date:\\n raise serializers.ValidationError('Ride has not started yet')\\n\\n return data\",\n \"def datesBeforeCurrentDate(individual):\\n birthdate = individual.get_birth_data()[0]\\n deathdate = individual.get_death_data()[0]\\n marriageDates = gedcom_parser.get_marriages(individual)\\n\\n fams = gedcom_parser.get_families(individual)\\n childElements = [(fam.get_child_elements()) for fam in fams]\\n\\n divorceDates = []\\n for elements in childElements:\\n for element in elements:\\n if element.get_tag() == \\\"DIV\\\":\\n divorceDates.append(element.get_child_elements()[0].get_value())\\n\\n\\n latestDivorceDate = max(convertGedcomDate(date)\\n for date in divorceDates) if divorceDates else None\\n latestMarriageDate = max(convertGedcomDate(\\n date[0]) for date in marriageDates) if marriageDates else None\\n birthdate = convertGedcomDate(birthdate) if birthdate else None\\n deathdate = convertGedcomDate(deathdate) if deathdate else None\\n\\n comparisonDates = [birthdate, deathdate,\\n latestMarriageDate, latestDivorceDate]\\n\\n if any(day > dt.now() for day in comparisonDates if day):\\n print(\\n f\\\"Error US05: Date associated with {individual.get_name()[0]} {individual.get_name()[1]} ({individual.get_pointer()}) occurs after current date\\\")\\n return False\\n else:\\n return True\",\n \"def has_previous_day(self):\\n\\n today = datetime.now()\\n start = self.file_date\\n if not start:\\n return False\\n return start.day != today.day or start.month != today.month\",\n \"def departure(self, when: datetime.date):\\n if self._departure:\\n logging.warning(\\n f'Overwriting departure date of {self._departure.isoformat()} '\\n f'for pet {self.animal_id} with {when.isoformat()}'\\n )\\n\\n self._departure = when\\n if self.intake_date and self.intake_date != \\\"NULL\\\" and self._departure != \\\"NULL\\\":\\n self._adoption_time = self._departure - self.intake_date\",\n \"def _check_date(self):\\n\\n limit_hours = self.env.user.company_id.product_rejected_limit_hours\\n if limit_hours > 0:\\n\\n for record in self:\\n\\n if record.partner_id:\\n last_record = self.search([\\n ('id', '!=', record.id),\\n ('product_id', '=', record.product_id.id),\\n ('partner_id', '=', record.partner_id.id),\\n ('company_id', '=', self.env.user.company_id.id),\\n ], order='date')\\n\\n if last_record:\\n last_record_date = last_record[-1].date\\n last_record_datetime = datetime.strptime(\\n last_record_date, '%Y-%m-%d %H:%M:%S')\\n record_date = datetime.strptime(\\n record.date, '%Y-%m-%d %H:%M:%S')\\n\\n diff = record_date - last_record_datetime\\n hours_diff = (diff.seconds / 60.0) / 60\\n\\n if hours_diff <= limit_hours:\\n raise ValidationError(\\n _('This product rejected has already been registered for this same partner in the last %s hours.' % limit_hours)\\n )\",\n \"def _check_data_continuity(self):\\n dates = list(self.data.open_date.unique())\\n dates.sort()\\n\\n f = lambda x : tb.DateConvert(x).datetime\\n dates = list(map(f, dates))\\n\\n delta = []\\n for i, _ in enumerate(dates, start=1):\\n if i < len(dates):\\n delta.append(dates[i]-dates[i-1])\\n\\n if len(pd.unique(delta)) > 1:\\n raise DiscontinuousError(\\n 'There appear to be missing dates in the market data.'\\n )\",\n \"def _checkstate(self, queryset):\\n for presup in queryset.filter(estado='borrador').exclude(fecha_realizado=None):\\n if ((presup.fecha_realizado + timedelta(days=21) < datetime.now().date() and presup.tipo != 'asistencia') or\\n (presup.fecha_realizado + timedelta(days=60) < datetime.now().date() and presup.tipo == 'asistencia')):\\n presup._toState_cancelado(obs=\\\"Registro automático: Presupuesto vencido\\\")\",\n \"def is_before(self,other_date):\",\n \"def __data_set_is_payday_negative_16_17_18(cls):\\n _pay_cycle_object = pay_cycle_object()\\n date_to_check = date_class(2019,1,24) # The day before first payday\\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\\n\\n date_to_check = date_class(2018,12,27)\\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\\n\\n date_to_check = date_class(2018,2,28)\\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\",\n \"def in_past(self):\\n return self.election_date < datetime.date.today()\",\n \"def doAdjustmentBeforeForecast(startDate : dt.datetime, endDate :dt.datetime, configDict:dict)->bool:\\n conString:str = configDict['con_string_mis_warehouse']\\n isAdjustmentSuccesscount = 0\\n currDate = startDate\\n #create object of class Adjustment\\n obj_adjustment = Adjustment(conString)\\n\\n while currDate <= endDate:\\n isAdjustmentSuccess = obj_adjustment.doAdjustment(currDate)\\n if isAdjustmentSuccess:\\n isAdjustmentSuccesscount = isAdjustmentSuccesscount + 1\\n currDate += dt.timedelta(days=1)\\n\\n numOfDays = (endDate-startDate).days\\n if isAdjustmentSuccesscount == numOfDays +1 :\\n return True\\n else:\\n return False\",\n \"def periodCheck(data):\",\n \"def conference_departure_at(self, date_time: datetime.datetime):\\n self.add_not_available(start=date_time)\",\n \"def _set_days_until_triage(self):\\n if self.sla_triaged_at:\\n btd = dates.businesstimedelta(self.created_at, self.sla_triaged_at)\\n self.days_until_triage = btd.days\\n else:\\n self.days_until_triage = None\",\n \"def checkValidDate(self, nextDate, startDate):\\n\\t\\tcurrentDay = nextDate.day\\n\\t\\tcurrentMonth = nextDate.month\\n\\t\\tcurrentYear = nextDate.year\\n\\t\\t\\n\\t\\tstartDay = startDate.day\\n\\t\\tcurrentDate = datetime.datetime(currentYear, currentMonth, startDay)\\n\\t\\t\\n\\t\\tminDaysDiff = 99\\n\\t\\tresult = None\\n\\t\\t\\n\\t\\tfor dataPoint in self.dataPoints:\\n\\t\\t\\tdataPointDate = dataPoint.getDate()\\n\\t\\t\\tdaysDiff = (dataPointDate - currentDate).days\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\tif daysDiff == 0:\\n\\t\\t\\t\\treturn dataPointDate\\n\\t\\t\\telif daysDiff >= 0 and daysDiff < minDaysDiff:\\n\\t\\t\\t\\tminDaysDiff = daysDiff\\n\\t\\t\\t\\tresult = dataPointDate\\n\\t\\treturn result\",\n \"def _recompute(self):\\n current_date = self.start_date\\n self.quarterly_date_list = []\\n self.daily_date_list = []\\n while current_date <= self.end_date:\\n current_quarter = get_quarter(current_date)\\n current_year = current_date.year\\n next_year, next_quarter = add_quarter(current_year, current_quarter)\\n next_start_quarter_date = date(next_year, get_month(next_quarter),\\n 1)\\n\\n days_till_next_quarter = (next_start_quarter_date -\\n current_date).days\\n days_till_end = (self.end_date - current_date).days\\n if days_till_next_quarter <= days_till_end:\\n current_start_quarter_date = date(current_year,\\n get_month(current_quarter), 1)\\n if current_start_quarter_date == current_date:\\n self.quarterly_date_list.append(\\n (current_year, current_quarter, lambda x: True))\\n current_date = next_start_quarter_date\\n elif days_till_next_quarter > self.balancing_point:\\n self.quarterly_date_list.append(\\n (current_year, current_quarter,\\n lambda x: date(x['date_filed']) >= self.start_date))\\n current_date = next_start_quarter_date\\n else:\\n while current_date < next_start_quarter_date:\\n self.daily_date_list.append(current_date)\\n current_date += timedelta(days=1)\\n else:\\n if days_till_end > self.balancing_point:\\n if days_till_next_quarter - 1 == days_till_end:\\n self.quarterly_date_list.append(\\n (current_year, current_quarter, lambda x: True))\\n current_date = next_start_quarter_date\\n else:\\n self.quarterly_date_list.append(\\n (current_year, current_quarter,\\n lambda x: date(x['date_filed']) <= self.end_date))\\n current_date = self.end_date\\n else:\\n while current_date <= self.end_date:\\n self.daily_date_list.append(current_date)\\n current_date += timedelta(days=1)\",\n \"def filter_according_to_travel_day(self,day):\\n \\\"\\\"\\\"First check it the data has any mising values\\\"\\\"\\\"\\n dataset = os.path.abspath('./dataset/train_revised.csv')\\n if not self.check_for_missing_values(dataset):\\n #Understand the dataset\\n # self.understand_the_data(self.df)\\n # Transform the travel date column to date time values to be accessedby dt\\n self.df['travel_date'] = pd.to_datetime(self.df['travel_date'])\\n # Get the respective day of the week and store it in a new column\\n self.df['day_of_week'] = self.df['travel_date'].dt.day_name()\\n # Drop all rows where the day was not the day passed:Sunday\\n self.df.drop(self.df[self.df['day_of_week'] != day].index, axis=0, inplace=True)\\n return self.df\",\n \"def validate_departure_date(self,data):\\n print(data)\\n min_date = timezone.now()+ timedelta(minutes=10)\\n if data <=min_date:\\n raise serializers.ValidationError(\\n 'Departure time must be at least pass the next 20 minutes window'\\n )\\n return data\",\n \"def test_is_payday_negative1(self):\\n date_to_check = date_class(2020,12,25)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == False\\n\\n date_to_check = date_class(2021,12,24)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == False\\n\\n date_to_check = date_class(2022,11,11)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == False\",\n \"def check_dataset_dates(self):\\n # TODO: graph traverse and date checking\\n pass\",\n \"def getMaximumPreviousPrice(self, departureDate, state, datas):\\n specificDatas = []\\n specificDatas = [data for data in datas if data[\\\"Date\\\"]==departureDate]\\n\\n maximumPreviousPrice = util.getPrice(specificDatas[0][\\\"MinimumPrice\\\"])\\n for data in specificDatas:\\n if util.getPrice(data[\\\"MinimumPrice\\\"]) > maximumPreviousPrice and data[\\\"State\\\"]>=state:\\n maximumPreviousPrice = util.getPrice(data[\\\"MinimumPrice\\\"])\\n\\n return maximumPreviousPrice\",\n \"def ElectionAfterStart(obj):\\n if obj.election_date >= obj.start_date:\\n raise interface.Invalid(\\n _(\\\"A parliament has to be elected before it can be sworn in\\\"), \\n \\\"election_date\\\", \\n \\\"start_date\\\")\",\n \"def is_outdated(self):\\n today = datetime.datetime.today()\\n day = datetime.datetime.combine(self.date, self.start_time)\\n return day <= today\",\n \"def getMinimumPreviousPrice(self, departureDate, state, datas):\\n specificDatas = []\\n specificDatas = [data for data in datas if data[\\\"Date\\\"]==departureDate]\\n\\n minimumPreviousPrice = util.getPrice(specificDatas[0][\\\"MinimumPrice\\\"])\\n for data in specificDatas:\\n if util.getPrice(data[\\\"MinimumPrice\\\"]) < minimumPreviousPrice and data[\\\"State\\\"]>=state:\\n minimumPreviousPrice = util.getPrice(data[\\\"MinimumPrice\\\"])\\n\\n return minimumPreviousPrice\",\n \"def enough_days(self, cur, username, start_date, end_date):\\n cur.execute('SELECT days_free FROM users WHERE username = ?', (username,))\\n days_free = cur.fetchone()[0]\\n days_between = abs(self.days_difference(start_date, end_date))\\n return days_free >= days_between\",\n \"def _check_day_data(self, datetime):\\n if self.curr_day_data is None or self.compare_dates(self.curr_day_data.index[0], datetime) is False:\\n date = dt.datetime(year=datetime.year, month=datetime.month, day=datetime.day)\\n symbols = [product.symbol for product in self.products]\\n self.curr_day_data = get_data_multi(symbols, date, second_bars=self.second_bars)\\n self.clear_resting_orders()\",\n \"def test_is_payday_negative2(self):\\n date_to_check = date_class(2018,11,23)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == False\\n\\n date_to_check = date_class(2019,1,18)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == False\\n\\n date_to_check = date_class(2021,12,17)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == False\",\n \"def _first_good_date(self, day):\\n count = 0\\n while True:\\n try:\\n self.data.loc[day - timedelta(count)]\\n return day - timedelta(count)\\n except KeyError:\\n count += 1\",\n \"def _check_date_not_in_future(self, date):\\n if date is None:\\n pass\\n else:\\n assert (\\n date <= datetime.datetime.now()\\n ), \\\"Provided date cannot be in the future\\\"\",\n \"def new_day(self):\\n self.previous_days.append(self.energy_debt)\\n self.energy_debt = defaultdict(lambda: 0.0)\\n\\n #TODO: add the settelement mechanism here\",\n \"def test_new_items_have_equal_higher_dates(self):\\n input_ = [\\n self.indicator_record(date=datetime.date(2014, 2, 24),\\n end_date=datetime.date(2014, 3, 24),\\n value=0.0000),\\n self.indicator_record(date=datetime.date(2014, 2, 25),\\n end_date=datetime.date(2014, 3, 25),\\n value=0.0007),\\n ]\\n records = self.expander._daily_three_field_indicator_expander(input_)\\n increasing_days = [records[index_].date <= record.date and\\n records[index_].end_date <= record.end_date\\n for index_, record in enumerate(records[1:])]\\n\\n self.assertTrue(all(increasing_days))\",\n \"def service_currently_down(self):\\n\\n return self.end_time and self.start_time <= self.local_tz.localize(datetime.now()) <= self.end_time\",\n \"def prior_determination_date(ddates,clo_idx):\\n dd = ddates.loc[ddates['Fund']==clo_idx,'Determination Date']\\n prior_ddate = max(dd.loc[dd<pd.Timestamp.today()], key=lambda s: (s-pd.Timestamp.today()))\\n return prior_ddate\",\n \"def get_today():\\n global endDate\\n check_today=date_trans_x(time.strftime(\\\"%Y.%m.%d\\\"))\\n if(get_article_ammount(check_today,True)>0): \\n diff=datetime.strptime(check_today,'%Y.%m.%d')-datetime.strptime(endDate,'%Y.%m.%d')\\n if(diff.total_seconds()>=0):\\n endDate=check_today\\n print \\\"get_today : \\\"+ check_today\\n return check_today\\n else:\\n print \\\"get_today : \\\"+ endDate\\n return endDate\",\n \"def _is_eruption_in(self, days, from_time):\\n for te in self.tes:\\n if 0 < (te-from_time).total_seconds()/(3600*24) < days:\\n return 1.\\n return 0.\",\n \"def is_upcoming(self):\\n\\n return timezone.now() < self.start < timezone.now() + timedelta(days=1)\",\n \"def test_07_no_future_records(self):\\n bad_date = timezone.now() + timedelta(days=1)\\n record = SwimRecord(record_date=bad_date)\\n try:\\n record.full_clean()\\n except ValidationError as e:\\n self.assertTrue(\\\"Can't set record in the future.\\\" in e.message_dict['record_date'])\",\n \"def _checkDT(self):\\r\\n dt = np.diff(self.tsec)\\r\\n \\r\\n dt_unique = np.unique(dt)\\r\\n \\r\\n if np.size(dt_unique) == 1:\\r\\n self.isequal = True\\r\\n else:\\r\\n self.isequal = False\\r\\n \\r\\n try:\\r\\n self.dt = dt[1]\\r\\n except:\\r\\n self.dt = 0.0\",\n \"def _onchange_date_from(self):\\n\\t\\tdate_from = self.date_from\\n\\t\\tdate_to = self.date_to\\n\\t\\tself.compute_valid_leaves_for_employee(date_from, date_to)\\n\\n\\t\\t# policy_id = self.env['leaves.policy'].sudo().search(\\n\\t\\t# \\t[('leave_type', '=', self.holiday_status_id.id), ('company_id', '=', self.env.user.company_id.id)])\\n\\t\\t# if date_from and not date_to:\\n\\t\\t# \\tdate_to_with_delta = fields.Datetime.from_string(date_from) + timedelta(hours=8)\\n\\t\\t# \\tself.date_to = str(date_to_with_delta)\\n\\t\\t# \\tnumber_of_day = (datetime.strptime(self.date_to, DEFAULT_SERVER_DATETIME_FORMAT) - datetime.strptime(date_from, DEFAULT_SERVER_DATETIME_FORMAT)).total_seconds()/(24*3600)\\n\\t\\t# \\tself.number_of_days_temp = number_of_day\\n\\t\\t# # Compute and update the number of days\\n\\t\\t# if (date_to and date_from) and (date_from <= date_to):\\n\\t\\t# \\tif policy_id:\\n\\t\\t# \\t\\tfor val in policy_id:\\n\\t\\t# \\t\\t\\tnumber_of_days = 0\\n\\t\\t# \\t\\t\\tif val.weekends_leave_period == 'dont_count':\\n\\t\\t# \\t\\t\\t\\tnum_days = self._get_number_of_days(date_from, date_to, self.employee_id.id)\\n\\t\\t# \\t\\t\\t\\tdate_to1 = datetime.strptime(date_to, '%Y-%m-%d %H:%M:%S')\\n\\t\\t# \\t\\t\\t\\tdate_from1 = datetime.strptime(date_from, '%Y-%m-%d %H:%M:%S')\\n\\t\\t#\\n\\t\\t# \\t\\t\\t\\t# Logic of Public Holidays when week offs count as holidays is True 2019-11-19\\n\\t\\t# \\t\\t\\t\\temp_shift = self.employee_id.resource_calendar_ids\\n\\t\\t# \\t\\t\\t\\tglobal_leaves = emp_shift.global_leave_ids\\n\\t\\t# \\t\\t\\t\\t# List to store the global leaves\\n\\t\\t# \\t\\t\\t\\tpublic_holidays = []\\n\\t\\t# \\t\\t\\t\\tfor holiday in global_leaves:\\n\\t\\t# \\t\\t\\t\\t\\tpublic_holidays.append((holiday.date_from, holiday.date_to))\\n\\t\\t#\\n\\t\\t# \\t\\t\\t\\t# Public holidays between leave period\\n\\t\\t# \\t\\t\\t\\tleave_period_dates = []\\n\\t\\t# \\t\\t\\t\\tstart_date = date_from1.date()\\n\\t\\t# \\t\\t\\t\\tend_date = date_to1.date()\\n\\t\\t# \\t\\t\\t\\tdelta = end_date - start_date\\n\\t\\t# \\t\\t\\t\\tfor i in range(delta.days + 1):\\n\\t\\t# \\t\\t\\t\\t\\tday = start_date + timedelta(days=i)\\n\\t\\t# \\t\\t\\t\\t\\tleave_period_dates.append(day)\\n\\t\\t# \\t\\t\\t\\tcount = 0\\n\\t\\t# \\t\\t\\t\\tfor date in public_holidays:\\n\\t\\t# \\t\\t\\t\\t\\tif datetime.strptime(date[0], '%Y-%m-%d %H:%M:%S').date() in leave_period_dates:\\n\\t\\t# \\t\\t\\t\\t\\t\\tcount += 1\\n\\t\\t# \\t\\t\\t# End of Public Holidays logic\\n\\t\\t#\\n\\t\\t# \\t\\t\\t\\tself.number_of_days_temp = num_days - count\\n\\t\\t# \\t\\t\\telse:\\n\\t\\t# \\t\\t\\t\\tnumber_of_days = self._get_number_of_days(date_from, date_to, self.employee_id.id)\\n\\t\\t# \\t\\t\\t\\tdate_to1 = datetime.strptime(date_to, '%Y-%m-%d %H:%M:%S')\\n\\t\\t# \\t\\t\\t\\tdate_from1 = datetime.strptime(date_from, '%Y-%m-%d %H:%M:%S')\\n\\t\\t# \\t\\t\\t\\tif val.dur_full and not val.dur_half:\\n\\t\\t# \\t\\t\\t\\t\\ttotal_days = (date_to1 - date_from1).days\\n\\t\\t# \\t\\t\\t\\telse:\\n\\t\\t# \\t\\t\\t\\t\\ttotal_seconds = (date_to1 - date_from1).seconds\\n\\t\\t# \\t\\t\\t\\t\\ttotal_days = total_seconds / (24 * 3600)\\n\\t\\t#\\n\\t\\t# \\t\\t\\t\\tweek_offs = total_days - number_of_days\\n\\t\\t# \\t\\t\\t\\tself.number_of_days_temp = number_of_days + week_offs\\n\\t\\t# \\telse:\\n\\t\\t# \\t\\t# self.number_of_days_temp = self._get_number_of_days(date_from, date_to, self.employee_id.id)\\n\\t\\t# \\t\\tnumber_of_day = (datetime.strptime(self.date_to, DEFAULT_SERVER_DATETIME_FORMAT) - datetime.strptime(\\n\\t\\t# \\t\\t\\tdate_from, DEFAULT_SERVER_DATETIME_FORMAT)).total_seconds() / (24 * 3600)\\n\\t\\t# \\t\\tself.number_of_days_temp = number_of_day\\n\\t\\t#\\n\\t\\t# elif (date_to and date_from) and (date_from > date_to):\\n\\t\\t# \\traise ValidationError(\\\"From Date cannot be greater then To Date\\\")\\n\\t\\t# else:\\n\\t\\t# \\tself.number_of_days_temp = 0\",\n \"def check_market_status():\\n # today = datetime.datetime.now(pytz.timezone('America/New_York')).date()\\n today_utc = pd.to_datetime('now').date()\\n ndq = mcal.get_calendar('NASDAQ')\\n open_days = ndq.schedule(start_date=today_utc - pd.Timedelta('10 days'), end_date=today_utc)\\n if today_utc in open_days.index:\\n return open_days\\n else:\\n return None\",\n \"def test_is_payday_positive_25(self):\\n expected_count = 3\\n expected_paydays = [\\n date_class(2020,10,2), \\n date_class(2020,10,16), \\n date_class(2020,10,30)\\n ]\\n\\n curr_date = date_class(2020,10,1)\\n end_date = date_class(2020,10,31)\\n paydays = []\\n\\n while curr_date <= end_date:\\n is_payday = pay_cycle_object().is_payday(curr_date)\\n if is_payday: \\n paydays.append(curr_date)\\n curr_date += timedelta(days=1)\\n\\n assert len(paydays) == expected_count, \\\\\\n f'Got {len(paydays)}, expected {expected_count}'\\n assert paydays == expected_paydays, \\\\\\n f'Got {paydays}, expected {expected_paydays}'\",\n \"def __data_set_is_payday_negative_22_23_24(cls):\\n _pay_cycle_object = pay_cycle_object()\\n date_to_check = date_class(2018,11,23)\\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\\n\\n date_to_check = date_class(2019,1,18)\\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\\n\\n date_to_check = date_class(2021,12,17)\\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\",\n \"def compute_prev_fy_performance(self):\\n PrevFY = self.env['%s.prev.fy.view' % self._name]\\n PrevFY._fill_prev_fy_performance(self) # self = plans\",\n \"def test_is_payday_negative0(self):\\n date_to_check = date_class(2019,1,24)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == False\\n\\n date_to_check = date_class(2018,12,27)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == False\\n\\n date_to_check = date_class(2018,2,28)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == False\",\n \"def change_possible(self, departure_time):\\r\\n if (departure_time >= self.min_departure_time) and (departure_time <= self.max_departure_time):\\r\\n return True\\r\\n\\r\\n return False\",\n \"def good_standing(self):\\n # Date of last AR or founding date if they haven't yet filed one\\n last_ar_date = self.last_ar_date or self.founding_date\\n # Good standing is if last AR was filed within the past 1 year, 2 months and 1 day\\n return last_ar_date + datedelta.datedelta(years=1, months=2, days=1) > datetime.utcnow()\",\n \"def DissolutionAfterReinstatement(obj):\\n if (obj.dissolution_date is None) or (obj.reinstatement_date is None): \\n return\\n if obj.dissolution_date > obj.reinstatement_date:\\n raise interface.Invalid(\\n _(\\\"A committee must be disolved before it can be reinstated\\\"), \\n \\\"dissolution_date\\\", \\n \\\"reinstatement_date\\\")\",\n \"def _check_dates(self):\\n for record in self:\\n if record.end_date and record.end_date < record.start_date:\\n raise exceptions.Warning(\\n _('Agreement end date must be greater than start date'))\",\n \"def _check_dates(self, cr, uid, ids, context=None):\\n for act in self.browse(cr, uid, ids, context):\\n date_from = self.get_date(act.date_from)\\n date_to = self.get_date(act.date_to)\\n previous_ids = self.search(cr, uid, [('id','!=',act.id), ('alternative_setting_id','=',act.alternative_setting_id.id)],context=context)\\n dates = self.read(cr, uid, previous_ids, ['date_from','date_to'], context=context)\\n\\n dates = [{'date_from':self.get_date(x['date_from']),'date_to':self.get_date(x['date_to'])} for x in dates]\\n for date in dates:\\n case0 = date['date_from'] >= date_from and date['date_to'] <= date_to\\n\\n case1 = date['date_from'] <= date_from and date['date_to'] >= date_to\\n\\n case2 = date['date_from'] <= date_from and date_from <= date['date_to'] \\n\\n case3 = date_from <= date['date_from'] and date['date_from'] <= date_to\\n \\n if case0 or case1 or case2 or case3:\\n raise osv.except_osv(_('Error'), _(\\\"THIS RANGE OF DATE HAVE BEEN FETCHED BEFORE\\\"))\\n return True\",\n \"def test_holidays():\\n\\n assert not datetime.datetime(2003, 12, 25) in TRADING_DATES\\n assert not datetime.datetime(2003, 5, 26) in TRADING_DATES # memorial day\",\n \"def test_date_accept_yesterday(self):\\n import dateutil.relativedelta\\n spi_search = \\\"find date yesterday\\\"\\n inv_search = \\\"year:\\\" + datetime.datetime.strftime(datetime.datetime.today()+dateutil.relativedelta.relativedelta(days=-1), '%Y-%m-%d')\\n self._compare_searches(inv_search, spi_search)\",\n \"def period_check(init_dates, fcst_dates):\\n check_dates(init_dates)\\n check_dates(fcst_dates)\\n \\n if max(init_dates) > min(fcst_dates):\\n raise ValueError('Forecast date, %s comes before initialisation '\\\\\\n 'date, %s.' % (min(fcst_dates), max(init_dates)))\\n\\n fcst_dates = change_zeroth_hour(fcst_dates)\\n return init_dates, fcst_dates\",\n \"def check_changes(yield_curve, forecast):\\r\\n df = pd.read_csv('data/diff_df.csv').set_index('DATE')\\r\\n if list(df.index)[-1] != list(yield_curve.index)[-1]:\\r\\n forecast = pd.read_csv('data/forecast.csv')\\r\\n yield_curve = df\",\n \"def test_fall_back(self):\\n # Exact crossover time:\\n # datetime.datetime(2011, 11, 6, 2, 0, 0, tzinfo=pytz.utc)\\n # This test will use times on either side of it.\\n\\n # From the PDT vantage point, the run time is 24.2 and 48.2 hours away:\\n s1a, s1b = self.hours_to_job_at_datetime(\\n 'tz_test_job', 2011, 11, 6, 0, 50, 0)\\n\\n # From the PST vantage point, the run time is 21.8 and 45.8 hours away:\\n s2a, s2b = self.hours_to_job_at_datetime(\\n 'tz_test_job', 2011, 11, 6, 2, 10, 0)\\n\\n # Make sure the measurements are consistent for each vantage point,\\n # meaning that each run is 24 hours apart no matter where you measure\\n # from, even if the start time appears different for each vantage\\n # point.\\n self._assert_range(s1b - s1a, 23.99, 24.01)\\n self._assert_range(s2b - s2a, 23.99, 24.01)\\n\\n # Start times should differ by 2.4 hours.\\n self._assert_range(s1a - s2a, 2.39, 2.41)\",\n \"def _check_dates_tarea_start(self, cr, uid, ids, context=None):\\n for leave in self.read(cr, uid, ids, ['date_start_tarea', 'date_start_proyecto'], context=context):\\n if leave['date_start_tarea'] and leave['date_start_proyecto']:\\n if leave['date_start_tarea'] < leave['date_start_proyecto']:\\n return False\\n return True\",\n \"def check(self):\\n validity_year = int(self.date[0:4])\\n validity_month = int(self.date[5:7])\\n validity_day = int(self.date[8:10])\\n if datetime.today().year > validity_year:\\n self.flag = False\\n elif datetime.today().year == validity_year:\\n if datetime.today().month > validity_month:\\n self.flag = False\\n elif datetime.today().month == validity_month:\\n if datetime.today().day > validity_day:\\n self.flag = False\\n else:\\n self.flag = True\\n else:\\n self.flag = True\\n else:\\n self.flag = True\",\n \"def clean(self):\\n\\t\\tlogging.info(\\\"Checking week for old days\\\")\\n\\t\\ttoday = datetime.now().date()\\n\\t\\tfor i,d in enumerate(self.days):\\n\\t\\t\\tif d is not None and today-d.date > timedelta(7):\\n\\t\\t\\t\\tself.days[i] = None\\n\\t\\t\\t\\tlogging.info(\\\"Deleting old workday from %d/%d in slot %d\\\" \\\\\\n\\t\\t\\t\\t\\t% (d.date.month, d.date.day, i)\\n\\t\\t\\t\\t\\t)\",\n \"def test_is_payday_positive2(self):\\n date_to_check = date_class(2019,11,1)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == True\\n\\n date_to_check = date_class(2019,11,29)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == True\\n\\n date_to_check = date_class(2019,12,13)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == True\",\n \"def check_sequence_for_days(self):\\n # delta = (max(self.giorni) - min(self.giorni)).days + 1 # the difference returns a timedelta\\n try:\\n delta = abs(max(self.giorni).daysTo(min(self.giorni))) + 1\\n if delta != len(self.giorni):\\n raise ValidationError('dates need to be in sequence')\\n except ValueError as e:\\n return print(e)\",\n \"def is_before_eof_finals_week(now, request):\\n logger.debug(\\\"{} is_before_eof_finals_week {} ==> {}\\\".format(\\n now, get_eod_current_term_last_final_exam(request),\\n now < get_eod_current_term_last_final_exam(request)))\\n return now < get_eod_current_term_last_final_exam(request)\",\n \"def _check_dates(self, cr, uid, ids, context=None):\\n for act in self.browse(cr, uid, ids, context):\\n date_from = self.get_date(act.date_from)\\n date_to = self.get_date(act.date_to)\\n previous_ids = self.search(cr, uid, [('id','!=',act.id)],context=context)\\n dates = self.read(cr, uid, previous_ids, ['date_from','date_to'], context=context)\\n\\n dates = [{'date_from':self.get_date(x['date_from']),'date_to':self.get_date(x['date_to'])} for x in dates]\\n for date in dates:\\n case0 = date['date_from'] >= date_from and date['date_to'] <= date_to\\n\\n case1 = date['date_from'] <= date_from and date['date_to'] >= date_to\\n\\n case2 = date['date_from'] <= date_from and date_from <= date['date_to'] \\n\\n case3 = date_from <= date['date_from'] and date['date_from'] <= date_to\\n \\n if case0 or case1 or case2 or case3:\\n raise osv.except_osv(_('Error'), _(\\\"THIS RANGE OF DATE HAVE BEEN FETCHED BEFORE\\\"))\\n return True\",\n \"def test_check_date_tour(self):\\n date_start = timezone.now()\\n date_end = timezone.now() - timedelta(days=5)\\n new_tour = Tournament(date_start=date_start, date_end=date_end)\\n\\n self.assertEqual(new_tour.check_date(), False)\",\n \"def __data_set_is_payday_negative_19_20_21(cls):\\n _pay_cycle_object = pay_cycle_object()\\n date_to_check = date_class(2020,12,25) # Christmas\\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\\n\\n date_to_check = date_class(2021,12,24)\\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\\n\\n date_to_check = date_class(2022,11,11)\\n cls.TEST_DATA_SET.append((_pay_cycle_object, date_to_check, False))\",\n \"def previous_date(date):\\n #This function is basically the same as the next_date function, except I subtracted 1 instead of adding 1.\\n #The main difference was figuring out what to do when transitioning to a different month with a different amount of days.\\n #This is why August, for example, is in it's own if else statement; most 31 day months go backwards into a 30 day month.\\n #August, however, transitions into July, which is another 31 day month. Because of this, I needed to create a case just for August.\\n #I used the same thought process for the other monthly transitions, as well as the year transition (1-1-XXXX -> 12-31-XXX(X-1))\\n if date[0] == 5 or date[0] == 7 or date[0] == 10 or date[0] == 12:\\n if date[1] > 1:\\n prevday = (date[0], date[1] - 1, date[2])\\n return prevday\\n elif date[1] == 1:\\n prevday = (date[0] - 1, 30, date[2])\\n return prevday\\n elif date[0] == 8:\\n if date[1] > 1:\\n prevday = (date[0], date[1] - 1, date[2])\\n return prevday\\n elif date[1] == 1:\\n prevday = (date[0] - 1, 31, date[2])\\n return prevday\\n elif date[0] == 1:\\n if date[1] > 1:\\n prevday = (date[0], date[1] - 1, date[2])\\n return prevday\\n elif date[1] == 1:\\n prevday = (12, 31, date[2] - 1)\\n return prevday\\n elif date[0] == 4 or date[0] == 6 or date[0] == 9 or date[0] == 11:\\n if date[1] > 1:\\n prevday = (date[0], date[1] - 1, date[2])\\n return prevday\\n elif date[1] == 1:\\n prevday = (date[0] - 1, 31, date[2])\\n return prevday\\n elif date[0] == 3:\\n if date[2] % 4 == 0 or date[2] % 1000 == 0:\\n if date[1] > 1:\\n prevday = (date[0], date[1] - 1, date[2])\\n return prevday\\n elif date[1] == 1:\\n prevday = (2, 29, date[2])\\n return prevday\\n elif date[1] > 1:\\n prevday = (date[0], date[1] - 1, date[2])\\n return prevday\\n elif date[1] == 1:\\n prevday = (date[0] - 1, 28, date[2])\\n return prevday\\n elif date[0] == 2:\\n if date[1] > 1:\\n prevday = (date[0], date[1] - 1, date[2])\\n return prevday\\n elif date[1] == 1:\\n prevday = (date[0] - 1, 31, date[2])\\n return prevday\",\n \"def check_market_status():\\n today_ny = datetime.datetime.now(pytz.timezone('America/New_York'))\\n ndq = mcal.get_calendar('NASDAQ')\\n open_days = ndq.schedule(start_date=today_ny - pd.Timedelta('10 days'), end_date=today_ny)\\n if today_ny.date() in open_days.index:\\n return open_days\\n else:\\n return None\",\n \"def test_is_payday_positive3(self):\\n date_to_check = date_class(2020,1,10)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == True\\n\\n date_to_check = date_class(2020,1,24)\\n is_payday = self.pay_cycle.is_payday(date_to_check)\\n assert is_payday == True\",\n \"def get_next_departure(self,day,link,current_time): \\n if link not in self.data[day]:\\n return None\\n import numpy as np\\n index=[np.searchsorted(self.data[day][link][0:,0],current_time)]\\n print(len(self.data[day][link]))\\n print(index) \\n if index[0] < len(self.data[day][link]):\\n return self.data[day][link][index[0]]\\n else:\\n return None\",\n \"async def test_source_up_to_dateness(self):\\n self.set_source_parameter(\\\"date\\\", \\\"2019-06-01\\\")\\n response = await self.collect()\\n self.assert_measurement(response, value=str((datetime.now() - datetime(2019, 6, 1)).days))\",\n \"def yesterday(self):\\n if self.isLeapYear():\\n fdays = 29\\n else:\\n fdays = 28\\n\\n DIM = [0, 31, fdays, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]\\n\\n currentDay = self.day\\n firstMonth = 1\\n firstDay = 1\\n\\n if currentDay == firstDay and self.month == firstMonth:\\n self.year -= 1\\n self.month = 12\\n self.day = 31\\n elif currentDay == firstDay:\\n self.month -= 1\\n self.day = DIM[self.month]\\n else:\\n self.day -= 1\",\n \"def trade_position_effective_date_valid(record):\\n knowledge_date = record['knowledge_date']\\n effective_date = record['effective_date']\\n assert effective_date == knowledge_date + timedelta(days=2)\",\n \"def date_in_past(date: dt.datetime) -> bool:\\n return date < dt.datetime.now()\",\n \"def _departure_on_duty(self) -> bool:\\n return self._get_departure_shift().is_on_duty()\",\n \"def __find_previous_cf_element(self) -> LineElement:\\n index = (self.current_time_in_eighths - 1) // N_EIGHTHS_PER_MEASURE\\n result = self.cantus_firmus[index]\\n return result\",\n \"def condition(self, year, month, day, lastday, leapday):\\n try:\\n if len(day) == 0 or int(day) > int(lastday):\\n if int(month) == 2 and day == leapday:\\n Input.change_display(self, self.entries[4],\\n 'Not a leap year')\\n else:\\n Input.change_display(self, self.entries[4],\\n 'Enter day between 1-' + lastday)\\n elif int(day) <= int(lastday):\\n Input.change_display(self, self.entries[3], #Weekday message\\n Output.message(self, year, month, day))\\n except:\\n Input.change_display(self, self.entries[4],\\n 'Enter day between 1-' + lastday)\",\n \"def test_form_invalid_date_in_past(self):\\n login = self.client.login(\\n username='testuser2',\\n password='2HJ1vRV0Z&3iD')\\n past_date = datetime.date.today() - datetime.timedelta(days=1)\\n response = self.client.post(\\n reverse('librarian-renew-book',\\n kwargs={'pk': self.test_bookinstance2.pk}),\\n {'due_back': past_date})\\n self.assertEqual(response.status_code, 200)\\n self.assertFormError(response,\\n 'form',\\n 'due_back',\\n 'Invalid date - renewal in the past')\",\n \"def one_day(self):\\n return self.end.date() == self.date\",\n \"def CheckIfEarliestDeparture(ConnectionInfo, PathInfo):\\r\\n\\tif not hasattr(CheckIfEarliestDeparture, \\\"DepartureTimeDic\\\"):\\r\\n\\t\\tCheckIfEarliestDeparture.DepartureTimeDic = {}\\r\\n\\r\\n\\t# return True\\r\\n\\r\\n\\tcurr_station = ConnectionInfo[ConnInfoInd['station_from']]\\r\\n\\tnext_station = ConnectionInfo[ConnInfoInd['station_to']]\\r\\n\\r\\n\\tline_id = ConnectionInfo[ConnInfoInd['line_id']]\\r\\n\\t\\r\\n\\tNextLine = (curr_station, next_station, line_id)\\r\\n\\tdeparture_next_station = ConnectionInfo[ConnInfoInd['arrival_hour']]*60 + ConnectionInfo[ConnInfoInd['arrival_min']]\\r\\n\\r\\n\\tif CheckIfEarliestDeparture.DepartureTimeDic.has_key(next_station):\\r\\n\\t\\tearliest_departure = CheckIfEarliestDeparture.DepartureTimeDic[NextLine]\\r\\n\\r\\n\\t\\tif departure_next_station < earliest_departure:\\r\\n\\t\\t\\tCheckIfEarliestDeparture.DepartureTimeDic[NextLine] = departure_next_station\\r\\n\\t\\t\\tprint \\\"CheckIfEarliestDeparture: True\\\"\\r\\n\\t\\t\\treturn True\\r\\n\\t\\telse:\\r\\n\\t\\t\\tprint \\\"CheckIfEarliestDeparture: False\\\"\\r\\n\\t\\t\\treturn False\\r\\n\\telse:\\r\\n\\t\\tCheckIfEarliestDeparture.DepartureTimeDic[NextLine] = departure_next_station\\r\\n\\t\\treturn True\",\n \"def test_date_accept_date_minus_many_days(self):\\n spi_search = \\\"find date 2011-02-24 - 946\\\"\\n inv_search = \\\"year:2008-07-23\\\"\\n self._compare_searches(inv_search, spi_search)\",\n \"def get_days_delta(query):\\n # the format of delta: 18 days, 0:00:00\\n\\n try:\\n delta_string = str(get_date() - get_start_date(query)).split(' ')[0]\\n delta = int(delta_string)\\n\\n except TypeError as err:\\n \\\"\\\"\\\"\\n could get_start_date of contact because it hasn't been initialized.\\n \\\"\\\"\\\"\\n # print(\\\"the contact hasn't initialize the evaluation: \\\", err)\\n return None, err\\n\\n except ValueError as err:\\n \\\"\\\"\\\"\\n this exception is used to handle the first day record error.\\n minus the same dates will get \\\"0:00:00\\\".\\n \\\"\\\"\\\"\\n if delta_string == \\\"0:00:00\\\":\\n delta = 0\\n else:\\n # print(\\\"the date has some problem: \\\", err)\\n return None, err\\n return delta\",\n \"def prev(self):\\n return self.from_date(self.date_a - datetime.timedelta(1))\",\n \"def testPrevDayOfMonthWithCrossing(self):\\n base = datetime(2012, 3, 15, 0, 0)\\n itr = croniter('0 0 22 * *', base)\\n prev = itr.get_prev(datetime)\\n self.assertEqual(prev.year, 2012)\\n self.assertEqual(prev.month, 2)\\n self.assertEqual(prev.day, 22)\\n self.assertEqual(prev.hour, 0)\\n self.assertEqual(prev.minute, 0)\",\n \"def test_before():\\n date = datetime.datetime\\n\\n #july forth is this week\\n assert CALENDAR.nth_trading_day_before(3, date(2006, 7, 7)) == date(2006, 7, 3)\\n assert CALENDAR.nth_trading_day_before(0, date(2006, 7, 7)) == date(2006, 7, 7)\\n assert CALENDAR.nth_trading_day_before(0, date(2006, 7, 8)) == date(2006, 7, 7)\",\n \"def isOutOfDate(self):\\n cert = self.getLatestValidCertification()\\n today = date.today()\\n if cert and cert.getValidTo():\\n validto = cert.getValidTo().asdatetime().date();\\n if validto > today:\\n return False\\n return True\",\n \"def test_looking_back_to_prior_state(self):\\n schedule = parser.parse_schedule(SCHEDULE)\\n self.assertIsNone(schedule.get_latest_event(\\n dt(saturday, '09:30'), lookback=False))\\n self.assertEqual((dt(friday, '11:00'), \\\"c\\\"),\\n schedule.get_latest_event(dt(saturday, '09:30')))\",\n \"def test_date_accept_date_minus_days(self):\\n spi_search = \\\"find date 2011-01-03 - 2\\\"\\n inv_search = \\\"year:2011-01\\\"\\n self._compare_searches(inv_search, spi_search)\",\n \"def prev_quarter_boundaries(now):\\n first_of_month = datetime.datetime(now.year, now.month, 1)\\n\\n # 75 days before the 1st is always in the previous quarter\\n date_in_prev_q = first_of_month - datetime.timedelta(days=75)\\n\\n q_y = date_in_prev_q.year\\n q_start_m = int((date_in_prev_q.month-1) / 3)*3 + 1\\n q_end_m = q_start_m + 2\\n q_end_d = calendar.monthrange(q_y, q_end_m)[1]\\n\\n s_d = datetime.datetime(q_y, q_start_m, 1)\\n e_d = datetime.datetime(q_y, q_end_m, q_end_d)\\n\\n return s_d, e_d\",\n \"def previous(self):\\n try:\\n return self.filter(end_date__lt=self.current().start_date).latest()\\n except self.model.DoesNotExist:\\n return None\",\n \"def flag_day_if_not_enough_consecutive_days(self, min_number_days: int):\\n\\n for wearable in self.wearables.values():\\n\\n days = self.get_valid_days(wearable.get_pid())[wearable.get_pid()]\\n\\n if len(days) == 0:\\n continue\\n\\n s = sorted(days)\\n\\n consecutive = 1\\n last_value = s[0]\\n saved_so_far = [last_value]\\n okay = []\\n\\n for actual in s[1:]:\\n if actual == last_value + 1:\\n consecutive += 1\\n last_value = actual\\n saved_so_far.append(last_value)\\n\\n else:\\n # Ops! We found a gap in the sequence.\\n # First we check if we already have enough days:\\n if len(saved_so_far) >= min_number_days:\\n okay.extend(saved_so_far) # Cool! We have enough days.\\n\\n else: # Otherwise we start over\\n consecutive = 1\\n last_value = actual\\n saved_so_far = [last_value]\\n\\n if len(saved_so_far) >= min_number_days:\\n okay.extend(saved_so_far)\\n\\n # In the okay set, we have all days that we can keep.\\n new_invalid = set(days) - set(okay)\\n if new_invalid:\\n print(\\\"Flagging the following days as invalid for pid %s: %s\\\" % (\\n wearable.get_pid(), ','.join(map(str, new_invalid))))\\n\\n wearable.data.loc[wearable.data[wearable.get_experiment_day_col()].isin(\\n new_invalid), self.invalid_col] |= InvCode.FLAG_DAY_NOT_ENOUGH_CONSECUTIVE_DAYS\",\n \"def _deadline_same_day(self) -> pd.Timestamp:\\n # Get the workshift on the deadline\\n workshift = self._get_departure_shift()\\n\\n # Departure was on duty, see if there is enough time to meet deadline\\n if (\\n self._departure_on_duty()\\n and self.compare_shift(workshift, self._lt_sec()) > 0\\n ):\\n # There is enough time to schedule the loading on same workshift\\n return workshift.end_time - self.loading_time\\n elif self.compare_shift(workshift.rollback(1), self._lt_sec()) > 0:\\n # Not enough time to schedule loading same day so get previous on duty workshift\\n return workshift.rollback(1).end_time - self.loading_time\\n else:\\n # Departure was not on duty so get closest workshift\\n raise InvalidScheduleException(workshift.duration, self.loading_time)\",\n \"def revise_agreements_expirations_planned(self):\\n for agreement in self.search([('prolong', '=', 'unlimited')]):\\n if agreement.next_expiration_date <= fields.Date.today():\\n # force recalculate next_expiration_date\\n agreement.write({'prolong': 'unlimited'})\\n return True\",\n \"def test_new_items_have_increasing_dates(self):\\n input_ = [\\n self.indicator_record(date=datetime.date(2004, 11, 1), value=0.69),\\n self.indicator_record(date=datetime.date(2004, 12, 1), value=0.86),\\n self.indicator_record(date=datetime.date(2005, 1, 1), value=0.58),\\n ]\\n records = self.expander._ipca_from_15_expander(input_)\\n\\n self.assertTrue(records[-1].date > input_[-1].date)\",\n \"def check_day(self, day_of_week):\\n\\n day_of_week -= 1\\n if (day_of_week == -1):\\n self.day_of_week = 6\\n else:\\n self.day_of_week = day_of_week\",\n \"def createDayAheadForecast(startDate:dt.datetime ,endDate: dt.datetime, configDict:dict)->bool: \\n\\n \\n conString:str = configDict['con_string_mis_warehouse']\\n demandInsertionSuccessCount = 0\\n r0InsertionSuccessCount = 0\\n\\n #creating instance of classes\\n obj_demandFetchForAlgo = DemandFetchForAlgoRepo(conString)\\n obj_dayAheadDemandForecastInsertion = DayAheadDemandForecastInsertion(conString)\\n obj_r0ForecastInsertion = R0RevisionInsertion(conString)\\n \\n currDate = startDate\\n \\n # Iterating through each day and inserting day ahead forecasted demand of all entities \\n while currDate <= endDate:\\n\\n resultDict : IResultDict = obj_demandFetchForAlgo.fetchBlockwiseDemandForAlgo(currDate)\\n # print(data)\\n isForecastedDemandInsSuccess = obj_dayAheadDemandForecastInsertion.insertDayAheadDemandForecast(resultDict['demandData'])\\n if isForecastedDemandInsSuccess:\\n demandInsertionSuccessCount = demandInsertionSuccessCount + 1\\n \\n isR0InsertionSuccess = obj_r0ForecastInsertion.insertR0DemandForecast(resultDict['r0AData'])\\n if isR0InsertionSuccess:\\n r0InsertionSuccessCount += 1\\n\\n currDate += dt.timedelta(days=1)\\n \\n numOfDays = (endDate-startDate).days\\n\\n #checking whether data is inserted for each day or not\\n if demandInsertionSuccessCount == numOfDays +1 and r0InsertionSuccessCount == numOfDays +1:\\n return True\\n else:\\n return False\",\n \"def judge_today_point_give(self,uid,pid,gid=0):\\n early_night_timestamp = self.get_early_night_timestamp()\\n return self.find_db_sum('fs_point_from',uid=uid,pid=pid,gid=gid,time={'rule':'>','value':early_night_timestamp})\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.65856576","0.60677063","0.5963223","0.59185475","0.5852571","0.5852219","0.5837756","0.5755815","0.57509553","0.56721824","0.56598383","0.56210434","0.56133294","0.55789524","0.5559235","0.55514705","0.5542802","0.5537821","0.5515126","0.5511169","0.5470787","0.5467804","0.5461065","0.54463714","0.54382694","0.53769755","0.5374978","0.53573453","0.53401005","0.53377414","0.5326326","0.53070414","0.5302542","0.52901727","0.5287383","0.5280927","0.5265557","0.5259684","0.5254714","0.524852","0.5238575","0.52315515","0.52121586","0.52067965","0.5205626","0.51752007","0.5172167","0.5166015","0.51654106","0.51419264","0.51291656","0.5120027","0.51111156","0.50988096","0.50977343","0.50960815","0.5094844","0.5084161","0.50832933","0.5068127","0.50582546","0.5055168","0.5050377","0.5047973","0.5046899","0.50400335","0.50399834","0.5035714","0.5034264","0.50318336","0.5028829","0.50233746","0.50159174","0.5015039","0.5014593","0.5013514","0.50090677","0.5007546","0.5003173","0.50006956","0.4991741","0.4991469","0.49900448","0.49898878","0.49870124","0.498177","0.4979907","0.49771976","0.49745128","0.4974485","0.49706355","0.49687243","0.4965952","0.49618274","0.49600565","0.49596626","0.49567264","0.49554607","0.4955232","0.4949542"],"string":"[\n \"0.65856576\",\n \"0.60677063\",\n \"0.5963223\",\n \"0.59185475\",\n \"0.5852571\",\n \"0.5852219\",\n \"0.5837756\",\n \"0.5755815\",\n \"0.57509553\",\n \"0.56721824\",\n \"0.56598383\",\n \"0.56210434\",\n \"0.56133294\",\n \"0.55789524\",\n \"0.5559235\",\n \"0.55514705\",\n \"0.5542802\",\n \"0.5537821\",\n \"0.5515126\",\n \"0.5511169\",\n \"0.5470787\",\n \"0.5467804\",\n \"0.5461065\",\n \"0.54463714\",\n \"0.54382694\",\n \"0.53769755\",\n \"0.5374978\",\n \"0.53573453\",\n \"0.53401005\",\n \"0.53377414\",\n \"0.5326326\",\n \"0.53070414\",\n \"0.5302542\",\n \"0.52901727\",\n \"0.5287383\",\n \"0.5280927\",\n \"0.5265557\",\n \"0.5259684\",\n \"0.5254714\",\n \"0.524852\",\n \"0.5238575\",\n \"0.52315515\",\n \"0.52121586\",\n \"0.52067965\",\n \"0.5205626\",\n \"0.51752007\",\n \"0.5172167\",\n \"0.5166015\",\n \"0.51654106\",\n \"0.51419264\",\n \"0.51291656\",\n \"0.5120027\",\n \"0.51111156\",\n \"0.50988096\",\n \"0.50977343\",\n \"0.50960815\",\n \"0.5094844\",\n \"0.5084161\",\n \"0.50832933\",\n \"0.5068127\",\n \"0.50582546\",\n \"0.5055168\",\n \"0.5050377\",\n \"0.5047973\",\n \"0.5046899\",\n \"0.50400335\",\n \"0.50399834\",\n \"0.5035714\",\n \"0.5034264\",\n \"0.50318336\",\n \"0.5028829\",\n \"0.50233746\",\n \"0.50159174\",\n \"0.5015039\",\n \"0.5014593\",\n \"0.5013514\",\n \"0.50090677\",\n \"0.5007546\",\n \"0.5003173\",\n \"0.50006956\",\n \"0.4991741\",\n \"0.4991469\",\n \"0.49900448\",\n \"0.49898878\",\n \"0.49870124\",\n \"0.498177\",\n \"0.4979907\",\n \"0.49771976\",\n \"0.49745128\",\n \"0.4974485\",\n \"0.49706355\",\n \"0.49687243\",\n \"0.4965952\",\n \"0.49618274\",\n \"0.49600565\",\n \"0.49596626\",\n \"0.49567264\",\n \"0.49554607\",\n \"0.4955232\",\n \"0.4949542\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.57666147"},"document_rank":{"kind":"string","value":"7"}}},{"rowIdx":92989,"cells":{"query":{"kind":"string","value":"Converts a list of strings to a string by concatenating all elements of the list"},"document":{"kind":"string","value":"def collapse(L):\n output = \"\"\n for s in L:\n output = output + s\n return output"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def stringer(list):\n\tstring = \"\"\n\tfor x in list:\n\t\tstring = string + str(x)\n\treturn string","def list2string(a_list):\n\n the_string = ''\n for elem in a_list:\n the_string += str(elem)\n return the_string","def list_to_str(list_to_convert):\n return ' '.join(to_str(item) for item in list_to_convert)","def list_to_str(input_str):\r\n\r\n return \" \".join([str(val) for val in input_str])","def join_list(items: Iterable[str]) -> str:\n\n return ITEM_SEPARATOR.join(items)","def get_list_as_str(list_to_convert):\n return \", \".join([\"'{}'\".format(list_item) for list_item in list_to_convert])","def listToString(L):\r\n S = ''\r\n for x in L:\r\n S += str(x)\r\n return S","def list_join(the_list):\n return ' '.join(the_list)","def listtostring(self, charlist):\n s = \"\"\n for char in charlist:\n s += char\n return s","def list_to_str(\n l: list,\n c: str,\n ) -> str:\n\n s = c.join(map(str, l))\n\n return s","def concat_list(str_lst):\n concatenation = ''\n if len(str_lst) != 0:\n for string in str_lst:\n concatenation = concatenation + string\n return concatenation","def list_to_str( L ):\n if len(L) == 0: return ''\n return L[0] + list_to_str( L[1:] )","def list_to_str( L ):\n if len(L) == 0: return ''\n return L[0] + list_to_str( L[1:] )","def list_string(join_list):\n joined_list = '[{}]'.format(join_list, join_list)\n return joined_list","def listToStringFormat(self, list) ->str:\n string = ''\n for element in list:\n string = string + str(element) + \"\\n\"\n return string","def str_transform_list(L):\n return [str(x) for x in L]","def _convertListToString(self, list_of_objects):\n return (';').join(list_of_objects)","def list_str(lis):\r\n as_str = \"\"\r\n for item in lis:\r\n as_str += \" \" + str(item) + \",\"\r\n return as_str[:-1]","def list_to_str(a_list):\n new_str = \"\"\n for item in a_list:\n item = str(item).replace(\"\\'\", \"\\'\\'\")\n if new_str:\n new_str += \", '\" + item + \"'\"\n else:\n new_str = \"'\" + item + \"'\"\n return new_str","def listToString(s):\n # initialize an empty string\n str1 = \"\"\n\n # traverse in the string\n for ele in s:\n str1 += ele\n\n # return string\n return str1","def list_to_string(in_list):\n if not in_list:\n return \"[]\"\n else:\n return \"\\n- \" + \"\\n- \".join(in_list)","def format_list(list):\n return \" \".join(str(tok) for tok in list)","def concat_strings(l_strings):\n if l_strings == []:\n return \"\"\n else: \n return l_strings[0] + \" \" + concat_strings(l_strings[1:])","def join_str(lst, new_line=False):\n if new_line:\n j_str = \"/n\".join([str(i) for i in lst])\n else:\n j_str = \"\".join([str(i) for i in lst])\n return j_str","def listToString(s):\n # initialize an empty string\n str1 = \"\"\n\n # traverse in the string\n for ele in s:\n try:\n str1 = str1 + \" \" + ele\n except:\n pass\n\n # return string\n return str1","def listToStr(lst):\n return ','.join(lst)","def list_to_string(inputlist):\n outstring = \"\"\n numusers = len(inputlist)\n if numusers == 1: # foo\n outstring += inputlist[0]\n if numusers == 2: # foo and bar\n outstring += (inputlist[0] + \" and \" + inputlist[1])\n if numusers >= 3: # foo, bar and baz\n for x in range(numusers-2):\n outstring += inputlist[x] + \", \"\n outstring += (inputlist[-2] + \" and \" + inputlist[-1])\n return outstring","def create_list_string(list_):\n return f\"[{' '.join(list_)}]\"","def _toStr(toList):\n\n names = [formataddr(i) for i in zip(*toList)]\n return ', '.join(names)","def _char_list_to_string(char_list):\n ret = \"\"\n for i in char_list:\n ret+=i\n return ret","def print_string_list(string_list):\n\tfinal_string = \"\"\n\n\tfor string in string_list:\n\t\tfinal_string += string + \" \"\n\n\treturn final_string","def flatten_list(items: List[str]) -> str:\n if len(items) == 1:\n return f'\"{items[0]}\"'\n\n try:\n last = items[-1]\n except IndexError:\n # Empty list\n raise ValueError('Empty list of values received')\n\n return ', '.join(f'\"{item}\"' for item in items[:-1]) + f' or \"{last}\"'","def JoinList(LIST):\r\n if type(LIST) == list:\r\n out = ', '.join(LIST)\r\n elif type(LIST) == str:\r\n out = LIST\r\n return out","def encode_as_str(list_to_encode, sep = \"|\"):\n return sep.join([str(x) for x in list_to_encode])","def stringify(List):\n if List is None:\n return ''\n if not List:\n return ''\n\n return '-'.join(str(elem) for elem in List)","def join_and_sanitize(list_):\n if isinstance(list_, str):\n return list_\n\n new_list = []\n for item in list_:\n if isinstance(item, str):\n new_list.append(item)\n elif isinstance(item, int):\n new_list.append(str(item))\n elif isinstance(item, float):\n new_list.append(str(item))\n elif isinstance(item, unicode):\n new_list.append(str(item))\n else:\n raise Exception('Invalid type when attempting to join and sanitize')\n\n return ' '.join(new_list)","def _join_list_of_list(lst):\n\n int_list = [list(map(int, each)) for each in lst]\n # print(*int_list, sep=\"\\n\")\n str_list = [\",\".join(map(str, each)) for each in int_list]\n # print(*int_list, sep=\"\\n\")\n # print(str_list)\n final_str = \" \".join(str_list)\n # print(final_str)\n return final_str","def join_and_sanitize(list_):\n if isinstance(list_, str):\n return list_\n\n new_list = []\n for item in list_:\n if isinstance(item, str):\n new_list.append(item)\n elif isinstance(item, int):\n new_list.append(str(item))\n elif isinstance(item, float):\n new_list.append(str(item))\n else:\n raise Exception('Invalid type when attempting to join and sanitize')\n\n return ' '.join(new_list)","def rejoin(textList):\n return ','.join(textList)","def process_list(a_list: list):\n\n return ', '.join(str(s) for s in a_list) if a_list else Presenter.DEFAULT","def join_str_list(str_list):\n result = \"\"\n for s in str_list:\n if s.startswith(\"##\"):\n result += s[2:]\n else:\n result += \" \" + s\n return result","def join(self, iterable) -> String:\n pass","def convertListToString(list):\n return re.sub(r'[^\\w ]', '', str(list))","def join_list(jlist, joiner=', '):\n if len(jlist) == 0:\n jlist = '[]'\n else:\n jlist = joiner.join(jlist)\n return jlist","def __join_if_list(text_or_list: Union[List[str], str]) -> str:\n\n if isinstance(text_or_list, list):\n return ' '.join(text_or_list)\n return text_or_list","def join_strings(words):\n joined_string = ''\n for word in words:\n joined_string += word\n\n return joined_string","def ListToStr(val):\n return ''.join(['%c' % c for c in val])","def format_output(list_to_output):\n return \" \".join(str(item) for item in list_to_output)","def list_to_string(list):\n if len(list) == 1:\n string = '{}x1'.format(list[0])\n elif list[1:] == list[:-1]:\n string = '{}x{}'.format(list[1], len(list))\n else:\n string = ''\n for i in range(len(list) - 1):\n string += str(list[i]) + ','\n string += str(list[-1])\n return string","def unicode_list_to_str(u_code_list): #This is just a function for me. Has nothing to do with flask or anything, okay?\n out_list = \"\"\n for item in u_code_list:\n out_list = out_list + str(item) + \"-\"\n return out_list.rstrip(\"-\") #removes the extra '-' (i.e 2-3-4-1-)","def join(self, iterable):\n result = ANSIString(\"\")\n last_item = None\n for item in iterable:\n if last_item is not None:\n result += self._raw_string\n if not isinstance(item, ANSIString):\n item = ANSIString(item)\n result += item\n last_item = item\n return result","def _to_string(self, lst, indent=''):\n result = []\n for elem in lst:\n if isinstance(elem, list):\n if len(elem) > 0:\n result.append('\\n')\n result.append(self._to_string(elem, indent + ' '))\n elif isinstance(elem, float):\n result.append('%.6f' % elem)\n elif isinstance(elem, basestring):\n for char in ('(', ')', ' '):\n if char in elem:\n result.append('\"%s\"' % elem)\n break\n else:\n result.append(str(elem))\n elif elem is not None:\n result.append(str(elem))\n return indent + '(' + ' '.join(result) + ')\\n' + indent","def flatten_to_strings(listOfLists):\n result = []\n\n for i in listOfLists:\n # Only append if i is a basestring (superclass of string)\n if isinstance(i, basestring):\n result.append(i)\n # Otherwise call this function recursively\n else:\n result.extend(flatten_to_strings(i))\n return result","def __str__(self):\n \n return reduce(lambda a,b : str(a)+str(b),self.list)","def _list2str(self, data, delimiter=\",\", classify=lambda x: x):\n res = \"\"\n for i in range(len(data)):\n res += classify(data[i])\n if i != len(data) - 1:\n res += delimiter + \" \"\n return res","def concatena(*args):\n linea = ''\n for l in args:\n linea += str(l if l else '')\n return linea","def list_str_breaks(lis):\r\n as_str = \"\"\r\n for item in lis:\r\n as_str += str(item) + \"\\n\"\r\n return as_str[:-1]","def join_lines(lst):\n out = \"\"\n for line in lst:\n if line.startswith(\"[\") and line.endswith(\"]\"):\n out = f\"{out}\\n{line}\\n\"\n elif out.endswith(\".\"):\n out = f\"{out}\\n{line}\"\n else:\n out = f\"{out} {line}\"\n return out","def _render_list_to_string(self, alist):\n return \",\".join(self._render_row(alist))","def my_join(iters, string):\n out = ''\n for i in range(iters):\n out += string.join(\", \")\n return out","def l2s(l):\n return ''.join(l)","def _format_list(param_list: Iterable[Any]):\n fmt_list = []\n for item in param_list:\n if isinstance(item, str):\n fmt_list.append(f\"'{item}'\")\n else:\n fmt_list.append(f\"{item}\")\n return \",\".join(fmt_list)","def join_items(values, sort=False):\n\tif isinstance(values, str):\n\t\treturn clean_string(values)\n\n\ttry:\n\t\tval = []\n\t\tfor v in values:\n\t\t\tval.append(clean_string(v))\n\t\tif sort:\n\t\t\tval.sort()\n\t\treturn \"-\".join(val)\n\texcept TypeError:\n\t\treturn str(values)","def _to_space_separated_string(l):\n s = '';\n for x in l:\n if len(s)>0: s += ' '\n s += repr(x)\n return s","def list_stringify(inlist):\n outlist = []\n for item in inlist:\n if not isinstance(item, list):\n if not isinstance(item, str):\n thisitem = str(item)\n else:\n thisitem = item\n else:\n thisitem = list_stringify(item)\n outlist.append(thisitem)\n return outlist","def toStrFromList(values, precision, delim=\",\"):\n\tsValues = list(map(lambda v: toStr(v, precision), values))\n\treturn delim.join(sValues)","def array_to_concatenated_string(array):\r\n return \",\".join(str(x) for x in array)","def my_join(iters, string):\n out = ''\n for i in range(iters):\n out += \", \" + string\n return out","def merge_speeches(speeches_list):\n\n # Create a new string variable\n speeches_string = ''\n\n # Iterate over speeches in the given list\n for speech in speeches_list:\n # Append the speech and add a single space at the end\n speeches_string += speech + ' '\n\n return speeches_string","def _concat(self, *args, **kwargs):\n values = list(args)\n output = []\n for value in values:\n if not isinstance(value, (str, basestring)):\n value = unicode(value)\n else:\n value = unicode(value)\n value = value.strip()\n output.append(value)\n output = kwargs[\"delimiter\"].join(output)\n output = unicode(output)\n return output","def list_to_sentence(self, list):\n sentence = \"\\n\"\n for i in range(0, len(list)):\n if i == len(list) - 1:\n sentence += \"'\" + list[i] + \"'\"\n else:\n sentence += \"'\" + list[i] + \"'\\n\"\n return sentence","def list_stringify(inlist):\n outlist = []\n for item in inlist:\n if not isinstance(item, (tuple, list)):\n if not isinstance(item, basestring):\n item = str(item)\n else:\n item = list_stringify(item)\n outlist.append(item)\n return outlist","def array_to_concatenated_string(array):\n return \",\".join(str(x) for x in array)","def my_join(iters, string):\n out = \"\"\n for i in range(iters):\n out += \",\" + string \n return out","def __join_expanded(expanded: list[typing.Union[str, list[str]]]) -> list[str]:\n list_values = [(i, val) for i, val in enumerate(expanded) if isinstance(val, list)]\n\n if len(list_values) == 0:\n return [\"\".join(expanded)]\n\n initial_len = len(list_values[0][1]) if list_values else None\n\n if not all(len(i) == initial_len for _, i in list_values[1::]):\n raise ValueError(\"not all non-expanded list are of the same size\")\n\n pairs = zip(*[[(i, j) for j in val] for i, val in list_values])\n\n result = list()\n for pair in pairs:\n cc = expanded.copy()\n\n for i, v in pair:\n del(cc[i])\n cc.insert(i, v)\n\n result.append(\"\".join(cc))\n\n return result","def join_list(\n object_list: list, delimiter: str = \", \", last_delimiter: str = \" & \"\n) -> str:\n if not object_list:\n return \"\"\n list_copy = list(object_list)\n last = list_copy.pop()\n if list_copy:\n return f\"{delimiter.join(list_copy)}{last_delimiter}{last}\"\n return f\"{last}\"","def bytearray_join(glue, list_of_barrays):\n res = list_of_barrays[0]\n for i in range(1,len(list_of_barrays)):\n res += glue + list_of_barrays[i]\n return res","def num_to_str(numList):\n\n\tresult = ''\n\tfor num in numList:\n\t\tresult += str(num)\n\treturn result","def join_path(list):\n return functools.reduce(os.path.join, list)","def sqllist(lst):\n if isinstance(lst, basestring): \n return lst\n else:\n return ', '.join(lst)","def human_list(lst, connector='and'):\n # we don't want to listify non iterables\n if not getattr(lst, '__iter__', False):\n return lst\n else:\n s = ''\n max_idx = len(lst) - 1\n for i, item in enumerate(lst):\n if i == 0:\n t = '%s'\n elif i == max_idx and max_idx > 1:\n t = ', ' + connector + ' %s'\n elif i == max_idx and max_idx == 1:\n t = ' ' + connector + ' %s'\n else:\n t = ', %s'\n s += t % filter.conditional_escape(item)\n return mark_safe(s)","def to_string(student_list):\n student_info = \"\"\n for student in student_list:\n student_info += f\"{str(student)}\\n\"\n return student_info","def my_join(iters, string):\n out=''\n for i in range(iters):\n out += string.join(\", \")\n #add string together with , as seperator\n #repeat iters numbers of times\n return out","def escape_list(l):\n return [_escape_harlowe_html(item) if isinstance(item, text_type) else str(item) for item in l]","def convert_list_to_string(key, data, errors, context): # noqa\n value = data.get(key, None)\n\n if not value:\n return\n\n if not isinstance(value, list):\n return\n\n data[key] = '{' + ','.join(map(str, value)) + '}'","def underscore_join(iterable):\n iterable_as_str = [str(x) for x in iterable]\n return \"__\".join(iterable_as_str)","def make_safe(value, delimiter):\n if isinstance(value,list):\n return delimiter.join(map(lambda x: make_safe(x, delimiter),value))\n return str(value)","def to_strs(items) -> List[str]:\n result = []\n for item in items:\n if isinstance(item, str):\n if len(item) > 0:\n if not ((item[0] == '\"' and item[-1] == '\"') or (item[0] == \"'\" and item[-1] == \"'\")):\n result.append('\"' + item + '\"')\n else:\n result.append(item)\n else:\n result.append(item)\n else:\n result.append(str(item))\n return result","def join(sep, xs):\n return str(sep).join(xs)","def flatten(*args: Strings) -> List[str]:\n return list(each_string(*args))","def join_recursive(lst, sep):\n msg = ''\n for i in lst:\n if isinstance(i, tuple) or isinstance(i, list):\n msg += join_recursive(i, sep)\n else:\n msg += (i + sep)\n return msg","def list_2_string(l, name='List'):\n buff = io.StringIO()\n print_list(l, name=name, output=buff)\n return buff.getvalue()","def ilist_to_string(ilist):\n return ','.join([str(i.id) for i in ilist])","def _fmt_csv(string_list, list_braces = None):\n if len(string_list) == 0:\n return \"\"\n first = True\n str_ = \"\"\n if list_braces != None:\n str_ += list_braces[0]\n for string in string_list:\n if string != None:\n if first:\n first = False\n else:\n str_ += \", \"\n str_ += string\n if list_braces != None:\n str_ += list_braces[1]\n return str_","def lists_to_strings(dictionary, separator=' '):\n for key in dictionary:\n if isinstance(dictionary[key], list):\n dictionary[key] = separator.join(str(elem) for elem in dictionary[key])","def convert_list_to_unicode_str(data):\n string = ''\n for i, val in enumerate(data):\n # string = string + unicode(unichr(int(val)))\n string = string + str(int(val))\n return string","def __str__(self):\n return ' '.join([str(item) for item in self])"],"string":"[\n \"def stringer(list):\\n\\tstring = \\\"\\\"\\n\\tfor x in list:\\n\\t\\tstring = string + str(x)\\n\\treturn string\",\n \"def list2string(a_list):\\n\\n the_string = ''\\n for elem in a_list:\\n the_string += str(elem)\\n return the_string\",\n \"def list_to_str(list_to_convert):\\n return ' '.join(to_str(item) for item in list_to_convert)\",\n \"def list_to_str(input_str):\\r\\n\\r\\n return \\\" \\\".join([str(val) for val in input_str])\",\n \"def join_list(items: Iterable[str]) -> str:\\n\\n return ITEM_SEPARATOR.join(items)\",\n \"def get_list_as_str(list_to_convert):\\n return \\\", \\\".join([\\\"'{}'\\\".format(list_item) for list_item in list_to_convert])\",\n \"def listToString(L):\\r\\n S = ''\\r\\n for x in L:\\r\\n S += str(x)\\r\\n return S\",\n \"def list_join(the_list):\\n return ' '.join(the_list)\",\n \"def listtostring(self, charlist):\\n s = \\\"\\\"\\n for char in charlist:\\n s += char\\n return s\",\n \"def list_to_str(\\n l: list,\\n c: str,\\n ) -> str:\\n\\n s = c.join(map(str, l))\\n\\n return s\",\n \"def concat_list(str_lst):\\n concatenation = ''\\n if len(str_lst) != 0:\\n for string in str_lst:\\n concatenation = concatenation + string\\n return concatenation\",\n \"def list_to_str( L ):\\n if len(L) == 0: return ''\\n return L[0] + list_to_str( L[1:] )\",\n \"def list_to_str( L ):\\n if len(L) == 0: return ''\\n return L[0] + list_to_str( L[1:] )\",\n \"def list_string(join_list):\\n joined_list = '[{}]'.format(join_list, join_list)\\n return joined_list\",\n \"def listToStringFormat(self, list) ->str:\\n string = ''\\n for element in list:\\n string = string + str(element) + \\\"\\\\n\\\"\\n return string\",\n \"def str_transform_list(L):\\n return [str(x) for x in L]\",\n \"def _convertListToString(self, list_of_objects):\\n return (';').join(list_of_objects)\",\n \"def list_str(lis):\\r\\n as_str = \\\"\\\"\\r\\n for item in lis:\\r\\n as_str += \\\" \\\" + str(item) + \\\",\\\"\\r\\n return as_str[:-1]\",\n \"def list_to_str(a_list):\\n new_str = \\\"\\\"\\n for item in a_list:\\n item = str(item).replace(\\\"\\\\'\\\", \\\"\\\\'\\\\'\\\")\\n if new_str:\\n new_str += \\\", '\\\" + item + \\\"'\\\"\\n else:\\n new_str = \\\"'\\\" + item + \\\"'\\\"\\n return new_str\",\n \"def listToString(s):\\n # initialize an empty string\\n str1 = \\\"\\\"\\n\\n # traverse in the string\\n for ele in s:\\n str1 += ele\\n\\n # return string\\n return str1\",\n \"def list_to_string(in_list):\\n if not in_list:\\n return \\\"[]\\\"\\n else:\\n return \\\"\\\\n- \\\" + \\\"\\\\n- \\\".join(in_list)\",\n \"def format_list(list):\\n return \\\" \\\".join(str(tok) for tok in list)\",\n \"def concat_strings(l_strings):\\n if l_strings == []:\\n return \\\"\\\"\\n else: \\n return l_strings[0] + \\\" \\\" + concat_strings(l_strings[1:])\",\n \"def join_str(lst, new_line=False):\\n if new_line:\\n j_str = \\\"/n\\\".join([str(i) for i in lst])\\n else:\\n j_str = \\\"\\\".join([str(i) for i in lst])\\n return j_str\",\n \"def listToString(s):\\n # initialize an empty string\\n str1 = \\\"\\\"\\n\\n # traverse in the string\\n for ele in s:\\n try:\\n str1 = str1 + \\\" \\\" + ele\\n except:\\n pass\\n\\n # return string\\n return str1\",\n \"def listToStr(lst):\\n return ','.join(lst)\",\n \"def list_to_string(inputlist):\\n outstring = \\\"\\\"\\n numusers = len(inputlist)\\n if numusers == 1: # foo\\n outstring += inputlist[0]\\n if numusers == 2: # foo and bar\\n outstring += (inputlist[0] + \\\" and \\\" + inputlist[1])\\n if numusers >= 3: # foo, bar and baz\\n for x in range(numusers-2):\\n outstring += inputlist[x] + \\\", \\\"\\n outstring += (inputlist[-2] + \\\" and \\\" + inputlist[-1])\\n return outstring\",\n \"def create_list_string(list_):\\n return f\\\"[{' '.join(list_)}]\\\"\",\n \"def _toStr(toList):\\n\\n names = [formataddr(i) for i in zip(*toList)]\\n return ', '.join(names)\",\n \"def _char_list_to_string(char_list):\\n ret = \\\"\\\"\\n for i in char_list:\\n ret+=i\\n return ret\",\n \"def print_string_list(string_list):\\n\\tfinal_string = \\\"\\\"\\n\\n\\tfor string in string_list:\\n\\t\\tfinal_string += string + \\\" \\\"\\n\\n\\treturn final_string\",\n \"def flatten_list(items: List[str]) -> str:\\n if len(items) == 1:\\n return f'\\\"{items[0]}\\\"'\\n\\n try:\\n last = items[-1]\\n except IndexError:\\n # Empty list\\n raise ValueError('Empty list of values received')\\n\\n return ', '.join(f'\\\"{item}\\\"' for item in items[:-1]) + f' or \\\"{last}\\\"'\",\n \"def JoinList(LIST):\\r\\n if type(LIST) == list:\\r\\n out = ', '.join(LIST)\\r\\n elif type(LIST) == str:\\r\\n out = LIST\\r\\n return out\",\n \"def encode_as_str(list_to_encode, sep = \\\"|\\\"):\\n return sep.join([str(x) for x in list_to_encode])\",\n \"def stringify(List):\\n if List is None:\\n return ''\\n if not List:\\n return ''\\n\\n return '-'.join(str(elem) for elem in List)\",\n \"def join_and_sanitize(list_):\\n if isinstance(list_, str):\\n return list_\\n\\n new_list = []\\n for item in list_:\\n if isinstance(item, str):\\n new_list.append(item)\\n elif isinstance(item, int):\\n new_list.append(str(item))\\n elif isinstance(item, float):\\n new_list.append(str(item))\\n elif isinstance(item, unicode):\\n new_list.append(str(item))\\n else:\\n raise Exception('Invalid type when attempting to join and sanitize')\\n\\n return ' '.join(new_list)\",\n \"def _join_list_of_list(lst):\\n\\n int_list = [list(map(int, each)) for each in lst]\\n # print(*int_list, sep=\\\"\\\\n\\\")\\n str_list = [\\\",\\\".join(map(str, each)) for each in int_list]\\n # print(*int_list, sep=\\\"\\\\n\\\")\\n # print(str_list)\\n final_str = \\\" \\\".join(str_list)\\n # print(final_str)\\n return final_str\",\n \"def join_and_sanitize(list_):\\n if isinstance(list_, str):\\n return list_\\n\\n new_list = []\\n for item in list_:\\n if isinstance(item, str):\\n new_list.append(item)\\n elif isinstance(item, int):\\n new_list.append(str(item))\\n elif isinstance(item, float):\\n new_list.append(str(item))\\n else:\\n raise Exception('Invalid type when attempting to join and sanitize')\\n\\n return ' '.join(new_list)\",\n \"def rejoin(textList):\\n return ','.join(textList)\",\n \"def process_list(a_list: list):\\n\\n return ', '.join(str(s) for s in a_list) if a_list else Presenter.DEFAULT\",\n \"def join_str_list(str_list):\\n result = \\\"\\\"\\n for s in str_list:\\n if s.startswith(\\\"##\\\"):\\n result += s[2:]\\n else:\\n result += \\\" \\\" + s\\n return result\",\n \"def join(self, iterable) -> String:\\n pass\",\n \"def convertListToString(list):\\n return re.sub(r'[^\\\\w ]', '', str(list))\",\n \"def join_list(jlist, joiner=', '):\\n if len(jlist) == 0:\\n jlist = '[]'\\n else:\\n jlist = joiner.join(jlist)\\n return jlist\",\n \"def __join_if_list(text_or_list: Union[List[str], str]) -> str:\\n\\n if isinstance(text_or_list, list):\\n return ' '.join(text_or_list)\\n return text_or_list\",\n \"def join_strings(words):\\n joined_string = ''\\n for word in words:\\n joined_string += word\\n\\n return joined_string\",\n \"def ListToStr(val):\\n return ''.join(['%c' % c for c in val])\",\n \"def format_output(list_to_output):\\n return \\\" \\\".join(str(item) for item in list_to_output)\",\n \"def list_to_string(list):\\n if len(list) == 1:\\n string = '{}x1'.format(list[0])\\n elif list[1:] == list[:-1]:\\n string = '{}x{}'.format(list[1], len(list))\\n else:\\n string = ''\\n for i in range(len(list) - 1):\\n string += str(list[i]) + ','\\n string += str(list[-1])\\n return string\",\n \"def unicode_list_to_str(u_code_list): #This is just a function for me. Has nothing to do with flask or anything, okay?\\n out_list = \\\"\\\"\\n for item in u_code_list:\\n out_list = out_list + str(item) + \\\"-\\\"\\n return out_list.rstrip(\\\"-\\\") #removes the extra '-' (i.e 2-3-4-1-)\",\n \"def join(self, iterable):\\n result = ANSIString(\\\"\\\")\\n last_item = None\\n for item in iterable:\\n if last_item is not None:\\n result += self._raw_string\\n if not isinstance(item, ANSIString):\\n item = ANSIString(item)\\n result += item\\n last_item = item\\n return result\",\n \"def _to_string(self, lst, indent=''):\\n result = []\\n for elem in lst:\\n if isinstance(elem, list):\\n if len(elem) > 0:\\n result.append('\\\\n')\\n result.append(self._to_string(elem, indent + ' '))\\n elif isinstance(elem, float):\\n result.append('%.6f' % elem)\\n elif isinstance(elem, basestring):\\n for char in ('(', ')', ' '):\\n if char in elem:\\n result.append('\\\"%s\\\"' % elem)\\n break\\n else:\\n result.append(str(elem))\\n elif elem is not None:\\n result.append(str(elem))\\n return indent + '(' + ' '.join(result) + ')\\\\n' + indent\",\n \"def flatten_to_strings(listOfLists):\\n result = []\\n\\n for i in listOfLists:\\n # Only append if i is a basestring (superclass of string)\\n if isinstance(i, basestring):\\n result.append(i)\\n # Otherwise call this function recursively\\n else:\\n result.extend(flatten_to_strings(i))\\n return result\",\n \"def __str__(self):\\n \\n return reduce(lambda a,b : str(a)+str(b),self.list)\",\n \"def _list2str(self, data, delimiter=\\\",\\\", classify=lambda x: x):\\n res = \\\"\\\"\\n for i in range(len(data)):\\n res += classify(data[i])\\n if i != len(data) - 1:\\n res += delimiter + \\\" \\\"\\n return res\",\n \"def concatena(*args):\\n linea = ''\\n for l in args:\\n linea += str(l if l else '')\\n return linea\",\n \"def list_str_breaks(lis):\\r\\n as_str = \\\"\\\"\\r\\n for item in lis:\\r\\n as_str += str(item) + \\\"\\\\n\\\"\\r\\n return as_str[:-1]\",\n \"def join_lines(lst):\\n out = \\\"\\\"\\n for line in lst:\\n if line.startswith(\\\"[\\\") and line.endswith(\\\"]\\\"):\\n out = f\\\"{out}\\\\n{line}\\\\n\\\"\\n elif out.endswith(\\\".\\\"):\\n out = f\\\"{out}\\\\n{line}\\\"\\n else:\\n out = f\\\"{out} {line}\\\"\\n return out\",\n \"def _render_list_to_string(self, alist):\\n return \\\",\\\".join(self._render_row(alist))\",\n \"def my_join(iters, string):\\n out = ''\\n for i in range(iters):\\n out += string.join(\\\", \\\")\\n return out\",\n \"def l2s(l):\\n return ''.join(l)\",\n \"def _format_list(param_list: Iterable[Any]):\\n fmt_list = []\\n for item in param_list:\\n if isinstance(item, str):\\n fmt_list.append(f\\\"'{item}'\\\")\\n else:\\n fmt_list.append(f\\\"{item}\\\")\\n return \\\",\\\".join(fmt_list)\",\n \"def join_items(values, sort=False):\\n\\tif isinstance(values, str):\\n\\t\\treturn clean_string(values)\\n\\n\\ttry:\\n\\t\\tval = []\\n\\t\\tfor v in values:\\n\\t\\t\\tval.append(clean_string(v))\\n\\t\\tif sort:\\n\\t\\t\\tval.sort()\\n\\t\\treturn \\\"-\\\".join(val)\\n\\texcept TypeError:\\n\\t\\treturn str(values)\",\n \"def _to_space_separated_string(l):\\n s = '';\\n for x in l:\\n if len(s)>0: s += ' '\\n s += repr(x)\\n return s\",\n \"def list_stringify(inlist):\\n outlist = []\\n for item in inlist:\\n if not isinstance(item, list):\\n if not isinstance(item, str):\\n thisitem = str(item)\\n else:\\n thisitem = item\\n else:\\n thisitem = list_stringify(item)\\n outlist.append(thisitem)\\n return outlist\",\n \"def toStrFromList(values, precision, delim=\\\",\\\"):\\n\\tsValues = list(map(lambda v: toStr(v, precision), values))\\n\\treturn delim.join(sValues)\",\n \"def array_to_concatenated_string(array):\\r\\n return \\\",\\\".join(str(x) for x in array)\",\n \"def my_join(iters, string):\\n out = ''\\n for i in range(iters):\\n out += \\\", \\\" + string\\n return out\",\n \"def merge_speeches(speeches_list):\\n\\n # Create a new string variable\\n speeches_string = ''\\n\\n # Iterate over speeches in the given list\\n for speech in speeches_list:\\n # Append the speech and add a single space at the end\\n speeches_string += speech + ' '\\n\\n return speeches_string\",\n \"def _concat(self, *args, **kwargs):\\n values = list(args)\\n output = []\\n for value in values:\\n if not isinstance(value, (str, basestring)):\\n value = unicode(value)\\n else:\\n value = unicode(value)\\n value = value.strip()\\n output.append(value)\\n output = kwargs[\\\"delimiter\\\"].join(output)\\n output = unicode(output)\\n return output\",\n \"def list_to_sentence(self, list):\\n sentence = \\\"\\\\n\\\"\\n for i in range(0, len(list)):\\n if i == len(list) - 1:\\n sentence += \\\"'\\\" + list[i] + \\\"'\\\"\\n else:\\n sentence += \\\"'\\\" + list[i] + \\\"'\\\\n\\\"\\n return sentence\",\n \"def list_stringify(inlist):\\n outlist = []\\n for item in inlist:\\n if not isinstance(item, (tuple, list)):\\n if not isinstance(item, basestring):\\n item = str(item)\\n else:\\n item = list_stringify(item)\\n outlist.append(item)\\n return outlist\",\n \"def array_to_concatenated_string(array):\\n return \\\",\\\".join(str(x) for x in array)\",\n \"def my_join(iters, string):\\n out = \\\"\\\"\\n for i in range(iters):\\n out += \\\",\\\" + string \\n return out\",\n \"def __join_expanded(expanded: list[typing.Union[str, list[str]]]) -> list[str]:\\n list_values = [(i, val) for i, val in enumerate(expanded) if isinstance(val, list)]\\n\\n if len(list_values) == 0:\\n return [\\\"\\\".join(expanded)]\\n\\n initial_len = len(list_values[0][1]) if list_values else None\\n\\n if not all(len(i) == initial_len for _, i in list_values[1::]):\\n raise ValueError(\\\"not all non-expanded list are of the same size\\\")\\n\\n pairs = zip(*[[(i, j) for j in val] for i, val in list_values])\\n\\n result = list()\\n for pair in pairs:\\n cc = expanded.copy()\\n\\n for i, v in pair:\\n del(cc[i])\\n cc.insert(i, v)\\n\\n result.append(\\\"\\\".join(cc))\\n\\n return result\",\n \"def join_list(\\n object_list: list, delimiter: str = \\\", \\\", last_delimiter: str = \\\" & \\\"\\n) -> str:\\n if not object_list:\\n return \\\"\\\"\\n list_copy = list(object_list)\\n last = list_copy.pop()\\n if list_copy:\\n return f\\\"{delimiter.join(list_copy)}{last_delimiter}{last}\\\"\\n return f\\\"{last}\\\"\",\n \"def bytearray_join(glue, list_of_barrays):\\n res = list_of_barrays[0]\\n for i in range(1,len(list_of_barrays)):\\n res += glue + list_of_barrays[i]\\n return res\",\n \"def num_to_str(numList):\\n\\n\\tresult = ''\\n\\tfor num in numList:\\n\\t\\tresult += str(num)\\n\\treturn result\",\n \"def join_path(list):\\n return functools.reduce(os.path.join, list)\",\n \"def sqllist(lst):\\n if isinstance(lst, basestring): \\n return lst\\n else:\\n return ', '.join(lst)\",\n \"def human_list(lst, connector='and'):\\n # we don't want to listify non iterables\\n if not getattr(lst, '__iter__', False):\\n return lst\\n else:\\n s = ''\\n max_idx = len(lst) - 1\\n for i, item in enumerate(lst):\\n if i == 0:\\n t = '%s'\\n elif i == max_idx and max_idx > 1:\\n t = ', ' + connector + ' %s'\\n elif i == max_idx and max_idx == 1:\\n t = ' ' + connector + ' %s'\\n else:\\n t = ', %s'\\n s += t % filter.conditional_escape(item)\\n return mark_safe(s)\",\n \"def to_string(student_list):\\n student_info = \\\"\\\"\\n for student in student_list:\\n student_info += f\\\"{str(student)}\\\\n\\\"\\n return student_info\",\n \"def my_join(iters, string):\\n out=''\\n for i in range(iters):\\n out += string.join(\\\", \\\")\\n #add string together with , as seperator\\n #repeat iters numbers of times\\n return out\",\n \"def escape_list(l):\\n return [_escape_harlowe_html(item) if isinstance(item, text_type) else str(item) for item in l]\",\n \"def convert_list_to_string(key, data, errors, context): # noqa\\n value = data.get(key, None)\\n\\n if not value:\\n return\\n\\n if not isinstance(value, list):\\n return\\n\\n data[key] = '{' + ','.join(map(str, value)) + '}'\",\n \"def underscore_join(iterable):\\n iterable_as_str = [str(x) for x in iterable]\\n return \\\"__\\\".join(iterable_as_str)\",\n \"def make_safe(value, delimiter):\\n if isinstance(value,list):\\n return delimiter.join(map(lambda x: make_safe(x, delimiter),value))\\n return str(value)\",\n \"def to_strs(items) -> List[str]:\\n result = []\\n for item in items:\\n if isinstance(item, str):\\n if len(item) > 0:\\n if not ((item[0] == '\\\"' and item[-1] == '\\\"') or (item[0] == \\\"'\\\" and item[-1] == \\\"'\\\")):\\n result.append('\\\"' + item + '\\\"')\\n else:\\n result.append(item)\\n else:\\n result.append(item)\\n else:\\n result.append(str(item))\\n return result\",\n \"def join(sep, xs):\\n return str(sep).join(xs)\",\n \"def flatten(*args: Strings) -> List[str]:\\n return list(each_string(*args))\",\n \"def join_recursive(lst, sep):\\n msg = ''\\n for i in lst:\\n if isinstance(i, tuple) or isinstance(i, list):\\n msg += join_recursive(i, sep)\\n else:\\n msg += (i + sep)\\n return msg\",\n \"def list_2_string(l, name='List'):\\n buff = io.StringIO()\\n print_list(l, name=name, output=buff)\\n return buff.getvalue()\",\n \"def ilist_to_string(ilist):\\n return ','.join([str(i.id) for i in ilist])\",\n \"def _fmt_csv(string_list, list_braces = None):\\n if len(string_list) == 0:\\n return \\\"\\\"\\n first = True\\n str_ = \\\"\\\"\\n if list_braces != None:\\n str_ += list_braces[0]\\n for string in string_list:\\n if string != None:\\n if first:\\n first = False\\n else:\\n str_ += \\\", \\\"\\n str_ += string\\n if list_braces != None:\\n str_ += list_braces[1]\\n return str_\",\n \"def lists_to_strings(dictionary, separator=' '):\\n for key in dictionary:\\n if isinstance(dictionary[key], list):\\n dictionary[key] = separator.join(str(elem) for elem in dictionary[key])\",\n \"def convert_list_to_unicode_str(data):\\n string = ''\\n for i, val in enumerate(data):\\n # string = string + unicode(unichr(int(val)))\\n string = string + str(int(val))\\n return string\",\n \"def __str__(self):\\n return ' '.join([str(item) for item in self])\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.845377","0.7836319","0.7773371","0.7705512","0.7661951","0.7658474","0.7595569","0.7587454","0.7479857","0.7459654","0.74586385","0.7406689","0.7406689","0.7394045","0.7386286","0.7349678","0.7333463","0.733121","0.7291625","0.7260772","0.71728444","0.71112806","0.7063908","0.70387524","0.70186424","0.7015675","0.69769394","0.6975982","0.6961543","0.691275","0.6910822","0.6893366","0.68932444","0.68905187","0.6879961","0.68651104","0.68299663","0.6815819","0.6811026","0.6805567","0.67674303","0.6743737","0.6719011","0.66928685","0.6684226","0.6658465","0.66508794","0.6633169","0.66244096","0.6618504","0.66128176","0.65923005","0.65493256","0.6521632","0.64857584","0.6472786","0.6468196","0.6442063","0.64219856","0.63330734","0.6331352","0.6323295","0.6308252","0.62925327","0.6254319","0.62506896","0.622984","0.6218811","0.62027955","0.6201592","0.6196517","0.6189968","0.61736745","0.617026","0.61604595","0.61448836","0.61410826","0.6128951","0.61046666","0.6066805","0.6056225","0.6054773","0.6049699","0.60427874","0.6042118","0.60329175","0.60318506","0.6028512","0.6010638","0.60029787","0.5993571","0.59909165","0.5988412","0.59830743","0.59780276","0.59738255","0.5973736"],"string":"[\n \"0.845377\",\n \"0.7836319\",\n \"0.7773371\",\n \"0.7705512\",\n \"0.7661951\",\n \"0.7658474\",\n \"0.7595569\",\n \"0.7587454\",\n \"0.7479857\",\n \"0.7459654\",\n \"0.74586385\",\n \"0.7406689\",\n \"0.7406689\",\n \"0.7394045\",\n \"0.7386286\",\n \"0.7349678\",\n \"0.7333463\",\n \"0.733121\",\n \"0.7291625\",\n \"0.7260772\",\n \"0.71728444\",\n \"0.71112806\",\n \"0.7063908\",\n \"0.70387524\",\n \"0.70186424\",\n \"0.7015675\",\n \"0.69769394\",\n \"0.6975982\",\n \"0.6961543\",\n \"0.691275\",\n \"0.6910822\",\n \"0.6893366\",\n \"0.68932444\",\n \"0.68905187\",\n \"0.6879961\",\n \"0.68651104\",\n \"0.68299663\",\n \"0.6815819\",\n \"0.6811026\",\n \"0.6805567\",\n \"0.67674303\",\n \"0.6743737\",\n \"0.6719011\",\n \"0.66928685\",\n \"0.6684226\",\n \"0.6658465\",\n \"0.66508794\",\n \"0.6633169\",\n \"0.66244096\",\n \"0.6618504\",\n \"0.66128176\",\n \"0.65923005\",\n \"0.65493256\",\n \"0.6521632\",\n \"0.64857584\",\n \"0.6472786\",\n \"0.6468196\",\n \"0.6442063\",\n \"0.64219856\",\n \"0.63330734\",\n \"0.6331352\",\n \"0.6323295\",\n \"0.6308252\",\n \"0.62925327\",\n \"0.6254319\",\n \"0.62506896\",\n \"0.622984\",\n \"0.6218811\",\n \"0.62027955\",\n \"0.6201592\",\n \"0.6196517\",\n \"0.6189968\",\n \"0.61736745\",\n \"0.617026\",\n \"0.61604595\",\n \"0.61448836\",\n \"0.61410826\",\n \"0.6128951\",\n \"0.61046666\",\n \"0.6066805\",\n \"0.6056225\",\n \"0.6054773\",\n \"0.6049699\",\n \"0.60427874\",\n \"0.6042118\",\n \"0.60329175\",\n \"0.60318506\",\n \"0.6028512\",\n \"0.6010638\",\n \"0.60029787\",\n \"0.5993571\",\n \"0.59909165\",\n \"0.5988412\",\n \"0.59830743\",\n \"0.59780276\",\n \"0.59738255\",\n \"0.5973736\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.652098"},"document_rank":{"kind":"string","value":"56"}}},{"rowIdx":92990,"cells":{"query":{"kind":"string","value":"Computes the Protein encoded by a sequence of DNA. This function does not check for start and stop codons (it assumes that the input DNA sequence represents an protein coding region)."},"document":{"kind":"string","value":"def coding_strand_to_AA(dna):\n l = len(dna)\n res = []\n for i in range(0, l, 3):\n s = dna[i: i + 3]\n for j in range(len(codons)):\n# for codon in codons[j]:\n# if codon == s:\n# res.append(aa[j])\n# break;\n if s in codons[j]: # [WOW] Python is really nice unlike C, yay!!\n res.append(aa[j])\n return collapse(res)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def dna_to_protein(seq):\n\n # Verify a convertible sequence\n if len(seq) % 3 != 0:\n raise RuntimeError('Total number of bases must be a multiple of 3')\n\n # Iterate through adding the proteins\n protein = ''\n for i in range(0, len(seq), 3):\n protein += bioinfo_dicts.codons[seq[i:i+3]]\n return protein","def dna_to_protein(dna: str, start: int=0):\n return rna_to_protein(dna_to_rna(dna, start), start=start)","def proteinTranslation(seq, geneticCode = STANDARD_GENETIC_CODE):\n\n seq = seq.replace('T','U') # Make sure we have RNA sequence\n proteinSeq = []\n \n i = 0\n while i+2 < len(seq):\n \n codon = seq[i:i+3]\n aminoAcid = geneticCode[codon]\n \n if aminoAcid is None: # Found stop codon\n break\n\n proteinSeq.append(aminoAcid)\n i += 3\n\n return proteinSeq","def return_peptide (RNA):\n\t# Should work with already made sequence without stop codons. Only one peptide per call\n\n\tdna.isNucleotide(RNA)\n\tif 'T' in RNA: raise dna.InvalidSequenceError\t\n\tpeptide = \"\"\n\tid = 0\n\twhile id < len(RNA):\n\t\ttRNA = RNA[id:id+3]\n\t\tif not tRNA in RNA_code: break\n\t\tAA = RNA_code[tRNA]\n\t\tif AA == False: # In the case if was mistake in the previous step\n\t\t\tbreak\n\t\tpeptide += AA\n\t\tid += 3\t\n\treturn peptide","def protein_from_orfs(dna):\n rna = dna.replace(\"T\", \"U\")\n reverse_complement_rna = complement_strand(dna).replace(\"T\", \"U\")\n\n candidate_proteins = set()\n\n for strand in [rna, reverse_complement_rna]:\n for index in [m.start() for m in re.finditer('AUG', strand)]:\n codons_list = codons(strand[index:])\n protein = \"\"\n\n if any(rna_codon_dict[codon] == \"Stop\" for codon in codons_list):\n for codon in codons_list:\n symbol = rna_codon_dict[codon]\n\n if symbol != \"Stop\":\n protein += symbol\n else:\n candidate_proteins.add(protein)\n break\n\n return candidate_proteins","def rna_to_protein(rna: str, to_str=True, start: Union[int, Callable[[str], int]]=start_with_the_beggining,\n end=False):\n pos = start(rna) if callable(start) else start\n if pos < 0:\n return None if not to_str else \"\"\n else:\n rna = rna[pos:]\n result = [\"\"] * (len(rna) // 3)\n for i in range(len(result)):\n elem = rna_codon_table[rna[3 * i: 3 * i + 3]]\n if elem != STOP_CODON:\n result[i] = elem\n else:\n result = result[:i]\n break\n else:\n # if no break occurs, then stop codon wasn't found, so if end argument is True empty sequence should be returned\n if end:\n result = []\n if to_str:\n result = \"\".join(result)\n return result","def __init__(self, seq, peptide):\r\n self.seq = seq # original DNA sequence\r\n self.peptide = peptide # original peptide sequence\r\n self.allPepSeqs = [] # list to hold all possible nuc sequences based on the peptide sequence\r\n self.codonTable = { # holds all amino acids and their associated codons\r\n 'F': ['TTT', 'TTC'], 'S': ['TCT', 'TCC', 'TCA', 'TCG', 'AGT', 'AGC'],\r\n 'Y': ['TAT', 'TAC'], 'C': ['TGT', 'TGC'], 'L': ['TTA', 'TTG', 'CTT', 'CTC', 'CTA', 'CTG'],\r\n '-': ['TAA', 'TGA', 'TAG'], 'W': ['TGG'], 'P': ['CCT', 'CCC', 'CCA', 'CCG'],\r\n 'H': ['CAT', 'CAC'], 'R': ['CGT', 'CGC', 'CGA', 'CGG', 'AGA', 'AGG'], 'Q': ['CAA', 'CAG'],\r\n 'I': ['ATT', 'ATC', 'ATA'], 'T': ['ACT', 'ACC', 'ACA', 'ACG'], 'N': ['AAT', 'AAC'],\r\n 'K': ['AAA', 'AAG'], 'M': ['ATG'], 'V': ['GTT', 'GTC', 'GTA', 'GTG'],\r\n 'A': ['GCT', 'GCC', 'GCA', 'GCG'], 'D': ['GAT', 'GAC'], 'G': ['GGT', 'GGC', 'GGA', 'GGG'],\r\n 'E': ['GAA', 'GAG']\r\n }","def coding_strand_to_AA(dna):\n protein=''\n for i in range(0,len(dna),3):\n\t if dna[i:i+3] in aa_table.keys():\n\t \tprotein += aa_table[dna[i:i+3]]\n return protein","def coding_strand_to_AA(dna):\n dnainp = dna\n protein = ''\n if len(dnainp)<3:\n return \"ERROR: The provided fragment is too short to contain any codons.\"\n# elif len(dnainp)%3 is not 0:\n# print \"Warning: The provided DNA fragment does not contain an integer number of codons. Excess bases were leftout.\"\n while len(dnainp) >=3:\n cod = dnainp[:3]\n for i in codons:\n for j in i:\n if j == cod:\n protein = protein + aa[codons.index(i)]\n dnainp = dnainp[3:]\n return protein","def translate(dna):\n rna = dna.replace('T', 'U')\n startIndex = dna.find('AUG') + 1\n aminoAcidsSeq = \"\"\n for i in range(startIndex, len(rna), 3):\n # codon = rna[i: i+3]\n aminoAcidsSeq += code[rna[i: i+3]]\n if aminoAcidsSeq[len(aminoAcidsSeq) - 1] == '*':\n aminoAcidsSeq = aminoAcidsSeq[:-1]\n break\n return aminoAcidsSeq","def coding_strand_to_AA(dna):\n #inital conditions\n protein = ''\n i = 0\n\n #for the length of DNA, translate each codon in an ORF to an amino acid\n while i < (len(dna)-2):\n codon = dna[i:i+3] \n amino_acid = aa_table[codon]\n protein= protein + amino_acid\n i += 3\n\n #return the string of amino acids\n return protein","def Translate(self):\n dna_to_protein = {\n 'ATA':'I', 'ATC':'I', 'ATT':'I', 'ATG':'M',\n 'ACA':'T', 'ACC':'T', 'ACG':'T', 'ACT':'T',\n 'AAC':'N', 'AAT':'N', 'AAA':'K', 'AAG':'K',\n 'AGC':'S', 'AGT':'S', 'AGA':'R', 'AGG':'R',\n 'CTA':'L', 'CTC':'L', 'CTG':'L', 'CTT':'L',\n 'CCA':'P', 'CCC':'P', 'CCG':'P', 'CCT':'P',\n 'CAC':'H', 'CAT':'H', 'CAA':'Q', 'CAG':'Q',\n 'CGA':'R', 'CGC':'R', 'CGG':'R', 'CGT':'R',\n 'GTA':'V', 'GTC':'V', 'GTG':'V', 'GTT':'V',\n 'GCA':'A', 'GCC':'A', 'GCG':'A', 'GCT':'A',\n 'GAC':'D', 'GAT':'D', 'GAA':'E', 'GAG':'E',\n 'GGA':'G', 'GGC':'G', 'GGG':'G', 'GGT':'G',\n 'TCA':'S', 'TCC':'S', 'TCG':'S', 'TCT':'S',\n 'TTC':'F', 'TTT':'F', 'TTA':'L', 'TTG':'L',\n 'TAC':'Y', 'TAT':'Y', 'TAA':'*', 'TAG':'*',\n 'TGC':'C', 'TGT':'C', 'TGA':'*', 'TGG':'W',\n }\n \n length = self.length\n reading = {}\n for i in range(3):\n reading['frame_'+str(i+1)] = tuple([dna_to_protein[self.sequence[index:index+3]] for index in range(i,length-2,3)])\n reverse_strand = Analyze_DNA_Sequence.Complementary(self,'5-3')\n for i in range(3):\n reading['frame_'+str(i+4)] = tuple([dna_to_protein[reverse_strand[index:index+3]] for index in range(i,length-2,3)])\n\n return reading","def getCodonSeqs(self):\r\n combinations = list(self.codonTable[aa] for aa in self.peptide) # creates a list of possible codons based on AA\r\n self.allPepSeqs = list(''.join(codon) for codon in itertools.product(*combinations)) # creates list of peptides\r\n return","def translate_sequence(sequence, genetic_code = {'GUC': 'V', 'ACC': 'T', 'GUA': 'V', 'GUG': 'V', 'ACU': 'T', 'AAC': 'N', 'CCU': 'P', 'UGG': 'W', 'AGC': 'S', 'AUC': 'I', 'CAU': 'H', 'AAU': 'N', 'AGU': 'S', 'GUU': 'V', 'CAC': 'H', 'ACG': 'T', 'CCG': 'P', 'CCA': 'P', 'ACA': 'T', 'CCC': 'P', 'UGU': 'C', 'GGU': 'G', 'UCU': 'S', 'GCG': 'A', 'UGC': 'C', 'CAG': 'Q', 'GAU': 'D', 'UAU': 'Y', 'CGG': 'R', 'UCG': 'S', 'AGG': 'R', 'GGG': 'G', 'UCC': 'S', 'UCA': 'S', 'UAA': '*', 'GGA': 'G', 'UAC': 'Y', 'GAC': 'D', 'UAG': '*', 'AUA': 'I', 'GCA': 'A', 'CUU': 'L', 'GGC': 'G', 'AUG': 'M', 'CUG': 'L', 'GAG': 'E', 'CUC': 'L', 'AGA': 'R', 'CUA': 'L', 'GCC': 'A', 'AAA': 'K', 'AAG': 'K', 'CAA': 'Q', 'UUU': 'F', 'CGU': 'R', 'CGC': 'R', 'CGA': 'R', 'GCU': 'A', 'GAA': 'E', 'AUU': 'I', 'UUG': 'L', 'UUA': 'L', 'UGA': '*', 'UUC': 'F'}, start_pos = 0):\n #find first orf\n #first_orf_seq = find_first_orf(sequence)\n\n # ensure sequence is uppercase\n seq = sequence.upper()\n\n #translate the sequence\n protein = \"\"\n for i in range(0, len(seq) - (len(seq) % 3), 3):\n codon = seq[i:i + 3]\n if genetic_code[codon] == \"*\":\n break\n protein += genetic_code[codon]\n return protein","def TranslateRNA(rna):\n rna = rna.lower().replace('\\n', '').replace(' ', '')\n \n ### codon table ###\n \n bases = [ 'u', 'c', 'a', 'g']\n codons = [a+b+c for a in bases for b in bases for c in bases]\n aminoacids = 'FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG'\n codon_table = dict(zip(codons, aminoacids))\n \n ### codon lookup ### \n \n pos = 0\n protein = ''\n while pos < len(rna)-2:\n codon = rna[pos:pos+3]\n for key in codon_table:\n if codon == key:\n if codon_table[key] != '*':\n protein = protein + codon_table[key]\n pos +=3\n else:\n pos +=3\n break \n return (protein)","def translate_DNA(dnaStrand,translation_table='DNA_TABLE.txt'):\r\n\r\n #dictionary to store the corresponding protein for each codon\r\n d={'TTT':'F','CTT':'L','ATT':'I','GTT':'V','TTC':'F','CTC':'L','ATC':'I','GTC':'V','TTA':'L','CTA':'L','ATA':'I','GTA':'V','TTG':'L','CTG':'L','ATG':'M','GTG':'V','TCT':'S','CCT':'P','ACT':'T','GCT':'A','TCC':'S','CCC':'P','ACC':'T','GCC':'A','TCA':'S','CCA':'P','ACA':'T','GCA':'A','TCG':'S','CCG':'P','ACG':'T','GCG':'A','TAT':'Y','CAT':'H','AAT':'N','GAT':'D','TAC':'Y','CAC':'H','AAC':'N','GAC':'D','TAA':'Stop','CAA':'Q','AAA':'K','GAA':'E','TAG':'Stop','CAG':'Q','AAG':'K','GAG':'E','TGT':'C','CGT':'R','AGT':'S','GGT':'G','TGC':'C','CGC':'R','AGC':'S','GGC':'G','TGA':'Stop','CGA':'R','AGA':'R','GGA':'G','TGG':'W','CGG':'R','AGG':'R','GGG':'G'}\r\n protiens=\"\"\r\n for i in range(0,len(dnaStrand),3):\r\n #extracting each codon\r\n s=dnaStrand[i:i+3]\r\n if(d[s]!=\"Stop\"):\r\n protiens+=d[s]\r\n\r\n return protiens","def translate_sequence(rna_sequence, genetic_code):\n #Crate an empty list to store AA sequence:\n AA_list = []\n # Convert all rna_sequence to upper case:\n rna_sequence=rna_sequence.upper()\n # Convert all rna_sequence into a list:\n rna_list = list(rna_sequence)\n # This conditon will run if rna_sequence is at least 3 bases long, and only once it find start codon ,\n #and stop once it finds stop codon.\n while True:\n if len(rna_list) > 2:\n codon=''.join(rna_list[0:3])\n #Delete first 3 bases since its alread added as codon, thus no longer needed.\n del rna_list[0:3]\n else:\n break\n #Using genetic code dictionary to find AA for each corresponding codon:\n AA=genetic_code[codon]\n #Break loop once it finds stop codon\n if AA=='*':\n break\n #Add add translatable AA to the AA_list:\n AA_list.append(AA)\n return ''.join(AA_list)","def coding_strand_to_AA(dna):\n amino_acid=\"\"\n for i in range(0, len(dna), 3):\n mycodon=dna[i:i+3]\n # print'this is my codon'\n #print mycodon\n for j in range(len(codons)):\n for k in range(len(codons[j])):\n #print codons[j][k]\n if codons[j][k] == mycodon:\n #print aa[j]\n amino_acid += aa[j]\n return amino_acid\n \n #step uno break apart string into groups of three\n #find sequence +find index\n #then connect to amino acids ","def thread_dna(\n PROT, NUCL, STOP\n ):\n\n # read in aligned protein fasta file\n format = \"fasta\"\n handle = open(PROT)\n PROTa = list(SeqIO.parse(handle, format))\n\n # read in aligned protein fasta file\n format = \"fasta\"\n handle = open(NUCL)\n NUCLf = list(SeqIO.parse(handle, format))\n\n # initialize dictionary for sequences\n pal2nal = {}\n\n # loop through genes and thread DNA over\n # protein alignment\n for entry in range(0, len(PROTa)):\n # save the gene ID to ID\n ID = ''\n ID = PROTa[entry].id\n # save protein sequence to Pseq\n Pseq = ''\n Pseq = PROTa[entry].seq\n # save nucleotide sequence to Nseq\n Nseq = ''\n Nseq = NUCLf[entry].seq\n\n # # check that Nseq is divisible by three and therefore not a pseudogene\n # if len(Nseq) % 3 != 0:\n # print(\"\")\n # print(ID, \"nucleotide sequence has a length of\", len(Nseq))\n # print(\"and cannot be threaded over the protein alignment.\")\n # print(\"Exiting now...\\n\")\n # sys.exit()\n\n pal2nal[ID] = ''\n GAPcnt = 0\n # loop through the sequence\n for AA in range(0, (int(len(Pseq))+1) - 1, 1):\n # if stops should be included\n if STOP == 'T':\n # if AA is a gap insert a codon of gaps\n if Pseq[AA] == \"-\":\n pal2nal[ID] += ('---')\n GAPcnt+=1\n # if AA is not a gap, insert the corresponding codon\n elif Pseq[AA] != \"-\":\n NTwin=(AA-GAPcnt)*3\n pal2nal[ID] += (Nseq[NTwin:NTwin+3])\n # if stops should not be included\n elif STOP == 'F':\n # if AA is a gap insert a codon of gaps\n if Pseq[AA] == \"-\":\n pal2nal[ID] += ('---')\n GAPcnt+=1\n # if AA is not a gap, insert the corresponding codon\n elif Pseq[AA] != \"-\":\n # if AA is a stop or ambiguous insert a codon of gaps\n if Pseq[AA] == 'X' or Pseq[AA] == '*':\n pal2nal[ID] += ('---')\n else:\n NTwin=(AA-GAPcnt)*3\n pal2nal[ID] += (Nseq[NTwin:NTwin+3])\n\n\n\n ## this commented code will check if the nucleotide window \n ## translates to the corresponding codon\n # if Pseq[AA] != Nseq[NTwin:NTwin+3].translate():\n # print(\"\\nAmino acid position\", AA, \"(\",Pseq[AA],\")\", \"does not correspond to codon\")\n # print(Nseq[NTwin:NTwin+3], \"in nucleotide window\", NTwin,\"-\",NTwin+3)\n # print(Nseq[NTwin:NTwin+3], \"translates to\", Nseq[NTwin:NTwin+3].translate())\n # print(\"Nucleotides cannot be threaded ontop of the protein sequence.\")\n # print(\"Exiting now...\\n\")\n # sys.exit()\n\n # print out threaded DNA alignment\n for entry in range(0, len(PROTa)):\n print(\">{}\\n{}\".format(PROTa[entry].id, pal2nal[PROTa[entry].id]))","def translate(self,frame=1):\n if self.seq_type.upper() != \"DNA\":\n return \"Not a DNA sequence (wrong seq_type)\"\n\n aa_output=\"\"\n dna_input=self.seq\n if frame == 0 or frame not in range(-3,4):\n return \"Please specify a correct reading frame number. (+/- 1,2,3)\"\n\n elif frame in range(-3,0):\n dna_input=reverse_complement(dna_input)\n\n for pos in range (abs(frame)-1,len(dna_input)-2,3):\n codon=dna_input[pos:pos+3]\n aa_output += translation_codon(codon)\n\n return myseq(aa_output,\"Protein\")","def coding_strand_to_AA(dna):\n Seq = ''\n for i in range(0,len(dna),3): \n triple = dna[i:i+3]\n print triple\n for k in range(len(codons)):\n if triple in codons[k]: \n print \"Casey Rocks\"\n print codons[k]\n amino = aa[k]\n Seq+=amino\n return Seq","def collapse(L):\n output = \"\"\n for s in L:\n output = output + s\n return output\n\n\n \"\"\"1) Computes the Protein encoded by a sequence of DNA. This function\n does not check for start and stop codons (it assumes that the input\n DNA sequence represents an protein coding region).\n \n dna: a DNA sequence represented as a string\n returns: a string containing the sequence of amino acids encoded by the\n the input DNA fragment\n \"\"\"","def convert_to_dna(protein_sequence, wt_protein_dict):\n variant_dna_codons = []\n for index in range(0, len(protein_sequence.seq)):\n wt_aa = str(wt_protein_dict[index + 1][0])\n codon = str(wt_protein_dict[index + 1][1])\n variant_aa = protein_sequence.seq[index]\n if variant_aa != wt_aa:\n if variant_aa is not '-':\n codon = sorted_codon_table[str(variant_aa)][0]\n variant_dna_codons.append(codon)\n variant_dna_str = \"\".join(variant_dna_codons)\n variant_dna_seq = Seq(variant_dna_str, IUPAC.unambiguous_dna)\n variant_dna_seq_obj = SeqRecord(variant_dna_seq, id=protein_sequence.id, name=protein_sequence.name,\n description=protein_sequence.description)\n return variant_dna_seq_obj","def _process_prosody(sonority):\n assert 9 not in sonority[1:-1]\n assert sonority[0] == sonority[-1] == 9\n\n # create the output values\n psequence = []\n first = True # stores whether first syllable is currently being processed\n\n for i in range(1, len(sonority) - 1):\n # get a segment with context\n a, b, c = sonority[i - 1], sonority[i], sonority[i + 1]\n\n if b == 7: # a vowel\n if first:\n psequence.append('X')\n first = False\n elif c == 9: # last\n psequence.append('Z')\n else:\n psequence.append('Y')\n elif b == 8: # a tone\n psequence.append('T')\n elif a >= b >= c or c == 8: # descending\n if c == 9: # word final position\n psequence.append('Z' if b == 7 else 'N') # vowel or consonant\n else:\n if first:\n first = False\n psequence.append('A')\n else:\n psequence.append('L')\n elif b < c or a > b <= c or a < b <= c: # ascending\n # check for syllable first\n if a == 9:\n psequence.append('A')\n elif a >= b:\n if c == 9:\n psequence.append('N')\n else:\n if psequence[-1] != 'A':\n psequence = psequence[:-1] + [psequence[-1].replace('L', 'M')] + ['B']\n else:\n psequence.append('C')\n else:\n psequence.append('C')\n elif a < b > c: # consonant peak\n if first:\n psequence.append('X')\n first = False\n else:\n psequence.append('Y')\n else:\n raise ValueError(\n \"Conversion to prosodic string failed due to a condition which was not \"\n \"defined in the convertion, for details compare the numerical string \"\n \"{0} with the profile string {1}\".format(sonority, psequence))\n return psequence","def translation (RNA):\n\tresult = []\n\tif len(RNA) == 0: return result\n\tdna.isNucleotide(RNA)\n\tif \"T\" in RNA: raise dna.InvalidSequenceError\n\n\torf = dna.get_orf(RNA)\n\n\tfor frame in orf:\n\t\tpeptide = return_peptide(RNA[frame[0]:frame[1]])\n\t\tresult.append(peptide)\n\treturn result","def proteins(strand: str) -> list:\n codons_to_translate = codonify(strand)\n return translation(codons_to_translate)","def main():\r\n\r\n # contents = ['ATGGCCATGGCCCCCAGAACTGAGATCAATAGTACCCGTATTAACGGGTGA', 'MA'] # sample input\r\n contents = []\r\n for line in sys.stdin:\r\n contents.append(line.strip())\r\n myPeptide = GenomeEncoding(contents[0], contents[1])\r\n myPeptide.getCodonSeqs()\r\n myPeptide.getRevCodonSeqs()\r\n myPeptide.printEncodePep()","def try_protein(self):\n location = [0, 0]\n fold = 0\n \n # loop over aminoacids of the data and add info to aminoacids object\n for i, char in enumerate(self.data):\n aminoacid_number = i\n aminoacid_type = char \n \n # make aminoacid object and add to aminoacids list\n aminoacid = Aminoacid(aminoacid_type, aminoacid_number, location, fold)\n self.occupied.append(aminoacid.location)\n self.aminoacids.append(aminoacid)\n\n # make a line orientation as default\n location = [0, len(self.data) + i]\n return","def translate(codon):\n \n table = { \n 'ATA':'I', 'ATC':'I', 'ATT':'I', 'ATG':'M', \n 'ACA':'T', 'ACC':'T', 'ACG':'T', 'ACT':'T', \n 'AAC':'N', 'AAT':'N', 'AAA':'K', 'AAG':'K', \n 'AGC':'S', 'AGT':'S', 'AGA':'R', 'AGG':'R', \n 'CTA':'L', 'CTC':'L', 'CTG':'L', 'CTT':'L', \n 'CCA':'P', 'CCC':'P', 'CCG':'P', 'CCT':'P', \n 'CAC':'H', 'CAT':'H', 'CAA':'Q', 'CAG':'Q', \n 'CGA':'R', 'CGC':'R', 'CGG':'R', 'CGT':'R', \n 'GTA':'V', 'GTC':'V', 'GTG':'V', 'GTT':'V', \n 'GCA':'A', 'GCC':'A', 'GCG':'A', 'GCT':'A', \n 'GAC':'D', 'GAT':'D', 'GAA':'E', 'GAG':'E', \n 'GGA':'G', 'GGC':'G', 'GGG':'G', 'GGT':'G', \n 'TCA':'S', 'TCC':'S', 'TCG':'S', 'TCT':'S', \n 'TTC':'F', 'TTT':'F', 'TTA':'L', 'TTG':'L', \n 'TAC':'Y', 'TAT':'Y', 'TAA':'*', 'TAG':'*', \n 'TGC':'C', 'TGT':'C', 'TGA':'*', 'TGG':'W', \n } \n \n assert codon in table.keys(), \"Not a valid codon sequence.\"\n \n return table[codon]","def get_seq_from_pdbchain(chain):\n type_chain = check_type(chain)\n if type_chain == \"protein\":\n three_res_list = []\n for res in chain:\n residues_atoms = res.get_atoms()\n for atom in residues_atoms:\n if atom.get_name() == 'CA':\n residue = atom.get_parent()\n three_res_list.append(residue.get_resname())\n return three_to_one(three_res_list) # three_to_one function\n else:\n nucleic_acid_res = []\n for res in chain:\n residues_atoms = res.get_atoms()\n for atom in residues_atoms:\n if atom.get_name() == 'P':\n residue = atom.get_parent()\n nucleic_acid_res.append(residue.get_resname())\n nucleic_acid_seq = [x[2] for x in nucleic_acid_res]\n return \"\".join(nucleic_acid_seq)","def main():\n\n args = get_args()\n seq = args.seq.upper()\n codon_to_aa = {\n 'AAA': 'K',\n 'AAC': 'N',\n 'AAG': 'K',\n 'AAU': 'N',\n 'ACA': 'T',\n 'ACC': 'T',\n 'ACG': 'T',\n 'ACU': 'T',\n 'AGA': 'R',\n 'AGC': 'S',\n 'AGG': 'R',\n 'AGU': 'S',\n 'AUA': 'I',\n 'AUC': 'I',\n 'AUG': 'M',\n 'AUU': 'I',\n 'CAA': 'Q',\n 'CAC': 'H',\n 'CAG': 'Q',\n 'CAU': 'H',\n 'CCA': 'P',\n 'CCC': 'P',\n 'CCG': 'P',\n 'CCU': 'P',\n 'CGA': 'R',\n 'CGC': 'R',\n 'CGG': 'R',\n 'CGU': 'R',\n 'CUA': 'L',\n 'CUC': 'L',\n 'CUG': 'L',\n 'CUU': 'L',\n 'GAA': 'E',\n 'GAC': 'D',\n 'GAG': 'E',\n 'GAU': 'D',\n 'GCA': 'A',\n 'GCC': 'A',\n 'GCG': 'A',\n 'GCU': 'A',\n 'GGA': 'G',\n 'GGC': 'G',\n 'GGG': 'G',\n 'GGU': 'G',\n 'GUA': 'V',\n 'GUC': 'V',\n 'GUG': 'V',\n 'GUU': 'V',\n 'UAA': 'Stop',\n 'UAC': 'Y',\n 'UAG': 'Stop',\n 'UAU': 'Y',\n 'UCA': 'S',\n 'UCC': 'S',\n 'UCG': 'S',\n 'UCU': 'S',\n 'UGA': 'Stop',\n 'UGC': 'C',\n 'UGG': 'W',\n 'UGU': 'C',\n 'UUA': 'L',\n 'UUC': 'F',\n 'UUG': 'L',\n 'UUU': 'F',\n }\n\n k = 3\n\n # 1: for loop\n # protein = ''\n # for codon in [seq[i:i + k] for i in range(0, len(seq), k)]:\n # aa = codon_to_aa.get(codon, '-')\n # if aa == 'Stop':\n # break\n # protein += aa\n\n # 2: list comprehension, slice to remove Stop\n # codons = [seq[i:i + k] for i in range(0, len(seq), k)]\n # aa = [codon_to_aa.get(codon, '-') for codon in codons]\n # if 'Stop' in aa:\n # aa = aa[:aa.index('Stop')]\n # print(''.join(aa))\n\n # 3: L.C. -> map(), slice -> takewhile\n # codons = map(lambda i: seq[i:i + k], range(0, len(seq), k))\n # aa = map(lambda codon: codon_to_aa.get(codon, '-'), codons)\n # print(''.join(takewhile(lambda c: c != 'Stop', aa)))\n\n # 4: combine map()\n # aa = map(lambda c: codon_to_aa.get(c, '-'),\n # map(lambda i: seq[i:i + k], range(0, len(seq), k)))\n # print(''.join(takewhile(lambda c: c != 'Stop', aa)))\n\n # 5: combine all\n # print(''.join(\n # takewhile(\n # lambda c: c != 'Stop',\n # map(lambda c: codon_to_aa.get(c, '-'),\n # map(lambda i: seq[i:i + k], range(0, len(seq), k))))))\n\n # 6: Seq\n print(str(Seq(args.seq).translate()).replace('*', ''))","def gene_to_protein(gene: str, intrones: Union[str, Collection[str]]) -> str:\n intrones = intrones if not isinstance(intrones, str) else (intrones,)\n for introne in intrones:\n gene = gene.replace(introne, \"\")\n return dna_to_protein(gene)","def prot_sequence_finder(protL):\n \n idDict = prot_id_converter(protL, \"9606\", inpDB = \"genesymbol\",outDB=\"refseqproteingi\")\n seqD = prot_entrez_fetch(idDict, retM=\"gb\", retT=\"fasta\")\n \n protD = {}\n \n for keyS, valueS in idDict.items():\n protD[keyS] = seqD[valueS]\n \n return protD","def ProteinRead(pdb_file, Include_dAA = True, IncludeWATER = False):\n # structure from input file or fetched if not present\n if(pdb_file[-4:] == '.pdb' or pdb_file[-3:] == '.gz'):\n ppdb = PandasPdb().read_pdb(pdb_file)\n else:\n ppdb = PandasPdb().fetch_pdb(pdb_file)\n \n # lists for standard and d-AA used to save structure to dataset \n standardAA = ['ALA','ARG','ASN','ASP','CYS','GLN','GLU','GLY','HIS','ILE','LEU','LYS','MET','PHE','PRO','SER','THR','TRP','TYR','VAL']\n d_AA = ['DAL','DAR','DSG','DAS','DCY','DGN','DGL','GLY','DHI','DIL','DLE','DLY','MED','DPN','DPR','DSN','DTH','DTR','DTY','DVA']#scan takes into account only standard amino acids\n\n for aa in standardAA: #ATOM entries, excluding water molecules \n if(aa==standardAA[0]):\n ppdb_ATOM = ppdb.df['ATOM'][ppdb.df['ATOM']['residue_name'] == aa] \n else:\n ppdb_ATOM = pd.concat([ppdb_ATOM, ppdb.df['ATOM'][ppdb.df['ATOM']['residue_name'] == aa]], ignore_index=True) \n\n if(Include_dAA):\n for i in range(0,len(d_AA)): \n if(d_AA[i]!='GLY'):\n ppdb_d_AA = pd.concat([ppdb.df['ATOM'][ppdb.df['ATOM']['residue_name'] == d_AA[i]],ppdb.df['HETATM'][ppdb.df['HETATM']['residue_name'] == d_AA[i]]], ignore_index=True)\n pd.options.mode.chained_assignment = None \n ppdb_d_AA['residue_name'].iloc[:] = standardAA[i] #dAA considered as standard one for scan \n ppdb_ATOM = pd.concat([ppdb_ATOM, ppdb_d_AA], ignore_index=True) \n\n ppdb_PROTEIN = ppdb_ATOM #protein atoms saved here \n ppdb_WATER = pd.concat([ppdb.df['HETATM'][ppdb.df['HETATM']['residue_name'] == 'HOH'],ppdb.df['ATOM'][ppdb.df['ATOM']['residue_name'] == 'HOH'],ppdb.df['HETATM'][ppdb.df['HETATM']['residue_name'] == 'WAT'],ppdb.df['ATOM'][ppdb.df['ATOM']['residue_name'] == 'WAT']], ignore_index=True) #oxygen atoms of water molecules\n #can be both HETATM (standard pdb file) or ATOM (vmd output)\n if(len(ppdb_WATER)>0 and IncludeWATER):\n pd.options.mode.chained_assignment = None \n ppdb_WATER['residue_name'].iloc[:] = 'HOH'\n ppdb_WATER['chain_id'].iloc[:] = 'water'\n ppdb_ATOM = pd.concat([ppdb_ATOM, ppdb_WATER], ignore_index=True)\n\n Chains = []\n for i in range(0,len(ppdb_ATOM)):\n if(ppdb_ATOM['chain_id'].iloc[i] in Chains):\n continue\n else:\n Chains.append(ppdb_ATOM['chain_id'].iloc[i]) \n return ppdb_ATOM, Chains","def cropdna(dna, start=0, end=None, supfeature=False, product=None, process_description=None, process_name=None, \n pd=None, pn=None, quinable=True, **kwargs):\n \n kwargs.setdefault(\"_sourcefile\", None) \n kwargs.setdefault(\"process_id\", None)\n kwargs.setdefault(\"original_ids\", []) \n _sourcefile = kwargs[\"_sourcefile\"] \n process_id = kwargs[\"process_id\"] \n original_ids = kwargs[\"original_ids\"]\n\n project = None\n project = project if product is None else product\n process_name = pn if process_name is None else process_name\n process_description = pd if process_description is None else process_description\n\n if end is None or end == 0:\n end = len(dna.seq) \n \n if start == 0 and end == len(dna.seq):\n subdna = cutdna(dna, start, product=project, quinable=0)[0] \n crop_positions = ((0, 0), (len(dna.seq), len(dna.seq)))\n else:\n subdna, crop_positions = cutdna(dna, start, end, product=project, crop=True, quinable=0) \n \n if quinable == 1 and quinable == True: \n args = []\n new_positions = [] \n history_features = [subdna._history_feature] \n for new_pos, pos in zip(crop_positions, (start, end)):\n new_pos = \"/\".join(list(map(str,new_pos)))\n new_pos = \"'\" + new_pos + \"'\"\n if \"__dict__\" in dir(pos) and \"_dnafeature\" in pos.__dict__:\n qkey = pos._qkey\n for qindex, qfeat in enumerate(dna.__class__.queried_features_dict[qkey]):\n if qfeat._second_id == pos._second_id:\n break\n args.append(\"QUEEN.queried_features_dict['{}'][{}]\".format(qkey, qindex))\n history_features.append(pos.subject._history_feature) \n \n elif \"__dict__\" in dir(pos) and \"_qint\" in pos.__dict__:\n qkey = pos.qkey\n for qindex, qfeat in enumerate(dna.__class__.queried_features_dict[qkey]):\n if qfeat._second_id == pos.parental_id:\n break\n args.append(\"QUEEN.queried_features_dict['{}'][{}].{}\".format(pos.qkey, qindex, pos.name))\n history_features.append(pos.parent.subject._history_feature) \n \n else:\n args.append(new_pos)\n\n pos1, pos2 = new_pos.split(\"/\") \n if pos1[1:] == pos2[:-1]:\n new_positions.append(pos1[1:]) \n else:\n new_positions.append(new_pos) \n \n if type(supfeature) in (tuple, list) and type(supfeature[0]) == dict:\n for feature_dict in supfeature: \n subdna.setfeature(feature_dict) \n elif type(supfeature) == dict:\n subdna.setfeature(supfeature)\n\n project = \"\" \n fsupfeature = \"\" if supfeature == False else \", supfeature={}\".format(str(supfeature)) \n fproduct = \"\" if product is None else \", product='\" + product + \"'\"\n process_name = \"\" if process_name is None else \", process_name='\" + process_name + \"'\"\n process_description = \"\" if process_description is None else \", process_description='\" + process_description + \"'\" \n \n subdna._product_id = subdna._unique_id if product is None else product \n building_history = \"QUEEN.dna_dict['{}'] = cropdna(QUEEN.dna_dict['{}'], start={}, end={}{}{}{}{}{})\".format(subdna._product_id, dna._product_id, args[0], args[1], fsupfeature, project, fproduct, process_name, process_description)\n \n history_feature = _combine_history(subdna, history_features)\n subdna._history_feature = history_feature\n process_id, original_ids = make_processid(subdna, building_history, process_id, original_ids)\n add_history(subdna, [building_history, \"start: {}; end: {}\".format(*new_positions), \",\".join([process_id] + original_ids)], _sourcefile) \n subdna._check_uniqueness()\n else:\n subdna.__dict__[\"_product_id\"] = dna._product_id if \"_product_id\" in dna.__dict__ else dna._unique_id\n\n if product is None:\n pass \n else:\n product.replace(\" \",\"\") \n match = re.fullmatch(\"(.+)\\[(.+)\\]\", product)\n if match:\n if match.group(2).isdecimal() == True:\n subdna.__class__._namespace[match.group(1)][int(match.group(2))] = subdna\n else:\n subdna.__class__._namespace[match.group(1)][match.group(2)] = subdna\n else: \n subdna.__class__._namespace[product] = subdna\n return subdna","def get_all_translations(rna_sequence, genetic_code):\n #Convert all rna_sequence to upper case:\n rna_sequence=rna_sequence.upper()\n #get the lengh of RNA seq.\n total_rna_bases=len(rna_sequence)\n #Create an empty list to store all possible AA seq.\n polypeptide_list = []\n #Looping through all the RNA bases, selecting all 3 possible reading frames to scan for tranlation.\n for i in range(total_rna_bases):\n i_end= i +3\n next_three=rna_sequence[i:i_end]\n #Condition to check if the condon is start codon\n if next_three=='AUG':\n #If condition satisfies, translate all rna seq from start to stop codon using first function,\n #translate_sequence\n polypeptide=translate_sequence(rna_sequence[i:], genetic_code)\n polypeptide_list.append(polypeptide)\n #Return all 3 possible reading frames as a list in polypeptide_list\n return polypeptide_list","def extract_sequence(molecule, begin, gap = 8):\n # Validte the length of the molecule\n validate_molecule_length(molecule)\n # Define the sequence variable to store the amino acid sequence\n sequence = ''\n # Get the total numbers of residues\n length = len(molecule)\n # The begin point should be equal or larger than 1 and equal or less than len(molecule) - gap \n if isinstance(begin, int) and begin >= 0 and begin <= (length - gap) : \n for i in range(gap + 1):\n # Get the amino acid kind\n aa = molecule[begin + i].kind\n # Convert the three-letter amino acid name to one-letter character \n # Store it in the sequence\n sequence += convertAA[\"PDB\"][aa] \n if len(sequence) == gap + 1 :\n return sequence\n else:\n text += \"The amino acid number in the sequence is not correct\"\n raise DeimmunizationError(text)","def binary_to_seq():\n bin_seq, dico_binary, comp_seq, file_comp = utf8_to_binary()\n \n #for each binary value associate the corresponding letter (key) \n #according to the dictionnary \n dna_seq = \"\"\n reading_binary = \"\"\n for value in bin_seq:\n reading_binary += value\n for letter, code in dico_binary.items():\n if code == reading_binary:\n dna_seq += letter\n reading_binary = \"\"\n break\n \n #print(dna_seq, bin_seq, comp_seq, file_comp)\n return dna_seq, bin_seq, comp_seq, file_comp","def find_aligned_codons(aln):\n # throw out codons with non mod 3 gaps\n ind2 = []\n for i in range(0, aln.alignlen(), 3):\n bad = False\n\n for key, val in aln.iteritems():\n codon = val[i:i+3]\n if \"-\" in codon and codon != \"---\":\n bad = True\n break\n\n if not bad:\n ind2.extend([i, i+1, i+2])\n\n return ind2","def coding_strand_to_AA(dna):\n amino_acid = ''\n i = 0\n while i + 3 < len(dna) + 1:\n amino_acid += aa_table[dna[i:i+3]]\n i += 3\n return amino_acid","def _process_cdss(self, prot_fasta_path):\n if self.is_metagenome:\n prot_fasta = {} # type: dict\n untranslatable_prot = set()\n for cds_id in self.cdss:\n cds = self.feature_dict[cds_id]\n try:\n prot_seq = str(Seq(cds['dna_sequence']).translate(\n self.code_table, cds=True).strip(\"*\"))\n except TranslationError as e:\n cds['warnings'] = cds.get('warnings', []) + [str(e)]\n # NOTE: we may need a different way of handling this for metagenomes.\n prot_seq = \"\"\n if self.is_metagenome:\n untranslatable_prot.add(cds_id)\n\n if self.is_metagenome:\n if prot_seq != \"\":\n protein_id = \"\"\n if cds.get(\"aliases\"):\n aliases = cds['aliases']\n for key, val in aliases:\n if key == \"protein_id\":\n protein_id = val\n if not protein_id:\n protein_id = cds['id'] # assign to some default\n else:\n # log a warning here?\n pass\n # TODO: update header to reflect what we actually want people\n # to see.\n if protein_id in prot_fasta:\n prot_fasta[protein_id][0] += \"|\" + cds['id']\n else:\n fasta_seq_data = \">\" + protein_id + \" cds_ids:\" + cds['id']\n prot_fasta[protein_id] = [fasta_seq_data, prot_seq]\n else:\n pass\n\n else:\n cds.update({\n \"protein_translation\": prot_seq,\n \"protein_md5\": hashlib.md5(prot_seq.encode('utf8')).hexdigest(),\n \"protein_translation_length\": len(prot_seq),\n })\n\n if 'parent_gene' in cds:\n parent_gene = self.feature_dict[cds['parent_gene']]\n # no propigation for now\n propagate_cds_props_to_gene(cds, parent_gene, self.is_metagenome)\n elif self.generate_genes:\n spoof = copy.copy(cds)\n spoof['type'] = 'gene'\n spoof['id'] = cds['id']+\"_gene\"\n spoof['cdss'] = [cds['id']]\n spoof['warnings'] = [warnings['spoofed_gene'].format(cds['id'])]\n self.feature_dict[spoof['id']] = spoof\n cds['parent_gene'] = spoof['id']\n self.spoof_gene_count += 1\n else:\n raise ValueError(warnings['no_spoof'])\n\n self.feature_dict[cds['id']] = cds\n\n if self.is_metagenome:\n with open(prot_fasta_path, 'w') as fid:\n for key, line in prot_fasta.items():\n fid.write('\\n'.join(line))\n # do something with 'untranslatable_prot'","def all_possible_gene_transcription(dna: str):\n result = set()\n for dna in (dna, reverse_complement(dna)):\n rna = dna_to_rna(dna)\n start = find_motif(rna, START_CODON)\n for s in start:\n r = rna_to_protein(rna, start=s, end=True)\n if r:\n result.add(r)\n return result","def translate_framed_strand(framed_strand):\n\n polypeptide = []\n # Iterate through all the codons in our strand and look up their resultant amino acid\n logging.info(\"Translating strand: \" + str(framed_strand))\n for codon in framed_strand:\n if len(codon) != 3:\n break\n if codon in stop_codons:\n # We are at the end of the sequence, so cut.\n logging.debug(\"Stopping at codon \" + codon)\n break\n logging.debug(\"Adding polypeptide \" + codons_to_amino_acids[codon][2])\n polypeptide.append(codons_to_amino_acids[codon])\n return polypeptide","def _GetPseudoAAC2(ProteinSequence,lamda=10,weight=0.05):\n\trightpart=[]\n\tfor i in range(lamda):\n\t\trightpart.append(_GetSequenceOrderCorrelationFactor(ProteinSequence,k=i+1))\n\t\n\tresult={}\n\ttemp=1+weight*sum(rightpart)\n\tfor index in range(20,20+lamda):\n\t\tresult['PAAC'+str(index+1)]=round(weight*rightpart[index-20]/temp*100,3)\n\t\n\treturn result","def getSequencefromPDB(pdbfile, chain='C', index=0):\n parser = PDB.PDBParser(QUIET=True)\n struct = parser.get_structure(pdbfile,pdbfile)\n ppb = PDB.PPBuilder()\n model = struct[0]\n peptides = ppb.build_peptides(model[chain])\n seq=''\n for i,pep in enumerate(peptides):\n seq+=str(pep.get_sequence())\n return seq","def coding_strand_to_AA(dna):\n coding_strand = ''\n for i in range(len(dna)/3):\n aa = dna[3*i:(3*i)+3]\n coding_strand += aa_table[aa]\n return coding_strand","def translate(rna):\n RNA_CODON_TABLE = {\"UUU\": \"F\", \"UUC\": \"F\", \"UUA\": \"L\", \"UUG\": \"L\",\n \"UCU\": \"S\", \"UCC\": \"S\", \"UCA\": \"S\", \"UCG\": \"S\",\n \"UAU\": \"Y\", \"UAC\": \"Y\", \"UAA\": \"*\", \"UAG\": \"*\",\n \"UGU\": \"C\", \"UGC\": \"C\", \"UGA\": \"*\", \"UGG\": \"W\",\n \"CUU\": \"L\", \"CUC\": \"L\", \"CUA\": \"L\", \"CUG\": \"L\",\n \"CCU\": \"P\", \"CCC\": \"P\", \"CCA\": \"P\", \"CCG\": \"P\",\n \"CAU\": \"H\", \"CAC\": \"H\", \"CAA\": \"Q\", \"CAG\": \"Q\",\n \"CGU\": \"R\", \"CGC\": \"R\", \"CGA\": \"R\", \"CGG\": \"R\",\n \"AUU\": \"I\", \"AUC\": \"I\", \"AUA\": \"I\", \"AUG\": \"M\",\n \"ACU\": \"T\", \"ACC\": \"T\", \"ACA\": \"T\", \"ACG\": \"T\",\n \"AAU\": \"N\", \"AAC\": \"N\", \"AAA\": \"K\", \"AAG\": \"K\",\n \"AGU\": \"S\", \"AGC\": \"S\", \"AGA\": \"R\", \"AGG\": \"R\",\n \"GUU\": \"V\", \"GUC\": \"V\", \"GUA\": \"V\", \"GUG\": \"V\",\n \"GCU\": \"A\", \"GCC\": \"A\", \"GCA\": \"A\", \"GCG\": \"A\",\n \"GAU\": \"D\", \"GAC\": \"D\", \"GAA\": \"E\", \"GAG\": \"E\",\n \"GGU\": \"G\", \"GGC\": \"G\", \"GGA\": \"G\", \"GGG\": \"G\"}\n str = ''\n list = [rna[i:i+3] for i in range(0,len(rna),3)]\n for x in list:\n #checks if x is in key of RNA_CODON_TABLE\n if x in RNA_CODON_TABLE:\n #appends only if the value for the given key is not *\n if RNA_CODON_TABLE[x] != '*':\n str = str + RNA_CODON_TABLE[x]\n #if only one char is extra(meaning apart form the 3 pair characters available in dictionary)\n #checks if the char is in following\n elif len(x) == 1 and x in ['A','G','C','U']:\n str = str + x\n #if the char is of length 2 i.e, 2 words extra\n elif len(x) == 2 and x[0] in ['A','G','C','U'] and x[1] in ['A','G','C','U']:\n #Then appending the char to the actually converted string\n str = str + x[0]\n str = str + x[1]\n #if the char is not in the above characters then it is a unrecognised character.\n else:\n print(\"Unrecognised character:\",x)\n return str","def write_protein_fasta(args, clusters=None, fasta_dir=None):\n row, concat_fasta_path, frags = args\n dotpath = row[\"path\"]\n phylogeny_dict = {\"prot.idx\": row.name, \"path\": dotpath}\n for phy_prop in [name for name in row.index if name.startswith(\"phy.\")]:\n phylogeny_dict[phy_prop] = row[phy_prop]\n inpath = dotpath_to_path(dotpath)\n prot_info = read_tsv_or_parquet(inpath / PROTEINS_FILE)\n prot_info[\"frag.idx\"] = prot_info[\"frag.id\"].map(\n lambda oid: frags.loc[oid][\"frag.idx\"]\n )\n prot_info[\"frag.is_plas\"] = prot_info[\"frag.id\"].map(\n lambda oid: frags.loc[oid][\"frag.is_plas\"]\n )\n prot_info[\"frag.is_scaf\"] = prot_info[\"frag.id\"].map(\n lambda oid: frags.loc[oid][\"frag.is_scaf\"]\n )\n prot_info[\"frag.is_chr\"] = prot_info[\"frag.id\"].map(\n lambda oid: frags.loc[oid][\"frag.is_chr\"]\n )\n prot_info[\"frag.id\"] = prot_info[\"frag.id\"].map(\n lambda oid: frags.loc[oid][\"frag.id\"]\n )\n # Write out updated protein info\n write_tsv_or_parquet(prot_info, inpath / HOMOLOGY_FILE)\n # include phylogeny info in per-sequence info\n for prop in phylogeny_dict:\n prot_info[prop] = phylogeny_dict[prop]\n # write concatenated sequence info\n if clusters is None:\n fasta_path = concat_fasta_path\n info_to_fasta(None, fasta_path, append=True, infoobj=prot_info)\n else:\n for cluster_id, subframe in clusters.groupby(by=[\"cluster_id\"]):\n cluster_info = prot_info[prot_info.index.isin(subframe[\"members\"])]\n fasta_path = fasta_dir / f\"{cluster_id}.fa\"\n info_to_fasta(None, fasta_path, append=True, infoobj=cluster_info)","def GetPseudoAAC2(ProteinSequence,lamda=30,weight=0.05,AAP=[_Hydrophobicity,_hydrophilicity]):\n\trightpart=[]\n\tfor i in range(lamda):\n\t\trightpart.append(GetSequenceOrderCorrelationFactor(ProteinSequence,i+1,AAP))\n\t\n\tresult={}\n\ttemp=1+weight*sum(rightpart)\n\tfor index in range(20,20+lamda):\n\t\tresult['PAAC'+str(index+1)]=round(weight*rightpart[index-20]/temp*100,3)\n\t\n\treturn result","def build_seq_data(seq,\n sequence_length,\n initial_primers,\n search_range):\n \n aligned_seq=DNA.make_seq(seq)\n # remove gap characters\n unaligned_seq=str(DNA.make_seq(seq).degap())\n gaps=aligned_seq.gap_maps()\n \n if search_range:\n primer_start = get_corrected_index(seq,int(search_range.split(\":\")[0]))\n primer_end = get_corrected_index(seq,int(search_range.split(\":\")[1]))\n # Correct in case end index is close to the end of the sequence\n if primer_end + sequence_length > len(unaligned_seq):\n primer_end = len(unaligned_seq)-sequence_length+1\n\n else:\n primer_start = 0\n primer_end = len(unaligned_seq)-sequence_length+1\n \n for n in range(primer_start, primer_end):\n seq_slice=unaligned_seq[n:n+sequence_length]\n aligned_index=gaps[0][n]\n unaligned_index=n\n init_key=(seq_slice,aligned_index)\n initial_primers[init_key]=unaligned_index\n \n return initial_primers","def coding_strand_to_AA(dna):\n dna_codons = split_into_codons(dna)\n i = 0\n aa_string = ''\n while i < len(dna_codons):\n if len(dna_codons[i]) == 3:\n amino_acid = aa_table[dna_codons[i]]\n aa_string += amino_acid\n i += 1\n return aa_string","def binaryEncode(peptide):\n\n #do 1 hot encoding\n binaryPeptide=''\n for aa in peptide:\n binaryAmino=''\n if aa =='A':\n binaryAmino='10000000000000000000'\n if aa =='R':\n binaryAmino='01000000000000000000'\n if aa =='N':\n binaryAmino='00100000000000000000'\n if aa =='D':\n binaryAmino='00010000000000000000'\n if aa =='C':\n binaryAmino='00001000000000000000'\n if aa =='Q':\n binaryAmino='00000100000000000000'\n if aa =='E':\n binaryAmino='00000010000000000000'\n if aa =='G':\n binaryAmino='00000001000000000000'\n if aa =='H':\n binaryAmino='00000000100000000000'\n if aa =='I':\n binaryAmino='00000000010000000000'\n if aa =='L':\n binaryAmino='00000000001000000000'\n if aa =='K':\n binaryAmino='00000000000100000000'\n if aa =='M':\n binaryAmino='00000000000010000000'\n if aa =='F':\n binaryAmino='00000000000001000000'\n if aa =='P':\n binaryAmino='00000000000000100000'\n if aa =='S':\n binaryAmino='00000000000000010000'\n if aa =='T':\n binaryAmino='00000000000000001000'\n if aa =='W':\n binaryAmino='00000000000000000100'\n if aa =='Y':\n binaryAmino='00000000000000000010'\n if aa =='V':\n binaryAmino='00000000000000000001'\n binaryPeptide=binaryPeptide +binaryAmino\n if len(binaryPeptide) == 500*20:\n break \n \n while len(binaryPeptide) < 500*20:\n binaryPeptide = binaryPeptide +str(0)\n \n binaryPeptide = np.array(list(binaryPeptide),dtype=float)\n binaryPeptide = np.reshape(binaryPeptide,(binaryPeptide.shape[0],1))\n binaryPeptide = np.transpose(binaryPeptide)\n return binaryPeptide","def get_protein_fasta(uniprot_id):\r\n url = \"http://www.uniprot.org/uniprot/{}.fasta\".format(uniprot_id)\r\n string = re.split(\"\\n\",ur.urlopen(url).read().decode(),1)[1]\r\n return re.sub(\"\\n\",\"\",string)","def getMaskedSeq(align, mode='mask', barcode=False, delimiter=default_delimiter):\n seq = align.seq\n\n # Build output sequence\n if mode == 'tag' or not align.align_primer:\n # Do not modify sequence\n out_seq = seq\n elif mode == 'trim':\n # Remove region before primer\n if not align.rev_primer:\n out_seq = seq[align.start:]\n else: \n out_seq = seq[:align.end]\n elif mode == 'cut':\n # Remove primer and preceding region\n if not align.rev_primer:\n out_seq = seq[align.end:]\n else: \n out_seq = seq[:align.start]\n elif mode == 'mask':\n # Mask primer with Ns and remove preceding region\n if not align.rev_primer:\n mask_len = align.end - align.start + align.gaps\n out_seq = 'N' * mask_len + seq[align.end:]\n if hasattr(seq, 'letter_annotations') and \\\n 'phred_quality' in seq.letter_annotations:\n out_seq.letter_annotations['phred_quality'] = \\\n [0] * mask_len + \\\n seq.letter_annotations['phred_quality'][align.end:]\n else:\n mask_len = min(align.end, len(seq)) - align.start + align.gaps\n out_seq = seq[:align.start] + 'N' * mask_len\n if hasattr(seq, 'letter_annotations') and \\\n 'phred_quality' in seq.letter_annotations:\n out_seq.letter_annotations['phred_quality'] = \\\n seq.letter_annotations['phred_quality'][:align.start] + \\\n [0] * mask_len\n \n # Add alignment annotations to output SeqRecord\n out_seq.annotations = seq.annotations \n out_seq.annotations['primer'] = align.primer\n out_seq.annotations['prstart'] = align.start\n out_seq.annotations['error'] = align.error\n\n # Parse seq annotation and create output annotation\n seq_ann = parseAnnotation(seq.description, delimiter=delimiter)\n out_ann = OrderedDict([('SEQORIENT', seq.annotations['seqorient']),\n ('PRIMER', align.primer)])\n \n # Add ID sequence to description\n if barcode:\n seq_code = seq[:align.start].seq if not align.rev_primer \\\n else seq[align.end:].seq\n out_seq.annotations['barcode'] = seq_code\n out_ann['BARCODE'] = seq_code\n \n out_ann = mergeAnnotation(seq_ann, out_ann, delimiter=delimiter)\n out_seq.id = flattenAnnotation(out_ann, delimiter=delimiter)\n out_seq.description = ''\n\n return out_seq","def coding_strand_to_AA(dna):\n list1 = get_codons(dna)\n string = ''\n for codon in list1:\n try:\n string = string + aa_table[codon]\n except KeyError:\n continue\n return string","def _parse_peptidoform(seq: str, modification_list: list[dict], charge: Union[int, None]):\n peptide = [\"\"] + list(seq) + [\"\"]\n\n # Add modification labels\n for mod in modification_list:\n peptide[int(mod[\"location\"])] += f\"[{mod['name']}]\"\n\n # Add dashes between residues and termini, and join sequence\n peptide[0] = peptide[0] + \"-\" if peptide[0] else \"\"\n peptide[-1] = \"-\" + peptide[-1] if peptide[-1] else \"\"\n proforma_seq = \"\".join(peptide)\n\n # Add charge state\n if charge:\n proforma_seq += f\"/{charge}\"\n\n return Peptidoform(proforma_seq)","def test_translate(self):\n \n orf = 'ATGTGGAGACGGAAACATCCGAGGACATCCGGAGGAACCCGGGGAGTTCTGAGTGGTAATTAG'\n expected_primers = Seq('MWRRKHPRTSGGTRGVLSGN*', HasStopCodon(IUPAC.ExtendedIUPACProtein(), '*'))\n result_primers = translate(orf)\n self.assertEqual(result_primers, expected_primers)\n self.assertEqual(len(result_primers), 21)\n self.assertEqual(isinstance(result_primers, Seq), True)","def guess_seq(seq):\n dna = \"ACTG-N\"\n \n chars = util.unique(seq.upper())\n \n for char in chars:\n if char not in dna:\n return \"pep\"\n return \"dna\"","def _find_iupac(self):\n # Create a string of the two states of the SNP in alphabetical order\n ordered_snp = ''.join(sorted(re.findall('[ACGT]', self._snp)))\n # Find the IUPAC code for the SNP\n self._code = ''.join([c for c, o in self._IUPAC_CODES.items() if ordered_snp == o])\n # Create the IUPAC version of the sequence\n self._iupac = re.sub(r'\\[%s\\]' % self._snp[1:-1], self._code, self._sequence)\n # Calculate the length of the sequence\n self._length = len(self._iupac)","def get_seq(self, table=1, cds=True):\n dna_seq = '' \n for exon in self.transcript.exons: \n dna_seq += self.transcript.rna.gene.polymer.get_subseq(\n start=max(self.coding_region.start, exon.start), \n end=min(self.coding_region.end, exon.end))\n \n if self.transcript.rna.gene.strand == core.PolymerStrand.negative:\n dna_seq = dna_seq.reverse_complement()\n \n return dna_seq.transcribe().translate(table=table, cds=cds)","def cyclopeptide_sequence(self, spectrum):\n\t# Make dict for faster access\n\tspectrum_dict = dict(zip(spectrum, spectrum))\n # Compute the max weight in spectrum. That has to be the weight of the acid\n max_spectrum_weight = max(spectrum)\n sequences = [\"\"]\n final_sequences = []\n while len(sequences) > 0:\n # Copy sequences to new_seq\n new_seq = copy.deepcopy(sequences)\n sequences = list()\n # Add new amino acid and check for consistency\n for s in new_seq:\n sequence_weight = ProteinTransformer(s).int_weight()\n for a in protein_util.amino_acids_by_weight:\n new_protein = s+a\n new_weight = sequence_weight + protein_util.protein_mass_int[a]\n # Case 1: Check if the new acid is consistent with spectrum\n flag = True\n for i in range(len(s)):\n w = ProteinTransformer(s[i:]+a).int_weight()\n if w not in spectrum_dict:\n flag = False\n break\n if not flag:\n continue\n # Check if new weight attained maximum. If not, just append to pending sequences\n elif new_weight < max_spectrum_weight:\n sequences.append(new_protein)\n # Finally, compare entire new spectrum with given spectrum\n else:\n new_spectrum = ProteinTransformer(new_protein).cyclospectrum()\n if new_spectrum == spectrum:\n final_sequences.append(new_protein)\n \n \n\t# Done. Now return final sequences\n return final_sequences","def seq_positions(seq, codon):\n\n positions = []\n i = 0\n\n while codon in seq[i:]:\n pos = seq.find(codon, i)\n positions.append(pos)\n i = pos + 1\n positions.sort()\n return positions","def intercalateCodons( seq ):\r\n\tseqLen = len(seq)\r\n\tsitesPerCod = seqLen/3\r\n\textraSites = seqLen%3\r\n\tif extraSites == 0:\r\n\t\tcodOne = seq[0:sitesPerCod]\r\n\t\tcodTwo = seq[sitesPerCod:2*sitesPerCod]\r\n\t\tcodThree = seq[2*sitesPerCod:3*sitesPerCod]\r\n\telif extraSites == 1:\r\n\t\tcodOne = seq[0:sitesPerCod+1]\r\n\t\tcodTwo = seq[sitesPerCod+1:(2*sitesPerCod)+1]\r\n\t\tcodThree = seq[(2*sitesPerCod)+1:(3*sitesPerCod)+1]\r\n\telse:\r\n\t\tcodOne = seq[0:sitesPerCod+1]\r\n\t\tcodTwo = seq[sitesPerCod+1:(2*sitesPerCod)+2]\r\n\t\tcodThree = seq[(2*sitesPerCod)+2:(3*sitesPerCod)+2]\r\n\tnewSeq = [x for t in itertools.izip_longest(codOne,codTwo,codThree) for x in t]\r\n\t\"\"\"\r\n\thttp://stackoverflow.com/questions/11125212/interleaving-lists-in-python\r\n\t\"\"\"\r\n\tnewSeq = filter(lambda a: a != None, newSeq)\r\n\t\"\"\"\r\n\thttp://stackoverflow.com/questions/1157106/remove-all-occurrences-of-a-value-from-a-python-list\r\n\t\"\"\"\r\n\treturn newSeq","def GetPseudoAAC(ProteinSequence,lamda=30,weight=0.05,AAP=[_Hydrophobicity,_hydrophilicity]):\n\tres={}\n\tres.update(GetPseudoAAC1(ProteinSequence,lamda,weight,AAP))\n\tres.update(GetPseudoAAC2(ProteinSequence,lamda,weight,AAP))\n\treturn res","def RNAorDNA ( seq ) :\n\tif dna_regex . search ( seq ):\n\t\treturn RNA ( seq )\n\n\tif rna_regex . search ( seq ):\n\t\treturn DNA ( seq )","def to_rna(seq):\n seq=seq.replace('A','U')\n seq=seq.replace('T','A')\n seq=seq.replace('C',\"P\")\n seq=seq.replace('G','C')\n seq=seq.replace('P','G')\n return seq","def coding_strand_to_AA(dna):\n num_codons = int(len(dna)/3)\n num = 0\n list_codons = []\n aacids = ''\n while num < num_codons:\n num_start = int(num*3)\n num_end = int(num*3 + 3)\n list_codons.append(dna[num_start:num_end])\n num = num + 1\n for element in list_codons:\n thing = aa_table[element]\n aacids = aacids + thing\n return aacids","def aa(seq):\n global codontable\n seq = seq.upper()\n if codontable is None:\n # TODO: figure out the right place for the pre-computed information here\n bases = ['T', 'C', 'A', 'G']\n codons = [a+b+c for a in bases for b in bases for c in bases]\n codons = codons + list(map(lambda x: x.lower(), codons))\n amino_acids = 'FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG'\n amino_acids = amino_acids + amino_acids.lower()\n codontable = dict(zip(codons, amino_acids))\n res = ''\n for i in range(0, len(seq) - 2, 3):\n res += codontable[seq[i:(i+3)]]\n return res","def preprocess(fasta_files, qual_files, mapping_file,\r\n barcode_type=\"golay_12\",\r\n min_seq_len=200, max_seq_len=1000, min_qual_score=25, starting_ix=1,\r\n keep_primer=False, max_ambig=0, max_primer_mm=0, trim_seq_len=False,\r\n dir_prefix='.', max_bc_errors=2, max_homopolymer=4,\r\n retain_unassigned_reads=False, keep_barcode=False,\r\n attempt_bc_correction=True, qual_score_window=0,\r\n disable_primer_check=False, reverse_primers='disable',\r\n reverse_primer_mismatches=0,\r\n record_qual_scores=False, discard_bad_windows=False,\r\n median_length_filtering=None, added_demultiplex_field=None,\r\n truncate_ambi_bases=False):\r\n\r\n if max_seq_len < 10:\r\n raise ValueError(\"Max sequence must be >= 10\")\r\n if min_seq_len >= max_seq_len:\r\n raise ValueError(\"Min len cannot be >= max len\")\r\n if min_qual_score < 0:\r\n raise ValueError(\"Min qual score must be > 0\")\r\n if starting_ix < 1:\r\n raise ValueError(\"Starting index must be > 0.\")\r\n if max_ambig < 0:\r\n raise ValueError(\"Max ambig chars must be >= 0.\")\r\n if max_primer_mm < 0:\r\n raise ValueError(\"Max primer mismatches must be >= 0.\")\r\n if reverse_primers not in ['disable', 'truncate_only', 'truncate_remove']:\r\n raise ValueError(\"reverse_primers parameter must be 'disable', \" +\r\n \"truncate_only, or truncate_remove.\")\r\n\r\n create_dir(dir_prefix, fail_on_exist=False)\r\n\r\n# try:\r\n# stat(dir_prefix)\r\n# except OSError:\r\n# mkdir(dir_prefix)\r\n\r\n \"\"\"# Generate primer sequence patterns - changing to mapping file primers.\r\n all_primer_seqs, primer_seq_len = \\\r\n get_primer_seqs(primer_seq_pats.split(',')) \"\"\"\r\n\r\n # Check mapping file and get barcode mapping\r\n map_file = open(mapping_file, 'U')\r\n headers, id_map, valid_map, warnings, errors, \\\r\n primer_seqs_lens, all_primers = check_map(\r\n map_file, disable_primer_check,\r\n barcode_type, added_demultiplex_field)\r\n\r\n if reverse_primers != 'disable':\r\n if 'ReversePrimer' not in headers:\r\n raise ValueError('To enable reverse primer check, there must ' +\r\n 'be a \"ReversePrimer\" column in the mapping file with a reverse ' +\r\n 'primer in each cell.')\r\n rev_primers = get_reverse_primers(id_map)\r\n else:\r\n rev_primers = False\r\n\r\n # *** Generate dictionary of {barcode: DNA(ReversePrimer).rc()}\r\n # First check for ReversePrimer in headers, raise error if not found\r\n # Implement local alignment for primer after barcode is determined.\r\n # Add option to flag seq with error for rev_primer not found\r\n # Check primer hit index, truncate sequence\r\n # unit tests.\r\n\r\n map_file.close()\r\n if errors:\r\n raise ValueError(\"Invalid mapping file. \" +\r\n \"Validate with check_id_map first: %s\" % \"\\n\".join(errors))\r\n\r\n # Find actual length of barcodes in the mapping file, also check for\r\n # variable lengths, in case of added_demultiplex, split on comma.\r\n barcode_length_check =\\\r\n list(set([len(bc.split(',')[0]) for bc in valid_map]))\r\n\r\n # Check barcode type\r\n if barcode_type not in BARCODE_TYPES:\r\n try:\r\n barcode_len, barcode_fun = int(barcode_type), correct_barcode\r\n except ValueError:\r\n raise ValueError(\"Unsupported barcode type: %s\" % barcode_type)\r\n else:\r\n barcode_len, barcode_fun = BARCODE_TYPES[barcode_type]\r\n\r\n # As people often do not specify a barcode that matches the lengths\r\n # of the barcodes used, a check on the actual barcode lengths needs to\r\n # be done, and an exception raised if they are variable length and not\r\n # specified as so.\r\n if barcode_type != \"variable_length\":\r\n # Raise error if variable length barcodes are present but not\r\n # specified\r\n if len(barcode_length_check) != 1:\r\n raise ValueError('Mapping file has variable length ' +\r\n 'barcodes. If this is intended, specifiy variable lengths ' +\r\n 'with the -b variable_length option.')\r\n # Raise error if the specified barcode length doesn't match what\r\n # is present in the mapping file.\r\n if barcode_len != barcode_length_check[0]:\r\n raise ValueError('Barcode length detected in the mapping file, ' +\r\n ' %d does not match specified barcode length, %d. ' %\r\n (barcode_length_check[0], barcode_len) + 'To specify a barcode ' +\r\n 'length use -b golay_12 or -b hamming_8 for 12 and 8 base pair ' +\r\n 'golay or hamming codes respectively, or -b # where # is the ' +\r\n 'length of the barcode used. E.g. -b 4 for 4 base pair barcodes.')\r\n\r\n fasta_files = map(get_infile, fasta_files)\r\n qual_files = map(get_infile, qual_files)\r\n\r\n # Check fasta files valid format, no duplicate ids\r\n # and ids match between fasta and qual files\r\n all_fasta_ids = fasta_ids(fasta_files)\r\n all_qual_ids = fasta_ids(qual_files)\r\n if qual_files and (len(all_fasta_ids) != len(all_qual_ids)):\r\n f_ids = all_fasta_ids.difference(all_qual_ids)\r\n q_ids = all_qual_ids.difference(all_fasta_ids)\r\n raise ValueError(\r\n \"Found %d ids in fasta file not in qual file, %d ids in qual file not in fasta\" %\r\n (len(f_ids), len(q_ids)))\r\n\r\n for f in fasta_files:\r\n f.seek(0)\r\n if qual_files:\r\n for q in qual_files:\r\n q.seek(0)\r\n # Load quality scores\r\n qual_mappings = parse_qual_scores(qual_files)\r\n for q in qual_files:\r\n q.close()\r\n else:\r\n qual_mappings = {}\r\n\r\n # make filters\r\n filters = []\r\n # seq len filter depends on whether we're including the barcode, if\r\n # median_length_filtering turned on, no length filtering.\r\n if not median_length_filtering:\r\n if trim_seq_len:\r\n # This processing occurs before primer testing, will use largest\r\n # primer length to calculate lengths. the dict all_primers has\r\n # keys of each primer with the length of said primer as the value\r\n if disable_primer_check:\r\n primer_seq_len = 0\r\n else:\r\n primer_seq_len = max(all_primers.values())\r\n\r\n if barcode_type == \"variable_length\":\r\n barcode_len = max(barcode_length_check)\r\n\r\n trim = barcode_len + primer_seq_len\r\n filters.append(SeqQualBad(\r\n 'Length outside bounds of %s and %s' % (\r\n min_seq_len,\r\n max_seq_len),\r\n lambda id_, seq, qual:\r\n not (min_seq_len <= len(seq) - trim <= max_seq_len)))\r\n else:\r\n filters.append(SeqQualBad(\r\n 'Length outside bounds of %s and %s' % (\r\n min_seq_len,\r\n max_seq_len),\r\n lambda id_, seq, qual: not (min_seq_len <= len(seq) <= max_seq_len)))\r\n\r\n if not truncate_ambi_bases:\r\n filters.append(SeqQualBad(\r\n 'Num ambiguous bases exceeds limit of %s' % max_ambig,\r\n lambda id_, seq, qual: count_ambig(seq) > max_ambig))\r\n\r\n if qual_mappings:\r\n filters.append(QualMissing)\r\n filters.append(SeqQualBad(\r\n 'Mean qual score below minimum of %s' % min_qual_score,\r\n lambda id_, seq, qual: mean(qual) < min_qual_score))\r\n \"\"\"if qual_score_window:\r\n filters.append(SeqQualBad('Mean window qual score below '+\\\r\n 'minimum of %s' % min_qual_score,\r\n lambda id_, seq, qual: \\\r\n not check_window_qual_scores(qual, qual_score_window, \\\r\n min_qual_score))) \"\"\"\r\n\r\n # Changed this to check entire sequence after barcode-could cause issue\r\n # if barcode-linker-primer have long homopolymers though.\r\n filters.append(SeqQualBad(\r\n 'Max homopolymer run exceeds limit of %s' % max_homopolymer,\r\n lambda id_, seq, qual: seq_exceeds_homopolymers(\r\n seq[barcode_len:], max_homopolymer)))\r\n\r\n # Check seqs and write out\r\n fasta_out = open(dir_prefix + '/' + 'seqs.fna.tmp', 'w+')\r\n if record_qual_scores:\r\n qual_out = open(dir_prefix + '/' + 'seqs_filtered.qual', 'w+')\r\n else:\r\n qual_out = False\r\n\r\n '''log_stats, pre_lens, post_lens = check_seqs(fasta_out, fasta_files,\r\n starting_ix, valid_map, qual_mappings, filters, barcode_len,\r\n primer_seq_len, keep_primer, keep_barcode, barcode_type, max_bc_errors,\r\n retain_unassigned_reads) '''\r\n log_stats, raw_lens, pre_lens, post_lens = check_seqs(fasta_out,\r\n fasta_files, starting_ix, valid_map, qual_mappings, filters,\r\n barcode_len, keep_primer, keep_barcode, barcode_type, max_bc_errors,\r\n retain_unassigned_reads, attempt_bc_correction,\r\n primer_seqs_lens, all_primers, max_primer_mm, disable_primer_check,\r\n reverse_primers, rev_primers, qual_out, qual_score_window,\r\n discard_bad_windows, min_qual_score, min_seq_len,\r\n median_length_filtering, added_demultiplex_field,\r\n reverse_primer_mismatches, truncate_ambi_bases)\r\n\r\n # Write log file\r\n log_file = open(dir_prefix + '/' + \"split_library_log.txt\", 'w+')\r\n log_file.write('\\n'.join(log_stats))\r\n log_file.close()\r\n\r\n # Write sequence distros here\r\n histogram_file = open(dir_prefix + '/' + 'histograms.txt', 'w+')\r\n\r\n histogram_file.write(format_histograms\r\n (*make_histograms(raw_lens, pre_lens, post_lens)))\r\n histogram_file.close()","def coding_strand_to_AA(dna):\n s = \"\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitialize empty list\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n for i in range(0, len(dna)-2, 3):\t\t\t\t\t\t\t\t\t\t\t\t\t\t# for range of length of dna, indexes w/ step 3 (to isolate codons)\n \t\tamino_acid = aa_table[dna[i:i+3]]\t\t\t\t\t\t\t\t\t\t\t\t# translates each codon to an amino acid\n \t\ts = s + amino_acid \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# adds amino acid to list\n return s \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns list of amino acids","def test_ModelDnaCodonSequence(self):\n d = ArrayDnaCodonSequence(\"UUUCGU\")\n self.assertEqual(str(d), \"TTTCGT\")\n self.assertEqual(d._data, array([0, 28]))\n self.assertEqual(str(d.to_rna()), \"UUUCGU\")\n self.assertEqual(str(d.to_dna()), \"TTTCGT\")","def _GetPseudoAAC(ProteinSequence,lamda=10,weight=0.05):\n\tres={}\n\tres.update(_GetPseudoAAC1(ProteinSequence,lamda=lamda,weight=weight))\n\tres.update(_GetPseudoAAC2(ProteinSequence,lamda=lamda,weight=weight))\n\treturn res","def GetPseudoAAC1(ProteinSequence,lamda=30,weight=0.05,AAP=[_Hydrophobicity,_hydrophilicity]):\n\trightpart=0.0\n\tfor i in range(lamda):\n\t\trightpart=rightpart+GetSequenceOrderCorrelationFactor(ProteinSequence,i+1,AAP)\n\tAAC=GetAAComposition(ProteinSequence)\n\t\n\tresult={}\n\ttemp=1+weight*rightpart\n\tfor index,i in enumerate(AALetter):\n\t\tresult['PAAC'+str(index+1)]=round(AAC[i]/temp,3)\n\t\n\treturn result","def produce_proteinSeq_dict (inPath, outPath):\n s = list(SeqIO.parse(str(inPath), 'fasta'))\n proteinSeq = {}\n for _, elm in enumerate(s):\n proteinSeq[elm.id] = str(elm.seq)\n with open(outPath, 'wb') as fOut:\n pickle.dump(proteinSeq, fOut)","def reconstruct_seq_centered(seq, nucleosome_pos):\n\n # equivalence\n d_nucleotide = {0: 1, # 'A',\n 1: 0, # 'C',\n 2: 1, # 'T',\n 3: 0, # 'G'\n }\n\n seqd = np.vectorize(d_nucleotide.get)(seq)\n array_nuc = []\n\n # select only the nucleosome positions\n for pos in nucleosome_pos:\n array_nuc.append(seqd[pos - 58:pos + 59])\n\n # do the stack\n center_nucleosome = np.sum(array_nuc, axis=0) / len(array_nuc)\n\n return center_nucleosome","def codon_table_to_codon_map(codon_table: dict, deterministic: bool = True) -> Callable[[SeqLike], SeqLike]:\n\n def backtranslator(seq):\n if seq._type != \"AA\":\n raise TypeError(\"Sequence must be an AA SeqLike!\")\n seq_str = seq.to_str()\n\n nt = \"\"\n for aa in seq_str:\n codons, probs = zip(*codon_table[aa].items())\n\n # we normalize the probabilities\n # most tables are near 1.0, but issues with precision exist\n sum_prob = sum(probs)\n probs = [p / sum_prob for p in probs]\n\n if deterministic:\n nt += codons[0]\n else:\n nt += np.random.choice(codons, p=probs)\n\n new_seqlike = SeqLike(\n nt,\n id=seq.id,\n name=seq.name,\n description=seq.description,\n annotations=seq.annotations,\n dbxrefs=seq.dbxrefs,\n seq_type=\"dna\",\n codon_map=seq.codon_map,\n )\n new_seqlike._aa_record = deepcopy(seq._aa_record)\n return new_seqlike\n\n return backtranslator","def make_codon_pos_align(aln):\n\n def func(seq):\n dct = {-1: \"-\",\n 0: \"0\",\n 1: \"1\",\n 2: \"2\"}\n return \"\".join(util.mget(dct, mark_codon_pos(seq)))\n return mapalign(aln, valfunc=func)","def getValidityOfResiduesInSequence(self, seq):\n seqList = list(seq)\n aSpotted_Index = -1\n aSpotted_residue = \"\"\n if self.aligntIsDna:\n _alphabet = self.DNA_ALPHABET\n else:\n _alphabet = self.PROTEIN_ALPHABET\n # iterate over the sequence given the prior knowldege of the user\n for i in range(len(seqList)):\n residue = seqList[i]\n if str.upper(residue) not in list(_alphabet):\n aSpotted_Index = i\n aSpotted_residue = residue\n break\n rv = {\n \"residueIndex\": aSpotted_Index,\n \"residue\": aSpotted_residue,\n \"recognizedAlphabet\": self.VALID_DNA_OR_PROTEIN\n }\n if (aSpotted_residue != \"\"):\n if self.aligntIsDna:\n rv[\"recognizedAlphabet\"] = self.INVALID_DNA\n else:\n rv[\"recognizedAlphabet\"] = self.INVALID_PROTEIN\n return(rv)","def _GetPseudoAAC1(ProteinSequence,lamda=10,weight=0.05):\n\trightpart=0.0\n\tfor i in range(lamda):\n\t\trightpart=rightpart+_GetSequenceOrderCorrelationFactor(ProteinSequence,k=i+1)\n\tAAC=GetAAComposition(ProteinSequence)\n\t\n\tresult={}\n\ttemp=1+weight*rightpart\n\tfor index,i in enumerate(AALetter):\n\t\tresult['PAAC'+str(index+1)]=round(AAC[i]/temp,3)\n\t\n\treturn result","def extract_seq_from_structure(self, struct):\n ppb = PPBuilder() # Polypeptide builder object\n aa_seqs = []\n chains = struct.get_chains()\n for pp in ppb.build_peptides(struct):\n seq = pp.get_sequence()\n aa_seqs.append(str(seq))\n chain_aa_map = [[chain.id, aa_seqs[index]] for index, chain in enumerate(chains)]\n return chain_aa_map","def GetAAComposition(ProteinSequence):\n\tLengthSequence=len(ProteinSequence)\n\tResult={}\n\tfor i in AALetter:\n\t\tResult[i]=round(float(ProteinSequence.count(i))/LengthSequence*100,3)\n\treturn Result","def cpos2codon(self, cpos):\n self.ensure_seq()\n cpos = int(cpos)\n if self.strand == \"+\":\n np = []\n for beg, end in self.exons:\n np += list(range(max(beg, self.cds_beg),\n min(self.cds_end, end)+1))\n assert len(np) == len(self.seq)\n\n ni = cpos*3\n if ni <= len(np):\n codon = Codon()\n codon.index = cpos\n codon.locs = tuple(np[ni-3:ni])\n codon.gene = self.gene\n codon.chrm = self.chrm\n codon.strand = self.strand\n codon.seq = self.seq[ni-3:ni]\n return codon\n else:\n raise IncompatibleTranscriptError('invalid_cDNA_position_%d;expect_[0_%d]' % (ni, len(np)))\n else:\n np = []\n for beg, end in reversed(self.exons):\n np += list(range(min(self.cds_end, end),\n max(beg, self.cds_beg)-1,-1))\n assert len(np) == len(self.seq)\n\n ni = cpos*3\n if ni <= len(np):\n codon = Codon()\n codon.index = cpos\n codon.locs = tuple(reversed(np[ni-3:ni]))\n codon.gene = self.gene\n codon.chrm = self.chrm\n codon.strand = self.strand\n codon.seq = self.seq[ni-3:ni]\n return codon\n else:\n raise IncompatibleTranscriptError('invalid_cDNA_position_%d;expect_[0_%d]' % (ni, len(np)))","def alignprotein(self, sample, analysistype, target, program, index, hit):\n # Initialise lists to store the outputs\n if target not in sample[analysistype].dnaseq:\n sample[analysistype].dnaseq[target] = list()\n sample[analysistype].protseq[target] = list()\n sample[analysistype].ntalign[target] = list()\n sample[analysistype].ntindex[target] = list()\n sample[analysistype].aaidentity[target] = list()\n sample[analysistype].aaalign[target] = list()\n sample[analysistype].aaindex[target] = list()\n # Only BLASTn analyses require additional effort to find the protein sequence\n if program == 'blastn':\n # Convert the extracted, properly-oriented DNA sequence to a Seq object\n sample[analysistype].dnaseq[target].append(Seq(hit['query_sequence']))\n # Create the BLAST-like interleaved outputs with the query and subject sequences\n sample[analysistype].ntalign[target].append(self.interleaveblastresults(query=hit['query_sequence'],\n subject=hit['subject_sequence']))\n # Determine the number and position of SNPs\n count = 0\n ntindex = str()\n # Iterate through every position in the query sequence, and determine if the subject sequence at that\n # position is a match\n for i, bp in enumerate(hit['query_sequence']):\n # If the sequence at the query and subject sequences do not match, store the location\n if bp != hit['subject_sequence'][i]:\n # Append the current location (+1 due to zero indexing)\n ntindex += '{i};'.format(i=i + 1)\n # Increment the count by the length of the current position - should make the output more\n # uniform due to the fact that the numbers are not padded\n count += len(str(i))\n # If there are many SNPs, then insert line breaks for every 15+ characters\n if count >= 15:\n ntindex += '\\n'\n # Reset the character count to 0\n count = 0\n # Remove trailing ';' (or ';' followed by a newline)\n ntindex = ntindex.rstrip(';').replace(';\\n', '\\n') if ntindex else '-'\n # Add the cleaned string to the list\n sample[analysistype].ntindex[target].append(ntindex)\n # Convert the target name to a string without illegal characters - necessary for creating the\n # temporary databases below\n clean_target = ''.join(filter(str.isalnum, target))\n # Set the absolute path, and create the tmp working directory\n tmp_dir = os.path.join(sample[analysistype].reportdir, 'tmp')\n make_path(tmp_dir)\n # Set the absolute path of the FASTA file that will store the subject sequence. Will be used as the\n # database in the tblastx analysis used to translate the query and subject sequence to amino acid\n tmp_subject = os.path.join(tmp_dir, '{sn}_{target}_{at}_db_{index}.fa'\n .format(sn=sample.name,\n target=clean_target,\n at=analysistype,\n index=index))\n # Write the appropriately-converted subject sequence to the database file\n with open(tmp_subject, 'w') as tmp_db:\n SeqIO.write(SeqRecord(Seq(hit['subject_sequence'].replace('-', '')),\n id='{}_{}'.format(sample.name, target),\n description=''), tmp_db, 'fasta')\n # Create a BLAST database from this file\n self.makeblastdb(fasta=tmp_subject)\n # Create the tblastx (translated nt query: translated nt subject) call. Remove any masking. Do not\n # include the 'query' parameter, as it will be supplied below\n tblastx = NcbitblastxCommandline(db=os.path.splitext(tmp_subject)[0],\n evalue=0.1,\n outfmt=15,\n soft_masking=False,\n seg='no')\n # Run the tblastx analysis. Supply the query as stdin. Capture stdout, and stderr\n stdout, stderr = tblastx(stdin=sample[analysistype].targetsequence[target][index].replace('-', ''))\n # Convert the string stdout to JSON format\n json_output = json.loads(stdout)\n # Extract the necessary list of HSPs from the JSON-formatted outputs\n data = json_output['BlastOutput2'][0]['report']['results']['search']['hits'][0]['hsps']\n # Initialise a string to store the extracted amino acid subject sequence\n ref_prot = str()\n for results in data:\n # Attempt to use hit_frame 1 - the .targetsequence attribute was populated with the nt sequence in\n # (hopefully) the correct orientation, so attempt to use that\n if results['hit_frame'] == 1:\n # Populate the .protseq attribute with the Seq-converted amino acid sequence extracted from the\n # report\n sample[analysistype].protseq[target].append(Seq(results['qseq'].upper()))\n # Grab the subject sequence\n ref_prot = results['hseq']\n # Only the first result is required\n break\n # If there were no results with the hit_frame equal to 1, get the best result from the analysis\n if not ref_prot:\n for results in data:\n sample[analysistype].protseq[target].append(Seq(results['qseq'].upper()))\n ref_prot = results['hseq']\n break\n # Clear out the tmp directory\n try:\n shutil.rmtree(tmp_dir)\n except FileNotFoundError:\n pass\n else:\n # Non-blastn analyses will already have the outputs as amino acid sequences. Populate variables as required\n ref_prot = hit['subject_sequence']\n sample[analysistype].protseq[target].append(Seq(hit['query_sequence']))\n # Create the BLAST-like alignment of the amino acid query and subject sequences\n sample[analysistype].aaalign[target]\\\n .append(self.interleaveblastresults(query=sample[analysistype].protseq[target][index],\n subject=ref_prot))\n # Determine the number of matches, as well as the number and location of mismatches\n count = 0\n matches = 0\n aaindex = str()\n # Iterate through the query sequence to determine matching positions\n for i, bp in enumerate(sample[analysistype].protseq[target][index]):\n if bp != ref_prot[i]:\n aaindex += '{i};'.format(i=i + 1)\n count += len(str(i))\n # If there are many SNPs, then insert line breaks for every 10 SNPs\n if count >= 15:\n aaindex += '\\n'\n count = 0\n # Increment the total number of matches\n if bp == ref_prot[i]:\n matches += 1\n # Clean the index string\n aaindex = aaindex.rstrip(';').replace(';\\n', '\\n') if aaindex else '-'\n # Append the cleaned string to the list\n sample[analysistype].aaindex[target].append(aaindex)\n # Determine percent identity between the query and subject amino acid sequence by dividing the number of\n # matches by the total length of the query sequence and multiplying this result by 100. Convert to two\n # decimal places\n pid = float('{:.2f}'.format(matches / len(sample[analysistype].protseq[target][index]) * 100))\n # Append the calculated percent identity to the list\n sample[analysistype].aaidentity[target].append(pid)\n return sample","def computeProbs(psDf, add_masked_seqs=True, filterOut=False, max_cdr3_length=30, allow_stop_codons=False, allow_X=False):\n \n out = []\n for rowi, row in psDf.iterrows():\n \"\"\"If iterrows is slow there are potentially ways to speed this up using psDf.apply()\"\"\"\n vals = {}\n vals['ind'] = rowi\n \n if filterOut:\n fo = filterOutRow(row,\n max_cdr3_length=max_cdr3_length,\n allow_stop_codons=allow_stop_codons,\n allow_X=allow_X)\n if fo:\n \"\"\"vals will be missing keys, which will be assigned Nan in outDf\"\"\"\n continue\n \n aprob_nucseq, aprob_protseq = samplerProb(row, 'a')\n va_rep_prob, ja_rep_prob = rearrangementProb(row, 'a')\n \n vals['a_protseq_prob' ] = aprob_protseq * va_rep_prob * ja_rep_prob\n vals['cdr3a_protseq_prob'] = aprob_protseq\n vals['va_rep_prob' ] = va_rep_prob\n vals['ja_rep_prob' ] = ja_rep_prob\n vals['a_nucseq_prob' ] = aprob_nucseq * va_rep_prob * ja_rep_prob\n \n bprob_nucseq, bprob_protseq = samplerProb(row, 'b')\n vb_rep_prob, jb_rep_prob = rearrangementProb(row, 'b')\n \n vals['b_protseq_prob' ] = bprob_protseq * vb_rep_prob * jb_rep_prob\n vals['cdr3b_protseq_prob'] = bprob_protseq\n vals['vb_rep_prob' ] = vb_rep_prob\n vals['jb_rep_prob' ] = jb_rep_prob\n vals['b_nucseq_prob' ] = bprob_nucseq * vb_rep_prob * jb_rep_prob\n \n if add_masked_seqs:\n cdr3a_protseq_masked, ita, cdr3a_new_nucseq = getMaskedSeqs(row, 'a')\n cdr3b_protseq_masked, itb, cdr3b_new_nucseq = getMaskedSeqs(row, 'b')\n\n vals[ 'cdr3a_protseq_masked'] = cdr3a_protseq_masked\n vals[ 'a_indels'] = ita\n vals[ 'cdr3a_new_nucseq' ] = cdr3a_new_nucseq\n vals[ 'cdr3b_protseq_masked'] = cdr3b_protseq_masked\n vals[ 'b_indels'] = itb\n vals[ 'cdr3b_new_nucseq' ] = cdr3b_new_nucseq\n out.append(vals)\n \n outDf = pd.DataFrame(out).set_index('ind')\n assert outDf.shape[0] == psDf.shape[0]\n return outDf","def calc_conservation(aln):\n\n length = len(aln.values()[0])\n seqs = aln.values()\n percids = []\n\n # find identity positions\n for i in xrange(length):\n chars = util.hist_dict(util.cget(seqs, i))\n if \"-\" in chars:\n del chars[\"-\"]\n\n if len(chars) == 0:\n percids.append(0.0)\n else:\n pid = max(chars.values()) / float(len(aln))\n percids.append(pid)\n return percids","def filter_aligned_codons(aln):\n\n ind = find_aligned_codons(aln)\n return subalign(aln, ind)","def translate_DNA(dnaseq):\n\n gen = aa_generator_DNA(dnaseq)\n seq = ''\n aa = next(gen, None)\n while aa:\n seq += aa\n aa = next(gen, None)\n return seq","def get_seq(peaks_df, genome, width):\n vals = []\n peaks_used = []\n for i, r in peaks_df.iterrows():\n sequence = str(genome[r['chr']][(r['start']+r['summit'] - width//2):(r['start'] + r['summit'] + width//2)])\n if len(sequence) == width:\n vals.append(sequence)\n peaks_used.append(True)\n else:\n peaks_used.append(False)\n\n return one_hot.dna_to_one_hot(vals), np.array(peaks_used)","def create_protein_sequences_table(self,fn_proteins_fasta_file):\n log.info(\"Creating table of protein sequences ...\")\n self.create_table(self.SequenceTable,self.SequenceFields,\n self.SequenceTypes)\n parser = SeqIO.parse(fn_proteins_fasta_file, \"fasta\")\n data = []\n n_stored = 0\n chunk_size = 1000\n for seq_record in parser:\n description = seq_record.description\n m = re.match(self.protein_record_pattern,description)\n gene_id = m.group(1)\n locus_tag = m.group(2)\n protein_description = m.group(3)\n table_record = [gene_id, locus_tag, protein_description, seq_record.seq.tostring()]\n data.append(table_record)\n # store chunks of data\n if len(data) > chunk_size:\n self.store_data(self.SequenceTable,data)\n n_stored += chunk_size\n log.info(\"Stored %20d sequences\\r\",n_stored)\n data = [] # empty data to avoid using a lot of memory\n # store last chunk\n if len(data) > 0:\n n_stored += len(data)\n self.store_data(self.SequenceTable,data)\n log.info(\"Stored %20d sequences\\r\",n_stored)","def codonify(strand: str) -> list:\n\n # Loops through the whole string and slices every set of three characters into\n # the list codons\n codons = [strand[index : index + len_codon] for index in range(0,len(strand),len_codon)]\n return codons","def readPairedSequences(organism, paired_seqs_file):\n\n raw = pd.read_csv(paired_seqs_file, delimiter='\\t')\n \"\"\"E.g. ['a', 'b']\"\"\"\n chains = [s.split('_')[0] for s in raw.columns if s.find('nucseq') > 0]\n \n out = []\n for c in chains:\n out.append(raw.apply(lambda row: processNT(organism, c.upper(), row['%s_nucseq' % c], row['%s_quals' % c]).to_series(), axis=1))\n\n otherCols = [c for c in raw.columns if c.find('nucseq') == -1 and c.find('quals') == -1]\n out = [raw[otherCols]] + out\n psDf = pd.concat(out, axis=1)\n psDf.loc[:, 'organism'] = organism\n return psDf","def parse_wt_sequences(wt_dna_fasta):\n with open(wt_dna_fasta, 'r') as f:\n sequence_generator_obj = SeqIO.parse(f, 'fasta', IUPAC.unambiguous_dna)\n sequences = []\n for sequence_obj in sequence_generator_obj:\n sequences.append(sequence_obj.seq.upper())\n assert len(sequences) == 1, 'Only one wild type dna sequence can be present in the wild type dna fasta file'\n wt_dna_seq = sequences[0]\n if wt_dna_seq.translate().find('*') == -1:\n raise Exception(\"Stop codon not found in wild type sequence\")\n elif (len(wt_dna_seq)) / 3 != (wt_dna_seq.translate().find('*') + 1):\n raise Exception(\"Premature stop codon found in wild type sequence\")\n\n native_protein_dict = {}\n for i in range(3, len(wt_dna_seq) + 1, 3):\n if not (i / 3) in native_protein_dict:\n native_protein_dict[i / 3] = ()\n native_protein_dict[i / 3] = (wt_dna_seq[i - 3:i].translate(), wt_dna_seq[i - 3:i])\n return wt_dna_seq, native_protein_dict","def guess_align(aln):\n \n if \"pep\" in [guess_seq(seq) for seq in aln.itervalues()]:\n return \"pep\"\n else:\n return \"dna\"","def main(fileToCheck, minLength=-1, maxLength=-1):\n\n # Initialise variables.\n lineCount = 1 # The number of the line being examined. Used for displaying error messages.\n protDescription = True # Whether or not we are currently expecting a line starting with >.\n firstLine = True # Whether or not we are currently examining the first line of the file.\n proteinsInFile = {} # A dictionary indexed by the protein description line of the FASTA file.\n # The value of each entry is the correctly formatted protein sequence corresponding to the index.\n\n # Strip off all excess whitespace, and split the string into the individual lines of the file.\n checking = fileToCheck.rstrip()\n checking = checking.lstrip()\n checking = checking.split('\\n')\n for line in checking:\n line = line.rstrip()\n if firstLine:\n # True if we have just started parsing the file string, and haven;t yet examined any lines.\n if line[0] == '>':\n currentProt = line # Record the description line of the protein which is about to have its sequence inspected.\n currentSeq = '' # Initialise the sequence of the protein.\n protDescription = False # We are now expecting a protein sequence, not a protein description.\n firstLine = False\n else:\n # The first line of the file MUST be a protein description line (i.e. start with '>'). If the line was not\n # the beginning of a protein record, terminate the program.\n errorMessage = \"Expected line \" + str(lineCount) + \" to start with a >, but instead got: \" + line\n return 1, errorMessage\n elif protDescription:\n # This is true only if a line beginning with a '>' is expected.\n if line[0] == '>':\n # Expected a protein description line, and found a protein description line. This means that the entire sequence\n # of the currentProt protein has been found (i.e. we have finished inspecting the sequence of a protein, and\n # have found the protein to be valid). Now determine if the length of the sequence is within the user\n # specified bounds.\n if minLength == -1:\n if maxLength == -1:\n # If there are no restrictions on the protein sequence length, then record the protein and its sequence.\n proteinsInFile[currentProt] = currentSeq\n elif len(currentSeq) <= maxLength:\n # If there is no minimum length restriction, and the protein sequence is not longer than the maximum\n # sequence length permitted, then record the protein and its sequence.\n proteinsInFile[currentProt] = currentSeq\n elif len(currentSeq) >= minLength:\n if maxLength == -1:\n # If there is no maximum length restriction, and the protein sequence is not shorter than the minimum\n # sequence length permitted, then record the protein and its sequence.\n proteinsInFile[currentProt] = currentSeq\n elif len(currentSeq) <= maxLength:\n # If the protein sequence is not shorter than the minimum sequence length permitted and not longer\n # than the maximum length permitted, then record the protein and its sequence.\n proteinsInFile[currentProt] = currentSeq\n currentProt = line # Record the description line of the protein which is about to have its sequence inspected.\n currentSeq = '' # Initialise the sequence of the protein.\n protDescription = False # We are now expecting a protein sequence, not a protein description.\n else:\n # If the line does not begin with a '>', and it is expected to, it is possible that the amino acid sequence\n # is split over multiple lines.\n if line.isalpha():\n # If every character on the line is a letter, then the line contains a valid portion of the sequence.\n # Add the uppercase version of the sequence portion to the sequence currently being recorded.\n currentSeq += line.upper()\n else:\n # If the line did not contain only letters, terminate the program.\n errorMessage = \"Expected line \" + str(lineCount) + \" to start with a >, but instead got: \" + line\n return 1, errorMessage\n else:\n # If an amino acid sequence is expected.\n if line.isalpha():\n # If the line is all alphabetic characters, write the line out and indicate that we are expecting a\n # protein description line next (i.e. one beginning with a '>').\n currentSeq += line.upper()\n protDescription = True\n else:\n # If the line did not contain only letters, terminate the program.\n errorMessage = \"Expected line \" + str(lineCount) + \" to contain only letters, but instead got: \" + line\n return 2, errorMessage\n\n lineCount += 1\n\n # Catch the final protein from the file, and determine whether it should be recorded.\n if minLength == -1:\n if maxLength == -1:\n proteinsInFile[currentProt] = currentSeq\n elif len(currentSeq) <= maxLength:\n proteinsInFile[currentProt] = currentSeq\n elif len(currentSeq) >= minLength:\n if maxLength == -1:\n proteinsInFile[currentProt] = currentSeq\n elif len(currentSeq) <= maxLength:\n proteinsInFile[currentProt] = currentSeq\n\n if len(proteinsInFile.keys()) < 2:\n # There are too few protein sequences entered\n errorMessage = (\"Not enough unique protein sequences have been entered.\" +\n \" This is possibly caused by not enough sequences of the required minimum and maximum length being provided.\"\n )\n return 3, errorMessage\n elif protDescription:\n # Return an indication that the FASTA file is correctly formatted.\n outputString = ''\n for i in proteinsInFile.keys():\n outputString += i + '\\n' + proteinsInFile[i] + '\\n'\n return 0, outputString[:-1]\n else:\n # The file did not end with a protein sequence.\n errorMessage = \"Reached the end of the file, but no protein sequence found for the final protein.\"\n return 3, errorMessage","def printEncodePep(self):\r\n for i in range(len(self.seq)):\r\n if self.seq[i:i+(len(self.peptide*3))] in self.allPepSeqs:\r\n print(self.seq[i:i+(len(self.peptide*3))]) # print peptide if DNA region matches a possible peptide\r\n return","def count_variant(self, variant_dna, include_indels=True):\n if not re.match(\"^[ACGTNXacgtnx]+$\", variant_dna):\n raise ValueError(\n \"Variant DNA sequence contains unexpected \"\n \"characters [{}]\".format(self.name)\n )\n\n variant_dna = variant_dna.upper()\n\n if len(variant_dna) != len(self.wt.dna_seq):\n if self.aligner is not None:\n mutations = self.align_variant(variant_dna)\n else:\n return None\n else:\n mutations = list()\n for i in range(len(variant_dna)):\n if variant_dna[i] != self.wt.dna_seq[i]:\n mutations.append(\n (\n i,\n \"{pre}>{post}\".format(\n pre=self.wt.dna_seq[i], post=variant_dna[i]\n ),\n )\n )\n if len(mutations) > self.max_mutations:\n if self.aligner is not None:\n mutations = self.align_variant(variant_dna)\n if len(mutations) > self.max_mutations:\n # too many mutations post-alignment\n return None\n else:\n # stop looping over this variant\n break\n else:\n # too many mutations and not using aligner\n return None\n\n mutation_strings = list()\n if self.is_coding():\n variant_protein = \"\"\n for i in range(0, len(variant_dna), 3):\n try:\n variant_protein += CODON_TABLE[variant_dna[i : i + 3]]\n except KeyError: # garbage codon due to indel, X, or N\n variant_protein += \"?\"\n\n for pos, change in mutations:\n ref_dna_pos = pos + self.wt.dna_offset + 1\n ref_pro_pos = pos // 3 + self.wt.protein_offset + 1\n mut = \"c.{pos}{change}\".format(pos=ref_dna_pos, change=change)\n if has_indel(change):\n mut += \" (p.{pre}{pos}fs)\".format(\n pre=AA_CODES[self.wt.protein_seq[pos // 3]], pos=ref_pro_pos\n )\n elif variant_protein[pos // 3] == self.wt.protein_seq[pos // 3]:\n mut += \" (p.=)\"\n else:\n mut += \" (p.{pre}{pos}{post})\".format(\n pre=AA_CODES[self.wt.protein_seq[pos // 3]],\n pos=ref_pro_pos,\n post=AA_CODES[variant_protein[pos // 3]],\n )\n mutation_strings.append(mut)\n else:\n for pos, change in mutations:\n ref_dna_pos = pos + self.wt.dna_offset + 1\n mut = \"n.{pos}{change}\".format(pos=ref_dna_pos, change=change)\n mutation_strings.append(mut)\n\n if len(mutation_strings) > 0:\n variant_string = \", \".join(mutation_strings)\n else:\n variant_string = WILD_TYPE_VARIANT\n return variant_string","def getRevCodonSeqs(self):\r\n compDict = {'A': 't', 'T': 'a', 'G': 'c', 'C': 'g'} # nuc compliments for reverse strand\r\n revPep = [] # list to hold the temporary reverse peptides before incorporation into the complete list\r\n for seq in self.allPepSeqs:\r\n revSeq = seq[::-1] # reverses the strand to be prepped for nt compliments\r\n for nuc in compDict:\r\n revSeq = revSeq.replace(nuc, compDict[nuc]) # replaces nt's with their compliments\r\n revSeq = revSeq.upper()\r\n revPep.append(revSeq)\r\n for i in revPep:\r\n self.allPepSeqs.append(i) # adds the reverse strand peptide to the list of possible peptide seqs\r\n return","def gene_finder(dna):\n viable_strings = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitialize empty list (for strings)\n viable_amino_acids = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitialize empty list (for amino acids)\n threshold = longest_ORF_noncoding(dna, 1500)\t\t\t\t\t\t\t\t\t\t\t# sets threshold to longest random dna string\n real_dna = list(find_all_ORFs_both_strands(dna))\t\t\t\t\t\t\t\t\t\t# sets real_dna equal to all the ORFs, both strands\n for i in range(len(real_dna)):\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# searches through all the elements in list real_dna\n \tif len(real_dna[i]) > len(threshold):\t\t\t\t\t\t\t\t\t\t\t\t# compares real string to random string\n \t\tviable_strings.append(real_dna[i])\t\t\t\t\t\t\t\t\t\t\t\t# if real string is longer, adds it to list\n for i in range(len(viable_strings)):\t\t\t\t\t\t\t\t\t\t\t\t\t# searches through all elements in viable_strings\n \ta = coding_strand_to_AA(viable_strings[i])\t\t\t\t\t\t\t\t\t\t\t# translates each string to amino acid sequence\n \tviable_amino_acids.append(a)\t\t\t\t\t\t\t\t\t\t\t\t\t\t# adds amino acids to list\n return viable_amino_acids\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns list","def handle_seq(seq, barcode_map, result_dict):\n for i in range(len(seq)):\n for barcode in barcode_map.keys():\n possible_match = seq[i: i + len(barcode)]\n if possible_match == barcode:\n result_dict[barcode][i] += 1","def _obtain_t_strand(self, protein):\r\n\r\n strand = [[], []]\r\n for amino_acid in protein:\r\n codon_chooser = base_maps[numpy.where(codons == amino_acid)]\r\n for index in range(3):\r\n strand[0].append(codon_chooser[0][index])\r\n if len(codon_chooser) > 1:\r\n strand[1].append(codon_chooser[1][index])\r\n else:\r\n strand[1].append(0)\r\n\r\n return numpy.array(strand)"],"string":"[\n \"def dna_to_protein(seq):\\n\\n # Verify a convertible sequence\\n if len(seq) % 3 != 0:\\n raise RuntimeError('Total number of bases must be a multiple of 3')\\n\\n # Iterate through adding the proteins\\n protein = ''\\n for i in range(0, len(seq), 3):\\n protein += bioinfo_dicts.codons[seq[i:i+3]]\\n return protein\",\n \"def dna_to_protein(dna: str, start: int=0):\\n return rna_to_protein(dna_to_rna(dna, start), start=start)\",\n \"def proteinTranslation(seq, geneticCode = STANDARD_GENETIC_CODE):\\n\\n seq = seq.replace('T','U') # Make sure we have RNA sequence\\n proteinSeq = []\\n \\n i = 0\\n while i+2 < len(seq):\\n \\n codon = seq[i:i+3]\\n aminoAcid = geneticCode[codon]\\n \\n if aminoAcid is None: # Found stop codon\\n break\\n\\n proteinSeq.append(aminoAcid)\\n i += 3\\n\\n return proteinSeq\",\n \"def return_peptide (RNA):\\n\\t# Should work with already made sequence without stop codons. Only one peptide per call\\n\\n\\tdna.isNucleotide(RNA)\\n\\tif 'T' in RNA: raise dna.InvalidSequenceError\\t\\n\\tpeptide = \\\"\\\"\\n\\tid = 0\\n\\twhile id < len(RNA):\\n\\t\\ttRNA = RNA[id:id+3]\\n\\t\\tif not tRNA in RNA_code: break\\n\\t\\tAA = RNA_code[tRNA]\\n\\t\\tif AA == False: # In the case if was mistake in the previous step\\n\\t\\t\\tbreak\\n\\t\\tpeptide += AA\\n\\t\\tid += 3\\t\\n\\treturn peptide\",\n \"def protein_from_orfs(dna):\\n rna = dna.replace(\\\"T\\\", \\\"U\\\")\\n reverse_complement_rna = complement_strand(dna).replace(\\\"T\\\", \\\"U\\\")\\n\\n candidate_proteins = set()\\n\\n for strand in [rna, reverse_complement_rna]:\\n for index in [m.start() for m in re.finditer('AUG', strand)]:\\n codons_list = codons(strand[index:])\\n protein = \\\"\\\"\\n\\n if any(rna_codon_dict[codon] == \\\"Stop\\\" for codon in codons_list):\\n for codon in codons_list:\\n symbol = rna_codon_dict[codon]\\n\\n if symbol != \\\"Stop\\\":\\n protein += symbol\\n else:\\n candidate_proteins.add(protein)\\n break\\n\\n return candidate_proteins\",\n \"def rna_to_protein(rna: str, to_str=True, start: Union[int, Callable[[str], int]]=start_with_the_beggining,\\n end=False):\\n pos = start(rna) if callable(start) else start\\n if pos < 0:\\n return None if not to_str else \\\"\\\"\\n else:\\n rna = rna[pos:]\\n result = [\\\"\\\"] * (len(rna) // 3)\\n for i in range(len(result)):\\n elem = rna_codon_table[rna[3 * i: 3 * i + 3]]\\n if elem != STOP_CODON:\\n result[i] = elem\\n else:\\n result = result[:i]\\n break\\n else:\\n # if no break occurs, then stop codon wasn't found, so if end argument is True empty sequence should be returned\\n if end:\\n result = []\\n if to_str:\\n result = \\\"\\\".join(result)\\n return result\",\n \"def __init__(self, seq, peptide):\\r\\n self.seq = seq # original DNA sequence\\r\\n self.peptide = peptide # original peptide sequence\\r\\n self.allPepSeqs = [] # list to hold all possible nuc sequences based on the peptide sequence\\r\\n self.codonTable = { # holds all amino acids and their associated codons\\r\\n 'F': ['TTT', 'TTC'], 'S': ['TCT', 'TCC', 'TCA', 'TCG', 'AGT', 'AGC'],\\r\\n 'Y': ['TAT', 'TAC'], 'C': ['TGT', 'TGC'], 'L': ['TTA', 'TTG', 'CTT', 'CTC', 'CTA', 'CTG'],\\r\\n '-': ['TAA', 'TGA', 'TAG'], 'W': ['TGG'], 'P': ['CCT', 'CCC', 'CCA', 'CCG'],\\r\\n 'H': ['CAT', 'CAC'], 'R': ['CGT', 'CGC', 'CGA', 'CGG', 'AGA', 'AGG'], 'Q': ['CAA', 'CAG'],\\r\\n 'I': ['ATT', 'ATC', 'ATA'], 'T': ['ACT', 'ACC', 'ACA', 'ACG'], 'N': ['AAT', 'AAC'],\\r\\n 'K': ['AAA', 'AAG'], 'M': ['ATG'], 'V': ['GTT', 'GTC', 'GTA', 'GTG'],\\r\\n 'A': ['GCT', 'GCC', 'GCA', 'GCG'], 'D': ['GAT', 'GAC'], 'G': ['GGT', 'GGC', 'GGA', 'GGG'],\\r\\n 'E': ['GAA', 'GAG']\\r\\n }\",\n \"def coding_strand_to_AA(dna):\\n protein=''\\n for i in range(0,len(dna),3):\\n\\t if dna[i:i+3] in aa_table.keys():\\n\\t \\tprotein += aa_table[dna[i:i+3]]\\n return protein\",\n \"def coding_strand_to_AA(dna):\\n dnainp = dna\\n protein = ''\\n if len(dnainp)<3:\\n return \\\"ERROR: The provided fragment is too short to contain any codons.\\\"\\n# elif len(dnainp)%3 is not 0:\\n# print \\\"Warning: The provided DNA fragment does not contain an integer number of codons. Excess bases were leftout.\\\"\\n while len(dnainp) >=3:\\n cod = dnainp[:3]\\n for i in codons:\\n for j in i:\\n if j == cod:\\n protein = protein + aa[codons.index(i)]\\n dnainp = dnainp[3:]\\n return protein\",\n \"def translate(dna):\\n rna = dna.replace('T', 'U')\\n startIndex = dna.find('AUG') + 1\\n aminoAcidsSeq = \\\"\\\"\\n for i in range(startIndex, len(rna), 3):\\n # codon = rna[i: i+3]\\n aminoAcidsSeq += code[rna[i: i+3]]\\n if aminoAcidsSeq[len(aminoAcidsSeq) - 1] == '*':\\n aminoAcidsSeq = aminoAcidsSeq[:-1]\\n break\\n return aminoAcidsSeq\",\n \"def coding_strand_to_AA(dna):\\n #inital conditions\\n protein = ''\\n i = 0\\n\\n #for the length of DNA, translate each codon in an ORF to an amino acid\\n while i < (len(dna)-2):\\n codon = dna[i:i+3] \\n amino_acid = aa_table[codon]\\n protein= protein + amino_acid\\n i += 3\\n\\n #return the string of amino acids\\n return protein\",\n \"def Translate(self):\\n dna_to_protein = {\\n 'ATA':'I', 'ATC':'I', 'ATT':'I', 'ATG':'M',\\n 'ACA':'T', 'ACC':'T', 'ACG':'T', 'ACT':'T',\\n 'AAC':'N', 'AAT':'N', 'AAA':'K', 'AAG':'K',\\n 'AGC':'S', 'AGT':'S', 'AGA':'R', 'AGG':'R',\\n 'CTA':'L', 'CTC':'L', 'CTG':'L', 'CTT':'L',\\n 'CCA':'P', 'CCC':'P', 'CCG':'P', 'CCT':'P',\\n 'CAC':'H', 'CAT':'H', 'CAA':'Q', 'CAG':'Q',\\n 'CGA':'R', 'CGC':'R', 'CGG':'R', 'CGT':'R',\\n 'GTA':'V', 'GTC':'V', 'GTG':'V', 'GTT':'V',\\n 'GCA':'A', 'GCC':'A', 'GCG':'A', 'GCT':'A',\\n 'GAC':'D', 'GAT':'D', 'GAA':'E', 'GAG':'E',\\n 'GGA':'G', 'GGC':'G', 'GGG':'G', 'GGT':'G',\\n 'TCA':'S', 'TCC':'S', 'TCG':'S', 'TCT':'S',\\n 'TTC':'F', 'TTT':'F', 'TTA':'L', 'TTG':'L',\\n 'TAC':'Y', 'TAT':'Y', 'TAA':'*', 'TAG':'*',\\n 'TGC':'C', 'TGT':'C', 'TGA':'*', 'TGG':'W',\\n }\\n \\n length = self.length\\n reading = {}\\n for i in range(3):\\n reading['frame_'+str(i+1)] = tuple([dna_to_protein[self.sequence[index:index+3]] for index in range(i,length-2,3)])\\n reverse_strand = Analyze_DNA_Sequence.Complementary(self,'5-3')\\n for i in range(3):\\n reading['frame_'+str(i+4)] = tuple([dna_to_protein[reverse_strand[index:index+3]] for index in range(i,length-2,3)])\\n\\n return reading\",\n \"def getCodonSeqs(self):\\r\\n combinations = list(self.codonTable[aa] for aa in self.peptide) # creates a list of possible codons based on AA\\r\\n self.allPepSeqs = list(''.join(codon) for codon in itertools.product(*combinations)) # creates list of peptides\\r\\n return\",\n \"def translate_sequence(sequence, genetic_code = {'GUC': 'V', 'ACC': 'T', 'GUA': 'V', 'GUG': 'V', 'ACU': 'T', 'AAC': 'N', 'CCU': 'P', 'UGG': 'W', 'AGC': 'S', 'AUC': 'I', 'CAU': 'H', 'AAU': 'N', 'AGU': 'S', 'GUU': 'V', 'CAC': 'H', 'ACG': 'T', 'CCG': 'P', 'CCA': 'P', 'ACA': 'T', 'CCC': 'P', 'UGU': 'C', 'GGU': 'G', 'UCU': 'S', 'GCG': 'A', 'UGC': 'C', 'CAG': 'Q', 'GAU': 'D', 'UAU': 'Y', 'CGG': 'R', 'UCG': 'S', 'AGG': 'R', 'GGG': 'G', 'UCC': 'S', 'UCA': 'S', 'UAA': '*', 'GGA': 'G', 'UAC': 'Y', 'GAC': 'D', 'UAG': '*', 'AUA': 'I', 'GCA': 'A', 'CUU': 'L', 'GGC': 'G', 'AUG': 'M', 'CUG': 'L', 'GAG': 'E', 'CUC': 'L', 'AGA': 'R', 'CUA': 'L', 'GCC': 'A', 'AAA': 'K', 'AAG': 'K', 'CAA': 'Q', 'UUU': 'F', 'CGU': 'R', 'CGC': 'R', 'CGA': 'R', 'GCU': 'A', 'GAA': 'E', 'AUU': 'I', 'UUG': 'L', 'UUA': 'L', 'UGA': '*', 'UUC': 'F'}, start_pos = 0):\\n #find first orf\\n #first_orf_seq = find_first_orf(sequence)\\n\\n # ensure sequence is uppercase\\n seq = sequence.upper()\\n\\n #translate the sequence\\n protein = \\\"\\\"\\n for i in range(0, len(seq) - (len(seq) % 3), 3):\\n codon = seq[i:i + 3]\\n if genetic_code[codon] == \\\"*\\\":\\n break\\n protein += genetic_code[codon]\\n return protein\",\n \"def TranslateRNA(rna):\\n rna = rna.lower().replace('\\\\n', '').replace(' ', '')\\n \\n ### codon table ###\\n \\n bases = [ 'u', 'c', 'a', 'g']\\n codons = [a+b+c for a in bases for b in bases for c in bases]\\n aminoacids = 'FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG'\\n codon_table = dict(zip(codons, aminoacids))\\n \\n ### codon lookup ### \\n \\n pos = 0\\n protein = ''\\n while pos < len(rna)-2:\\n codon = rna[pos:pos+3]\\n for key in codon_table:\\n if codon == key:\\n if codon_table[key] != '*':\\n protein = protein + codon_table[key]\\n pos +=3\\n else:\\n pos +=3\\n break \\n return (protein)\",\n \"def translate_DNA(dnaStrand,translation_table='DNA_TABLE.txt'):\\r\\n\\r\\n #dictionary to store the corresponding protein for each codon\\r\\n d={'TTT':'F','CTT':'L','ATT':'I','GTT':'V','TTC':'F','CTC':'L','ATC':'I','GTC':'V','TTA':'L','CTA':'L','ATA':'I','GTA':'V','TTG':'L','CTG':'L','ATG':'M','GTG':'V','TCT':'S','CCT':'P','ACT':'T','GCT':'A','TCC':'S','CCC':'P','ACC':'T','GCC':'A','TCA':'S','CCA':'P','ACA':'T','GCA':'A','TCG':'S','CCG':'P','ACG':'T','GCG':'A','TAT':'Y','CAT':'H','AAT':'N','GAT':'D','TAC':'Y','CAC':'H','AAC':'N','GAC':'D','TAA':'Stop','CAA':'Q','AAA':'K','GAA':'E','TAG':'Stop','CAG':'Q','AAG':'K','GAG':'E','TGT':'C','CGT':'R','AGT':'S','GGT':'G','TGC':'C','CGC':'R','AGC':'S','GGC':'G','TGA':'Stop','CGA':'R','AGA':'R','GGA':'G','TGG':'W','CGG':'R','AGG':'R','GGG':'G'}\\r\\n protiens=\\\"\\\"\\r\\n for i in range(0,len(dnaStrand),3):\\r\\n #extracting each codon\\r\\n s=dnaStrand[i:i+3]\\r\\n if(d[s]!=\\\"Stop\\\"):\\r\\n protiens+=d[s]\\r\\n\\r\\n return protiens\",\n \"def translate_sequence(rna_sequence, genetic_code):\\n #Crate an empty list to store AA sequence:\\n AA_list = []\\n # Convert all rna_sequence to upper case:\\n rna_sequence=rna_sequence.upper()\\n # Convert all rna_sequence into a list:\\n rna_list = list(rna_sequence)\\n # This conditon will run if rna_sequence is at least 3 bases long, and only once it find start codon ,\\n #and stop once it finds stop codon.\\n while True:\\n if len(rna_list) > 2:\\n codon=''.join(rna_list[0:3])\\n #Delete first 3 bases since its alread added as codon, thus no longer needed.\\n del rna_list[0:3]\\n else:\\n break\\n #Using genetic code dictionary to find AA for each corresponding codon:\\n AA=genetic_code[codon]\\n #Break loop once it finds stop codon\\n if AA=='*':\\n break\\n #Add add translatable AA to the AA_list:\\n AA_list.append(AA)\\n return ''.join(AA_list)\",\n \"def coding_strand_to_AA(dna):\\n amino_acid=\\\"\\\"\\n for i in range(0, len(dna), 3):\\n mycodon=dna[i:i+3]\\n # print'this is my codon'\\n #print mycodon\\n for j in range(len(codons)):\\n for k in range(len(codons[j])):\\n #print codons[j][k]\\n if codons[j][k] == mycodon:\\n #print aa[j]\\n amino_acid += aa[j]\\n return amino_acid\\n \\n #step uno break apart string into groups of three\\n #find sequence +find index\\n #then connect to amino acids \",\n \"def thread_dna(\\n PROT, NUCL, STOP\\n ):\\n\\n # read in aligned protein fasta file\\n format = \\\"fasta\\\"\\n handle = open(PROT)\\n PROTa = list(SeqIO.parse(handle, format))\\n\\n # read in aligned protein fasta file\\n format = \\\"fasta\\\"\\n handle = open(NUCL)\\n NUCLf = list(SeqIO.parse(handle, format))\\n\\n # initialize dictionary for sequences\\n pal2nal = {}\\n\\n # loop through genes and thread DNA over\\n # protein alignment\\n for entry in range(0, len(PROTa)):\\n # save the gene ID to ID\\n ID = ''\\n ID = PROTa[entry].id\\n # save protein sequence to Pseq\\n Pseq = ''\\n Pseq = PROTa[entry].seq\\n # save nucleotide sequence to Nseq\\n Nseq = ''\\n Nseq = NUCLf[entry].seq\\n\\n # # check that Nseq is divisible by three and therefore not a pseudogene\\n # if len(Nseq) % 3 != 0:\\n # print(\\\"\\\")\\n # print(ID, \\\"nucleotide sequence has a length of\\\", len(Nseq))\\n # print(\\\"and cannot be threaded over the protein alignment.\\\")\\n # print(\\\"Exiting now...\\\\n\\\")\\n # sys.exit()\\n\\n pal2nal[ID] = ''\\n GAPcnt = 0\\n # loop through the sequence\\n for AA in range(0, (int(len(Pseq))+1) - 1, 1):\\n # if stops should be included\\n if STOP == 'T':\\n # if AA is a gap insert a codon of gaps\\n if Pseq[AA] == \\\"-\\\":\\n pal2nal[ID] += ('---')\\n GAPcnt+=1\\n # if AA is not a gap, insert the corresponding codon\\n elif Pseq[AA] != \\\"-\\\":\\n NTwin=(AA-GAPcnt)*3\\n pal2nal[ID] += (Nseq[NTwin:NTwin+3])\\n # if stops should not be included\\n elif STOP == 'F':\\n # if AA is a gap insert a codon of gaps\\n if Pseq[AA] == \\\"-\\\":\\n pal2nal[ID] += ('---')\\n GAPcnt+=1\\n # if AA is not a gap, insert the corresponding codon\\n elif Pseq[AA] != \\\"-\\\":\\n # if AA is a stop or ambiguous insert a codon of gaps\\n if Pseq[AA] == 'X' or Pseq[AA] == '*':\\n pal2nal[ID] += ('---')\\n else:\\n NTwin=(AA-GAPcnt)*3\\n pal2nal[ID] += (Nseq[NTwin:NTwin+3])\\n\\n\\n\\n ## this commented code will check if the nucleotide window \\n ## translates to the corresponding codon\\n # if Pseq[AA] != Nseq[NTwin:NTwin+3].translate():\\n # print(\\\"\\\\nAmino acid position\\\", AA, \\\"(\\\",Pseq[AA],\\\")\\\", \\\"does not correspond to codon\\\")\\n # print(Nseq[NTwin:NTwin+3], \\\"in nucleotide window\\\", NTwin,\\\"-\\\",NTwin+3)\\n # print(Nseq[NTwin:NTwin+3], \\\"translates to\\\", Nseq[NTwin:NTwin+3].translate())\\n # print(\\\"Nucleotides cannot be threaded ontop of the protein sequence.\\\")\\n # print(\\\"Exiting now...\\\\n\\\")\\n # sys.exit()\\n\\n # print out threaded DNA alignment\\n for entry in range(0, len(PROTa)):\\n print(\\\">{}\\\\n{}\\\".format(PROTa[entry].id, pal2nal[PROTa[entry].id]))\",\n \"def translate(self,frame=1):\\n if self.seq_type.upper() != \\\"DNA\\\":\\n return \\\"Not a DNA sequence (wrong seq_type)\\\"\\n\\n aa_output=\\\"\\\"\\n dna_input=self.seq\\n if frame == 0 or frame not in range(-3,4):\\n return \\\"Please specify a correct reading frame number. (+/- 1,2,3)\\\"\\n\\n elif frame in range(-3,0):\\n dna_input=reverse_complement(dna_input)\\n\\n for pos in range (abs(frame)-1,len(dna_input)-2,3):\\n codon=dna_input[pos:pos+3]\\n aa_output += translation_codon(codon)\\n\\n return myseq(aa_output,\\\"Protein\\\")\",\n \"def coding_strand_to_AA(dna):\\n Seq = ''\\n for i in range(0,len(dna),3): \\n triple = dna[i:i+3]\\n print triple\\n for k in range(len(codons)):\\n if triple in codons[k]: \\n print \\\"Casey Rocks\\\"\\n print codons[k]\\n amino = aa[k]\\n Seq+=amino\\n return Seq\",\n \"def collapse(L):\\n output = \\\"\\\"\\n for s in L:\\n output = output + s\\n return output\\n\\n\\n \\\"\\\"\\\"1) Computes the Protein encoded by a sequence of DNA. This function\\n does not check for start and stop codons (it assumes that the input\\n DNA sequence represents an protein coding region).\\n \\n dna: a DNA sequence represented as a string\\n returns: a string containing the sequence of amino acids encoded by the\\n the input DNA fragment\\n \\\"\\\"\\\"\",\n \"def convert_to_dna(protein_sequence, wt_protein_dict):\\n variant_dna_codons = []\\n for index in range(0, len(protein_sequence.seq)):\\n wt_aa = str(wt_protein_dict[index + 1][0])\\n codon = str(wt_protein_dict[index + 1][1])\\n variant_aa = protein_sequence.seq[index]\\n if variant_aa != wt_aa:\\n if variant_aa is not '-':\\n codon = sorted_codon_table[str(variant_aa)][0]\\n variant_dna_codons.append(codon)\\n variant_dna_str = \\\"\\\".join(variant_dna_codons)\\n variant_dna_seq = Seq(variant_dna_str, IUPAC.unambiguous_dna)\\n variant_dna_seq_obj = SeqRecord(variant_dna_seq, id=protein_sequence.id, name=protein_sequence.name,\\n description=protein_sequence.description)\\n return variant_dna_seq_obj\",\n \"def _process_prosody(sonority):\\n assert 9 not in sonority[1:-1]\\n assert sonority[0] == sonority[-1] == 9\\n\\n # create the output values\\n psequence = []\\n first = True # stores whether first syllable is currently being processed\\n\\n for i in range(1, len(sonority) - 1):\\n # get a segment with context\\n a, b, c = sonority[i - 1], sonority[i], sonority[i + 1]\\n\\n if b == 7: # a vowel\\n if first:\\n psequence.append('X')\\n first = False\\n elif c == 9: # last\\n psequence.append('Z')\\n else:\\n psequence.append('Y')\\n elif b == 8: # a tone\\n psequence.append('T')\\n elif a >= b >= c or c == 8: # descending\\n if c == 9: # word final position\\n psequence.append('Z' if b == 7 else 'N') # vowel or consonant\\n else:\\n if first:\\n first = False\\n psequence.append('A')\\n else:\\n psequence.append('L')\\n elif b < c or a > b <= c or a < b <= c: # ascending\\n # check for syllable first\\n if a == 9:\\n psequence.append('A')\\n elif a >= b:\\n if c == 9:\\n psequence.append('N')\\n else:\\n if psequence[-1] != 'A':\\n psequence = psequence[:-1] + [psequence[-1].replace('L', 'M')] + ['B']\\n else:\\n psequence.append('C')\\n else:\\n psequence.append('C')\\n elif a < b > c: # consonant peak\\n if first:\\n psequence.append('X')\\n first = False\\n else:\\n psequence.append('Y')\\n else:\\n raise ValueError(\\n \\\"Conversion to prosodic string failed due to a condition which was not \\\"\\n \\\"defined in the convertion, for details compare the numerical string \\\"\\n \\\"{0} with the profile string {1}\\\".format(sonority, psequence))\\n return psequence\",\n \"def translation (RNA):\\n\\tresult = []\\n\\tif len(RNA) == 0: return result\\n\\tdna.isNucleotide(RNA)\\n\\tif \\\"T\\\" in RNA: raise dna.InvalidSequenceError\\n\\n\\torf = dna.get_orf(RNA)\\n\\n\\tfor frame in orf:\\n\\t\\tpeptide = return_peptide(RNA[frame[0]:frame[1]])\\n\\t\\tresult.append(peptide)\\n\\treturn result\",\n \"def proteins(strand: str) -> list:\\n codons_to_translate = codonify(strand)\\n return translation(codons_to_translate)\",\n \"def main():\\r\\n\\r\\n # contents = ['ATGGCCATGGCCCCCAGAACTGAGATCAATAGTACCCGTATTAACGGGTGA', 'MA'] # sample input\\r\\n contents = []\\r\\n for line in sys.stdin:\\r\\n contents.append(line.strip())\\r\\n myPeptide = GenomeEncoding(contents[0], contents[1])\\r\\n myPeptide.getCodonSeqs()\\r\\n myPeptide.getRevCodonSeqs()\\r\\n myPeptide.printEncodePep()\",\n \"def try_protein(self):\\n location = [0, 0]\\n fold = 0\\n \\n # loop over aminoacids of the data and add info to aminoacids object\\n for i, char in enumerate(self.data):\\n aminoacid_number = i\\n aminoacid_type = char \\n \\n # make aminoacid object and add to aminoacids list\\n aminoacid = Aminoacid(aminoacid_type, aminoacid_number, location, fold)\\n self.occupied.append(aminoacid.location)\\n self.aminoacids.append(aminoacid)\\n\\n # make a line orientation as default\\n location = [0, len(self.data) + i]\\n return\",\n \"def translate(codon):\\n \\n table = { \\n 'ATA':'I', 'ATC':'I', 'ATT':'I', 'ATG':'M', \\n 'ACA':'T', 'ACC':'T', 'ACG':'T', 'ACT':'T', \\n 'AAC':'N', 'AAT':'N', 'AAA':'K', 'AAG':'K', \\n 'AGC':'S', 'AGT':'S', 'AGA':'R', 'AGG':'R', \\n 'CTA':'L', 'CTC':'L', 'CTG':'L', 'CTT':'L', \\n 'CCA':'P', 'CCC':'P', 'CCG':'P', 'CCT':'P', \\n 'CAC':'H', 'CAT':'H', 'CAA':'Q', 'CAG':'Q', \\n 'CGA':'R', 'CGC':'R', 'CGG':'R', 'CGT':'R', \\n 'GTA':'V', 'GTC':'V', 'GTG':'V', 'GTT':'V', \\n 'GCA':'A', 'GCC':'A', 'GCG':'A', 'GCT':'A', \\n 'GAC':'D', 'GAT':'D', 'GAA':'E', 'GAG':'E', \\n 'GGA':'G', 'GGC':'G', 'GGG':'G', 'GGT':'G', \\n 'TCA':'S', 'TCC':'S', 'TCG':'S', 'TCT':'S', \\n 'TTC':'F', 'TTT':'F', 'TTA':'L', 'TTG':'L', \\n 'TAC':'Y', 'TAT':'Y', 'TAA':'*', 'TAG':'*', \\n 'TGC':'C', 'TGT':'C', 'TGA':'*', 'TGG':'W', \\n } \\n \\n assert codon in table.keys(), \\\"Not a valid codon sequence.\\\"\\n \\n return table[codon]\",\n \"def get_seq_from_pdbchain(chain):\\n type_chain = check_type(chain)\\n if type_chain == \\\"protein\\\":\\n three_res_list = []\\n for res in chain:\\n residues_atoms = res.get_atoms()\\n for atom in residues_atoms:\\n if atom.get_name() == 'CA':\\n residue = atom.get_parent()\\n three_res_list.append(residue.get_resname())\\n return three_to_one(three_res_list) # three_to_one function\\n else:\\n nucleic_acid_res = []\\n for res in chain:\\n residues_atoms = res.get_atoms()\\n for atom in residues_atoms:\\n if atom.get_name() == 'P':\\n residue = atom.get_parent()\\n nucleic_acid_res.append(residue.get_resname())\\n nucleic_acid_seq = [x[2] for x in nucleic_acid_res]\\n return \\\"\\\".join(nucleic_acid_seq)\",\n \"def main():\\n\\n args = get_args()\\n seq = args.seq.upper()\\n codon_to_aa = {\\n 'AAA': 'K',\\n 'AAC': 'N',\\n 'AAG': 'K',\\n 'AAU': 'N',\\n 'ACA': 'T',\\n 'ACC': 'T',\\n 'ACG': 'T',\\n 'ACU': 'T',\\n 'AGA': 'R',\\n 'AGC': 'S',\\n 'AGG': 'R',\\n 'AGU': 'S',\\n 'AUA': 'I',\\n 'AUC': 'I',\\n 'AUG': 'M',\\n 'AUU': 'I',\\n 'CAA': 'Q',\\n 'CAC': 'H',\\n 'CAG': 'Q',\\n 'CAU': 'H',\\n 'CCA': 'P',\\n 'CCC': 'P',\\n 'CCG': 'P',\\n 'CCU': 'P',\\n 'CGA': 'R',\\n 'CGC': 'R',\\n 'CGG': 'R',\\n 'CGU': 'R',\\n 'CUA': 'L',\\n 'CUC': 'L',\\n 'CUG': 'L',\\n 'CUU': 'L',\\n 'GAA': 'E',\\n 'GAC': 'D',\\n 'GAG': 'E',\\n 'GAU': 'D',\\n 'GCA': 'A',\\n 'GCC': 'A',\\n 'GCG': 'A',\\n 'GCU': 'A',\\n 'GGA': 'G',\\n 'GGC': 'G',\\n 'GGG': 'G',\\n 'GGU': 'G',\\n 'GUA': 'V',\\n 'GUC': 'V',\\n 'GUG': 'V',\\n 'GUU': 'V',\\n 'UAA': 'Stop',\\n 'UAC': 'Y',\\n 'UAG': 'Stop',\\n 'UAU': 'Y',\\n 'UCA': 'S',\\n 'UCC': 'S',\\n 'UCG': 'S',\\n 'UCU': 'S',\\n 'UGA': 'Stop',\\n 'UGC': 'C',\\n 'UGG': 'W',\\n 'UGU': 'C',\\n 'UUA': 'L',\\n 'UUC': 'F',\\n 'UUG': 'L',\\n 'UUU': 'F',\\n }\\n\\n k = 3\\n\\n # 1: for loop\\n # protein = ''\\n # for codon in [seq[i:i + k] for i in range(0, len(seq), k)]:\\n # aa = codon_to_aa.get(codon, '-')\\n # if aa == 'Stop':\\n # break\\n # protein += aa\\n\\n # 2: list comprehension, slice to remove Stop\\n # codons = [seq[i:i + k] for i in range(0, len(seq), k)]\\n # aa = [codon_to_aa.get(codon, '-') for codon in codons]\\n # if 'Stop' in aa:\\n # aa = aa[:aa.index('Stop')]\\n # print(''.join(aa))\\n\\n # 3: L.C. -> map(), slice -> takewhile\\n # codons = map(lambda i: seq[i:i + k], range(0, len(seq), k))\\n # aa = map(lambda codon: codon_to_aa.get(codon, '-'), codons)\\n # print(''.join(takewhile(lambda c: c != 'Stop', aa)))\\n\\n # 4: combine map()\\n # aa = map(lambda c: codon_to_aa.get(c, '-'),\\n # map(lambda i: seq[i:i + k], range(0, len(seq), k)))\\n # print(''.join(takewhile(lambda c: c != 'Stop', aa)))\\n\\n # 5: combine all\\n # print(''.join(\\n # takewhile(\\n # lambda c: c != 'Stop',\\n # map(lambda c: codon_to_aa.get(c, '-'),\\n # map(lambda i: seq[i:i + k], range(0, len(seq), k))))))\\n\\n # 6: Seq\\n print(str(Seq(args.seq).translate()).replace('*', ''))\",\n \"def gene_to_protein(gene: str, intrones: Union[str, Collection[str]]) -> str:\\n intrones = intrones if not isinstance(intrones, str) else (intrones,)\\n for introne in intrones:\\n gene = gene.replace(introne, \\\"\\\")\\n return dna_to_protein(gene)\",\n \"def prot_sequence_finder(protL):\\n \\n idDict = prot_id_converter(protL, \\\"9606\\\", inpDB = \\\"genesymbol\\\",outDB=\\\"refseqproteingi\\\")\\n seqD = prot_entrez_fetch(idDict, retM=\\\"gb\\\", retT=\\\"fasta\\\")\\n \\n protD = {}\\n \\n for keyS, valueS in idDict.items():\\n protD[keyS] = seqD[valueS]\\n \\n return protD\",\n \"def ProteinRead(pdb_file, Include_dAA = True, IncludeWATER = False):\\n # structure from input file or fetched if not present\\n if(pdb_file[-4:] == '.pdb' or pdb_file[-3:] == '.gz'):\\n ppdb = PandasPdb().read_pdb(pdb_file)\\n else:\\n ppdb = PandasPdb().fetch_pdb(pdb_file)\\n \\n # lists for standard and d-AA used to save structure to dataset \\n standardAA = ['ALA','ARG','ASN','ASP','CYS','GLN','GLU','GLY','HIS','ILE','LEU','LYS','MET','PHE','PRO','SER','THR','TRP','TYR','VAL']\\n d_AA = ['DAL','DAR','DSG','DAS','DCY','DGN','DGL','GLY','DHI','DIL','DLE','DLY','MED','DPN','DPR','DSN','DTH','DTR','DTY','DVA']#scan takes into account only standard amino acids\\n\\n for aa in standardAA: #ATOM entries, excluding water molecules \\n if(aa==standardAA[0]):\\n ppdb_ATOM = ppdb.df['ATOM'][ppdb.df['ATOM']['residue_name'] == aa] \\n else:\\n ppdb_ATOM = pd.concat([ppdb_ATOM, ppdb.df['ATOM'][ppdb.df['ATOM']['residue_name'] == aa]], ignore_index=True) \\n\\n if(Include_dAA):\\n for i in range(0,len(d_AA)): \\n if(d_AA[i]!='GLY'):\\n ppdb_d_AA = pd.concat([ppdb.df['ATOM'][ppdb.df['ATOM']['residue_name'] == d_AA[i]],ppdb.df['HETATM'][ppdb.df['HETATM']['residue_name'] == d_AA[i]]], ignore_index=True)\\n pd.options.mode.chained_assignment = None \\n ppdb_d_AA['residue_name'].iloc[:] = standardAA[i] #dAA considered as standard one for scan \\n ppdb_ATOM = pd.concat([ppdb_ATOM, ppdb_d_AA], ignore_index=True) \\n\\n ppdb_PROTEIN = ppdb_ATOM #protein atoms saved here \\n ppdb_WATER = pd.concat([ppdb.df['HETATM'][ppdb.df['HETATM']['residue_name'] == 'HOH'],ppdb.df['ATOM'][ppdb.df['ATOM']['residue_name'] == 'HOH'],ppdb.df['HETATM'][ppdb.df['HETATM']['residue_name'] == 'WAT'],ppdb.df['ATOM'][ppdb.df['ATOM']['residue_name'] == 'WAT']], ignore_index=True) #oxygen atoms of water molecules\\n #can be both HETATM (standard pdb file) or ATOM (vmd output)\\n if(len(ppdb_WATER)>0 and IncludeWATER):\\n pd.options.mode.chained_assignment = None \\n ppdb_WATER['residue_name'].iloc[:] = 'HOH'\\n ppdb_WATER['chain_id'].iloc[:] = 'water'\\n ppdb_ATOM = pd.concat([ppdb_ATOM, ppdb_WATER], ignore_index=True)\\n\\n Chains = []\\n for i in range(0,len(ppdb_ATOM)):\\n if(ppdb_ATOM['chain_id'].iloc[i] in Chains):\\n continue\\n else:\\n Chains.append(ppdb_ATOM['chain_id'].iloc[i]) \\n return ppdb_ATOM, Chains\",\n \"def cropdna(dna, start=0, end=None, supfeature=False, product=None, process_description=None, process_name=None, \\n pd=None, pn=None, quinable=True, **kwargs):\\n \\n kwargs.setdefault(\\\"_sourcefile\\\", None) \\n kwargs.setdefault(\\\"process_id\\\", None)\\n kwargs.setdefault(\\\"original_ids\\\", []) \\n _sourcefile = kwargs[\\\"_sourcefile\\\"] \\n process_id = kwargs[\\\"process_id\\\"] \\n original_ids = kwargs[\\\"original_ids\\\"]\\n\\n project = None\\n project = project if product is None else product\\n process_name = pn if process_name is None else process_name\\n process_description = pd if process_description is None else process_description\\n\\n if end is None or end == 0:\\n end = len(dna.seq) \\n \\n if start == 0 and end == len(dna.seq):\\n subdna = cutdna(dna, start, product=project, quinable=0)[0] \\n crop_positions = ((0, 0), (len(dna.seq), len(dna.seq)))\\n else:\\n subdna, crop_positions = cutdna(dna, start, end, product=project, crop=True, quinable=0) \\n \\n if quinable == 1 and quinable == True: \\n args = []\\n new_positions = [] \\n history_features = [subdna._history_feature] \\n for new_pos, pos in zip(crop_positions, (start, end)):\\n new_pos = \\\"/\\\".join(list(map(str,new_pos)))\\n new_pos = \\\"'\\\" + new_pos + \\\"'\\\"\\n if \\\"__dict__\\\" in dir(pos) and \\\"_dnafeature\\\" in pos.__dict__:\\n qkey = pos._qkey\\n for qindex, qfeat in enumerate(dna.__class__.queried_features_dict[qkey]):\\n if qfeat._second_id == pos._second_id:\\n break\\n args.append(\\\"QUEEN.queried_features_dict['{}'][{}]\\\".format(qkey, qindex))\\n history_features.append(pos.subject._history_feature) \\n \\n elif \\\"__dict__\\\" in dir(pos) and \\\"_qint\\\" in pos.__dict__:\\n qkey = pos.qkey\\n for qindex, qfeat in enumerate(dna.__class__.queried_features_dict[qkey]):\\n if qfeat._second_id == pos.parental_id:\\n break\\n args.append(\\\"QUEEN.queried_features_dict['{}'][{}].{}\\\".format(pos.qkey, qindex, pos.name))\\n history_features.append(pos.parent.subject._history_feature) \\n \\n else:\\n args.append(new_pos)\\n\\n pos1, pos2 = new_pos.split(\\\"/\\\") \\n if pos1[1:] == pos2[:-1]:\\n new_positions.append(pos1[1:]) \\n else:\\n new_positions.append(new_pos) \\n \\n if type(supfeature) in (tuple, list) and type(supfeature[0]) == dict:\\n for feature_dict in supfeature: \\n subdna.setfeature(feature_dict) \\n elif type(supfeature) == dict:\\n subdna.setfeature(supfeature)\\n\\n project = \\\"\\\" \\n fsupfeature = \\\"\\\" if supfeature == False else \\\", supfeature={}\\\".format(str(supfeature)) \\n fproduct = \\\"\\\" if product is None else \\\", product='\\\" + product + \\\"'\\\"\\n process_name = \\\"\\\" if process_name is None else \\\", process_name='\\\" + process_name + \\\"'\\\"\\n process_description = \\\"\\\" if process_description is None else \\\", process_description='\\\" + process_description + \\\"'\\\" \\n \\n subdna._product_id = subdna._unique_id if product is None else product \\n building_history = \\\"QUEEN.dna_dict['{}'] = cropdna(QUEEN.dna_dict['{}'], start={}, end={}{}{}{}{}{})\\\".format(subdna._product_id, dna._product_id, args[0], args[1], fsupfeature, project, fproduct, process_name, process_description)\\n \\n history_feature = _combine_history(subdna, history_features)\\n subdna._history_feature = history_feature\\n process_id, original_ids = make_processid(subdna, building_history, process_id, original_ids)\\n add_history(subdna, [building_history, \\\"start: {}; end: {}\\\".format(*new_positions), \\\",\\\".join([process_id] + original_ids)], _sourcefile) \\n subdna._check_uniqueness()\\n else:\\n subdna.__dict__[\\\"_product_id\\\"] = dna._product_id if \\\"_product_id\\\" in dna.__dict__ else dna._unique_id\\n\\n if product is None:\\n pass \\n else:\\n product.replace(\\\" \\\",\\\"\\\") \\n match = re.fullmatch(\\\"(.+)\\\\[(.+)\\\\]\\\", product)\\n if match:\\n if match.group(2).isdecimal() == True:\\n subdna.__class__._namespace[match.group(1)][int(match.group(2))] = subdna\\n else:\\n subdna.__class__._namespace[match.group(1)][match.group(2)] = subdna\\n else: \\n subdna.__class__._namespace[product] = subdna\\n return subdna\",\n \"def get_all_translations(rna_sequence, genetic_code):\\n #Convert all rna_sequence to upper case:\\n rna_sequence=rna_sequence.upper()\\n #get the lengh of RNA seq.\\n total_rna_bases=len(rna_sequence)\\n #Create an empty list to store all possible AA seq.\\n polypeptide_list = []\\n #Looping through all the RNA bases, selecting all 3 possible reading frames to scan for tranlation.\\n for i in range(total_rna_bases):\\n i_end= i +3\\n next_three=rna_sequence[i:i_end]\\n #Condition to check if the condon is start codon\\n if next_three=='AUG':\\n #If condition satisfies, translate all rna seq from start to stop codon using first function,\\n #translate_sequence\\n polypeptide=translate_sequence(rna_sequence[i:], genetic_code)\\n polypeptide_list.append(polypeptide)\\n #Return all 3 possible reading frames as a list in polypeptide_list\\n return polypeptide_list\",\n \"def extract_sequence(molecule, begin, gap = 8):\\n # Validte the length of the molecule\\n validate_molecule_length(molecule)\\n # Define the sequence variable to store the amino acid sequence\\n sequence = ''\\n # Get the total numbers of residues\\n length = len(molecule)\\n # The begin point should be equal or larger than 1 and equal or less than len(molecule) - gap \\n if isinstance(begin, int) and begin >= 0 and begin <= (length - gap) : \\n for i in range(gap + 1):\\n # Get the amino acid kind\\n aa = molecule[begin + i].kind\\n # Convert the three-letter amino acid name to one-letter character \\n # Store it in the sequence\\n sequence += convertAA[\\\"PDB\\\"][aa] \\n if len(sequence) == gap + 1 :\\n return sequence\\n else:\\n text += \\\"The amino acid number in the sequence is not correct\\\"\\n raise DeimmunizationError(text)\",\n \"def binary_to_seq():\\n bin_seq, dico_binary, comp_seq, file_comp = utf8_to_binary()\\n \\n #for each binary value associate the corresponding letter (key) \\n #according to the dictionnary \\n dna_seq = \\\"\\\"\\n reading_binary = \\\"\\\"\\n for value in bin_seq:\\n reading_binary += value\\n for letter, code in dico_binary.items():\\n if code == reading_binary:\\n dna_seq += letter\\n reading_binary = \\\"\\\"\\n break\\n \\n #print(dna_seq, bin_seq, comp_seq, file_comp)\\n return dna_seq, bin_seq, comp_seq, file_comp\",\n \"def find_aligned_codons(aln):\\n # throw out codons with non mod 3 gaps\\n ind2 = []\\n for i in range(0, aln.alignlen(), 3):\\n bad = False\\n\\n for key, val in aln.iteritems():\\n codon = val[i:i+3]\\n if \\\"-\\\" in codon and codon != \\\"---\\\":\\n bad = True\\n break\\n\\n if not bad:\\n ind2.extend([i, i+1, i+2])\\n\\n return ind2\",\n \"def coding_strand_to_AA(dna):\\n amino_acid = ''\\n i = 0\\n while i + 3 < len(dna) + 1:\\n amino_acid += aa_table[dna[i:i+3]]\\n i += 3\\n return amino_acid\",\n \"def _process_cdss(self, prot_fasta_path):\\n if self.is_metagenome:\\n prot_fasta = {} # type: dict\\n untranslatable_prot = set()\\n for cds_id in self.cdss:\\n cds = self.feature_dict[cds_id]\\n try:\\n prot_seq = str(Seq(cds['dna_sequence']).translate(\\n self.code_table, cds=True).strip(\\\"*\\\"))\\n except TranslationError as e:\\n cds['warnings'] = cds.get('warnings', []) + [str(e)]\\n # NOTE: we may need a different way of handling this for metagenomes.\\n prot_seq = \\\"\\\"\\n if self.is_metagenome:\\n untranslatable_prot.add(cds_id)\\n\\n if self.is_metagenome:\\n if prot_seq != \\\"\\\":\\n protein_id = \\\"\\\"\\n if cds.get(\\\"aliases\\\"):\\n aliases = cds['aliases']\\n for key, val in aliases:\\n if key == \\\"protein_id\\\":\\n protein_id = val\\n if not protein_id:\\n protein_id = cds['id'] # assign to some default\\n else:\\n # log a warning here?\\n pass\\n # TODO: update header to reflect what we actually want people\\n # to see.\\n if protein_id in prot_fasta:\\n prot_fasta[protein_id][0] += \\\"|\\\" + cds['id']\\n else:\\n fasta_seq_data = \\\">\\\" + protein_id + \\\" cds_ids:\\\" + cds['id']\\n prot_fasta[protein_id] = [fasta_seq_data, prot_seq]\\n else:\\n pass\\n\\n else:\\n cds.update({\\n \\\"protein_translation\\\": prot_seq,\\n \\\"protein_md5\\\": hashlib.md5(prot_seq.encode('utf8')).hexdigest(),\\n \\\"protein_translation_length\\\": len(prot_seq),\\n })\\n\\n if 'parent_gene' in cds:\\n parent_gene = self.feature_dict[cds['parent_gene']]\\n # no propigation for now\\n propagate_cds_props_to_gene(cds, parent_gene, self.is_metagenome)\\n elif self.generate_genes:\\n spoof = copy.copy(cds)\\n spoof['type'] = 'gene'\\n spoof['id'] = cds['id']+\\\"_gene\\\"\\n spoof['cdss'] = [cds['id']]\\n spoof['warnings'] = [warnings['spoofed_gene'].format(cds['id'])]\\n self.feature_dict[spoof['id']] = spoof\\n cds['parent_gene'] = spoof['id']\\n self.spoof_gene_count += 1\\n else:\\n raise ValueError(warnings['no_spoof'])\\n\\n self.feature_dict[cds['id']] = cds\\n\\n if self.is_metagenome:\\n with open(prot_fasta_path, 'w') as fid:\\n for key, line in prot_fasta.items():\\n fid.write('\\\\n'.join(line))\\n # do something with 'untranslatable_prot'\",\n \"def all_possible_gene_transcription(dna: str):\\n result = set()\\n for dna in (dna, reverse_complement(dna)):\\n rna = dna_to_rna(dna)\\n start = find_motif(rna, START_CODON)\\n for s in start:\\n r = rna_to_protein(rna, start=s, end=True)\\n if r:\\n result.add(r)\\n return result\",\n \"def translate_framed_strand(framed_strand):\\n\\n polypeptide = []\\n # Iterate through all the codons in our strand and look up their resultant amino acid\\n logging.info(\\\"Translating strand: \\\" + str(framed_strand))\\n for codon in framed_strand:\\n if len(codon) != 3:\\n break\\n if codon in stop_codons:\\n # We are at the end of the sequence, so cut.\\n logging.debug(\\\"Stopping at codon \\\" + codon)\\n break\\n logging.debug(\\\"Adding polypeptide \\\" + codons_to_amino_acids[codon][2])\\n polypeptide.append(codons_to_amino_acids[codon])\\n return polypeptide\",\n \"def _GetPseudoAAC2(ProteinSequence,lamda=10,weight=0.05):\\n\\trightpart=[]\\n\\tfor i in range(lamda):\\n\\t\\trightpart.append(_GetSequenceOrderCorrelationFactor(ProteinSequence,k=i+1))\\n\\t\\n\\tresult={}\\n\\ttemp=1+weight*sum(rightpart)\\n\\tfor index in range(20,20+lamda):\\n\\t\\tresult['PAAC'+str(index+1)]=round(weight*rightpart[index-20]/temp*100,3)\\n\\t\\n\\treturn result\",\n \"def getSequencefromPDB(pdbfile, chain='C', index=0):\\n parser = PDB.PDBParser(QUIET=True)\\n struct = parser.get_structure(pdbfile,pdbfile)\\n ppb = PDB.PPBuilder()\\n model = struct[0]\\n peptides = ppb.build_peptides(model[chain])\\n seq=''\\n for i,pep in enumerate(peptides):\\n seq+=str(pep.get_sequence())\\n return seq\",\n \"def coding_strand_to_AA(dna):\\n coding_strand = ''\\n for i in range(len(dna)/3):\\n aa = dna[3*i:(3*i)+3]\\n coding_strand += aa_table[aa]\\n return coding_strand\",\n \"def translate(rna):\\n RNA_CODON_TABLE = {\\\"UUU\\\": \\\"F\\\", \\\"UUC\\\": \\\"F\\\", \\\"UUA\\\": \\\"L\\\", \\\"UUG\\\": \\\"L\\\",\\n \\\"UCU\\\": \\\"S\\\", \\\"UCC\\\": \\\"S\\\", \\\"UCA\\\": \\\"S\\\", \\\"UCG\\\": \\\"S\\\",\\n \\\"UAU\\\": \\\"Y\\\", \\\"UAC\\\": \\\"Y\\\", \\\"UAA\\\": \\\"*\\\", \\\"UAG\\\": \\\"*\\\",\\n \\\"UGU\\\": \\\"C\\\", \\\"UGC\\\": \\\"C\\\", \\\"UGA\\\": \\\"*\\\", \\\"UGG\\\": \\\"W\\\",\\n \\\"CUU\\\": \\\"L\\\", \\\"CUC\\\": \\\"L\\\", \\\"CUA\\\": \\\"L\\\", \\\"CUG\\\": \\\"L\\\",\\n \\\"CCU\\\": \\\"P\\\", \\\"CCC\\\": \\\"P\\\", \\\"CCA\\\": \\\"P\\\", \\\"CCG\\\": \\\"P\\\",\\n \\\"CAU\\\": \\\"H\\\", \\\"CAC\\\": \\\"H\\\", \\\"CAA\\\": \\\"Q\\\", \\\"CAG\\\": \\\"Q\\\",\\n \\\"CGU\\\": \\\"R\\\", \\\"CGC\\\": \\\"R\\\", \\\"CGA\\\": \\\"R\\\", \\\"CGG\\\": \\\"R\\\",\\n \\\"AUU\\\": \\\"I\\\", \\\"AUC\\\": \\\"I\\\", \\\"AUA\\\": \\\"I\\\", \\\"AUG\\\": \\\"M\\\",\\n \\\"ACU\\\": \\\"T\\\", \\\"ACC\\\": \\\"T\\\", \\\"ACA\\\": \\\"T\\\", \\\"ACG\\\": \\\"T\\\",\\n \\\"AAU\\\": \\\"N\\\", \\\"AAC\\\": \\\"N\\\", \\\"AAA\\\": \\\"K\\\", \\\"AAG\\\": \\\"K\\\",\\n \\\"AGU\\\": \\\"S\\\", \\\"AGC\\\": \\\"S\\\", \\\"AGA\\\": \\\"R\\\", \\\"AGG\\\": \\\"R\\\",\\n \\\"GUU\\\": \\\"V\\\", \\\"GUC\\\": \\\"V\\\", \\\"GUA\\\": \\\"V\\\", \\\"GUG\\\": \\\"V\\\",\\n \\\"GCU\\\": \\\"A\\\", \\\"GCC\\\": \\\"A\\\", \\\"GCA\\\": \\\"A\\\", \\\"GCG\\\": \\\"A\\\",\\n \\\"GAU\\\": \\\"D\\\", \\\"GAC\\\": \\\"D\\\", \\\"GAA\\\": \\\"E\\\", \\\"GAG\\\": \\\"E\\\",\\n \\\"GGU\\\": \\\"G\\\", \\\"GGC\\\": \\\"G\\\", \\\"GGA\\\": \\\"G\\\", \\\"GGG\\\": \\\"G\\\"}\\n str = ''\\n list = [rna[i:i+3] for i in range(0,len(rna),3)]\\n for x in list:\\n #checks if x is in key of RNA_CODON_TABLE\\n if x in RNA_CODON_TABLE:\\n #appends only if the value for the given key is not *\\n if RNA_CODON_TABLE[x] != '*':\\n str = str + RNA_CODON_TABLE[x]\\n #if only one char is extra(meaning apart form the 3 pair characters available in dictionary)\\n #checks if the char is in following\\n elif len(x) == 1 and x in ['A','G','C','U']:\\n str = str + x\\n #if the char is of length 2 i.e, 2 words extra\\n elif len(x) == 2 and x[0] in ['A','G','C','U'] and x[1] in ['A','G','C','U']:\\n #Then appending the char to the actually converted string\\n str = str + x[0]\\n str = str + x[1]\\n #if the char is not in the above characters then it is a unrecognised character.\\n else:\\n print(\\\"Unrecognised character:\\\",x)\\n return str\",\n \"def write_protein_fasta(args, clusters=None, fasta_dir=None):\\n row, concat_fasta_path, frags = args\\n dotpath = row[\\\"path\\\"]\\n phylogeny_dict = {\\\"prot.idx\\\": row.name, \\\"path\\\": dotpath}\\n for phy_prop in [name for name in row.index if name.startswith(\\\"phy.\\\")]:\\n phylogeny_dict[phy_prop] = row[phy_prop]\\n inpath = dotpath_to_path(dotpath)\\n prot_info = read_tsv_or_parquet(inpath / PROTEINS_FILE)\\n prot_info[\\\"frag.idx\\\"] = prot_info[\\\"frag.id\\\"].map(\\n lambda oid: frags.loc[oid][\\\"frag.idx\\\"]\\n )\\n prot_info[\\\"frag.is_plas\\\"] = prot_info[\\\"frag.id\\\"].map(\\n lambda oid: frags.loc[oid][\\\"frag.is_plas\\\"]\\n )\\n prot_info[\\\"frag.is_scaf\\\"] = prot_info[\\\"frag.id\\\"].map(\\n lambda oid: frags.loc[oid][\\\"frag.is_scaf\\\"]\\n )\\n prot_info[\\\"frag.is_chr\\\"] = prot_info[\\\"frag.id\\\"].map(\\n lambda oid: frags.loc[oid][\\\"frag.is_chr\\\"]\\n )\\n prot_info[\\\"frag.id\\\"] = prot_info[\\\"frag.id\\\"].map(\\n lambda oid: frags.loc[oid][\\\"frag.id\\\"]\\n )\\n # Write out updated protein info\\n write_tsv_or_parquet(prot_info, inpath / HOMOLOGY_FILE)\\n # include phylogeny info in per-sequence info\\n for prop in phylogeny_dict:\\n prot_info[prop] = phylogeny_dict[prop]\\n # write concatenated sequence info\\n if clusters is None:\\n fasta_path = concat_fasta_path\\n info_to_fasta(None, fasta_path, append=True, infoobj=prot_info)\\n else:\\n for cluster_id, subframe in clusters.groupby(by=[\\\"cluster_id\\\"]):\\n cluster_info = prot_info[prot_info.index.isin(subframe[\\\"members\\\"])]\\n fasta_path = fasta_dir / f\\\"{cluster_id}.fa\\\"\\n info_to_fasta(None, fasta_path, append=True, infoobj=cluster_info)\",\n \"def GetPseudoAAC2(ProteinSequence,lamda=30,weight=0.05,AAP=[_Hydrophobicity,_hydrophilicity]):\\n\\trightpart=[]\\n\\tfor i in range(lamda):\\n\\t\\trightpart.append(GetSequenceOrderCorrelationFactor(ProteinSequence,i+1,AAP))\\n\\t\\n\\tresult={}\\n\\ttemp=1+weight*sum(rightpart)\\n\\tfor index in range(20,20+lamda):\\n\\t\\tresult['PAAC'+str(index+1)]=round(weight*rightpart[index-20]/temp*100,3)\\n\\t\\n\\treturn result\",\n \"def build_seq_data(seq,\\n sequence_length,\\n initial_primers,\\n search_range):\\n \\n aligned_seq=DNA.make_seq(seq)\\n # remove gap characters\\n unaligned_seq=str(DNA.make_seq(seq).degap())\\n gaps=aligned_seq.gap_maps()\\n \\n if search_range:\\n primer_start = get_corrected_index(seq,int(search_range.split(\\\":\\\")[0]))\\n primer_end = get_corrected_index(seq,int(search_range.split(\\\":\\\")[1]))\\n # Correct in case end index is close to the end of the sequence\\n if primer_end + sequence_length > len(unaligned_seq):\\n primer_end = len(unaligned_seq)-sequence_length+1\\n\\n else:\\n primer_start = 0\\n primer_end = len(unaligned_seq)-sequence_length+1\\n \\n for n in range(primer_start, primer_end):\\n seq_slice=unaligned_seq[n:n+sequence_length]\\n aligned_index=gaps[0][n]\\n unaligned_index=n\\n init_key=(seq_slice,aligned_index)\\n initial_primers[init_key]=unaligned_index\\n \\n return initial_primers\",\n \"def coding_strand_to_AA(dna):\\n dna_codons = split_into_codons(dna)\\n i = 0\\n aa_string = ''\\n while i < len(dna_codons):\\n if len(dna_codons[i]) == 3:\\n amino_acid = aa_table[dna_codons[i]]\\n aa_string += amino_acid\\n i += 1\\n return aa_string\",\n \"def binaryEncode(peptide):\\n\\n #do 1 hot encoding\\n binaryPeptide=''\\n for aa in peptide:\\n binaryAmino=''\\n if aa =='A':\\n binaryAmino='10000000000000000000'\\n if aa =='R':\\n binaryAmino='01000000000000000000'\\n if aa =='N':\\n binaryAmino='00100000000000000000'\\n if aa =='D':\\n binaryAmino='00010000000000000000'\\n if aa =='C':\\n binaryAmino='00001000000000000000'\\n if aa =='Q':\\n binaryAmino='00000100000000000000'\\n if aa =='E':\\n binaryAmino='00000010000000000000'\\n if aa =='G':\\n binaryAmino='00000001000000000000'\\n if aa =='H':\\n binaryAmino='00000000100000000000'\\n if aa =='I':\\n binaryAmino='00000000010000000000'\\n if aa =='L':\\n binaryAmino='00000000001000000000'\\n if aa =='K':\\n binaryAmino='00000000000100000000'\\n if aa =='M':\\n binaryAmino='00000000000010000000'\\n if aa =='F':\\n binaryAmino='00000000000001000000'\\n if aa =='P':\\n binaryAmino='00000000000000100000'\\n if aa =='S':\\n binaryAmino='00000000000000010000'\\n if aa =='T':\\n binaryAmino='00000000000000001000'\\n if aa =='W':\\n binaryAmino='00000000000000000100'\\n if aa =='Y':\\n binaryAmino='00000000000000000010'\\n if aa =='V':\\n binaryAmino='00000000000000000001'\\n binaryPeptide=binaryPeptide +binaryAmino\\n if len(binaryPeptide) == 500*20:\\n break \\n \\n while len(binaryPeptide) < 500*20:\\n binaryPeptide = binaryPeptide +str(0)\\n \\n binaryPeptide = np.array(list(binaryPeptide),dtype=float)\\n binaryPeptide = np.reshape(binaryPeptide,(binaryPeptide.shape[0],1))\\n binaryPeptide = np.transpose(binaryPeptide)\\n return binaryPeptide\",\n \"def get_protein_fasta(uniprot_id):\\r\\n url = \\\"http://www.uniprot.org/uniprot/{}.fasta\\\".format(uniprot_id)\\r\\n string = re.split(\\\"\\\\n\\\",ur.urlopen(url).read().decode(),1)[1]\\r\\n return re.sub(\\\"\\\\n\\\",\\\"\\\",string)\",\n \"def getMaskedSeq(align, mode='mask', barcode=False, delimiter=default_delimiter):\\n seq = align.seq\\n\\n # Build output sequence\\n if mode == 'tag' or not align.align_primer:\\n # Do not modify sequence\\n out_seq = seq\\n elif mode == 'trim':\\n # Remove region before primer\\n if not align.rev_primer:\\n out_seq = seq[align.start:]\\n else: \\n out_seq = seq[:align.end]\\n elif mode == 'cut':\\n # Remove primer and preceding region\\n if not align.rev_primer:\\n out_seq = seq[align.end:]\\n else: \\n out_seq = seq[:align.start]\\n elif mode == 'mask':\\n # Mask primer with Ns and remove preceding region\\n if not align.rev_primer:\\n mask_len = align.end - align.start + align.gaps\\n out_seq = 'N' * mask_len + seq[align.end:]\\n if hasattr(seq, 'letter_annotations') and \\\\\\n 'phred_quality' in seq.letter_annotations:\\n out_seq.letter_annotations['phred_quality'] = \\\\\\n [0] * mask_len + \\\\\\n seq.letter_annotations['phred_quality'][align.end:]\\n else:\\n mask_len = min(align.end, len(seq)) - align.start + align.gaps\\n out_seq = seq[:align.start] + 'N' * mask_len\\n if hasattr(seq, 'letter_annotations') and \\\\\\n 'phred_quality' in seq.letter_annotations:\\n out_seq.letter_annotations['phred_quality'] = \\\\\\n seq.letter_annotations['phred_quality'][:align.start] + \\\\\\n [0] * mask_len\\n \\n # Add alignment annotations to output SeqRecord\\n out_seq.annotations = seq.annotations \\n out_seq.annotations['primer'] = align.primer\\n out_seq.annotations['prstart'] = align.start\\n out_seq.annotations['error'] = align.error\\n\\n # Parse seq annotation and create output annotation\\n seq_ann = parseAnnotation(seq.description, delimiter=delimiter)\\n out_ann = OrderedDict([('SEQORIENT', seq.annotations['seqorient']),\\n ('PRIMER', align.primer)])\\n \\n # Add ID sequence to description\\n if barcode:\\n seq_code = seq[:align.start].seq if not align.rev_primer \\\\\\n else seq[align.end:].seq\\n out_seq.annotations['barcode'] = seq_code\\n out_ann['BARCODE'] = seq_code\\n \\n out_ann = mergeAnnotation(seq_ann, out_ann, delimiter=delimiter)\\n out_seq.id = flattenAnnotation(out_ann, delimiter=delimiter)\\n out_seq.description = ''\\n\\n return out_seq\",\n \"def coding_strand_to_AA(dna):\\n list1 = get_codons(dna)\\n string = ''\\n for codon in list1:\\n try:\\n string = string + aa_table[codon]\\n except KeyError:\\n continue\\n return string\",\n \"def _parse_peptidoform(seq: str, modification_list: list[dict], charge: Union[int, None]):\\n peptide = [\\\"\\\"] + list(seq) + [\\\"\\\"]\\n\\n # Add modification labels\\n for mod in modification_list:\\n peptide[int(mod[\\\"location\\\"])] += f\\\"[{mod['name']}]\\\"\\n\\n # Add dashes between residues and termini, and join sequence\\n peptide[0] = peptide[0] + \\\"-\\\" if peptide[0] else \\\"\\\"\\n peptide[-1] = \\\"-\\\" + peptide[-1] if peptide[-1] else \\\"\\\"\\n proforma_seq = \\\"\\\".join(peptide)\\n\\n # Add charge state\\n if charge:\\n proforma_seq += f\\\"/{charge}\\\"\\n\\n return Peptidoform(proforma_seq)\",\n \"def test_translate(self):\\n \\n orf = 'ATGTGGAGACGGAAACATCCGAGGACATCCGGAGGAACCCGGGGAGTTCTGAGTGGTAATTAG'\\n expected_primers = Seq('MWRRKHPRTSGGTRGVLSGN*', HasStopCodon(IUPAC.ExtendedIUPACProtein(), '*'))\\n result_primers = translate(orf)\\n self.assertEqual(result_primers, expected_primers)\\n self.assertEqual(len(result_primers), 21)\\n self.assertEqual(isinstance(result_primers, Seq), True)\",\n \"def guess_seq(seq):\\n dna = \\\"ACTG-N\\\"\\n \\n chars = util.unique(seq.upper())\\n \\n for char in chars:\\n if char not in dna:\\n return \\\"pep\\\"\\n return \\\"dna\\\"\",\n \"def _find_iupac(self):\\n # Create a string of the two states of the SNP in alphabetical order\\n ordered_snp = ''.join(sorted(re.findall('[ACGT]', self._snp)))\\n # Find the IUPAC code for the SNP\\n self._code = ''.join([c for c, o in self._IUPAC_CODES.items() if ordered_snp == o])\\n # Create the IUPAC version of the sequence\\n self._iupac = re.sub(r'\\\\[%s\\\\]' % self._snp[1:-1], self._code, self._sequence)\\n # Calculate the length of the sequence\\n self._length = len(self._iupac)\",\n \"def get_seq(self, table=1, cds=True):\\n dna_seq = '' \\n for exon in self.transcript.exons: \\n dna_seq += self.transcript.rna.gene.polymer.get_subseq(\\n start=max(self.coding_region.start, exon.start), \\n end=min(self.coding_region.end, exon.end))\\n \\n if self.transcript.rna.gene.strand == core.PolymerStrand.negative:\\n dna_seq = dna_seq.reverse_complement()\\n \\n return dna_seq.transcribe().translate(table=table, cds=cds)\",\n \"def cyclopeptide_sequence(self, spectrum):\\n\\t# Make dict for faster access\\n\\tspectrum_dict = dict(zip(spectrum, spectrum))\\n # Compute the max weight in spectrum. That has to be the weight of the acid\\n max_spectrum_weight = max(spectrum)\\n sequences = [\\\"\\\"]\\n final_sequences = []\\n while len(sequences) > 0:\\n # Copy sequences to new_seq\\n new_seq = copy.deepcopy(sequences)\\n sequences = list()\\n # Add new amino acid and check for consistency\\n for s in new_seq:\\n sequence_weight = ProteinTransformer(s).int_weight()\\n for a in protein_util.amino_acids_by_weight:\\n new_protein = s+a\\n new_weight = sequence_weight + protein_util.protein_mass_int[a]\\n # Case 1: Check if the new acid is consistent with spectrum\\n flag = True\\n for i in range(len(s)):\\n w = ProteinTransformer(s[i:]+a).int_weight()\\n if w not in spectrum_dict:\\n flag = False\\n break\\n if not flag:\\n continue\\n # Check if new weight attained maximum. If not, just append to pending sequences\\n elif new_weight < max_spectrum_weight:\\n sequences.append(new_protein)\\n # Finally, compare entire new spectrum with given spectrum\\n else:\\n new_spectrum = ProteinTransformer(new_protein).cyclospectrum()\\n if new_spectrum == spectrum:\\n final_sequences.append(new_protein)\\n \\n \\n\\t# Done. Now return final sequences\\n return final_sequences\",\n \"def seq_positions(seq, codon):\\n\\n positions = []\\n i = 0\\n\\n while codon in seq[i:]:\\n pos = seq.find(codon, i)\\n positions.append(pos)\\n i = pos + 1\\n positions.sort()\\n return positions\",\n \"def intercalateCodons( seq ):\\r\\n\\tseqLen = len(seq)\\r\\n\\tsitesPerCod = seqLen/3\\r\\n\\textraSites = seqLen%3\\r\\n\\tif extraSites == 0:\\r\\n\\t\\tcodOne = seq[0:sitesPerCod]\\r\\n\\t\\tcodTwo = seq[sitesPerCod:2*sitesPerCod]\\r\\n\\t\\tcodThree = seq[2*sitesPerCod:3*sitesPerCod]\\r\\n\\telif extraSites == 1:\\r\\n\\t\\tcodOne = seq[0:sitesPerCod+1]\\r\\n\\t\\tcodTwo = seq[sitesPerCod+1:(2*sitesPerCod)+1]\\r\\n\\t\\tcodThree = seq[(2*sitesPerCod)+1:(3*sitesPerCod)+1]\\r\\n\\telse:\\r\\n\\t\\tcodOne = seq[0:sitesPerCod+1]\\r\\n\\t\\tcodTwo = seq[sitesPerCod+1:(2*sitesPerCod)+2]\\r\\n\\t\\tcodThree = seq[(2*sitesPerCod)+2:(3*sitesPerCod)+2]\\r\\n\\tnewSeq = [x for t in itertools.izip_longest(codOne,codTwo,codThree) for x in t]\\r\\n\\t\\\"\\\"\\\"\\r\\n\\thttp://stackoverflow.com/questions/11125212/interleaving-lists-in-python\\r\\n\\t\\\"\\\"\\\"\\r\\n\\tnewSeq = filter(lambda a: a != None, newSeq)\\r\\n\\t\\\"\\\"\\\"\\r\\n\\thttp://stackoverflow.com/questions/1157106/remove-all-occurrences-of-a-value-from-a-python-list\\r\\n\\t\\\"\\\"\\\"\\r\\n\\treturn newSeq\",\n \"def GetPseudoAAC(ProteinSequence,lamda=30,weight=0.05,AAP=[_Hydrophobicity,_hydrophilicity]):\\n\\tres={}\\n\\tres.update(GetPseudoAAC1(ProteinSequence,lamda,weight,AAP))\\n\\tres.update(GetPseudoAAC2(ProteinSequence,lamda,weight,AAP))\\n\\treturn res\",\n \"def RNAorDNA ( seq ) :\\n\\tif dna_regex . search ( seq ):\\n\\t\\treturn RNA ( seq )\\n\\n\\tif rna_regex . search ( seq ):\\n\\t\\treturn DNA ( seq )\",\n \"def to_rna(seq):\\n seq=seq.replace('A','U')\\n seq=seq.replace('T','A')\\n seq=seq.replace('C',\\\"P\\\")\\n seq=seq.replace('G','C')\\n seq=seq.replace('P','G')\\n return seq\",\n \"def coding_strand_to_AA(dna):\\n num_codons = int(len(dna)/3)\\n num = 0\\n list_codons = []\\n aacids = ''\\n while num < num_codons:\\n num_start = int(num*3)\\n num_end = int(num*3 + 3)\\n list_codons.append(dna[num_start:num_end])\\n num = num + 1\\n for element in list_codons:\\n thing = aa_table[element]\\n aacids = aacids + thing\\n return aacids\",\n \"def aa(seq):\\n global codontable\\n seq = seq.upper()\\n if codontable is None:\\n # TODO: figure out the right place for the pre-computed information here\\n bases = ['T', 'C', 'A', 'G']\\n codons = [a+b+c for a in bases for b in bases for c in bases]\\n codons = codons + list(map(lambda x: x.lower(), codons))\\n amino_acids = 'FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG'\\n amino_acids = amino_acids + amino_acids.lower()\\n codontable = dict(zip(codons, amino_acids))\\n res = ''\\n for i in range(0, len(seq) - 2, 3):\\n res += codontable[seq[i:(i+3)]]\\n return res\",\n \"def preprocess(fasta_files, qual_files, mapping_file,\\r\\n barcode_type=\\\"golay_12\\\",\\r\\n min_seq_len=200, max_seq_len=1000, min_qual_score=25, starting_ix=1,\\r\\n keep_primer=False, max_ambig=0, max_primer_mm=0, trim_seq_len=False,\\r\\n dir_prefix='.', max_bc_errors=2, max_homopolymer=4,\\r\\n retain_unassigned_reads=False, keep_barcode=False,\\r\\n attempt_bc_correction=True, qual_score_window=0,\\r\\n disable_primer_check=False, reverse_primers='disable',\\r\\n reverse_primer_mismatches=0,\\r\\n record_qual_scores=False, discard_bad_windows=False,\\r\\n median_length_filtering=None, added_demultiplex_field=None,\\r\\n truncate_ambi_bases=False):\\r\\n\\r\\n if max_seq_len < 10:\\r\\n raise ValueError(\\\"Max sequence must be >= 10\\\")\\r\\n if min_seq_len >= max_seq_len:\\r\\n raise ValueError(\\\"Min len cannot be >= max len\\\")\\r\\n if min_qual_score < 0:\\r\\n raise ValueError(\\\"Min qual score must be > 0\\\")\\r\\n if starting_ix < 1:\\r\\n raise ValueError(\\\"Starting index must be > 0.\\\")\\r\\n if max_ambig < 0:\\r\\n raise ValueError(\\\"Max ambig chars must be >= 0.\\\")\\r\\n if max_primer_mm < 0:\\r\\n raise ValueError(\\\"Max primer mismatches must be >= 0.\\\")\\r\\n if reverse_primers not in ['disable', 'truncate_only', 'truncate_remove']:\\r\\n raise ValueError(\\\"reverse_primers parameter must be 'disable', \\\" +\\r\\n \\\"truncate_only, or truncate_remove.\\\")\\r\\n\\r\\n create_dir(dir_prefix, fail_on_exist=False)\\r\\n\\r\\n# try:\\r\\n# stat(dir_prefix)\\r\\n# except OSError:\\r\\n# mkdir(dir_prefix)\\r\\n\\r\\n \\\"\\\"\\\"# Generate primer sequence patterns - changing to mapping file primers.\\r\\n all_primer_seqs, primer_seq_len = \\\\\\r\\n get_primer_seqs(primer_seq_pats.split(',')) \\\"\\\"\\\"\\r\\n\\r\\n # Check mapping file and get barcode mapping\\r\\n map_file = open(mapping_file, 'U')\\r\\n headers, id_map, valid_map, warnings, errors, \\\\\\r\\n primer_seqs_lens, all_primers = check_map(\\r\\n map_file, disable_primer_check,\\r\\n barcode_type, added_demultiplex_field)\\r\\n\\r\\n if reverse_primers != 'disable':\\r\\n if 'ReversePrimer' not in headers:\\r\\n raise ValueError('To enable reverse primer check, there must ' +\\r\\n 'be a \\\"ReversePrimer\\\" column in the mapping file with a reverse ' +\\r\\n 'primer in each cell.')\\r\\n rev_primers = get_reverse_primers(id_map)\\r\\n else:\\r\\n rev_primers = False\\r\\n\\r\\n # *** Generate dictionary of {barcode: DNA(ReversePrimer).rc()}\\r\\n # First check for ReversePrimer in headers, raise error if not found\\r\\n # Implement local alignment for primer after barcode is determined.\\r\\n # Add option to flag seq with error for rev_primer not found\\r\\n # Check primer hit index, truncate sequence\\r\\n # unit tests.\\r\\n\\r\\n map_file.close()\\r\\n if errors:\\r\\n raise ValueError(\\\"Invalid mapping file. \\\" +\\r\\n \\\"Validate with check_id_map first: %s\\\" % \\\"\\\\n\\\".join(errors))\\r\\n\\r\\n # Find actual length of barcodes in the mapping file, also check for\\r\\n # variable lengths, in case of added_demultiplex, split on comma.\\r\\n barcode_length_check =\\\\\\r\\n list(set([len(bc.split(',')[0]) for bc in valid_map]))\\r\\n\\r\\n # Check barcode type\\r\\n if barcode_type not in BARCODE_TYPES:\\r\\n try:\\r\\n barcode_len, barcode_fun = int(barcode_type), correct_barcode\\r\\n except ValueError:\\r\\n raise ValueError(\\\"Unsupported barcode type: %s\\\" % barcode_type)\\r\\n else:\\r\\n barcode_len, barcode_fun = BARCODE_TYPES[barcode_type]\\r\\n\\r\\n # As people often do not specify a barcode that matches the lengths\\r\\n # of the barcodes used, a check on the actual barcode lengths needs to\\r\\n # be done, and an exception raised if they are variable length and not\\r\\n # specified as so.\\r\\n if barcode_type != \\\"variable_length\\\":\\r\\n # Raise error if variable length barcodes are present but not\\r\\n # specified\\r\\n if len(barcode_length_check) != 1:\\r\\n raise ValueError('Mapping file has variable length ' +\\r\\n 'barcodes. If this is intended, specifiy variable lengths ' +\\r\\n 'with the -b variable_length option.')\\r\\n # Raise error if the specified barcode length doesn't match what\\r\\n # is present in the mapping file.\\r\\n if barcode_len != barcode_length_check[0]:\\r\\n raise ValueError('Barcode length detected in the mapping file, ' +\\r\\n ' %d does not match specified barcode length, %d. ' %\\r\\n (barcode_length_check[0], barcode_len) + 'To specify a barcode ' +\\r\\n 'length use -b golay_12 or -b hamming_8 for 12 and 8 base pair ' +\\r\\n 'golay or hamming codes respectively, or -b # where # is the ' +\\r\\n 'length of the barcode used. E.g. -b 4 for 4 base pair barcodes.')\\r\\n\\r\\n fasta_files = map(get_infile, fasta_files)\\r\\n qual_files = map(get_infile, qual_files)\\r\\n\\r\\n # Check fasta files valid format, no duplicate ids\\r\\n # and ids match between fasta and qual files\\r\\n all_fasta_ids = fasta_ids(fasta_files)\\r\\n all_qual_ids = fasta_ids(qual_files)\\r\\n if qual_files and (len(all_fasta_ids) != len(all_qual_ids)):\\r\\n f_ids = all_fasta_ids.difference(all_qual_ids)\\r\\n q_ids = all_qual_ids.difference(all_fasta_ids)\\r\\n raise ValueError(\\r\\n \\\"Found %d ids in fasta file not in qual file, %d ids in qual file not in fasta\\\" %\\r\\n (len(f_ids), len(q_ids)))\\r\\n\\r\\n for f in fasta_files:\\r\\n f.seek(0)\\r\\n if qual_files:\\r\\n for q in qual_files:\\r\\n q.seek(0)\\r\\n # Load quality scores\\r\\n qual_mappings = parse_qual_scores(qual_files)\\r\\n for q in qual_files:\\r\\n q.close()\\r\\n else:\\r\\n qual_mappings = {}\\r\\n\\r\\n # make filters\\r\\n filters = []\\r\\n # seq len filter depends on whether we're including the barcode, if\\r\\n # median_length_filtering turned on, no length filtering.\\r\\n if not median_length_filtering:\\r\\n if trim_seq_len:\\r\\n # This processing occurs before primer testing, will use largest\\r\\n # primer length to calculate lengths. the dict all_primers has\\r\\n # keys of each primer with the length of said primer as the value\\r\\n if disable_primer_check:\\r\\n primer_seq_len = 0\\r\\n else:\\r\\n primer_seq_len = max(all_primers.values())\\r\\n\\r\\n if barcode_type == \\\"variable_length\\\":\\r\\n barcode_len = max(barcode_length_check)\\r\\n\\r\\n trim = barcode_len + primer_seq_len\\r\\n filters.append(SeqQualBad(\\r\\n 'Length outside bounds of %s and %s' % (\\r\\n min_seq_len,\\r\\n max_seq_len),\\r\\n lambda id_, seq, qual:\\r\\n not (min_seq_len <= len(seq) - trim <= max_seq_len)))\\r\\n else:\\r\\n filters.append(SeqQualBad(\\r\\n 'Length outside bounds of %s and %s' % (\\r\\n min_seq_len,\\r\\n max_seq_len),\\r\\n lambda id_, seq, qual: not (min_seq_len <= len(seq) <= max_seq_len)))\\r\\n\\r\\n if not truncate_ambi_bases:\\r\\n filters.append(SeqQualBad(\\r\\n 'Num ambiguous bases exceeds limit of %s' % max_ambig,\\r\\n lambda id_, seq, qual: count_ambig(seq) > max_ambig))\\r\\n\\r\\n if qual_mappings:\\r\\n filters.append(QualMissing)\\r\\n filters.append(SeqQualBad(\\r\\n 'Mean qual score below minimum of %s' % min_qual_score,\\r\\n lambda id_, seq, qual: mean(qual) < min_qual_score))\\r\\n \\\"\\\"\\\"if qual_score_window:\\r\\n filters.append(SeqQualBad('Mean window qual score below '+\\\\\\r\\n 'minimum of %s' % min_qual_score,\\r\\n lambda id_, seq, qual: \\\\\\r\\n not check_window_qual_scores(qual, qual_score_window, \\\\\\r\\n min_qual_score))) \\\"\\\"\\\"\\r\\n\\r\\n # Changed this to check entire sequence after barcode-could cause issue\\r\\n # if barcode-linker-primer have long homopolymers though.\\r\\n filters.append(SeqQualBad(\\r\\n 'Max homopolymer run exceeds limit of %s' % max_homopolymer,\\r\\n lambda id_, seq, qual: seq_exceeds_homopolymers(\\r\\n seq[barcode_len:], max_homopolymer)))\\r\\n\\r\\n # Check seqs and write out\\r\\n fasta_out = open(dir_prefix + '/' + 'seqs.fna.tmp', 'w+')\\r\\n if record_qual_scores:\\r\\n qual_out = open(dir_prefix + '/' + 'seqs_filtered.qual', 'w+')\\r\\n else:\\r\\n qual_out = False\\r\\n\\r\\n '''log_stats, pre_lens, post_lens = check_seqs(fasta_out, fasta_files,\\r\\n starting_ix, valid_map, qual_mappings, filters, barcode_len,\\r\\n primer_seq_len, keep_primer, keep_barcode, barcode_type, max_bc_errors,\\r\\n retain_unassigned_reads) '''\\r\\n log_stats, raw_lens, pre_lens, post_lens = check_seqs(fasta_out,\\r\\n fasta_files, starting_ix, valid_map, qual_mappings, filters,\\r\\n barcode_len, keep_primer, keep_barcode, barcode_type, max_bc_errors,\\r\\n retain_unassigned_reads, attempt_bc_correction,\\r\\n primer_seqs_lens, all_primers, max_primer_mm, disable_primer_check,\\r\\n reverse_primers, rev_primers, qual_out, qual_score_window,\\r\\n discard_bad_windows, min_qual_score, min_seq_len,\\r\\n median_length_filtering, added_demultiplex_field,\\r\\n reverse_primer_mismatches, truncate_ambi_bases)\\r\\n\\r\\n # Write log file\\r\\n log_file = open(dir_prefix + '/' + \\\"split_library_log.txt\\\", 'w+')\\r\\n log_file.write('\\\\n'.join(log_stats))\\r\\n log_file.close()\\r\\n\\r\\n # Write sequence distros here\\r\\n histogram_file = open(dir_prefix + '/' + 'histograms.txt', 'w+')\\r\\n\\r\\n histogram_file.write(format_histograms\\r\\n (*make_histograms(raw_lens, pre_lens, post_lens)))\\r\\n histogram_file.close()\",\n \"def coding_strand_to_AA(dna):\\n s = \\\"\\\"\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitialize empty list\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n for i in range(0, len(dna)-2, 3):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# for range of length of dna, indexes w/ step 3 (to isolate codons)\\n \\t\\tamino_acid = aa_table[dna[i:i+3]]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# translates each codon to an amino acid\\n \\t\\ts = s + amino_acid \\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# adds amino acid to list\\n return s \\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns list of amino acids\",\n \"def test_ModelDnaCodonSequence(self):\\n d = ArrayDnaCodonSequence(\\\"UUUCGU\\\")\\n self.assertEqual(str(d), \\\"TTTCGT\\\")\\n self.assertEqual(d._data, array([0, 28]))\\n self.assertEqual(str(d.to_rna()), \\\"UUUCGU\\\")\\n self.assertEqual(str(d.to_dna()), \\\"TTTCGT\\\")\",\n \"def _GetPseudoAAC(ProteinSequence,lamda=10,weight=0.05):\\n\\tres={}\\n\\tres.update(_GetPseudoAAC1(ProteinSequence,lamda=lamda,weight=weight))\\n\\tres.update(_GetPseudoAAC2(ProteinSequence,lamda=lamda,weight=weight))\\n\\treturn res\",\n \"def GetPseudoAAC1(ProteinSequence,lamda=30,weight=0.05,AAP=[_Hydrophobicity,_hydrophilicity]):\\n\\trightpart=0.0\\n\\tfor i in range(lamda):\\n\\t\\trightpart=rightpart+GetSequenceOrderCorrelationFactor(ProteinSequence,i+1,AAP)\\n\\tAAC=GetAAComposition(ProteinSequence)\\n\\t\\n\\tresult={}\\n\\ttemp=1+weight*rightpart\\n\\tfor index,i in enumerate(AALetter):\\n\\t\\tresult['PAAC'+str(index+1)]=round(AAC[i]/temp,3)\\n\\t\\n\\treturn result\",\n \"def produce_proteinSeq_dict (inPath, outPath):\\n s = list(SeqIO.parse(str(inPath), 'fasta'))\\n proteinSeq = {}\\n for _, elm in enumerate(s):\\n proteinSeq[elm.id] = str(elm.seq)\\n with open(outPath, 'wb') as fOut:\\n pickle.dump(proteinSeq, fOut)\",\n \"def reconstruct_seq_centered(seq, nucleosome_pos):\\n\\n # equivalence\\n d_nucleotide = {0: 1, # 'A',\\n 1: 0, # 'C',\\n 2: 1, # 'T',\\n 3: 0, # 'G'\\n }\\n\\n seqd = np.vectorize(d_nucleotide.get)(seq)\\n array_nuc = []\\n\\n # select only the nucleosome positions\\n for pos in nucleosome_pos:\\n array_nuc.append(seqd[pos - 58:pos + 59])\\n\\n # do the stack\\n center_nucleosome = np.sum(array_nuc, axis=0) / len(array_nuc)\\n\\n return center_nucleosome\",\n \"def codon_table_to_codon_map(codon_table: dict, deterministic: bool = True) -> Callable[[SeqLike], SeqLike]:\\n\\n def backtranslator(seq):\\n if seq._type != \\\"AA\\\":\\n raise TypeError(\\\"Sequence must be an AA SeqLike!\\\")\\n seq_str = seq.to_str()\\n\\n nt = \\\"\\\"\\n for aa in seq_str:\\n codons, probs = zip(*codon_table[aa].items())\\n\\n # we normalize the probabilities\\n # most tables are near 1.0, but issues with precision exist\\n sum_prob = sum(probs)\\n probs = [p / sum_prob for p in probs]\\n\\n if deterministic:\\n nt += codons[0]\\n else:\\n nt += np.random.choice(codons, p=probs)\\n\\n new_seqlike = SeqLike(\\n nt,\\n id=seq.id,\\n name=seq.name,\\n description=seq.description,\\n annotations=seq.annotations,\\n dbxrefs=seq.dbxrefs,\\n seq_type=\\\"dna\\\",\\n codon_map=seq.codon_map,\\n )\\n new_seqlike._aa_record = deepcopy(seq._aa_record)\\n return new_seqlike\\n\\n return backtranslator\",\n \"def make_codon_pos_align(aln):\\n\\n def func(seq):\\n dct = {-1: \\\"-\\\",\\n 0: \\\"0\\\",\\n 1: \\\"1\\\",\\n 2: \\\"2\\\"}\\n return \\\"\\\".join(util.mget(dct, mark_codon_pos(seq)))\\n return mapalign(aln, valfunc=func)\",\n \"def getValidityOfResiduesInSequence(self, seq):\\n seqList = list(seq)\\n aSpotted_Index = -1\\n aSpotted_residue = \\\"\\\"\\n if self.aligntIsDna:\\n _alphabet = self.DNA_ALPHABET\\n else:\\n _alphabet = self.PROTEIN_ALPHABET\\n # iterate over the sequence given the prior knowldege of the user\\n for i in range(len(seqList)):\\n residue = seqList[i]\\n if str.upper(residue) not in list(_alphabet):\\n aSpotted_Index = i\\n aSpotted_residue = residue\\n break\\n rv = {\\n \\\"residueIndex\\\": aSpotted_Index,\\n \\\"residue\\\": aSpotted_residue,\\n \\\"recognizedAlphabet\\\": self.VALID_DNA_OR_PROTEIN\\n }\\n if (aSpotted_residue != \\\"\\\"):\\n if self.aligntIsDna:\\n rv[\\\"recognizedAlphabet\\\"] = self.INVALID_DNA\\n else:\\n rv[\\\"recognizedAlphabet\\\"] = self.INVALID_PROTEIN\\n return(rv)\",\n \"def _GetPseudoAAC1(ProteinSequence,lamda=10,weight=0.05):\\n\\trightpart=0.0\\n\\tfor i in range(lamda):\\n\\t\\trightpart=rightpart+_GetSequenceOrderCorrelationFactor(ProteinSequence,k=i+1)\\n\\tAAC=GetAAComposition(ProteinSequence)\\n\\t\\n\\tresult={}\\n\\ttemp=1+weight*rightpart\\n\\tfor index,i in enumerate(AALetter):\\n\\t\\tresult['PAAC'+str(index+1)]=round(AAC[i]/temp,3)\\n\\t\\n\\treturn result\",\n \"def extract_seq_from_structure(self, struct):\\n ppb = PPBuilder() # Polypeptide builder object\\n aa_seqs = []\\n chains = struct.get_chains()\\n for pp in ppb.build_peptides(struct):\\n seq = pp.get_sequence()\\n aa_seqs.append(str(seq))\\n chain_aa_map = [[chain.id, aa_seqs[index]] for index, chain in enumerate(chains)]\\n return chain_aa_map\",\n \"def GetAAComposition(ProteinSequence):\\n\\tLengthSequence=len(ProteinSequence)\\n\\tResult={}\\n\\tfor i in AALetter:\\n\\t\\tResult[i]=round(float(ProteinSequence.count(i))/LengthSequence*100,3)\\n\\treturn Result\",\n \"def cpos2codon(self, cpos):\\n self.ensure_seq()\\n cpos = int(cpos)\\n if self.strand == \\\"+\\\":\\n np = []\\n for beg, end in self.exons:\\n np += list(range(max(beg, self.cds_beg),\\n min(self.cds_end, end)+1))\\n assert len(np) == len(self.seq)\\n\\n ni = cpos*3\\n if ni <= len(np):\\n codon = Codon()\\n codon.index = cpos\\n codon.locs = tuple(np[ni-3:ni])\\n codon.gene = self.gene\\n codon.chrm = self.chrm\\n codon.strand = self.strand\\n codon.seq = self.seq[ni-3:ni]\\n return codon\\n else:\\n raise IncompatibleTranscriptError('invalid_cDNA_position_%d;expect_[0_%d]' % (ni, len(np)))\\n else:\\n np = []\\n for beg, end in reversed(self.exons):\\n np += list(range(min(self.cds_end, end),\\n max(beg, self.cds_beg)-1,-1))\\n assert len(np) == len(self.seq)\\n\\n ni = cpos*3\\n if ni <= len(np):\\n codon = Codon()\\n codon.index = cpos\\n codon.locs = tuple(reversed(np[ni-3:ni]))\\n codon.gene = self.gene\\n codon.chrm = self.chrm\\n codon.strand = self.strand\\n codon.seq = self.seq[ni-3:ni]\\n return codon\\n else:\\n raise IncompatibleTranscriptError('invalid_cDNA_position_%d;expect_[0_%d]' % (ni, len(np)))\",\n \"def alignprotein(self, sample, analysistype, target, program, index, hit):\\n # Initialise lists to store the outputs\\n if target not in sample[analysistype].dnaseq:\\n sample[analysistype].dnaseq[target] = list()\\n sample[analysistype].protseq[target] = list()\\n sample[analysistype].ntalign[target] = list()\\n sample[analysistype].ntindex[target] = list()\\n sample[analysistype].aaidentity[target] = list()\\n sample[analysistype].aaalign[target] = list()\\n sample[analysistype].aaindex[target] = list()\\n # Only BLASTn analyses require additional effort to find the protein sequence\\n if program == 'blastn':\\n # Convert the extracted, properly-oriented DNA sequence to a Seq object\\n sample[analysistype].dnaseq[target].append(Seq(hit['query_sequence']))\\n # Create the BLAST-like interleaved outputs with the query and subject sequences\\n sample[analysistype].ntalign[target].append(self.interleaveblastresults(query=hit['query_sequence'],\\n subject=hit['subject_sequence']))\\n # Determine the number and position of SNPs\\n count = 0\\n ntindex = str()\\n # Iterate through every position in the query sequence, and determine if the subject sequence at that\\n # position is a match\\n for i, bp in enumerate(hit['query_sequence']):\\n # If the sequence at the query and subject sequences do not match, store the location\\n if bp != hit['subject_sequence'][i]:\\n # Append the current location (+1 due to zero indexing)\\n ntindex += '{i};'.format(i=i + 1)\\n # Increment the count by the length of the current position - should make the output more\\n # uniform due to the fact that the numbers are not padded\\n count += len(str(i))\\n # If there are many SNPs, then insert line breaks for every 15+ characters\\n if count >= 15:\\n ntindex += '\\\\n'\\n # Reset the character count to 0\\n count = 0\\n # Remove trailing ';' (or ';' followed by a newline)\\n ntindex = ntindex.rstrip(';').replace(';\\\\n', '\\\\n') if ntindex else '-'\\n # Add the cleaned string to the list\\n sample[analysistype].ntindex[target].append(ntindex)\\n # Convert the target name to a string without illegal characters - necessary for creating the\\n # temporary databases below\\n clean_target = ''.join(filter(str.isalnum, target))\\n # Set the absolute path, and create the tmp working directory\\n tmp_dir = os.path.join(sample[analysistype].reportdir, 'tmp')\\n make_path(tmp_dir)\\n # Set the absolute path of the FASTA file that will store the subject sequence. Will be used as the\\n # database in the tblastx analysis used to translate the query and subject sequence to amino acid\\n tmp_subject = os.path.join(tmp_dir, '{sn}_{target}_{at}_db_{index}.fa'\\n .format(sn=sample.name,\\n target=clean_target,\\n at=analysistype,\\n index=index))\\n # Write the appropriately-converted subject sequence to the database file\\n with open(tmp_subject, 'w') as tmp_db:\\n SeqIO.write(SeqRecord(Seq(hit['subject_sequence'].replace('-', '')),\\n id='{}_{}'.format(sample.name, target),\\n description=''), tmp_db, 'fasta')\\n # Create a BLAST database from this file\\n self.makeblastdb(fasta=tmp_subject)\\n # Create the tblastx (translated nt query: translated nt subject) call. Remove any masking. Do not\\n # include the 'query' parameter, as it will be supplied below\\n tblastx = NcbitblastxCommandline(db=os.path.splitext(tmp_subject)[0],\\n evalue=0.1,\\n outfmt=15,\\n soft_masking=False,\\n seg='no')\\n # Run the tblastx analysis. Supply the query as stdin. Capture stdout, and stderr\\n stdout, stderr = tblastx(stdin=sample[analysistype].targetsequence[target][index].replace('-', ''))\\n # Convert the string stdout to JSON format\\n json_output = json.loads(stdout)\\n # Extract the necessary list of HSPs from the JSON-formatted outputs\\n data = json_output['BlastOutput2'][0]['report']['results']['search']['hits'][0]['hsps']\\n # Initialise a string to store the extracted amino acid subject sequence\\n ref_prot = str()\\n for results in data:\\n # Attempt to use hit_frame 1 - the .targetsequence attribute was populated with the nt sequence in\\n # (hopefully) the correct orientation, so attempt to use that\\n if results['hit_frame'] == 1:\\n # Populate the .protseq attribute with the Seq-converted amino acid sequence extracted from the\\n # report\\n sample[analysistype].protseq[target].append(Seq(results['qseq'].upper()))\\n # Grab the subject sequence\\n ref_prot = results['hseq']\\n # Only the first result is required\\n break\\n # If there were no results with the hit_frame equal to 1, get the best result from the analysis\\n if not ref_prot:\\n for results in data:\\n sample[analysistype].protseq[target].append(Seq(results['qseq'].upper()))\\n ref_prot = results['hseq']\\n break\\n # Clear out the tmp directory\\n try:\\n shutil.rmtree(tmp_dir)\\n except FileNotFoundError:\\n pass\\n else:\\n # Non-blastn analyses will already have the outputs as amino acid sequences. Populate variables as required\\n ref_prot = hit['subject_sequence']\\n sample[analysistype].protseq[target].append(Seq(hit['query_sequence']))\\n # Create the BLAST-like alignment of the amino acid query and subject sequences\\n sample[analysistype].aaalign[target]\\\\\\n .append(self.interleaveblastresults(query=sample[analysistype].protseq[target][index],\\n subject=ref_prot))\\n # Determine the number of matches, as well as the number and location of mismatches\\n count = 0\\n matches = 0\\n aaindex = str()\\n # Iterate through the query sequence to determine matching positions\\n for i, bp in enumerate(sample[analysistype].protseq[target][index]):\\n if bp != ref_prot[i]:\\n aaindex += '{i};'.format(i=i + 1)\\n count += len(str(i))\\n # If there are many SNPs, then insert line breaks for every 10 SNPs\\n if count >= 15:\\n aaindex += '\\\\n'\\n count = 0\\n # Increment the total number of matches\\n if bp == ref_prot[i]:\\n matches += 1\\n # Clean the index string\\n aaindex = aaindex.rstrip(';').replace(';\\\\n', '\\\\n') if aaindex else '-'\\n # Append the cleaned string to the list\\n sample[analysistype].aaindex[target].append(aaindex)\\n # Determine percent identity between the query and subject amino acid sequence by dividing the number of\\n # matches by the total length of the query sequence and multiplying this result by 100. Convert to two\\n # decimal places\\n pid = float('{:.2f}'.format(matches / len(sample[analysistype].protseq[target][index]) * 100))\\n # Append the calculated percent identity to the list\\n sample[analysistype].aaidentity[target].append(pid)\\n return sample\",\n \"def computeProbs(psDf, add_masked_seqs=True, filterOut=False, max_cdr3_length=30, allow_stop_codons=False, allow_X=False):\\n \\n out = []\\n for rowi, row in psDf.iterrows():\\n \\\"\\\"\\\"If iterrows is slow there are potentially ways to speed this up using psDf.apply()\\\"\\\"\\\"\\n vals = {}\\n vals['ind'] = rowi\\n \\n if filterOut:\\n fo = filterOutRow(row,\\n max_cdr3_length=max_cdr3_length,\\n allow_stop_codons=allow_stop_codons,\\n allow_X=allow_X)\\n if fo:\\n \\\"\\\"\\\"vals will be missing keys, which will be assigned Nan in outDf\\\"\\\"\\\"\\n continue\\n \\n aprob_nucseq, aprob_protseq = samplerProb(row, 'a')\\n va_rep_prob, ja_rep_prob = rearrangementProb(row, 'a')\\n \\n vals['a_protseq_prob' ] = aprob_protseq * va_rep_prob * ja_rep_prob\\n vals['cdr3a_protseq_prob'] = aprob_protseq\\n vals['va_rep_prob' ] = va_rep_prob\\n vals['ja_rep_prob' ] = ja_rep_prob\\n vals['a_nucseq_prob' ] = aprob_nucseq * va_rep_prob * ja_rep_prob\\n \\n bprob_nucseq, bprob_protseq = samplerProb(row, 'b')\\n vb_rep_prob, jb_rep_prob = rearrangementProb(row, 'b')\\n \\n vals['b_protseq_prob' ] = bprob_protseq * vb_rep_prob * jb_rep_prob\\n vals['cdr3b_protseq_prob'] = bprob_protseq\\n vals['vb_rep_prob' ] = vb_rep_prob\\n vals['jb_rep_prob' ] = jb_rep_prob\\n vals['b_nucseq_prob' ] = bprob_nucseq * vb_rep_prob * jb_rep_prob\\n \\n if add_masked_seqs:\\n cdr3a_protseq_masked, ita, cdr3a_new_nucseq = getMaskedSeqs(row, 'a')\\n cdr3b_protseq_masked, itb, cdr3b_new_nucseq = getMaskedSeqs(row, 'b')\\n\\n vals[ 'cdr3a_protseq_masked'] = cdr3a_protseq_masked\\n vals[ 'a_indels'] = ita\\n vals[ 'cdr3a_new_nucseq' ] = cdr3a_new_nucseq\\n vals[ 'cdr3b_protseq_masked'] = cdr3b_protseq_masked\\n vals[ 'b_indels'] = itb\\n vals[ 'cdr3b_new_nucseq' ] = cdr3b_new_nucseq\\n out.append(vals)\\n \\n outDf = pd.DataFrame(out).set_index('ind')\\n assert outDf.shape[0] == psDf.shape[0]\\n return outDf\",\n \"def calc_conservation(aln):\\n\\n length = len(aln.values()[0])\\n seqs = aln.values()\\n percids = []\\n\\n # find identity positions\\n for i in xrange(length):\\n chars = util.hist_dict(util.cget(seqs, i))\\n if \\\"-\\\" in chars:\\n del chars[\\\"-\\\"]\\n\\n if len(chars) == 0:\\n percids.append(0.0)\\n else:\\n pid = max(chars.values()) / float(len(aln))\\n percids.append(pid)\\n return percids\",\n \"def filter_aligned_codons(aln):\\n\\n ind = find_aligned_codons(aln)\\n return subalign(aln, ind)\",\n \"def translate_DNA(dnaseq):\\n\\n gen = aa_generator_DNA(dnaseq)\\n seq = ''\\n aa = next(gen, None)\\n while aa:\\n seq += aa\\n aa = next(gen, None)\\n return seq\",\n \"def get_seq(peaks_df, genome, width):\\n vals = []\\n peaks_used = []\\n for i, r in peaks_df.iterrows():\\n sequence = str(genome[r['chr']][(r['start']+r['summit'] - width//2):(r['start'] + r['summit'] + width//2)])\\n if len(sequence) == width:\\n vals.append(sequence)\\n peaks_used.append(True)\\n else:\\n peaks_used.append(False)\\n\\n return one_hot.dna_to_one_hot(vals), np.array(peaks_used)\",\n \"def create_protein_sequences_table(self,fn_proteins_fasta_file):\\n log.info(\\\"Creating table of protein sequences ...\\\")\\n self.create_table(self.SequenceTable,self.SequenceFields,\\n self.SequenceTypes)\\n parser = SeqIO.parse(fn_proteins_fasta_file, \\\"fasta\\\")\\n data = []\\n n_stored = 0\\n chunk_size = 1000\\n for seq_record in parser:\\n description = seq_record.description\\n m = re.match(self.protein_record_pattern,description)\\n gene_id = m.group(1)\\n locus_tag = m.group(2)\\n protein_description = m.group(3)\\n table_record = [gene_id, locus_tag, protein_description, seq_record.seq.tostring()]\\n data.append(table_record)\\n # store chunks of data\\n if len(data) > chunk_size:\\n self.store_data(self.SequenceTable,data)\\n n_stored += chunk_size\\n log.info(\\\"Stored %20d sequences\\\\r\\\",n_stored)\\n data = [] # empty data to avoid using a lot of memory\\n # store last chunk\\n if len(data) > 0:\\n n_stored += len(data)\\n self.store_data(self.SequenceTable,data)\\n log.info(\\\"Stored %20d sequences\\\\r\\\",n_stored)\",\n \"def codonify(strand: str) -> list:\\n\\n # Loops through the whole string and slices every set of three characters into\\n # the list codons\\n codons = [strand[index : index + len_codon] for index in range(0,len(strand),len_codon)]\\n return codons\",\n \"def readPairedSequences(organism, paired_seqs_file):\\n\\n raw = pd.read_csv(paired_seqs_file, delimiter='\\\\t')\\n \\\"\\\"\\\"E.g. ['a', 'b']\\\"\\\"\\\"\\n chains = [s.split('_')[0] for s in raw.columns if s.find('nucseq') > 0]\\n \\n out = []\\n for c in chains:\\n out.append(raw.apply(lambda row: processNT(organism, c.upper(), row['%s_nucseq' % c], row['%s_quals' % c]).to_series(), axis=1))\\n\\n otherCols = [c for c in raw.columns if c.find('nucseq') == -1 and c.find('quals') == -1]\\n out = [raw[otherCols]] + out\\n psDf = pd.concat(out, axis=1)\\n psDf.loc[:, 'organism'] = organism\\n return psDf\",\n \"def parse_wt_sequences(wt_dna_fasta):\\n with open(wt_dna_fasta, 'r') as f:\\n sequence_generator_obj = SeqIO.parse(f, 'fasta', IUPAC.unambiguous_dna)\\n sequences = []\\n for sequence_obj in sequence_generator_obj:\\n sequences.append(sequence_obj.seq.upper())\\n assert len(sequences) == 1, 'Only one wild type dna sequence can be present in the wild type dna fasta file'\\n wt_dna_seq = sequences[0]\\n if wt_dna_seq.translate().find('*') == -1:\\n raise Exception(\\\"Stop codon not found in wild type sequence\\\")\\n elif (len(wt_dna_seq)) / 3 != (wt_dna_seq.translate().find('*') + 1):\\n raise Exception(\\\"Premature stop codon found in wild type sequence\\\")\\n\\n native_protein_dict = {}\\n for i in range(3, len(wt_dna_seq) + 1, 3):\\n if not (i / 3) in native_protein_dict:\\n native_protein_dict[i / 3] = ()\\n native_protein_dict[i / 3] = (wt_dna_seq[i - 3:i].translate(), wt_dna_seq[i - 3:i])\\n return wt_dna_seq, native_protein_dict\",\n \"def guess_align(aln):\\n \\n if \\\"pep\\\" in [guess_seq(seq) for seq in aln.itervalues()]:\\n return \\\"pep\\\"\\n else:\\n return \\\"dna\\\"\",\n \"def main(fileToCheck, minLength=-1, maxLength=-1):\\n\\n # Initialise variables.\\n lineCount = 1 # The number of the line being examined. Used for displaying error messages.\\n protDescription = True # Whether or not we are currently expecting a line starting with >.\\n firstLine = True # Whether or not we are currently examining the first line of the file.\\n proteinsInFile = {} # A dictionary indexed by the protein description line of the FASTA file.\\n # The value of each entry is the correctly formatted protein sequence corresponding to the index.\\n\\n # Strip off all excess whitespace, and split the string into the individual lines of the file.\\n checking = fileToCheck.rstrip()\\n checking = checking.lstrip()\\n checking = checking.split('\\\\n')\\n for line in checking:\\n line = line.rstrip()\\n if firstLine:\\n # True if we have just started parsing the file string, and haven;t yet examined any lines.\\n if line[0] == '>':\\n currentProt = line # Record the description line of the protein which is about to have its sequence inspected.\\n currentSeq = '' # Initialise the sequence of the protein.\\n protDescription = False # We are now expecting a protein sequence, not a protein description.\\n firstLine = False\\n else:\\n # The first line of the file MUST be a protein description line (i.e. start with '>'). If the line was not\\n # the beginning of a protein record, terminate the program.\\n errorMessage = \\\"Expected line \\\" + str(lineCount) + \\\" to start with a >, but instead got: \\\" + line\\n return 1, errorMessage\\n elif protDescription:\\n # This is true only if a line beginning with a '>' is expected.\\n if line[0] == '>':\\n # Expected a protein description line, and found a protein description line. This means that the entire sequence\\n # of the currentProt protein has been found (i.e. we have finished inspecting the sequence of a protein, and\\n # have found the protein to be valid). Now determine if the length of the sequence is within the user\\n # specified bounds.\\n if minLength == -1:\\n if maxLength == -1:\\n # If there are no restrictions on the protein sequence length, then record the protein and its sequence.\\n proteinsInFile[currentProt] = currentSeq\\n elif len(currentSeq) <= maxLength:\\n # If there is no minimum length restriction, and the protein sequence is not longer than the maximum\\n # sequence length permitted, then record the protein and its sequence.\\n proteinsInFile[currentProt] = currentSeq\\n elif len(currentSeq) >= minLength:\\n if maxLength == -1:\\n # If there is no maximum length restriction, and the protein sequence is not shorter than the minimum\\n # sequence length permitted, then record the protein and its sequence.\\n proteinsInFile[currentProt] = currentSeq\\n elif len(currentSeq) <= maxLength:\\n # If the protein sequence is not shorter than the minimum sequence length permitted and not longer\\n # than the maximum length permitted, then record the protein and its sequence.\\n proteinsInFile[currentProt] = currentSeq\\n currentProt = line # Record the description line of the protein which is about to have its sequence inspected.\\n currentSeq = '' # Initialise the sequence of the protein.\\n protDescription = False # We are now expecting a protein sequence, not a protein description.\\n else:\\n # If the line does not begin with a '>', and it is expected to, it is possible that the amino acid sequence\\n # is split over multiple lines.\\n if line.isalpha():\\n # If every character on the line is a letter, then the line contains a valid portion of the sequence.\\n # Add the uppercase version of the sequence portion to the sequence currently being recorded.\\n currentSeq += line.upper()\\n else:\\n # If the line did not contain only letters, terminate the program.\\n errorMessage = \\\"Expected line \\\" + str(lineCount) + \\\" to start with a >, but instead got: \\\" + line\\n return 1, errorMessage\\n else:\\n # If an amino acid sequence is expected.\\n if line.isalpha():\\n # If the line is all alphabetic characters, write the line out and indicate that we are expecting a\\n # protein description line next (i.e. one beginning with a '>').\\n currentSeq += line.upper()\\n protDescription = True\\n else:\\n # If the line did not contain only letters, terminate the program.\\n errorMessage = \\\"Expected line \\\" + str(lineCount) + \\\" to contain only letters, but instead got: \\\" + line\\n return 2, errorMessage\\n\\n lineCount += 1\\n\\n # Catch the final protein from the file, and determine whether it should be recorded.\\n if minLength == -1:\\n if maxLength == -1:\\n proteinsInFile[currentProt] = currentSeq\\n elif len(currentSeq) <= maxLength:\\n proteinsInFile[currentProt] = currentSeq\\n elif len(currentSeq) >= minLength:\\n if maxLength == -1:\\n proteinsInFile[currentProt] = currentSeq\\n elif len(currentSeq) <= maxLength:\\n proteinsInFile[currentProt] = currentSeq\\n\\n if len(proteinsInFile.keys()) < 2:\\n # There are too few protein sequences entered\\n errorMessage = (\\\"Not enough unique protein sequences have been entered.\\\" +\\n \\\" This is possibly caused by not enough sequences of the required minimum and maximum length being provided.\\\"\\n )\\n return 3, errorMessage\\n elif protDescription:\\n # Return an indication that the FASTA file is correctly formatted.\\n outputString = ''\\n for i in proteinsInFile.keys():\\n outputString += i + '\\\\n' + proteinsInFile[i] + '\\\\n'\\n return 0, outputString[:-1]\\n else:\\n # The file did not end with a protein sequence.\\n errorMessage = \\\"Reached the end of the file, but no protein sequence found for the final protein.\\\"\\n return 3, errorMessage\",\n \"def printEncodePep(self):\\r\\n for i in range(len(self.seq)):\\r\\n if self.seq[i:i+(len(self.peptide*3))] in self.allPepSeqs:\\r\\n print(self.seq[i:i+(len(self.peptide*3))]) # print peptide if DNA region matches a possible peptide\\r\\n return\",\n \"def count_variant(self, variant_dna, include_indels=True):\\n if not re.match(\\\"^[ACGTNXacgtnx]+$\\\", variant_dna):\\n raise ValueError(\\n \\\"Variant DNA sequence contains unexpected \\\"\\n \\\"characters [{}]\\\".format(self.name)\\n )\\n\\n variant_dna = variant_dna.upper()\\n\\n if len(variant_dna) != len(self.wt.dna_seq):\\n if self.aligner is not None:\\n mutations = self.align_variant(variant_dna)\\n else:\\n return None\\n else:\\n mutations = list()\\n for i in range(len(variant_dna)):\\n if variant_dna[i] != self.wt.dna_seq[i]:\\n mutations.append(\\n (\\n i,\\n \\\"{pre}>{post}\\\".format(\\n pre=self.wt.dna_seq[i], post=variant_dna[i]\\n ),\\n )\\n )\\n if len(mutations) > self.max_mutations:\\n if self.aligner is not None:\\n mutations = self.align_variant(variant_dna)\\n if len(mutations) > self.max_mutations:\\n # too many mutations post-alignment\\n return None\\n else:\\n # stop looping over this variant\\n break\\n else:\\n # too many mutations and not using aligner\\n return None\\n\\n mutation_strings = list()\\n if self.is_coding():\\n variant_protein = \\\"\\\"\\n for i in range(0, len(variant_dna), 3):\\n try:\\n variant_protein += CODON_TABLE[variant_dna[i : i + 3]]\\n except KeyError: # garbage codon due to indel, X, or N\\n variant_protein += \\\"?\\\"\\n\\n for pos, change in mutations:\\n ref_dna_pos = pos + self.wt.dna_offset + 1\\n ref_pro_pos = pos // 3 + self.wt.protein_offset + 1\\n mut = \\\"c.{pos}{change}\\\".format(pos=ref_dna_pos, change=change)\\n if has_indel(change):\\n mut += \\\" (p.{pre}{pos}fs)\\\".format(\\n pre=AA_CODES[self.wt.protein_seq[pos // 3]], pos=ref_pro_pos\\n )\\n elif variant_protein[pos // 3] == self.wt.protein_seq[pos // 3]:\\n mut += \\\" (p.=)\\\"\\n else:\\n mut += \\\" (p.{pre}{pos}{post})\\\".format(\\n pre=AA_CODES[self.wt.protein_seq[pos // 3]],\\n pos=ref_pro_pos,\\n post=AA_CODES[variant_protein[pos // 3]],\\n )\\n mutation_strings.append(mut)\\n else:\\n for pos, change in mutations:\\n ref_dna_pos = pos + self.wt.dna_offset + 1\\n mut = \\\"n.{pos}{change}\\\".format(pos=ref_dna_pos, change=change)\\n mutation_strings.append(mut)\\n\\n if len(mutation_strings) > 0:\\n variant_string = \\\", \\\".join(mutation_strings)\\n else:\\n variant_string = WILD_TYPE_VARIANT\\n return variant_string\",\n \"def getRevCodonSeqs(self):\\r\\n compDict = {'A': 't', 'T': 'a', 'G': 'c', 'C': 'g'} # nuc compliments for reverse strand\\r\\n revPep = [] # list to hold the temporary reverse peptides before incorporation into the complete list\\r\\n for seq in self.allPepSeqs:\\r\\n revSeq = seq[::-1] # reverses the strand to be prepped for nt compliments\\r\\n for nuc in compDict:\\r\\n revSeq = revSeq.replace(nuc, compDict[nuc]) # replaces nt's with their compliments\\r\\n revSeq = revSeq.upper()\\r\\n revPep.append(revSeq)\\r\\n for i in revPep:\\r\\n self.allPepSeqs.append(i) # adds the reverse strand peptide to the list of possible peptide seqs\\r\\n return\",\n \"def gene_finder(dna):\\n viable_strings = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitialize empty list (for strings)\\n viable_amino_acids = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitialize empty list (for amino acids)\\n threshold = longest_ORF_noncoding(dna, 1500)\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# sets threshold to longest random dna string\\n real_dna = list(find_all_ORFs_both_strands(dna))\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# sets real_dna equal to all the ORFs, both strands\\n for i in range(len(real_dna)):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# searches through all the elements in list real_dna\\n \\tif len(real_dna[i]) > len(threshold):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# compares real string to random string\\n \\t\\tviable_strings.append(real_dna[i])\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if real string is longer, adds it to list\\n for i in range(len(viable_strings)):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# searches through all elements in viable_strings\\n \\ta = coding_strand_to_AA(viable_strings[i])\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# translates each string to amino acid sequence\\n \\tviable_amino_acids.append(a)\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# adds amino acids to list\\n return viable_amino_acids\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns list\",\n \"def handle_seq(seq, barcode_map, result_dict):\\n for i in range(len(seq)):\\n for barcode in barcode_map.keys():\\n possible_match = seq[i: i + len(barcode)]\\n if possible_match == barcode:\\n result_dict[barcode][i] += 1\",\n \"def _obtain_t_strand(self, protein):\\r\\n\\r\\n strand = [[], []]\\r\\n for amino_acid in protein:\\r\\n codon_chooser = base_maps[numpy.where(codons == amino_acid)]\\r\\n for index in range(3):\\r\\n strand[0].append(codon_chooser[0][index])\\r\\n if len(codon_chooser) > 1:\\r\\n strand[1].append(codon_chooser[1][index])\\r\\n else:\\r\\n strand[1].append(0)\\r\\n\\r\\n return numpy.array(strand)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.79057974","0.76611775","0.7121469","0.6961111","0.68622816","0.68331707","0.6547189","0.64678174","0.6421204","0.62824553","0.6257737","0.62457687","0.62001413","0.6168047","0.6160185","0.6150737","0.60523367","0.60273343","0.5976103","0.5961816","0.59389555","0.5912025","0.58708626","0.5860369","0.5761462","0.57120883","0.5679209","0.5629829","0.5542008","0.55359304","0.55285645","0.5525298","0.5495969","0.5469691","0.545937","0.5449023","0.54480946","0.5431368","0.5430303","0.54280376","0.53905547","0.5386233","0.5383803","0.53594226","0.53493655","0.5344777","0.534434","0.5343192","0.53431636","0.53361756","0.5332222","0.53138506","0.5292164","0.5282693","0.52778333","0.5269213","0.52425325","0.52405745","0.5229423","0.5220854","0.5211958","0.5209804","0.520127","0.51998293","0.5187987","0.5178068","0.51669246","0.51665425","0.5162269","0.5150969","0.5149532","0.5148913","0.5147401","0.51377225","0.5129953","0.51233125","0.51190484","0.5111797","0.5104564","0.5102446","0.50940144","0.50909644","0.50867033","0.50862813","0.50813997","0.5078073","0.5075784","0.50680196","0.50396955","0.5035808","0.5028574","0.50262964","0.50250936","0.5024102","0.5020154","0.5006196","0.5006144","0.49965453","0.49944142","0.49923646"],"string":"[\n \"0.79057974\",\n \"0.76611775\",\n \"0.7121469\",\n \"0.6961111\",\n \"0.68622816\",\n \"0.68331707\",\n \"0.6547189\",\n \"0.64678174\",\n \"0.6421204\",\n \"0.62824553\",\n \"0.6257737\",\n \"0.62457687\",\n \"0.62001413\",\n \"0.6168047\",\n \"0.6160185\",\n \"0.6150737\",\n \"0.60523367\",\n \"0.60273343\",\n \"0.5976103\",\n \"0.5961816\",\n \"0.59389555\",\n \"0.5912025\",\n \"0.58708626\",\n \"0.5860369\",\n \"0.5761462\",\n \"0.57120883\",\n \"0.5679209\",\n \"0.5629829\",\n \"0.5542008\",\n \"0.55359304\",\n \"0.55285645\",\n \"0.5525298\",\n \"0.5495969\",\n \"0.5469691\",\n \"0.545937\",\n \"0.5449023\",\n \"0.54480946\",\n \"0.5431368\",\n \"0.5430303\",\n \"0.54280376\",\n \"0.53905547\",\n \"0.5386233\",\n \"0.5383803\",\n \"0.53594226\",\n \"0.53493655\",\n \"0.5344777\",\n \"0.534434\",\n \"0.5343192\",\n \"0.53431636\",\n \"0.53361756\",\n \"0.5332222\",\n \"0.53138506\",\n \"0.5292164\",\n \"0.5282693\",\n \"0.52778333\",\n \"0.5269213\",\n \"0.52425325\",\n \"0.52405745\",\n \"0.5229423\",\n \"0.5220854\",\n \"0.5211958\",\n \"0.5209804\",\n \"0.520127\",\n \"0.51998293\",\n \"0.5187987\",\n \"0.5178068\",\n \"0.51669246\",\n \"0.51665425\",\n \"0.5162269\",\n \"0.5150969\",\n \"0.5149532\",\n \"0.5148913\",\n \"0.5147401\",\n \"0.51377225\",\n \"0.5129953\",\n \"0.51233125\",\n \"0.51190484\",\n \"0.5111797\",\n \"0.5104564\",\n \"0.5102446\",\n \"0.50940144\",\n \"0.50909644\",\n \"0.50867033\",\n \"0.50862813\",\n \"0.50813997\",\n \"0.5078073\",\n \"0.5075784\",\n \"0.50680196\",\n \"0.50396955\",\n \"0.5035808\",\n \"0.5028574\",\n \"0.50262964\",\n \"0.50250936\",\n \"0.5024102\",\n \"0.5020154\",\n \"0.5006196\",\n \"0.5006144\",\n \"0.49965453\",\n \"0.49944142\",\n \"0.49923646\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.53833807"},"document_rank":{"kind":"string","value":"43"}}},{"rowIdx":92991,"cells":{"query":{"kind":"string","value":"Unit tests for the coding_strand_to_AA function"},"document":{"kind":"string","value":"def coding_strand_to_AA_unit_tests():\n # list of [input, expected output]\n data_list = [\n # pass cases\n [\"ATGCGA\", \"MR\"],\n [\"ATGCCCGCTTT\", \"MPA\"],\n [\"AAA\", \"K\"],\n [\"TTT\", \"F\"],\n [\"CCC\", \"P\"],\n [\"GGG\", \"G\"],\n [\"AAAA\", \"K\"],\n [\"AAAAA\", \"K\"],\n [\"AAAAAA\", \"KK\"],\n [\"CTAGAGTCT\", \"LES\"],\n [\"TTCCTCATCCCG\", \"FLIP\"],\n [\"GGTGGA\", \"GG\"],\n [\"TGAACCCGTAACGCACCTTGG\", \"|TRNAPW\"],\n [\"AGGGCCATTAAT\", \"RAIN\"],\n [\"CCGGAGCCTAGTATA\", \"PEPSI\"],\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\" ,\n print \"expected output: \" + str(data[1]) + \",\",\n o = coding_strand_to_AA(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\""},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def coding_strand_to_AA_unit_tests():\n print \"input: GTTGACAGTACGTACAGGGAA, \"+\"output: \"+coding_strand_to_AA(\"GTTGACAGTACGTACAGGGAA\")+\", actual output: VDSTYRE\"\n print \"input: TTATTGCTTATTATCATG, \"+\"output: \"+coding_strand_to_AA(\"TTATTGCTTATTATCATG\")+\", actual output: LLLIIM\"\n print \"input: TTTTTAATTATGGTTTCTCCTACTGCTTATTAACATCAAAATAAAGATGAATGTTGGCGTGGT, \"+\"output: \"+coding_strand_to_AA(\"TTTTTAATTATGGTTTCTCCTACTGCTTATTAACATCAAAATAAAGATGAATGTTGGCGTGGT\")+\", actual output: FLIMVSPTAY|HQNKDECWRG\"\n print \"input: TT, \" + \"output: \"+coding_strand_to_AA(\"TT\")+\", actual output: ERROR: The provided fragment is too short to contain any codons.\"","def coding_strand_to_AA_unit_tests():\n input_a='ATTATTATT'\n expected_output='III'\n actual_output=coding_strand_to_AA(input_a)\n print 'Expected Output is ' + expected_output\n print 'Actual Output is ' +actual_output\n \n input_a='ATGATGATT'\n expected_output='MMI'\n actual_output=coding_strand_to_AA(input_a)\n print 'Expected Output is ' + expected_output\n print 'Actual Output is ' +actual_output\n \n # YOUR IMPLEMENTATION HERE","def coding_strand_to_AA_unit_tests(dna, expected):\n print coding_strand_to_AA(\"ATGCGA\")\n print coding_strand_to_AA(\"ATGCCCGCTTT\")\n print coding_strand_to_AA(\"GGTAAA\")\n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + coding_strand_to_AA(dna)","def coding_strand_to_AA_unit_tests():\n # YOUR IMPLEMENTATION HERE\n input = [\"ATG\", \"ATGCEAFD\", \"FAS\"]\n expected_output = [\"MR\", \"RDS\", \"FF\"]\n actual = []\n for i in input:\n actual.append(coding_strand_to_AA(i))\n print input \n print actual\n print expected_output","def coding_strand_to_AA(dna):\n list1 = get_codons(dna)\n string = ''\n for codon in list1:\n try:\n string = string + aa_table[codon]\n except KeyError:\n continue\n return string","def coding_strand_to_AA(dna):\n coding_strand = ''\n for i in range(len(dna)/3):\n aa = dna[3*i:(3*i)+3]\n coding_strand += aa_table[aa]\n return coding_strand","def coding_strand_to_AA(dna):\n dna_codons = split_into_codons(dna)\n i = 0\n aa_string = ''\n while i < len(dna_codons):\n if len(dna_codons[i]) == 3:\n amino_acid = aa_table[dna_codons[i]]\n aa_string += amino_acid\n i += 1\n return aa_string","def coding_strand_to_AA(dna):\n l = len(dna)\n res = []\n for i in range(0, l, 3):\n s = dna[i: i + 3]\n for j in range(len(codons)):\n# for codon in codons[j]:\n# if codon == s:\n# res.append(aa[j])\n# break;\n if s in codons[j]: # [WOW] Python is really nice unlike C, yay!!\n res.append(aa[j])\n return collapse(res)","def coding_strand_to_AA(dna):\n #inital conditions\n protein = ''\n i = 0\n\n #for the length of DNA, translate each codon in an ORF to an amino acid\n while i < (len(dna)-2):\n codon = dna[i:i+3] \n amino_acid = aa_table[codon]\n protein= protein + amino_acid\n i += 3\n\n #return the string of amino acids\n return protein","def coding_strand_to_AA(dna):\n dnainp = dna\n protein = ''\n if len(dnainp)<3:\n return \"ERROR: The provided fragment is too short to contain any codons.\"\n# elif len(dnainp)%3 is not 0:\n# print \"Warning: The provided DNA fragment does not contain an integer number of codons. Excess bases were leftout.\"\n while len(dnainp) >=3:\n cod = dnainp[:3]\n for i in codons:\n for j in i:\n if j == cod:\n protein = protein + aa[codons.index(i)]\n dnainp = dnainp[3:]\n return protein","def coding_strand_to_AA(dna):\n Seq = ''\n for i in range(0,len(dna),3): \n triple = dna[i:i+3]\n print triple\n for k in range(len(codons)):\n if triple in codons[k]: \n print \"Casey Rocks\"\n print codons[k]\n amino = aa[k]\n Seq+=amino\n return Seq","def coding_strand_to_AA(dna):\n num_codons = int(len(dna)/3)\n num = 0\n list_codons = []\n aacids = ''\n while num < num_codons:\n num_start = int(num*3)\n num_end = int(num*3 + 3)\n list_codons.append(dna[num_start:num_end])\n num = num + 1\n for element in list_codons:\n thing = aa_table[element]\n aacids = aacids + thing\n return aacids","def coding_strand_to_AA(dna):\n amino_acid = ''\n i = 0\n while i + 3 < len(dna) + 1:\n amino_acid += aa_table[dna[i:i+3]]\n i += 3\n return amino_acid","def coding_strand_to_AA(dna):\n protein=''\n for i in range(0,len(dna),3):\n\t if dna[i:i+3] in aa_table.keys():\n\t \tprotein += aa_table[dna[i:i+3]]\n return protein","def test_fasta(self):\n aln2fasta = hhsuite.AlignmentToFasta()\n self.assertEqual(\n aln2fasta.fasta(self.hit, \"A-E----\"),\n \">Query\\nJKLMNOP\\n>Template\\nA-E----\\n\")","def coding_strand_to_AA(dna):\n amino_acid=\"\"\n for i in range(0, len(dna), 3):\n mycodon=dna[i:i+3]\n # print'this is my codon'\n #print mycodon\n for j in range(len(codons)):\n for k in range(len(codons[j])):\n #print codons[j][k]\n if codons[j][k] == mycodon:\n #print aa[j]\n amino_acid += aa[j]\n return amino_acid\n \n #step uno break apart string into groups of three\n #find sequence +find index\n #then connect to amino acids ","def coding_strand_to_AA(dna):\n s = \"\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitialize empty list\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n for i in range(0, len(dna)-2, 3):\t\t\t\t\t\t\t\t\t\t\t\t\t\t# for range of length of dna, indexes w/ step 3 (to isolate codons)\n \t\tamino_acid = aa_table[dna[i:i+3]]\t\t\t\t\t\t\t\t\t\t\t\t# translates each codon to an amino acid\n \t\ts = s + amino_acid \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# adds amino acid to list\n return s \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns list of amino acids","def test_to_dna(self):\n r = self.RNA(\"TCA\")\n self.assertEqual(str(r), \"UCA\")\n self.assertEqual(str(r.to_dna()), \"TCA\")","def test_conversion(self):\n r = self.RNA(\"TCAtu\")\n self.assertEqual(str(r), \"UCAUU\")\n\n d = self.DNA(\"UCAtu\")\n self.assertEqual(str(d), \"TCATT\")","def aa(seq):\n global codontable\n seq = seq.upper()\n if codontable is None:\n # TODO: figure out the right place for the pre-computed information here\n bases = ['T', 'C', 'A', 'G']\n codons = [a+b+c for a in bases for b in bases for c in bases]\n codons = codons + list(map(lambda x: x.lower(), codons))\n amino_acids = 'FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG'\n amino_acids = amino_acids + amino_acids.lower()\n codontable = dict(zip(codons, amino_acids))\n res = ''\n for i in range(0, len(seq) - 2, 3):\n res += codontable[seq[i:(i+3)]]\n return res","def get_aa (tRNA):\n\tpass","def test_amino_acid_slicing(self):\n chrom_result = [None, \"Y\", \"Y\", \"Y\", None, None, None]\n for i in xrange(len(chrom_result)):\n self.assertEqual(self.t.chromosome_coordinate_to_amino_acid(i, self.chrom_seq), chrom_result[i])\n cds_result = [\"Y\", \"Y\", \"Y\", None]\n for i in xrange(len(cds_result)):\n self.assertEqual(self.t.cds_coordinate_to_amino_acid(i, self.chrom_seq), cds_result[i])\n transcript_result = [None, \"Y\", \"Y\", \"Y\", None, None, None, None]\n for i in xrange(len(transcript_result)):\n self.assertEqual(self.t.transcript_coordinate_to_amino_acid(i, self.chrom_seq), transcript_result[i])","def test_to_fasta(self):\n even = \"TCAGAT\"\n odd = even + \"AAA\"\n even_dna = self.SEQ(even, name=\"even\")\n odd_dna = self.SEQ(odd, name=\"odd\")\n self.assertEqual(even_dna.to_fasta(), \">even\\nTCAGAT\\n\")\n # set line wrap to small number so we can test that it works\n self.assertEqual(even_dna.to_fasta(block_size=2), \">even\\nTC\\nAG\\nAT\\n\")\n self.assertEqual(odd_dna.to_fasta(block_size=2), \">odd\\nTC\\nAG\\nAT\\nAA\\nA\\n\")\n # check that changing the linewrap again works\n self.assertEqual(even_dna.to_fasta(block_size=4), \">even\\nTCAG\\nAT\\n\")","def test_to_fasta(self):\n even = \"TCAGAT\"\n odd = even + \"AAA\"\n even_dna = self.SequenceClass(even, name=\"even\")\n odd_dna = self.SequenceClass(odd, name=\"odd\")\n self.assertEqual(even_dna.to_fasta(), \">even\\nTCAGAT\\n\")\n # set line wrap to small number so we can test that it works\n self.assertEqual(even_dna.to_fasta(block_size=2), \">even\\nTC\\nAG\\nAT\\n\")\n self.assertEqual(odd_dna.to_fasta(block_size=2), \">odd\\nTC\\nAG\\nAT\\nAA\\nA\\n\")\n # check that changing the linewrap again works\n self.assertEqual(even_dna.to_fasta(block_size=4), \">even\\nTCAG\\nAT\\n\")","def test_to_rna(self):\n r = self.DNA(\"UCA\")\n self.assertEqual(str(r), \"TCA\")\n self.assertEqual(str(r.to_rna()), \"UCA\")","def translateORFtoAAs(self,sequence,number):\r\n AAStringfromORF = str()\r\n startingM = int()\r\n for i in range(0,len(sequence)-2,3):\r\n if sequence[i:i+3] != \"AUG\":\r\n pass\r\n else:\r\n startingM = i\r\n for i in range(startingM,len(sequence)-2,3):\r\n x = self.tabletoTranslate(sequence[i:i+3])\r\n AAStringfromORF+=x\r\n if x == \"-\":\r\n self.listofSequences.append(AAStringfromORF.rstrip(\"-\").lstrip().rstrip())\r\n AAStringfromORF = str()\r\n break","def main():\n\n args = get_args()\n seq = args.seq.upper()\n codon_to_aa = {\n 'AAA': 'K',\n 'AAC': 'N',\n 'AAG': 'K',\n 'AAU': 'N',\n 'ACA': 'T',\n 'ACC': 'T',\n 'ACG': 'T',\n 'ACU': 'T',\n 'AGA': 'R',\n 'AGC': 'S',\n 'AGG': 'R',\n 'AGU': 'S',\n 'AUA': 'I',\n 'AUC': 'I',\n 'AUG': 'M',\n 'AUU': 'I',\n 'CAA': 'Q',\n 'CAC': 'H',\n 'CAG': 'Q',\n 'CAU': 'H',\n 'CCA': 'P',\n 'CCC': 'P',\n 'CCG': 'P',\n 'CCU': 'P',\n 'CGA': 'R',\n 'CGC': 'R',\n 'CGG': 'R',\n 'CGU': 'R',\n 'CUA': 'L',\n 'CUC': 'L',\n 'CUG': 'L',\n 'CUU': 'L',\n 'GAA': 'E',\n 'GAC': 'D',\n 'GAG': 'E',\n 'GAU': 'D',\n 'GCA': 'A',\n 'GCC': 'A',\n 'GCG': 'A',\n 'GCU': 'A',\n 'GGA': 'G',\n 'GGC': 'G',\n 'GGG': 'G',\n 'GGU': 'G',\n 'GUA': 'V',\n 'GUC': 'V',\n 'GUG': 'V',\n 'GUU': 'V',\n 'UAA': 'Stop',\n 'UAC': 'Y',\n 'UAG': 'Stop',\n 'UAU': 'Y',\n 'UCA': 'S',\n 'UCC': 'S',\n 'UCG': 'S',\n 'UCU': 'S',\n 'UGA': 'Stop',\n 'UGC': 'C',\n 'UGG': 'W',\n 'UGU': 'C',\n 'UUA': 'L',\n 'UUC': 'F',\n 'UUG': 'L',\n 'UUU': 'F',\n }\n\n k = 3\n\n # 1: for loop\n # protein = ''\n # for codon in [seq[i:i + k] for i in range(0, len(seq), k)]:\n # aa = codon_to_aa.get(codon, '-')\n # if aa == 'Stop':\n # break\n # protein += aa\n\n # 2: list comprehension, slice to remove Stop\n # codons = [seq[i:i + k] for i in range(0, len(seq), k)]\n # aa = [codon_to_aa.get(codon, '-') for codon in codons]\n # if 'Stop' in aa:\n # aa = aa[:aa.index('Stop')]\n # print(''.join(aa))\n\n # 3: L.C. -> map(), slice -> takewhile\n # codons = map(lambda i: seq[i:i + k], range(0, len(seq), k))\n # aa = map(lambda codon: codon_to_aa.get(codon, '-'), codons)\n # print(''.join(takewhile(lambda c: c != 'Stop', aa)))\n\n # 4: combine map()\n # aa = map(lambda c: codon_to_aa.get(c, '-'),\n # map(lambda i: seq[i:i + k], range(0, len(seq), k)))\n # print(''.join(takewhile(lambda c: c != 'Stop', aa)))\n\n # 5: combine all\n # print(''.join(\n # takewhile(\n # lambda c: c != 'Stop',\n # map(lambda c: codon_to_aa.get(c, '-'),\n # map(lambda i: seq[i:i + k], range(0, len(seq), k))))))\n\n # 6: Seq\n print(str(Seq(args.seq).translate()).replace('*', ''))","def test_assign_seqs_two_fastas_quals(self):\r\n\r\n # Handles single fasta and single qual\r\n file_data = {}\r\n file_data['fasta_files'] = [self.valid_fasta_file_no_errors,\r\n self.valid_fasta_file_no_errors]\r\n file_data['qual_files'] = [self.valid_qual_file_no_errors,\r\n self.valid_qual_file_no_errors]\r\n file_data['demultiplexed_seqs_f'] = FakeOutFile()\r\n file_data['demultiplexed_qual_f'] = FakeOutFile()\r\n\r\n ids_bcs_added_field = {('AACTCGTCGATG', ''): 's1',\r\n ('AGCAGCACTTGT', ''): 's2', ('ACCGCAGAGTCA', ''): 's3'}\r\n bc_lens = [12]\r\n all_bcs = ['AACTCGTCGATG', 'AGCAGCACTTGT', 'ACCGCAGAGTCA']\r\n keep_barcode = False\r\n barcode_type = \"golay_12\"\r\n max_bc_errors = 1.5\r\n start_index = 1\r\n write_unassigned_reads = False\r\n disable_bc_correction = False\r\n added_demultiplex_field = None\r\n\r\n log_data, bc_freqs, seq_counts, corrected_bc_count =\\\r\n assign_seqs(file_data, ids_bcs_added_field, bc_lens, all_bcs,\r\n keep_barcode, barcode_type, max_bc_errors, start_index,\r\n write_unassigned_reads, disable_bc_correction,\r\n added_demultiplex_field)\r\n\r\n expected_demultiplexed_fasta_seq = '>s1_1 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\nCAGGACGAGACGAGGTT\\n>s3_2 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\nCCAGATTACGAGATTA\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\nGACCGATTACGATAACG\\n>s1_4 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\nCAGGACGAGACGAGGTT\\n>s3_5 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\nCCAGATTACGAGATTA\\n>s2_6 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\nGACCGATTACGATAACG\\n'\r\n expected_demultiplexed_qual_seq = '>s1_1 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\n30 26 11 11 29 20 19 16 24 17 29 28 11 27 14 24 24\\n>s3_2 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\n12 14 27 23 22 19 24 18 19 20 28 10 17 14 17 13\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\n10 20 16 20 25 27 22 28 16 22 16 18 12 13 16 25 17\\n>s1_4 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\n30 26 11 11 29 20 19 16 24 17 29 28 11 27 14 24 24\\n>s3_5 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\n12 14 27 23 22 19 24 18 19 20 28 10 17 14 17 13\\n>s2_6 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\n10 20 16 20 25 27 22 28 16 22 16 18 12 13 16 25 17\\n'\r\n self.assertEqual(file_data['demultiplexed_seqs_f'].data,\r\n expected_demultiplexed_fasta_seq)\r\n self.assertEqual(file_data['demultiplexed_qual_f'].data,\r\n expected_demultiplexed_qual_seq)\r\n\r\n expected_log_data = {'ACCGCAGAGTCA,s3': 2, 'AACTCGTCGATG,s1': 2,\r\n 'AGCAGCACTTGT,s2': 2}\r\n expected_bc_freqs = {'AACTCGTCGATG': 2, 'AGCAGCACTTGT': 2,\r\n 'ACCGCAGAGTCA': 2}\r\n expected_seq_counts = 6\r\n expected_corrected_bc_count = [0, 0]\r\n\r\n self.assertEqual(log_data, expected_log_data)\r\n self.assertEqual(bc_freqs, expected_bc_freqs)\r\n self.assertEqual(seq_counts, expected_seq_counts)\r\n self.assertEqual(corrected_bc_count, expected_corrected_bc_count)","def test_sort_fasta_by_abundance(self):\r\n class FakeOutF(object):\r\n\r\n def __init__(self):\r\n self.s = \"\"\r\n\r\n def write(self, s):\r\n self.s += s\r\n\r\n actual = FakeOutF()\r\n expected = \"\"\r\n sort_fasta_by_abundance([], actual)\r\n self.assertEqual(actual.s, expected)\r\n\r\n # no sorting necessary\r\n actual = FakeOutF()\r\n expected1 = \"\\n\".join(['>s1', 'ACCGT', '>s2 comment', 'ATTGC', ''])\r\n expected2 = \"\\n\".join(['>s2 comment', 'ATTGC', '>s1', 'ACCGT', ''])\r\n sort_fasta_by_abundance(\r\n ['>s1',\r\n 'ACCGT',\r\n '>s2 comment',\r\n 'ATTGC'],\r\n actual)\r\n # order is unimportant here\r\n self.assertTrue(actual.s == expected1 or actual.s == expected2)\r\n\r\n # sorting necessary\r\n actual = FakeOutF()\r\n inseqs = ['>s1', 'ACCGT',\r\n '>s2 comment', 'ATTGC',\r\n '>s3 blah', 'ATTGC']\r\n expected = \"\\n\".join(['>s2 comment', 'ATTGC',\r\n '>s3 blah', 'ATTGC',\r\n '>s1', 'ACCGT', ''])\r\n sort_fasta_by_abundance(inseqs, actual)\r\n self.assertEqual(actual.s, expected)","def get_AA_subs(s):\r\n test_seq = s.toseq()[70:217].translate() #Translate the mutated region\r\n substitutions = []\r\n \r\n for i in range(len(test_seq)):\r\n if test_seq[i] != align_temp[i]:\r\n substitutions.append(''.join([str(align_temp[i]),\r\n str(i+48),\r\n str(test_seq[i]),\r\n ' ']))\r\n \r\n return ''.join(substitutions).strip()","def test_amino_acid_slicing(self):\n chrom_result = [None, None, None, None, \"R\", \"R\", None, \"R\", \"A\", \"A\", None, None,\n \"A\", None, None, None]\n for i in xrange(len(chrom_result)):\n self.assertEqual(self.t.chromosome_coordinate_to_amino_acid(i, self.chrom_seq), chrom_result[i])\n cds_result = [\"A\", \"A\", \"A\", \"R\", \"R\", \"R\", None]\n for i in xrange(len(cds_result)):\n self.assertEqual(self.t.cds_coordinate_to_amino_acid(i, self.chrom_seq), cds_result[i])\n transcript_result = [None, None, \"A\", \"A\", \"A\", \"R\", \"R\", \"R\", None, None, None]\n for i in xrange(len(transcript_result)):\n self.assertEqual(self.t.transcript_coordinate_to_amino_acid(i, self.chrom_seq), transcript_result[i])","def test_assign_seqs_fasta_plus_qual(self):\r\n\r\n # Handles single fasta and single qual\r\n file_data = {}\r\n file_data['fasta_files'] = [self.valid_fasta_file_no_errors]\r\n file_data['qual_files'] = [self.valid_qual_file_no_errors]\r\n file_data['demultiplexed_seqs_f'] = FakeOutFile()\r\n file_data['demultiplexed_qual_f'] = FakeOutFile()\r\n\r\n ids_bcs_added_field = {('AACTCGTCGATG', ''): 's1',\r\n ('AGCAGCACTTGT', ''): 's2', ('ACCGCAGAGTCA', ''): 's3'}\r\n bc_lens = [12]\r\n all_bcs = ['AACTCGTCGATG', 'AGCAGCACTTGT', 'ACCGCAGAGTCA']\r\n keep_barcode = False\r\n barcode_type = \"golay_12\"\r\n max_bc_errors = 1.5\r\n start_index = 1\r\n write_unassigned_reads = False\r\n disable_bc_correction = False\r\n added_demultiplex_field = None\r\n\r\n log_data, bc_freqs, seq_counts, corrected_bc_count =\\\r\n assign_seqs(file_data, ids_bcs_added_field, bc_lens, all_bcs,\r\n keep_barcode, barcode_type, max_bc_errors, start_index,\r\n write_unassigned_reads, disable_bc_correction,\r\n added_demultiplex_field)\r\n\r\n expected_demultiplexed_fasta_seq = \">s1_1 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\nCAGGACGAGACGAGGTT\\n>s3_2 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\nCCAGATTACGAGATTA\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\nGACCGATTACGATAACG\\n\"\r\n expected_demultiplexed_qual_seq = '>s1_1 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\n30 26 11 11 29 20 19 16 24 17 29 28 11 27 14 24 24\\n>s3_2 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\n12 14 27 23 22 19 24 18 19 20 28 10 17 14 17 13\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\n10 20 16 20 25 27 22 28 16 22 16 18 12 13 16 25 17\\n'\r\n\r\n self.assertEqual(file_data['demultiplexed_seqs_f'].data,\r\n expected_demultiplexed_fasta_seq)\r\n self.assertEqual(file_data['demultiplexed_qual_f'].data,\r\n expected_demultiplexed_qual_seq)\r\n\r\n expected_log_data = {'ACCGCAGAGTCA,s3': 1, 'AACTCGTCGATG,s1': 1,\r\n 'AGCAGCACTTGT,s2': 1}\r\n expected_bc_freqs = {'AACTCGTCGATG': 1, 'AGCAGCACTTGT': 1,\r\n 'ACCGCAGAGTCA': 1}\r\n expected_seq_counts = 3\r\n expected_corrected_bc_count = [0, 0]\r\n\r\n self.assertEqual(log_data, expected_log_data)\r\n self.assertEqual(bc_freqs, expected_bc_freqs)\r\n self.assertEqual(seq_counts, expected_seq_counts)\r\n self.assertEqual(corrected_bc_count, expected_corrected_bc_count)","def test_amino_acid_slicing(self):\n chrom_result = [None, None, None, None, \"S\", \"S\", None, \"S\", \"G\", \"G\", None, None,\n \"G\", None, None, None]\n for i in xrange(len(chrom_result)):\n try:\n self.assertEqual(self.t.chromosome_coordinate_to_amino_acid(i, self.chrom_seq), chrom_result[i])\n except:\n assert False, (chrom_result, self.chrom_seq['chr1'][:], chrom_result[i], i)\n cds_result = [\"S\", \"S\", \"S\", \"G\", \"G\", \"G\", None]\n for i in xrange(len(cds_result)):\n self.assertEqual(self.t.cds_coordinate_to_amino_acid(i, self.chrom_seq), cds_result[i])\n transcript_result = [None, None, \"S\", \"S\", \"S\", \"G\", \"G\", \"G\", None, None, None]\n for i in xrange(len(transcript_result)):\n self.assertEqual(self.t.transcript_coordinate_to_amino_acid(i, self.chrom_seq), transcript_result[i])","def generate_aa_sequence(chain):\n\n chain.strip()\n chain_list = chain.split(' ')\n # TODO: What if aa is not in the lookup\n seq = [IUPAC_AA_codes[aa] for aa in chain_list]\n return ''.join(seq)","def test_xyz_to_ase(self):\n atoms_1 = converter.xyz_to_ase(self.xyz1['dict'])\n self.assertIsInstance(atoms_1, Atoms)\n self.assertEqual(str(atoms_1.symbols), 'CH4')\n np.testing.assert_array_equal(atoms_1.positions, [[0., 0., 0.],\n [0.6300326, 0.6300326, 0.6300326],\n [-0.6300326, -0.6300326, 0.6300326],\n [-0.6300326, 0.6300326, -0.6300326],\n [0.6300326, -0.6300326, -0.6300326]])","def determine_aa_change( self ):\n for k,v in self.obj_mi.hash_isoforms.iteritems(): #k = string that is isoform_id, v = Isoform instance\n obj_tt = self.create_transcript_instances( k )\n\n #METHOD 1: get the original codon & mutated codon\n # orig_codon = obj_tt.retrieve_containing_codon( self.snv_start, self.snv_strand )\n # i_genome_pos = obj_tt.arr_genome_pos.index( self.snv_start )\n # obj_tt.arr_nuc_seq[ i_genome_pos ] = self.base_alt\n # mut_codon = obj_tt.retrieve_containing_codon( self.snv_start, self.snv_strand )\n\n\n #METHOD 2: get the mutated codon\n full_pos = self.snv_chrom + ':' + str( self.snv_start ) + '-' + str( self.snv_end )\n hash_codon_info = obj_tt.get_mutated_codon( self.base_orig, self.base_alt, full_pos, self.snv_strand, True ) #output is hash -> {'codon_orig': codon_orig, 'codon_mut': codon_mut, 'aa_orig': aa_orig, 'aa_mut': aa_mut}\n\n\n\n ##TEST:: show the AA change based on mutation\n # print \"hash_codon_info: \"\n # print hash_codon_info\n\n # print \"gene strand & snv strand: \", obj_tt.iso_sj.strand, \" & \", self.snv_strand\n # print \"original base > mutated base: \", self.base_orig, \" > \", self.base_alt\n # print \"original codon > mutated codon: \", hash_codon_info['codon_orig'], \" > \", hash_codon_info['codon_mut']\n # print \"original AA > mutated AA: \", hash_codon_info['aa_orig'], \" > \", hash_codon_info['aa_mut']\n\n\n ##TEST:: determine consequence\n print \"GV_DAAC 1: \"\n obj_tt.alteration_consequence( self.base_alt, self.get_genomic_range(), self.snv_strand, self.alt_type )\n \n\n ##TEST METHOD - SEE WHAT STEPS I NEED TO PERFORM\n #TEST:: retrieve the original base & the mutated base\n # i_genome_pos = obj_tt.arr_genome_pos.index( self.snv_start )\n # orig_base = obj_tt.arr_nuc_seq[ i_genome_pos ]\n # print \"k = \", k, \" & i_genome_pos = \", i_genome_pos, \" | orig_base = \", orig_base, \" & double_check = \", self.base_orig, \" & iso_sj.strand = \", obj_tt.iso_sj.strand, \" & mut strand = \", self.snv_strand\n # hash_orig_codon = obj_tt.find_containing_codon( self.snv_start )\n # print \"hash_orig = \", hash_orig_codon\n # get_orig_codon = obj_tt.arr_nuc_seq[ hash_orig_codon['i_genome_start']:hash_orig_codon['i_genome_end'] + 1 ]\n # str_orig_codon = ''.join( get_orig_codon ) if obj_tt.iso_sj.strand > 0 else ''.join( get_orig_codon[::-1] )\n # print \"seq_orig = \", str_orig_codon, \" & type = \", type( get_orig_codon ), \" & rf = \", obj_tt.arr_rf[ hash_orig_codon['i_genome_start']:hash_orig_codon['i_genome_end'] + 1 ], \" & list_orig_codon = \", get_orig_codon\n\n # ##TEST:: make mutation\n # obj_tt.arr_nuc_seq[ i_genome_pos ] = self.base_alt\n # hash_mut_codon = obj_tt.find_containing_codon( self.snv_start )\n # print \"hash_muts = \", hash_mut_codon\n # get_mut_codon = obj_tt.arr_nuc_seq[ hash_mut_codon['i_genome_start']:hash_mut_codon['i_genome_end'] + 1 ]\n # str_mut_codon = ''.join( get_mut_codon ) if obj_tt.iso_sj.strand > 0 else ''.join( get_mut_codon[::-1] )\n # print \"seq_muts = \", str_mut_codon, \" & type = \", type( get_mut_codon ), \" & rf = \", obj_tt.arr_rf[ hash_mut_codon['i_genome_start']:hash_mut_codon['i_genome_end'] + 1 ], \" & list_mut_codon = \", get_mut_codon \n\n # ##TEST:: retrieve \n # print \"AA: from \", Seq( str_orig_codon ).translate( to_stop = False ), \">\", Seq( str_mut_codon ).translate( to_stop = False )\n\n # try:\n # i_genome_pos = obj_tt.arr_genome_pos.index( self.snv_start )\n # orig_base = obj_tt.arr_nuc_seq[ i_genome_pos ]\n # print \"k = \", k, \" & i_genome_pos = \", i_genome_pos, \" | orig_base = \", orig_base, \" & double_check = \", self.base_orig, \" & iso_sj.strand = \", obj_tt.iso_sj.strand, \" & mut strand = \", self.snv_strand\n # hash_orig_codon = obj_tt.find_containing_codon( self.snv_start )\n # print \"hash_orig = \", hash_orig_codon\n # get_orig_codon = obj_tt.arr_nuc_seq[ hash_orig_codon['i_genome_start']:hash_orig_codon['i_genome_end'] ]\n # print \"seq_orig = \", get_orig_codon\n\n # ##TEST:: make mutation\n # obj_tt.arr_nuc_seq[ i_genome_pos ] = self.base_alt\n # hash_mut_codon = obj_tt.find_containing_codon( self.snv_start )\n # print \"hash_muts = \", hash_mut_codon\n # get_mut_codon = obj_tt.arr_nuc_seq[ hash_mut_codon['i_genome_start']:hash_mut_codon['i_genome_end'] ]\n # print \"seq_muts = \", get_mut_codon \n\n # ##TEST:: retrieve \n # print \"AA: from \", Seq( orig_codon ).translate( to_stop = False ), \">\", Seq( mut_codon ).translate( to_stop = False )\n # except:\n # print \"ERROR:: for \", k, \", position does not exist: \", self.snv_start\n # continue\n\n print \"////////////////////\\n\"","def test_flip_strand(self):\n # Flipping the strand\n self.g.flip_strand()\n\n # Checking the reference and coded allele did change\n self.assertEqual(self.g.reference, \"AGCGT\")\n self.assertEqual(self.g.coded, \"G\")\n\n # Checking the genotypes did not changed\n np.testing.assert_array_equal(\n np.array([2, 2, 1, 2, 0, 1, 1, 1, np.nan, 0]),\n self.g.genotypes,\n )\n\n # The variant's allele should have changed\n self.assertEqual((\"AGCGT\", \"G\"), self.g.variant.alleles)\n\n # The rest of the information should be the same\n self.assertEqual(\"marker_1\", self.g.variant.name)\n self.assertEqual(1, self.g.variant.chrom)\n self.assertEqual(1234, self.g.variant.pos)\n self.assertFalse(self.g.multiallelic)","def output_aa_string(residues):\n # Dictionary of 3 letter to 1 letter AA conversion\n aa_dict = {'CYS': 'C', 'ASP': 'D', 'SER': 'S', 'GLN': 'Q', 'LYS': 'K',\n 'ILE': 'I', 'PRO': 'P', 'THR': 'T', 'PHE': 'F', 'ASN': 'N',\n 'GLY': 'G', 'HIS': 'H', 'LEU': 'L', 'ARG': 'R', 'TRP': 'W',\n 'ALA': 'A', 'VAL':'V', 'GLU': 'E', 'TYR': 'Y', 'MET': 'M'}\n\n s = ''\n for res in residues:\n s = s + aa_dict.get(res.type)\n return s","def test_fasta_naming(self):\n aln2fasta = hhsuite.AlignmentToFasta(q_name=\"foo\", t_name=\"{name}\")\n self.assertEqual(\n aln2fasta.fasta(self.hit, \"A-E----\"),\n \">foo\\nJKLMNOP\\n>templatename\\nA-E----\\n\")","def test_assign_seqs_fasta_only(self):\r\n\r\n # Initial test for single fasta file alone.\r\n file_data = {}\r\n file_data['fasta_files'] = [self.valid_fasta_file_no_errors]\r\n file_data['qual_files'] = []\r\n #file_data['mapping_file'] = self.valid_mapping_data_golay_upper\r\n file_data['demultiplexed_seqs_f'] = FakeOutFile()\r\n\r\n ids_bcs_added_field = {('AACTCGTCGATG', ''): 's1',\r\n ('AGCAGCACTTGT', ''): 's2', ('ACCGCAGAGTCA', ''): 's3'}\r\n bc_lens = [12]\r\n all_bcs = ['AACTCGTCGATG', 'AGCAGCACTTGT', 'ACCGCAGAGTCA']\r\n keep_barcode = False\r\n barcode_type = \"golay_12\"\r\n max_bc_errors = 1.5\r\n start_index = 1\r\n write_unassigned_reads = False\r\n disable_bc_correction = False\r\n added_demultiplex_field = None\r\n\r\n log_data, bc_freqs, seq_counts, corrected_bc_count =\\\r\n assign_seqs(file_data, ids_bcs_added_field, bc_lens, all_bcs,\r\n keep_barcode, barcode_type, max_bc_errors, start_index,\r\n write_unassigned_reads, disable_bc_correction,\r\n added_demultiplex_field)\r\n\r\n expected_demultiplexed_fasta_seq = \">s1_1 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\nCAGGACGAGACGAGGTT\\n>s3_2 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\nCCAGATTACGAGATTA\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\nGACCGATTACGATAACG\\n\"\r\n\r\n self.assertEqual(file_data['demultiplexed_seqs_f'].data,\r\n expected_demultiplexed_fasta_seq)\r\n\r\n expected_log_data = {'ACCGCAGAGTCA,s3': 1, 'AACTCGTCGATG,s1': 1,\r\n 'AGCAGCACTTGT,s2': 1}\r\n expected_bc_freqs = {'AACTCGTCGATG': 1, 'AGCAGCACTTGT': 1,\r\n 'ACCGCAGAGTCA': 1}\r\n expected_seq_counts = 3\r\n expected_corrected_bc_count = [0, 0]\r\n\r\n self.assertEqual(log_data, expected_log_data)\r\n self.assertEqual(bc_freqs, expected_bc_freqs)\r\n self.assertEqual(seq_counts, expected_seq_counts)\r\n self.assertEqual(corrected_bc_count, expected_corrected_bc_count)","def gene_finder(dna):\n all_orfs_both_strands = find_all_ORFs_both_strands(dna)\n longest_fake_orf = longest_ORF_noncoding(dna, 20)\n for element in all_orfs_both_strands:\n if len(element) > longest_fake_orf:\n a_a_string = coding_strand_to_AA(element)\n else:\n a_a_string = 'not longer than shuffle'\n print(a_a_string)","def test_regular_to_regular(self):\n r = RNA.make_seq(\"AAA\", name=\"x\")\n s = RNA.make_seq(r)\n self.assertEqual(str(s), \"AAA\")\n self.assertEqual(s.moltype, RNA)\n self.assertEqual(s.name, \"x\")","def translate_sequence(rna_sequence, genetic_code):\n #Crate an empty list to store AA sequence:\n AA_list = []\n # Convert all rna_sequence to upper case:\n rna_sequence=rna_sequence.upper()\n # Convert all rna_sequence into a list:\n rna_list = list(rna_sequence)\n # This conditon will run if rna_sequence is at least 3 bases long, and only once it find start codon ,\n #and stop once it finds stop codon.\n while True:\n if len(rna_list) > 2:\n codon=''.join(rna_list[0:3])\n #Delete first 3 bases since its alread added as codon, thus no longer needed.\n del rna_list[0:3]\n else:\n break\n #Using genetic code dictionary to find AA for each corresponding codon:\n AA=genetic_code[codon]\n #Break loop once it finds stop codon\n if AA=='*':\n break\n #Add add translatable AA to the AA_list:\n AA_list.append(AA)\n return ''.join(AA_list)","def do(s):\r\n return get_AA_subs(generate_mutString(s))","def test_add_seqs_to_alignment(self):\n res = add_seqs_to_alignment(self.seqs2_fp, self.seqs1_aln_fp, RNA)\n self.assertEqual(res.toFasta(), self.add_seqs_aligned)","def test_assign_seqs_two_fastas(self):\r\n\r\n # Handles two fasta files alone\r\n file_data = {}\r\n file_data['fasta_files'] = [self.valid_fasta_file_no_errors,\r\n self.valid_fasta_file_no_errors]\r\n file_data['qual_files'] = []\r\n #file_data['mapping_file'] = self.valid_mapping_data_golay_upper\r\n file_data['demultiplexed_seqs_f'] = FakeOutFile()\r\n\r\n ids_bcs_added_field = {('AACTCGTCGATG', ''): 's1',\r\n ('AGCAGCACTTGT', ''): 's2', ('ACCGCAGAGTCA', ''): 's3'}\r\n bc_lens = [12]\r\n all_bcs = ['AACTCGTCGATG', 'AGCAGCACTTGT', 'ACCGCAGAGTCA']\r\n keep_barcode = False\r\n barcode_type = \"golay_12\"\r\n max_bc_errors = 1.5\r\n start_index = 1\r\n write_unassigned_reads = False\r\n disable_bc_correction = False\r\n added_demultiplex_field = None\r\n\r\n log_data, bc_freqs, seq_counts, corrected_bc_count =\\\r\n assign_seqs(file_data, ids_bcs_added_field, bc_lens, all_bcs,\r\n keep_barcode, barcode_type, max_bc_errors, start_index,\r\n write_unassigned_reads, disable_bc_correction,\r\n added_demultiplex_field)\r\n\r\n expected_demultiplexed_fasta_seq = '>s1_1 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\nCAGGACGAGACGAGGTT\\n>s3_2 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\nCCAGATTACGAGATTA\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\nGACCGATTACGATAACG\\n>s1_4 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\nCAGGACGAGACGAGGTT\\n>s3_5 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\nCCAGATTACGAGATTA\\n>s2_6 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\nGACCGATTACGATAACG\\n'\r\n self.assertEqual(file_data['demultiplexed_seqs_f'].data,\r\n expected_demultiplexed_fasta_seq)\r\n\r\n expected_log_data = {'ACCGCAGAGTCA,s3': 2, 'AACTCGTCGATG,s1': 2,\r\n 'AGCAGCACTTGT,s2': 2}\r\n expected_bc_freqs = {'AACTCGTCGATG': 2, 'AGCAGCACTTGT': 2,\r\n 'ACCGCAGAGTCA': 2}\r\n expected_seq_counts = 6\r\n expected_corrected_bc_count = [0, 0]\r\n\r\n self.assertEqual(log_data, expected_log_data)\r\n self.assertEqual(bc_freqs, expected_bc_freqs)\r\n self.assertEqual(seq_counts, expected_seq_counts)\r\n self.assertEqual(corrected_bc_count, expected_corrected_bc_count)","def isaac_():\n global aa, bb, cc, randcnt\n\n cc = cc + 1\n bb = (bb + cc)\n\n for i in range(0, 256):\n x = mm[i]\n mod = i % 4\n if mod == 0:\n aa = aa ^ (aa << 13)\n elif mod == 1:\n aa = aa ^ (aa >> 6)\n elif mod == 2:\n aa = aa ^ (aa << 2)\n elif mod == 3:\n aa = aa ^ (aa >> 16)\n\n aa = mm[(i + 128) % 256] + aa\n mm[i] = y = mm[(x >> 2) % 256] + aa + bb\n randrsl[i] = bb = mm[(y >> 10) % 256] + x\n\n randcnt = 0","def test_ACE(self): \n self.assertFloatEqual(ACE(array([2,0])), 1.0, eps=0.001)\n # next: just returns the number of species when all are abundant\n self.assertFloatEqual(ACE(array([12,0,9])), 2.0, eps=0.001)\n self.assertFloatEqual(ACE(array([12,2,8])), 3.0, eps=0.001)\n self.assertFloatEqual(ACE(array([12,2,1])), 4.0, eps=0.001)\n self.assertFloatEqual(ACE(array([12,1,2,1])), 7.0, eps=0.001)\n self.assertFloatEqual(ACE(array([12,3,2,1])), 4.6, eps=0.001)\n self.assertFloatEqual(ACE(array([12,3,6,1,10])), 5.62749672, eps=0.001)","def test_correct_barcode_exact_match(self):\r\n barcode = \"GGAGACAAGGGA\"\r\n barcode_to_sample_id = {\r\n \"GGAGACAAGGGA\": \"s1\",\r\n \"ACACCTGGTGAT\": \"s2\"}\r\n correction_fn = None\r\n\r\n actual = correct_barcode(barcode, barcode_to_sample_id, correction_fn)\r\n expected = (0, barcode, False, 's1')\r\n self.assertEqual(actual, expected)\r\n\r\n correction_fn = decode_golay_12\r\n actual = correct_barcode(barcode, barcode_to_sample_id, correction_fn)\r\n expected = (0, barcode, False, 's1')\r\n self.assertEqual(actual, expected)","def test_convert_input(self):\n m, seq = DNA.make_seq(\"ACGGT--A\").parse_out_gaps()\n aligned_seq = Aligned(m, seq)\n mapped_gap, new_seq = _convert_input(aligned_seq, None)\n self.assertIs(new_seq.moltype, DNA)\n self.assertIs(mapped_gap, m)\n self.assertIs(new_seq, seq)\n mapped_gap, new_seq = _convert_input(\"ACGGT--A\", DNA)\n self.assertEqual(str(mapped_gap), str(m))\n self.assertEqual(str(new_seq), str(seq))","def rs1_score(sequence):\n import math\n import numpy as np\n seq = str(sequence).upper()\n seq = list(seq)\n matrix1 = np.zeros([len(sequence),4], dtype=int)\n for i,item in enumerate(sequence):\n if item == 'A':\n matrix1[i,0] = 1\n if item == 'T':\n matrix1[i,1] = 1\n if item == 'U':\n matrix1[i,1] = 1\n if item == 'C':\n matrix1[i,2] = 1\n if item == 'G':\n matrix1[i,3] = 1\n\n\n \"\"\"\n Generates a binary matrix for DNA/RNA sequence, where each column is a possible\n pair of adjacent bases, and each row is a position along the sequence.\n Matrix column order is AA, AT, AC, AG, TA, TT, TC, TG, CA, CT, CC, CG, GA, GT, GC, GG\n \"\"\"\n sequence = sequence.replace('U','T')\n pairwise_sequence = []\n for i in range(len(sequence)):\n if i < len(sequence)-1:\n basepair = sequence[i]+sequence[i+1]\n pairwise_sequence.append(basepair)\n matrix2 = np.zeros([len(pairwise_sequence),16], dtype=int)\n for i,item in enumerate(pairwise_sequence):\n if item == 'AA':\n matrix2[i,0] = 1\n if item == 'AT':\n matrix2[i,1] = 1\n if item == 'AC':\n matrix2[i,2] = 1\n if item == 'AG':\n matrix2[i,3] = 1\n if item == 'TA':\n matrix2[i,4] = 1\n if item == 'TT':\n matrix2[i,5] = 1\n if item == 'TC':\n matrix2[i,6] = 1\n if item == 'TG':\n matrix2[i,7] = 1\n if item == 'CA':\n matrix2[i,8] = 1\n if item == 'CT':\n matrix2[i,9] = 1\n if item == 'CC':\n matrix2[i,10] = 1\n if item == 'CG':\n matrix2[i,11] = 1\n if item == 'GA':\n matrix2[i,12] = 1\n if item == 'GT':\n matrix2[i,13] = 1\n if item == 'GC':\n matrix2[i,14] = 1\n if item == 'GG':\n matrix2[i,15] = 1\n\n\n \"\"\"\n Scoring matrix\n \"\"\"\n intersect = 0.59763615\n low_gc = -0.2026259\n high_gc = -0.1665878\n\n first_order = ['G02','A03','C03','C04','C05',\n 'G05','A06','C06','C07','G07',\n 'A12','A15','C15','A16','C16',\n 'T16','A17','G17','C18','G18',\n 'A19','C19','G20','T20','G21',\n 'T21','C22','T22','T23','C24',\n 'G24','T24','A25','C25','T25',\n 'G28','T28','C29','G30']\n first_scores = [-0.2753771,-0.3238875,0.17212887,-0.1006662,-0.2018029,\n 0.24595663,0.03644004,0.09837684,-0.7411813,-0.3932644,\n -0.466099,0.08537695,-0.013814,0.27262051,0.1190226,\n -0.2859442,0.09745459,-0.1755462,-0.3457955,-0.6780964,\n 0.22508903,-0.5077941,-0.4173736,-0.054307,0.37989937,\n -0.0907126,0.05782332,-0.5305673,-0.8770074,-0.8762358,\n 0.27891626,-0.4031022,-0.0773007,0.28793562,-0.2216372,\n -0.6890167,0.11787758,-0.1604453,0.38634258]\n first_order_scores = dict(zip(first_order,first_scores))\n\n second_order = ['GT02','GC05','AA06','TA06','GG07',\n 'GG12','TA12','TC12','TT12','GG13',\n 'GA14','GC14','TG17','GG19','TC19',\n 'CC20','TG20','AC21','CG21','GA21',\n 'GG21','TC22','CG23','CT23','AA24',\n 'AG24','AG25','CG25','TG25','GT27',\n 'GG29']\n second_scores = [-0.6257787,0.30004332,-0.8348362,0.76062777,-0.4908167,\n -1.5169074,0.7092612,0.49629861,-0.5868739,-0.3345637,\n 0.76384993,-0.5370252,-0.7981461,-0.6668087,0.35318325,\n 0.74807209,-0.3672668,0.56820913,0.32907207,-0.8364568,\n -0.7822076,-1.029693,0.85619782,-0.4632077,-0.5794924,\n 0.64907554,-0.0773007,0.28793562,-0.2216372,0.11787758,\n -0.69774]\n second_order_scores = dict(zip(second_order,second_scores))\n\n\n # order 1 score matrix\n \"\"\" row order == A T/U C G \"\"\"\n first_matrix = np.zeros([4,30], dtype=float)\n def posit(key):\n return int(key[1:])-1\n for k,v in first_order_scores.items():\n if k[0] == 'A':\n first_matrix[0,posit(k)] = v\n elif k[0] == 'T':\n first_matrix[1,posit(k)] = v\n elif k[0] == 'C':\n first_matrix[2,posit(k)] = v\n elif k[0] == 'G':\n first_matrix[3,posit(k)] = v\n\n\n # order 2 score matrix\n \"\"\" row order == AA AT AC AG TA TT TC TG CA CT CC CG GA GT GC GG \"\"\"\n second_matrix = np.zeros([16,29], dtype=float)\n for k,v in second_order_scores.items():\n if k[0:2] == 'AA':\n second_matrix[0,int(k[2:])-1] = v\n if k[0:2] == 'AT':\n second_matrix[1,int(k[2:])-1] = v\n if k[0:2] == 'AC':\n second_matrix[2,int(k[2:])-1] = v\n if k[0:2] == 'AG':\n second_matrix[3,int(k[2:])-1] = v\n if k[0:2] == 'TA':\n second_matrix[4,int(k[2:])-1] = v\n if k[0:2] == 'TT':\n second_matrix[5,int(k[2:])-1] = v\n if k[0:2] == 'TC':\n second_matrix[6,int(k[2:])-1] = v\n if k[0:2] == 'TG':\n second_matrix[7,int(k[2:])-1] = v\n if k[0:2] == 'CA':\n second_matrix[8,int(k[2:])-1] = v\n if k[0:2] == 'CT':\n second_matrix[9,int(k[2:])-1] = v\n if k[0:2] == 'CC':\n second_matrix[10,int(k[2:])-1] = v\n if k[0:2] == 'CG':\n second_matrix[11,int(k[2:])-1] = v\n if k[0:2] == 'GA':\n second_matrix[12,int(k[2:])-1] = v\n if k[0:2] == 'GT':\n second_matrix[13,int(k[2:])-1] = v\n if k[0:2] == 'GC':\n second_matrix[14,int(k[2:])-1] = v\n if k[0:2] == 'GG':\n second_matrix[15,int(k[2:])-1] = v\n\n item_gc = sequence[0][5:-5]\n gc_count = item_gc.count('G') + item_gc.count('C')\n if gc_count < 10:\n gc_score = low_gc\n else:\n gc_score = high_gc\n first_first = np.matmul(first_matrix,matrix1)\n score_first = np.trace(first_first)\n score_second = np.trace(np.matmul(second_matrix,matrix2))\n score = (1/(1 + math.exp(-(intersect + gc_score + score_first + score_second))))\n return score","def transcribe_to_rna(strand):\n # First, validate input\n if not set(strand) <= set('{}{}{}{}'.format(Bases.Adenine, Bases.Thymine, Bases.Cytosine, Bases.Guanine)):\n raise ValueError(\"Tried to transcribe strand with an invalid base.\")\n transcribed_strand = strand.translate(transcription_rna_transtab)\n return transcribed_strand","def test_isc_rr_type_a_passing(self):\n test_string = [\n 'a',\n 'A',\n ]\n result = rr_type_a.runTests(test_string, failureTests=False)\n self.assertTrue(result[0])","def test_a():\n result = SECOND_TASK.start(\"aca\")\n\n assert result.replace(\"*\", \"\").replace(\"_\", \"\").replace(\"#\", \"\").replace(\"^\", \"\") == \"aac\"","def test_run_fasta_checks(self):\r\n\r\n actual_fasta_report = run_fasta_checks(self.sample_fasta_fp,\r\n self.sample_mapping_fp)\r\n\r\n # All values should be zero\r\n expected_fasta_report = {'invalid_labels': '0.000',\r\n 'tree_subset': False,\r\n 'all_ids_found': False,\r\n 'same_seq_lens': False,\r\n 'barcodes_detected': '0.000',\r\n 'duplicate_labels': '0.000',\r\n 'duplicate_ids': [],\r\n 'invalid_seq_chars': '0.000',\r\n 'nosample_ids_map': '0.000',\r\n 'linkerprimers_detected': '0.000',\r\n 'tree_exact_match': False,\r\n 'barcodes_at_start': '0.000'}\r\n\r\n self.assertEqual(actual_fasta_report, expected_fasta_report)","def test_encode():","def test_amino_acid_slicing(self):\n pass","def test_amino_acid_slicing(self):\n pass","def test_2():\n results = base_tests()\n correct = {\n \"Consequence\": \"synonymous_variant\",\n \"Codons\": \"tgC/tgT\",\n \"Amino_acids\": \"C\",\n \"Gene\": \"ENSG00000130164\",\n \"SYMBOL\": \"LDLR\",\n \"Feature\": \"ENST00000558013\",\n \"EXON\": \"2/18\",\n \"PolyPhen\": \"\",\n \"SIFT\": \"\",\n \"Protein_position\": \"27/858\",\n 'BIOTYPE\"': \"protein_coding\",\n }\n assert results[0] == correct","def test_attempt_bc_correction_hamming8(self):\r\n\r\n curr_bc = \"AGCAGCAC\"\r\n all_bcs = [\"AGCAGAAC\", \"TGCAGTAC\", \"ACAGAGTC\"]\r\n barcode_type = \"hamming_8\"\r\n actual_bc, actual_errs = attempt_bc_correction(curr_bc,\r\n all_bcs, barcode_type)\r\n\r\n expected_bc = \"AGCAGAAC\"\r\n expected_errs = 0.5\r\n self.assertEqual(actual_bc, expected_bc)\r\n self.assertEqual(actual_errs, expected_errs)","def find_all_ORFs_both_strands_unit_tests(dna, expected):\n\n print find_all_ORFs_both_strands(\"ATGCGAATGTAGCATCAAA\")\n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + find_all_ORFs_both_strands(dna)","def test_compare_to_string(self):\n r = self.RNA(\"UCC\")\n self.assertEqual(r, \"UCC\")","def test_double_sharp_2():\n assert note_to_frequency(\"Ax4\") == note_to_frequency(\"B4\")","def test_anglicize20to99():\n print('Testing anglicize20to99')\n\n result = funcs.anglicize20to99(35)\n introcs.assert_equals(\"thirty five\", result)\n\n result = funcs.anglicize20to99(50)\n introcs.assert_equals(\"fifty\", result)\n\n result = funcs.anglicize20to99(99)\n introcs.assert_equals(\"ninety nine\", result)","def transcribe(strand):\n # First, validate input\n if not set(strand) <= set('{}{}{}{}'.format(Bases.Adenine, Bases.Thymine, Bases.Cytosine, Bases.Guanine)):\n raise ValueError(\"Tried to transcribe strand with an invalid base.\")\n transcribed_strand = strand.translate(transcription_transtab)\n return transcribed_strand","def test_check_seqs_qual_out(self):\r\n\r\n in_seqs = self.in_seqs_fixed_len_bc1\r\n bc_map = self.bc_map_fixed_len_bc1\r\n primer_seq_lens = self.primer_seq_lens_fixed_len_bc1\r\n all_primers = self.all_primers_fixed_len_bc1\r\n expected = expected_qual_fixed_len_bc1\r\n\r\n fd, out_fp = mkstemp(prefix=\"sample_seqs_\", suffix=\".fna.tmp\")\r\n close(fd)\r\n out_f = open(out_fp, \"w\")\r\n self._files_to_remove.append(out_f.name.replace('.tmp', ''))\r\n\r\n qual_out_f = FakeOutFile()\r\n\r\n actual = check_seqs(\r\n fasta_out=out_f,\r\n fasta_files=[in_seqs],\r\n starting_ix=0,\r\n valid_map=bc_map,\r\n qual_mappings=parse_qual_score(\r\n self.in_seqs_fixed_len_bc1_qual_scores),\r\n filters=[],\r\n barcode_len=12,\r\n keep_primer=False,\r\n keep_barcode=False,\r\n barcode_type=\"golay_12\",\r\n max_bc_errors=1.5,\r\n retain_unassigned_reads=False,\r\n attempt_bc_correction=True,\r\n primer_seqs_lens=primer_seq_lens,\r\n all_primers=all_primers,\r\n max_primer_mm=0,\r\n disable_primer_check=False,\r\n reverse_primers='disable',\r\n rev_primers={},\r\n qual_out=qual_out_f)\r\n\r\n self.assertEqual(qual_out_f.data, expected)","def test_align_two_alignments(self):\n res = align_two_alignments(self.align1_fp, self.align2_fp, RNA)\n self.assertEqual(res.toFasta(), self.align_two_align)","def test_basic():\n a1 = astropy.coordinates.SkyCoord(10.625 * units.degree, 41.2 * units.degree)\n c1 = coord.CelestialCoord(10.625 * coord.degrees, 41.2 * coord.degrees)\n np.testing.assert_almost_equal(c1.rad, [a1.ra.rad, a1.dec.rad], decimal=12)\n\n a2 = astropy.coordinates.SkyCoord('00:42.5 +41:12', unit=(units.hourangle, units.deg))\n c2 = coord.CelestialCoord(coord.Angle.from_hms('00:42:30'), coord.Angle.from_dms('41:12:00'))\n np.testing.assert_almost_equal(c2.rad, [a2.ra.rad, a2.dec.rad], decimal=12)\n\n # astropy made different choices for the HMS and DMS string representations, but we can\n # make it match our choice without too much trouble.\n astr = a2.to_string(style='hmsdms', sep=':')\n print('astr = ',astr)\n astr_ra, astr_dec = astr.split()\n cstr_ra = c2.ra.hms()\n cstr_dec = c2.dec.dms(plus_sign=True)\n assert astr_ra == cstr_ra\n assert astr_dec == cstr_dec","def test_get_consensus_assignment_overlapping_names(self):\r\n # here the 3rd level is different, but the 4th level is the same\r\n # across the three assignments. this can happen in practice if\r\n # three different genera are assigned, and under each there is\r\n # an unnamed species\r\n # (e.g., f__x;g__A;s__, f__x;g__B;s__, f__x;g__B;s__)\r\n # in this case, the assignment should be f__x.\r\n in1 = [['Ab', 'Bc', 'De', 'Jk'],\r\n ['Ab', 'Bc', 'Fg', 'Jk'],\r\n ['Ab', 'Bc', 'Hi', 'Jk']]\r\n\r\n params = {'id_to_taxonomy_fp': self.id_to_tax1_fp,\r\n 'reference_sequences_fp': self.refseqs1_fp}\r\n expected = (['Ab', 'Bc'], 1., 3)\r\n t = UclustConsensusTaxonAssigner(params)\r\n self.assertEqual(t._get_consensus_assignment(in1),\r\n expected)\r\n\r\n # here the third level is the same in 4/5 of the\r\n # assignments, but one of them (z, y, c) refers to a\r\n # different taxa since the higher levels are different.\r\n # the consensus value should be 3/5, not 4/5, to\r\n # reflect that.\r\n in2 = [['a', 'b', 'c'],\r\n ['a', 'd', 'e'],\r\n ['a', 'b', 'c'],\r\n ['a', 'b', 'c'],\r\n ['z', 'y', 'c']]\r\n expected = (['a', 'b', 'c'], 0.6, 5)\r\n t = UclustConsensusTaxonAssigner(params)\r\n self.assertEqual(t._get_consensus_assignment(in2),\r\n expected)","def test_pcoa(self):\r\n res = pcoa(self.distmtx_txt)\r\n assert res # formatting tested elsewhere\r","def test_to_from_iupac(self):\n from openff.toolkit.utils.toolkits import (\n InvalidIUPACNameError,\n UndefinedStereochemistryError,\n )\n\n with pytest.raises(InvalidIUPACNameError):\n Molecule.from_iupac(\".BETA.-PINENE\")\n\n # DrugBank_977, tagged as a problem molecule in earlier tests\n bad_stereo_iupac = (\n \"(~{E},3~{R},5~{S})-7-[4-(4-fluorophenyl)-6-isopropyl-2-\"\n \"[methyl(methylsulfonyl)amino]pyrimidin-5-yl]-3,5-\"\n \"dihydroxy-hept-6-enoic acid\"\n )\n with pytest.raises(UndefinedStereochemistryError):\n Molecule.from_iupac(bad_stereo_iupac)\n\n cholesterol = Molecule.from_smiles(\n \"C[C@H](CCCC(C)C)[C@H]1CC[C@@H]2[C@@]1(CC[C@H]3[C@H]2CC=C4[C@@]3(CC[C@@H](C4)O)C)C\"\n )\n\n cholesterol_iupac = cholesterol.to_iupac()\n\n assert Molecule.are_isomorphic(\n cholesterol, Molecule.from_iupac(cholesterol_iupac)\n )","async def test_amplification(test_handler, braf_amplification, prpf8_amplification):\n q = \"BRAF Amplification\"\n resp = await test_handler.normalize(q)\n assertion_checks(resp.variation_descriptor, braf_amplification, q)\n\n # Gene with > 1 sequence location\n q = \"PRPF8 AMPLIFICATION\"\n resp = await test_handler.normalize(q)\n assertion_checks(resp.variation_descriptor, prpf8_amplification, q)\n\n # Gene with no location. This should NOT return a variation\n resp = await test_handler.normalize(\"IFNR amplification\")\n assert resp.variation_descriptor is None","def isochrone_to_aa(*args, **kwargs):\n return isochrone_xv_to_aa(*args, **kwargs)","def test_assign_seqs_error_correction(self):\r\n\r\n # Handles single fasta and single qual with error correction\r\n file_data = {}\r\n file_data['fasta_files'] = [self.valid_fasta_file_with_bc_errors]\r\n file_data['qual_files'] = [self.valid_qual_file_no_errors]\r\n file_data['demultiplexed_seqs_f'] = FakeOutFile()\r\n file_data['demultiplexed_qual_f'] = FakeOutFile()\r\n\r\n ids_bcs_added_field = {('AACTCGTCGATG', ''): 's1',\r\n ('AGCAGCACTTGT', ''): 's2', ('ACCGCAGAGTCA', ''): 's3'}\r\n bc_lens = [12]\r\n all_bcs = ['AACTCGTCGATG', 'AGCAGCACTTGT', 'ACCGCAGAGTCA']\r\n keep_barcode = False\r\n barcode_type = \"golay_12\"\r\n max_bc_errors = 1.5\r\n start_index = 1\r\n write_unassigned_reads = False\r\n disable_bc_correction = False\r\n added_demultiplex_field = None\r\n\r\n log_data, bc_freqs, seq_counts, corrected_bc_count =\\\r\n assign_seqs(file_data, ids_bcs_added_field, bc_lens, all_bcs,\r\n keep_barcode, barcode_type, max_bc_errors, start_index,\r\n write_unassigned_reads, disable_bc_correction,\r\n added_demultiplex_field)\r\n\r\n expected_demultiplexed_fasta_seq = '>s1_1 ABCD0001 orig_bc=TACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=1\\nCAGGACGAGACGAGGTT\\n>s3_2 EFGH0002 orig_bc=GCCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=1\\nCCAGATTACGAGATTA\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\nGACCGATTACGATAACG\\n'\r\n expected_demultiplexed_qual_seq = '>s1_1 ABCD0001 orig_bc=TACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=1\\n30 26 11 11 29 20 19 16 24 17 29 28 11 27 14 24 24\\n>s3_2 EFGH0002 orig_bc=GCCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=1\\n12 14 27 23 22 19 24 18 19 20 28 10 17 14 17 13\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\n10 20 16 20 25 27 22 28 16 22 16 18 12 13 16 25 17\\n'\r\n self.assertEqual(file_data['demultiplexed_seqs_f'].data,\r\n expected_demultiplexed_fasta_seq)\r\n self.assertEqual(file_data['demultiplexed_qual_f'].data,\r\n expected_demultiplexed_qual_seq)\r\n\r\n expected_log_data = {'ACCGCAGAGTCA,s3': 1, 'AACTCGTCGATG,s1': 1,\r\n 'AGCAGCACTTGT,s2': 1}\r\n expected_bc_freqs = {'TACTCGTCGATG': 1, 'GCCGCAGAGTCA': 1,\r\n 'AGCAGCACTTGT': 1}\r\n expected_seq_counts = 3\r\n expected_corrected_bc_count = [2, 0]\r\n\r\n self.assertEqual(log_data, expected_log_data)\r\n self.assertEqual(bc_freqs, expected_bc_freqs)\r\n self.assertEqual(seq_counts, expected_seq_counts)\r\n self.assertEqual(corrected_bc_count, expected_corrected_bc_count)","def test_DnaSequence(self):\n x = DnaSequence(\"tcag\")\n # note: no longer preserves case\n self.assertEqual(x, \"TCAG\")\n\n x = DnaSequence(\"aaa\") + DnaSequence(\"ccc\")\n # note: doesn't preserve case\n self.assertEqual(x, \"AAACCC\")\n assert x.moltype is DNA\n self.assertRaises(AlphabetError, x.__add__, \"z\")\n self.assertEqual(DnaSequence(\"TTTAc\").rc(), \"GTAAA\")","def test_convert_azfp_01a_different_ranges(azfp_path):\n azfp_01a_path = azfp_path / '17031001.01A'\n azfp_xml_path = azfp_path / '17030815.XML'\n\n # Convert file\n echodata = open_raw(\n raw_file=azfp_01a_path, sonar_model='AZFP', xml_path=azfp_xml_path\n )\n assert echodata[\"Sonar/Beam_group1\"].backscatter_r.sel(channel='55030-125-1').dropna(\n 'range_sample'\n ).shape == (360, 438)\n assert echodata[\"Sonar/Beam_group1\"].backscatter_r.sel(channel='55030-769-4').dropna(\n 'range_sample'\n ).shape == (360, 135)\n\n # check convention-required variables in the Platform group\n check_platform_required_scalar_vars(echodata)","def normalize_alleles_by_strand(snp_string):\n # get alleles as tuple\n allele1, allele2 = extract_alleles_from_snp_string(snp_string)\n # get reverse compliment of bases and return\n return REVERSE_COMPLIMENT[allele1], REVERSE_COMPLIMENT[allele2]","def test_fastaqual_output(self):\r\n self.assertRaises(IOError, convert_fastaqual, self.fasta_file_path,\r\n output_directory=self.read_only_output_dir)","def test_lowercase_input(self):\n State(substance=\"water\")\n State(substance=\"r22\")\n State(substance=\"r134a\")\n State(substance=\"ammonia\")\n State(substance=\"propane\")\n State(substance=\"air\")\n State(substance=\"isobutane\")\n State(substance=\"carbondioxide\")\n State(substance=\"oxygen\")\n State(substance=\"nitrogen\")","def test_strand_symmetry(self):\n from cogent3 import get_moltype\n from cogent3.core.alignment import Aligned\n\n seq = DnaSequence(\"ACGGCTGAAGCGCTCCGGGTTTAAAACG\")\n ssym = seq.strand_symmetry(motif_length=1)\n assert_allclose(ssym.observed.array, [[7, 5], [7, 9]])\n assert_allclose(ssym.expected.array, [[6, 6], [8, 8]])\n\n # RNA too\n seq = seq.to_rna()\n ssym = seq.strand_symmetry(motif_length=1)\n assert_allclose(ssym.observed.array, [[7, 5], [7, 9]])\n\n # Aligned\n seq = DnaSequence(\"ACGGCTGAAGCGCTCCGGGTTTAAAACG\")\n m, s = seq.parse_out_gaps()\n seq = Aligned(m, s)\n ssym = seq.strand_symmetry(motif_length=1)\n assert_allclose(ssym.observed.array, [[7, 5], [7, 9]])\n\n with self.assertRaises(TypeError):\n text = get_moltype(\"text\")\n m, s = text.make_seq(\"ACGGCTGAAGCGCTCCGGGTTTAAAACG\").parse_out_gaps()\n s.strand_symmetry(motif_length=1)\n\n # with motif_length=2\n seq = DnaSequence(\"AC GG CT GA AG CG CT CC GG GT TT AA AA CG\".replace(\" \", \"\"))\n ssym = seq.strand_symmetry(motif_length=2)\n self.assertLessEqual(len(ssym.observed.keys()), 8)\n assert_allclose(ssym.observed[\"AA\"].to_array(), [2, 1])\n assert_allclose(ssym.observed[\"CC\"].to_array(), [1, 2])","def find_all_ORFs_both_strands_unit_tests():\n print ''\n print 'Begin Unit test Find_all_ORFs both tests'\n input_a='ATGCGAGGGTAGATGGATTAG'\n expected_output='[ATGCGAGGG, ATGGAT]'\n actual_output=find_all_ORFs_both_strands(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output\n \n \n input_a='ATGCGAATGTAGCATCAAATAGATGTAG'\n expected_output='[ATGCGAATG, ATG, ATGCTACATTCGCAT]'\n actual_output=find_all_ORFs_both_strands(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output \n print 'end'\n print ''","def test_double_sharp_1():\n assert note_to_frequency(\"A##4\") == note_to_frequency(\"B4\")","def test_is_AKs_preHandSimple_correct(self):\n self.assertEqual(self.hand.getPreHandSimple(), 'AKs')","def test_conversion_type(self):\r\n self.assertRaises(ValueError, convert_fastaqual_fastq,\r\n self.fasta_file_path, self.qual_file_path, conversion_type='soijdfl',\r\n output_directory=self.output_dir)","def test_check_dna_chars_bcs(self):\r\n\r\n header =\\\r\n ['SampleID',\r\n 'BarcodeSequence',\r\n 'LinkerPrimerSequence',\r\n 'Description']\r\n mapping_data = [['s-1', 'ACGT', 'AARNCWSVDAA', 's1&data'],\r\n ['s2', 'CGTA', 'AAA1A', 's2_data']]\r\n errors = []\r\n\r\n errors = check_dna_chars_bcs(header, mapping_data, errors)\r\n\r\n expected_errors = []\r\n\r\n self.assertEqual(errors, expected_errors)\r\n\r\n # Should find no errors\r\n\r\n header =\\\r\n ['SampleID', 'BarcodeSequence', 'LinkerPrimerSequence',\r\n 'ReversePrimer', 'Description']\r\n mapping_data = [['s-1', 'ACGT', 'AARNCWSVDAA', 'ACGT', 's1&data'],\r\n ['s2', 'C1GTA', 'AAA1A', 'ACGTF', 's2_data']]\r\n errors = []\r\n\r\n errors = check_dna_chars_bcs(header, mapping_data, errors,\r\n has_barcodes=False)\r\n\r\n expected_errors = []\r\n\r\n self.assertEqual(errors, expected_errors)\r\n\r\n # Should find errors with has_barcodes=True\r\n\r\n header =\\\r\n ['SampleID', 'BarcodeSequence', 'LinkerPrimerSequence',\r\n 'ReversePrimer', 'Description']\r\n mapping_data = [['s-1', 'ACGT', 'AARNCWSVDAA', 'ACGT', 's1&data'],\r\n ['s2', 'CNGTA', 'AAA1A', 'ACGTF', 's2_data']]\r\n errors = []\r\n\r\n errors = check_dna_chars_bcs(header, mapping_data, errors,\r\n has_barcodes=True)\r\n\r\n expected_errors = ['Invalid DNA sequence detected: CNGTA\\t2,1']\r\n\r\n self.assertEqual(errors, expected_errors)","def test_ModelDnaCodonSequence(self):\n d = ArrayDnaCodonSequence(\"UUUCGU\")\n self.assertEqual(str(d), \"TTTCGT\")\n self.assertEqual(d._data, array([0, 28]))\n self.assertEqual(str(d.to_rna()), \"UUUCGU\")\n self.assertEqual(str(d.to_dna()), \"TTTCGT\")","def test_convert():","def test_make_fasta_rec(self):\r\n header = '>E2_1 FYI2DSB01B17QJ orig_bc=ATCACTAGTCAC new_bc=ATCACTAGTCAC bc_diffs=0'\r\n seq = 'CTGGTC'\r\n qual = map(int, '32 32 32 19 19 19'.split())\r\n self.assertEqual(make_fastq_rec(header, seq, qual),\r\n \"\"\"@E2_1 FYI2DSB01B17QJ orig_bc=ATCACTAGTCAC new_bc=ATCACTAGTCAC bc_diffs=0\r\nCTGGTC\r\n+E2_1 FYI2DSB01B17QJ orig_bc=ATCACTAGTCAC new_bc=ATCACTAGTCAC bc_diffs=0\r\nAAA444\"\"\")","def test_init_data(self):\n r = self.RNA(\"ucagg\")\n # no longer preserves case\n self.assertEqual(r, \"UCAGG\")","def test_convert_adjective():\n result = convert(\"adjective\")\n assert result == \"adjectiveway\"","def to_rna(dna_strand):\n rta = [] # create an empty rna string\n dna = list(dna_strand) # create a list of dna so iterating is possible\n to_replace = {'C': 'G', 'G': 'C', 'T': 'A', 'A': 'U'}\n for letter in dna:\n if letter in to_replace.keys():\n rta.append(to_replace[letter])\n return ''.join(rta) # returning the rta string","def translate_sequence(sequence, genetic_code = {'GUC': 'V', 'ACC': 'T', 'GUA': 'V', 'GUG': 'V', 'ACU': 'T', 'AAC': 'N', 'CCU': 'P', 'UGG': 'W', 'AGC': 'S', 'AUC': 'I', 'CAU': 'H', 'AAU': 'N', 'AGU': 'S', 'GUU': 'V', 'CAC': 'H', 'ACG': 'T', 'CCG': 'P', 'CCA': 'P', 'ACA': 'T', 'CCC': 'P', 'UGU': 'C', 'GGU': 'G', 'UCU': 'S', 'GCG': 'A', 'UGC': 'C', 'CAG': 'Q', 'GAU': 'D', 'UAU': 'Y', 'CGG': 'R', 'UCG': 'S', 'AGG': 'R', 'GGG': 'G', 'UCC': 'S', 'UCA': 'S', 'UAA': '*', 'GGA': 'G', 'UAC': 'Y', 'GAC': 'D', 'UAG': '*', 'AUA': 'I', 'GCA': 'A', 'CUU': 'L', 'GGC': 'G', 'AUG': 'M', 'CUG': 'L', 'GAG': 'E', 'CUC': 'L', 'AGA': 'R', 'CUA': 'L', 'GCC': 'A', 'AAA': 'K', 'AAG': 'K', 'CAA': 'Q', 'UUU': 'F', 'CGU': 'R', 'CGC': 'R', 'CGA': 'R', 'GCU': 'A', 'GAA': 'E', 'AUU': 'I', 'UUG': 'L', 'UUA': 'L', 'UGA': '*', 'UUC': 'F'}, start_pos = 0):\n #find first orf\n #first_orf_seq = find_first_orf(sequence)\n\n # ensure sequence is uppercase\n seq = sequence.upper()\n\n #translate the sequence\n protein = \"\"\n for i in range(0, len(seq) - (len(seq) % 3), 3):\n codon = seq[i:i + 3]\n if genetic_code[codon] == \"*\":\n break\n protein += genetic_code[codon]\n return protein","def convert_bismark_add_strand_and_seq(indf, outfn):\n logger.debug(f'Start add strand and seq to bismark cov file, total len={len(indf)}')\n\n outf = gzip.open(outfn, 'wt')\n\n for index, row in tqdm(indf.iterrows(), total=len(indf), desc='Bismark_cov'):\n # if report_num and index % report_num == 0:\n # logger.debug(f'processed index={index}')\n chr = row['chr']\n start = int(row['start']) # Keep raw 1-based format of bismark results\n ret = get_dna_base_from_reference(chr, start - 1, ref_fasta=ref_fasta)\n if ret[5] == 'C': # strand is +\n strand = '+'\n elif ret[5] == 'G':\n strand = '-'\n else:\n raise Exception(f'We can not identify this bg-truth file with non-CG results, such as row={row}')\n\n outstr = '\\t'.join([chr, str(start), strand, str(row['mcount']), str(row['ccount']), ret[4:7]])\n outf.write(f'{outstr}\\n')\n outf.close()\n logger.info(f'save to {outfn}')\n\n logger.debug(f'Finish add strand info task')","def toBed(self,value = 'score'):\n return \"%s\\t%d\\t%d\\t%s\\t%.2f\\t%s\" %(self.chr,self.start,self.end,self.name,self.__dict__[value],self.strand)","def test():\n LowerCaseStr().from_python('ABC')","def test_RNA_position_strand_equality(self):\n \n tool = pybedtools.create_interval_from_list(\"chr1 50 60 ENSMUSG1_1_83;ENSMUSG1_6_83 0 - 60 60\".split())\n location_dict = {\"ENSMUSG1\" : {\"strand\" : \"+\", \"regions\" : [(0,100),\n ] \n }\n }\n \n self.assertRaises(ValueError, RNA_position, tool, location_dict)","def test_get_consensus_assignment(self):\r\n in1 = [['Ab', 'Bc', 'De'],\r\n ['Ab', 'Bc', 'Fg', 'Hi'],\r\n ['Ab', 'Bc', 'Fg', 'Jk']]\r\n\r\n # defaults\r\n params = {'id_to_taxonomy_fp': self.id_to_tax1_fp,\r\n 'reference_sequences_fp': self.refseqs1_fp}\r\n expected = (['Ab', 'Bc', 'Fg'], 2. / 3., 3)\r\n t = UclustConsensusTaxonAssigner(params)\r\n self.assertEqual(t._get_consensus_assignment(in1),\r\n expected)\r\n\r\n # increased min_consensus_fraction yields decreased specificity\r\n params = {'id_to_taxonomy_fp': self.id_to_tax1_fp,\r\n 'reference_sequences_fp': self.refseqs1_fp,\r\n 'min_consensus_fraction': 0.99}\r\n expected = (['Ab', 'Bc'], 1.0, 3)\r\n t = UclustConsensusTaxonAssigner(params)\r\n self.assertEqual(t._get_consensus_assignment(in1),\r\n expected)\r\n\r\n # if only a single input assignment, it is returned as consensus\r\n in2 = [['Ab', 'Bc', 'De']]\r\n\r\n # increased min_consensus_fraction\r\n params = {'id_to_taxonomy_fp': self.id_to_tax1_fp,\r\n 'reference_sequences_fp': self.refseqs1_fp,\r\n 'min_consensus_fraction': 1.0}\r\n expected = (['Ab', 'Bc', 'De'], 1.0, 1)\r\n t = UclustConsensusTaxonAssigner(params)\r\n self.assertEqual(t._get_consensus_assignment(in2),\r\n expected)\r\n\r\n # decreased min_consensus_fraction\r\n params = {'id_to_taxonomy_fp': self.id_to_tax1_fp,\r\n 'reference_sequences_fp': self.refseqs1_fp,\r\n 'min_consensus_fraction': 0.0}\r\n expected = (['Ab', 'Bc', 'De'], 1.0, 1)\r\n t = UclustConsensusTaxonAssigner(params)\r\n self.assertEqual(t._get_consensus_assignment(in2),\r\n expected)\r\n\r\n # no consensus\r\n in2 = [['Ab', 'Bc', 'De'],\r\n ['Cd', 'Bc', 'Fg', 'Hi'],\r\n ['Ef', 'Bc', 'Fg', 'Jk']]\r\n\r\n # defaults\r\n params = {'id_to_taxonomy_fp': self.id_to_tax1_fp,\r\n 'reference_sequences_fp': self.refseqs1_fp}\r\n expected = (['Unassigned'], 1., 3)\r\n t = UclustConsensusTaxonAssigner(params)\r\n self.assertEqual(t._get_consensus_assignment(in2),\r\n expected)","def test_align_unaligned_seqs(self):\n res = align_unaligned_seqs(self.seqs1_fp, RNA)\n self.assertEqual(res.toFasta(), self.seqs1_aln)","def test_to_from_iupac_wrapper(self):\n from openff.toolkit.utils import OpenEyeToolkitWrapper\n\n assert (\n Molecule.from_iupac(\n \"benzene\", toolkit_registry=OpenEyeToolkitWrapper()\n ).to_iupac(toolkit_registry=OpenEyeToolkitWrapper())\n == \"benzene\"\n )","def testB():\n \n #Test first_inside_quotes():\n cunittest.assert_equals(\"cake\",first_inside_quotes(\"The \\\"cake\\\" is a lie\"))\n cunittest.assert_equals(\"cake\",\n first_inside_quotes(\"The \\\"cake\\\" is a \\\"lie\\\"\"))\n\n #Test get_lhs():\n cunittest.assert_equals(\"42 Euros\",get_lhs(\n '{lhs: \"42 Euros\",rhs: \"171.43569717129 Polish zloty\",error: \"\",icc: true}'))\n cunittest.assert_equals(\"0.7734 Canadian dollars\",\n get_lhs('{lhs: \"0.7734 Canadian dollars\",rhs: \"0.78231730165439 U.S. dollars\",error: \"\",icc: true}'))\n cunittest.assert_equals(\"\",get_lhs('{lhs: \"\",rhs: \"\",error: \"4\",icc: false}'))\n \n #Test get_rhs():\n cunittest.assert_equals(\"171.43569717129 Polish zloty\",\n get_rhs('{lhs: \"42 Euros\",rhs: \"171.43569717129 Polish zloty\",error: \"\",icc: true}'))\n cunittest.assert_equals(\"0.78231730165439 U.S. dollars\",\n get_rhs('{lhs: \"0.7734 Canadian dollars\",rhs: \"0.78231730165439 U.S. dollars\",error: \"\",icc: true}'))\n cunittest.assert_equals(\"\",get_rhs('{lhs: \"\",rhs: \"\",error: \"4\",icc: false}'))"],"string":"[\n \"def coding_strand_to_AA_unit_tests():\\n print \\\"input: GTTGACAGTACGTACAGGGAA, \\\"+\\\"output: \\\"+coding_strand_to_AA(\\\"GTTGACAGTACGTACAGGGAA\\\")+\\\", actual output: VDSTYRE\\\"\\n print \\\"input: TTATTGCTTATTATCATG, \\\"+\\\"output: \\\"+coding_strand_to_AA(\\\"TTATTGCTTATTATCATG\\\")+\\\", actual output: LLLIIM\\\"\\n print \\\"input: TTTTTAATTATGGTTTCTCCTACTGCTTATTAACATCAAAATAAAGATGAATGTTGGCGTGGT, \\\"+\\\"output: \\\"+coding_strand_to_AA(\\\"TTTTTAATTATGGTTTCTCCTACTGCTTATTAACATCAAAATAAAGATGAATGTTGGCGTGGT\\\")+\\\", actual output: FLIMVSPTAY|HQNKDECWRG\\\"\\n print \\\"input: TT, \\\" + \\\"output: \\\"+coding_strand_to_AA(\\\"TT\\\")+\\\", actual output: ERROR: The provided fragment is too short to contain any codons.\\\"\",\n \"def coding_strand_to_AA_unit_tests():\\n input_a='ATTATTATT'\\n expected_output='III'\\n actual_output=coding_strand_to_AA(input_a)\\n print 'Expected Output is ' + expected_output\\n print 'Actual Output is ' +actual_output\\n \\n input_a='ATGATGATT'\\n expected_output='MMI'\\n actual_output=coding_strand_to_AA(input_a)\\n print 'Expected Output is ' + expected_output\\n print 'Actual Output is ' +actual_output\\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def coding_strand_to_AA_unit_tests(dna, expected):\\n print coding_strand_to_AA(\\\"ATGCGA\\\")\\n print coding_strand_to_AA(\\\"ATGCCCGCTTT\\\")\\n print coding_strand_to_AA(\\\"GGTAAA\\\")\\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + coding_strand_to_AA(dna)\",\n \"def coding_strand_to_AA_unit_tests():\\n # YOUR IMPLEMENTATION HERE\\n input = [\\\"ATG\\\", \\\"ATGCEAFD\\\", \\\"FAS\\\"]\\n expected_output = [\\\"MR\\\", \\\"RDS\\\", \\\"FF\\\"]\\n actual = []\\n for i in input:\\n actual.append(coding_strand_to_AA(i))\\n print input \\n print actual\\n print expected_output\",\n \"def coding_strand_to_AA(dna):\\n list1 = get_codons(dna)\\n string = ''\\n for codon in list1:\\n try:\\n string = string + aa_table[codon]\\n except KeyError:\\n continue\\n return string\",\n \"def coding_strand_to_AA(dna):\\n coding_strand = ''\\n for i in range(len(dna)/3):\\n aa = dna[3*i:(3*i)+3]\\n coding_strand += aa_table[aa]\\n return coding_strand\",\n \"def coding_strand_to_AA(dna):\\n dna_codons = split_into_codons(dna)\\n i = 0\\n aa_string = ''\\n while i < len(dna_codons):\\n if len(dna_codons[i]) == 3:\\n amino_acid = aa_table[dna_codons[i]]\\n aa_string += amino_acid\\n i += 1\\n return aa_string\",\n \"def coding_strand_to_AA(dna):\\n l = len(dna)\\n res = []\\n for i in range(0, l, 3):\\n s = dna[i: i + 3]\\n for j in range(len(codons)):\\n# for codon in codons[j]:\\n# if codon == s:\\n# res.append(aa[j])\\n# break;\\n if s in codons[j]: # [WOW] Python is really nice unlike C, yay!!\\n res.append(aa[j])\\n return collapse(res)\",\n \"def coding_strand_to_AA(dna):\\n #inital conditions\\n protein = ''\\n i = 0\\n\\n #for the length of DNA, translate each codon in an ORF to an amino acid\\n while i < (len(dna)-2):\\n codon = dna[i:i+3] \\n amino_acid = aa_table[codon]\\n protein= protein + amino_acid\\n i += 3\\n\\n #return the string of amino acids\\n return protein\",\n \"def coding_strand_to_AA(dna):\\n dnainp = dna\\n protein = ''\\n if len(dnainp)<3:\\n return \\\"ERROR: The provided fragment is too short to contain any codons.\\\"\\n# elif len(dnainp)%3 is not 0:\\n# print \\\"Warning: The provided DNA fragment does not contain an integer number of codons. Excess bases were leftout.\\\"\\n while len(dnainp) >=3:\\n cod = dnainp[:3]\\n for i in codons:\\n for j in i:\\n if j == cod:\\n protein = protein + aa[codons.index(i)]\\n dnainp = dnainp[3:]\\n return protein\",\n \"def coding_strand_to_AA(dna):\\n Seq = ''\\n for i in range(0,len(dna),3): \\n triple = dna[i:i+3]\\n print triple\\n for k in range(len(codons)):\\n if triple in codons[k]: \\n print \\\"Casey Rocks\\\"\\n print codons[k]\\n amino = aa[k]\\n Seq+=amino\\n return Seq\",\n \"def coding_strand_to_AA(dna):\\n num_codons = int(len(dna)/3)\\n num = 0\\n list_codons = []\\n aacids = ''\\n while num < num_codons:\\n num_start = int(num*3)\\n num_end = int(num*3 + 3)\\n list_codons.append(dna[num_start:num_end])\\n num = num + 1\\n for element in list_codons:\\n thing = aa_table[element]\\n aacids = aacids + thing\\n return aacids\",\n \"def coding_strand_to_AA(dna):\\n amino_acid = ''\\n i = 0\\n while i + 3 < len(dna) + 1:\\n amino_acid += aa_table[dna[i:i+3]]\\n i += 3\\n return amino_acid\",\n \"def coding_strand_to_AA(dna):\\n protein=''\\n for i in range(0,len(dna),3):\\n\\t if dna[i:i+3] in aa_table.keys():\\n\\t \\tprotein += aa_table[dna[i:i+3]]\\n return protein\",\n \"def test_fasta(self):\\n aln2fasta = hhsuite.AlignmentToFasta()\\n self.assertEqual(\\n aln2fasta.fasta(self.hit, \\\"A-E----\\\"),\\n \\\">Query\\\\nJKLMNOP\\\\n>Template\\\\nA-E----\\\\n\\\")\",\n \"def coding_strand_to_AA(dna):\\n amino_acid=\\\"\\\"\\n for i in range(0, len(dna), 3):\\n mycodon=dna[i:i+3]\\n # print'this is my codon'\\n #print mycodon\\n for j in range(len(codons)):\\n for k in range(len(codons[j])):\\n #print codons[j][k]\\n if codons[j][k] == mycodon:\\n #print aa[j]\\n amino_acid += aa[j]\\n return amino_acid\\n \\n #step uno break apart string into groups of three\\n #find sequence +find index\\n #then connect to amino acids \",\n \"def coding_strand_to_AA(dna):\\n s = \\\"\\\"\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitialize empty list\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n for i in range(0, len(dna)-2, 3):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# for range of length of dna, indexes w/ step 3 (to isolate codons)\\n \\t\\tamino_acid = aa_table[dna[i:i+3]]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# translates each codon to an amino acid\\n \\t\\ts = s + amino_acid \\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# adds amino acid to list\\n return s \\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns list of amino acids\",\n \"def test_to_dna(self):\\n r = self.RNA(\\\"TCA\\\")\\n self.assertEqual(str(r), \\\"UCA\\\")\\n self.assertEqual(str(r.to_dna()), \\\"TCA\\\")\",\n \"def test_conversion(self):\\n r = self.RNA(\\\"TCAtu\\\")\\n self.assertEqual(str(r), \\\"UCAUU\\\")\\n\\n d = self.DNA(\\\"UCAtu\\\")\\n self.assertEqual(str(d), \\\"TCATT\\\")\",\n \"def aa(seq):\\n global codontable\\n seq = seq.upper()\\n if codontable is None:\\n # TODO: figure out the right place for the pre-computed information here\\n bases = ['T', 'C', 'A', 'G']\\n codons = [a+b+c for a in bases for b in bases for c in bases]\\n codons = codons + list(map(lambda x: x.lower(), codons))\\n amino_acids = 'FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG'\\n amino_acids = amino_acids + amino_acids.lower()\\n codontable = dict(zip(codons, amino_acids))\\n res = ''\\n for i in range(0, len(seq) - 2, 3):\\n res += codontable[seq[i:(i+3)]]\\n return res\",\n \"def get_aa (tRNA):\\n\\tpass\",\n \"def test_amino_acid_slicing(self):\\n chrom_result = [None, \\\"Y\\\", \\\"Y\\\", \\\"Y\\\", None, None, None]\\n for i in xrange(len(chrom_result)):\\n self.assertEqual(self.t.chromosome_coordinate_to_amino_acid(i, self.chrom_seq), chrom_result[i])\\n cds_result = [\\\"Y\\\", \\\"Y\\\", \\\"Y\\\", None]\\n for i in xrange(len(cds_result)):\\n self.assertEqual(self.t.cds_coordinate_to_amino_acid(i, self.chrom_seq), cds_result[i])\\n transcript_result = [None, \\\"Y\\\", \\\"Y\\\", \\\"Y\\\", None, None, None, None]\\n for i in xrange(len(transcript_result)):\\n self.assertEqual(self.t.transcript_coordinate_to_amino_acid(i, self.chrom_seq), transcript_result[i])\",\n \"def test_to_fasta(self):\\n even = \\\"TCAGAT\\\"\\n odd = even + \\\"AAA\\\"\\n even_dna = self.SEQ(even, name=\\\"even\\\")\\n odd_dna = self.SEQ(odd, name=\\\"odd\\\")\\n self.assertEqual(even_dna.to_fasta(), \\\">even\\\\nTCAGAT\\\\n\\\")\\n # set line wrap to small number so we can test that it works\\n self.assertEqual(even_dna.to_fasta(block_size=2), \\\">even\\\\nTC\\\\nAG\\\\nAT\\\\n\\\")\\n self.assertEqual(odd_dna.to_fasta(block_size=2), \\\">odd\\\\nTC\\\\nAG\\\\nAT\\\\nAA\\\\nA\\\\n\\\")\\n # check that changing the linewrap again works\\n self.assertEqual(even_dna.to_fasta(block_size=4), \\\">even\\\\nTCAG\\\\nAT\\\\n\\\")\",\n \"def test_to_fasta(self):\\n even = \\\"TCAGAT\\\"\\n odd = even + \\\"AAA\\\"\\n even_dna = self.SequenceClass(even, name=\\\"even\\\")\\n odd_dna = self.SequenceClass(odd, name=\\\"odd\\\")\\n self.assertEqual(even_dna.to_fasta(), \\\">even\\\\nTCAGAT\\\\n\\\")\\n # set line wrap to small number so we can test that it works\\n self.assertEqual(even_dna.to_fasta(block_size=2), \\\">even\\\\nTC\\\\nAG\\\\nAT\\\\n\\\")\\n self.assertEqual(odd_dna.to_fasta(block_size=2), \\\">odd\\\\nTC\\\\nAG\\\\nAT\\\\nAA\\\\nA\\\\n\\\")\\n # check that changing the linewrap again works\\n self.assertEqual(even_dna.to_fasta(block_size=4), \\\">even\\\\nTCAG\\\\nAT\\\\n\\\")\",\n \"def test_to_rna(self):\\n r = self.DNA(\\\"UCA\\\")\\n self.assertEqual(str(r), \\\"TCA\\\")\\n self.assertEqual(str(r.to_rna()), \\\"UCA\\\")\",\n \"def translateORFtoAAs(self,sequence,number):\\r\\n AAStringfromORF = str()\\r\\n startingM = int()\\r\\n for i in range(0,len(sequence)-2,3):\\r\\n if sequence[i:i+3] != \\\"AUG\\\":\\r\\n pass\\r\\n else:\\r\\n startingM = i\\r\\n for i in range(startingM,len(sequence)-2,3):\\r\\n x = self.tabletoTranslate(sequence[i:i+3])\\r\\n AAStringfromORF+=x\\r\\n if x == \\\"-\\\":\\r\\n self.listofSequences.append(AAStringfromORF.rstrip(\\\"-\\\").lstrip().rstrip())\\r\\n AAStringfromORF = str()\\r\\n break\",\n \"def main():\\n\\n args = get_args()\\n seq = args.seq.upper()\\n codon_to_aa = {\\n 'AAA': 'K',\\n 'AAC': 'N',\\n 'AAG': 'K',\\n 'AAU': 'N',\\n 'ACA': 'T',\\n 'ACC': 'T',\\n 'ACG': 'T',\\n 'ACU': 'T',\\n 'AGA': 'R',\\n 'AGC': 'S',\\n 'AGG': 'R',\\n 'AGU': 'S',\\n 'AUA': 'I',\\n 'AUC': 'I',\\n 'AUG': 'M',\\n 'AUU': 'I',\\n 'CAA': 'Q',\\n 'CAC': 'H',\\n 'CAG': 'Q',\\n 'CAU': 'H',\\n 'CCA': 'P',\\n 'CCC': 'P',\\n 'CCG': 'P',\\n 'CCU': 'P',\\n 'CGA': 'R',\\n 'CGC': 'R',\\n 'CGG': 'R',\\n 'CGU': 'R',\\n 'CUA': 'L',\\n 'CUC': 'L',\\n 'CUG': 'L',\\n 'CUU': 'L',\\n 'GAA': 'E',\\n 'GAC': 'D',\\n 'GAG': 'E',\\n 'GAU': 'D',\\n 'GCA': 'A',\\n 'GCC': 'A',\\n 'GCG': 'A',\\n 'GCU': 'A',\\n 'GGA': 'G',\\n 'GGC': 'G',\\n 'GGG': 'G',\\n 'GGU': 'G',\\n 'GUA': 'V',\\n 'GUC': 'V',\\n 'GUG': 'V',\\n 'GUU': 'V',\\n 'UAA': 'Stop',\\n 'UAC': 'Y',\\n 'UAG': 'Stop',\\n 'UAU': 'Y',\\n 'UCA': 'S',\\n 'UCC': 'S',\\n 'UCG': 'S',\\n 'UCU': 'S',\\n 'UGA': 'Stop',\\n 'UGC': 'C',\\n 'UGG': 'W',\\n 'UGU': 'C',\\n 'UUA': 'L',\\n 'UUC': 'F',\\n 'UUG': 'L',\\n 'UUU': 'F',\\n }\\n\\n k = 3\\n\\n # 1: for loop\\n # protein = ''\\n # for codon in [seq[i:i + k] for i in range(0, len(seq), k)]:\\n # aa = codon_to_aa.get(codon, '-')\\n # if aa == 'Stop':\\n # break\\n # protein += aa\\n\\n # 2: list comprehension, slice to remove Stop\\n # codons = [seq[i:i + k] for i in range(0, len(seq), k)]\\n # aa = [codon_to_aa.get(codon, '-') for codon in codons]\\n # if 'Stop' in aa:\\n # aa = aa[:aa.index('Stop')]\\n # print(''.join(aa))\\n\\n # 3: L.C. -> map(), slice -> takewhile\\n # codons = map(lambda i: seq[i:i + k], range(0, len(seq), k))\\n # aa = map(lambda codon: codon_to_aa.get(codon, '-'), codons)\\n # print(''.join(takewhile(lambda c: c != 'Stop', aa)))\\n\\n # 4: combine map()\\n # aa = map(lambda c: codon_to_aa.get(c, '-'),\\n # map(lambda i: seq[i:i + k], range(0, len(seq), k)))\\n # print(''.join(takewhile(lambda c: c != 'Stop', aa)))\\n\\n # 5: combine all\\n # print(''.join(\\n # takewhile(\\n # lambda c: c != 'Stop',\\n # map(lambda c: codon_to_aa.get(c, '-'),\\n # map(lambda i: seq[i:i + k], range(0, len(seq), k))))))\\n\\n # 6: Seq\\n print(str(Seq(args.seq).translate()).replace('*', ''))\",\n \"def test_assign_seqs_two_fastas_quals(self):\\r\\n\\r\\n # Handles single fasta and single qual\\r\\n file_data = {}\\r\\n file_data['fasta_files'] = [self.valid_fasta_file_no_errors,\\r\\n self.valid_fasta_file_no_errors]\\r\\n file_data['qual_files'] = [self.valid_qual_file_no_errors,\\r\\n self.valid_qual_file_no_errors]\\r\\n file_data['demultiplexed_seqs_f'] = FakeOutFile()\\r\\n file_data['demultiplexed_qual_f'] = FakeOutFile()\\r\\n\\r\\n ids_bcs_added_field = {('AACTCGTCGATG', ''): 's1',\\r\\n ('AGCAGCACTTGT', ''): 's2', ('ACCGCAGAGTCA', ''): 's3'}\\r\\n bc_lens = [12]\\r\\n all_bcs = ['AACTCGTCGATG', 'AGCAGCACTTGT', 'ACCGCAGAGTCA']\\r\\n keep_barcode = False\\r\\n barcode_type = \\\"golay_12\\\"\\r\\n max_bc_errors = 1.5\\r\\n start_index = 1\\r\\n write_unassigned_reads = False\\r\\n disable_bc_correction = False\\r\\n added_demultiplex_field = None\\r\\n\\r\\n log_data, bc_freqs, seq_counts, corrected_bc_count =\\\\\\r\\n assign_seqs(file_data, ids_bcs_added_field, bc_lens, all_bcs,\\r\\n keep_barcode, barcode_type, max_bc_errors, start_index,\\r\\n write_unassigned_reads, disable_bc_correction,\\r\\n added_demultiplex_field)\\r\\n\\r\\n expected_demultiplexed_fasta_seq = '>s1_1 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\\\nCAGGACGAGACGAGGTT\\\\n>s3_2 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\\\nCCAGATTACGAGATTA\\\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\\\nGACCGATTACGATAACG\\\\n>s1_4 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\\\nCAGGACGAGACGAGGTT\\\\n>s3_5 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\\\nCCAGATTACGAGATTA\\\\n>s2_6 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\\\nGACCGATTACGATAACG\\\\n'\\r\\n expected_demultiplexed_qual_seq = '>s1_1 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\\\n30 26 11 11 29 20 19 16 24 17 29 28 11 27 14 24 24\\\\n>s3_2 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\\\n12 14 27 23 22 19 24 18 19 20 28 10 17 14 17 13\\\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\\\n10 20 16 20 25 27 22 28 16 22 16 18 12 13 16 25 17\\\\n>s1_4 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\\\n30 26 11 11 29 20 19 16 24 17 29 28 11 27 14 24 24\\\\n>s3_5 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\\\n12 14 27 23 22 19 24 18 19 20 28 10 17 14 17 13\\\\n>s2_6 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\\\n10 20 16 20 25 27 22 28 16 22 16 18 12 13 16 25 17\\\\n'\\r\\n self.assertEqual(file_data['demultiplexed_seqs_f'].data,\\r\\n expected_demultiplexed_fasta_seq)\\r\\n self.assertEqual(file_data['demultiplexed_qual_f'].data,\\r\\n expected_demultiplexed_qual_seq)\\r\\n\\r\\n expected_log_data = {'ACCGCAGAGTCA,s3': 2, 'AACTCGTCGATG,s1': 2,\\r\\n 'AGCAGCACTTGT,s2': 2}\\r\\n expected_bc_freqs = {'AACTCGTCGATG': 2, 'AGCAGCACTTGT': 2,\\r\\n 'ACCGCAGAGTCA': 2}\\r\\n expected_seq_counts = 6\\r\\n expected_corrected_bc_count = [0, 0]\\r\\n\\r\\n self.assertEqual(log_data, expected_log_data)\\r\\n self.assertEqual(bc_freqs, expected_bc_freqs)\\r\\n self.assertEqual(seq_counts, expected_seq_counts)\\r\\n self.assertEqual(corrected_bc_count, expected_corrected_bc_count)\",\n \"def test_sort_fasta_by_abundance(self):\\r\\n class FakeOutF(object):\\r\\n\\r\\n def __init__(self):\\r\\n self.s = \\\"\\\"\\r\\n\\r\\n def write(self, s):\\r\\n self.s += s\\r\\n\\r\\n actual = FakeOutF()\\r\\n expected = \\\"\\\"\\r\\n sort_fasta_by_abundance([], actual)\\r\\n self.assertEqual(actual.s, expected)\\r\\n\\r\\n # no sorting necessary\\r\\n actual = FakeOutF()\\r\\n expected1 = \\\"\\\\n\\\".join(['>s1', 'ACCGT', '>s2 comment', 'ATTGC', ''])\\r\\n expected2 = \\\"\\\\n\\\".join(['>s2 comment', 'ATTGC', '>s1', 'ACCGT', ''])\\r\\n sort_fasta_by_abundance(\\r\\n ['>s1',\\r\\n 'ACCGT',\\r\\n '>s2 comment',\\r\\n 'ATTGC'],\\r\\n actual)\\r\\n # order is unimportant here\\r\\n self.assertTrue(actual.s == expected1 or actual.s == expected2)\\r\\n\\r\\n # sorting necessary\\r\\n actual = FakeOutF()\\r\\n inseqs = ['>s1', 'ACCGT',\\r\\n '>s2 comment', 'ATTGC',\\r\\n '>s3 blah', 'ATTGC']\\r\\n expected = \\\"\\\\n\\\".join(['>s2 comment', 'ATTGC',\\r\\n '>s3 blah', 'ATTGC',\\r\\n '>s1', 'ACCGT', ''])\\r\\n sort_fasta_by_abundance(inseqs, actual)\\r\\n self.assertEqual(actual.s, expected)\",\n \"def get_AA_subs(s):\\r\\n test_seq = s.toseq()[70:217].translate() #Translate the mutated region\\r\\n substitutions = []\\r\\n \\r\\n for i in range(len(test_seq)):\\r\\n if test_seq[i] != align_temp[i]:\\r\\n substitutions.append(''.join([str(align_temp[i]),\\r\\n str(i+48),\\r\\n str(test_seq[i]),\\r\\n ' ']))\\r\\n \\r\\n return ''.join(substitutions).strip()\",\n \"def test_amino_acid_slicing(self):\\n chrom_result = [None, None, None, None, \\\"R\\\", \\\"R\\\", None, \\\"R\\\", \\\"A\\\", \\\"A\\\", None, None,\\n \\\"A\\\", None, None, None]\\n for i in xrange(len(chrom_result)):\\n self.assertEqual(self.t.chromosome_coordinate_to_amino_acid(i, self.chrom_seq), chrom_result[i])\\n cds_result = [\\\"A\\\", \\\"A\\\", \\\"A\\\", \\\"R\\\", \\\"R\\\", \\\"R\\\", None]\\n for i in xrange(len(cds_result)):\\n self.assertEqual(self.t.cds_coordinate_to_amino_acid(i, self.chrom_seq), cds_result[i])\\n transcript_result = [None, None, \\\"A\\\", \\\"A\\\", \\\"A\\\", \\\"R\\\", \\\"R\\\", \\\"R\\\", None, None, None]\\n for i in xrange(len(transcript_result)):\\n self.assertEqual(self.t.transcript_coordinate_to_amino_acid(i, self.chrom_seq), transcript_result[i])\",\n \"def test_assign_seqs_fasta_plus_qual(self):\\r\\n\\r\\n # Handles single fasta and single qual\\r\\n file_data = {}\\r\\n file_data['fasta_files'] = [self.valid_fasta_file_no_errors]\\r\\n file_data['qual_files'] = [self.valid_qual_file_no_errors]\\r\\n file_data['demultiplexed_seqs_f'] = FakeOutFile()\\r\\n file_data['demultiplexed_qual_f'] = FakeOutFile()\\r\\n\\r\\n ids_bcs_added_field = {('AACTCGTCGATG', ''): 's1',\\r\\n ('AGCAGCACTTGT', ''): 's2', ('ACCGCAGAGTCA', ''): 's3'}\\r\\n bc_lens = [12]\\r\\n all_bcs = ['AACTCGTCGATG', 'AGCAGCACTTGT', 'ACCGCAGAGTCA']\\r\\n keep_barcode = False\\r\\n barcode_type = \\\"golay_12\\\"\\r\\n max_bc_errors = 1.5\\r\\n start_index = 1\\r\\n write_unassigned_reads = False\\r\\n disable_bc_correction = False\\r\\n added_demultiplex_field = None\\r\\n\\r\\n log_data, bc_freqs, seq_counts, corrected_bc_count =\\\\\\r\\n assign_seqs(file_data, ids_bcs_added_field, bc_lens, all_bcs,\\r\\n keep_barcode, barcode_type, max_bc_errors, start_index,\\r\\n write_unassigned_reads, disable_bc_correction,\\r\\n added_demultiplex_field)\\r\\n\\r\\n expected_demultiplexed_fasta_seq = \\\">s1_1 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\\\nCAGGACGAGACGAGGTT\\\\n>s3_2 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\\\nCCAGATTACGAGATTA\\\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\\\nGACCGATTACGATAACG\\\\n\\\"\\r\\n expected_demultiplexed_qual_seq = '>s1_1 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\\\n30 26 11 11 29 20 19 16 24 17 29 28 11 27 14 24 24\\\\n>s3_2 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\\\n12 14 27 23 22 19 24 18 19 20 28 10 17 14 17 13\\\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\\\n10 20 16 20 25 27 22 28 16 22 16 18 12 13 16 25 17\\\\n'\\r\\n\\r\\n self.assertEqual(file_data['demultiplexed_seqs_f'].data,\\r\\n expected_demultiplexed_fasta_seq)\\r\\n self.assertEqual(file_data['demultiplexed_qual_f'].data,\\r\\n expected_demultiplexed_qual_seq)\\r\\n\\r\\n expected_log_data = {'ACCGCAGAGTCA,s3': 1, 'AACTCGTCGATG,s1': 1,\\r\\n 'AGCAGCACTTGT,s2': 1}\\r\\n expected_bc_freqs = {'AACTCGTCGATG': 1, 'AGCAGCACTTGT': 1,\\r\\n 'ACCGCAGAGTCA': 1}\\r\\n expected_seq_counts = 3\\r\\n expected_corrected_bc_count = [0, 0]\\r\\n\\r\\n self.assertEqual(log_data, expected_log_data)\\r\\n self.assertEqual(bc_freqs, expected_bc_freqs)\\r\\n self.assertEqual(seq_counts, expected_seq_counts)\\r\\n self.assertEqual(corrected_bc_count, expected_corrected_bc_count)\",\n \"def test_amino_acid_slicing(self):\\n chrom_result = [None, None, None, None, \\\"S\\\", \\\"S\\\", None, \\\"S\\\", \\\"G\\\", \\\"G\\\", None, None,\\n \\\"G\\\", None, None, None]\\n for i in xrange(len(chrom_result)):\\n try:\\n self.assertEqual(self.t.chromosome_coordinate_to_amino_acid(i, self.chrom_seq), chrom_result[i])\\n except:\\n assert False, (chrom_result, self.chrom_seq['chr1'][:], chrom_result[i], i)\\n cds_result = [\\\"S\\\", \\\"S\\\", \\\"S\\\", \\\"G\\\", \\\"G\\\", \\\"G\\\", None]\\n for i in xrange(len(cds_result)):\\n self.assertEqual(self.t.cds_coordinate_to_amino_acid(i, self.chrom_seq), cds_result[i])\\n transcript_result = [None, None, \\\"S\\\", \\\"S\\\", \\\"S\\\", \\\"G\\\", \\\"G\\\", \\\"G\\\", None, None, None]\\n for i in xrange(len(transcript_result)):\\n self.assertEqual(self.t.transcript_coordinate_to_amino_acid(i, self.chrom_seq), transcript_result[i])\",\n \"def generate_aa_sequence(chain):\\n\\n chain.strip()\\n chain_list = chain.split(' ')\\n # TODO: What if aa is not in the lookup\\n seq = [IUPAC_AA_codes[aa] for aa in chain_list]\\n return ''.join(seq)\",\n \"def test_xyz_to_ase(self):\\n atoms_1 = converter.xyz_to_ase(self.xyz1['dict'])\\n self.assertIsInstance(atoms_1, Atoms)\\n self.assertEqual(str(atoms_1.symbols), 'CH4')\\n np.testing.assert_array_equal(atoms_1.positions, [[0., 0., 0.],\\n [0.6300326, 0.6300326, 0.6300326],\\n [-0.6300326, -0.6300326, 0.6300326],\\n [-0.6300326, 0.6300326, -0.6300326],\\n [0.6300326, -0.6300326, -0.6300326]])\",\n \"def determine_aa_change( self ):\\n for k,v in self.obj_mi.hash_isoforms.iteritems(): #k = string that is isoform_id, v = Isoform instance\\n obj_tt = self.create_transcript_instances( k )\\n\\n #METHOD 1: get the original codon & mutated codon\\n # orig_codon = obj_tt.retrieve_containing_codon( self.snv_start, self.snv_strand )\\n # i_genome_pos = obj_tt.arr_genome_pos.index( self.snv_start )\\n # obj_tt.arr_nuc_seq[ i_genome_pos ] = self.base_alt\\n # mut_codon = obj_tt.retrieve_containing_codon( self.snv_start, self.snv_strand )\\n\\n\\n #METHOD 2: get the mutated codon\\n full_pos = self.snv_chrom + ':' + str( self.snv_start ) + '-' + str( self.snv_end )\\n hash_codon_info = obj_tt.get_mutated_codon( self.base_orig, self.base_alt, full_pos, self.snv_strand, True ) #output is hash -> {'codon_orig': codon_orig, 'codon_mut': codon_mut, 'aa_orig': aa_orig, 'aa_mut': aa_mut}\\n\\n\\n\\n ##TEST:: show the AA change based on mutation\\n # print \\\"hash_codon_info: \\\"\\n # print hash_codon_info\\n\\n # print \\\"gene strand & snv strand: \\\", obj_tt.iso_sj.strand, \\\" & \\\", self.snv_strand\\n # print \\\"original base > mutated base: \\\", self.base_orig, \\\" > \\\", self.base_alt\\n # print \\\"original codon > mutated codon: \\\", hash_codon_info['codon_orig'], \\\" > \\\", hash_codon_info['codon_mut']\\n # print \\\"original AA > mutated AA: \\\", hash_codon_info['aa_orig'], \\\" > \\\", hash_codon_info['aa_mut']\\n\\n\\n ##TEST:: determine consequence\\n print \\\"GV_DAAC 1: \\\"\\n obj_tt.alteration_consequence( self.base_alt, self.get_genomic_range(), self.snv_strand, self.alt_type )\\n \\n\\n ##TEST METHOD - SEE WHAT STEPS I NEED TO PERFORM\\n #TEST:: retrieve the original base & the mutated base\\n # i_genome_pos = obj_tt.arr_genome_pos.index( self.snv_start )\\n # orig_base = obj_tt.arr_nuc_seq[ i_genome_pos ]\\n # print \\\"k = \\\", k, \\\" & i_genome_pos = \\\", i_genome_pos, \\\" | orig_base = \\\", orig_base, \\\" & double_check = \\\", self.base_orig, \\\" & iso_sj.strand = \\\", obj_tt.iso_sj.strand, \\\" & mut strand = \\\", self.snv_strand\\n # hash_orig_codon = obj_tt.find_containing_codon( self.snv_start )\\n # print \\\"hash_orig = \\\", hash_orig_codon\\n # get_orig_codon = obj_tt.arr_nuc_seq[ hash_orig_codon['i_genome_start']:hash_orig_codon['i_genome_end'] + 1 ]\\n # str_orig_codon = ''.join( get_orig_codon ) if obj_tt.iso_sj.strand > 0 else ''.join( get_orig_codon[::-1] )\\n # print \\\"seq_orig = \\\", str_orig_codon, \\\" & type = \\\", type( get_orig_codon ), \\\" & rf = \\\", obj_tt.arr_rf[ hash_orig_codon['i_genome_start']:hash_orig_codon['i_genome_end'] + 1 ], \\\" & list_orig_codon = \\\", get_orig_codon\\n\\n # ##TEST:: make mutation\\n # obj_tt.arr_nuc_seq[ i_genome_pos ] = self.base_alt\\n # hash_mut_codon = obj_tt.find_containing_codon( self.snv_start )\\n # print \\\"hash_muts = \\\", hash_mut_codon\\n # get_mut_codon = obj_tt.arr_nuc_seq[ hash_mut_codon['i_genome_start']:hash_mut_codon['i_genome_end'] + 1 ]\\n # str_mut_codon = ''.join( get_mut_codon ) if obj_tt.iso_sj.strand > 0 else ''.join( get_mut_codon[::-1] )\\n # print \\\"seq_muts = \\\", str_mut_codon, \\\" & type = \\\", type( get_mut_codon ), \\\" & rf = \\\", obj_tt.arr_rf[ hash_mut_codon['i_genome_start']:hash_mut_codon['i_genome_end'] + 1 ], \\\" & list_mut_codon = \\\", get_mut_codon \\n\\n # ##TEST:: retrieve \\n # print \\\"AA: from \\\", Seq( str_orig_codon ).translate( to_stop = False ), \\\">\\\", Seq( str_mut_codon ).translate( to_stop = False )\\n\\n # try:\\n # i_genome_pos = obj_tt.arr_genome_pos.index( self.snv_start )\\n # orig_base = obj_tt.arr_nuc_seq[ i_genome_pos ]\\n # print \\\"k = \\\", k, \\\" & i_genome_pos = \\\", i_genome_pos, \\\" | orig_base = \\\", orig_base, \\\" & double_check = \\\", self.base_orig, \\\" & iso_sj.strand = \\\", obj_tt.iso_sj.strand, \\\" & mut strand = \\\", self.snv_strand\\n # hash_orig_codon = obj_tt.find_containing_codon( self.snv_start )\\n # print \\\"hash_orig = \\\", hash_orig_codon\\n # get_orig_codon = obj_tt.arr_nuc_seq[ hash_orig_codon['i_genome_start']:hash_orig_codon['i_genome_end'] ]\\n # print \\\"seq_orig = \\\", get_orig_codon\\n\\n # ##TEST:: make mutation\\n # obj_tt.arr_nuc_seq[ i_genome_pos ] = self.base_alt\\n # hash_mut_codon = obj_tt.find_containing_codon( self.snv_start )\\n # print \\\"hash_muts = \\\", hash_mut_codon\\n # get_mut_codon = obj_tt.arr_nuc_seq[ hash_mut_codon['i_genome_start']:hash_mut_codon['i_genome_end'] ]\\n # print \\\"seq_muts = \\\", get_mut_codon \\n\\n # ##TEST:: retrieve \\n # print \\\"AA: from \\\", Seq( orig_codon ).translate( to_stop = False ), \\\">\\\", Seq( mut_codon ).translate( to_stop = False )\\n # except:\\n # print \\\"ERROR:: for \\\", k, \\\", position does not exist: \\\", self.snv_start\\n # continue\\n\\n print \\\"////////////////////\\\\n\\\"\",\n \"def test_flip_strand(self):\\n # Flipping the strand\\n self.g.flip_strand()\\n\\n # Checking the reference and coded allele did change\\n self.assertEqual(self.g.reference, \\\"AGCGT\\\")\\n self.assertEqual(self.g.coded, \\\"G\\\")\\n\\n # Checking the genotypes did not changed\\n np.testing.assert_array_equal(\\n np.array([2, 2, 1, 2, 0, 1, 1, 1, np.nan, 0]),\\n self.g.genotypes,\\n )\\n\\n # The variant's allele should have changed\\n self.assertEqual((\\\"AGCGT\\\", \\\"G\\\"), self.g.variant.alleles)\\n\\n # The rest of the information should be the same\\n self.assertEqual(\\\"marker_1\\\", self.g.variant.name)\\n self.assertEqual(1, self.g.variant.chrom)\\n self.assertEqual(1234, self.g.variant.pos)\\n self.assertFalse(self.g.multiallelic)\",\n \"def output_aa_string(residues):\\n # Dictionary of 3 letter to 1 letter AA conversion\\n aa_dict = {'CYS': 'C', 'ASP': 'D', 'SER': 'S', 'GLN': 'Q', 'LYS': 'K',\\n 'ILE': 'I', 'PRO': 'P', 'THR': 'T', 'PHE': 'F', 'ASN': 'N',\\n 'GLY': 'G', 'HIS': 'H', 'LEU': 'L', 'ARG': 'R', 'TRP': 'W',\\n 'ALA': 'A', 'VAL':'V', 'GLU': 'E', 'TYR': 'Y', 'MET': 'M'}\\n\\n s = ''\\n for res in residues:\\n s = s + aa_dict.get(res.type)\\n return s\",\n \"def test_fasta_naming(self):\\n aln2fasta = hhsuite.AlignmentToFasta(q_name=\\\"foo\\\", t_name=\\\"{name}\\\")\\n self.assertEqual(\\n aln2fasta.fasta(self.hit, \\\"A-E----\\\"),\\n \\\">foo\\\\nJKLMNOP\\\\n>templatename\\\\nA-E----\\\\n\\\")\",\n \"def test_assign_seqs_fasta_only(self):\\r\\n\\r\\n # Initial test for single fasta file alone.\\r\\n file_data = {}\\r\\n file_data['fasta_files'] = [self.valid_fasta_file_no_errors]\\r\\n file_data['qual_files'] = []\\r\\n #file_data['mapping_file'] = self.valid_mapping_data_golay_upper\\r\\n file_data['demultiplexed_seqs_f'] = FakeOutFile()\\r\\n\\r\\n ids_bcs_added_field = {('AACTCGTCGATG', ''): 's1',\\r\\n ('AGCAGCACTTGT', ''): 's2', ('ACCGCAGAGTCA', ''): 's3'}\\r\\n bc_lens = [12]\\r\\n all_bcs = ['AACTCGTCGATG', 'AGCAGCACTTGT', 'ACCGCAGAGTCA']\\r\\n keep_barcode = False\\r\\n barcode_type = \\\"golay_12\\\"\\r\\n max_bc_errors = 1.5\\r\\n start_index = 1\\r\\n write_unassigned_reads = False\\r\\n disable_bc_correction = False\\r\\n added_demultiplex_field = None\\r\\n\\r\\n log_data, bc_freqs, seq_counts, corrected_bc_count =\\\\\\r\\n assign_seqs(file_data, ids_bcs_added_field, bc_lens, all_bcs,\\r\\n keep_barcode, barcode_type, max_bc_errors, start_index,\\r\\n write_unassigned_reads, disable_bc_correction,\\r\\n added_demultiplex_field)\\r\\n\\r\\n expected_demultiplexed_fasta_seq = \\\">s1_1 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\\\nCAGGACGAGACGAGGTT\\\\n>s3_2 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\\\nCCAGATTACGAGATTA\\\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\\\nGACCGATTACGATAACG\\\\n\\\"\\r\\n\\r\\n self.assertEqual(file_data['demultiplexed_seqs_f'].data,\\r\\n expected_demultiplexed_fasta_seq)\\r\\n\\r\\n expected_log_data = {'ACCGCAGAGTCA,s3': 1, 'AACTCGTCGATG,s1': 1,\\r\\n 'AGCAGCACTTGT,s2': 1}\\r\\n expected_bc_freqs = {'AACTCGTCGATG': 1, 'AGCAGCACTTGT': 1,\\r\\n 'ACCGCAGAGTCA': 1}\\r\\n expected_seq_counts = 3\\r\\n expected_corrected_bc_count = [0, 0]\\r\\n\\r\\n self.assertEqual(log_data, expected_log_data)\\r\\n self.assertEqual(bc_freqs, expected_bc_freqs)\\r\\n self.assertEqual(seq_counts, expected_seq_counts)\\r\\n self.assertEqual(corrected_bc_count, expected_corrected_bc_count)\",\n \"def gene_finder(dna):\\n all_orfs_both_strands = find_all_ORFs_both_strands(dna)\\n longest_fake_orf = longest_ORF_noncoding(dna, 20)\\n for element in all_orfs_both_strands:\\n if len(element) > longest_fake_orf:\\n a_a_string = coding_strand_to_AA(element)\\n else:\\n a_a_string = 'not longer than shuffle'\\n print(a_a_string)\",\n \"def test_regular_to_regular(self):\\n r = RNA.make_seq(\\\"AAA\\\", name=\\\"x\\\")\\n s = RNA.make_seq(r)\\n self.assertEqual(str(s), \\\"AAA\\\")\\n self.assertEqual(s.moltype, RNA)\\n self.assertEqual(s.name, \\\"x\\\")\",\n \"def translate_sequence(rna_sequence, genetic_code):\\n #Crate an empty list to store AA sequence:\\n AA_list = []\\n # Convert all rna_sequence to upper case:\\n rna_sequence=rna_sequence.upper()\\n # Convert all rna_sequence into a list:\\n rna_list = list(rna_sequence)\\n # This conditon will run if rna_sequence is at least 3 bases long, and only once it find start codon ,\\n #and stop once it finds stop codon.\\n while True:\\n if len(rna_list) > 2:\\n codon=''.join(rna_list[0:3])\\n #Delete first 3 bases since its alread added as codon, thus no longer needed.\\n del rna_list[0:3]\\n else:\\n break\\n #Using genetic code dictionary to find AA for each corresponding codon:\\n AA=genetic_code[codon]\\n #Break loop once it finds stop codon\\n if AA=='*':\\n break\\n #Add add translatable AA to the AA_list:\\n AA_list.append(AA)\\n return ''.join(AA_list)\",\n \"def do(s):\\r\\n return get_AA_subs(generate_mutString(s))\",\n \"def test_add_seqs_to_alignment(self):\\n res = add_seqs_to_alignment(self.seqs2_fp, self.seqs1_aln_fp, RNA)\\n self.assertEqual(res.toFasta(), self.add_seqs_aligned)\",\n \"def test_assign_seqs_two_fastas(self):\\r\\n\\r\\n # Handles two fasta files alone\\r\\n file_data = {}\\r\\n file_data['fasta_files'] = [self.valid_fasta_file_no_errors,\\r\\n self.valid_fasta_file_no_errors]\\r\\n file_data['qual_files'] = []\\r\\n #file_data['mapping_file'] = self.valid_mapping_data_golay_upper\\r\\n file_data['demultiplexed_seqs_f'] = FakeOutFile()\\r\\n\\r\\n ids_bcs_added_field = {('AACTCGTCGATG', ''): 's1',\\r\\n ('AGCAGCACTTGT', ''): 's2', ('ACCGCAGAGTCA', ''): 's3'}\\r\\n bc_lens = [12]\\r\\n all_bcs = ['AACTCGTCGATG', 'AGCAGCACTTGT', 'ACCGCAGAGTCA']\\r\\n keep_barcode = False\\r\\n barcode_type = \\\"golay_12\\\"\\r\\n max_bc_errors = 1.5\\r\\n start_index = 1\\r\\n write_unassigned_reads = False\\r\\n disable_bc_correction = False\\r\\n added_demultiplex_field = None\\r\\n\\r\\n log_data, bc_freqs, seq_counts, corrected_bc_count =\\\\\\r\\n assign_seqs(file_data, ids_bcs_added_field, bc_lens, all_bcs,\\r\\n keep_barcode, barcode_type, max_bc_errors, start_index,\\r\\n write_unassigned_reads, disable_bc_correction,\\r\\n added_demultiplex_field)\\r\\n\\r\\n expected_demultiplexed_fasta_seq = '>s1_1 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\\\nCAGGACGAGACGAGGTT\\\\n>s3_2 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\\\nCCAGATTACGAGATTA\\\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\\\nGACCGATTACGATAACG\\\\n>s1_4 ABCD0001 orig_bc=AACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=0\\\\nCAGGACGAGACGAGGTT\\\\n>s3_5 EFGH0002 orig_bc=ACCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=0\\\\nCCAGATTACGAGATTA\\\\n>s2_6 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\\\nGACCGATTACGATAACG\\\\n'\\r\\n self.assertEqual(file_data['demultiplexed_seqs_f'].data,\\r\\n expected_demultiplexed_fasta_seq)\\r\\n\\r\\n expected_log_data = {'ACCGCAGAGTCA,s3': 2, 'AACTCGTCGATG,s1': 2,\\r\\n 'AGCAGCACTTGT,s2': 2}\\r\\n expected_bc_freqs = {'AACTCGTCGATG': 2, 'AGCAGCACTTGT': 2,\\r\\n 'ACCGCAGAGTCA': 2}\\r\\n expected_seq_counts = 6\\r\\n expected_corrected_bc_count = [0, 0]\\r\\n\\r\\n self.assertEqual(log_data, expected_log_data)\\r\\n self.assertEqual(bc_freqs, expected_bc_freqs)\\r\\n self.assertEqual(seq_counts, expected_seq_counts)\\r\\n self.assertEqual(corrected_bc_count, expected_corrected_bc_count)\",\n \"def isaac_():\\n global aa, bb, cc, randcnt\\n\\n cc = cc + 1\\n bb = (bb + cc)\\n\\n for i in range(0, 256):\\n x = mm[i]\\n mod = i % 4\\n if mod == 0:\\n aa = aa ^ (aa << 13)\\n elif mod == 1:\\n aa = aa ^ (aa >> 6)\\n elif mod == 2:\\n aa = aa ^ (aa << 2)\\n elif mod == 3:\\n aa = aa ^ (aa >> 16)\\n\\n aa = mm[(i + 128) % 256] + aa\\n mm[i] = y = mm[(x >> 2) % 256] + aa + bb\\n randrsl[i] = bb = mm[(y >> 10) % 256] + x\\n\\n randcnt = 0\",\n \"def test_ACE(self): \\n self.assertFloatEqual(ACE(array([2,0])), 1.0, eps=0.001)\\n # next: just returns the number of species when all are abundant\\n self.assertFloatEqual(ACE(array([12,0,9])), 2.0, eps=0.001)\\n self.assertFloatEqual(ACE(array([12,2,8])), 3.0, eps=0.001)\\n self.assertFloatEqual(ACE(array([12,2,1])), 4.0, eps=0.001)\\n self.assertFloatEqual(ACE(array([12,1,2,1])), 7.0, eps=0.001)\\n self.assertFloatEqual(ACE(array([12,3,2,1])), 4.6, eps=0.001)\\n self.assertFloatEqual(ACE(array([12,3,6,1,10])), 5.62749672, eps=0.001)\",\n \"def test_correct_barcode_exact_match(self):\\r\\n barcode = \\\"GGAGACAAGGGA\\\"\\r\\n barcode_to_sample_id = {\\r\\n \\\"GGAGACAAGGGA\\\": \\\"s1\\\",\\r\\n \\\"ACACCTGGTGAT\\\": \\\"s2\\\"}\\r\\n correction_fn = None\\r\\n\\r\\n actual = correct_barcode(barcode, barcode_to_sample_id, correction_fn)\\r\\n expected = (0, barcode, False, 's1')\\r\\n self.assertEqual(actual, expected)\\r\\n\\r\\n correction_fn = decode_golay_12\\r\\n actual = correct_barcode(barcode, barcode_to_sample_id, correction_fn)\\r\\n expected = (0, barcode, False, 's1')\\r\\n self.assertEqual(actual, expected)\",\n \"def test_convert_input(self):\\n m, seq = DNA.make_seq(\\\"ACGGT--A\\\").parse_out_gaps()\\n aligned_seq = Aligned(m, seq)\\n mapped_gap, new_seq = _convert_input(aligned_seq, None)\\n self.assertIs(new_seq.moltype, DNA)\\n self.assertIs(mapped_gap, m)\\n self.assertIs(new_seq, seq)\\n mapped_gap, new_seq = _convert_input(\\\"ACGGT--A\\\", DNA)\\n self.assertEqual(str(mapped_gap), str(m))\\n self.assertEqual(str(new_seq), str(seq))\",\n \"def rs1_score(sequence):\\n import math\\n import numpy as np\\n seq = str(sequence).upper()\\n seq = list(seq)\\n matrix1 = np.zeros([len(sequence),4], dtype=int)\\n for i,item in enumerate(sequence):\\n if item == 'A':\\n matrix1[i,0] = 1\\n if item == 'T':\\n matrix1[i,1] = 1\\n if item == 'U':\\n matrix1[i,1] = 1\\n if item == 'C':\\n matrix1[i,2] = 1\\n if item == 'G':\\n matrix1[i,3] = 1\\n\\n\\n \\\"\\\"\\\"\\n Generates a binary matrix for DNA/RNA sequence, where each column is a possible\\n pair of adjacent bases, and each row is a position along the sequence.\\n Matrix column order is AA, AT, AC, AG, TA, TT, TC, TG, CA, CT, CC, CG, GA, GT, GC, GG\\n \\\"\\\"\\\"\\n sequence = sequence.replace('U','T')\\n pairwise_sequence = []\\n for i in range(len(sequence)):\\n if i < len(sequence)-1:\\n basepair = sequence[i]+sequence[i+1]\\n pairwise_sequence.append(basepair)\\n matrix2 = np.zeros([len(pairwise_sequence),16], dtype=int)\\n for i,item in enumerate(pairwise_sequence):\\n if item == 'AA':\\n matrix2[i,0] = 1\\n if item == 'AT':\\n matrix2[i,1] = 1\\n if item == 'AC':\\n matrix2[i,2] = 1\\n if item == 'AG':\\n matrix2[i,3] = 1\\n if item == 'TA':\\n matrix2[i,4] = 1\\n if item == 'TT':\\n matrix2[i,5] = 1\\n if item == 'TC':\\n matrix2[i,6] = 1\\n if item == 'TG':\\n matrix2[i,7] = 1\\n if item == 'CA':\\n matrix2[i,8] = 1\\n if item == 'CT':\\n matrix2[i,9] = 1\\n if item == 'CC':\\n matrix2[i,10] = 1\\n if item == 'CG':\\n matrix2[i,11] = 1\\n if item == 'GA':\\n matrix2[i,12] = 1\\n if item == 'GT':\\n matrix2[i,13] = 1\\n if item == 'GC':\\n matrix2[i,14] = 1\\n if item == 'GG':\\n matrix2[i,15] = 1\\n\\n\\n \\\"\\\"\\\"\\n Scoring matrix\\n \\\"\\\"\\\"\\n intersect = 0.59763615\\n low_gc = -0.2026259\\n high_gc = -0.1665878\\n\\n first_order = ['G02','A03','C03','C04','C05',\\n 'G05','A06','C06','C07','G07',\\n 'A12','A15','C15','A16','C16',\\n 'T16','A17','G17','C18','G18',\\n 'A19','C19','G20','T20','G21',\\n 'T21','C22','T22','T23','C24',\\n 'G24','T24','A25','C25','T25',\\n 'G28','T28','C29','G30']\\n first_scores = [-0.2753771,-0.3238875,0.17212887,-0.1006662,-0.2018029,\\n 0.24595663,0.03644004,0.09837684,-0.7411813,-0.3932644,\\n -0.466099,0.08537695,-0.013814,0.27262051,0.1190226,\\n -0.2859442,0.09745459,-0.1755462,-0.3457955,-0.6780964,\\n 0.22508903,-0.5077941,-0.4173736,-0.054307,0.37989937,\\n -0.0907126,0.05782332,-0.5305673,-0.8770074,-0.8762358,\\n 0.27891626,-0.4031022,-0.0773007,0.28793562,-0.2216372,\\n -0.6890167,0.11787758,-0.1604453,0.38634258]\\n first_order_scores = dict(zip(first_order,first_scores))\\n\\n second_order = ['GT02','GC05','AA06','TA06','GG07',\\n 'GG12','TA12','TC12','TT12','GG13',\\n 'GA14','GC14','TG17','GG19','TC19',\\n 'CC20','TG20','AC21','CG21','GA21',\\n 'GG21','TC22','CG23','CT23','AA24',\\n 'AG24','AG25','CG25','TG25','GT27',\\n 'GG29']\\n second_scores = [-0.6257787,0.30004332,-0.8348362,0.76062777,-0.4908167,\\n -1.5169074,0.7092612,0.49629861,-0.5868739,-0.3345637,\\n 0.76384993,-0.5370252,-0.7981461,-0.6668087,0.35318325,\\n 0.74807209,-0.3672668,0.56820913,0.32907207,-0.8364568,\\n -0.7822076,-1.029693,0.85619782,-0.4632077,-0.5794924,\\n 0.64907554,-0.0773007,0.28793562,-0.2216372,0.11787758,\\n -0.69774]\\n second_order_scores = dict(zip(second_order,second_scores))\\n\\n\\n # order 1 score matrix\\n \\\"\\\"\\\" row order == A T/U C G \\\"\\\"\\\"\\n first_matrix = np.zeros([4,30], dtype=float)\\n def posit(key):\\n return int(key[1:])-1\\n for k,v in first_order_scores.items():\\n if k[0] == 'A':\\n first_matrix[0,posit(k)] = v\\n elif k[0] == 'T':\\n first_matrix[1,posit(k)] = v\\n elif k[0] == 'C':\\n first_matrix[2,posit(k)] = v\\n elif k[0] == 'G':\\n first_matrix[3,posit(k)] = v\\n\\n\\n # order 2 score matrix\\n \\\"\\\"\\\" row order == AA AT AC AG TA TT TC TG CA CT CC CG GA GT GC GG \\\"\\\"\\\"\\n second_matrix = np.zeros([16,29], dtype=float)\\n for k,v in second_order_scores.items():\\n if k[0:2] == 'AA':\\n second_matrix[0,int(k[2:])-1] = v\\n if k[0:2] == 'AT':\\n second_matrix[1,int(k[2:])-1] = v\\n if k[0:2] == 'AC':\\n second_matrix[2,int(k[2:])-1] = v\\n if k[0:2] == 'AG':\\n second_matrix[3,int(k[2:])-1] = v\\n if k[0:2] == 'TA':\\n second_matrix[4,int(k[2:])-1] = v\\n if k[0:2] == 'TT':\\n second_matrix[5,int(k[2:])-1] = v\\n if k[0:2] == 'TC':\\n second_matrix[6,int(k[2:])-1] = v\\n if k[0:2] == 'TG':\\n second_matrix[7,int(k[2:])-1] = v\\n if k[0:2] == 'CA':\\n second_matrix[8,int(k[2:])-1] = v\\n if k[0:2] == 'CT':\\n second_matrix[9,int(k[2:])-1] = v\\n if k[0:2] == 'CC':\\n second_matrix[10,int(k[2:])-1] = v\\n if k[0:2] == 'CG':\\n second_matrix[11,int(k[2:])-1] = v\\n if k[0:2] == 'GA':\\n second_matrix[12,int(k[2:])-1] = v\\n if k[0:2] == 'GT':\\n second_matrix[13,int(k[2:])-1] = v\\n if k[0:2] == 'GC':\\n second_matrix[14,int(k[2:])-1] = v\\n if k[0:2] == 'GG':\\n second_matrix[15,int(k[2:])-1] = v\\n\\n item_gc = sequence[0][5:-5]\\n gc_count = item_gc.count('G') + item_gc.count('C')\\n if gc_count < 10:\\n gc_score = low_gc\\n else:\\n gc_score = high_gc\\n first_first = np.matmul(first_matrix,matrix1)\\n score_first = np.trace(first_first)\\n score_second = np.trace(np.matmul(second_matrix,matrix2))\\n score = (1/(1 + math.exp(-(intersect + gc_score + score_first + score_second))))\\n return score\",\n \"def transcribe_to_rna(strand):\\n # First, validate input\\n if not set(strand) <= set('{}{}{}{}'.format(Bases.Adenine, Bases.Thymine, Bases.Cytosine, Bases.Guanine)):\\n raise ValueError(\\\"Tried to transcribe strand with an invalid base.\\\")\\n transcribed_strand = strand.translate(transcription_rna_transtab)\\n return transcribed_strand\",\n \"def test_isc_rr_type_a_passing(self):\\n test_string = [\\n 'a',\\n 'A',\\n ]\\n result = rr_type_a.runTests(test_string, failureTests=False)\\n self.assertTrue(result[0])\",\n \"def test_a():\\n result = SECOND_TASK.start(\\\"aca\\\")\\n\\n assert result.replace(\\\"*\\\", \\\"\\\").replace(\\\"_\\\", \\\"\\\").replace(\\\"#\\\", \\\"\\\").replace(\\\"^\\\", \\\"\\\") == \\\"aac\\\"\",\n \"def test_run_fasta_checks(self):\\r\\n\\r\\n actual_fasta_report = run_fasta_checks(self.sample_fasta_fp,\\r\\n self.sample_mapping_fp)\\r\\n\\r\\n # All values should be zero\\r\\n expected_fasta_report = {'invalid_labels': '0.000',\\r\\n 'tree_subset': False,\\r\\n 'all_ids_found': False,\\r\\n 'same_seq_lens': False,\\r\\n 'barcodes_detected': '0.000',\\r\\n 'duplicate_labels': '0.000',\\r\\n 'duplicate_ids': [],\\r\\n 'invalid_seq_chars': '0.000',\\r\\n 'nosample_ids_map': '0.000',\\r\\n 'linkerprimers_detected': '0.000',\\r\\n 'tree_exact_match': False,\\r\\n 'barcodes_at_start': '0.000'}\\r\\n\\r\\n self.assertEqual(actual_fasta_report, expected_fasta_report)\",\n \"def test_encode():\",\n \"def test_amino_acid_slicing(self):\\n pass\",\n \"def test_amino_acid_slicing(self):\\n pass\",\n \"def test_2():\\n results = base_tests()\\n correct = {\\n \\\"Consequence\\\": \\\"synonymous_variant\\\",\\n \\\"Codons\\\": \\\"tgC/tgT\\\",\\n \\\"Amino_acids\\\": \\\"C\\\",\\n \\\"Gene\\\": \\\"ENSG00000130164\\\",\\n \\\"SYMBOL\\\": \\\"LDLR\\\",\\n \\\"Feature\\\": \\\"ENST00000558013\\\",\\n \\\"EXON\\\": \\\"2/18\\\",\\n \\\"PolyPhen\\\": \\\"\\\",\\n \\\"SIFT\\\": \\\"\\\",\\n \\\"Protein_position\\\": \\\"27/858\\\",\\n 'BIOTYPE\\\"': \\\"protein_coding\\\",\\n }\\n assert results[0] == correct\",\n \"def test_attempt_bc_correction_hamming8(self):\\r\\n\\r\\n curr_bc = \\\"AGCAGCAC\\\"\\r\\n all_bcs = [\\\"AGCAGAAC\\\", \\\"TGCAGTAC\\\", \\\"ACAGAGTC\\\"]\\r\\n barcode_type = \\\"hamming_8\\\"\\r\\n actual_bc, actual_errs = attempt_bc_correction(curr_bc,\\r\\n all_bcs, barcode_type)\\r\\n\\r\\n expected_bc = \\\"AGCAGAAC\\\"\\r\\n expected_errs = 0.5\\r\\n self.assertEqual(actual_bc, expected_bc)\\r\\n self.assertEqual(actual_errs, expected_errs)\",\n \"def find_all_ORFs_both_strands_unit_tests(dna, expected):\\n\\n print find_all_ORFs_both_strands(\\\"ATGCGAATGTAGCATCAAA\\\")\\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + find_all_ORFs_both_strands(dna)\",\n \"def test_compare_to_string(self):\\n r = self.RNA(\\\"UCC\\\")\\n self.assertEqual(r, \\\"UCC\\\")\",\n \"def test_double_sharp_2():\\n assert note_to_frequency(\\\"Ax4\\\") == note_to_frequency(\\\"B4\\\")\",\n \"def test_anglicize20to99():\\n print('Testing anglicize20to99')\\n\\n result = funcs.anglicize20to99(35)\\n introcs.assert_equals(\\\"thirty five\\\", result)\\n\\n result = funcs.anglicize20to99(50)\\n introcs.assert_equals(\\\"fifty\\\", result)\\n\\n result = funcs.anglicize20to99(99)\\n introcs.assert_equals(\\\"ninety nine\\\", result)\",\n \"def transcribe(strand):\\n # First, validate input\\n if not set(strand) <= set('{}{}{}{}'.format(Bases.Adenine, Bases.Thymine, Bases.Cytosine, Bases.Guanine)):\\n raise ValueError(\\\"Tried to transcribe strand with an invalid base.\\\")\\n transcribed_strand = strand.translate(transcription_transtab)\\n return transcribed_strand\",\n \"def test_check_seqs_qual_out(self):\\r\\n\\r\\n in_seqs = self.in_seqs_fixed_len_bc1\\r\\n bc_map = self.bc_map_fixed_len_bc1\\r\\n primer_seq_lens = self.primer_seq_lens_fixed_len_bc1\\r\\n all_primers = self.all_primers_fixed_len_bc1\\r\\n expected = expected_qual_fixed_len_bc1\\r\\n\\r\\n fd, out_fp = mkstemp(prefix=\\\"sample_seqs_\\\", suffix=\\\".fna.tmp\\\")\\r\\n close(fd)\\r\\n out_f = open(out_fp, \\\"w\\\")\\r\\n self._files_to_remove.append(out_f.name.replace('.tmp', ''))\\r\\n\\r\\n qual_out_f = FakeOutFile()\\r\\n\\r\\n actual = check_seqs(\\r\\n fasta_out=out_f,\\r\\n fasta_files=[in_seqs],\\r\\n starting_ix=0,\\r\\n valid_map=bc_map,\\r\\n qual_mappings=parse_qual_score(\\r\\n self.in_seqs_fixed_len_bc1_qual_scores),\\r\\n filters=[],\\r\\n barcode_len=12,\\r\\n keep_primer=False,\\r\\n keep_barcode=False,\\r\\n barcode_type=\\\"golay_12\\\",\\r\\n max_bc_errors=1.5,\\r\\n retain_unassigned_reads=False,\\r\\n attempt_bc_correction=True,\\r\\n primer_seqs_lens=primer_seq_lens,\\r\\n all_primers=all_primers,\\r\\n max_primer_mm=0,\\r\\n disable_primer_check=False,\\r\\n reverse_primers='disable',\\r\\n rev_primers={},\\r\\n qual_out=qual_out_f)\\r\\n\\r\\n self.assertEqual(qual_out_f.data, expected)\",\n \"def test_align_two_alignments(self):\\n res = align_two_alignments(self.align1_fp, self.align2_fp, RNA)\\n self.assertEqual(res.toFasta(), self.align_two_align)\",\n \"def test_basic():\\n a1 = astropy.coordinates.SkyCoord(10.625 * units.degree, 41.2 * units.degree)\\n c1 = coord.CelestialCoord(10.625 * coord.degrees, 41.2 * coord.degrees)\\n np.testing.assert_almost_equal(c1.rad, [a1.ra.rad, a1.dec.rad], decimal=12)\\n\\n a2 = astropy.coordinates.SkyCoord('00:42.5 +41:12', unit=(units.hourangle, units.deg))\\n c2 = coord.CelestialCoord(coord.Angle.from_hms('00:42:30'), coord.Angle.from_dms('41:12:00'))\\n np.testing.assert_almost_equal(c2.rad, [a2.ra.rad, a2.dec.rad], decimal=12)\\n\\n # astropy made different choices for the HMS and DMS string representations, but we can\\n # make it match our choice without too much trouble.\\n astr = a2.to_string(style='hmsdms', sep=':')\\n print('astr = ',astr)\\n astr_ra, astr_dec = astr.split()\\n cstr_ra = c2.ra.hms()\\n cstr_dec = c2.dec.dms(plus_sign=True)\\n assert astr_ra == cstr_ra\\n assert astr_dec == cstr_dec\",\n \"def test_get_consensus_assignment_overlapping_names(self):\\r\\n # here the 3rd level is different, but the 4th level is the same\\r\\n # across the three assignments. this can happen in practice if\\r\\n # three different genera are assigned, and under each there is\\r\\n # an unnamed species\\r\\n # (e.g., f__x;g__A;s__, f__x;g__B;s__, f__x;g__B;s__)\\r\\n # in this case, the assignment should be f__x.\\r\\n in1 = [['Ab', 'Bc', 'De', 'Jk'],\\r\\n ['Ab', 'Bc', 'Fg', 'Jk'],\\r\\n ['Ab', 'Bc', 'Hi', 'Jk']]\\r\\n\\r\\n params = {'id_to_taxonomy_fp': self.id_to_tax1_fp,\\r\\n 'reference_sequences_fp': self.refseqs1_fp}\\r\\n expected = (['Ab', 'Bc'], 1., 3)\\r\\n t = UclustConsensusTaxonAssigner(params)\\r\\n self.assertEqual(t._get_consensus_assignment(in1),\\r\\n expected)\\r\\n\\r\\n # here the third level is the same in 4/5 of the\\r\\n # assignments, but one of them (z, y, c) refers to a\\r\\n # different taxa since the higher levels are different.\\r\\n # the consensus value should be 3/5, not 4/5, to\\r\\n # reflect that.\\r\\n in2 = [['a', 'b', 'c'],\\r\\n ['a', 'd', 'e'],\\r\\n ['a', 'b', 'c'],\\r\\n ['a', 'b', 'c'],\\r\\n ['z', 'y', 'c']]\\r\\n expected = (['a', 'b', 'c'], 0.6, 5)\\r\\n t = UclustConsensusTaxonAssigner(params)\\r\\n self.assertEqual(t._get_consensus_assignment(in2),\\r\\n expected)\",\n \"def test_pcoa(self):\\r\\n res = pcoa(self.distmtx_txt)\\r\\n assert res # formatting tested elsewhere\\r\",\n \"def test_to_from_iupac(self):\\n from openff.toolkit.utils.toolkits import (\\n InvalidIUPACNameError,\\n UndefinedStereochemistryError,\\n )\\n\\n with pytest.raises(InvalidIUPACNameError):\\n Molecule.from_iupac(\\\".BETA.-PINENE\\\")\\n\\n # DrugBank_977, tagged as a problem molecule in earlier tests\\n bad_stereo_iupac = (\\n \\\"(~{E},3~{R},5~{S})-7-[4-(4-fluorophenyl)-6-isopropyl-2-\\\"\\n \\\"[methyl(methylsulfonyl)amino]pyrimidin-5-yl]-3,5-\\\"\\n \\\"dihydroxy-hept-6-enoic acid\\\"\\n )\\n with pytest.raises(UndefinedStereochemistryError):\\n Molecule.from_iupac(bad_stereo_iupac)\\n\\n cholesterol = Molecule.from_smiles(\\n \\\"C[C@H](CCCC(C)C)[C@H]1CC[C@@H]2[C@@]1(CC[C@H]3[C@H]2CC=C4[C@@]3(CC[C@@H](C4)O)C)C\\\"\\n )\\n\\n cholesterol_iupac = cholesterol.to_iupac()\\n\\n assert Molecule.are_isomorphic(\\n cholesterol, Molecule.from_iupac(cholesterol_iupac)\\n )\",\n \"async def test_amplification(test_handler, braf_amplification, prpf8_amplification):\\n q = \\\"BRAF Amplification\\\"\\n resp = await test_handler.normalize(q)\\n assertion_checks(resp.variation_descriptor, braf_amplification, q)\\n\\n # Gene with > 1 sequence location\\n q = \\\"PRPF8 AMPLIFICATION\\\"\\n resp = await test_handler.normalize(q)\\n assertion_checks(resp.variation_descriptor, prpf8_amplification, q)\\n\\n # Gene with no location. This should NOT return a variation\\n resp = await test_handler.normalize(\\\"IFNR amplification\\\")\\n assert resp.variation_descriptor is None\",\n \"def isochrone_to_aa(*args, **kwargs):\\n return isochrone_xv_to_aa(*args, **kwargs)\",\n \"def test_assign_seqs_error_correction(self):\\r\\n\\r\\n # Handles single fasta and single qual with error correction\\r\\n file_data = {}\\r\\n file_data['fasta_files'] = [self.valid_fasta_file_with_bc_errors]\\r\\n file_data['qual_files'] = [self.valid_qual_file_no_errors]\\r\\n file_data['demultiplexed_seqs_f'] = FakeOutFile()\\r\\n file_data['demultiplexed_qual_f'] = FakeOutFile()\\r\\n\\r\\n ids_bcs_added_field = {('AACTCGTCGATG', ''): 's1',\\r\\n ('AGCAGCACTTGT', ''): 's2', ('ACCGCAGAGTCA', ''): 's3'}\\r\\n bc_lens = [12]\\r\\n all_bcs = ['AACTCGTCGATG', 'AGCAGCACTTGT', 'ACCGCAGAGTCA']\\r\\n keep_barcode = False\\r\\n barcode_type = \\\"golay_12\\\"\\r\\n max_bc_errors = 1.5\\r\\n start_index = 1\\r\\n write_unassigned_reads = False\\r\\n disable_bc_correction = False\\r\\n added_demultiplex_field = None\\r\\n\\r\\n log_data, bc_freqs, seq_counts, corrected_bc_count =\\\\\\r\\n assign_seqs(file_data, ids_bcs_added_field, bc_lens, all_bcs,\\r\\n keep_barcode, barcode_type, max_bc_errors, start_index,\\r\\n write_unassigned_reads, disable_bc_correction,\\r\\n added_demultiplex_field)\\r\\n\\r\\n expected_demultiplexed_fasta_seq = '>s1_1 ABCD0001 orig_bc=TACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=1\\\\nCAGGACGAGACGAGGTT\\\\n>s3_2 EFGH0002 orig_bc=GCCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=1\\\\nCCAGATTACGAGATTA\\\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\\\nGACCGATTACGATAACG\\\\n'\\r\\n expected_demultiplexed_qual_seq = '>s1_1 ABCD0001 orig_bc=TACTCGTCGATG new_bc=AACTCGTCGATG bc_diffs=1\\\\n30 26 11 11 29 20 19 16 24 17 29 28 11 27 14 24 24\\\\n>s3_2 EFGH0002 orig_bc=GCCGCAGAGTCA new_bc=ACCGCAGAGTCA bc_diffs=1\\\\n12 14 27 23 22 19 24 18 19 20 28 10 17 14 17 13\\\\n>s2_3 IJKL0003 orig_bc=AGCAGCACTTGT new_bc=AGCAGCACTTGT bc_diffs=0\\\\n10 20 16 20 25 27 22 28 16 22 16 18 12 13 16 25 17\\\\n'\\r\\n self.assertEqual(file_data['demultiplexed_seqs_f'].data,\\r\\n expected_demultiplexed_fasta_seq)\\r\\n self.assertEqual(file_data['demultiplexed_qual_f'].data,\\r\\n expected_demultiplexed_qual_seq)\\r\\n\\r\\n expected_log_data = {'ACCGCAGAGTCA,s3': 1, 'AACTCGTCGATG,s1': 1,\\r\\n 'AGCAGCACTTGT,s2': 1}\\r\\n expected_bc_freqs = {'TACTCGTCGATG': 1, 'GCCGCAGAGTCA': 1,\\r\\n 'AGCAGCACTTGT': 1}\\r\\n expected_seq_counts = 3\\r\\n expected_corrected_bc_count = [2, 0]\\r\\n\\r\\n self.assertEqual(log_data, expected_log_data)\\r\\n self.assertEqual(bc_freqs, expected_bc_freqs)\\r\\n self.assertEqual(seq_counts, expected_seq_counts)\\r\\n self.assertEqual(corrected_bc_count, expected_corrected_bc_count)\",\n \"def test_DnaSequence(self):\\n x = DnaSequence(\\\"tcag\\\")\\n # note: no longer preserves case\\n self.assertEqual(x, \\\"TCAG\\\")\\n\\n x = DnaSequence(\\\"aaa\\\") + DnaSequence(\\\"ccc\\\")\\n # note: doesn't preserve case\\n self.assertEqual(x, \\\"AAACCC\\\")\\n assert x.moltype is DNA\\n self.assertRaises(AlphabetError, x.__add__, \\\"z\\\")\\n self.assertEqual(DnaSequence(\\\"TTTAc\\\").rc(), \\\"GTAAA\\\")\",\n \"def test_convert_azfp_01a_different_ranges(azfp_path):\\n azfp_01a_path = azfp_path / '17031001.01A'\\n azfp_xml_path = azfp_path / '17030815.XML'\\n\\n # Convert file\\n echodata = open_raw(\\n raw_file=azfp_01a_path, sonar_model='AZFP', xml_path=azfp_xml_path\\n )\\n assert echodata[\\\"Sonar/Beam_group1\\\"].backscatter_r.sel(channel='55030-125-1').dropna(\\n 'range_sample'\\n ).shape == (360, 438)\\n assert echodata[\\\"Sonar/Beam_group1\\\"].backscatter_r.sel(channel='55030-769-4').dropna(\\n 'range_sample'\\n ).shape == (360, 135)\\n\\n # check convention-required variables in the Platform group\\n check_platform_required_scalar_vars(echodata)\",\n \"def normalize_alleles_by_strand(snp_string):\\n # get alleles as tuple\\n allele1, allele2 = extract_alleles_from_snp_string(snp_string)\\n # get reverse compliment of bases and return\\n return REVERSE_COMPLIMENT[allele1], REVERSE_COMPLIMENT[allele2]\",\n \"def test_fastaqual_output(self):\\r\\n self.assertRaises(IOError, convert_fastaqual, self.fasta_file_path,\\r\\n output_directory=self.read_only_output_dir)\",\n \"def test_lowercase_input(self):\\n State(substance=\\\"water\\\")\\n State(substance=\\\"r22\\\")\\n State(substance=\\\"r134a\\\")\\n State(substance=\\\"ammonia\\\")\\n State(substance=\\\"propane\\\")\\n State(substance=\\\"air\\\")\\n State(substance=\\\"isobutane\\\")\\n State(substance=\\\"carbondioxide\\\")\\n State(substance=\\\"oxygen\\\")\\n State(substance=\\\"nitrogen\\\")\",\n \"def test_strand_symmetry(self):\\n from cogent3 import get_moltype\\n from cogent3.core.alignment import Aligned\\n\\n seq = DnaSequence(\\\"ACGGCTGAAGCGCTCCGGGTTTAAAACG\\\")\\n ssym = seq.strand_symmetry(motif_length=1)\\n assert_allclose(ssym.observed.array, [[7, 5], [7, 9]])\\n assert_allclose(ssym.expected.array, [[6, 6], [8, 8]])\\n\\n # RNA too\\n seq = seq.to_rna()\\n ssym = seq.strand_symmetry(motif_length=1)\\n assert_allclose(ssym.observed.array, [[7, 5], [7, 9]])\\n\\n # Aligned\\n seq = DnaSequence(\\\"ACGGCTGAAGCGCTCCGGGTTTAAAACG\\\")\\n m, s = seq.parse_out_gaps()\\n seq = Aligned(m, s)\\n ssym = seq.strand_symmetry(motif_length=1)\\n assert_allclose(ssym.observed.array, [[7, 5], [7, 9]])\\n\\n with self.assertRaises(TypeError):\\n text = get_moltype(\\\"text\\\")\\n m, s = text.make_seq(\\\"ACGGCTGAAGCGCTCCGGGTTTAAAACG\\\").parse_out_gaps()\\n s.strand_symmetry(motif_length=1)\\n\\n # with motif_length=2\\n seq = DnaSequence(\\\"AC GG CT GA AG CG CT CC GG GT TT AA AA CG\\\".replace(\\\" \\\", \\\"\\\"))\\n ssym = seq.strand_symmetry(motif_length=2)\\n self.assertLessEqual(len(ssym.observed.keys()), 8)\\n assert_allclose(ssym.observed[\\\"AA\\\"].to_array(), [2, 1])\\n assert_allclose(ssym.observed[\\\"CC\\\"].to_array(), [1, 2])\",\n \"def find_all_ORFs_both_strands_unit_tests():\\n print ''\\n print 'Begin Unit test Find_all_ORFs both tests'\\n input_a='ATGCGAGGGTAGATGGATTAG'\\n expected_output='[ATGCGAGGG, ATGGAT]'\\n actual_output=find_all_ORFs_both_strands(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\\n \\n \\n input_a='ATGCGAATGTAGCATCAAATAGATGTAG'\\n expected_output='[ATGCGAATG, ATG, ATGCTACATTCGCAT]'\\n actual_output=find_all_ORFs_both_strands(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output \\n print 'end'\\n print ''\",\n \"def test_double_sharp_1():\\n assert note_to_frequency(\\\"A##4\\\") == note_to_frequency(\\\"B4\\\")\",\n \"def test_is_AKs_preHandSimple_correct(self):\\n self.assertEqual(self.hand.getPreHandSimple(), 'AKs')\",\n \"def test_conversion_type(self):\\r\\n self.assertRaises(ValueError, convert_fastaqual_fastq,\\r\\n self.fasta_file_path, self.qual_file_path, conversion_type='soijdfl',\\r\\n output_directory=self.output_dir)\",\n \"def test_check_dna_chars_bcs(self):\\r\\n\\r\\n header =\\\\\\r\\n ['SampleID',\\r\\n 'BarcodeSequence',\\r\\n 'LinkerPrimerSequence',\\r\\n 'Description']\\r\\n mapping_data = [['s-1', 'ACGT', 'AARNCWSVDAA', 's1&data'],\\r\\n ['s2', 'CGTA', 'AAA1A', 's2_data']]\\r\\n errors = []\\r\\n\\r\\n errors = check_dna_chars_bcs(header, mapping_data, errors)\\r\\n\\r\\n expected_errors = []\\r\\n\\r\\n self.assertEqual(errors, expected_errors)\\r\\n\\r\\n # Should find no errors\\r\\n\\r\\n header =\\\\\\r\\n ['SampleID', 'BarcodeSequence', 'LinkerPrimerSequence',\\r\\n 'ReversePrimer', 'Description']\\r\\n mapping_data = [['s-1', 'ACGT', 'AARNCWSVDAA', 'ACGT', 's1&data'],\\r\\n ['s2', 'C1GTA', 'AAA1A', 'ACGTF', 's2_data']]\\r\\n errors = []\\r\\n\\r\\n errors = check_dna_chars_bcs(header, mapping_data, errors,\\r\\n has_barcodes=False)\\r\\n\\r\\n expected_errors = []\\r\\n\\r\\n self.assertEqual(errors, expected_errors)\\r\\n\\r\\n # Should find errors with has_barcodes=True\\r\\n\\r\\n header =\\\\\\r\\n ['SampleID', 'BarcodeSequence', 'LinkerPrimerSequence',\\r\\n 'ReversePrimer', 'Description']\\r\\n mapping_data = [['s-1', 'ACGT', 'AARNCWSVDAA', 'ACGT', 's1&data'],\\r\\n ['s2', 'CNGTA', 'AAA1A', 'ACGTF', 's2_data']]\\r\\n errors = []\\r\\n\\r\\n errors = check_dna_chars_bcs(header, mapping_data, errors,\\r\\n has_barcodes=True)\\r\\n\\r\\n expected_errors = ['Invalid DNA sequence detected: CNGTA\\\\t2,1']\\r\\n\\r\\n self.assertEqual(errors, expected_errors)\",\n \"def test_ModelDnaCodonSequence(self):\\n d = ArrayDnaCodonSequence(\\\"UUUCGU\\\")\\n self.assertEqual(str(d), \\\"TTTCGT\\\")\\n self.assertEqual(d._data, array([0, 28]))\\n self.assertEqual(str(d.to_rna()), \\\"UUUCGU\\\")\\n self.assertEqual(str(d.to_dna()), \\\"TTTCGT\\\")\",\n \"def test_convert():\",\n \"def test_make_fasta_rec(self):\\r\\n header = '>E2_1 FYI2DSB01B17QJ orig_bc=ATCACTAGTCAC new_bc=ATCACTAGTCAC bc_diffs=0'\\r\\n seq = 'CTGGTC'\\r\\n qual = map(int, '32 32 32 19 19 19'.split())\\r\\n self.assertEqual(make_fastq_rec(header, seq, qual),\\r\\n \\\"\\\"\\\"@E2_1 FYI2DSB01B17QJ orig_bc=ATCACTAGTCAC new_bc=ATCACTAGTCAC bc_diffs=0\\r\\nCTGGTC\\r\\n+E2_1 FYI2DSB01B17QJ orig_bc=ATCACTAGTCAC new_bc=ATCACTAGTCAC bc_diffs=0\\r\\nAAA444\\\"\\\"\\\")\",\n \"def test_init_data(self):\\n r = self.RNA(\\\"ucagg\\\")\\n # no longer preserves case\\n self.assertEqual(r, \\\"UCAGG\\\")\",\n \"def test_convert_adjective():\\n result = convert(\\\"adjective\\\")\\n assert result == \\\"adjectiveway\\\"\",\n \"def to_rna(dna_strand):\\n rta = [] # create an empty rna string\\n dna = list(dna_strand) # create a list of dna so iterating is possible\\n to_replace = {'C': 'G', 'G': 'C', 'T': 'A', 'A': 'U'}\\n for letter in dna:\\n if letter in to_replace.keys():\\n rta.append(to_replace[letter])\\n return ''.join(rta) # returning the rta string\",\n \"def translate_sequence(sequence, genetic_code = {'GUC': 'V', 'ACC': 'T', 'GUA': 'V', 'GUG': 'V', 'ACU': 'T', 'AAC': 'N', 'CCU': 'P', 'UGG': 'W', 'AGC': 'S', 'AUC': 'I', 'CAU': 'H', 'AAU': 'N', 'AGU': 'S', 'GUU': 'V', 'CAC': 'H', 'ACG': 'T', 'CCG': 'P', 'CCA': 'P', 'ACA': 'T', 'CCC': 'P', 'UGU': 'C', 'GGU': 'G', 'UCU': 'S', 'GCG': 'A', 'UGC': 'C', 'CAG': 'Q', 'GAU': 'D', 'UAU': 'Y', 'CGG': 'R', 'UCG': 'S', 'AGG': 'R', 'GGG': 'G', 'UCC': 'S', 'UCA': 'S', 'UAA': '*', 'GGA': 'G', 'UAC': 'Y', 'GAC': 'D', 'UAG': '*', 'AUA': 'I', 'GCA': 'A', 'CUU': 'L', 'GGC': 'G', 'AUG': 'M', 'CUG': 'L', 'GAG': 'E', 'CUC': 'L', 'AGA': 'R', 'CUA': 'L', 'GCC': 'A', 'AAA': 'K', 'AAG': 'K', 'CAA': 'Q', 'UUU': 'F', 'CGU': 'R', 'CGC': 'R', 'CGA': 'R', 'GCU': 'A', 'GAA': 'E', 'AUU': 'I', 'UUG': 'L', 'UUA': 'L', 'UGA': '*', 'UUC': 'F'}, start_pos = 0):\\n #find first orf\\n #first_orf_seq = find_first_orf(sequence)\\n\\n # ensure sequence is uppercase\\n seq = sequence.upper()\\n\\n #translate the sequence\\n protein = \\\"\\\"\\n for i in range(0, len(seq) - (len(seq) % 3), 3):\\n codon = seq[i:i + 3]\\n if genetic_code[codon] == \\\"*\\\":\\n break\\n protein += genetic_code[codon]\\n return protein\",\n \"def convert_bismark_add_strand_and_seq(indf, outfn):\\n logger.debug(f'Start add strand and seq to bismark cov file, total len={len(indf)}')\\n\\n outf = gzip.open(outfn, 'wt')\\n\\n for index, row in tqdm(indf.iterrows(), total=len(indf), desc='Bismark_cov'):\\n # if report_num and index % report_num == 0:\\n # logger.debug(f'processed index={index}')\\n chr = row['chr']\\n start = int(row['start']) # Keep raw 1-based format of bismark results\\n ret = get_dna_base_from_reference(chr, start - 1, ref_fasta=ref_fasta)\\n if ret[5] == 'C': # strand is +\\n strand = '+'\\n elif ret[5] == 'G':\\n strand = '-'\\n else:\\n raise Exception(f'We can not identify this bg-truth file with non-CG results, such as row={row}')\\n\\n outstr = '\\\\t'.join([chr, str(start), strand, str(row['mcount']), str(row['ccount']), ret[4:7]])\\n outf.write(f'{outstr}\\\\n')\\n outf.close()\\n logger.info(f'save to {outfn}')\\n\\n logger.debug(f'Finish add strand info task')\",\n \"def toBed(self,value = 'score'):\\n return \\\"%s\\\\t%d\\\\t%d\\\\t%s\\\\t%.2f\\\\t%s\\\" %(self.chr,self.start,self.end,self.name,self.__dict__[value],self.strand)\",\n \"def test():\\n LowerCaseStr().from_python('ABC')\",\n \"def test_RNA_position_strand_equality(self):\\n \\n tool = pybedtools.create_interval_from_list(\\\"chr1 50 60 ENSMUSG1_1_83;ENSMUSG1_6_83 0 - 60 60\\\".split())\\n location_dict = {\\\"ENSMUSG1\\\" : {\\\"strand\\\" : \\\"+\\\", \\\"regions\\\" : [(0,100),\\n ] \\n }\\n }\\n \\n self.assertRaises(ValueError, RNA_position, tool, location_dict)\",\n \"def test_get_consensus_assignment(self):\\r\\n in1 = [['Ab', 'Bc', 'De'],\\r\\n ['Ab', 'Bc', 'Fg', 'Hi'],\\r\\n ['Ab', 'Bc', 'Fg', 'Jk']]\\r\\n\\r\\n # defaults\\r\\n params = {'id_to_taxonomy_fp': self.id_to_tax1_fp,\\r\\n 'reference_sequences_fp': self.refseqs1_fp}\\r\\n expected = (['Ab', 'Bc', 'Fg'], 2. / 3., 3)\\r\\n t = UclustConsensusTaxonAssigner(params)\\r\\n self.assertEqual(t._get_consensus_assignment(in1),\\r\\n expected)\\r\\n\\r\\n # increased min_consensus_fraction yields decreased specificity\\r\\n params = {'id_to_taxonomy_fp': self.id_to_tax1_fp,\\r\\n 'reference_sequences_fp': self.refseqs1_fp,\\r\\n 'min_consensus_fraction': 0.99}\\r\\n expected = (['Ab', 'Bc'], 1.0, 3)\\r\\n t = UclustConsensusTaxonAssigner(params)\\r\\n self.assertEqual(t._get_consensus_assignment(in1),\\r\\n expected)\\r\\n\\r\\n # if only a single input assignment, it is returned as consensus\\r\\n in2 = [['Ab', 'Bc', 'De']]\\r\\n\\r\\n # increased min_consensus_fraction\\r\\n params = {'id_to_taxonomy_fp': self.id_to_tax1_fp,\\r\\n 'reference_sequences_fp': self.refseqs1_fp,\\r\\n 'min_consensus_fraction': 1.0}\\r\\n expected = (['Ab', 'Bc', 'De'], 1.0, 1)\\r\\n t = UclustConsensusTaxonAssigner(params)\\r\\n self.assertEqual(t._get_consensus_assignment(in2),\\r\\n expected)\\r\\n\\r\\n # decreased min_consensus_fraction\\r\\n params = {'id_to_taxonomy_fp': self.id_to_tax1_fp,\\r\\n 'reference_sequences_fp': self.refseqs1_fp,\\r\\n 'min_consensus_fraction': 0.0}\\r\\n expected = (['Ab', 'Bc', 'De'], 1.0, 1)\\r\\n t = UclustConsensusTaxonAssigner(params)\\r\\n self.assertEqual(t._get_consensus_assignment(in2),\\r\\n expected)\\r\\n\\r\\n # no consensus\\r\\n in2 = [['Ab', 'Bc', 'De'],\\r\\n ['Cd', 'Bc', 'Fg', 'Hi'],\\r\\n ['Ef', 'Bc', 'Fg', 'Jk']]\\r\\n\\r\\n # defaults\\r\\n params = {'id_to_taxonomy_fp': self.id_to_tax1_fp,\\r\\n 'reference_sequences_fp': self.refseqs1_fp}\\r\\n expected = (['Unassigned'], 1., 3)\\r\\n t = UclustConsensusTaxonAssigner(params)\\r\\n self.assertEqual(t._get_consensus_assignment(in2),\\r\\n expected)\",\n \"def test_align_unaligned_seqs(self):\\n res = align_unaligned_seqs(self.seqs1_fp, RNA)\\n self.assertEqual(res.toFasta(), self.seqs1_aln)\",\n \"def test_to_from_iupac_wrapper(self):\\n from openff.toolkit.utils import OpenEyeToolkitWrapper\\n\\n assert (\\n Molecule.from_iupac(\\n \\\"benzene\\\", toolkit_registry=OpenEyeToolkitWrapper()\\n ).to_iupac(toolkit_registry=OpenEyeToolkitWrapper())\\n == \\\"benzene\\\"\\n )\",\n \"def testB():\\n \\n #Test first_inside_quotes():\\n cunittest.assert_equals(\\\"cake\\\",first_inside_quotes(\\\"The \\\\\\\"cake\\\\\\\" is a lie\\\"))\\n cunittest.assert_equals(\\\"cake\\\",\\n first_inside_quotes(\\\"The \\\\\\\"cake\\\\\\\" is a \\\\\\\"lie\\\\\\\"\\\"))\\n\\n #Test get_lhs():\\n cunittest.assert_equals(\\\"42 Euros\\\",get_lhs(\\n '{lhs: \\\"42 Euros\\\",rhs: \\\"171.43569717129 Polish zloty\\\",error: \\\"\\\",icc: true}'))\\n cunittest.assert_equals(\\\"0.7734 Canadian dollars\\\",\\n get_lhs('{lhs: \\\"0.7734 Canadian dollars\\\",rhs: \\\"0.78231730165439 U.S. dollars\\\",error: \\\"\\\",icc: true}'))\\n cunittest.assert_equals(\\\"\\\",get_lhs('{lhs: \\\"\\\",rhs: \\\"\\\",error: \\\"4\\\",icc: false}'))\\n \\n #Test get_rhs():\\n cunittest.assert_equals(\\\"171.43569717129 Polish zloty\\\",\\n get_rhs('{lhs: \\\"42 Euros\\\",rhs: \\\"171.43569717129 Polish zloty\\\",error: \\\"\\\",icc: true}'))\\n cunittest.assert_equals(\\\"0.78231730165439 U.S. dollars\\\",\\n get_rhs('{lhs: \\\"0.7734 Canadian dollars\\\",rhs: \\\"0.78231730165439 U.S. dollars\\\",error: \\\"\\\",icc: true}'))\\n cunittest.assert_equals(\\\"\\\",get_rhs('{lhs: \\\"\\\",rhs: \\\"\\\",error: \\\"4\\\",icc: false}'))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.87473875","0.87198865","0.8259528","0.80338943","0.7117547","0.7100833","0.7016442","0.6978917","0.6892497","0.68684465","0.68575025","0.6806628","0.68016726","0.6616816","0.6553702","0.6507176","0.64127254","0.6405748","0.6327928","0.6140289","0.6128374","0.60628533","0.6053119","0.6050664","0.603404","0.6021932","0.6015046","0.5989927","0.5986825","0.5901212","0.5884028","0.58826125","0.58445185","0.5740331","0.57355726","0.5723268","0.56052077","0.5596301","0.5571231","0.5533036","0.5493829","0.54898083","0.54884744","0.5476896","0.5470593","0.5448481","0.54311603","0.54302156","0.54268426","0.5364997","0.53538626","0.53385854","0.53037256","0.53022814","0.52995795","0.5288744","0.52841675","0.52841675","0.52726287","0.5255185","0.5252454","0.52523476","0.5241484","0.52411586","0.52360684","0.52167803","0.52062094","0.5201111","0.51762706","0.51682204","0.5155352","0.51511157","0.5148384","0.51477295","0.5143908","0.5143784","0.51434976","0.5132984","0.51186407","0.51162297","0.510064","0.5095146","0.50943357","0.5090548","0.5082942","0.5078055","0.50771385","0.50721264","0.50716573","0.50684124","0.50655645","0.50574917","0.5052247","0.5050622","0.50477576","0.5034992","0.5018952","0.50141823","0.50139076","0.50110406"],"string":"[\n \"0.87473875\",\n \"0.87198865\",\n \"0.8259528\",\n \"0.80338943\",\n \"0.7117547\",\n \"0.7100833\",\n \"0.7016442\",\n \"0.6978917\",\n \"0.6892497\",\n \"0.68684465\",\n \"0.68575025\",\n \"0.6806628\",\n \"0.68016726\",\n \"0.6616816\",\n \"0.6553702\",\n \"0.6507176\",\n \"0.64127254\",\n \"0.6405748\",\n \"0.6327928\",\n \"0.6140289\",\n \"0.6128374\",\n \"0.60628533\",\n \"0.6053119\",\n \"0.6050664\",\n \"0.603404\",\n \"0.6021932\",\n \"0.6015046\",\n \"0.5989927\",\n \"0.5986825\",\n \"0.5901212\",\n \"0.5884028\",\n \"0.58826125\",\n \"0.58445185\",\n \"0.5740331\",\n \"0.57355726\",\n \"0.5723268\",\n \"0.56052077\",\n \"0.5596301\",\n \"0.5571231\",\n \"0.5533036\",\n \"0.5493829\",\n \"0.54898083\",\n \"0.54884744\",\n \"0.5476896\",\n \"0.5470593\",\n \"0.5448481\",\n \"0.54311603\",\n \"0.54302156\",\n \"0.54268426\",\n \"0.5364997\",\n \"0.53538626\",\n \"0.53385854\",\n \"0.53037256\",\n \"0.53022814\",\n \"0.52995795\",\n \"0.5288744\",\n \"0.52841675\",\n \"0.52841675\",\n \"0.52726287\",\n \"0.5255185\",\n \"0.5252454\",\n \"0.52523476\",\n \"0.5241484\",\n \"0.52411586\",\n \"0.52360684\",\n \"0.52167803\",\n \"0.52062094\",\n \"0.5201111\",\n \"0.51762706\",\n \"0.51682204\",\n \"0.5155352\",\n \"0.51511157\",\n \"0.5148384\",\n \"0.51477295\",\n \"0.5143908\",\n \"0.5143784\",\n \"0.51434976\",\n \"0.5132984\",\n \"0.51186407\",\n \"0.51162297\",\n \"0.510064\",\n \"0.5095146\",\n \"0.50943357\",\n \"0.5090548\",\n \"0.5082942\",\n \"0.5078055\",\n \"0.50771385\",\n \"0.50721264\",\n \"0.50716573\",\n \"0.50684124\",\n \"0.50655645\",\n \"0.50574917\",\n \"0.5052247\",\n \"0.5050622\",\n \"0.50477576\",\n \"0.5034992\",\n \"0.5018952\",\n \"0.50141823\",\n \"0.50139076\",\n \"0.50110406\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.83976924"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":92992,"cells":{"query":{"kind":"string","value":"Computes the reverse complementary sequence of DNA for the specfied DNA sequence"},"document":{"kind":"string","value":"def get_reverse_complement(dna):\n res = \"\";\n for c in dna:\n if c == 'A':\n res = 'T' + res\n elif c == 'T':\n res = 'A' + res\n elif c == 'G':\n res = 'C' + res\n elif c == 'C':\n res = 'G' + res\n return res"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_reverse_complement(dna):\n rev_comp = ''\n for i in range(0, len(dna)):\n nucleo = dna[i]\n comp = get_complement(nucleo)\n rev_comp = comp + rev_comp\n return rev_comp","def reverse_complement_strand(dna):\n reverse_complement = \"\"\n\n for character in dna[::-1]:\n if character == \"A\":\n reverse_complement += \"T\"\n elif character == \"T\":\n reverse_complement += \"A\"\n elif character == \"C\":\n reverse_complement += \"G\"\n elif character == \"G\":\n reverse_complement += \"C\"\n\n return reverse_complement","def get_reverse_complement(dna):\n reversed_dna_string = ''\n dna_reverse = dna[::-1]\n for i in range(len(dna)):\n dna_nucleotide = dna_reverse[i]\n reversed_dna_string += get_complement(dna_nucleotide)\n return reversed_dna_string","def reverse_complement_strand(dna):\n assert (is_dna(dna))\n return ''.join(_rev_mapping[nn] for nn in dna[::-1])","def get_reverse_complement(dna):\n reverseDNA = ''\n newDNA = ''\n for i in range(len(dna)): \n reverseDNA+= dna[-1-i]\n for k in range(len(dna)): \n if reverseDNA[k] == 'A': \n newDNA+='T'\n elif reverseDNA[k] =='T':\n newDNA+= 'A' \n elif reverseDNA[k] =='G':\n newDNA+= 'C'\n elif reverseDNA[k] =='C':\n newDNA+= 'G' \n return newDNA","def get_reverse_complement(dna):\n\n n = len(dna)\n\n i = 0\n\n reverse_dna = []\n\n for i in range(n):\n reverse_dna.append (get_complement(dna[n - 1 - i]))\n reverse_complement = ''.join(reverse_dna)\n return reverse_complement","def get_reverse_complement(dna):\r\n\r\n seq = Seq(dna)\r\n rev_seq = seq.reverse_complement()\r\n return str(rev_seq)","def get_reverse_complement(dna):\n \n dna = dna.replace('T','N')\n dna = dna.replace('A','T')\n dna = dna.replace('N','A')\n dna = dna.replace('C','N')\n dna = dna.replace('G','C')\n dna = dna.replace('N','G')\n dna = dna[::-1]\n return dna","def reverse_complement_RNA(RNAsequence):\n complement = \"\"\n for nucleotide in RNAsequence:\n if nucleotide == \"A\":\n complement = \"U\" + complement\n if nucleotide == \"C\":\n complement = \"G\" + complement\n if nucleotide == \"G\":\n complement = \"C\" + complement\n if nucleotide == \"U\":\n complement = \"A\" + complement\n return complement","def reverse_and_complement(sequence):\n #Convert all rna_sequence to upper case:\n sequence=sequence.upper()\n # Conver RNA sequence into a list\n rna_list = list(sequence)\n #reverse rna sequence:\n rna_list.reverse()\n #Create an empty list to store reverse complement seq.\n rev_c = []\n #Complement code corresponsing for all RNA bases\n complement = {'A' : 'U', 'C' : 'G', 'G': 'C', 'U': 'A'}\n #Looping through all the bases in complement RNA seq. of reversed RNA seq. using dictionary values.\n for i in rna_list:\n rev_c.append(complement[i])\n return ''.join(rev_c)","def get_reverse_complement(dna):\n l = [get_complement(char) for char in dna[::-1]]\n return ''.join(l)","def get_reverse_complement(dna):\n #set up initial empty strings for later use\n complement = \"\"\n reverse_complement = \"\"\n\n #for each element in the list of dna, get the complement and add it to an empty list\n for i in range(len(dna)):\n complement = complement + get_complement(dna[i]) \n\n #for each element in the list of complement, return the complement by calling the list in reverse\n for i in range(len(dna)):\n reverse_complement = reverse_complement + complement[len(dna)-1-i]\n\n return reverse_complement","def get_reverse_complement(dna):\n dna=\"ATCG\"\n b = list(dna)\n b.reverse()\n \"\".join(b)\n\n for n in range(0, len(b), 1):\n if b[n] == \"A\":\n b[n] = \"T\"\n elif b[n] == \"C\":\n b[n] = \"G\"\n elif b[n] == \"T\":\n b[n] = \"A\"\n elif b[n] == \"G\":\n b[n] = \"C\"\n \n print \"\".join(b)","def reverse_complementary(seq):\n\n complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\n return \"\".join(complement[n] for n in reversed(seq))","def rev_comp(dna):\n return dna[::-1].translate(maketrans('ATCG', 'TAGC'))","def reverse_rna_complement(seq):\n\n seq_upper = seq.isupper()\n\n seq = seq[::-1]\n\n seq = seq.upper()\n\n #compute complement\n seq = seq.replace('A','u')\n seq = seq.replace('T','a')\n seq = seq.replace('G','c')\n seq = seq.replace('C','g')\n\n if seq_upper:\n return seq.upper()\n else:\n return seq","def reverse_complement(dna: str):\n dna = dna.strip()\n result = [\" \"] * len(dna)\n for index, letter in enumerate(reversed(dna)):\n result[index] = complement_map[letter]\n return \"\".join(result)","def get_reverse_complement(dna):\n L=dna\n rdna=L[::-1]\n print rdna\n newrdna=\"\"\n for i in range(0,len(rdna)):\n if rdna[i]=='A':\n newrdna='T'+newrdna\n elif rdna[i]=='G':\n newrdna='C'+newrdna\n elif rdna[i]=='T':\n newrdna='A'+newrdna\n elif rdna[i]=='C':\n newrdna='G'+newrdna\n S=newrdna\n P=S[::-1]\n return P","def complement_strand(dna):\n reverse_complement = \"\"\n\n for character in dna[::-1]:\n if character == \"A\":\n reverse_complement += \"T\"\n elif character == \"T\":\n reverse_complement += \"A\"\n elif character == \"C\":\n reverse_complement += \"G\"\n elif character == \"G\":\n reverse_complement += \"C\"\n\n return reverse_complement","def get_reverse_complement(dna):\n reverse=[None]*len(dna)\n for i in range(0,len(dna)):\n \treverse[len(dna)-i-1]=get_complement(dna[i])\n s=''\n reverse=s.join(reverse)\n return reverse","def get_reverse_complement(dna):\n dna2 = get_complement(dna)\n dna3 = dna2[::-1]\n return str(dna3)","def get_reverse_complement(dna):\n rdna = dna[::-1]\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# reverses input\n\n rev_dna = \"\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# initializes empty string\n index = 0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitialize index\n while index < len(rdna):\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# while loop, ends at len(dna)-1\n \treverse_letter = get_complement(rdna[index])\t\t\t\t\t\t\t\t\t\t# gets the complement for the string\n \trev_dna = rev_dna + reverse_letter\t\t\t\t\t\t\t\t\t\t\t\t\t# adds the new letter to the string\n \tindex += 1\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# indexes up 1\n return rev_dna \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns string","def reverse_complement(seq):\n if sys.version_info.major == 2:\n conversion = string.maketrans('ACGTacgt','TGCAtgca')\n else:\n conversion = str.maketrans('ACGTacgt','TGCAtgca')\n\n comp = seq.translate(conversion)\n rev_comp = comp[::-1]\n return rev_comp","def reverse_complement(dna, reverse=True, complement=True):\n \n # Make translation table\n trans_table = string.maketrans('ATGCatgc', 'TACGtacg')\n \n # Make complement to DNA\n comp_dna = dna.translate(trans_table)\n \n # Output all as strings\n if reverse and complement:\n return comp_dna[::-1]\n if reverse and not complement:\n return dna[::-1]\n if complement and not reverse:\n return comp_dna\n if not complement and not reverse:\n return dna","def reverse_complement(sequence):\n\n #define complement dictionary\n complement_dictionary = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A', 'N': 'N' }\n\n #Reversing the string by using extended slice syntax which works by doing \"[begin:end:step]\", by leaving begin and end out and specifying a step of -1, it reverses a strings order.\n sequence = sequence[::-1]\n \n #Taking the complement by turning the sequence into a list of bases so I can turn a single base at a time into it's complement base using a list comprehension\n bases = list(sequence)\n bases = [complement_dictionary[base] for base in bases]#This takes a base from the bases list and switches it for its complement base\n\n #return the reverse complement by joining all of the bases from the list bases\n return ''.join(bases)","def ReverseComplement1(seq):\n seq_dict = {'A':'T','T':'A','G':'C','C':'G'}\n return \"\".join([seq_dict[base] for base in reversed(seq)])","def reversecomp(sequence):\n\tseqrc = \"\"\n\ttempzrev = sequence\n\ttempzrev = tempzrev.replace(\"T\",\"X\")\n\ttempzrev = tempzrev.replace(\"A\",\"T\")\n\ttempzrev = tempzrev.replace(\"X\",\"A\")\n\ttempzrev = tempzrev.replace(\"C\",\"Y\")\n\ttempzrev = tempzrev.replace(\"G\",\"C\")\n\ttempzrev = tempzrev.replace(\"Y\",\"G\")\n\ttemplist = list(tempzrev)\n\ttemplist.reverse()\n\tfor i in templist:\n\t\tseqrc += i\n\treturn seqrc","def reverse_complement(seq):\n\n # Initialize dict of complements\n complements = {\n 'A': 'T',\n 'C': 'G',\n 'T': 'A',\n 'G': 'C'\n }\n\n # Initialize reverse complement\n rev_seq = ''\n\n # Loop through and populate list with reverse complement\n for base in reversed(seq.upper()):\n rev_seq += complements[base] \n\n return rev_seq","def getSecondStrand(sequences):\n compDNA = []\n for dna in sequences:\n compDNAAux = dna.replace('A', 't')\n compDNAAux = compDNAAux.replace('T', 'a')\n compDNAAux = compDNAAux.replace('C', 'g')\n compDNAAux = compDNAAux.replace('G', 'c')\n compDNA.append(compDNAAux.upper())\n\n for i in range(0, len(compDNA)):\n compDNA[i] = compDNA[i][::-1]\n\n return compDNA","def reverse_complement(DNA, as_string=False, unreversed_order=False):\n comp_dict = {'A': 'T', 'T': 'A', 'C': 'G', 'G': 'C'}\n\n if unreversed_order:\n complements = [comp_dict[nuc] for nuc in DNA]\n else:\n complements = [comp_dict[nuc] for nuc in DNA[::-1]]\n\n if as_string:\n complements = \"\".join(complements)\n\n return complements","def reverse_complement(seq):\n return ''.join([BASE_TO_COMP[b] for b in seq][::-1])","def reverse_complement(sequence: str) -> str:\n complement_dict = sequence_utils.DNA_COMPLEMENT\n # If a base is not present in the vocabulary, we don't reverse complement it\n # in this function, and these sequences will get discarded downstream in the\n # TF Example generation pipeline.\n return ''.join(complement_dict.get(nt, nt) for nt in reversed(sequence))","def get_reverse_complement(sequence):\n return get_strand_complement(sequence)[::-1]","def complementary_seq(self):\n if not self.data['DNAseq']:\n self.complement_seq_var.set(0)\n self.warning('No DNA sequence loaded','You have to load a DNA sequence first')\n return\n compl={'A':'T','T':'A','C':'G','G':'C'}\n comDNA=''\n for base in self.data['DNAseq']:\n comDNA=comDNA+compl[base]\n self.data['DNAseq']=comDNA\n\n # Update\n self.update_sequence_window()\n return","def complement_this(seq):\n compliment_dict = {'A':'T', 'T':'A', 'C':'G', 'G':'C'}\n rev_seq = ''\n for nuc in seq:\n if nuc in ['A', 'T', 'G', 'C']:\n rev_seq += compliment_dict[nuc]\n return rev_seq","def reverseComplementer(self, ORFsequence):\r\n reverseComplement = str()\r\n reverserDict = {\"A\":\"U\",\"U\":\"A\",\"C\":\"G\",\"G\":\"C\"}\r\n reversedseq = ORFsequence[::-1]\r\n for nucleotide in reversedseq:\r\n reverseComplement+=reverserDict[nucleotide]\r\n return reverseComplement","def get_reverse_complement(sequence):\n seq = sequence.upper()\n return get_strand_complement(seq)[::-1]","def reverse_compliment(seq):\n compliment = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\n reverse = seq[::-1]\n rev_comp = ''.join([compliment[nt] for nt in reverse])\n return rev_comp","def reverseComplement(seq, alphabet='ACGT'):\n compl= dict(zip('ACGTNRYWSMKBHDV', 'TGCANYRWSKMVDHB'))\n return ''.join([compl[base]\n for base in seq.upper().replace('U', 'T')])[::-1]","def reverse_complement(dna):\n str = ''\n dict = {'C': 'G', 'G': 'C', 'A': 'T', 'T': 'A'}\n for char in dna:\n if char == 'C' or char == 'G' or char == 'T' or char == 'A':\n str = str + dict[char]\n else :\n str = 'invalid character entered, please check the input'\n break\n return str[::-1]","def revcomp(self, seq):\n tab = self.maketrans(b'ACNGT', b'TGNCA')\n return seq.translate(tab)[::-1]","def get_complementary_sequence(sequence):\n\n complementary_sequence = ''\n for char in sequence:\n complementary_sequence = complementary_sequence + get_complement(char)\n return complementary_sequence","def get_complement(sequence):\n #Convert all rna_sequence to upper case:\n sequence=sequence.upper()\n # Conver RNA sequence into a list\n rna_list=list(sequence)\n #Create an empty list to store complement sequence:\n comlement_sequence=[]\n #Complement code corresponsing for all RNA bases\n complement= {'A' : 'U', 'C' : 'G', 'G': 'C', 'U': 'A'}\n # Looping through all the bases in RNA seq. to convert to its complement seq using dictionary values.\n for i in rna_list:\n comlement_sequence.append(complement[i])\n return ''.join(comlement_sequence)","def reverse_compliment(seq: str) -> str:\n return ''.join([{'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}[base] for base in reversed(seq)])","def complement_RNA(RNAsequence):\n complement = \"\"\n for nucleotide in RNAsequence:\n if nucleotide == \"A\":\n complement += \"U\"\n if nucleotide == \"C\":\n complement += \"G\"\n if nucleotide == \"G\":\n complement += \"C\"\n if nucleotide == \"U\":\n complement += \"A\"\n return complement","def reverse_complement(seq):\n i=0;\n while i < len(seq):\n # Initialize reverse complement\n rev_seq = ''\n\n # Loop through and populate list with reverse complement\n\n rev_seq += complement_base(base)\n\n return rev_seq","def get_reverse_complement(s):\n dna_complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\n return ''.join(filter(None, reversed([ dna_complement[c.upper()] if c.upper() in dna_complement else '' for c in s ])))","def make_reverse_complement(seq):\n \n comp ={\"A\":\"T\", \"T\":\"A\", \"G\":\"C\", \"C\":\"G\", \"a\":\"t\", \"t\":\"a\", \"g\":\"c\", \"c\":\"g\", \"N\":\"N\", \\\n \"R\":\"R\", \"K\":\"K\", \"M\":\"M\", \"B\":\"B\", \"V\":\"V\", \"S\":\"S\", \"W\":\"W\", \"D\":\"D\", \"-\":\"-\",\\\n \"U\":\"U\", \"Y\":\"Y\", \"H\":\"H\", \" \":\"\"}\n\n rev = \"\"\n for i in range(0,len(seq)):\n rev += comp[seq[i]]\n\n return rev[::-1]","def reverse_complement(sequence):\n return sequence[::-1].translate(RC_TRANS)","def reverseComplement(seq):\n seq=seq.upper()\n # complement\n compl = complement(seq)\n # reverse\n return compl[::-1]","def reverse_complement(seq, material='DNA'):\n\n # Initialize reverse complement\n rev_seq = ''\n\n # Loop through and populate list with reverse complement\n for base in reversed(seq):\n rev_seq += complement_base(base, material=material)\n\n return rev_seq","def backtranslate(p_seq, n_seq):\r\n # Keep track of the new sequence. Also keep track of which codon we are\r\n # actually processing (gaps don't count)\r\n newseq = ''\r\n codon = 0\r\n for aa in p_seq:\r\n if aa == '-':\r\n newseq += '---'\r\n else:\r\n newseq += n_seq[codon*3:(codon*3) + 3]\r\n codon += 1\r\n return newseq","def get_reverse(sequence):\n #Convert all rna_sequence to upper case:\n sequence=sequence.upper()\n #reverse rna sequence:\n rna_rev_list=sequence[::-1]\n return rna_rev_list","def get_reverse_complement(cls, pattern: str) -> str:\n return ''.join(reversed([cls.dna_complement[nuc] for nuc in pattern]))","def complement(seq):\n complement_dict = {'A': 'T', 'C': 'G', 'T': 'A', 'G': 'C'}\n seq_list = list(seq)\n seq_list = [complement_dict[base] for base in seq_list]\n return ''.join(seq_list)","def translate_DNA(dnaseq):\n\n gen = aa_generator_DNA(dnaseq)\n seq = ''\n aa = next(gen, None)\n while aa:\n seq += aa\n aa = next(gen, None)\n return seq","def rev_comp(seq):\n return(complement_this(reverse_this(seq)))","def translate_sequence(rna_sequence, genetic_code):\n #Crate an empty list to store AA sequence:\n AA_list = []\n # Convert all rna_sequence to upper case:\n rna_sequence=rna_sequence.upper()\n # Convert all rna_sequence into a list:\n rna_list = list(rna_sequence)\n # This conditon will run if rna_sequence is at least 3 bases long, and only once it find start codon ,\n #and stop once it finds stop codon.\n while True:\n if len(rna_list) > 2:\n codon=''.join(rna_list[0:3])\n #Delete first 3 bases since its alread added as codon, thus no longer needed.\n del rna_list[0:3]\n else:\n break\n #Using genetic code dictionary to find AA for each corresponding codon:\n AA=genetic_code[codon]\n #Break loop once it finds stop codon\n if AA=='*':\n break\n #Add add translatable AA to the AA_list:\n AA_list.append(AA)\n return ''.join(AA_list)","def reverse_complement(seq):\n seq = reverse(seq)\n seq = complement(seq)\n return seq","def get_strand_complement(sequence):\n seq = sequence.upper()\n change = str.maketrans('ACGT', 'TGCA')\n return seq.translate(change)","def find_reverse_palindromes(dna: str, min_len: int=4, max_len: int=12, zero_based: bool=True):\n def helper_for_non_zero_based(indexes: List[Tuple[int, int]]):\n if not zero_based:\n return [(i + 1, l) for i, l in indexes]\n else:\n return indexes\n\n length = len(dna)\n result = []\n for i in range(length):\n for l in range(min(min_len, length - i), min(max_len + 1, length - i + 1)):\n if l > max_len or l < min_len:\n continue\n sub_dna = dna[i: i + l]\n if sub_dna == reverse_complement(sub_dna):\n result.append((i, l))\n return helper_for_non_zero_based(result)","def reverse_complement(sequence):\n reverse = [complement_base(base) for base in sequence[::-1]]\n return \"\".join(reverse)","def reverse_complement(pattern):\n\n complement = ''\n for i in range(len(pattern)):\n if pattern[i] == 'A':\n complement = complement + 'T'\n elif pattern[i] == 'T':\n complement = complement + 'A'\n elif pattern[i] == 'C':\n complement = complement + 'G'\n else:\n complement = complement + 'C'\n rev_complement = list(reversed(complement))\n return ''.join(rev_complement)","def find_all_ORFs_both_strands(dna):\n \n #reverse first \n #then take compliment \n #then find ORF \n reverseStrand = [] \n original = [] \n new = []\n reverseStrand.append(get_reverse_complement(dna)) \n original.append(find_all_ORFs(dna))\n new.append(find_all_ORFs(reverseStrand))\n return original + new","def reverse_complement(base):\n try:\n assert isinstance(base, str)\n assert len(base) is 1\n rc = str.maketrans('ACGT', 'TGCA') # Traslation table for reverse complentary sequences\n return base.translate(rc)\n except AssertionError:\n raise NotABaseError","def get_complement(nucleotide):\n #if statements change nucleotide inputs to their complementary nucleotide\n if nucleotide == \"A\":\n return \"T\"\n if nucleotide == \"T\":\n return \"A\" \n if nucleotide == \"C\":\n return \"G\"\n if nucleotide == \"G\":\n return \"C\"","def _rc_seq(self):\n logger.debug(\"Extracting sequences on the reverse strand\")\n sequences_rc = []\n table = str.maketrans({'a': 't', 'c': 'g', 'g': 'c', 't': 'a',\n 'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'})\n for sequence in self.sequences:\n sequences_rc.append(sequence.translate(table)[::-1])\n self.sequences_rc = sequences_rc","def get_strand_complement(sequence):\n # make the sequence upper case\n seq = sequence.upper()\n # table to change the complement characters\n change = str.maketrans('ACGT', 'TGCA')\n return seq.translate(change)","def back_translate(self):\n base = Bio.Alphabet._get_base_alphabet(self.alphabet)\n if not isinstance(base, Bio.Alphabet.ProteinAlphabet):\n raise ValueError(\"Nucleic acids cannot be back translated!\")\n\n # right now this just uses the most-prevalent codon for each AA\n # TODO: select codons with a weighted average using random.choice\n return Seq(\n \"\".join([CodonUsage.SynonymousCodons[seq3(AA).upper()][0] for AA in str(self)]),\n IUPAC.unambiguous_dna,\n )","def get_complement(nucleotide): # This one works\n nuc = list(nucleotide)\n count = 0\n complement = ''\n for element in nuc:\n if element == 'A':\n nuc[count] = 'T'\n elif element == 'T':\n nuc[count] = 'A'\n elif element == 'C':\n nuc[count] = 'G'\n elif element == 'G':\n nuc[count] = 'C'\n complement = complement + nuc[count]\n count = count + 1\n return complement","def get_reverse_complement_unit_tests():\n print \"input: GTTGACAGTACGTACAGGGAA, \"+\"output: \"+ get_reverse_complement(\"GTTGACAGTACGTACAGGGAA\") +\", actual output: AAGGGACATGCATGACAGTTG\" \n print \"input: TTATTGCTTATTATCATG, \"+\"output: \"+get_reverse_complement(\"TTATTGCTTATTATCATG\")+\", actual output: GTACTATTATTCGTTATT\"\n print \"input: ATC, \"+\"output: \"+get_reverse_complement(\"ATC\")+\", actual output: GAT\"\n print \"input: CTA, \"+\"output: \"+get_reverse_complement(\"CTA\")+\", actual output: TAG\"","def fast_complement(dna):\n str = ''\n dict = {'C':'G','G':'C','A':'T','T':'A'}\n for char in dna:\n if char == 'C' or char == 'G' or char == 'T' or char == 'A':\n str = str + dict[char]\n else :\n str = 'invalid character entered, please check the input'\n break\n return str","def translate(dna):\n rna = dna.replace('T', 'U')\n startIndex = dna.find('AUG') + 1\n aminoAcidsSeq = \"\"\n for i in range(startIndex, len(rna), 3):\n # codon = rna[i: i+3]\n aminoAcidsSeq += code[rna[i: i+3]]\n if aminoAcidsSeq[len(aminoAcidsSeq) - 1] == '*':\n aminoAcidsSeq = aminoAcidsSeq[:-1]\n break\n return aminoAcidsSeq","def ReverseComplement(self):\n if (self.translated == False):\n for i in range(len(self.alignment)):\n self.alignment[i].seq = self.alignment[i].seq.reverse_complement()\n self.Show(self.displayedColumn)\n self.BackupAlignment()\n else:\n self.AlertMessage(\"Can't reverse-complement protein sequences.\", 'medium')","def back_translate(seq):\n\n base_nucleotide_list = []\n for i in seq:\n res = __get_key(i,CodonTable)\n base_nucleotide_list.append(res)\n return ''.join(base_nucleotide_list)","def getRevCodonSeqs(self):\r\n compDict = {'A': 't', 'T': 'a', 'G': 'c', 'C': 'g'} # nuc compliments for reverse strand\r\n revPep = [] # list to hold the temporary reverse peptides before incorporation into the complete list\r\n for seq in self.allPepSeqs:\r\n revSeq = seq[::-1] # reverses the strand to be prepped for nt compliments\r\n for nuc in compDict:\r\n revSeq = revSeq.replace(nuc, compDict[nuc]) # replaces nt's with their compliments\r\n revSeq = revSeq.upper()\r\n revPep.append(revSeq)\r\n for i in revPep:\r\n self.allPepSeqs.append(i) # adds the reverse strand peptide to the list of possible peptide seqs\r\n return","def flexible_reverse_complements(sequence, exclude_wobble=True):\n sequence, expansions = _frc_process(sequence, list(), exclude_wobble)\n while len(sequence):\n sequence, expansions = _frc_process(sequence, expansions, exclude_wobble)\n return [\"\".join(expansion) for expansion in expansions]","def complement(seq):\n if PY3:\n table = str.maketrans('ACTGNactg', 'TGACNtgac')\n elif PY2:\n table = string.maketrans('ACTGNactg', 'TGACNtgac')\n return str(seq).translate(table)","def wc(seq):\n return \"\".join(complement[nt] for nt in reversed(seq))","def reading_frames(dna):\n #the 6 types are as follows\n # the actual string and the reverse complement\n list = []\n #this is the actual string\n list.append(dna)\n #this is the reverse complement of the string\n # done reusing the fastcomplement() method that was already available.\n #others are done likewise\n list.append(fast_complement(dna[::-1]))\n list.append(dna[1:len(dna)])\n list.append(fast_complement(dna[1:len(dna)][::-1]))\n list.append(dna[2:len(dna)])\n list.append(fast_complement(dna[2:len(dna)][::-1]))\n return list","def revcom(s):\n def complement(s):\n basecomplement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A', 'N': 'N'}\n letters = list(s)\n letters = [basecomplement[base] for base in letters]\n return ''.join(letters)\n return complement(s[::-1])","def to_rna(seq):\n seq=seq.replace('A','U')\n seq=seq.replace('T','A')\n seq=seq.replace('C',\"P\")\n seq=seq.replace('G','C')\n seq=seq.replace('P','G')\n return seq","def get_complement(nucleotide):\n if nucleotide=='A':\n \treturn 'T'\n if nucleotide=='C':\n \treturn 'G'\n if nucleotide=='T':\n \treturn 'A'\n if nucleotide=='G':\n \treturn 'C'","def invert_seq(self):\n if not self.data['DNAseq']:\n self.invert_seq_var.set(0)\n self.warning('No DNA sequence loaded','You have to load a DNA sequence first')\n return\n inverted=''\n for count in range(len(self.data['DNAseq'])):\n pos=-count-1\n inverted=inverted+self.data['DNAseq'][pos]\n self.data['DNAseq']=inverted\n #\n # Update\n #\n self.update_sequence_window()\n return","def reverse_complement(sequence):\n try:\n return ''.join([COMPLEMENTARY_BASE[base]\n for base in reversed(sequence)])\n except KeyError:\n raise ValueError('Not able to reverse complement: %s' % sequence)","def complementary_sequence(s):\n res = \"\"\n for char in s:\n tot = res + (get_complement(char))","def get_complement(nucleotide):\n if nucleotide == 'A':\n return 'T'\n elif nucleotide == 'T':\n return 'A'\n elif nucleotide == 'C':\n return 'G'\n elif nucleotide == 'G':\n return 'C'","def reverseComplement(s):\n\tcomplement = {'A':'T', 'C':'G', 'G':'C', 'T':'A', 'N':'N'}\n\tt = ''\n\tfor base in s:\n\t\tt = complement[base] + t\n\treturn t","def get_complement(nucleotide):\n\n if nucleotide == 'T':\n return 'A'\n elif nucleotide == 'A':\n return 'T'\n elif nucleotide == 'C':\n return 'G'\n elif nucleotide == 'G':\n return 'C'","def longest_ORF_noncoding(dna, num_trials):\n\n # YOUR IMPLEMENTATION HERE","def rest_of_ORF(dna):\n for h in range(0, len(dna), 3):\n curr_triplet = dna[h : h + 3] \n #for n in range(0, len(amino_acids.codons),1):\n if curr_triplet in amino_acids.codons[10]:\n return dna[0 : h] \n return dna","def reverse(seq):\n return seq[::-1]","def reverse(seq):\n return seq[::-1]","def palindrome_reads_fasta(self):\n return op.join(self.out_dir, \"palindrome_subreads.fasta\")","def get_reverse_complement_unit_tests():\n input = [\"dna\"]\n expected_output = [\"reversed_dna\"]\n actual = []\n for j in input:\n actual.append(get_reverse_complement(j))\n print input \n print actual\n print expected_output","def get_complement(nucleotide):\n if nucleotide == 'A':\n return 'T'\n elif nucleotide == 'C':\n return 'G'\n elif nucleotide == 'G':\n return 'C'\n elif nucleotide == 'T':\n return 'A'\n else:\n return None","def Complementary(self,direction):\n complementary = self.sequence.upper().replace('A','t')\\\n .replace('T','a').replace('G','c')\\\n .replace('C','g').upper()\n if direction == '3-5':\n return complementary\n else:\n return complementary[::-1]","def compress_seq(s: str):\n bits = 64\n assert len(s) <= (bits / 2 - 1)\n result = 0\n for nuc in s:\n if nuc not in NUCS_INVERSE:\n return 1 << (bits - 1)\n result = result << 2\n result = result | NUCS_INVERSE[nuc]\n return result","def find_all_ORFs_both_strands(dna):\n return find_all_ORFs(dna)+find_all_ORFs(get_reverse_complement(dna))\n \n \n # YOUR IMPLEMENTATION HERE","def get_complement(s):\n dna_complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\n return ''.join(filter(None, [ dna_complement[c.upper()] if c.upper() in dna_complement else '' for c in s ] ))"],"string":"[\n \"def get_reverse_complement(dna):\\n rev_comp = ''\\n for i in range(0, len(dna)):\\n nucleo = dna[i]\\n comp = get_complement(nucleo)\\n rev_comp = comp + rev_comp\\n return rev_comp\",\n \"def reverse_complement_strand(dna):\\n reverse_complement = \\\"\\\"\\n\\n for character in dna[::-1]:\\n if character == \\\"A\\\":\\n reverse_complement += \\\"T\\\"\\n elif character == \\\"T\\\":\\n reverse_complement += \\\"A\\\"\\n elif character == \\\"C\\\":\\n reverse_complement += \\\"G\\\"\\n elif character == \\\"G\\\":\\n reverse_complement += \\\"C\\\"\\n\\n return reverse_complement\",\n \"def get_reverse_complement(dna):\\n reversed_dna_string = ''\\n dna_reverse = dna[::-1]\\n for i in range(len(dna)):\\n dna_nucleotide = dna_reverse[i]\\n reversed_dna_string += get_complement(dna_nucleotide)\\n return reversed_dna_string\",\n \"def reverse_complement_strand(dna):\\n assert (is_dna(dna))\\n return ''.join(_rev_mapping[nn] for nn in dna[::-1])\",\n \"def get_reverse_complement(dna):\\n reverseDNA = ''\\n newDNA = ''\\n for i in range(len(dna)): \\n reverseDNA+= dna[-1-i]\\n for k in range(len(dna)): \\n if reverseDNA[k] == 'A': \\n newDNA+='T'\\n elif reverseDNA[k] =='T':\\n newDNA+= 'A' \\n elif reverseDNA[k] =='G':\\n newDNA+= 'C'\\n elif reverseDNA[k] =='C':\\n newDNA+= 'G' \\n return newDNA\",\n \"def get_reverse_complement(dna):\\n\\n n = len(dna)\\n\\n i = 0\\n\\n reverse_dna = []\\n\\n for i in range(n):\\n reverse_dna.append (get_complement(dna[n - 1 - i]))\\n reverse_complement = ''.join(reverse_dna)\\n return reverse_complement\",\n \"def get_reverse_complement(dna):\\r\\n\\r\\n seq = Seq(dna)\\r\\n rev_seq = seq.reverse_complement()\\r\\n return str(rev_seq)\",\n \"def get_reverse_complement(dna):\\n \\n dna = dna.replace('T','N')\\n dna = dna.replace('A','T')\\n dna = dna.replace('N','A')\\n dna = dna.replace('C','N')\\n dna = dna.replace('G','C')\\n dna = dna.replace('N','G')\\n dna = dna[::-1]\\n return dna\",\n \"def reverse_complement_RNA(RNAsequence):\\n complement = \\\"\\\"\\n for nucleotide in RNAsequence:\\n if nucleotide == \\\"A\\\":\\n complement = \\\"U\\\" + complement\\n if nucleotide == \\\"C\\\":\\n complement = \\\"G\\\" + complement\\n if nucleotide == \\\"G\\\":\\n complement = \\\"C\\\" + complement\\n if nucleotide == \\\"U\\\":\\n complement = \\\"A\\\" + complement\\n return complement\",\n \"def reverse_and_complement(sequence):\\n #Convert all rna_sequence to upper case:\\n sequence=sequence.upper()\\n # Conver RNA sequence into a list\\n rna_list = list(sequence)\\n #reverse rna sequence:\\n rna_list.reverse()\\n #Create an empty list to store reverse complement seq.\\n rev_c = []\\n #Complement code corresponsing for all RNA bases\\n complement = {'A' : 'U', 'C' : 'G', 'G': 'C', 'U': 'A'}\\n #Looping through all the bases in complement RNA seq. of reversed RNA seq. using dictionary values.\\n for i in rna_list:\\n rev_c.append(complement[i])\\n return ''.join(rev_c)\",\n \"def get_reverse_complement(dna):\\n l = [get_complement(char) for char in dna[::-1]]\\n return ''.join(l)\",\n \"def get_reverse_complement(dna):\\n #set up initial empty strings for later use\\n complement = \\\"\\\"\\n reverse_complement = \\\"\\\"\\n\\n #for each element in the list of dna, get the complement and add it to an empty list\\n for i in range(len(dna)):\\n complement = complement + get_complement(dna[i]) \\n\\n #for each element in the list of complement, return the complement by calling the list in reverse\\n for i in range(len(dna)):\\n reverse_complement = reverse_complement + complement[len(dna)-1-i]\\n\\n return reverse_complement\",\n \"def get_reverse_complement(dna):\\n dna=\\\"ATCG\\\"\\n b = list(dna)\\n b.reverse()\\n \\\"\\\".join(b)\\n\\n for n in range(0, len(b), 1):\\n if b[n] == \\\"A\\\":\\n b[n] = \\\"T\\\"\\n elif b[n] == \\\"C\\\":\\n b[n] = \\\"G\\\"\\n elif b[n] == \\\"T\\\":\\n b[n] = \\\"A\\\"\\n elif b[n] == \\\"G\\\":\\n b[n] = \\\"C\\\"\\n \\n print \\\"\\\".join(b)\",\n \"def reverse_complementary(seq):\\n\\n complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\\n return \\\"\\\".join(complement[n] for n in reversed(seq))\",\n \"def rev_comp(dna):\\n return dna[::-1].translate(maketrans('ATCG', 'TAGC'))\",\n \"def reverse_rna_complement(seq):\\n\\n seq_upper = seq.isupper()\\n\\n seq = seq[::-1]\\n\\n seq = seq.upper()\\n\\n #compute complement\\n seq = seq.replace('A','u')\\n seq = seq.replace('T','a')\\n seq = seq.replace('G','c')\\n seq = seq.replace('C','g')\\n\\n if seq_upper:\\n return seq.upper()\\n else:\\n return seq\",\n \"def reverse_complement(dna: str):\\n dna = dna.strip()\\n result = [\\\" \\\"] * len(dna)\\n for index, letter in enumerate(reversed(dna)):\\n result[index] = complement_map[letter]\\n return \\\"\\\".join(result)\",\n \"def get_reverse_complement(dna):\\n L=dna\\n rdna=L[::-1]\\n print rdna\\n newrdna=\\\"\\\"\\n for i in range(0,len(rdna)):\\n if rdna[i]=='A':\\n newrdna='T'+newrdna\\n elif rdna[i]=='G':\\n newrdna='C'+newrdna\\n elif rdna[i]=='T':\\n newrdna='A'+newrdna\\n elif rdna[i]=='C':\\n newrdna='G'+newrdna\\n S=newrdna\\n P=S[::-1]\\n return P\",\n \"def complement_strand(dna):\\n reverse_complement = \\\"\\\"\\n\\n for character in dna[::-1]:\\n if character == \\\"A\\\":\\n reverse_complement += \\\"T\\\"\\n elif character == \\\"T\\\":\\n reverse_complement += \\\"A\\\"\\n elif character == \\\"C\\\":\\n reverse_complement += \\\"G\\\"\\n elif character == \\\"G\\\":\\n reverse_complement += \\\"C\\\"\\n\\n return reverse_complement\",\n \"def get_reverse_complement(dna):\\n reverse=[None]*len(dna)\\n for i in range(0,len(dna)):\\n \\treverse[len(dna)-i-1]=get_complement(dna[i])\\n s=''\\n reverse=s.join(reverse)\\n return reverse\",\n \"def get_reverse_complement(dna):\\n dna2 = get_complement(dna)\\n dna3 = dna2[::-1]\\n return str(dna3)\",\n \"def get_reverse_complement(dna):\\n rdna = dna[::-1]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# reverses input\\n\\n rev_dna = \\\"\\\"\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# initializes empty string\\n index = 0\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitialize index\\n while index < len(rdna):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# while loop, ends at len(dna)-1\\n \\treverse_letter = get_complement(rdna[index])\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# gets the complement for the string\\n \\trev_dna = rev_dna + reverse_letter\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# adds the new letter to the string\\n \\tindex += 1\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# indexes up 1\\n return rev_dna \\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns string\",\n \"def reverse_complement(seq):\\n if sys.version_info.major == 2:\\n conversion = string.maketrans('ACGTacgt','TGCAtgca')\\n else:\\n conversion = str.maketrans('ACGTacgt','TGCAtgca')\\n\\n comp = seq.translate(conversion)\\n rev_comp = comp[::-1]\\n return rev_comp\",\n \"def reverse_complement(dna, reverse=True, complement=True):\\n \\n # Make translation table\\n trans_table = string.maketrans('ATGCatgc', 'TACGtacg')\\n \\n # Make complement to DNA\\n comp_dna = dna.translate(trans_table)\\n \\n # Output all as strings\\n if reverse and complement:\\n return comp_dna[::-1]\\n if reverse and not complement:\\n return dna[::-1]\\n if complement and not reverse:\\n return comp_dna\\n if not complement and not reverse:\\n return dna\",\n \"def reverse_complement(sequence):\\n\\n #define complement dictionary\\n complement_dictionary = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A', 'N': 'N' }\\n\\n #Reversing the string by using extended slice syntax which works by doing \\\"[begin:end:step]\\\", by leaving begin and end out and specifying a step of -1, it reverses a strings order.\\n sequence = sequence[::-1]\\n \\n #Taking the complement by turning the sequence into a list of bases so I can turn a single base at a time into it's complement base using a list comprehension\\n bases = list(sequence)\\n bases = [complement_dictionary[base] for base in bases]#This takes a base from the bases list and switches it for its complement base\\n\\n #return the reverse complement by joining all of the bases from the list bases\\n return ''.join(bases)\",\n \"def ReverseComplement1(seq):\\n seq_dict = {'A':'T','T':'A','G':'C','C':'G'}\\n return \\\"\\\".join([seq_dict[base] for base in reversed(seq)])\",\n \"def reversecomp(sequence):\\n\\tseqrc = \\\"\\\"\\n\\ttempzrev = sequence\\n\\ttempzrev = tempzrev.replace(\\\"T\\\",\\\"X\\\")\\n\\ttempzrev = tempzrev.replace(\\\"A\\\",\\\"T\\\")\\n\\ttempzrev = tempzrev.replace(\\\"X\\\",\\\"A\\\")\\n\\ttempzrev = tempzrev.replace(\\\"C\\\",\\\"Y\\\")\\n\\ttempzrev = tempzrev.replace(\\\"G\\\",\\\"C\\\")\\n\\ttempzrev = tempzrev.replace(\\\"Y\\\",\\\"G\\\")\\n\\ttemplist = list(tempzrev)\\n\\ttemplist.reverse()\\n\\tfor i in templist:\\n\\t\\tseqrc += i\\n\\treturn seqrc\",\n \"def reverse_complement(seq):\\n\\n # Initialize dict of complements\\n complements = {\\n 'A': 'T',\\n 'C': 'G',\\n 'T': 'A',\\n 'G': 'C'\\n }\\n\\n # Initialize reverse complement\\n rev_seq = ''\\n\\n # Loop through and populate list with reverse complement\\n for base in reversed(seq.upper()):\\n rev_seq += complements[base] \\n\\n return rev_seq\",\n \"def getSecondStrand(sequences):\\n compDNA = []\\n for dna in sequences:\\n compDNAAux = dna.replace('A', 't')\\n compDNAAux = compDNAAux.replace('T', 'a')\\n compDNAAux = compDNAAux.replace('C', 'g')\\n compDNAAux = compDNAAux.replace('G', 'c')\\n compDNA.append(compDNAAux.upper())\\n\\n for i in range(0, len(compDNA)):\\n compDNA[i] = compDNA[i][::-1]\\n\\n return compDNA\",\n \"def reverse_complement(DNA, as_string=False, unreversed_order=False):\\n comp_dict = {'A': 'T', 'T': 'A', 'C': 'G', 'G': 'C'}\\n\\n if unreversed_order:\\n complements = [comp_dict[nuc] for nuc in DNA]\\n else:\\n complements = [comp_dict[nuc] for nuc in DNA[::-1]]\\n\\n if as_string:\\n complements = \\\"\\\".join(complements)\\n\\n return complements\",\n \"def reverse_complement(seq):\\n return ''.join([BASE_TO_COMP[b] for b in seq][::-1])\",\n \"def reverse_complement(sequence: str) -> str:\\n complement_dict = sequence_utils.DNA_COMPLEMENT\\n # If a base is not present in the vocabulary, we don't reverse complement it\\n # in this function, and these sequences will get discarded downstream in the\\n # TF Example generation pipeline.\\n return ''.join(complement_dict.get(nt, nt) for nt in reversed(sequence))\",\n \"def get_reverse_complement(sequence):\\n return get_strand_complement(sequence)[::-1]\",\n \"def complementary_seq(self):\\n if not self.data['DNAseq']:\\n self.complement_seq_var.set(0)\\n self.warning('No DNA sequence loaded','You have to load a DNA sequence first')\\n return\\n compl={'A':'T','T':'A','C':'G','G':'C'}\\n comDNA=''\\n for base in self.data['DNAseq']:\\n comDNA=comDNA+compl[base]\\n self.data['DNAseq']=comDNA\\n\\n # Update\\n self.update_sequence_window()\\n return\",\n \"def complement_this(seq):\\n compliment_dict = {'A':'T', 'T':'A', 'C':'G', 'G':'C'}\\n rev_seq = ''\\n for nuc in seq:\\n if nuc in ['A', 'T', 'G', 'C']:\\n rev_seq += compliment_dict[nuc]\\n return rev_seq\",\n \"def reverseComplementer(self, ORFsequence):\\r\\n reverseComplement = str()\\r\\n reverserDict = {\\\"A\\\":\\\"U\\\",\\\"U\\\":\\\"A\\\",\\\"C\\\":\\\"G\\\",\\\"G\\\":\\\"C\\\"}\\r\\n reversedseq = ORFsequence[::-1]\\r\\n for nucleotide in reversedseq:\\r\\n reverseComplement+=reverserDict[nucleotide]\\r\\n return reverseComplement\",\n \"def get_reverse_complement(sequence):\\n seq = sequence.upper()\\n return get_strand_complement(seq)[::-1]\",\n \"def reverse_compliment(seq):\\n compliment = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\\n reverse = seq[::-1]\\n rev_comp = ''.join([compliment[nt] for nt in reverse])\\n return rev_comp\",\n \"def reverseComplement(seq, alphabet='ACGT'):\\n compl= dict(zip('ACGTNRYWSMKBHDV', 'TGCANYRWSKMVDHB'))\\n return ''.join([compl[base]\\n for base in seq.upper().replace('U', 'T')])[::-1]\",\n \"def reverse_complement(dna):\\n str = ''\\n dict = {'C': 'G', 'G': 'C', 'A': 'T', 'T': 'A'}\\n for char in dna:\\n if char == 'C' or char == 'G' or char == 'T' or char == 'A':\\n str = str + dict[char]\\n else :\\n str = 'invalid character entered, please check the input'\\n break\\n return str[::-1]\",\n \"def revcomp(self, seq):\\n tab = self.maketrans(b'ACNGT', b'TGNCA')\\n return seq.translate(tab)[::-1]\",\n \"def get_complementary_sequence(sequence):\\n\\n complementary_sequence = ''\\n for char in sequence:\\n complementary_sequence = complementary_sequence + get_complement(char)\\n return complementary_sequence\",\n \"def get_complement(sequence):\\n #Convert all rna_sequence to upper case:\\n sequence=sequence.upper()\\n # Conver RNA sequence into a list\\n rna_list=list(sequence)\\n #Create an empty list to store complement sequence:\\n comlement_sequence=[]\\n #Complement code corresponsing for all RNA bases\\n complement= {'A' : 'U', 'C' : 'G', 'G': 'C', 'U': 'A'}\\n # Looping through all the bases in RNA seq. to convert to its complement seq using dictionary values.\\n for i in rna_list:\\n comlement_sequence.append(complement[i])\\n return ''.join(comlement_sequence)\",\n \"def reverse_compliment(seq: str) -> str:\\n return ''.join([{'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}[base] for base in reversed(seq)])\",\n \"def complement_RNA(RNAsequence):\\n complement = \\\"\\\"\\n for nucleotide in RNAsequence:\\n if nucleotide == \\\"A\\\":\\n complement += \\\"U\\\"\\n if nucleotide == \\\"C\\\":\\n complement += \\\"G\\\"\\n if nucleotide == \\\"G\\\":\\n complement += \\\"C\\\"\\n if nucleotide == \\\"U\\\":\\n complement += \\\"A\\\"\\n return complement\",\n \"def reverse_complement(seq):\\n i=0;\\n while i < len(seq):\\n # Initialize reverse complement\\n rev_seq = ''\\n\\n # Loop through and populate list with reverse complement\\n\\n rev_seq += complement_base(base)\\n\\n return rev_seq\",\n \"def get_reverse_complement(s):\\n dna_complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\\n return ''.join(filter(None, reversed([ dna_complement[c.upper()] if c.upper() in dna_complement else '' for c in s ])))\",\n \"def make_reverse_complement(seq):\\n \\n comp ={\\\"A\\\":\\\"T\\\", \\\"T\\\":\\\"A\\\", \\\"G\\\":\\\"C\\\", \\\"C\\\":\\\"G\\\", \\\"a\\\":\\\"t\\\", \\\"t\\\":\\\"a\\\", \\\"g\\\":\\\"c\\\", \\\"c\\\":\\\"g\\\", \\\"N\\\":\\\"N\\\", \\\\\\n \\\"R\\\":\\\"R\\\", \\\"K\\\":\\\"K\\\", \\\"M\\\":\\\"M\\\", \\\"B\\\":\\\"B\\\", \\\"V\\\":\\\"V\\\", \\\"S\\\":\\\"S\\\", \\\"W\\\":\\\"W\\\", \\\"D\\\":\\\"D\\\", \\\"-\\\":\\\"-\\\",\\\\\\n \\\"U\\\":\\\"U\\\", \\\"Y\\\":\\\"Y\\\", \\\"H\\\":\\\"H\\\", \\\" \\\":\\\"\\\"}\\n\\n rev = \\\"\\\"\\n for i in range(0,len(seq)):\\n rev += comp[seq[i]]\\n\\n return rev[::-1]\",\n \"def reverse_complement(sequence):\\n return sequence[::-1].translate(RC_TRANS)\",\n \"def reverseComplement(seq):\\n seq=seq.upper()\\n # complement\\n compl = complement(seq)\\n # reverse\\n return compl[::-1]\",\n \"def reverse_complement(seq, material='DNA'):\\n\\n # Initialize reverse complement\\n rev_seq = ''\\n\\n # Loop through and populate list with reverse complement\\n for base in reversed(seq):\\n rev_seq += complement_base(base, material=material)\\n\\n return rev_seq\",\n \"def backtranslate(p_seq, n_seq):\\r\\n # Keep track of the new sequence. Also keep track of which codon we are\\r\\n # actually processing (gaps don't count)\\r\\n newseq = ''\\r\\n codon = 0\\r\\n for aa in p_seq:\\r\\n if aa == '-':\\r\\n newseq += '---'\\r\\n else:\\r\\n newseq += n_seq[codon*3:(codon*3) + 3]\\r\\n codon += 1\\r\\n return newseq\",\n \"def get_reverse(sequence):\\n #Convert all rna_sequence to upper case:\\n sequence=sequence.upper()\\n #reverse rna sequence:\\n rna_rev_list=sequence[::-1]\\n return rna_rev_list\",\n \"def get_reverse_complement(cls, pattern: str) -> str:\\n return ''.join(reversed([cls.dna_complement[nuc] for nuc in pattern]))\",\n \"def complement(seq):\\n complement_dict = {'A': 'T', 'C': 'G', 'T': 'A', 'G': 'C'}\\n seq_list = list(seq)\\n seq_list = [complement_dict[base] for base in seq_list]\\n return ''.join(seq_list)\",\n \"def translate_DNA(dnaseq):\\n\\n gen = aa_generator_DNA(dnaseq)\\n seq = ''\\n aa = next(gen, None)\\n while aa:\\n seq += aa\\n aa = next(gen, None)\\n return seq\",\n \"def rev_comp(seq):\\n return(complement_this(reverse_this(seq)))\",\n \"def translate_sequence(rna_sequence, genetic_code):\\n #Crate an empty list to store AA sequence:\\n AA_list = []\\n # Convert all rna_sequence to upper case:\\n rna_sequence=rna_sequence.upper()\\n # Convert all rna_sequence into a list:\\n rna_list = list(rna_sequence)\\n # This conditon will run if rna_sequence is at least 3 bases long, and only once it find start codon ,\\n #and stop once it finds stop codon.\\n while True:\\n if len(rna_list) > 2:\\n codon=''.join(rna_list[0:3])\\n #Delete first 3 bases since its alread added as codon, thus no longer needed.\\n del rna_list[0:3]\\n else:\\n break\\n #Using genetic code dictionary to find AA for each corresponding codon:\\n AA=genetic_code[codon]\\n #Break loop once it finds stop codon\\n if AA=='*':\\n break\\n #Add add translatable AA to the AA_list:\\n AA_list.append(AA)\\n return ''.join(AA_list)\",\n \"def reverse_complement(seq):\\n seq = reverse(seq)\\n seq = complement(seq)\\n return seq\",\n \"def get_strand_complement(sequence):\\n seq = sequence.upper()\\n change = str.maketrans('ACGT', 'TGCA')\\n return seq.translate(change)\",\n \"def find_reverse_palindromes(dna: str, min_len: int=4, max_len: int=12, zero_based: bool=True):\\n def helper_for_non_zero_based(indexes: List[Tuple[int, int]]):\\n if not zero_based:\\n return [(i + 1, l) for i, l in indexes]\\n else:\\n return indexes\\n\\n length = len(dna)\\n result = []\\n for i in range(length):\\n for l in range(min(min_len, length - i), min(max_len + 1, length - i + 1)):\\n if l > max_len or l < min_len:\\n continue\\n sub_dna = dna[i: i + l]\\n if sub_dna == reverse_complement(sub_dna):\\n result.append((i, l))\\n return helper_for_non_zero_based(result)\",\n \"def reverse_complement(sequence):\\n reverse = [complement_base(base) for base in sequence[::-1]]\\n return \\\"\\\".join(reverse)\",\n \"def reverse_complement(pattern):\\n\\n complement = ''\\n for i in range(len(pattern)):\\n if pattern[i] == 'A':\\n complement = complement + 'T'\\n elif pattern[i] == 'T':\\n complement = complement + 'A'\\n elif pattern[i] == 'C':\\n complement = complement + 'G'\\n else:\\n complement = complement + 'C'\\n rev_complement = list(reversed(complement))\\n return ''.join(rev_complement)\",\n \"def find_all_ORFs_both_strands(dna):\\n \\n #reverse first \\n #then take compliment \\n #then find ORF \\n reverseStrand = [] \\n original = [] \\n new = []\\n reverseStrand.append(get_reverse_complement(dna)) \\n original.append(find_all_ORFs(dna))\\n new.append(find_all_ORFs(reverseStrand))\\n return original + new\",\n \"def reverse_complement(base):\\n try:\\n assert isinstance(base, str)\\n assert len(base) is 1\\n rc = str.maketrans('ACGT', 'TGCA') # Traslation table for reverse complentary sequences\\n return base.translate(rc)\\n except AssertionError:\\n raise NotABaseError\",\n \"def get_complement(nucleotide):\\n #if statements change nucleotide inputs to their complementary nucleotide\\n if nucleotide == \\\"A\\\":\\n return \\\"T\\\"\\n if nucleotide == \\\"T\\\":\\n return \\\"A\\\" \\n if nucleotide == \\\"C\\\":\\n return \\\"G\\\"\\n if nucleotide == \\\"G\\\":\\n return \\\"C\\\"\",\n \"def _rc_seq(self):\\n logger.debug(\\\"Extracting sequences on the reverse strand\\\")\\n sequences_rc = []\\n table = str.maketrans({'a': 't', 'c': 'g', 'g': 'c', 't': 'a',\\n 'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'})\\n for sequence in self.sequences:\\n sequences_rc.append(sequence.translate(table)[::-1])\\n self.sequences_rc = sequences_rc\",\n \"def get_strand_complement(sequence):\\n # make the sequence upper case\\n seq = sequence.upper()\\n # table to change the complement characters\\n change = str.maketrans('ACGT', 'TGCA')\\n return seq.translate(change)\",\n \"def back_translate(self):\\n base = Bio.Alphabet._get_base_alphabet(self.alphabet)\\n if not isinstance(base, Bio.Alphabet.ProteinAlphabet):\\n raise ValueError(\\\"Nucleic acids cannot be back translated!\\\")\\n\\n # right now this just uses the most-prevalent codon for each AA\\n # TODO: select codons with a weighted average using random.choice\\n return Seq(\\n \\\"\\\".join([CodonUsage.SynonymousCodons[seq3(AA).upper()][0] for AA in str(self)]),\\n IUPAC.unambiguous_dna,\\n )\",\n \"def get_complement(nucleotide): # This one works\\n nuc = list(nucleotide)\\n count = 0\\n complement = ''\\n for element in nuc:\\n if element == 'A':\\n nuc[count] = 'T'\\n elif element == 'T':\\n nuc[count] = 'A'\\n elif element == 'C':\\n nuc[count] = 'G'\\n elif element == 'G':\\n nuc[count] = 'C'\\n complement = complement + nuc[count]\\n count = count + 1\\n return complement\",\n \"def get_reverse_complement_unit_tests():\\n print \\\"input: GTTGACAGTACGTACAGGGAA, \\\"+\\\"output: \\\"+ get_reverse_complement(\\\"GTTGACAGTACGTACAGGGAA\\\") +\\\", actual output: AAGGGACATGCATGACAGTTG\\\" \\n print \\\"input: TTATTGCTTATTATCATG, \\\"+\\\"output: \\\"+get_reverse_complement(\\\"TTATTGCTTATTATCATG\\\")+\\\", actual output: GTACTATTATTCGTTATT\\\"\\n print \\\"input: ATC, \\\"+\\\"output: \\\"+get_reverse_complement(\\\"ATC\\\")+\\\", actual output: GAT\\\"\\n print \\\"input: CTA, \\\"+\\\"output: \\\"+get_reverse_complement(\\\"CTA\\\")+\\\", actual output: TAG\\\"\",\n \"def fast_complement(dna):\\n str = ''\\n dict = {'C':'G','G':'C','A':'T','T':'A'}\\n for char in dna:\\n if char == 'C' or char == 'G' or char == 'T' or char == 'A':\\n str = str + dict[char]\\n else :\\n str = 'invalid character entered, please check the input'\\n break\\n return str\",\n \"def translate(dna):\\n rna = dna.replace('T', 'U')\\n startIndex = dna.find('AUG') + 1\\n aminoAcidsSeq = \\\"\\\"\\n for i in range(startIndex, len(rna), 3):\\n # codon = rna[i: i+3]\\n aminoAcidsSeq += code[rna[i: i+3]]\\n if aminoAcidsSeq[len(aminoAcidsSeq) - 1] == '*':\\n aminoAcidsSeq = aminoAcidsSeq[:-1]\\n break\\n return aminoAcidsSeq\",\n \"def ReverseComplement(self):\\n if (self.translated == False):\\n for i in range(len(self.alignment)):\\n self.alignment[i].seq = self.alignment[i].seq.reverse_complement()\\n self.Show(self.displayedColumn)\\n self.BackupAlignment()\\n else:\\n self.AlertMessage(\\\"Can't reverse-complement protein sequences.\\\", 'medium')\",\n \"def back_translate(seq):\\n\\n base_nucleotide_list = []\\n for i in seq:\\n res = __get_key(i,CodonTable)\\n base_nucleotide_list.append(res)\\n return ''.join(base_nucleotide_list)\",\n \"def getRevCodonSeqs(self):\\r\\n compDict = {'A': 't', 'T': 'a', 'G': 'c', 'C': 'g'} # nuc compliments for reverse strand\\r\\n revPep = [] # list to hold the temporary reverse peptides before incorporation into the complete list\\r\\n for seq in self.allPepSeqs:\\r\\n revSeq = seq[::-1] # reverses the strand to be prepped for nt compliments\\r\\n for nuc in compDict:\\r\\n revSeq = revSeq.replace(nuc, compDict[nuc]) # replaces nt's with their compliments\\r\\n revSeq = revSeq.upper()\\r\\n revPep.append(revSeq)\\r\\n for i in revPep:\\r\\n self.allPepSeqs.append(i) # adds the reverse strand peptide to the list of possible peptide seqs\\r\\n return\",\n \"def flexible_reverse_complements(sequence, exclude_wobble=True):\\n sequence, expansions = _frc_process(sequence, list(), exclude_wobble)\\n while len(sequence):\\n sequence, expansions = _frc_process(sequence, expansions, exclude_wobble)\\n return [\\\"\\\".join(expansion) for expansion in expansions]\",\n \"def complement(seq):\\n if PY3:\\n table = str.maketrans('ACTGNactg', 'TGACNtgac')\\n elif PY2:\\n table = string.maketrans('ACTGNactg', 'TGACNtgac')\\n return str(seq).translate(table)\",\n \"def wc(seq):\\n return \\\"\\\".join(complement[nt] for nt in reversed(seq))\",\n \"def reading_frames(dna):\\n #the 6 types are as follows\\n # the actual string and the reverse complement\\n list = []\\n #this is the actual string\\n list.append(dna)\\n #this is the reverse complement of the string\\n # done reusing the fastcomplement() method that was already available.\\n #others are done likewise\\n list.append(fast_complement(dna[::-1]))\\n list.append(dna[1:len(dna)])\\n list.append(fast_complement(dna[1:len(dna)][::-1]))\\n list.append(dna[2:len(dna)])\\n list.append(fast_complement(dna[2:len(dna)][::-1]))\\n return list\",\n \"def revcom(s):\\n def complement(s):\\n basecomplement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A', 'N': 'N'}\\n letters = list(s)\\n letters = [basecomplement[base] for base in letters]\\n return ''.join(letters)\\n return complement(s[::-1])\",\n \"def to_rna(seq):\\n seq=seq.replace('A','U')\\n seq=seq.replace('T','A')\\n seq=seq.replace('C',\\\"P\\\")\\n seq=seq.replace('G','C')\\n seq=seq.replace('P','G')\\n return seq\",\n \"def get_complement(nucleotide):\\n if nucleotide=='A':\\n \\treturn 'T'\\n if nucleotide=='C':\\n \\treturn 'G'\\n if nucleotide=='T':\\n \\treturn 'A'\\n if nucleotide=='G':\\n \\treturn 'C'\",\n \"def invert_seq(self):\\n if not self.data['DNAseq']:\\n self.invert_seq_var.set(0)\\n self.warning('No DNA sequence loaded','You have to load a DNA sequence first')\\n return\\n inverted=''\\n for count in range(len(self.data['DNAseq'])):\\n pos=-count-1\\n inverted=inverted+self.data['DNAseq'][pos]\\n self.data['DNAseq']=inverted\\n #\\n # Update\\n #\\n self.update_sequence_window()\\n return\",\n \"def reverse_complement(sequence):\\n try:\\n return ''.join([COMPLEMENTARY_BASE[base]\\n for base in reversed(sequence)])\\n except KeyError:\\n raise ValueError('Not able to reverse complement: %s' % sequence)\",\n \"def complementary_sequence(s):\\n res = \\\"\\\"\\n for char in s:\\n tot = res + (get_complement(char))\",\n \"def get_complement(nucleotide):\\n if nucleotide == 'A':\\n return 'T'\\n elif nucleotide == 'T':\\n return 'A'\\n elif nucleotide == 'C':\\n return 'G'\\n elif nucleotide == 'G':\\n return 'C'\",\n \"def reverseComplement(s):\\n\\tcomplement = {'A':'T', 'C':'G', 'G':'C', 'T':'A', 'N':'N'}\\n\\tt = ''\\n\\tfor base in s:\\n\\t\\tt = complement[base] + t\\n\\treturn t\",\n \"def get_complement(nucleotide):\\n\\n if nucleotide == 'T':\\n return 'A'\\n elif nucleotide == 'A':\\n return 'T'\\n elif nucleotide == 'C':\\n return 'G'\\n elif nucleotide == 'G':\\n return 'C'\",\n \"def longest_ORF_noncoding(dna, num_trials):\\n\\n # YOUR IMPLEMENTATION HERE\",\n \"def rest_of_ORF(dna):\\n for h in range(0, len(dna), 3):\\n curr_triplet = dna[h : h + 3] \\n #for n in range(0, len(amino_acids.codons),1):\\n if curr_triplet in amino_acids.codons[10]:\\n return dna[0 : h] \\n return dna\",\n \"def reverse(seq):\\n return seq[::-1]\",\n \"def reverse(seq):\\n return seq[::-1]\",\n \"def palindrome_reads_fasta(self):\\n return op.join(self.out_dir, \\\"palindrome_subreads.fasta\\\")\",\n \"def get_reverse_complement_unit_tests():\\n input = [\\\"dna\\\"]\\n expected_output = [\\\"reversed_dna\\\"]\\n actual = []\\n for j in input:\\n actual.append(get_reverse_complement(j))\\n print input \\n print actual\\n print expected_output\",\n \"def get_complement(nucleotide):\\n if nucleotide == 'A':\\n return 'T'\\n elif nucleotide == 'C':\\n return 'G'\\n elif nucleotide == 'G':\\n return 'C'\\n elif nucleotide == 'T':\\n return 'A'\\n else:\\n return None\",\n \"def Complementary(self,direction):\\n complementary = self.sequence.upper().replace('A','t')\\\\\\n .replace('T','a').replace('G','c')\\\\\\n .replace('C','g').upper()\\n if direction == '3-5':\\n return complementary\\n else:\\n return complementary[::-1]\",\n \"def compress_seq(s: str):\\n bits = 64\\n assert len(s) <= (bits / 2 - 1)\\n result = 0\\n for nuc in s:\\n if nuc not in NUCS_INVERSE:\\n return 1 << (bits - 1)\\n result = result << 2\\n result = result | NUCS_INVERSE[nuc]\\n return result\",\n \"def find_all_ORFs_both_strands(dna):\\n return find_all_ORFs(dna)+find_all_ORFs(get_reverse_complement(dna))\\n \\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def get_complement(s):\\n dna_complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\\n return ''.join(filter(None, [ dna_complement[c.upper()] if c.upper() in dna_complement else '' for c in s ] ))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7621168","0.75488645","0.74943614","0.7489699","0.74795413","0.7419932","0.73843974","0.73704416","0.73488766","0.7339861","0.7338994","0.7278367","0.7258061","0.7248897","0.72437245","0.7231113","0.72207266","0.7216731","0.72124445","0.7201928","0.71746796","0.7117649","0.7048817","0.69890714","0.69804734","0.69511855","0.6934045","0.6932545","0.6876603","0.68498725","0.6767309","0.67561495","0.6743511","0.6736858","0.66847175","0.6661298","0.66501063","0.6623255","0.66037637","0.66005284","0.658492","0.6575805","0.6573117","0.6554889","0.65495","0.6538712","0.6537142","0.6522378","0.65214753","0.6517414","0.64792365","0.6456267","0.6431877","0.63982564","0.6392094","0.6361879","0.63310677","0.632392","0.63109833","0.63096803","0.63031113","0.6281053","0.6276436","0.62576145","0.62438893","0.62283283","0.6198985","0.618815","0.6184267","0.6175635","0.617397","0.6140929","0.61242807","0.61108583","0.6103262","0.60890377","0.6070225","0.6054526","0.60401505","0.6040135","0.60384357","0.6037253","0.6029363","0.60270995","0.60249525","0.601204","0.60038036","0.5977222","0.59751755","0.59659857","0.59489995","0.59181064","0.59181064","0.5915507","0.5885344","0.58719856","0.5843652","0.58368963","0.5836083","0.58199334"],"string":"[\n \"0.7621168\",\n \"0.75488645\",\n \"0.74943614\",\n \"0.7489699\",\n \"0.74795413\",\n \"0.7419932\",\n \"0.73843974\",\n \"0.73704416\",\n \"0.73488766\",\n \"0.7339861\",\n \"0.7338994\",\n \"0.7278367\",\n \"0.7258061\",\n \"0.7248897\",\n \"0.72437245\",\n \"0.7231113\",\n \"0.72207266\",\n \"0.7216731\",\n \"0.72124445\",\n \"0.7201928\",\n \"0.71746796\",\n \"0.7117649\",\n \"0.7048817\",\n \"0.69890714\",\n \"0.69804734\",\n \"0.69511855\",\n \"0.6934045\",\n \"0.6932545\",\n \"0.6876603\",\n \"0.68498725\",\n \"0.6767309\",\n \"0.67561495\",\n \"0.6743511\",\n \"0.6736858\",\n \"0.66847175\",\n \"0.6661298\",\n \"0.66501063\",\n \"0.6623255\",\n \"0.66037637\",\n \"0.66005284\",\n \"0.658492\",\n \"0.6575805\",\n \"0.6573117\",\n \"0.6554889\",\n \"0.65495\",\n \"0.6538712\",\n \"0.6537142\",\n \"0.6522378\",\n \"0.65214753\",\n \"0.6517414\",\n \"0.64792365\",\n \"0.6456267\",\n \"0.6431877\",\n \"0.63982564\",\n \"0.6392094\",\n \"0.6361879\",\n \"0.63310677\",\n \"0.632392\",\n \"0.63109833\",\n \"0.63096803\",\n \"0.63031113\",\n \"0.6281053\",\n \"0.6276436\",\n \"0.62576145\",\n \"0.62438893\",\n \"0.62283283\",\n \"0.6198985\",\n \"0.618815\",\n \"0.6184267\",\n \"0.6175635\",\n \"0.617397\",\n \"0.6140929\",\n \"0.61242807\",\n \"0.61108583\",\n \"0.6103262\",\n \"0.60890377\",\n \"0.6070225\",\n \"0.6054526\",\n \"0.60401505\",\n \"0.6040135\",\n \"0.60384357\",\n \"0.6037253\",\n \"0.6029363\",\n \"0.60270995\",\n \"0.60249525\",\n \"0.601204\",\n \"0.60038036\",\n \"0.5977222\",\n \"0.59751755\",\n \"0.59659857\",\n \"0.59489995\",\n \"0.59181064\",\n \"0.59181064\",\n \"0.5915507\",\n \"0.5885344\",\n \"0.58719856\",\n \"0.5843652\",\n \"0.58368963\",\n \"0.5836083\",\n \"0.58199334\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.75032"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":92993,"cells":{"query":{"kind":"string","value":"Unit tests for the get_complement function"},"document":{"kind":"string","value":"def get_reverse_complement_unit_tests():\n # list of [input, expected output]\n data_list = [\n [\"ATGCCCGCTTT\", \"AAAGCGGGCAT\"],\n [\"AAAGCGGGCAT\", \"ATGCCCGCTTT\"],\n [\"CCGCGTTCA\", \"TGAACGCGG\"],\n [\"AAAA\", \"TTTT\"],\n [\"TTTT\", \"AAAA\"],\n [\"CCCC\", \"GGGG\"],\n [\"GGGG\", \"CCCC\"],\n [\"ATGGGAATGA\", \"TCATTCCCAT\"],\n [\"TCATTCCCAT\", \"ATGGGAATGA\"],\n [\"TTTAAAGGGCCC\", \"GGGCCCTTTAAA\"],\n [\"GGGCCCTTTAAA\", \"TTTAAAGGGCCC\"],\n [\"ATCGATCG\", \"CGATCGAT\"],\n [\"CGATCGAT\", \"ATCGATCG\"],\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\" ,\n print \"expected output: \" + str(data[1]) + \",\",CTAATGATGCCCCAT\n o = get_reverse_complement(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\""},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_reverse_complement_unit_tests():\n \n print get_reverse_complement(\"ATGCCCGCTTT\")\n print get_reverse_complement(\"CCGCGTTCA\")\n print get_reverse_complement(\"ACCTTGGAAAATTT\")","def get_reverse_complement_unit_tests():\n input_a='ATTATTATT'\n expected_output='AATAATAAT'\n actual_output=get_reverse_complement(input_a)\n print 'Expected Output is ' + expected_output\n print 'Actual Output is ' +actual_output\n \n input_a='ATTCATATT'\n expected_output='AATATGAAT'\n actual_output=get_reverse_complement(input_a)\n print 'Expected Output is ' + expected_output\n print 'Actual Output is ' +actual_output","def find_complement(num):\n pass","def get_reverse_complement_unit_tests():\n print \"input: GTTGACAGTACGTACAGGGAA, \"+\"output: \"+ get_reverse_complement(\"GTTGACAGTACGTACAGGGAA\") +\", actual output: AAGGGACATGCATGACAGTTG\" \n print \"input: TTATTGCTTATTATCATG, \"+\"output: \"+get_reverse_complement(\"TTATTGCTTATTATCATG\")+\", actual output: GTACTATTATTCGTTATT\"\n print \"input: ATC, \"+\"output: \"+get_reverse_complement(\"ATC\")+\", actual output: GAT\"\n print \"input: CTA, \"+\"output: \"+get_reverse_complement(\"CTA\")+\", actual output: TAG\"","def test_complement(self):\n self.assertEqual(self.RNA(\"UAUCG-NR\").complement(), \"AUAGC-NY\")\n self.assertEqual(self.DNA(\"TATCG-NR\").complement(), \"ATAGC-NY\")\n self.assertEqual(self.DNA(\"\").complement(), \"\")\n self.assertRaises(TypeError, self.PROT(\"ACD\").complement)","def _compute_complement(self, complement):\n if self._.d == 2 and complement is not False:\n if complement is None:\n complement = self._complement()\n self._.complement = self.add_subscheme(complement, \"complement\")","def reverse_difference():","def get_reverse_complement_unit_tests():\n input = [\"dna\"]\n expected_output = [\"reversed_dna\"]\n actual = []\n for j in input:\n actual.append(get_reverse_complement(j))\n print input \n print actual\n print expected_output","def _complement(self):\n assert self._.d == 2, \"the complement is only defined for two classes\"\n kargs = {\"complement\": self}\n if self._has(\"p\"):\n kargs[\"p\"] = self._.p.reorder([0, 2, 1], inplace=False)\n elif self._has(\"q\"):\n kargs[\"q\"] = self._.q.reorder([0, 2, 1], inplace=False)\n elif self._has(\"P\"):\n kargs[\"P\"] = self._.P[[0, 2, 1], [0, 2, 1]]\n elif self._has(\"Q\"):\n kargs[\"Q\"] = self._.Q[[0, 2, 1], [0, 2, 1]]\n return ASParameters(**kargs)","def show_complement(self, **kwargs):\n self._data.switch_complement(whether=None, **kwargs)\n return self._data.show_complement()","def complement(self):\n assert self._.d == 2, \"the complement is only defined for two classes\"\n return self._.complement","def test_binary_complement_shorter_equal_mask(self):\n self.assertEqual(utils.binary_complement('11010', '00010'), '00000')\n self.assertEqual(utils.binary_complement('11010', '0010'), '00000')","def __neg__(self):\n return self[::-1].complement","def get_complement(c):\n if c == 'A':\n return 'T'\n if c == 'C':\n return 'G'\n if c == 'G':\n return 'C'\n if c == 'T':\n return 'A'","def test_binary_complement_longer_mask(self):\n self.assertEqual(utils.binary_complement('11010', '000010'), '00000')","def complement(self):\n comp = self.__class__(self.name, complement(self.seq),\n start=self.start, end=self.end)\n comp.comp = False if self.comp else True\n return comp","def test_right_binary_complement(self):\n self.assertEqual(utils.binary_complement('10110'), '01001')","def complement(x):\n out = 1 - x\n return out","def _complement(self, k, p):\n assert self._.d == 2, \"the complement is only defined for two classes\"\n if checkPos(self._.b[0] - self._.c[2]):\n return self._get_class()((k[2], p[2, 2, 1]),\n (Integer(1), p[1, 2, 2]),\n complement=self)\n else:\n return ASParameters._complement(self)","def complement_base(base):\n return complements[base]","def reverse_complement(seq):\n seq = reverse(seq)\n seq = complement(seq)\n return seq","def get_complement(nucleotide):\n #if statements change nucleotide inputs to their complementary nucleotide\n if nucleotide == \"A\":\n return \"T\"\n if nucleotide == \"T\":\n return \"A\" \n if nucleotide == \"C\":\n return \"G\"\n if nucleotide == \"G\":\n return \"C\"","def reverseComplement(seq):\n seq=seq.upper()\n # complement\n compl = complement(seq)\n # reverse\n return compl[::-1]","def get_complement(nucleotide): # This one works\n nuc = list(nucleotide)\n count = 0\n complement = ''\n for element in nuc:\n if element == 'A':\n nuc[count] = 'T'\n elif element == 'T':\n nuc[count] = 'A'\n elif element == 'C':\n nuc[count] = 'G'\n elif element == 'G':\n nuc[count] = 'C'\n complement = complement + nuc[count]\n count = count + 1\n return complement","def complement(self, **kwargs):\n self._data.switch_complement(whether=True, **kwargs)\n return self","def get_complement(nucleotide):\n if nucleotide == 'A':\n return 'T'\n elif nucleotide == 'C':\n return 'G'\n elif nucleotide == 'G':\n return 'C'\n elif nucleotide == 'T':\n return 'A'\n else:\n return None","def __invert__(self) -> Seq:\n return self.reverse_complement()","def get_complement(nucleotide):\n\n if nucleotide == 'T':\n return 'A'\n elif nucleotide == 'A':\n return 'T'\n elif nucleotide == 'C':\n return 'G'\n elif nucleotide == 'G':\n return 'C'","def reverse_complement(seq):\n if sys.version_info.major == 2:\n conversion = string.maketrans('ACGTacgt','TGCAtgca')\n else:\n conversion = str.maketrans('ACGTacgt','TGCAtgca')\n\n comp = seq.translate(conversion)\n rev_comp = comp[::-1]\n return rev_comp","def get_complement(nucleotide):\n if nucleotide=='A':\n \treturn 'T'\n if nucleotide=='C':\n \treturn 'G'\n if nucleotide=='T':\n \treturn 'A'\n if nucleotide=='G':\n \treturn 'C'","def reverse_complement(seq):\n\n # Initialize dict of complements\n complements = {\n 'A': 'T',\n 'C': 'G',\n 'T': 'A',\n 'G': 'C'\n }\n\n # Initialize reverse complement\n rev_seq = ''\n\n # Loop through and populate list with reverse complement\n for base in reversed(seq.upper()):\n rev_seq += complements[base] \n\n return rev_seq","def complement(fragment: str):\n c = reversed([COMPLEMENTS[l] for l in list(fragment)])\n return \"\".join(c)","def get_complement(nucleotide):\n if nucleotide == 'A':\n return 'T'\n elif nucleotide == 'T':\n return 'A'\n elif nucleotide == 'C':\n return 'G'\n elif nucleotide == 'G':\n return 'C'","def complement_reverse(self):\n self._data.switch_complement(whether=False)\n return self","def reverse_complement(base):\n try:\n assert isinstance(base, str)\n assert len(base) is 1\n rc = str.maketrans('ACGT', 'TGCA') # Traslation table for reverse complentary sequences\n return base.translate(rc)\n except AssertionError:\n raise NotABaseError","def get_complement(nucleotide):\n\n nucDict={'A':'T','G':'C','T':'A','C':'G'}\n return(nucDict[nucleotide])","def get_complement(nucleotide):\n\t# TODO: implement this\n\tletter = str(nucleotide)\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# set letter = parameter (make sure it's a string)\n\tif letter == 'A':\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# check if letter is A\n\t\treturn 'T'\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# return T\n\telif letter == 'T':\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# check if letter is T\n\t\treturn 'A'\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# return A\n\telif letter == 'G':\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# check if letter is G\n\t\treturn 'C'\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# return C\n\telif letter == 'C':\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# check if letter is C\n\t\treturn 'G'\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# return G\n\telse:\n\t\treturn None","def reverse_complement(seq):\n return ''.join([BASE_TO_COMP[b] for b in seq][::-1])","def reverse_complement(sequence):\n return sequence[::-1].translate(RC_TRANS)","def get_reverse_complement(sequence):\n return get_strand_complement(sequence)[::-1]","def __neg__(self) -> 'SInt':\r\n return self.complement()","def get_reverse_complement(dna):\n #set up initial empty strings for later use\n complement = \"\"\n reverse_complement = \"\"\n\n #for each element in the list of dna, get the complement and add it to an empty list\n for i in range(len(dna)):\n complement = complement + get_complement(dna[i]) \n\n #for each element in the list of complement, return the complement by calling the list in reverse\n for i in range(len(dna)):\n reverse_complement = reverse_complement + complement[len(dna)-1-i]\n\n return reverse_complement","def complement(self, aset):\n return self.all_n.difference(aset)","def complement(self):\n if not self.alpha.isComplementable():\n raise RuntimeError(\"Attempt to complement a Distrib \"\n \"based on a non-complementable alphabet.\")\n coms = self.alpha.getComplements()\n new_count = []\n for idx in range(len(coms)):\n cidx = coms[idx]\n if cidx == None:\n cidx = idx\n new_count.append(self.cnt[cidx])\n self.cnt = new_count\n return self","def get_complement(s):\n dna_complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\n return ''.join(filter(None, [ dna_complement[c.upper()] if c.upper() in dna_complement else '' for c in s ] ))","def pslComplementQuery( options) :\n\n iterator = Blat.BlatIterator( sys.stdin )\n\n ninput, noutput, ndiscarded, nskipped = 0, 0, 0, 0\n\n border = options.complement_border\n min_length = options.complement_min_length\n\n while 1:\n \n match = iterator.next()\n if not match: break\n\n ninput += 1 \n if options.test and ninput >= options.test:\n break\n\n if ninput % options.report_step == 0:\n E.info(\"progress: ninput=%i, noutput=%i\" % (ninput, noutput))\n\n if match.mNBlocks <= 1: \n nskipped += 1\n continue\n\n pairs = []\n for qstart, tstart, size in match.getBlocks():\n\n qend = qstart + size - border\n qstart += border\n \n if qend - qstart < options.complement_min_length:\n continue\n\n tend = tstart + size - border\n tstart += border\n\n if tend - tstart < options.complement_min_length:\n continue\n\n ndiscarded += 1\n\n\n options.stdout.write( str( new ) + \"\\n\" )\n noutput += 1\n\n E.info(\"ninput=%i, noutput=%i, nskipped=%i, ndiscarded=%i\" % (ninput, noutput, nskipped, ndiscarded) )","def schur_complement(m11, m12, m21, m22, return_complement_11=False):\n m_m22 = m11 - m12.matmul(m22.inverse().matmul(m21))\n if return_complement_11:\n m_m11 = m22 - m21.matmul(m11.inverse().matmul(m12))\n return (m_m22, m_m11)\n else:\n return m_m22","def get_complement(seta):\n\n complement_set = set()\n\n for elem in seta:\n new_elem_tuple = (elem[0], float(D('1.0') - D(str(elem[1]))))\n complement_set.add(new_elem_tuple)\n\n return complement_set","def get_reverse_complement(dna):\n\n n = len(dna)\n\n i = 0\n\n reverse_dna = []\n\n for i in range(n):\n reverse_dna.append (get_complement(dna[n - 1 - i]))\n reverse_complement = ''.join(reverse_dna)\n return reverse_complement","def get_reverse_complement(sequence):\n seq = sequence.upper()\n return get_strand_complement(seq)[::-1]","def rev_comp(seq):\n return(complement_this(reverse_this(seq)))","def get_reverse_complement(dna):\n l = [get_complement(char) for char in dna[::-1]]\n return ''.join(l)","def get_complement(nucleotide):\n nucDict = {'A':'T', 'T':'A', 'G':'C', 'C':'G'}\n try: \n return nucDict[nucleotide]\n except KeyError:\n print 'input not a nucleotide.'\n return None","def complement(seq,transl=None):\n transl = string.maketrans('aAcCgGtTnNxX-\\t\\n ','tTgGcCaAnNxX-\\t\\n ')\n compl = seq.translate(transl)\n return compl","def reverse_complement(sequence):\n reverse = [complement_base(base) for base in sequence[::-1]]\n return \"\".join(reverse)","def reverse_complement(seq):\n i=0;\n while i < len(seq):\n # Initialize reverse complement\n rev_seq = ''\n\n # Loop through and populate list with reverse complement\n\n rev_seq += complement_base(base)\n\n return rev_seq","def get_complement_events(self):\n\t\tif self.have_complements is False:\n\t\t\tself._extract_complement_events()\n\t\t\tself.have_complements = True\n\n\t\treturn self.complement_events","def get_reverse_complement(dna):\n reverse=[None]*len(dna)\n for i in range(0,len(dna)):\n \treverse[len(dna)-i-1]=get_complement(dna[i])\n s=''\n reverse=s.join(reverse)\n return reverse","def get_reverse_complement(dna):\n rev_comp = ''\n for i in range(0, len(dna)):\n nucleo = dna[i]\n comp = get_complement(nucleo)\n rev_comp = comp + rev_comp\n return rev_comp","def complement(seq):\n complement_dict = {'A': 'T', 'C': 'G', 'T': 'A', 'G': 'C'}\n seq_list = list(seq)\n seq_list = [complement_dict[base] for base in seq_list]\n return ''.join(seq_list)","def get_complement(self, text):\n\n complement_coordinate_map = {}\n\n current_map_coordinates: List[int] = []\n for start_key in self.map:\n start = start_key\n stop = self.map[start_key]\n current_map_coordinates += range(start, stop)\n\n text_coordinates = list(range(0, len(text)))\n complement_coordinates = list(\n set(text_coordinates) - set(current_map_coordinates)\n )\n\n # Remove punctuation from complement coordinates\n punctuation_matcher = re.compile(r\"[^a-zA-Z0-9*]\")\n for i in range(0, len(text)):\n if punctuation_matcher.match(text[i]):\n if i in complement_coordinates:\n complement_coordinates.remove(i)\n\n # Group complement coordinates into ranges\n def to_ranges(iterable):\n iterable = sorted(set(iterable))\n for key, group in itertools.groupby(\n enumerate(iterable), lambda t: t[1] - t[0]\n ):\n group_list = list(group)\n yield group_list[0][1], group_list[-1][1] + 1\n\n complement_coordinate_ranges = list(to_ranges(complement_coordinates))\n\n # Create complement dictionary\n for tup in complement_coordinate_ranges:\n start = tup[0]\n stop = tup[1]\n complement_coordinate_map[start] = stop\n\n return complement_coordinate_map","def get_reverse_complement(s):\n dna_complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\n return ''.join(filter(None, reversed([ dna_complement[c.upper()] if c.upper() in dna_complement else '' for c in s ])))","def test_subtract(self):\n self.assertEqual(work_file.subtract(10, 5), 5)\n self.assertEqual(work_file.subtract(-1, 1), -2)\n self.assertEqual(work_file.subtract(-1, -1), 0)","def get_reverse_complement(cls, pattern: str) -> str:\n return ''.join(reversed([cls.dna_complement[nuc] for nuc in pattern]))","def get_reverse_complement(dna):\n dna2 = get_complement(dna)\n dna3 = dna2[::-1]\n return str(dna3)","def test_correct_backward_order1(self):\r\n coeffs, shifts = finite_diff_coeffs(1, 1, \"backward\")\r\n assert np.allclose(coeffs, [1, -1])\r\n assert np.allclose(shifts, [0, -1])","def reverse_complementary(seq):\n\n complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\n return \"\".join(complement[n] for n in reversed(seq))","def complement(G):\n\n nset = set(G.nodes())\n n_nodes = G.order()\n n_edges = n_nodes * (n_nodes - 1) - G.size() + 1\n \n cmp_edges = ((u, v) for u in G.nodes()\n\t\t for v in nset - set(G.successors(u)))\n deg = make_deg(n_nodes, cmp_edges)\n cmp_edges = ((u, v) for u in G.nodes()\n\t\t for v in nset - set(G.successors(u)))\n H = make(n_nodes, n_edges, cmp_edges, deg)\n return H","def test_negation(self):\n\n a1 = tuples.Tuple([\"a\", \"b\", \"c\", \"d\"], 1, -2, 3, -4)\n\n a2 = -a1\n\n self.assertEqual(a2,\n tuples.Tuple([\"a\", \"b\", \"c\", \"d\"], -1, 2, -3, 4))","def ind_complement(inds, n):\n return tuple(i for i in range(n) if i not in inds)","def twos_complement(input_value, num_bits=16):\n mask = 2 ** (num_bits - 1)\n return -(input_value & mask) + (input_value & ~mask)","def ones_complement(val):\n #mask = (1 << val.bit_length()) - 1\n #return int(hex(val ^ mask), 16)\n b = bin(val)\n b = b.replace('0', 'x')\n b = b.replace('1', '0')\n b = b.replace('x', '1')\n b = b.replace('1b', '0b')\n return int(b, 2)","def reverse_complement(sequence):\n try:\n return ''.join([COMPLEMENTARY_BASE[base]\n for base in reversed(sequence)])\n except KeyError:\n raise ValueError('Not able to reverse complement: %s' % sequence)","def ReverseComplement(self):\n if (self.translated == False):\n for i in range(len(self.alignment)):\n self.alignment[i].seq = self.alignment[i].seq.reverse_complement()\n self.Show(self.displayedColumn)\n self.BackupAlignment()\n else:\n self.AlertMessage(\"Can't reverse-complement protein sequences.\", 'medium')","def complement(self):\n result = self.completion()\n for state in result.iter_states():\n state.is_final = not state.is_final\n\n return result","def test_neg_sub():\n c=[1,2]\n def myfunc(x,y):\n f1=1-x-y-2\n return -f1\n\n f_obj=ADiff(myfunc)\n res=f_obj.Jac(c)\n\n expectAns={'diff': [1,1], 'value': 4}\n\n assert res==expectAns","def get_reverse_complement(dna):\n L=dna\n rdna=L[::-1]\n print rdna\n newrdna=\"\"\n for i in range(0,len(rdna)):\n if rdna[i]=='A':\n newrdna='T'+newrdna\n elif rdna[i]=='G':\n newrdna='C'+newrdna\n elif rdna[i]=='T':\n newrdna='A'+newrdna\n elif rdna[i]=='C':\n newrdna='G'+newrdna\n S=newrdna\n P=S[::-1]\n return P","def minus(self, a, b):\n return a - b","def reverse_complement(pattern):\n\n complement = ''\n for i in range(len(pattern)):\n if pattern[i] == 'A':\n complement = complement + 'T'\n elif pattern[i] == 'T':\n complement = complement + 'A'\n elif pattern[i] == 'C':\n complement = complement + 'G'\n else:\n complement = complement + 'C'\n rev_complement = list(reversed(complement))\n return ''.join(rev_complement)","def twos_complement(val, bits):\n if (val & (1 << (bits - 1))) != 0: # if sign bit is set\n val = val - (2 ** bits) # compute negative value\n return val","def test_minus(self):\n self.assertEqual(1, minus(3, 2))","def reverse_and_complement(string):\n reverse_dict = dict([('A', 'T'), ('T', 'A'), ('C', 'G'), ('G', 'C'), ('*', '*')])\n complement_string = ''.join([reverse_dict[c] for c in string])\n return complement_string[::-1]","def test_contract_deepcopy_regression(entities, role):\n e1, e2 = entities\n c = f.Contract(e1, role.role, e2, \"ref\")\n i = c.get_inverse()\n assert i.entities[0] is e2\n assert i.entities[1] is e1","def reverseComplement(self):\n i = 0\n j = len(self.counts)-1\n while (i < j):\n temp = self.counts[i];\n self.counts[i] = self.counts[j]\n self.counts[j] = temp\n self.counts[i].complement()\n self.counts[j].complement()\n i += 1;\n j -= 1;\n if i == j:\n self.counts[i].complement()\n return self","def twos_complement(val, bits):\n if (val & (1 << (bits - 1))) != 0: # if sign bit is set e.g., 8bit: 128-255\n val = val - (1 << bits) # compute negative value\n return val # return positive value as is","def get_reverse_complement(dna):\n dna=\"ATCG\"\n b = list(dna)\n b.reverse()\n \"\".join(b)\n\n for n in range(0, len(b), 1):\n if b[n] == \"A\":\n b[n] = \"T\"\n elif b[n] == \"C\":\n b[n] = \"G\"\n elif b[n] == \"T\":\n b[n] = \"A\"\n elif b[n] == \"G\":\n b[n] = \"C\"\n \n print \"\".join(b)","def get_reverse_complement(dna):\n \n dna = dna.replace('T','N')\n dna = dna.replace('A','T')\n dna = dna.replace('N','A')\n dna = dna.replace('C','N')\n dna = dna.replace('G','C')\n dna = dna.replace('N','G')\n dna = dna[::-1]\n return dna","def complement(seq):\n if PY3:\n table = str.maketrans('ACTGNactg', 'TGACNtgac')\n elif PY2:\n table = string.maketrans('ACTGNactg', 'TGACNtgac')\n return str(seq).translate(table)","def reverseComplementAll(self):\n\t\tseqDict = self.sequenceDict()\n\t\tfor i in range(len(seqDict.keys())):\n\t\t\tx = seqDict.keys()[i]\n\t\t\tprint self.reverseComplement(x)\n\t\treturn ''","def test_clifford_1_qubit_generation(self):\n clifford_dicts = [\n {\"stabilizer\": [\"+Z\"], \"destabilizer\": [\"+X\"]},\n {\"stabilizer\": [\"+X\"], \"destabilizer\": [\"+Z\"]},\n {\"stabilizer\": [\"+Y\"], \"destabilizer\": [\"+X\"]},\n {\"stabilizer\": [\"+X\"], \"destabilizer\": [\"+Y\"]},\n {\"stabilizer\": [\"+Z\"], \"destabilizer\": [\"+Y\"]},\n {\"stabilizer\": [\"+Y\"], \"destabilizer\": [\"+Z\"]},\n {\"stabilizer\": [\"-Z\"], \"destabilizer\": [\"+X\"]},\n {\"stabilizer\": [\"+X\"], \"destabilizer\": [\"-Z\"]},\n {\"stabilizer\": [\"-Y\"], \"destabilizer\": [\"+X\"]},\n {\"stabilizer\": [\"+X\"], \"destabilizer\": [\"-Y\"]},\n {\"stabilizer\": [\"-Z\"], \"destabilizer\": [\"-Y\"]},\n {\"stabilizer\": [\"-Y\"], \"destabilizer\": [\"-Z\"]},\n {\"stabilizer\": [\"-Z\"], \"destabilizer\": [\"-X\"]},\n {\"stabilizer\": [\"-X\"], \"destabilizer\": [\"-Z\"]},\n {\"stabilizer\": [\"+Y\"], \"destabilizer\": [\"-X\"]},\n {\"stabilizer\": [\"-X\"], \"destabilizer\": [\"+Y\"]},\n {\"stabilizer\": [\"-Z\"], \"destabilizer\": [\"+Y\"]},\n {\"stabilizer\": [\"+Y\"], \"destabilizer\": [\"-Z\"]},\n {\"stabilizer\": [\"+Z\"], \"destabilizer\": [\"-X\"]},\n {\"stabilizer\": [\"-X\"], \"destabilizer\": [\"+Z\"]},\n {\"stabilizer\": [\"-Y\"], \"destabilizer\": [\"-X\"]},\n {\"stabilizer\": [\"-X\"], \"destabilizer\": [\"-Y\"]},\n {\"stabilizer\": [\"+Z\"], \"destabilizer\": [\"-Y\"]},\n {\"stabilizer\": [\"-Y\"], \"destabilizer\": [\"+Z\"]},\n ]\n cliffords = [Clifford.from_dict(i) for i in clifford_dicts]\n for n in range(24):\n clifford = CliffordUtils.clifford_1_qubit(n)\n self.assertEqual(clifford, cliffords[n])","def __invert(self, args):","def complement(self) -> JustLatticeChord:\n nodes = []\n for node in self._nodes:\n nodes.append(list(map(lambda x, y: y - x, node, self._root)))\n return JustLatticeChord(self._fundamental, self._root, nodes)","def reverseComplement(self):\n quality = None if self.quality is None else self.quality[::-1]\n sequence = self.sequence.translate(self.COMPLEMENT_TABLE)[::-1]\n return self.__class__(self.id, sequence, quality)","def test_exact_two_qubit_cnot_decompose_paulis(self):\n unitary = Operator.from_label(\"XZ\")\n self.check_exact_decomposition(unitary.data, two_qubit_cnot_decompose)","def complement(chromosome, point1, point2):\r\n new_chromosome = \"\"\r\n\r\n for i in range(len(chromosome)):\r\n if i >= point1 and i <= point2:\r\n if chromosome[i] == '0':\r\n new_chromosome += '1'\r\n else:\r\n new_chromosome += '0'\r\n else:\r\n new_chromosome += chromosome[i]\r\n\r\n return new_chromosome","def get_reverse_complement(dna):\r\n\r\n seq = Seq(dna)\r\n rev_seq = seq.reverse_complement()\r\n return str(rev_seq)","def __sub__(self, tc):\n tc = TwosComplement(tc)._negative()\n return self.__add__(tc)","def test_minus(self):\n self.assertEqual(1, foo.minus(3, 2))","def __invert__(self):\n return self.reverse()","def get_reverse_complement(dna):\n reverseDNA = ''\n newDNA = ''\n for i in range(len(dna)): \n reverseDNA+= dna[-1-i]\n for k in range(len(dna)): \n if reverseDNA[k] == 'A': \n newDNA+='T'\n elif reverseDNA[k] =='T':\n newDNA+= 'A' \n elif reverseDNA[k] =='G':\n newDNA+= 'C'\n elif reverseDNA[k] =='C':\n newDNA+= 'G' \n return newDNA"],"string":"[\n \"def get_reverse_complement_unit_tests():\\n \\n print get_reverse_complement(\\\"ATGCCCGCTTT\\\")\\n print get_reverse_complement(\\\"CCGCGTTCA\\\")\\n print get_reverse_complement(\\\"ACCTTGGAAAATTT\\\")\",\n \"def get_reverse_complement_unit_tests():\\n input_a='ATTATTATT'\\n expected_output='AATAATAAT'\\n actual_output=get_reverse_complement(input_a)\\n print 'Expected Output is ' + expected_output\\n print 'Actual Output is ' +actual_output\\n \\n input_a='ATTCATATT'\\n expected_output='AATATGAAT'\\n actual_output=get_reverse_complement(input_a)\\n print 'Expected Output is ' + expected_output\\n print 'Actual Output is ' +actual_output\",\n \"def find_complement(num):\\n pass\",\n \"def get_reverse_complement_unit_tests():\\n print \\\"input: GTTGACAGTACGTACAGGGAA, \\\"+\\\"output: \\\"+ get_reverse_complement(\\\"GTTGACAGTACGTACAGGGAA\\\") +\\\", actual output: AAGGGACATGCATGACAGTTG\\\" \\n print \\\"input: TTATTGCTTATTATCATG, \\\"+\\\"output: \\\"+get_reverse_complement(\\\"TTATTGCTTATTATCATG\\\")+\\\", actual output: GTACTATTATTCGTTATT\\\"\\n print \\\"input: ATC, \\\"+\\\"output: \\\"+get_reverse_complement(\\\"ATC\\\")+\\\", actual output: GAT\\\"\\n print \\\"input: CTA, \\\"+\\\"output: \\\"+get_reverse_complement(\\\"CTA\\\")+\\\", actual output: TAG\\\"\",\n \"def test_complement(self):\\n self.assertEqual(self.RNA(\\\"UAUCG-NR\\\").complement(), \\\"AUAGC-NY\\\")\\n self.assertEqual(self.DNA(\\\"TATCG-NR\\\").complement(), \\\"ATAGC-NY\\\")\\n self.assertEqual(self.DNA(\\\"\\\").complement(), \\\"\\\")\\n self.assertRaises(TypeError, self.PROT(\\\"ACD\\\").complement)\",\n \"def _compute_complement(self, complement):\\n if self._.d == 2 and complement is not False:\\n if complement is None:\\n complement = self._complement()\\n self._.complement = self.add_subscheme(complement, \\\"complement\\\")\",\n \"def reverse_difference():\",\n \"def get_reverse_complement_unit_tests():\\n input = [\\\"dna\\\"]\\n expected_output = [\\\"reversed_dna\\\"]\\n actual = []\\n for j in input:\\n actual.append(get_reverse_complement(j))\\n print input \\n print actual\\n print expected_output\",\n \"def _complement(self):\\n assert self._.d == 2, \\\"the complement is only defined for two classes\\\"\\n kargs = {\\\"complement\\\": self}\\n if self._has(\\\"p\\\"):\\n kargs[\\\"p\\\"] = self._.p.reorder([0, 2, 1], inplace=False)\\n elif self._has(\\\"q\\\"):\\n kargs[\\\"q\\\"] = self._.q.reorder([0, 2, 1], inplace=False)\\n elif self._has(\\\"P\\\"):\\n kargs[\\\"P\\\"] = self._.P[[0, 2, 1], [0, 2, 1]]\\n elif self._has(\\\"Q\\\"):\\n kargs[\\\"Q\\\"] = self._.Q[[0, 2, 1], [0, 2, 1]]\\n return ASParameters(**kargs)\",\n \"def show_complement(self, **kwargs):\\n self._data.switch_complement(whether=None, **kwargs)\\n return self._data.show_complement()\",\n \"def complement(self):\\n assert self._.d == 2, \\\"the complement is only defined for two classes\\\"\\n return self._.complement\",\n \"def test_binary_complement_shorter_equal_mask(self):\\n self.assertEqual(utils.binary_complement('11010', '00010'), '00000')\\n self.assertEqual(utils.binary_complement('11010', '0010'), '00000')\",\n \"def __neg__(self):\\n return self[::-1].complement\",\n \"def get_complement(c):\\n if c == 'A':\\n return 'T'\\n if c == 'C':\\n return 'G'\\n if c == 'G':\\n return 'C'\\n if c == 'T':\\n return 'A'\",\n \"def test_binary_complement_longer_mask(self):\\n self.assertEqual(utils.binary_complement('11010', '000010'), '00000')\",\n \"def complement(self):\\n comp = self.__class__(self.name, complement(self.seq),\\n start=self.start, end=self.end)\\n comp.comp = False if self.comp else True\\n return comp\",\n \"def test_right_binary_complement(self):\\n self.assertEqual(utils.binary_complement('10110'), '01001')\",\n \"def complement(x):\\n out = 1 - x\\n return out\",\n \"def _complement(self, k, p):\\n assert self._.d == 2, \\\"the complement is only defined for two classes\\\"\\n if checkPos(self._.b[0] - self._.c[2]):\\n return self._get_class()((k[2], p[2, 2, 1]),\\n (Integer(1), p[1, 2, 2]),\\n complement=self)\\n else:\\n return ASParameters._complement(self)\",\n \"def complement_base(base):\\n return complements[base]\",\n \"def reverse_complement(seq):\\n seq = reverse(seq)\\n seq = complement(seq)\\n return seq\",\n \"def get_complement(nucleotide):\\n #if statements change nucleotide inputs to their complementary nucleotide\\n if nucleotide == \\\"A\\\":\\n return \\\"T\\\"\\n if nucleotide == \\\"T\\\":\\n return \\\"A\\\" \\n if nucleotide == \\\"C\\\":\\n return \\\"G\\\"\\n if nucleotide == \\\"G\\\":\\n return \\\"C\\\"\",\n \"def reverseComplement(seq):\\n seq=seq.upper()\\n # complement\\n compl = complement(seq)\\n # reverse\\n return compl[::-1]\",\n \"def get_complement(nucleotide): # This one works\\n nuc = list(nucleotide)\\n count = 0\\n complement = ''\\n for element in nuc:\\n if element == 'A':\\n nuc[count] = 'T'\\n elif element == 'T':\\n nuc[count] = 'A'\\n elif element == 'C':\\n nuc[count] = 'G'\\n elif element == 'G':\\n nuc[count] = 'C'\\n complement = complement + nuc[count]\\n count = count + 1\\n return complement\",\n \"def complement(self, **kwargs):\\n self._data.switch_complement(whether=True, **kwargs)\\n return self\",\n \"def get_complement(nucleotide):\\n if nucleotide == 'A':\\n return 'T'\\n elif nucleotide == 'C':\\n return 'G'\\n elif nucleotide == 'G':\\n return 'C'\\n elif nucleotide == 'T':\\n return 'A'\\n else:\\n return None\",\n \"def __invert__(self) -> Seq:\\n return self.reverse_complement()\",\n \"def get_complement(nucleotide):\\n\\n if nucleotide == 'T':\\n return 'A'\\n elif nucleotide == 'A':\\n return 'T'\\n elif nucleotide == 'C':\\n return 'G'\\n elif nucleotide == 'G':\\n return 'C'\",\n \"def reverse_complement(seq):\\n if sys.version_info.major == 2:\\n conversion = string.maketrans('ACGTacgt','TGCAtgca')\\n else:\\n conversion = str.maketrans('ACGTacgt','TGCAtgca')\\n\\n comp = seq.translate(conversion)\\n rev_comp = comp[::-1]\\n return rev_comp\",\n \"def get_complement(nucleotide):\\n if nucleotide=='A':\\n \\treturn 'T'\\n if nucleotide=='C':\\n \\treturn 'G'\\n if nucleotide=='T':\\n \\treturn 'A'\\n if nucleotide=='G':\\n \\treturn 'C'\",\n \"def reverse_complement(seq):\\n\\n # Initialize dict of complements\\n complements = {\\n 'A': 'T',\\n 'C': 'G',\\n 'T': 'A',\\n 'G': 'C'\\n }\\n\\n # Initialize reverse complement\\n rev_seq = ''\\n\\n # Loop through and populate list with reverse complement\\n for base in reversed(seq.upper()):\\n rev_seq += complements[base] \\n\\n return rev_seq\",\n \"def complement(fragment: str):\\n c = reversed([COMPLEMENTS[l] for l in list(fragment)])\\n return \\\"\\\".join(c)\",\n \"def get_complement(nucleotide):\\n if nucleotide == 'A':\\n return 'T'\\n elif nucleotide == 'T':\\n return 'A'\\n elif nucleotide == 'C':\\n return 'G'\\n elif nucleotide == 'G':\\n return 'C'\",\n \"def complement_reverse(self):\\n self._data.switch_complement(whether=False)\\n return self\",\n \"def reverse_complement(base):\\n try:\\n assert isinstance(base, str)\\n assert len(base) is 1\\n rc = str.maketrans('ACGT', 'TGCA') # Traslation table for reverse complentary sequences\\n return base.translate(rc)\\n except AssertionError:\\n raise NotABaseError\",\n \"def get_complement(nucleotide):\\n\\n nucDict={'A':'T','G':'C','T':'A','C':'G'}\\n return(nucDict[nucleotide])\",\n \"def get_complement(nucleotide):\\n\\t# TODO: implement this\\n\\tletter = str(nucleotide)\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# set letter = parameter (make sure it's a string)\\n\\tif letter == 'A':\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# check if letter is A\\n\\t\\treturn 'T'\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# return T\\n\\telif letter == 'T':\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# check if letter is T\\n\\t\\treturn 'A'\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# return A\\n\\telif letter == 'G':\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# check if letter is G\\n\\t\\treturn 'C'\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# return C\\n\\telif letter == 'C':\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# check if letter is C\\n\\t\\treturn 'G'\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# return G\\n\\telse:\\n\\t\\treturn None\",\n \"def reverse_complement(seq):\\n return ''.join([BASE_TO_COMP[b] for b in seq][::-1])\",\n \"def reverse_complement(sequence):\\n return sequence[::-1].translate(RC_TRANS)\",\n \"def get_reverse_complement(sequence):\\n return get_strand_complement(sequence)[::-1]\",\n \"def __neg__(self) -> 'SInt':\\r\\n return self.complement()\",\n \"def get_reverse_complement(dna):\\n #set up initial empty strings for later use\\n complement = \\\"\\\"\\n reverse_complement = \\\"\\\"\\n\\n #for each element in the list of dna, get the complement and add it to an empty list\\n for i in range(len(dna)):\\n complement = complement + get_complement(dna[i]) \\n\\n #for each element in the list of complement, return the complement by calling the list in reverse\\n for i in range(len(dna)):\\n reverse_complement = reverse_complement + complement[len(dna)-1-i]\\n\\n return reverse_complement\",\n \"def complement(self, aset):\\n return self.all_n.difference(aset)\",\n \"def complement(self):\\n if not self.alpha.isComplementable():\\n raise RuntimeError(\\\"Attempt to complement a Distrib \\\"\\n \\\"based on a non-complementable alphabet.\\\")\\n coms = self.alpha.getComplements()\\n new_count = []\\n for idx in range(len(coms)):\\n cidx = coms[idx]\\n if cidx == None:\\n cidx = idx\\n new_count.append(self.cnt[cidx])\\n self.cnt = new_count\\n return self\",\n \"def get_complement(s):\\n dna_complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\\n return ''.join(filter(None, [ dna_complement[c.upper()] if c.upper() in dna_complement else '' for c in s ] ))\",\n \"def pslComplementQuery( options) :\\n\\n iterator = Blat.BlatIterator( sys.stdin )\\n\\n ninput, noutput, ndiscarded, nskipped = 0, 0, 0, 0\\n\\n border = options.complement_border\\n min_length = options.complement_min_length\\n\\n while 1:\\n \\n match = iterator.next()\\n if not match: break\\n\\n ninput += 1 \\n if options.test and ninput >= options.test:\\n break\\n\\n if ninput % options.report_step == 0:\\n E.info(\\\"progress: ninput=%i, noutput=%i\\\" % (ninput, noutput))\\n\\n if match.mNBlocks <= 1: \\n nskipped += 1\\n continue\\n\\n pairs = []\\n for qstart, tstart, size in match.getBlocks():\\n\\n qend = qstart + size - border\\n qstart += border\\n \\n if qend - qstart < options.complement_min_length:\\n continue\\n\\n tend = tstart + size - border\\n tstart += border\\n\\n if tend - tstart < options.complement_min_length:\\n continue\\n\\n ndiscarded += 1\\n\\n\\n options.stdout.write( str( new ) + \\\"\\\\n\\\" )\\n noutput += 1\\n\\n E.info(\\\"ninput=%i, noutput=%i, nskipped=%i, ndiscarded=%i\\\" % (ninput, noutput, nskipped, ndiscarded) )\",\n \"def schur_complement(m11, m12, m21, m22, return_complement_11=False):\\n m_m22 = m11 - m12.matmul(m22.inverse().matmul(m21))\\n if return_complement_11:\\n m_m11 = m22 - m21.matmul(m11.inverse().matmul(m12))\\n return (m_m22, m_m11)\\n else:\\n return m_m22\",\n \"def get_complement(seta):\\n\\n complement_set = set()\\n\\n for elem in seta:\\n new_elem_tuple = (elem[0], float(D('1.0') - D(str(elem[1]))))\\n complement_set.add(new_elem_tuple)\\n\\n return complement_set\",\n \"def get_reverse_complement(dna):\\n\\n n = len(dna)\\n\\n i = 0\\n\\n reverse_dna = []\\n\\n for i in range(n):\\n reverse_dna.append (get_complement(dna[n - 1 - i]))\\n reverse_complement = ''.join(reverse_dna)\\n return reverse_complement\",\n \"def get_reverse_complement(sequence):\\n seq = sequence.upper()\\n return get_strand_complement(seq)[::-1]\",\n \"def rev_comp(seq):\\n return(complement_this(reverse_this(seq)))\",\n \"def get_reverse_complement(dna):\\n l = [get_complement(char) for char in dna[::-1]]\\n return ''.join(l)\",\n \"def get_complement(nucleotide):\\n nucDict = {'A':'T', 'T':'A', 'G':'C', 'C':'G'}\\n try: \\n return nucDict[nucleotide]\\n except KeyError:\\n print 'input not a nucleotide.'\\n return None\",\n \"def complement(seq,transl=None):\\n transl = string.maketrans('aAcCgGtTnNxX-\\\\t\\\\n ','tTgGcCaAnNxX-\\\\t\\\\n ')\\n compl = seq.translate(transl)\\n return compl\",\n \"def reverse_complement(sequence):\\n reverse = [complement_base(base) for base in sequence[::-1]]\\n return \\\"\\\".join(reverse)\",\n \"def reverse_complement(seq):\\n i=0;\\n while i < len(seq):\\n # Initialize reverse complement\\n rev_seq = ''\\n\\n # Loop through and populate list with reverse complement\\n\\n rev_seq += complement_base(base)\\n\\n return rev_seq\",\n \"def get_complement_events(self):\\n\\t\\tif self.have_complements is False:\\n\\t\\t\\tself._extract_complement_events()\\n\\t\\t\\tself.have_complements = True\\n\\n\\t\\treturn self.complement_events\",\n \"def get_reverse_complement(dna):\\n reverse=[None]*len(dna)\\n for i in range(0,len(dna)):\\n \\treverse[len(dna)-i-1]=get_complement(dna[i])\\n s=''\\n reverse=s.join(reverse)\\n return reverse\",\n \"def get_reverse_complement(dna):\\n rev_comp = ''\\n for i in range(0, len(dna)):\\n nucleo = dna[i]\\n comp = get_complement(nucleo)\\n rev_comp = comp + rev_comp\\n return rev_comp\",\n \"def complement(seq):\\n complement_dict = {'A': 'T', 'C': 'G', 'T': 'A', 'G': 'C'}\\n seq_list = list(seq)\\n seq_list = [complement_dict[base] for base in seq_list]\\n return ''.join(seq_list)\",\n \"def get_complement(self, text):\\n\\n complement_coordinate_map = {}\\n\\n current_map_coordinates: List[int] = []\\n for start_key in self.map:\\n start = start_key\\n stop = self.map[start_key]\\n current_map_coordinates += range(start, stop)\\n\\n text_coordinates = list(range(0, len(text)))\\n complement_coordinates = list(\\n set(text_coordinates) - set(current_map_coordinates)\\n )\\n\\n # Remove punctuation from complement coordinates\\n punctuation_matcher = re.compile(r\\\"[^a-zA-Z0-9*]\\\")\\n for i in range(0, len(text)):\\n if punctuation_matcher.match(text[i]):\\n if i in complement_coordinates:\\n complement_coordinates.remove(i)\\n\\n # Group complement coordinates into ranges\\n def to_ranges(iterable):\\n iterable = sorted(set(iterable))\\n for key, group in itertools.groupby(\\n enumerate(iterable), lambda t: t[1] - t[0]\\n ):\\n group_list = list(group)\\n yield group_list[0][1], group_list[-1][1] + 1\\n\\n complement_coordinate_ranges = list(to_ranges(complement_coordinates))\\n\\n # Create complement dictionary\\n for tup in complement_coordinate_ranges:\\n start = tup[0]\\n stop = tup[1]\\n complement_coordinate_map[start] = stop\\n\\n return complement_coordinate_map\",\n \"def get_reverse_complement(s):\\n dna_complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\\n return ''.join(filter(None, reversed([ dna_complement[c.upper()] if c.upper() in dna_complement else '' for c in s ])))\",\n \"def test_subtract(self):\\n self.assertEqual(work_file.subtract(10, 5), 5)\\n self.assertEqual(work_file.subtract(-1, 1), -2)\\n self.assertEqual(work_file.subtract(-1, -1), 0)\",\n \"def get_reverse_complement(cls, pattern: str) -> str:\\n return ''.join(reversed([cls.dna_complement[nuc] for nuc in pattern]))\",\n \"def get_reverse_complement(dna):\\n dna2 = get_complement(dna)\\n dna3 = dna2[::-1]\\n return str(dna3)\",\n \"def test_correct_backward_order1(self):\\r\\n coeffs, shifts = finite_diff_coeffs(1, 1, \\\"backward\\\")\\r\\n assert np.allclose(coeffs, [1, -1])\\r\\n assert np.allclose(shifts, [0, -1])\",\n \"def reverse_complementary(seq):\\n\\n complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\\n return \\\"\\\".join(complement[n] for n in reversed(seq))\",\n \"def complement(G):\\n\\n nset = set(G.nodes())\\n n_nodes = G.order()\\n n_edges = n_nodes * (n_nodes - 1) - G.size() + 1\\n \\n cmp_edges = ((u, v) for u in G.nodes()\\n\\t\\t for v in nset - set(G.successors(u)))\\n deg = make_deg(n_nodes, cmp_edges)\\n cmp_edges = ((u, v) for u in G.nodes()\\n\\t\\t for v in nset - set(G.successors(u)))\\n H = make(n_nodes, n_edges, cmp_edges, deg)\\n return H\",\n \"def test_negation(self):\\n\\n a1 = tuples.Tuple([\\\"a\\\", \\\"b\\\", \\\"c\\\", \\\"d\\\"], 1, -2, 3, -4)\\n\\n a2 = -a1\\n\\n self.assertEqual(a2,\\n tuples.Tuple([\\\"a\\\", \\\"b\\\", \\\"c\\\", \\\"d\\\"], -1, 2, -3, 4))\",\n \"def ind_complement(inds, n):\\n return tuple(i for i in range(n) if i not in inds)\",\n \"def twos_complement(input_value, num_bits=16):\\n mask = 2 ** (num_bits - 1)\\n return -(input_value & mask) + (input_value & ~mask)\",\n \"def ones_complement(val):\\n #mask = (1 << val.bit_length()) - 1\\n #return int(hex(val ^ mask), 16)\\n b = bin(val)\\n b = b.replace('0', 'x')\\n b = b.replace('1', '0')\\n b = b.replace('x', '1')\\n b = b.replace('1b', '0b')\\n return int(b, 2)\",\n \"def reverse_complement(sequence):\\n try:\\n return ''.join([COMPLEMENTARY_BASE[base]\\n for base in reversed(sequence)])\\n except KeyError:\\n raise ValueError('Not able to reverse complement: %s' % sequence)\",\n \"def ReverseComplement(self):\\n if (self.translated == False):\\n for i in range(len(self.alignment)):\\n self.alignment[i].seq = self.alignment[i].seq.reverse_complement()\\n self.Show(self.displayedColumn)\\n self.BackupAlignment()\\n else:\\n self.AlertMessage(\\\"Can't reverse-complement protein sequences.\\\", 'medium')\",\n \"def complement(self):\\n result = self.completion()\\n for state in result.iter_states():\\n state.is_final = not state.is_final\\n\\n return result\",\n \"def test_neg_sub():\\n c=[1,2]\\n def myfunc(x,y):\\n f1=1-x-y-2\\n return -f1\\n\\n f_obj=ADiff(myfunc)\\n res=f_obj.Jac(c)\\n\\n expectAns={'diff': [1,1], 'value': 4}\\n\\n assert res==expectAns\",\n \"def get_reverse_complement(dna):\\n L=dna\\n rdna=L[::-1]\\n print rdna\\n newrdna=\\\"\\\"\\n for i in range(0,len(rdna)):\\n if rdna[i]=='A':\\n newrdna='T'+newrdna\\n elif rdna[i]=='G':\\n newrdna='C'+newrdna\\n elif rdna[i]=='T':\\n newrdna='A'+newrdna\\n elif rdna[i]=='C':\\n newrdna='G'+newrdna\\n S=newrdna\\n P=S[::-1]\\n return P\",\n \"def minus(self, a, b):\\n return a - b\",\n \"def reverse_complement(pattern):\\n\\n complement = ''\\n for i in range(len(pattern)):\\n if pattern[i] == 'A':\\n complement = complement + 'T'\\n elif pattern[i] == 'T':\\n complement = complement + 'A'\\n elif pattern[i] == 'C':\\n complement = complement + 'G'\\n else:\\n complement = complement + 'C'\\n rev_complement = list(reversed(complement))\\n return ''.join(rev_complement)\",\n \"def twos_complement(val, bits):\\n if (val & (1 << (bits - 1))) != 0: # if sign bit is set\\n val = val - (2 ** bits) # compute negative value\\n return val\",\n \"def test_minus(self):\\n self.assertEqual(1, minus(3, 2))\",\n \"def reverse_and_complement(string):\\n reverse_dict = dict([('A', 'T'), ('T', 'A'), ('C', 'G'), ('G', 'C'), ('*', '*')])\\n complement_string = ''.join([reverse_dict[c] for c in string])\\n return complement_string[::-1]\",\n \"def test_contract_deepcopy_regression(entities, role):\\n e1, e2 = entities\\n c = f.Contract(e1, role.role, e2, \\\"ref\\\")\\n i = c.get_inverse()\\n assert i.entities[0] is e2\\n assert i.entities[1] is e1\",\n \"def reverseComplement(self):\\n i = 0\\n j = len(self.counts)-1\\n while (i < j):\\n temp = self.counts[i];\\n self.counts[i] = self.counts[j]\\n self.counts[j] = temp\\n self.counts[i].complement()\\n self.counts[j].complement()\\n i += 1;\\n j -= 1;\\n if i == j:\\n self.counts[i].complement()\\n return self\",\n \"def twos_complement(val, bits):\\n if (val & (1 << (bits - 1))) != 0: # if sign bit is set e.g., 8bit: 128-255\\n val = val - (1 << bits) # compute negative value\\n return val # return positive value as is\",\n \"def get_reverse_complement(dna):\\n dna=\\\"ATCG\\\"\\n b = list(dna)\\n b.reverse()\\n \\\"\\\".join(b)\\n\\n for n in range(0, len(b), 1):\\n if b[n] == \\\"A\\\":\\n b[n] = \\\"T\\\"\\n elif b[n] == \\\"C\\\":\\n b[n] = \\\"G\\\"\\n elif b[n] == \\\"T\\\":\\n b[n] = \\\"A\\\"\\n elif b[n] == \\\"G\\\":\\n b[n] = \\\"C\\\"\\n \\n print \\\"\\\".join(b)\",\n \"def get_reverse_complement(dna):\\n \\n dna = dna.replace('T','N')\\n dna = dna.replace('A','T')\\n dna = dna.replace('N','A')\\n dna = dna.replace('C','N')\\n dna = dna.replace('G','C')\\n dna = dna.replace('N','G')\\n dna = dna[::-1]\\n return dna\",\n \"def complement(seq):\\n if PY3:\\n table = str.maketrans('ACTGNactg', 'TGACNtgac')\\n elif PY2:\\n table = string.maketrans('ACTGNactg', 'TGACNtgac')\\n return str(seq).translate(table)\",\n \"def reverseComplementAll(self):\\n\\t\\tseqDict = self.sequenceDict()\\n\\t\\tfor i in range(len(seqDict.keys())):\\n\\t\\t\\tx = seqDict.keys()[i]\\n\\t\\t\\tprint self.reverseComplement(x)\\n\\t\\treturn ''\",\n \"def test_clifford_1_qubit_generation(self):\\n clifford_dicts = [\\n {\\\"stabilizer\\\": [\\\"+Z\\\"], \\\"destabilizer\\\": [\\\"+X\\\"]},\\n {\\\"stabilizer\\\": [\\\"+X\\\"], \\\"destabilizer\\\": [\\\"+Z\\\"]},\\n {\\\"stabilizer\\\": [\\\"+Y\\\"], \\\"destabilizer\\\": [\\\"+X\\\"]},\\n {\\\"stabilizer\\\": [\\\"+X\\\"], \\\"destabilizer\\\": [\\\"+Y\\\"]},\\n {\\\"stabilizer\\\": [\\\"+Z\\\"], \\\"destabilizer\\\": [\\\"+Y\\\"]},\\n {\\\"stabilizer\\\": [\\\"+Y\\\"], \\\"destabilizer\\\": [\\\"+Z\\\"]},\\n {\\\"stabilizer\\\": [\\\"-Z\\\"], \\\"destabilizer\\\": [\\\"+X\\\"]},\\n {\\\"stabilizer\\\": [\\\"+X\\\"], \\\"destabilizer\\\": [\\\"-Z\\\"]},\\n {\\\"stabilizer\\\": [\\\"-Y\\\"], \\\"destabilizer\\\": [\\\"+X\\\"]},\\n {\\\"stabilizer\\\": [\\\"+X\\\"], \\\"destabilizer\\\": [\\\"-Y\\\"]},\\n {\\\"stabilizer\\\": [\\\"-Z\\\"], \\\"destabilizer\\\": [\\\"-Y\\\"]},\\n {\\\"stabilizer\\\": [\\\"-Y\\\"], \\\"destabilizer\\\": [\\\"-Z\\\"]},\\n {\\\"stabilizer\\\": [\\\"-Z\\\"], \\\"destabilizer\\\": [\\\"-X\\\"]},\\n {\\\"stabilizer\\\": [\\\"-X\\\"], \\\"destabilizer\\\": [\\\"-Z\\\"]},\\n {\\\"stabilizer\\\": [\\\"+Y\\\"], \\\"destabilizer\\\": [\\\"-X\\\"]},\\n {\\\"stabilizer\\\": [\\\"-X\\\"], \\\"destabilizer\\\": [\\\"+Y\\\"]},\\n {\\\"stabilizer\\\": [\\\"-Z\\\"], \\\"destabilizer\\\": [\\\"+Y\\\"]},\\n {\\\"stabilizer\\\": [\\\"+Y\\\"], \\\"destabilizer\\\": [\\\"-Z\\\"]},\\n {\\\"stabilizer\\\": [\\\"+Z\\\"], \\\"destabilizer\\\": [\\\"-X\\\"]},\\n {\\\"stabilizer\\\": [\\\"-X\\\"], \\\"destabilizer\\\": [\\\"+Z\\\"]},\\n {\\\"stabilizer\\\": [\\\"-Y\\\"], \\\"destabilizer\\\": [\\\"-X\\\"]},\\n {\\\"stabilizer\\\": [\\\"-X\\\"], \\\"destabilizer\\\": [\\\"-Y\\\"]},\\n {\\\"stabilizer\\\": [\\\"+Z\\\"], \\\"destabilizer\\\": [\\\"-Y\\\"]},\\n {\\\"stabilizer\\\": [\\\"-Y\\\"], \\\"destabilizer\\\": [\\\"+Z\\\"]},\\n ]\\n cliffords = [Clifford.from_dict(i) for i in clifford_dicts]\\n for n in range(24):\\n clifford = CliffordUtils.clifford_1_qubit(n)\\n self.assertEqual(clifford, cliffords[n])\",\n \"def __invert(self, args):\",\n \"def complement(self) -> JustLatticeChord:\\n nodes = []\\n for node in self._nodes:\\n nodes.append(list(map(lambda x, y: y - x, node, self._root)))\\n return JustLatticeChord(self._fundamental, self._root, nodes)\",\n \"def reverseComplement(self):\\n quality = None if self.quality is None else self.quality[::-1]\\n sequence = self.sequence.translate(self.COMPLEMENT_TABLE)[::-1]\\n return self.__class__(self.id, sequence, quality)\",\n \"def test_exact_two_qubit_cnot_decompose_paulis(self):\\n unitary = Operator.from_label(\\\"XZ\\\")\\n self.check_exact_decomposition(unitary.data, two_qubit_cnot_decompose)\",\n \"def complement(chromosome, point1, point2):\\r\\n new_chromosome = \\\"\\\"\\r\\n\\r\\n for i in range(len(chromosome)):\\r\\n if i >= point1 and i <= point2:\\r\\n if chromosome[i] == '0':\\r\\n new_chromosome += '1'\\r\\n else:\\r\\n new_chromosome += '0'\\r\\n else:\\r\\n new_chromosome += chromosome[i]\\r\\n\\r\\n return new_chromosome\",\n \"def get_reverse_complement(dna):\\r\\n\\r\\n seq = Seq(dna)\\r\\n rev_seq = seq.reverse_complement()\\r\\n return str(rev_seq)\",\n \"def __sub__(self, tc):\\n tc = TwosComplement(tc)._negative()\\n return self.__add__(tc)\",\n \"def test_minus(self):\\n self.assertEqual(1, foo.minus(3, 2))\",\n \"def __invert__(self):\\n return self.reverse()\",\n \"def get_reverse_complement(dna):\\n reverseDNA = ''\\n newDNA = ''\\n for i in range(len(dna)): \\n reverseDNA+= dna[-1-i]\\n for k in range(len(dna)): \\n if reverseDNA[k] == 'A': \\n newDNA+='T'\\n elif reverseDNA[k] =='T':\\n newDNA+= 'A' \\n elif reverseDNA[k] =='G':\\n newDNA+= 'C'\\n elif reverseDNA[k] =='C':\\n newDNA+= 'G' \\n return newDNA\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.78032184","0.7330259","0.7222587","0.7113062","0.69564736","0.69260347","0.6924214","0.68408453","0.6719885","0.6579124","0.65708894","0.65301526","0.6491171","0.64767414","0.6465325","0.6416435","0.6400825","0.63780624","0.6311535","0.6303076","0.62991154","0.62814194","0.6220854","0.6164569","0.6055362","0.60394186","0.6037278","0.6035784","0.603549","0.60035855","0.59918606","0.59871507","0.5980582","0.5944376","0.59342676","0.5911853","0.5886217","0.58767784","0.5872185","0.58640546","0.5804278","0.58018595","0.58003795","0.5798164","0.5786989","0.5772872","0.57545257","0.5752087","0.5742023","0.5737022","0.571929","0.5719028","0.5709605","0.570376","0.57031476","0.5699631","0.56941736","0.5673028","0.565974","0.56596065","0.5647786","0.5636268","0.5598488","0.55864954","0.55766547","0.5555853","0.5542303","0.55320567","0.5508517","0.5501033","0.5498765","0.5497895","0.5493925","0.5476764","0.5471396","0.5456554","0.5451394","0.54498494","0.5447335","0.5444056","0.544368","0.5440298","0.5433536","0.54183835","0.5408195","0.5405383","0.54038566","0.5400213","0.53869593","0.53620625","0.53568953","0.53563255","0.5350754","0.5350609","0.5347181","0.534644","0.5338647","0.53378415","0.533373","0.53311145"],"string":"[\n \"0.78032184\",\n \"0.7330259\",\n \"0.7222587\",\n \"0.7113062\",\n \"0.69564736\",\n \"0.69260347\",\n \"0.6924214\",\n \"0.68408453\",\n \"0.6719885\",\n \"0.6579124\",\n \"0.65708894\",\n \"0.65301526\",\n \"0.6491171\",\n \"0.64767414\",\n \"0.6465325\",\n \"0.6416435\",\n \"0.6400825\",\n \"0.63780624\",\n \"0.6311535\",\n \"0.6303076\",\n \"0.62991154\",\n \"0.62814194\",\n \"0.6220854\",\n \"0.6164569\",\n \"0.6055362\",\n \"0.60394186\",\n \"0.6037278\",\n \"0.6035784\",\n \"0.603549\",\n \"0.60035855\",\n \"0.59918606\",\n \"0.59871507\",\n \"0.5980582\",\n \"0.5944376\",\n \"0.59342676\",\n \"0.5911853\",\n \"0.5886217\",\n \"0.58767784\",\n \"0.5872185\",\n \"0.58640546\",\n \"0.5804278\",\n \"0.58018595\",\n \"0.58003795\",\n \"0.5798164\",\n \"0.5786989\",\n \"0.5772872\",\n \"0.57545257\",\n \"0.5752087\",\n \"0.5742023\",\n \"0.5737022\",\n \"0.571929\",\n \"0.5719028\",\n \"0.5709605\",\n \"0.570376\",\n \"0.57031476\",\n \"0.5699631\",\n \"0.56941736\",\n \"0.5673028\",\n \"0.565974\",\n \"0.56596065\",\n \"0.5647786\",\n \"0.5636268\",\n \"0.5598488\",\n \"0.55864954\",\n \"0.55766547\",\n \"0.5555853\",\n \"0.5542303\",\n \"0.55320567\",\n \"0.5508517\",\n \"0.5501033\",\n \"0.5498765\",\n \"0.5497895\",\n \"0.5493925\",\n \"0.5476764\",\n \"0.5471396\",\n \"0.5456554\",\n \"0.5451394\",\n \"0.54498494\",\n \"0.5447335\",\n \"0.5444056\",\n \"0.544368\",\n \"0.5440298\",\n \"0.5433536\",\n \"0.54183835\",\n \"0.5408195\",\n \"0.5405383\",\n \"0.54038566\",\n \"0.5400213\",\n \"0.53869593\",\n \"0.53620625\",\n \"0.53568953\",\n \"0.53563255\",\n \"0.5350754\",\n \"0.5350609\",\n \"0.5347181\",\n \"0.534644\",\n \"0.5338647\",\n \"0.53378415\",\n \"0.533373\",\n \"0.53311145\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.68050754"},"document_rank":{"kind":"string","value":"8"}}},{"rowIdx":92994,"cells":{"query":{"kind":"string","value":"Takes a DNA sequence that is assumed to begin with a start codon and returns the sequence up to but not including the first in frame stop codon. If there is no in frame stop codon, returns the whole string."},"document":{"kind":"string","value":"def rest_of_ORF(dna):\n # [???] 'assumed to begin with a start codon': doesn't need to check input?\n# if len(dna) < 3:\n# return \"\"\n# if dna[0:3] != start_codon:\n# return \"\"\n\n l = len(dna)\n for i in range(3, l, 3):\n if dna[i: i + 3] in stop_codons:\n return dna[0: i]\n return dna"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def remove_stop_from_end(codonseq, codon_table):\n if str(codonseq[-3:]) in codon_table.stop_codons:\n #print(\"chopped\", len(CodonSeq().from_seq(codonseq[:-3])))\n return CodonSeq().from_seq(codonseq[:-3])\n elif str(codonseq[-3:]) == '---':\n #print(\"chopped\", len(CodonSeq().from_seq(codonseq[:-3])))\n return CodonSeq().from_seq(codonseq[:-3])\n else:\n #print(\"unchopped\", len(codonseq))\n return codonseq","def frame_strand(strand):\n logging.info(\"Framing strand: \" + strand)\n framed_strand = []\n rolling_frame = ['','','']\n frame_begin = -1\n for i in range(0, len(strand)):\n rolling_frame[0] = rolling_frame[1]\n rolling_frame[1] = rolling_frame[2]\n rolling_frame[2] = strand[i]\n if rolling_frame[0]+rolling_frame[1]+rolling_frame[2] == start_codon:\n # We have the frame at this point. Prune the beginning of the string:\n # We are at a pos+2 (c ccc atg ccc ccc c) so cut back 2 and then break\n # ^\n frame_begin = i - 2\n logging.debug(\"Found start codon, strand is now framed at \" + str(frame_begin) + \".\")\n break\n if frame_begin == -1:\n # In this case, there is no valid frame in the strand. Return an empty list.\n logging.info(\"No valid frame in strand.\")\n return [], 0\n pruned_strand = strand[frame_begin:]\n framed_strand = [pruned_strand[i:i+3] for i in range(0, len(pruned_strand), 3)] # Make triples\n logging.debug(\"Framed strand is: \" + str(framed_strand))\n if len(framed_strand[-1]) < 3:\n logging.info(\"Newly framed sequence terminates with non-codon: \" + framed_strand[-1])\n return framed_strand, frame_begin","def rest_of_ORF(dna):\n\t# TODO: implement this\n\tindex = 0\n\twhile index < len(dna):\n\t\tcodon = dna[index:index + 3]\t\t\t\t\t\t\t\t\t\t\t\t\t\t# groups 3 nucleotides to make codon, index by 3\n\t\tif codon in [\"TAA\", \"TAG\", \"TGA\"]:\t\t\t\t\t\t\t\t\t\t\t\t\t# checks if stop codon is in string\n\t\t\treturn dna[:index]\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if True, returns string up to stop codon\n\t\tindex += 3\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# indexes by 3\n\treturn dna","def rest_of_ORF(dna):\n\n #inital conditions\n i = 3\n end_index = len(dna)\n stop_codon = ('TAG','TAA','TGA')\n\n #for the length of the string of DNA, run through each codon and break and return the indec of the string if the codon is a stop codon\n while i < len(dna)-2:\n codon = dna[i:i+3] #takes only every third index which is the length of a codon\n if codon in stop_codon:\n end_index = i \n break\n i += 3\n #returns a list from the start codon to the index where the stop codon begins\n return dna[0:end_index]","def rest_of_ORF(dna):\n readingFrame = ''\n endCodons = [\"TAG\", \"TAA\", \"TGA\"]\n for i in range(0,len(dna),3):\n triple = dna[i:i+3]\n if triple in endCodons:\n readingFrame = readingFrame\n break\n else: \n readingFrame+=triple \n return readingFrame","def rest_of_ORF(dna):\n index = -1\n dna_split = split_into_codons(dna)\n\n for i, j in enumerate(dna_split):\n if j == \"TAG\" or j == \"TGA\" or j == \"TAA\":\n index = i\n if index == -1:\n return ''.join(dna_split) # if there is no stop codon\n return ''.join(dna_split[:index])","def rest_of_ORF(dna): \n\n for i in range(3,len(dna)-2,3):\n \tstop_codon=dna[i:i+3]\n \tstart_codon=dna[:i]\n \tif stop_codon=='TAG' or stop_codon=='TAA' or stop_codon=='TGA':\n \t\treturn start_codon\n \t\tbreak\n \tif (i+3) >= len(dna)-2:\n \treturn dna","def break_up_frame(s):\n start = 0\n for match in re_stops.finditer(s):\n index = match.start() + 3\n if index % 3 != 0:\n continue\n n = s[start:index]\n if options.ftype == \"CDS\":\n offset, n, t = start_chop_and_trans(n)\n else:\n offset = 0\n t = translate(n, options.table, to_stop=True)\n if n and len(t) >= options.min_len:\n yield start + offset, n, t\n start = index\n if options.ends == \"open\":\n # No stop codon, Biopython's strict CDS translate will fail\n n = s[start:]\n # Ensure we have whole codons\n # TODO - Try appending N instead?\n # TODO - Do the next four lines more elegantly\n if len(n) % 3:\n n = n[:-1]\n if len(n) % 3:\n n = n[:-1]\n if options.ftype == \"CDS\":\n offset, n, t = start_chop_and_trans(n, strict=False)\n else:\n offset = 0\n t = translate(n, options.table, to_stop=True)\n if n and len(t) >= options.min_len:\n yield start + offset, n, t","def rest_of_ORF(dna):\n STOP_CODONS=['TAG','TGA','TAA' ]#constants are uppercase\n for i in range(0,len(dna),3):\n codon=dna[i:i+3]\n if codon in STOP_CODONS:\n return dna[0:i]\n return dna","def get_sequence_without_gaps_or_padding(sequence: str) -> str:\n return sequence.replace(dc_constants.GAP_OR_PAD,\n '').replace(dc_constants.GAP_OR_PAD, '')","def first_last_chop(seq):\n return seq[4:-4:2]","def find_all_ORFs_oneframe(dna):\n strand = []\n startCodon = [\"ATG\"]\n for i in range(0,len(dna),3):\n triple = dna[i:i+3]\n if triple in startCodon: \n strand.append(rest_of_ORF(dna[i:]))\n print strand\n return strand","def find_all_ORFs_oneframe(dna):\n #inital conditions\n i = 0\n start_codon = ('ATG')\n end_index = len(dna)\n return_variable = []\n\n #for each codon in the set of DNA, check if it is a start codon\n #if it is a start codon, add the string until the stop codon to a list\n #then continue running\n while i < len(dna)-2:\n codon = dna[i:i+3] \n if codon in start_codon:\n orf = rest_of_ORF(dna[i:])\n return_variable.append(orf)\n i += len(orf)\n i += 3\n\n\n #return a list of strings of DNA\n return return_variable","def start_with_start_codon(rna: str):\n return rna.find(START_CODON)","def start_with_the_beggining(rna: str):\n return 0","def rest_of_ORF(dna):\n string = ''\n for i in xrange(0, len(dna), 3):\n codon = dna[i:i+3]\n if codon == 'TAG' or codon =='TAA' or codon =='TGA':\n return string\n else:\n string += codon\n return string","def rest_of_ORF(dna):\n num_codons = int(len(dna)/3)\n num = 0\n list_codons = []\n cut_dna = ''\n stop_index = -1\n while num < num_codons:\n num_start = int(num*3)\n num_end = int(num*3 + 3)\n list_codons.append(dna[num_start:num_end])\n num = num + 1\n for element in list_codons:\n if element == 'TAA' or element == 'TAG' or element == 'TGA':\n stop_index = list_codons.index(element)\n break\n\n if stop_index != -1:\n this_ORF = list_codons[0:stop_index]\n for element in this_ORF:\n cut_dna = cut_dna + element\n return cut_dna\n else:\n return dna","def extract_sequence(molecule, begin, gap = 8):\n # Validte the length of the molecule\n validate_molecule_length(molecule)\n # Define the sequence variable to store the amino acid sequence\n sequence = ''\n # Get the total numbers of residues\n length = len(molecule)\n # The begin point should be equal or larger than 1 and equal or less than len(molecule) - gap \n if isinstance(begin, int) and begin >= 0 and begin <= (length - gap) : \n for i in range(gap + 1):\n # Get the amino acid kind\n aa = molecule[begin + i].kind\n # Convert the three-letter amino acid name to one-letter character \n # Store it in the sequence\n sequence += convertAA[\"PDB\"][aa] \n if len(sequence) == gap + 1 :\n return sequence\n else:\n text += \"The amino acid number in the sequence is not correct\"\n raise DeimmunizationError(text)","def proteinTranslation(seq, geneticCode = STANDARD_GENETIC_CODE):\n\n seq = seq.replace('T','U') # Make sure we have RNA sequence\n proteinSeq = []\n \n i = 0\n while i+2 < len(seq):\n \n codon = seq[i:i+3]\n aminoAcid = geneticCode[codon]\n \n if aminoAcid is None: # Found stop codon\n break\n\n proteinSeq.append(aminoAcid)\n i += 3\n\n return proteinSeq","def squeeze_seq(seq):\r\n\r\n return sub(r'([AGCTacgt])\\1+', '\\\\1', seq)","def find_all_ORFs_oneframe(dna):\n res = []\n l = len(dna)\n next_pos = 0\n while True:\n arg = dna[next_pos:]\n# orf = rest_of_ORF(arg)\n# res.append(orf)\n# if arg == orf: # if: no stop codon\n# break\n# next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\n# if next_pos >= l: # if: meet the end of dna\n# break\n if arg[0:3] == start_codon:\n orf = rest_of_ORF(arg)\n res.append(orf)\n if arg == orf: # if: no stop codon\n break\n next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\n else: # if: not start codon, see next\n next_pos += 3\n if next_pos >= l: # if: meet or go beyond the end of dna\n break\n return res","def translate(dna):\n rna = dna.replace('T', 'U')\n startIndex = dna.find('AUG') + 1\n aminoAcidsSeq = \"\"\n for i in range(startIndex, len(rna), 3):\n # codon = rna[i: i+3]\n aminoAcidsSeq += code[rna[i: i+3]]\n if aminoAcidsSeq[len(aminoAcidsSeq) - 1] == '*':\n aminoAcidsSeq = aminoAcidsSeq[:-1]\n break\n return aminoAcidsSeq","def translate_sequence(rna_sequence, genetic_code):\n #Crate an empty list to store AA sequence:\n AA_list = []\n # Convert all rna_sequence to upper case:\n rna_sequence=rna_sequence.upper()\n # Convert all rna_sequence into a list:\n rna_list = list(rna_sequence)\n # This conditon will run if rna_sequence is at least 3 bases long, and only once it find start codon ,\n #and stop once it finds stop codon.\n while True:\n if len(rna_list) > 2:\n codon=''.join(rna_list[0:3])\n #Delete first 3 bases since its alread added as codon, thus no longer needed.\n del rna_list[0:3]\n else:\n break\n #Using genetic code dictionary to find AA for each corresponding codon:\n AA=genetic_code[codon]\n #Break loop once it finds stop codon\n if AA=='*':\n break\n #Add add translatable AA to the AA_list:\n AA_list.append(AA)\n return ''.join(AA_list)","def rest_of_ORF(dna,aa,i):\n\n rest_of_ORF = []\n \n while len(aa) ==3 and aa not in stop_codons: #run this loop until locating a stop\n # if len(aa) == 3:\n rest_of_ORF.append (aa) #add each successive codon to list\n i = i+1\n aa = dna[3*i:(3*i)+3]\n # else:\n # rest_of_ORF.append (aa)\n # return ''.join(rest_of_ORF)\n\n return ''.join(rest_of_ORF)","def reading_frames(dna):\n #the 6 types are as follows\n # the actual string and the reverse complement\n list = []\n #this is the actual string\n list.append(dna)\n #this is the reverse complement of the string\n # done reusing the fastcomplement() method that was already available.\n #others are done likewise\n list.append(fast_complement(dna[::-1]))\n list.append(dna[1:len(dna)])\n list.append(fast_complement(dna[1:len(dna)][::-1]))\n list.append(dna[2:len(dna)])\n list.append(fast_complement(dna[2:len(dna)][::-1]))\n return list","def fragSeq(seq, ion):\n iontype = ion[0]\n ionnr = int(ion[1:])\n frag = seq[0:ionnr] if iontype == 'b' else seq[len(seq) - ionnr:]\n assert len(frag) == ionnr\n return frag","def first_four_last_four(seq):\n seq = seq[4:-4:2]\n return seq","def prune_decoded_seqs(seqs):\r\n out = []\r\n for s in seqs:\r\n if EOS in s:\r\n idx = s.index(EOS)\r\n out += [s[:idx]]\r\n else:\r\n out += [s]\r\n return out","def get_stop_codon_context(self):\n\n utr3_seq = self.three_prime_utr_sequence.upper()\n CDS_seq = self.coding_sequence.upper()\n\n seq = CDS_seq[len(CDS_seq)-9:] + utr3_seq[:6]\n\n return seq","def backtranslate(p_seq, n_seq):\r\n # Keep track of the new sequence. Also keep track of which codon we are\r\n # actually processing (gaps don't count)\r\n newseq = ''\r\n codon = 0\r\n for aa in p_seq:\r\n if aa == '-':\r\n newseq += '---'\r\n else:\r\n newseq += n_seq[codon*3:(codon*3) + 3]\r\n codon += 1\r\n return newseq","def fours_removed(seq):\n length = len(seq) - 4\n new_seq = seq[4:length:2]\n return new_seq","def without_end(s):\n string = s[1:-1]\n return string","def rna_to_protein(rna: str, to_str=True, start: Union[int, Callable[[str], int]]=start_with_the_beggining,\n end=False):\n pos = start(rna) if callable(start) else start\n if pos < 0:\n return None if not to_str else \"\"\n else:\n rna = rna[pos:]\n result = [\"\"] * (len(rna) // 3)\n for i in range(len(result)):\n elem = rna_codon_table[rna[3 * i: 3 * i + 3]]\n if elem != STOP_CODON:\n result[i] = elem\n else:\n result = result[:i]\n break\n else:\n # if no break occurs, then stop codon wasn't found, so if end argument is True empty sequence should be returned\n if end:\n result = []\n if to_str:\n result = \"\".join(result)\n return result","def find_first_orf(sequence,\n start_codons = ['AUG'],\n stop_codons = ['UAA', 'UAG', 'UGA']):\n \n # Make sure the sequence is valid\n vet_nucleotide_sequence(sequence)\n\n # Make sure the codons are valid\n for codon in start_codons:\n vet_codon(codon)\n for codon in stop_codons:\n vet_codon(codon)\n\n # Get copies of everything in uppercase\n seq = sequence.upper()\n starts = [c.upper() for c in start_codons]\n stops = [c.upper() for c in stop_codons]\n # Make sure seq is RNA\n seq = seq.replace('T', 'U')\n\n\n ##########################################################################\n # `orf_pattern_str` is a regular expression that will match an\n # open reading frame within a string of RNA bases. \n # Read the docstring above for additional clues.\n #I create variables as \"strings\" to take in start_codons & stop_codons \"lists\" so it can use them in the \"regex\"\n \n strt = '|'.join(start_codons) #takes the start codon provided and saves it as a string named 'strt'\n stp = '|'.join(stop_codons) #takes the stop codon provided and takes it as a string named 'stp'\n\n #here the `regex`\n orf_pattern_str = r'(' + strt +r')([AUCG]{3})*('+ stp +r')'\n #breakdown\n #the regex is in 3 groups\n #first group is the start codon\n # literarily it is 'AUG', but it is dynamic, and (' + strt +r') fixes that\n #the second group is ([AUGC]{3})* which captures zero or more sets of codon after the start codon\n #the last group is ((UAA)|(UAG)|(UGA)) dynamically captured as ('+ stp +r')\n ##########################################################################\n\n # Create the regular expression object\n orf_pattern = re.compile(orf_pattern_str)\n # Search the sequence\n match_object = orf_pattern.search(seq)\n if match_object:\n return match_object.group()\n return ''","def prune_decoded_seqs(seqs):\n out = []\n for s in seqs:\n if constant.EOS in s:\n idx = s.index(constant.EOS_TOKEN)\n out += [s[:idx]]\n else:\n out += [s]\n return out","def start_chop_and_trans(s, strict=True):\n if strict:\n assert s[-3:] in stops, s\n assert len(s) % 3 == 0\n for match in re_starts.finditer(s):\n # Must check the start is in frame\n start = match.start()\n if start % 3 == 0:\n n = s[start:]\n assert len(n) % 3 == 0, \"%s is len %i\" % (n, len(n))\n if strict:\n t = translate(n, options.table, cds=True)\n else:\n # Use when missing stop codon,\n t = \"M\" + translate(n[3:], options.table, to_stop=True)\n return start, n, t\n return None, None, None","def extractseq(geneID, db=dbpaths['cds'], startpos=0, endpos=-1):\n #fname = dbpaths[type]\n geneseq = \"\"\n fobj = open(db, 'rb')\n for line in fobj:\n if line[0] == '>':\n query = re.search( geneID + '[\\s]', line)\n if query:\n thisline = fobj.next()\n\n while thisline[0] != '>':\n geneseq += thisline.strip()\n try:\n thisline = fobj.next()\n except StopIteration:\n break\n else:\n break\n fobj.close()\n return geneseq[startpos:endpos]","def find_all_ORFs_oneframe(dna):\n\tindex = 0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# unitiate index at 0\n\tsegment = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitializes empty list\n\twhile index < len(dna):\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# given that index is smaller than length of string\n\t\tcodon = dna[index:index + 3]\t\t\t\t\t\t\t\t\t\t\t\t\t\t# creates codons from nucleotides starting with first 3 letters\n\t\tif codon == \"ATG\":\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if the codon is ATG\n\t\t\tsegment.append(rest_of_ORF(dna[index:]))\t\t\t\t\t\t\t\t\t\t# run rest_of_ORF starting at index\n\t\t\tindex = index + len(rest_of_ORF(dna[index:]))\t\t\t\t\t\t\t\t\t# new index starting at old + length of ORF output string\n\t\telse:\n\t\t\tindex += 3\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if ATG isn't found, move to next codon and check again\n\n\treturn segment\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns list of ORFs","def get_complementary_sequence(sequence):\n\n complementary_sequence = ''\n for char in sequence:\n complementary_sequence = complementary_sequence + get_complement(char)\n return complementary_sequence","def codons(self, frame):\n start = frame\n while start + 3 <= self.size:\n yield self.sequence[start : start + 3], start\n start += 3","def get_strand_complement(sequence):\n seq = sequence.upper()\n change = str.maketrans('ACGT', 'TGCA')\n return seq.translate(change)","def extract_sequence_molecule(molecule):\n sequence = \"\"\n for residue in molecule:\n sequence += convertAA[\"PDB\"][residue.kind]\n return sequence","def _get_seq_string(sequence) -> str:\n final_str = \"\"\n for seq in [sequence[i:i+60] for i in range(0, len(sequence), 60)]:\n final_str += \" \" + \" \".join(seq[i:i+10] for i in range(0, len(seq), 10)) + \"\\n\"\n\n return final_str","def _substitute_opening_gap_char(seq):\n newseq=list(seq)\n iterator=rex.finditer(seq)\n for match in iterator:\n try:\n newseq[match.span()[1]-1]=\"|\"\n except:\n continue\n return \"\".join(newseq)","def translate(self,frame=1):\n if self.seq_type.upper() != \"DNA\":\n return \"Not a DNA sequence (wrong seq_type)\"\n\n aa_output=\"\"\n dna_input=self.seq\n if frame == 0 or frame not in range(-3,4):\n return \"Please specify a correct reading frame number. (+/- 1,2,3)\"\n\n elif frame in range(-3,0):\n dna_input=reverse_complement(dna_input)\n\n for pos in range (abs(frame)-1,len(dna_input)-2,3):\n codon=dna_input[pos:pos+3]\n aa_output += translation_codon(codon)\n\n return myseq(aa_output,\"Protein\")","def scan_sequence(self, frame, direction):\n orf_start = None\n for c, index in self.codons(frame):\n if (\n c not in self.stop\n and (c in self.start or not self.start)\n and orf_start is None\n ):\n orf_start = index\n elif c in self.stop and orf_start is not None:\n self._update_longest(orf_start, index + 3, direction, frame)\n orf_start = None\n\n if orf_start is not None:\n self._update_longest(orf_start, index + 3, direction, frame)","def translate_framed_strand(framed_strand):\n\n polypeptide = []\n # Iterate through all the codons in our strand and look up their resultant amino acid\n logging.info(\"Translating strand: \" + str(framed_strand))\n for codon in framed_strand:\n if len(codon) != 3:\n break\n if codon in stop_codons:\n # We are at the end of the sequence, so cut.\n logging.debug(\"Stopping at codon \" + codon)\n break\n logging.debug(\"Adding polypeptide \" + codons_to_amino_acids[codon][2])\n polypeptide.append(codons_to_amino_acids[codon])\n return polypeptide","def test_fasta_get_codons_from_seq(self):\r\n\r\n codon_list = mfau.get_codons_from_sequence(\"AGGTGACACCGCAAGCCTTATATTAGC\")\r\n\r\n if debug:\r\n for codon in codon_list:\r\n print codon\r\n\r\n self.assertGreaterEqual(len(codon_list), 0)","def search_trimmers(seq: str) -> str:\n return [seq[i:i+3] for i in range(len(seq)-2)]","def find_all_ORFs_oneframe(dna):\n x = 3\n list_of_dna = []\n while (x < len(dna)):\n if dna[x-3:x] == 'ATG':\n current_dna = rest_of_ORF(dna[x-3:])\n list_of_dna.append(current_dna)\n x += len(current_dna)\n x += 3\n return list_of_dna","def get_reverse_complement(sequence):\n return get_strand_complement(sequence)[::-1]","def get_strand_complement(sequence):\n # make the sequence upper case\n seq = sequence.upper()\n # table to change the complement characters\n change = str.maketrans('ACGT', 'TGCA')\n return seq.translate(change)","def rest_of_ORF(dna):\n \n if dna[:3]== \"TAG\" or dna[:3]==\"TAA\" or dna[:3]==\"TGA\" or len(dna)<3:\n return \"\"\n if len(dna)<=3:\n return dna\n return dna[:3]+rest_of_ORF(dna[3:])","def read_genome(genome_file):\r\n with open(genome_file, 'r') as fid:\r\n seq = [line.strip() for line in fid.readlines()]\r\n sequence = ''.join(seq[1:])\r\n return sequence","def bipa(sequence):\n return [_token2clts(segment)[0] for segment in sequence]","def getSequencefromPDB(pdbfile, chain='C', index=0):\n parser = PDB.PDBParser(QUIET=True)\n struct = parser.get_structure(pdbfile,pdbfile)\n ppb = PDB.PPBuilder()\n model = struct[0]\n peptides = ppb.build_peptides(model[chain])\n seq=''\n for i,pep in enumerate(peptides):\n seq+=str(pep.get_sequence())\n return seq","def get_seq(self, table=1, cds=True):\n dna_seq = '' \n for exon in self.transcript.exons: \n dna_seq += self.transcript.rna.gene.polymer.get_subseq(\n start=max(self.coding_region.start, exon.start), \n end=min(self.coding_region.end, exon.end))\n \n if self.transcript.rna.gene.strand == core.PolymerStrand.negative:\n dna_seq = dna_seq.reverse_complement()\n \n return dna_seq.transcribe().translate(table=table, cds=cds)","def prepseq(self, seq):\n\n wtf = re.sub(r'\\*$', '', seq)\n return wtf","def rest_of_ORF(dna):\n end_dna = len(dna)\n for group in range(0, end_dna, 3):\n strand = dna[group:group+3]\n if strand in ['TGA', 'TAA', 'TAG']:\n return dna[0:group]\n return dna","def codonify(strand: str) -> list:\n\n # Loops through the whole string and slices every set of three characters into\n # the list codons\n codons = [strand[index : index + len_codon] for index in range(0,len(strand),len_codon)]\n return codons","def decode_sequence(self, sequence=list) -> str:\n try:\n out = []\n for word in sequence:\n out.append(self.decode(word))\n return(out)\n except Exception as error:\n print(f\"Error: self.decode_sequence({sequence}) -> {error}\")","def get_seq(self):\n dna_seq = ''\n\n for exon in self.exons: \n dna_seq += self.rna.gene.polymer.get_subseq(\n start=exon.start, end=exon.end)\n\n if self.rna.gene.strand==core.PolymerStrand.negative:\n dna_seq = dna_seq.reverse_complement() \n \n return dna_seq.transcribe()","def get_reverse_complement(sequence):\n seq = sequence.upper()\n return get_strand_complement(seq)[::-1]","def DNA_strand(string):\n return string.translate(DNA)","def find_all_ORFs_oneframe(dna):\n i=0 \n ORF_list = []\n while i<len(dna):\n if dna[i : i+3] == \"ATG\":\n start_place = i \n current_ORF = rest_of_ORF(dna[start_place:])\n i += 3 + len(current_ORF)\n ORF_list.append(current_ORF) \n return ORF_list","def getGenomeSequence(genomeId):\n \n r = urllib.urlopen(PatricURL+genomeId+'/'+genomeId+'.fna').read()\n soup = BeautifulSoup(r)\n #print type(soup)\n\n genomeSequence = soup.prettify().split('| '+genomeId+']')[1]\n return genomeSequence.replace('\\n', '')","def find_all_ORFs_oneframe(dna):\n\n ORFlist = []\n i = 0\n lend = len(dna)\n while i < lend:\n codon = dna[i:i+3]\n if codon == 'ATG':\n orf = rest_of_ORF(dna[i:])\n ORFlist.append(orf)\n i = i + len(orf)\n else:\n i = i+3\n return ORFlist","def rest_of_ORF(dna):\n for h in range(0, len(dna), 3):\n curr_triplet = dna[h : h + 3] \n #for n in range(0, len(amino_acids.codons),1):\n if curr_triplet in amino_acids.codons[10]:\n return dna[0 : h] \n return dna","def _mb_substr(string, start, length):\n return string.decode(_ENCODING)[start: start + length]","def remove_4s_every_other_in_between(seq):\n seq_copy = seq [4:-4:2]\n return seq_copy","def test_beginstring_combos():\n vc = vtec.parse(\"/O.NEW.KJAN.TO.W.0130.000000T0000Z-000000T0000Z/\")\n assert vc[0].get_begin_string(None) == \"\"","def get_region_seq(record,start,stop):\n segment = record[start:stop]\n segment_seq = segment.seq\n return segment_seq # pure sequence string","def remove_stop_sodon_signals(record_seq: str) -> str:\n return record_seq.replace(\"*\", \"\")","def get_barcode(curr_seq, barcode_len):\r\n raw_barcode = curr_seq[0:barcode_len]\r\n raw_seq = curr_seq[barcode_len:]\r\n return raw_barcode, raw_seq","def getStartPos(peptide, seq, subst=None):\n return getStartPosMapper(seq, subst)(peptide)","def find_all_ORFs_oneframe(dna):\n dna_split = split_into_codons(dna)\n i = 0\n all_ORFs_oneframe = []\n length_of_orf = 0\n while i < len(dna_split):\n if dna_split[i] == \"ATG\":\n orf = rest_of_ORF(dna[int(i)*3:])\n all_ORFs_oneframe += [orf]\n length_of_orf = math.ceil(len(orf)/3)\n i += length_of_orf\n else:\n i += 1\n return all_ORFs_oneframe","def get_reverse_complement(dna):\r\n\r\n seq = Seq(dna)\r\n rev_seq = seq.reverse_complement()\r\n return str(rev_seq)","def find_all_ORFs(dna):\n res = []\n for i in range(0, 3):\n s = dna[i:]\n# print i, s,\n# l = len(s)\n# for j in range(0, l, 3):\n# if s[j: j + 3] == start_codon:\n# r = find_all_ORFs_oneframe(s[j:])\n# print r\n# if len(r) > 0:\n# for item in r:\n# res.append(item)\n# break # careful for indentation here!!\n r = find_all_ORFs_oneframe(s)\n if len(r) > 0:\n# for item in r:\n# res.append(item)\n res += r # [WOW] I love python!\n return res","def get_seq_middle(seq_length):\n half_offset = int((seq_length - 1) / 2)\n return seq_length - 1 - half_offset","def find_all_ORFs_oneframe(dna):\n \n\n ORFs=[]\n i=0\n while i<len(dna):\n if dna[i:i+3]==\"ATG\":\n j=i\n dna2=rest_of_ORF(dna[j:])\n \n if dna2==None:\n \tbreak\n ORFs.append(dna2)\n i=i+len(dna2)\n i=i+3\n return ORFs","def sequence_del(my_str):\r\n new = ''\r\n l = len(my_str)\r\n for i in range(l -1):\r\n # for j in range(1,len(my_str)):\r\n if my_str[i] == my_str[i+1]:\r\n continue\r\n new += my_str[i]\r\n new += my_str[i]\r\n print(new)","def find_aligned_codons(aln):\n # throw out codons with non mod 3 gaps\n ind2 = []\n for i in range(0, aln.alignlen(), 3):\n bad = False\n\n for key, val in aln.iteritems():\n codon = val[i:i+3]\n if \"-\" in codon and codon != \"---\":\n bad = True\n break\n\n if not bad:\n ind2.extend([i, i+1, i+2])\n\n return ind2","def mark_codon_pos(seq, pos=0):\n\n codons = []\n\n for base in seq:\n if base != \"-\":\n codons.append(pos)\n pos = (pos + 1) % 3\n else:\n codons.append(-1)\n\n return codons","def get_seq_from_pdbchain(chain):\n type_chain = check_type(chain)\n if type_chain == \"protein\":\n three_res_list = []\n for res in chain:\n residues_atoms = res.get_atoms()\n for atom in residues_atoms:\n if atom.get_name() == 'CA':\n residue = atom.get_parent()\n three_res_list.append(residue.get_resname())\n return three_to_one(three_res_list) # three_to_one function\n else:\n nucleic_acid_res = []\n for res in chain:\n residues_atoms = res.get_atoms()\n for atom in residues_atoms:\n if atom.get_name() == 'P':\n residue = atom.get_parent()\n nucleic_acid_res.append(residue.get_resname())\n nucleic_acid_seq = [x[2] for x in nucleic_acid_res]\n return \"\".join(nucleic_acid_seq)","def guess_seq(seq):\n dna = \"ACTG-N\"\n \n chars = util.unique(seq.upper())\n \n for char in chars:\n if char not in dna:\n return \"pep\"\n return \"dna\"","def prefix(sequence, l):\n if l > len(sequence):\n return sequence\n else:\n return sequence[:l]","def translate(self) -> Seq:\n AA = \"\".join(\n self.codons[self.sequence[i : i + 3]]\n for i in range(0, len(self.sequence), 3)\n if self.codons[self.sequence[i : i + 3]] != \"Stop\"\n )\n return Seq(AA, self.id)","def _get_start(self, variant, reference_start, cigar, ignore_softclip=False):\n indels = get_indel_from_cigar(cigar, ignore_softclip)\n start = variant.POS - reference_start - 1\n # for pos, val in indels.iteritems(): # python2\n for pos, val in indels.items():\n if pos > start:\n break\n if val[0] == 'I':\n start += val[1]\n elif val[0] == 'D':\n start -= val[1]\n return start","def get_reference_seq_ucsc(chrom, start, end):\n if chrom.startswith('chr'):\n chrom = chrom.replace('chr', '')\n request = 'http://genome.ucsc.edu/cgi-bin/das/hg19/dna?segment=chr{}:{},{}'.format(chrom, start, end)\n try:\n dna = xmltodict.parse(urlopen(request).read())['DASDNA']['SEQUENCE']['DNA']['#text'].replace('\\n', '')\n except (URLError, ExpatError) as e:\n print('Could not open UCSC url. Please check your internet connection.\\n{}\\n{}'.format(request, e.message))\n dna = \"n\" * (start - end)\n return dna","def get_sequence( f ):\r\n sequence = ''\r\n line = f.readline().rstrip()\r\n while line:\r\n sequence += line\r\n line = f.readline().rstrip()\r\n return sequence","def return_peptide (RNA):\n\t# Should work with already made sequence without stop codons. Only one peptide per call\n\n\tdna.isNucleotide(RNA)\n\tif 'T' in RNA: raise dna.InvalidSequenceError\t\n\tpeptide = \"\"\n\tid = 0\n\twhile id < len(RNA):\n\t\ttRNA = RNA[id:id+3]\n\t\tif not tRNA in RNA_code: break\n\t\tAA = RNA_code[tRNA]\n\t\tif AA == False: # In the case if was mistake in the previous step\n\t\t\tbreak\n\t\tpeptide += AA\n\t\tid += 3\t\n\treturn peptide","def get_sequence(self):\n\n search_params = [\n '|',\n ('active', '=', True),\n ('year', '=', self.year),\n ('cod_gestion.name', '!=', 'Z8_01_dl15')\n ]\n codis_gestio = self.connection.model('cir8.2021.d2').search(search_params)\n\n return codis_gestio","def sequence_del(my_str):\n next = \"\"\n new_str = \"\"\n for index, letter in enumerate(my_str):\n if index + 1 < len(my_str):\n next = my_str[index + 1]\n else:\n new_str += letter\n if not (letter == next):\n new_str += letter\n return new_str","def determine_begin_end(molecule, index):\n # Validte the length of the molecule\n validate_molecule_length(molecule)\n # Validate_the index1, index2, index3, \n # Define the constant gap for accessing the 9mers sequence from a certain residue\n gap = 8\n # Get the total numbers of residues\n length = len(molecule)\n # Set the begin point \n begin = index - gap\n # Set the end point\n end = index + gap\n if begin < 0:\n begin = 0 \n if end > length:\n end = length\n \n return begin, end","def get_sequence(address):\n ref = ''\n with open(address,'rU') as ref_file:\n next(ref_file) # skip header lines\n for line in ref_file:\n ref = ref + line.strip()\n return ref","def find_all_ORFs_oneframe(dna):\n condition = 1\n dna2 = dna\n list_of_ORFs = []\n while condition == 1:\n num_codons = int(len(dna2)/3)\n num = 0\n list_codons = []\n start_index = -1\n while num < num_codons:\n num_start = int(num*3)\n num_end = int(num*3 + 3)\n list_codons.append(dna2[num_start:num_end])\n num = num + 1\n for element in list_codons:\n if element == 'ATG':\n start_index = list_codons.index(element)\n break\n if start_index != -1:\n this_orf = rest_of_ORF(dna2[start_index*3:])\n list_of_ORFs.append(this_orf)\n dna2 = dna2[start_index*3+len(this_orf)+3:]\n else:\n condition = 2\n\n return list_of_ORFs","def cropdna(dna, start=0, end=None, supfeature=False, product=None, process_description=None, process_name=None, \n pd=None, pn=None, quinable=True, **kwargs):\n \n kwargs.setdefault(\"_sourcefile\", None) \n kwargs.setdefault(\"process_id\", None)\n kwargs.setdefault(\"original_ids\", []) \n _sourcefile = kwargs[\"_sourcefile\"] \n process_id = kwargs[\"process_id\"] \n original_ids = kwargs[\"original_ids\"]\n\n project = None\n project = project if product is None else product\n process_name = pn if process_name is None else process_name\n process_description = pd if process_description is None else process_description\n\n if end is None or end == 0:\n end = len(dna.seq) \n \n if start == 0 and end == len(dna.seq):\n subdna = cutdna(dna, start, product=project, quinable=0)[0] \n crop_positions = ((0, 0), (len(dna.seq), len(dna.seq)))\n else:\n subdna, crop_positions = cutdna(dna, start, end, product=project, crop=True, quinable=0) \n \n if quinable == 1 and quinable == True: \n args = []\n new_positions = [] \n history_features = [subdna._history_feature] \n for new_pos, pos in zip(crop_positions, (start, end)):\n new_pos = \"/\".join(list(map(str,new_pos)))\n new_pos = \"'\" + new_pos + \"'\"\n if \"__dict__\" in dir(pos) and \"_dnafeature\" in pos.__dict__:\n qkey = pos._qkey\n for qindex, qfeat in enumerate(dna.__class__.queried_features_dict[qkey]):\n if qfeat._second_id == pos._second_id:\n break\n args.append(\"QUEEN.queried_features_dict['{}'][{}]\".format(qkey, qindex))\n history_features.append(pos.subject._history_feature) \n \n elif \"__dict__\" in dir(pos) and \"_qint\" in pos.__dict__:\n qkey = pos.qkey\n for qindex, qfeat in enumerate(dna.__class__.queried_features_dict[qkey]):\n if qfeat._second_id == pos.parental_id:\n break\n args.append(\"QUEEN.queried_features_dict['{}'][{}].{}\".format(pos.qkey, qindex, pos.name))\n history_features.append(pos.parent.subject._history_feature) \n \n else:\n args.append(new_pos)\n\n pos1, pos2 = new_pos.split(\"/\") \n if pos1[1:] == pos2[:-1]:\n new_positions.append(pos1[1:]) \n else:\n new_positions.append(new_pos) \n \n if type(supfeature) in (tuple, list) and type(supfeature[0]) == dict:\n for feature_dict in supfeature: \n subdna.setfeature(feature_dict) \n elif type(supfeature) == dict:\n subdna.setfeature(supfeature)\n\n project = \"\" \n fsupfeature = \"\" if supfeature == False else \", supfeature={}\".format(str(supfeature)) \n fproduct = \"\" if product is None else \", product='\" + product + \"'\"\n process_name = \"\" if process_name is None else \", process_name='\" + process_name + \"'\"\n process_description = \"\" if process_description is None else \", process_description='\" + process_description + \"'\" \n \n subdna._product_id = subdna._unique_id if product is None else product \n building_history = \"QUEEN.dna_dict['{}'] = cropdna(QUEEN.dna_dict['{}'], start={}, end={}{}{}{}{}{})\".format(subdna._product_id, dna._product_id, args[0], args[1], fsupfeature, project, fproduct, process_name, process_description)\n \n history_feature = _combine_history(subdna, history_features)\n subdna._history_feature = history_feature\n process_id, original_ids = make_processid(subdna, building_history, process_id, original_ids)\n add_history(subdna, [building_history, \"start: {}; end: {}\".format(*new_positions), \",\".join([process_id] + original_ids)], _sourcefile) \n subdna._check_uniqueness()\n else:\n subdna.__dict__[\"_product_id\"] = dna._product_id if \"_product_id\" in dna.__dict__ else dna._unique_id\n\n if product is None:\n pass \n else:\n product.replace(\" \",\"\") \n match = re.fullmatch(\"(.+)\\[(.+)\\]\", product)\n if match:\n if match.group(2).isdecimal() == True:\n subdna.__class__._namespace[match.group(1)][int(match.group(2))] = subdna\n else:\n subdna.__class__._namespace[match.group(1)][match.group(2)] = subdna\n else: \n subdna.__class__._namespace[product] = subdna\n return subdna","def filter_aligned_codons(aln):\n\n ind = find_aligned_codons(aln)\n return subalign(aln, ind)","def dummy_junction13():\n return 'junction:chr1:176-299:+'","def _chop_end_codes(line):\n return re.sub(r\"\\s\\s\\s\\s+[\\w]{4}.\\s+\\d*\\Z\", \"\", line)"],"string":"[\n \"def remove_stop_from_end(codonseq, codon_table):\\n if str(codonseq[-3:]) in codon_table.stop_codons:\\n #print(\\\"chopped\\\", len(CodonSeq().from_seq(codonseq[:-3])))\\n return CodonSeq().from_seq(codonseq[:-3])\\n elif str(codonseq[-3:]) == '---':\\n #print(\\\"chopped\\\", len(CodonSeq().from_seq(codonseq[:-3])))\\n return CodonSeq().from_seq(codonseq[:-3])\\n else:\\n #print(\\\"unchopped\\\", len(codonseq))\\n return codonseq\",\n \"def frame_strand(strand):\\n logging.info(\\\"Framing strand: \\\" + strand)\\n framed_strand = []\\n rolling_frame = ['','','']\\n frame_begin = -1\\n for i in range(0, len(strand)):\\n rolling_frame[0] = rolling_frame[1]\\n rolling_frame[1] = rolling_frame[2]\\n rolling_frame[2] = strand[i]\\n if rolling_frame[0]+rolling_frame[1]+rolling_frame[2] == start_codon:\\n # We have the frame at this point. Prune the beginning of the string:\\n # We are at a pos+2 (c ccc atg ccc ccc c) so cut back 2 and then break\\n # ^\\n frame_begin = i - 2\\n logging.debug(\\\"Found start codon, strand is now framed at \\\" + str(frame_begin) + \\\".\\\")\\n break\\n if frame_begin == -1:\\n # In this case, there is no valid frame in the strand. Return an empty list.\\n logging.info(\\\"No valid frame in strand.\\\")\\n return [], 0\\n pruned_strand = strand[frame_begin:]\\n framed_strand = [pruned_strand[i:i+3] for i in range(0, len(pruned_strand), 3)] # Make triples\\n logging.debug(\\\"Framed strand is: \\\" + str(framed_strand))\\n if len(framed_strand[-1]) < 3:\\n logging.info(\\\"Newly framed sequence terminates with non-codon: \\\" + framed_strand[-1])\\n return framed_strand, frame_begin\",\n \"def rest_of_ORF(dna):\\n\\t# TODO: implement this\\n\\tindex = 0\\n\\twhile index < len(dna):\\n\\t\\tcodon = dna[index:index + 3]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# groups 3 nucleotides to make codon, index by 3\\n\\t\\tif codon in [\\\"TAA\\\", \\\"TAG\\\", \\\"TGA\\\"]:\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# checks if stop codon is in string\\n\\t\\t\\treturn dna[:index]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if True, returns string up to stop codon\\n\\t\\tindex += 3\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# indexes by 3\\n\\treturn dna\",\n \"def rest_of_ORF(dna):\\n\\n #inital conditions\\n i = 3\\n end_index = len(dna)\\n stop_codon = ('TAG','TAA','TGA')\\n\\n #for the length of the string of DNA, run through each codon and break and return the indec of the string if the codon is a stop codon\\n while i < len(dna)-2:\\n codon = dna[i:i+3] #takes only every third index which is the length of a codon\\n if codon in stop_codon:\\n end_index = i \\n break\\n i += 3\\n #returns a list from the start codon to the index where the stop codon begins\\n return dna[0:end_index]\",\n \"def rest_of_ORF(dna):\\n readingFrame = ''\\n endCodons = [\\\"TAG\\\", \\\"TAA\\\", \\\"TGA\\\"]\\n for i in range(0,len(dna),3):\\n triple = dna[i:i+3]\\n if triple in endCodons:\\n readingFrame = readingFrame\\n break\\n else: \\n readingFrame+=triple \\n return readingFrame\",\n \"def rest_of_ORF(dna):\\n index = -1\\n dna_split = split_into_codons(dna)\\n\\n for i, j in enumerate(dna_split):\\n if j == \\\"TAG\\\" or j == \\\"TGA\\\" or j == \\\"TAA\\\":\\n index = i\\n if index == -1:\\n return ''.join(dna_split) # if there is no stop codon\\n return ''.join(dna_split[:index])\",\n \"def rest_of_ORF(dna): \\n\\n for i in range(3,len(dna)-2,3):\\n \\tstop_codon=dna[i:i+3]\\n \\tstart_codon=dna[:i]\\n \\tif stop_codon=='TAG' or stop_codon=='TAA' or stop_codon=='TGA':\\n \\t\\treturn start_codon\\n \\t\\tbreak\\n \\tif (i+3) >= len(dna)-2:\\n \\treturn dna\",\n \"def break_up_frame(s):\\n start = 0\\n for match in re_stops.finditer(s):\\n index = match.start() + 3\\n if index % 3 != 0:\\n continue\\n n = s[start:index]\\n if options.ftype == \\\"CDS\\\":\\n offset, n, t = start_chop_and_trans(n)\\n else:\\n offset = 0\\n t = translate(n, options.table, to_stop=True)\\n if n and len(t) >= options.min_len:\\n yield start + offset, n, t\\n start = index\\n if options.ends == \\\"open\\\":\\n # No stop codon, Biopython's strict CDS translate will fail\\n n = s[start:]\\n # Ensure we have whole codons\\n # TODO - Try appending N instead?\\n # TODO - Do the next four lines more elegantly\\n if len(n) % 3:\\n n = n[:-1]\\n if len(n) % 3:\\n n = n[:-1]\\n if options.ftype == \\\"CDS\\\":\\n offset, n, t = start_chop_and_trans(n, strict=False)\\n else:\\n offset = 0\\n t = translate(n, options.table, to_stop=True)\\n if n and len(t) >= options.min_len:\\n yield start + offset, n, t\",\n \"def rest_of_ORF(dna):\\n STOP_CODONS=['TAG','TGA','TAA' ]#constants are uppercase\\n for i in range(0,len(dna),3):\\n codon=dna[i:i+3]\\n if codon in STOP_CODONS:\\n return dna[0:i]\\n return dna\",\n \"def get_sequence_without_gaps_or_padding(sequence: str) -> str:\\n return sequence.replace(dc_constants.GAP_OR_PAD,\\n '').replace(dc_constants.GAP_OR_PAD, '')\",\n \"def first_last_chop(seq):\\n return seq[4:-4:2]\",\n \"def find_all_ORFs_oneframe(dna):\\n strand = []\\n startCodon = [\\\"ATG\\\"]\\n for i in range(0,len(dna),3):\\n triple = dna[i:i+3]\\n if triple in startCodon: \\n strand.append(rest_of_ORF(dna[i:]))\\n print strand\\n return strand\",\n \"def find_all_ORFs_oneframe(dna):\\n #inital conditions\\n i = 0\\n start_codon = ('ATG')\\n end_index = len(dna)\\n return_variable = []\\n\\n #for each codon in the set of DNA, check if it is a start codon\\n #if it is a start codon, add the string until the stop codon to a list\\n #then continue running\\n while i < len(dna)-2:\\n codon = dna[i:i+3] \\n if codon in start_codon:\\n orf = rest_of_ORF(dna[i:])\\n return_variable.append(orf)\\n i += len(orf)\\n i += 3\\n\\n\\n #return a list of strings of DNA\\n return return_variable\",\n \"def start_with_start_codon(rna: str):\\n return rna.find(START_CODON)\",\n \"def start_with_the_beggining(rna: str):\\n return 0\",\n \"def rest_of_ORF(dna):\\n string = ''\\n for i in xrange(0, len(dna), 3):\\n codon = dna[i:i+3]\\n if codon == 'TAG' or codon =='TAA' or codon =='TGA':\\n return string\\n else:\\n string += codon\\n return string\",\n \"def rest_of_ORF(dna):\\n num_codons = int(len(dna)/3)\\n num = 0\\n list_codons = []\\n cut_dna = ''\\n stop_index = -1\\n while num < num_codons:\\n num_start = int(num*3)\\n num_end = int(num*3 + 3)\\n list_codons.append(dna[num_start:num_end])\\n num = num + 1\\n for element in list_codons:\\n if element == 'TAA' or element == 'TAG' or element == 'TGA':\\n stop_index = list_codons.index(element)\\n break\\n\\n if stop_index != -1:\\n this_ORF = list_codons[0:stop_index]\\n for element in this_ORF:\\n cut_dna = cut_dna + element\\n return cut_dna\\n else:\\n return dna\",\n \"def extract_sequence(molecule, begin, gap = 8):\\n # Validte the length of the molecule\\n validate_molecule_length(molecule)\\n # Define the sequence variable to store the amino acid sequence\\n sequence = ''\\n # Get the total numbers of residues\\n length = len(molecule)\\n # The begin point should be equal or larger than 1 and equal or less than len(molecule) - gap \\n if isinstance(begin, int) and begin >= 0 and begin <= (length - gap) : \\n for i in range(gap + 1):\\n # Get the amino acid kind\\n aa = molecule[begin + i].kind\\n # Convert the three-letter amino acid name to one-letter character \\n # Store it in the sequence\\n sequence += convertAA[\\\"PDB\\\"][aa] \\n if len(sequence) == gap + 1 :\\n return sequence\\n else:\\n text += \\\"The amino acid number in the sequence is not correct\\\"\\n raise DeimmunizationError(text)\",\n \"def proteinTranslation(seq, geneticCode = STANDARD_GENETIC_CODE):\\n\\n seq = seq.replace('T','U') # Make sure we have RNA sequence\\n proteinSeq = []\\n \\n i = 0\\n while i+2 < len(seq):\\n \\n codon = seq[i:i+3]\\n aminoAcid = geneticCode[codon]\\n \\n if aminoAcid is None: # Found stop codon\\n break\\n\\n proteinSeq.append(aminoAcid)\\n i += 3\\n\\n return proteinSeq\",\n \"def squeeze_seq(seq):\\r\\n\\r\\n return sub(r'([AGCTacgt])\\\\1+', '\\\\\\\\1', seq)\",\n \"def find_all_ORFs_oneframe(dna):\\n res = []\\n l = len(dna)\\n next_pos = 0\\n while True:\\n arg = dna[next_pos:]\\n# orf = rest_of_ORF(arg)\\n# res.append(orf)\\n# if arg == orf: # if: no stop codon\\n# break\\n# next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\\n# if next_pos >= l: # if: meet the end of dna\\n# break\\n if arg[0:3] == start_codon:\\n orf = rest_of_ORF(arg)\\n res.append(orf)\\n if arg == orf: # if: no stop codon\\n break\\n next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\\n else: # if: not start codon, see next\\n next_pos += 3\\n if next_pos >= l: # if: meet or go beyond the end of dna\\n break\\n return res\",\n \"def translate(dna):\\n rna = dna.replace('T', 'U')\\n startIndex = dna.find('AUG') + 1\\n aminoAcidsSeq = \\\"\\\"\\n for i in range(startIndex, len(rna), 3):\\n # codon = rna[i: i+3]\\n aminoAcidsSeq += code[rna[i: i+3]]\\n if aminoAcidsSeq[len(aminoAcidsSeq) - 1] == '*':\\n aminoAcidsSeq = aminoAcidsSeq[:-1]\\n break\\n return aminoAcidsSeq\",\n \"def translate_sequence(rna_sequence, genetic_code):\\n #Crate an empty list to store AA sequence:\\n AA_list = []\\n # Convert all rna_sequence to upper case:\\n rna_sequence=rna_sequence.upper()\\n # Convert all rna_sequence into a list:\\n rna_list = list(rna_sequence)\\n # This conditon will run if rna_sequence is at least 3 bases long, and only once it find start codon ,\\n #and stop once it finds stop codon.\\n while True:\\n if len(rna_list) > 2:\\n codon=''.join(rna_list[0:3])\\n #Delete first 3 bases since its alread added as codon, thus no longer needed.\\n del rna_list[0:3]\\n else:\\n break\\n #Using genetic code dictionary to find AA for each corresponding codon:\\n AA=genetic_code[codon]\\n #Break loop once it finds stop codon\\n if AA=='*':\\n break\\n #Add add translatable AA to the AA_list:\\n AA_list.append(AA)\\n return ''.join(AA_list)\",\n \"def rest_of_ORF(dna,aa,i):\\n\\n rest_of_ORF = []\\n \\n while len(aa) ==3 and aa not in stop_codons: #run this loop until locating a stop\\n # if len(aa) == 3:\\n rest_of_ORF.append (aa) #add each successive codon to list\\n i = i+1\\n aa = dna[3*i:(3*i)+3]\\n # else:\\n # rest_of_ORF.append (aa)\\n # return ''.join(rest_of_ORF)\\n\\n return ''.join(rest_of_ORF)\",\n \"def reading_frames(dna):\\n #the 6 types are as follows\\n # the actual string and the reverse complement\\n list = []\\n #this is the actual string\\n list.append(dna)\\n #this is the reverse complement of the string\\n # done reusing the fastcomplement() method that was already available.\\n #others are done likewise\\n list.append(fast_complement(dna[::-1]))\\n list.append(dna[1:len(dna)])\\n list.append(fast_complement(dna[1:len(dna)][::-1]))\\n list.append(dna[2:len(dna)])\\n list.append(fast_complement(dna[2:len(dna)][::-1]))\\n return list\",\n \"def fragSeq(seq, ion):\\n iontype = ion[0]\\n ionnr = int(ion[1:])\\n frag = seq[0:ionnr] if iontype == 'b' else seq[len(seq) - ionnr:]\\n assert len(frag) == ionnr\\n return frag\",\n \"def first_four_last_four(seq):\\n seq = seq[4:-4:2]\\n return seq\",\n \"def prune_decoded_seqs(seqs):\\r\\n out = []\\r\\n for s in seqs:\\r\\n if EOS in s:\\r\\n idx = s.index(EOS)\\r\\n out += [s[:idx]]\\r\\n else:\\r\\n out += [s]\\r\\n return out\",\n \"def get_stop_codon_context(self):\\n\\n utr3_seq = self.three_prime_utr_sequence.upper()\\n CDS_seq = self.coding_sequence.upper()\\n\\n seq = CDS_seq[len(CDS_seq)-9:] + utr3_seq[:6]\\n\\n return seq\",\n \"def backtranslate(p_seq, n_seq):\\r\\n # Keep track of the new sequence. Also keep track of which codon we are\\r\\n # actually processing (gaps don't count)\\r\\n newseq = ''\\r\\n codon = 0\\r\\n for aa in p_seq:\\r\\n if aa == '-':\\r\\n newseq += '---'\\r\\n else:\\r\\n newseq += n_seq[codon*3:(codon*3) + 3]\\r\\n codon += 1\\r\\n return newseq\",\n \"def fours_removed(seq):\\n length = len(seq) - 4\\n new_seq = seq[4:length:2]\\n return new_seq\",\n \"def without_end(s):\\n string = s[1:-1]\\n return string\",\n \"def rna_to_protein(rna: str, to_str=True, start: Union[int, Callable[[str], int]]=start_with_the_beggining,\\n end=False):\\n pos = start(rna) if callable(start) else start\\n if pos < 0:\\n return None if not to_str else \\\"\\\"\\n else:\\n rna = rna[pos:]\\n result = [\\\"\\\"] * (len(rna) // 3)\\n for i in range(len(result)):\\n elem = rna_codon_table[rna[3 * i: 3 * i + 3]]\\n if elem != STOP_CODON:\\n result[i] = elem\\n else:\\n result = result[:i]\\n break\\n else:\\n # if no break occurs, then stop codon wasn't found, so if end argument is True empty sequence should be returned\\n if end:\\n result = []\\n if to_str:\\n result = \\\"\\\".join(result)\\n return result\",\n \"def find_first_orf(sequence,\\n start_codons = ['AUG'],\\n stop_codons = ['UAA', 'UAG', 'UGA']):\\n \\n # Make sure the sequence is valid\\n vet_nucleotide_sequence(sequence)\\n\\n # Make sure the codons are valid\\n for codon in start_codons:\\n vet_codon(codon)\\n for codon in stop_codons:\\n vet_codon(codon)\\n\\n # Get copies of everything in uppercase\\n seq = sequence.upper()\\n starts = [c.upper() for c in start_codons]\\n stops = [c.upper() for c in stop_codons]\\n # Make sure seq is RNA\\n seq = seq.replace('T', 'U')\\n\\n\\n ##########################################################################\\n # `orf_pattern_str` is a regular expression that will match an\\n # open reading frame within a string of RNA bases. \\n # Read the docstring above for additional clues.\\n #I create variables as \\\"strings\\\" to take in start_codons & stop_codons \\\"lists\\\" so it can use them in the \\\"regex\\\"\\n \\n strt = '|'.join(start_codons) #takes the start codon provided and saves it as a string named 'strt'\\n stp = '|'.join(stop_codons) #takes the stop codon provided and takes it as a string named 'stp'\\n\\n #here the `regex`\\n orf_pattern_str = r'(' + strt +r')([AUCG]{3})*('+ stp +r')'\\n #breakdown\\n #the regex is in 3 groups\\n #first group is the start codon\\n # literarily it is 'AUG', but it is dynamic, and (' + strt +r') fixes that\\n #the second group is ([AUGC]{3})* which captures zero or more sets of codon after the start codon\\n #the last group is ((UAA)|(UAG)|(UGA)) dynamically captured as ('+ stp +r')\\n ##########################################################################\\n\\n # Create the regular expression object\\n orf_pattern = re.compile(orf_pattern_str)\\n # Search the sequence\\n match_object = orf_pattern.search(seq)\\n if match_object:\\n return match_object.group()\\n return ''\",\n \"def prune_decoded_seqs(seqs):\\n out = []\\n for s in seqs:\\n if constant.EOS in s:\\n idx = s.index(constant.EOS_TOKEN)\\n out += [s[:idx]]\\n else:\\n out += [s]\\n return out\",\n \"def start_chop_and_trans(s, strict=True):\\n if strict:\\n assert s[-3:] in stops, s\\n assert len(s) % 3 == 0\\n for match in re_starts.finditer(s):\\n # Must check the start is in frame\\n start = match.start()\\n if start % 3 == 0:\\n n = s[start:]\\n assert len(n) % 3 == 0, \\\"%s is len %i\\\" % (n, len(n))\\n if strict:\\n t = translate(n, options.table, cds=True)\\n else:\\n # Use when missing stop codon,\\n t = \\\"M\\\" + translate(n[3:], options.table, to_stop=True)\\n return start, n, t\\n return None, None, None\",\n \"def extractseq(geneID, db=dbpaths['cds'], startpos=0, endpos=-1):\\n #fname = dbpaths[type]\\n geneseq = \\\"\\\"\\n fobj = open(db, 'rb')\\n for line in fobj:\\n if line[0] == '>':\\n query = re.search( geneID + '[\\\\s]', line)\\n if query:\\n thisline = fobj.next()\\n\\n while thisline[0] != '>':\\n geneseq += thisline.strip()\\n try:\\n thisline = fobj.next()\\n except StopIteration:\\n break\\n else:\\n break\\n fobj.close()\\n return geneseq[startpos:endpos]\",\n \"def find_all_ORFs_oneframe(dna):\\n\\tindex = 0\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# unitiate index at 0\\n\\tsegment = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitializes empty list\\n\\twhile index < len(dna):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# given that index is smaller than length of string\\n\\t\\tcodon = dna[index:index + 3]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# creates codons from nucleotides starting with first 3 letters\\n\\t\\tif codon == \\\"ATG\\\":\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if the codon is ATG\\n\\t\\t\\tsegment.append(rest_of_ORF(dna[index:]))\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# run rest_of_ORF starting at index\\n\\t\\t\\tindex = index + len(rest_of_ORF(dna[index:]))\\t\\t\\t\\t\\t\\t\\t\\t\\t# new index starting at old + length of ORF output string\\n\\t\\telse:\\n\\t\\t\\tindex += 3\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if ATG isn't found, move to next codon and check again\\n\\n\\treturn segment\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns list of ORFs\",\n \"def get_complementary_sequence(sequence):\\n\\n complementary_sequence = ''\\n for char in sequence:\\n complementary_sequence = complementary_sequence + get_complement(char)\\n return complementary_sequence\",\n \"def codons(self, frame):\\n start = frame\\n while start + 3 <= self.size:\\n yield self.sequence[start : start + 3], start\\n start += 3\",\n \"def get_strand_complement(sequence):\\n seq = sequence.upper()\\n change = str.maketrans('ACGT', 'TGCA')\\n return seq.translate(change)\",\n \"def extract_sequence_molecule(molecule):\\n sequence = \\\"\\\"\\n for residue in molecule:\\n sequence += convertAA[\\\"PDB\\\"][residue.kind]\\n return sequence\",\n \"def _get_seq_string(sequence) -> str:\\n final_str = \\\"\\\"\\n for seq in [sequence[i:i+60] for i in range(0, len(sequence), 60)]:\\n final_str += \\\" \\\" + \\\" \\\".join(seq[i:i+10] for i in range(0, len(seq), 10)) + \\\"\\\\n\\\"\\n\\n return final_str\",\n \"def _substitute_opening_gap_char(seq):\\n newseq=list(seq)\\n iterator=rex.finditer(seq)\\n for match in iterator:\\n try:\\n newseq[match.span()[1]-1]=\\\"|\\\"\\n except:\\n continue\\n return \\\"\\\".join(newseq)\",\n \"def translate(self,frame=1):\\n if self.seq_type.upper() != \\\"DNA\\\":\\n return \\\"Not a DNA sequence (wrong seq_type)\\\"\\n\\n aa_output=\\\"\\\"\\n dna_input=self.seq\\n if frame == 0 or frame not in range(-3,4):\\n return \\\"Please specify a correct reading frame number. (+/- 1,2,3)\\\"\\n\\n elif frame in range(-3,0):\\n dna_input=reverse_complement(dna_input)\\n\\n for pos in range (abs(frame)-1,len(dna_input)-2,3):\\n codon=dna_input[pos:pos+3]\\n aa_output += translation_codon(codon)\\n\\n return myseq(aa_output,\\\"Protein\\\")\",\n \"def scan_sequence(self, frame, direction):\\n orf_start = None\\n for c, index in self.codons(frame):\\n if (\\n c not in self.stop\\n and (c in self.start or not self.start)\\n and orf_start is None\\n ):\\n orf_start = index\\n elif c in self.stop and orf_start is not None:\\n self._update_longest(orf_start, index + 3, direction, frame)\\n orf_start = None\\n\\n if orf_start is not None:\\n self._update_longest(orf_start, index + 3, direction, frame)\",\n \"def translate_framed_strand(framed_strand):\\n\\n polypeptide = []\\n # Iterate through all the codons in our strand and look up their resultant amino acid\\n logging.info(\\\"Translating strand: \\\" + str(framed_strand))\\n for codon in framed_strand:\\n if len(codon) != 3:\\n break\\n if codon in stop_codons:\\n # We are at the end of the sequence, so cut.\\n logging.debug(\\\"Stopping at codon \\\" + codon)\\n break\\n logging.debug(\\\"Adding polypeptide \\\" + codons_to_amino_acids[codon][2])\\n polypeptide.append(codons_to_amino_acids[codon])\\n return polypeptide\",\n \"def test_fasta_get_codons_from_seq(self):\\r\\n\\r\\n codon_list = mfau.get_codons_from_sequence(\\\"AGGTGACACCGCAAGCCTTATATTAGC\\\")\\r\\n\\r\\n if debug:\\r\\n for codon in codon_list:\\r\\n print codon\\r\\n\\r\\n self.assertGreaterEqual(len(codon_list), 0)\",\n \"def search_trimmers(seq: str) -> str:\\n return [seq[i:i+3] for i in range(len(seq)-2)]\",\n \"def find_all_ORFs_oneframe(dna):\\n x = 3\\n list_of_dna = []\\n while (x < len(dna)):\\n if dna[x-3:x] == 'ATG':\\n current_dna = rest_of_ORF(dna[x-3:])\\n list_of_dna.append(current_dna)\\n x += len(current_dna)\\n x += 3\\n return list_of_dna\",\n \"def get_reverse_complement(sequence):\\n return get_strand_complement(sequence)[::-1]\",\n \"def get_strand_complement(sequence):\\n # make the sequence upper case\\n seq = sequence.upper()\\n # table to change the complement characters\\n change = str.maketrans('ACGT', 'TGCA')\\n return seq.translate(change)\",\n \"def rest_of_ORF(dna):\\n \\n if dna[:3]== \\\"TAG\\\" or dna[:3]==\\\"TAA\\\" or dna[:3]==\\\"TGA\\\" or len(dna)<3:\\n return \\\"\\\"\\n if len(dna)<=3:\\n return dna\\n return dna[:3]+rest_of_ORF(dna[3:])\",\n \"def read_genome(genome_file):\\r\\n with open(genome_file, 'r') as fid:\\r\\n seq = [line.strip() for line in fid.readlines()]\\r\\n sequence = ''.join(seq[1:])\\r\\n return sequence\",\n \"def bipa(sequence):\\n return [_token2clts(segment)[0] for segment in sequence]\",\n \"def getSequencefromPDB(pdbfile, chain='C', index=0):\\n parser = PDB.PDBParser(QUIET=True)\\n struct = parser.get_structure(pdbfile,pdbfile)\\n ppb = PDB.PPBuilder()\\n model = struct[0]\\n peptides = ppb.build_peptides(model[chain])\\n seq=''\\n for i,pep in enumerate(peptides):\\n seq+=str(pep.get_sequence())\\n return seq\",\n \"def get_seq(self, table=1, cds=True):\\n dna_seq = '' \\n for exon in self.transcript.exons: \\n dna_seq += self.transcript.rna.gene.polymer.get_subseq(\\n start=max(self.coding_region.start, exon.start), \\n end=min(self.coding_region.end, exon.end))\\n \\n if self.transcript.rna.gene.strand == core.PolymerStrand.negative:\\n dna_seq = dna_seq.reverse_complement()\\n \\n return dna_seq.transcribe().translate(table=table, cds=cds)\",\n \"def prepseq(self, seq):\\n\\n wtf = re.sub(r'\\\\*$', '', seq)\\n return wtf\",\n \"def rest_of_ORF(dna):\\n end_dna = len(dna)\\n for group in range(0, end_dna, 3):\\n strand = dna[group:group+3]\\n if strand in ['TGA', 'TAA', 'TAG']:\\n return dna[0:group]\\n return dna\",\n \"def codonify(strand: str) -> list:\\n\\n # Loops through the whole string and slices every set of three characters into\\n # the list codons\\n codons = [strand[index : index + len_codon] for index in range(0,len(strand),len_codon)]\\n return codons\",\n \"def decode_sequence(self, sequence=list) -> str:\\n try:\\n out = []\\n for word in sequence:\\n out.append(self.decode(word))\\n return(out)\\n except Exception as error:\\n print(f\\\"Error: self.decode_sequence({sequence}) -> {error}\\\")\",\n \"def get_seq(self):\\n dna_seq = ''\\n\\n for exon in self.exons: \\n dna_seq += self.rna.gene.polymer.get_subseq(\\n start=exon.start, end=exon.end)\\n\\n if self.rna.gene.strand==core.PolymerStrand.negative:\\n dna_seq = dna_seq.reverse_complement() \\n \\n return dna_seq.transcribe()\",\n \"def get_reverse_complement(sequence):\\n seq = sequence.upper()\\n return get_strand_complement(seq)[::-1]\",\n \"def DNA_strand(string):\\n return string.translate(DNA)\",\n \"def find_all_ORFs_oneframe(dna):\\n i=0 \\n ORF_list = []\\n while i<len(dna):\\n if dna[i : i+3] == \\\"ATG\\\":\\n start_place = i \\n current_ORF = rest_of_ORF(dna[start_place:])\\n i += 3 + len(current_ORF)\\n ORF_list.append(current_ORF) \\n return ORF_list\",\n \"def getGenomeSequence(genomeId):\\n \\n r = urllib.urlopen(PatricURL+genomeId+'/'+genomeId+'.fna').read()\\n soup = BeautifulSoup(r)\\n #print type(soup)\\n\\n genomeSequence = soup.prettify().split('| '+genomeId+']')[1]\\n return genomeSequence.replace('\\\\n', '')\",\n \"def find_all_ORFs_oneframe(dna):\\n\\n ORFlist = []\\n i = 0\\n lend = len(dna)\\n while i < lend:\\n codon = dna[i:i+3]\\n if codon == 'ATG':\\n orf = rest_of_ORF(dna[i:])\\n ORFlist.append(orf)\\n i = i + len(orf)\\n else:\\n i = i+3\\n return ORFlist\",\n \"def rest_of_ORF(dna):\\n for h in range(0, len(dna), 3):\\n curr_triplet = dna[h : h + 3] \\n #for n in range(0, len(amino_acids.codons),1):\\n if curr_triplet in amino_acids.codons[10]:\\n return dna[0 : h] \\n return dna\",\n \"def _mb_substr(string, start, length):\\n return string.decode(_ENCODING)[start: start + length]\",\n \"def remove_4s_every_other_in_between(seq):\\n seq_copy = seq [4:-4:2]\\n return seq_copy\",\n \"def test_beginstring_combos():\\n vc = vtec.parse(\\\"/O.NEW.KJAN.TO.W.0130.000000T0000Z-000000T0000Z/\\\")\\n assert vc[0].get_begin_string(None) == \\\"\\\"\",\n \"def get_region_seq(record,start,stop):\\n segment = record[start:stop]\\n segment_seq = segment.seq\\n return segment_seq # pure sequence string\",\n \"def remove_stop_sodon_signals(record_seq: str) -> str:\\n return record_seq.replace(\\\"*\\\", \\\"\\\")\",\n \"def get_barcode(curr_seq, barcode_len):\\r\\n raw_barcode = curr_seq[0:barcode_len]\\r\\n raw_seq = curr_seq[barcode_len:]\\r\\n return raw_barcode, raw_seq\",\n \"def getStartPos(peptide, seq, subst=None):\\n return getStartPosMapper(seq, subst)(peptide)\",\n \"def find_all_ORFs_oneframe(dna):\\n dna_split = split_into_codons(dna)\\n i = 0\\n all_ORFs_oneframe = []\\n length_of_orf = 0\\n while i < len(dna_split):\\n if dna_split[i] == \\\"ATG\\\":\\n orf = rest_of_ORF(dna[int(i)*3:])\\n all_ORFs_oneframe += [orf]\\n length_of_orf = math.ceil(len(orf)/3)\\n i += length_of_orf\\n else:\\n i += 1\\n return all_ORFs_oneframe\",\n \"def get_reverse_complement(dna):\\r\\n\\r\\n seq = Seq(dna)\\r\\n rev_seq = seq.reverse_complement()\\r\\n return str(rev_seq)\",\n \"def find_all_ORFs(dna):\\n res = []\\n for i in range(0, 3):\\n s = dna[i:]\\n# print i, s,\\n# l = len(s)\\n# for j in range(0, l, 3):\\n# if s[j: j + 3] == start_codon:\\n# r = find_all_ORFs_oneframe(s[j:])\\n# print r\\n# if len(r) > 0:\\n# for item in r:\\n# res.append(item)\\n# break # careful for indentation here!!\\n r = find_all_ORFs_oneframe(s)\\n if len(r) > 0:\\n# for item in r:\\n# res.append(item)\\n res += r # [WOW] I love python!\\n return res\",\n \"def get_seq_middle(seq_length):\\n half_offset = int((seq_length - 1) / 2)\\n return seq_length - 1 - half_offset\",\n \"def find_all_ORFs_oneframe(dna):\\n \\n\\n ORFs=[]\\n i=0\\n while i<len(dna):\\n if dna[i:i+3]==\\\"ATG\\\":\\n j=i\\n dna2=rest_of_ORF(dna[j:])\\n \\n if dna2==None:\\n \\tbreak\\n ORFs.append(dna2)\\n i=i+len(dna2)\\n i=i+3\\n return ORFs\",\n \"def sequence_del(my_str):\\r\\n new = ''\\r\\n l = len(my_str)\\r\\n for i in range(l -1):\\r\\n # for j in range(1,len(my_str)):\\r\\n if my_str[i] == my_str[i+1]:\\r\\n continue\\r\\n new += my_str[i]\\r\\n new += my_str[i]\\r\\n print(new)\",\n \"def find_aligned_codons(aln):\\n # throw out codons with non mod 3 gaps\\n ind2 = []\\n for i in range(0, aln.alignlen(), 3):\\n bad = False\\n\\n for key, val in aln.iteritems():\\n codon = val[i:i+3]\\n if \\\"-\\\" in codon and codon != \\\"---\\\":\\n bad = True\\n break\\n\\n if not bad:\\n ind2.extend([i, i+1, i+2])\\n\\n return ind2\",\n \"def mark_codon_pos(seq, pos=0):\\n\\n codons = []\\n\\n for base in seq:\\n if base != \\\"-\\\":\\n codons.append(pos)\\n pos = (pos + 1) % 3\\n else:\\n codons.append(-1)\\n\\n return codons\",\n \"def get_seq_from_pdbchain(chain):\\n type_chain = check_type(chain)\\n if type_chain == \\\"protein\\\":\\n three_res_list = []\\n for res in chain:\\n residues_atoms = res.get_atoms()\\n for atom in residues_atoms:\\n if atom.get_name() == 'CA':\\n residue = atom.get_parent()\\n three_res_list.append(residue.get_resname())\\n return three_to_one(three_res_list) # three_to_one function\\n else:\\n nucleic_acid_res = []\\n for res in chain:\\n residues_atoms = res.get_atoms()\\n for atom in residues_atoms:\\n if atom.get_name() == 'P':\\n residue = atom.get_parent()\\n nucleic_acid_res.append(residue.get_resname())\\n nucleic_acid_seq = [x[2] for x in nucleic_acid_res]\\n return \\\"\\\".join(nucleic_acid_seq)\",\n \"def guess_seq(seq):\\n dna = \\\"ACTG-N\\\"\\n \\n chars = util.unique(seq.upper())\\n \\n for char in chars:\\n if char not in dna:\\n return \\\"pep\\\"\\n return \\\"dna\\\"\",\n \"def prefix(sequence, l):\\n if l > len(sequence):\\n return sequence\\n else:\\n return sequence[:l]\",\n \"def translate(self) -> Seq:\\n AA = \\\"\\\".join(\\n self.codons[self.sequence[i : i + 3]]\\n for i in range(0, len(self.sequence), 3)\\n if self.codons[self.sequence[i : i + 3]] != \\\"Stop\\\"\\n )\\n return Seq(AA, self.id)\",\n \"def _get_start(self, variant, reference_start, cigar, ignore_softclip=False):\\n indels = get_indel_from_cigar(cigar, ignore_softclip)\\n start = variant.POS - reference_start - 1\\n # for pos, val in indels.iteritems(): # python2\\n for pos, val in indels.items():\\n if pos > start:\\n break\\n if val[0] == 'I':\\n start += val[1]\\n elif val[0] == 'D':\\n start -= val[1]\\n return start\",\n \"def get_reference_seq_ucsc(chrom, start, end):\\n if chrom.startswith('chr'):\\n chrom = chrom.replace('chr', '')\\n request = 'http://genome.ucsc.edu/cgi-bin/das/hg19/dna?segment=chr{}:{},{}'.format(chrom, start, end)\\n try:\\n dna = xmltodict.parse(urlopen(request).read())['DASDNA']['SEQUENCE']['DNA']['#text'].replace('\\\\n', '')\\n except (URLError, ExpatError) as e:\\n print('Could not open UCSC url. Please check your internet connection.\\\\n{}\\\\n{}'.format(request, e.message))\\n dna = \\\"n\\\" * (start - end)\\n return dna\",\n \"def get_sequence( f ):\\r\\n sequence = ''\\r\\n line = f.readline().rstrip()\\r\\n while line:\\r\\n sequence += line\\r\\n line = f.readline().rstrip()\\r\\n return sequence\",\n \"def return_peptide (RNA):\\n\\t# Should work with already made sequence without stop codons. Only one peptide per call\\n\\n\\tdna.isNucleotide(RNA)\\n\\tif 'T' in RNA: raise dna.InvalidSequenceError\\t\\n\\tpeptide = \\\"\\\"\\n\\tid = 0\\n\\twhile id < len(RNA):\\n\\t\\ttRNA = RNA[id:id+3]\\n\\t\\tif not tRNA in RNA_code: break\\n\\t\\tAA = RNA_code[tRNA]\\n\\t\\tif AA == False: # In the case if was mistake in the previous step\\n\\t\\t\\tbreak\\n\\t\\tpeptide += AA\\n\\t\\tid += 3\\t\\n\\treturn peptide\",\n \"def get_sequence(self):\\n\\n search_params = [\\n '|',\\n ('active', '=', True),\\n ('year', '=', self.year),\\n ('cod_gestion.name', '!=', 'Z8_01_dl15')\\n ]\\n codis_gestio = self.connection.model('cir8.2021.d2').search(search_params)\\n\\n return codis_gestio\",\n \"def sequence_del(my_str):\\n next = \\\"\\\"\\n new_str = \\\"\\\"\\n for index, letter in enumerate(my_str):\\n if index + 1 < len(my_str):\\n next = my_str[index + 1]\\n else:\\n new_str += letter\\n if not (letter == next):\\n new_str += letter\\n return new_str\",\n \"def determine_begin_end(molecule, index):\\n # Validte the length of the molecule\\n validate_molecule_length(molecule)\\n # Validate_the index1, index2, index3, \\n # Define the constant gap for accessing the 9mers sequence from a certain residue\\n gap = 8\\n # Get the total numbers of residues\\n length = len(molecule)\\n # Set the begin point \\n begin = index - gap\\n # Set the end point\\n end = index + gap\\n if begin < 0:\\n begin = 0 \\n if end > length:\\n end = length\\n \\n return begin, end\",\n \"def get_sequence(address):\\n ref = ''\\n with open(address,'rU') as ref_file:\\n next(ref_file) # skip header lines\\n for line in ref_file:\\n ref = ref + line.strip()\\n return ref\",\n \"def find_all_ORFs_oneframe(dna):\\n condition = 1\\n dna2 = dna\\n list_of_ORFs = []\\n while condition == 1:\\n num_codons = int(len(dna2)/3)\\n num = 0\\n list_codons = []\\n start_index = -1\\n while num < num_codons:\\n num_start = int(num*3)\\n num_end = int(num*3 + 3)\\n list_codons.append(dna2[num_start:num_end])\\n num = num + 1\\n for element in list_codons:\\n if element == 'ATG':\\n start_index = list_codons.index(element)\\n break\\n if start_index != -1:\\n this_orf = rest_of_ORF(dna2[start_index*3:])\\n list_of_ORFs.append(this_orf)\\n dna2 = dna2[start_index*3+len(this_orf)+3:]\\n else:\\n condition = 2\\n\\n return list_of_ORFs\",\n \"def cropdna(dna, start=0, end=None, supfeature=False, product=None, process_description=None, process_name=None, \\n pd=None, pn=None, quinable=True, **kwargs):\\n \\n kwargs.setdefault(\\\"_sourcefile\\\", None) \\n kwargs.setdefault(\\\"process_id\\\", None)\\n kwargs.setdefault(\\\"original_ids\\\", []) \\n _sourcefile = kwargs[\\\"_sourcefile\\\"] \\n process_id = kwargs[\\\"process_id\\\"] \\n original_ids = kwargs[\\\"original_ids\\\"]\\n\\n project = None\\n project = project if product is None else product\\n process_name = pn if process_name is None else process_name\\n process_description = pd if process_description is None else process_description\\n\\n if end is None or end == 0:\\n end = len(dna.seq) \\n \\n if start == 0 and end == len(dna.seq):\\n subdna = cutdna(dna, start, product=project, quinable=0)[0] \\n crop_positions = ((0, 0), (len(dna.seq), len(dna.seq)))\\n else:\\n subdna, crop_positions = cutdna(dna, start, end, product=project, crop=True, quinable=0) \\n \\n if quinable == 1 and quinable == True: \\n args = []\\n new_positions = [] \\n history_features = [subdna._history_feature] \\n for new_pos, pos in zip(crop_positions, (start, end)):\\n new_pos = \\\"/\\\".join(list(map(str,new_pos)))\\n new_pos = \\\"'\\\" + new_pos + \\\"'\\\"\\n if \\\"__dict__\\\" in dir(pos) and \\\"_dnafeature\\\" in pos.__dict__:\\n qkey = pos._qkey\\n for qindex, qfeat in enumerate(dna.__class__.queried_features_dict[qkey]):\\n if qfeat._second_id == pos._second_id:\\n break\\n args.append(\\\"QUEEN.queried_features_dict['{}'][{}]\\\".format(qkey, qindex))\\n history_features.append(pos.subject._history_feature) \\n \\n elif \\\"__dict__\\\" in dir(pos) and \\\"_qint\\\" in pos.__dict__:\\n qkey = pos.qkey\\n for qindex, qfeat in enumerate(dna.__class__.queried_features_dict[qkey]):\\n if qfeat._second_id == pos.parental_id:\\n break\\n args.append(\\\"QUEEN.queried_features_dict['{}'][{}].{}\\\".format(pos.qkey, qindex, pos.name))\\n history_features.append(pos.parent.subject._history_feature) \\n \\n else:\\n args.append(new_pos)\\n\\n pos1, pos2 = new_pos.split(\\\"/\\\") \\n if pos1[1:] == pos2[:-1]:\\n new_positions.append(pos1[1:]) \\n else:\\n new_positions.append(new_pos) \\n \\n if type(supfeature) in (tuple, list) and type(supfeature[0]) == dict:\\n for feature_dict in supfeature: \\n subdna.setfeature(feature_dict) \\n elif type(supfeature) == dict:\\n subdna.setfeature(supfeature)\\n\\n project = \\\"\\\" \\n fsupfeature = \\\"\\\" if supfeature == False else \\\", supfeature={}\\\".format(str(supfeature)) \\n fproduct = \\\"\\\" if product is None else \\\", product='\\\" + product + \\\"'\\\"\\n process_name = \\\"\\\" if process_name is None else \\\", process_name='\\\" + process_name + \\\"'\\\"\\n process_description = \\\"\\\" if process_description is None else \\\", process_description='\\\" + process_description + \\\"'\\\" \\n \\n subdna._product_id = subdna._unique_id if product is None else product \\n building_history = \\\"QUEEN.dna_dict['{}'] = cropdna(QUEEN.dna_dict['{}'], start={}, end={}{}{}{}{}{})\\\".format(subdna._product_id, dna._product_id, args[0], args[1], fsupfeature, project, fproduct, process_name, process_description)\\n \\n history_feature = _combine_history(subdna, history_features)\\n subdna._history_feature = history_feature\\n process_id, original_ids = make_processid(subdna, building_history, process_id, original_ids)\\n add_history(subdna, [building_history, \\\"start: {}; end: {}\\\".format(*new_positions), \\\",\\\".join([process_id] + original_ids)], _sourcefile) \\n subdna._check_uniqueness()\\n else:\\n subdna.__dict__[\\\"_product_id\\\"] = dna._product_id if \\\"_product_id\\\" in dna.__dict__ else dna._unique_id\\n\\n if product is None:\\n pass \\n else:\\n product.replace(\\\" \\\",\\\"\\\") \\n match = re.fullmatch(\\\"(.+)\\\\[(.+)\\\\]\\\", product)\\n if match:\\n if match.group(2).isdecimal() == True:\\n subdna.__class__._namespace[match.group(1)][int(match.group(2))] = subdna\\n else:\\n subdna.__class__._namespace[match.group(1)][match.group(2)] = subdna\\n else: \\n subdna.__class__._namespace[product] = subdna\\n return subdna\",\n \"def filter_aligned_codons(aln):\\n\\n ind = find_aligned_codons(aln)\\n return subalign(aln, ind)\",\n \"def dummy_junction13():\\n return 'junction:chr1:176-299:+'\",\n \"def _chop_end_codes(line):\\n return re.sub(r\\\"\\\\s\\\\s\\\\s\\\\s+[\\\\w]{4}.\\\\s+\\\\d*\\\\Z\\\", \\\"\\\", line)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.71757495","0.65072894","0.64979345","0.6329644","0.6183206","0.61209697","0.61035204","0.6082251","0.6023832","0.6007573","0.59589094","0.59459716","0.591217","0.5907929","0.57332164","0.57254994","0.5674605","0.563355","0.5596707","0.55794567","0.5574876","0.55737454","0.55634975","0.55518925","0.55341196","0.5533429","0.5509318","0.54816306","0.5473008","0.54083174","0.5358622","0.53507864","0.53504205","0.5339388","0.5331481","0.53292924","0.5313851","0.5291427","0.52874726","0.52481747","0.52409345","0.5216117","0.52095675","0.5207213","0.51966083","0.517709","0.51693517","0.5151185","0.51380664","0.5136433","0.5102514","0.50998783","0.5090947","0.50856274","0.5084883","0.50821775","0.5081975","0.50593275","0.5053772","0.5052329","0.5042602","0.5042466","0.5039833","0.50197107","0.50082433","0.5002132","0.5001117","0.49917087","0.49790952","0.4976891","0.4969578","0.4966658","0.49543986","0.49499846","0.4949084","0.49436635","0.49277207","0.49238008","0.4914853","0.4894961","0.48911035","0.48850557","0.4884362","0.48836228","0.48741543","0.48624355","0.48540226","0.4843319","0.48319927","0.48250803","0.48228964","0.48188004","0.48117918","0.48099524","0.4808721","0.48042288","0.4803637","0.48026025","0.47912943","0.4791073"],"string":"[\n \"0.71757495\",\n \"0.65072894\",\n \"0.64979345\",\n \"0.6329644\",\n \"0.6183206\",\n \"0.61209697\",\n \"0.61035204\",\n \"0.6082251\",\n \"0.6023832\",\n \"0.6007573\",\n \"0.59589094\",\n \"0.59459716\",\n \"0.591217\",\n \"0.5907929\",\n \"0.57332164\",\n \"0.57254994\",\n \"0.5674605\",\n \"0.563355\",\n \"0.5596707\",\n \"0.55794567\",\n \"0.5574876\",\n \"0.55737454\",\n \"0.55634975\",\n \"0.55518925\",\n \"0.55341196\",\n \"0.5533429\",\n \"0.5509318\",\n \"0.54816306\",\n \"0.5473008\",\n \"0.54083174\",\n \"0.5358622\",\n \"0.53507864\",\n \"0.53504205\",\n \"0.5339388\",\n \"0.5331481\",\n \"0.53292924\",\n \"0.5313851\",\n \"0.5291427\",\n \"0.52874726\",\n \"0.52481747\",\n \"0.52409345\",\n \"0.5216117\",\n \"0.52095675\",\n \"0.5207213\",\n \"0.51966083\",\n \"0.517709\",\n \"0.51693517\",\n \"0.5151185\",\n \"0.51380664\",\n \"0.5136433\",\n \"0.5102514\",\n \"0.50998783\",\n \"0.5090947\",\n \"0.50856274\",\n \"0.5084883\",\n \"0.50821775\",\n \"0.5081975\",\n \"0.50593275\",\n \"0.5053772\",\n \"0.5052329\",\n \"0.5042602\",\n \"0.5042466\",\n \"0.5039833\",\n \"0.50197107\",\n \"0.50082433\",\n \"0.5002132\",\n \"0.5001117\",\n \"0.49917087\",\n \"0.49790952\",\n \"0.4976891\",\n \"0.4969578\",\n \"0.4966658\",\n \"0.49543986\",\n \"0.49499846\",\n \"0.4949084\",\n \"0.49436635\",\n \"0.49277207\",\n \"0.49238008\",\n \"0.4914853\",\n \"0.4894961\",\n \"0.48911035\",\n \"0.48850557\",\n \"0.4884362\",\n \"0.48836228\",\n \"0.48741543\",\n \"0.48624355\",\n \"0.48540226\",\n \"0.4843319\",\n \"0.48319927\",\n \"0.48250803\",\n \"0.48228964\",\n \"0.48188004\",\n \"0.48117918\",\n \"0.48099524\",\n \"0.4808721\",\n \"0.48042288\",\n \"0.4803637\",\n \"0.48026025\",\n \"0.47912943\",\n \"0.4791073\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.67012167"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":92995,"cells":{"query":{"kind":"string","value":"Unit tests for the rest_of_ORF function"},"document":{"kind":"string","value":"def rest_of_ORF_unit_tests():\n data_list = [\n [\"ATGTGAA\", \"ATG\"],\n [\"ATGAGATAGG\", \"ATGAGA\"],\n [\"ATG\", \"ATG\"],\n [\"ATGTAG\", \"ATG\"],\n [\"ATGTAA\", \"ATG\"],\n [\"ATGTGA\", \"ATG\"],\n [\"ATGAAATTTGGGAAATTTGGGTAG\", \"ATGAAATTTGGGAAATTTGGG\"],\n [\"ATGAAATTTGGG\", \"ATGAAATTTGGG\"],\n [\"ATGAGAAGGAAATTTGATGGGGATGGAAGATT\", \"ATGAGAAGGAAATTTGATGGGGATGGAAGATT\"],\n [\"ATGAGAAGGAAATTTGATGGGGATGGAAGATAA\", \"ATGAGAAGGAAATTTGATGGGGATGGAAGA\"],\n [\"ATGAA\", \"ATGAA\"],\n [\"ATGATGATG\", \"ATGATGATG\"],\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\" ,\n print \"expected output: \" + str(data[1]) + \",\",\n o = rest_of_ORF(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\""},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def rest_of_ORF_unit_tests():\n input_a='ATTCATTAG'\n expected_output='ATTCAT'\n actual_output=rest_of_ORF(input_a)\n print 'Expected Output is ' + expected_output\n print 'Actual Output is ' +actual_output\n \n input_a='ATTCATCATCATCATTAG'\n expected_output='ATTCATCATCATCAT'\n actual_output=rest_of_ORF(input_a)\n print 'Expected Output is ' + expected_output\n print 'Actual Output is ' +actual_output","def rest_of_ORF_unit_tests():\n print \"input: CTA, \"+\"output: \"+rest_of_ORF(\"CTA\")+\", actual output: CTA\"\n print \"input: GTCACTTAGGGTTTT, \"+\"output: \"+rest_of_ORF(\"GTCACTTAGGGTTTT\")+\", actual output: GTCACT\"\n print \"input: AAATTTTATAATGGGTGAAGTTAG, \"+\"output: \"+rest_of_ORF(\"AAATTTTATAATGGGTGAAGTTAG\")+\", actual output: AAATTTTATAATGGG\"\n print \"input: TATATGGAGGATAATAGTTGATAATAG, \"+\"output: \"+rest_of_ORF(\"TATATGGAGGATAATAGTTGATAATAG\")+\", actual output: TATATGGAGGATAATAGT\"","def rest_of_ORF_unit_tests():\n input = [\"dna\"]\n expected_output = [\"rest of ORFs\"]\n actual = []\n for k in input:\n actual.append(rest_of_ORF(k))\n print input \n print actual\n print expected_output","def test_apply_endorsements(self):","def find_all_ORFs_unit_tests():\n print 'Begin Unit test Find_all_ORFs'\n input_a='ATGCATGAATGTAGATGTAG'\n expected_output='[ATGCATGAATGTAGATGTAG, ATGAATGTAGATGTAG, ATG, ATG]'\n actual_output=find_all_ORFs(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output\n \n input_a='ATGCATGAATGTAGATGCATCATTAG'\n expected_output='[ATGCATGAATGTAGATGCATCATTAG, ATGAATGTAGATGCATCATTAG, ATG, ATGCATCAT]'\n actual_output=find_all_ORFs(input_a)\n print 'Expected Output is ' + expected_output\n print \"actucal OUtput is\", actual_output\n print 'ENd Unit test Find_all_ORFs'","def rest_of_ORF_unit_tests(dna, expected):\n print rest_of_ORF(\"ATGCCGTAG\") \n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + rest_of_ORF(dna)","def find_all_ORFs_both_strands_unit_tests():\n\n # YOUR IMPLEMENTATION HERE","def find_all_ORFs_unit_tests():\n data_list = [\n [\"ATGCATGAATGTAG\", [\"ATGCATGAATGTAG\", \"ATGAATGTAG\", \"ATG\"]],\n [\"ATG\", [\"ATG\"]],\n [\"AATG\", [\"ATG\"]],\n [\"AAATG\", [\"ATG\"]],\n [\"ATGATG\", [\"ATGATG\"]],\n [\"ATATGGATTGA\", [\"ATGGAT\"]],\n [\"ATGAGATTAG\", [\"ATGAGATTAG\"]],\n [\"ATATGGATTAGTAGTAATGAAAGTATAG\", [\"ATGAAAGTA\", \"ATGGAT\", ]],\n# ATA TGG ATT AGT AGT AAT GAA AGT ATA G\n# TAT GGA TTA GTA GTA ATG AAA GTA TAG\n# ATG GAT TAG TAG TAA TGA AAG TAT AG\n [\"ATGTCACGCAATGTAGGATGGATGGATTAGAC\", [\"ATGTCACGCAATGTAGGATGGATGGAT\", \"ATG\", \"ATGGATGGATTAGAC\"]],\n# ATG TCA CGC AAT GTA GGA TGG ATG GAT TAG AC --> ATG TCA CGC AAT GTA GGA TGG ATG GAT\n# TGT CAC GCA ATG TAG GAT GGA TGG ATT AGA C\n# GTC ACG CAA TGT AGG ATG GAT GGA TTA GAC\n [\"ATGATGTAG\", [\"ATGATG\"]],\n [\"TCGATGC\", [\"ATGC\"]],\n [\"AAA\", []],\n# TCG ATG C\n# CGA TGC\n# GAT GC\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def find_all_ORFs_oneframe_unit_tests():\n\n # YOUR IMPLEMENTATION HERE","def find_all_ORFs_unit_tests():\n \n print \"input: ATGCTA, \"+\"output: \"+ \",\".join(find_all_ORFs(\"ATGCTA\"))+\", actual output: CTA\"\n print \"input: GTCACTTATGGGTTT, \"+\"output: \"+\",\".join(find_all_ORFs(\"ATGGATGCTTAGGGATGTTT\"))+\", actual output: GTCACT,GGTTTT,TCACTTAGGGTTTT,CACTTAGGGTTTT\"\n print \"input: AAATTTTATAATGGGTGAAGTTAG, \"+\"output: \"+\",\".join(find_all_ORFs(\"AAATTTTATAATGGGTGAAGTTAG\"))+\", actual output: ATGGGTGAAGTT\"\n print \"input: TATATGGAGGATAATAGTTGATAATAG, \"+\"output: \"+ \",\".join(find_all_ORFs(\"TATATGGAGGATAATAGTTGATAATAG\"))+\", actual output: ATGGAGGATAATAGT\"","def longest_ORF_unit_tests():\n\n # YOUR IMPLEMENTATION HERE","def longest_ORF_unit_tests():\n\n # YOUR IMPLEMENTATION HERE","def find_all_ORFs_both_strands_unit_tests():\n print ''\n print 'Begin Unit test Find_all_ORFs both tests'\n input_a='ATGCGAGGGTAGATGGATTAG'\n expected_output='[ATGCGAGGG, ATGGAT]'\n actual_output=find_all_ORFs_both_strands(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output\n \n \n input_a='ATGCGAATGTAGCATCAAATAGATGTAG'\n expected_output='[ATGCGAATG, ATG, ATGCTACATTCGCAT]'\n actual_output=find_all_ORFs_both_strands(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output \n print 'end'\n print ''","def unitary_test():","def test_empty_functions():","def _test(self):","def _test(self):","def _test(self):","def _test(self):","def _test(self):","def test_organizations_read(self):\n pass","def test_submit_for_endorsement(self):","def test_basic_execution(self):","def test_get_insumo(self):","def test_uparforvarg(self):","def test_data_in_param(self):","def test_getorgs(self):\n pass","def test_T01():","def test(self):\n pass","def test_all_filter_op_fields(self):\n for field in OCIFilterSerializer._opfields:\n field = \"and:\" + field\n filter_param = {field: [\"1\", \"2\"]}\n serializer = OCIFilterSerializer(data=filter_param)\n self.assertTrue(serializer.is_valid())\n for field in OCIFilterSerializer._opfields:\n field = \"or:\" + field\n filter_param = {field: [\"1\", \"2\"]}\n serializer = OCIFilterSerializer(data=filter_param)\n self.assertTrue(serializer.is_valid())","def test_T2():","def test_T2():","def test_postorgs(self):\n pass","def test_trailing_data(self):","def test_let(self):","def _test(self):\n pass","def _test(self):\n pass","def _test(self):\n pass","def longest_ORF_unit_tests():\n data_list = [\n [\"ATGCGAATGTAGCATCAAA\", \"ATGCTACATTCGCAT\"],\n [\"ATG\", \"ATG\"],\n [\"CAT\", \"ATG\"],\n [\"CATCAT\", \"ATGATG\"],\n [\"CATGGGCAT\", \"ATGCCCATG\"],\n [\"CATGCAGTGCACGGATGGCAT\", \"ATGCCATCCGTGCACTGCATG\"],\n# CATGCAGTGCACGGATGGCAT\n# CAT GCA GTG CAC GGA TGG CAT\n# ATG CAG TGC ACG GAT GGC AT\n# TGC AGT GCA CGG ATG GCA T\n# ATGCCATCCGTGCACTGCATG\n# ATG CCA TCC GTG CAC TGC ATG\n# TGC CAT CCG TGC ACT GCA TG\n# GCC ATC CGT GCA CTG CAT G\n [\"CATATGTAG\", \"ATG\"],\n [\"ATGGGGCATCATTAG\", \"ATGGGGCATCAT\"],\n# ATGGGGCATCATTAG\n# ATG GGG CAT CAT TAG\n# TGG GGC ATC ATT AG\n# GGG GCA TCA TTA G\n# CTAATGATGCCCCAT\n# CTA ATG ATG CCC CAT\n# TAA TGA TGC CCC AT\n# AAT GAT GCC CCA T\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = longest_ORF(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def test_something():","def test_required_methods(self):","def testApi(self):","def find_all_ORFs_oneframe_unit_tests():\n input_a='ATGATTATTTGATGAATGGATTGA'\n expected_output='[ATGATTATT,ATGGAT]'\n actual_output=find_all_ORFs_oneframe(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output\n \n input_a='ATGGGATTGTTT'\n expected_output='[ATGGATTGTTT]'\n actual_output=find_all_ORFs_oneframe(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output","def find_all_ORFs_both_strands_unit_tests():\n data_list = [\n [\"ATGCGAATGTAGCATCAAA\", [\"ATGCGAATG\", \"ATGCTACATTCGCAT\"]],\n [\"ATG\", [\"ATG\"]],\n [\"CAT\", [\"ATG\"]],\n [\"CATCAT\", [\"ATGATG\"]],\n [\"CATGGGCAT\", [\"ATGGGCAT\", \"ATGCCCATG\"]],\n [\"CATGCAGTGCACGGATGGCAT\", [\"ATGCAGTGCACGGATGGCAT\", \"ATGGCAT\", \"ATGCCATCCGTGCACTGCATG\"]],\n# CATGCAGTGCACGGATGGCAT\n# CAT GCA GTG CAC GGA TGG CAT\n# ATG CAG TGC ACG GAT GGC AT\n# TGC AGT GCA CGG ATG GCA T\n# ATGCCATCCGTGCACTGCATG\n# ATG CCA TCC GTG CAC TGC ATG\n# TGC CAT CCG TGC ACT GCA TG\n# GCC ATC CGT GCA CTG CAT G\n [\"CATATGTAG\", [\"ATG\", \"ATG\"]],\n [\"ATGGGGCATCATTAG\", [\"ATGGGGCATCAT\", \"ATGATGCCCCAT\"]],\n# ATGGGGCATCATTAG\n# ATG GGG CAT CAT TAG\n# TGG GGC ATC ATT AG\n# GGG GCA TCA TTA G\n# CTAATGATGCCCCAT\n# CTA ATG ATG CCC CAT\n# TAA TGA TGC CCC AT\n# AAT GAT GCC CCA T\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs_both_strands(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def find_all_ORFs_unit_tests():\n \n input = [\"dna\"]\n expected_output = [\"all non-nested ORFs\"]\n actual = []\n for k in input:\n actual.append(find_all_ORFs(k))\n print input \n print actual\n print expected_output","def test_prepare_bearer_request(self):\n self.assertEqual(prepare_bearer_headers(self.token), self.bearer_headers)\n self.assertEqual(prepare_bearer_body(self.token), self.bearer_body)\n self.assertEqual(prepare_bearer_uri(self.token, uri=self.uri), self.bearer_uri)","def test_process_data(self):\n pass","def test_get_run(self):\n pass","def test_T3():","def test_T3():","def test_if(self):","def test(self) -> Any:\n pass","def find_all_ORFs_oneframe_unit_tests():\n data_list = [\n [\"ATGCATGAATGTAGATAGATGTGCCC\", [\"ATGCATGAATGTAGA\", \"ATGTGCCC\"]],\n [\"ATGTAGATGTAG\", [\"ATG\", \"ATG\"]],\n [\"ATGATGATG\", [\"ATGATGATG\"]],\n [\"ATGGGGGATTAGATGATG\", [\"ATGGGGGAT\", \"ATGATG\"]],\n [\"ATGTGAATGTAA\", [\"ATG\", \"ATG\"]],\n [\"ATGTGAATGTAAATG\", [\"ATG\", \"ATG\", \"ATG\"]],\n [\"ATGCGTGGTGATTAGATGGATGGGGATTGA\", [\"ATGCGTGGTGAT\", \"ATGGATGGGGAT\"]],\n [\"ATGAAATTTCCCGGGAAATTTCCCGGG\", [\"ATGAAATTTCCCGGGAAATTTCCCGGG\"]],\n [\"ATGAAATTTTGAATGGGGCCC\", [\"ATGAAATTT\", \"ATGGGGCCC\"]],\n [\"ATGAAATTTTGAATGGGGCCCTAG\", [\"ATGAAATTT\", \"ATGGGGCCC\"]],\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs_oneframe(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def test_T0():","def test_get2(self):\n pass","def func_case(self):\n test.success(\"\")","def test_T4():","def test_T4():","def test(self):","def test(self):","def test_4_4_1_1(self):\n pass","def test(self):\n raise NotImplementedError","def test_api_response_data(self):","def test_dummy():","def test_untar(self):","def test():","def test():","def longest_ORF_unit_tests():\n\n input_a=\"ATGCGAATGTAGCATCAAA\"\n expected_output=''\n actual_output=longest_ORF(input_a)\n print 'Expected Output is ' + expected_output\n print \"actual output: \", actual_output","def test_nothing(self):","def test_require():","def test_create_from_pear(self):\n pass","def _test_example_fragments_orca():\n main([\"pnictogen/repo/split.ORCA.inp\", \"data/water-dimer.xyz\"])\n assert_equals(\n open(\"data/water-dimer.inp\").read(),\n \"\"\"# data/water-dimer.xyz\n! Opt\n\n* xyz 0 1\nO(1) 0.12908 -0.26336 0.64798\nH(1) 0.89795 0.28805 0.85518\nH(1) 0.10833 -0.20468 -0.33302\nO(2) 0.31020 0.07569 -2.07524\nH(2) -0.26065 0.64232 -2.62218\nH(2) 0.64083 -0.57862 -2.71449\n*\"\"\",\n )","def test_T1():","def test_T1():","def test_retrieve_l_organizations(self):\n pass","def test_function(eso_from_data:callable):\n print('Testing of eso_from_data with hardcoded data')\n # for context, relation, concepts_source in SEQUENCE:\n eso_from_data(0, 'site', 'contains', 'animal')","def test_open_fill(self):","def test_get1(self):\n pass","def test_searchOr(self):\n self.assertTrue(\n self.server.search_OR(\n [\"SENTSINCE\"] + self.earlierQuery +\n [\"SENTSINCE\"] + self.laterQuery,\n self.seq, self.msg, (None, None)))\n self.assertTrue(\n self.server.search_OR(\n [\"SENTSINCE\"] + self.laterQuery +\n [\"SENTSINCE\"] + self.earlierQuery,\n self.seq, self.msg, (None, None)))\n self.assertFalse(\n self.server.search_OR(\n [\"SENTON\"] + self.laterQuery +\n [\"SENTSINCE\"] + self.laterQuery,\n self.seq, self.msg, (None, None)))","def test_begin(self):","def find_all_ORFs_unit_tests(dna, expected):\n \n print find_all_ORFs(\"ATGCATGAATGTAG\")\n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + find_all_ORFs(dna)","def test():\n pass","def test_get_orders(self):\n pass","def test_get_results(self):\n pass","def test_OneOfEverything(self):\n self._run(self._test_scenarios, \"OneOfEverything\")","def test_organizations_list(self):\n pass","def test_orchestrator_http_simple(self):\n pass","def test_alien_data(self):","def test_filter_wea_zero_entry():\n pass","def test_4():","def test_01_lighting(self):","def test_theft_and_stealing(self):","def test_or(self):\n\n xy = t.Or([t.Exactly(\"x\"),\n t.Exactly(\"y\")])\n self.assertEqual(writePython(xy),\n dd(\"\"\"\n def _G_or_1():\n _G_exactly_2, lastError = self.exactly('x')\n self.considerError(lastError, None)\n return (_G_exactly_2, self.currentError)\n def _G_or_3():\n _G_exactly_4, lastError = self.exactly('y')\n self.considerError(lastError, None)\n return (_G_exactly_4, self.currentError)\n _G_or_5, lastError = self._or([_G_or_1, _G_or_3])\n self.considerError(lastError, None)\n _G_or_5\n \"\"\"))","def test_01_Init(self):\n pass","def orfFinder(data):\n\t\n\tORFile = getORFs(data.seqFile, \n\t\t\t\t\t data.queryName, \n\t\t\t\t\t data.o)\n\tsetattr(data, \"ORFs\", ORFile)","def test_read_o_auth_client_authorization(self):\n pass","def test_get_details7(self):\n pass","def test_solareclipses_get(self):\n pass","def test_rpcCall(self):\n pass","def test_init(self):\n assert self.route.route[\"transform\"] == \"transform\"\n assert self.route.route[\"output\"] == \"output\"\n assert \"api\" not in self.route.route"],"string":"[\n \"def rest_of_ORF_unit_tests():\\n input_a='ATTCATTAG'\\n expected_output='ATTCAT'\\n actual_output=rest_of_ORF(input_a)\\n print 'Expected Output is ' + expected_output\\n print 'Actual Output is ' +actual_output\\n \\n input_a='ATTCATCATCATCATTAG'\\n expected_output='ATTCATCATCATCAT'\\n actual_output=rest_of_ORF(input_a)\\n print 'Expected Output is ' + expected_output\\n print 'Actual Output is ' +actual_output\",\n \"def rest_of_ORF_unit_tests():\\n print \\\"input: CTA, \\\"+\\\"output: \\\"+rest_of_ORF(\\\"CTA\\\")+\\\", actual output: CTA\\\"\\n print \\\"input: GTCACTTAGGGTTTT, \\\"+\\\"output: \\\"+rest_of_ORF(\\\"GTCACTTAGGGTTTT\\\")+\\\", actual output: GTCACT\\\"\\n print \\\"input: AAATTTTATAATGGGTGAAGTTAG, \\\"+\\\"output: \\\"+rest_of_ORF(\\\"AAATTTTATAATGGGTGAAGTTAG\\\")+\\\", actual output: AAATTTTATAATGGG\\\"\\n print \\\"input: TATATGGAGGATAATAGTTGATAATAG, \\\"+\\\"output: \\\"+rest_of_ORF(\\\"TATATGGAGGATAATAGTTGATAATAG\\\")+\\\", actual output: TATATGGAGGATAATAGT\\\"\",\n \"def rest_of_ORF_unit_tests():\\n input = [\\\"dna\\\"]\\n expected_output = [\\\"rest of ORFs\\\"]\\n actual = []\\n for k in input:\\n actual.append(rest_of_ORF(k))\\n print input \\n print actual\\n print expected_output\",\n \"def test_apply_endorsements(self):\",\n \"def find_all_ORFs_unit_tests():\\n print 'Begin Unit test Find_all_ORFs'\\n input_a='ATGCATGAATGTAGATGTAG'\\n expected_output='[ATGCATGAATGTAGATGTAG, ATGAATGTAGATGTAG, ATG, ATG]'\\n actual_output=find_all_ORFs(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\\n \\n input_a='ATGCATGAATGTAGATGCATCATTAG'\\n expected_output='[ATGCATGAATGTAGATGCATCATTAG, ATGAATGTAGATGCATCATTAG, ATG, ATGCATCAT]'\\n actual_output=find_all_ORFs(input_a)\\n print 'Expected Output is ' + expected_output\\n print \\\"actucal OUtput is\\\", actual_output\\n print 'ENd Unit test Find_all_ORFs'\",\n \"def rest_of_ORF_unit_tests(dna, expected):\\n print rest_of_ORF(\\\"ATGCCGTAG\\\") \\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + rest_of_ORF(dna)\",\n \"def find_all_ORFs_both_strands_unit_tests():\\n\\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs_unit_tests():\\n data_list = [\\n [\\\"ATGCATGAATGTAG\\\", [\\\"ATGCATGAATGTAG\\\", \\\"ATGAATGTAG\\\", \\\"ATG\\\"]],\\n [\\\"ATG\\\", [\\\"ATG\\\"]],\\n [\\\"AATG\\\", [\\\"ATG\\\"]],\\n [\\\"AAATG\\\", [\\\"ATG\\\"]],\\n [\\\"ATGATG\\\", [\\\"ATGATG\\\"]],\\n [\\\"ATATGGATTGA\\\", [\\\"ATGGAT\\\"]],\\n [\\\"ATGAGATTAG\\\", [\\\"ATGAGATTAG\\\"]],\\n [\\\"ATATGGATTAGTAGTAATGAAAGTATAG\\\", [\\\"ATGAAAGTA\\\", \\\"ATGGAT\\\", ]],\\n# ATA TGG ATT AGT AGT AAT GAA AGT ATA G\\n# TAT GGA TTA GTA GTA ATG AAA GTA TAG\\n# ATG GAT TAG TAG TAA TGA AAG TAT AG\\n [\\\"ATGTCACGCAATGTAGGATGGATGGATTAGAC\\\", [\\\"ATGTCACGCAATGTAGGATGGATGGAT\\\", \\\"ATG\\\", \\\"ATGGATGGATTAGAC\\\"]],\\n# ATG TCA CGC AAT GTA GGA TGG ATG GAT TAG AC --> ATG TCA CGC AAT GTA GGA TGG ATG GAT\\n# TGT CAC GCA ATG TAG GAT GGA TGG ATT AGA C\\n# GTC ACG CAA TGT AGG ATG GAT GGA TTA GAC\\n [\\\"ATGATGTAG\\\", [\\\"ATGATG\\\"]],\\n [\\\"TCGATGC\\\", [\\\"ATGC\\\"]],\\n [\\\"AAA\\\", []],\\n# TCG ATG C\\n# CGA TGC\\n# GAT GC\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\",\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = find_all_ORFs(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n\\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs_unit_tests():\\n \\n print \\\"input: ATGCTA, \\\"+\\\"output: \\\"+ \\\",\\\".join(find_all_ORFs(\\\"ATGCTA\\\"))+\\\", actual output: CTA\\\"\\n print \\\"input: GTCACTTATGGGTTT, \\\"+\\\"output: \\\"+\\\",\\\".join(find_all_ORFs(\\\"ATGGATGCTTAGGGATGTTT\\\"))+\\\", actual output: GTCACT,GGTTTT,TCACTTAGGGTTTT,CACTTAGGGTTTT\\\"\\n print \\\"input: AAATTTTATAATGGGTGAAGTTAG, \\\"+\\\"output: \\\"+\\\",\\\".join(find_all_ORFs(\\\"AAATTTTATAATGGGTGAAGTTAG\\\"))+\\\", actual output: ATGGGTGAAGTT\\\"\\n print \\\"input: TATATGGAGGATAATAGTTGATAATAG, \\\"+\\\"output: \\\"+ \\\",\\\".join(find_all_ORFs(\\\"TATATGGAGGATAATAGTTGATAATAG\\\"))+\\\", actual output: ATGGAGGATAATAGT\\\"\",\n \"def longest_ORF_unit_tests():\\n\\n # YOUR IMPLEMENTATION HERE\",\n \"def longest_ORF_unit_tests():\\n\\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs_both_strands_unit_tests():\\n print ''\\n print 'Begin Unit test Find_all_ORFs both tests'\\n input_a='ATGCGAGGGTAGATGGATTAG'\\n expected_output='[ATGCGAGGG, ATGGAT]'\\n actual_output=find_all_ORFs_both_strands(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\\n \\n \\n input_a='ATGCGAATGTAGCATCAAATAGATGTAG'\\n expected_output='[ATGCGAATG, ATG, ATGCTACATTCGCAT]'\\n actual_output=find_all_ORFs_both_strands(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output \\n print 'end'\\n print ''\",\n \"def unitary_test():\",\n \"def test_empty_functions():\",\n \"def _test(self):\",\n \"def _test(self):\",\n \"def _test(self):\",\n \"def _test(self):\",\n \"def _test(self):\",\n \"def test_organizations_read(self):\\n pass\",\n \"def test_submit_for_endorsement(self):\",\n \"def test_basic_execution(self):\",\n \"def test_get_insumo(self):\",\n \"def test_uparforvarg(self):\",\n \"def test_data_in_param(self):\",\n \"def test_getorgs(self):\\n pass\",\n \"def test_T01():\",\n \"def test(self):\\n pass\",\n \"def test_all_filter_op_fields(self):\\n for field in OCIFilterSerializer._opfields:\\n field = \\\"and:\\\" + field\\n filter_param = {field: [\\\"1\\\", \\\"2\\\"]}\\n serializer = OCIFilterSerializer(data=filter_param)\\n self.assertTrue(serializer.is_valid())\\n for field in OCIFilterSerializer._opfields:\\n field = \\\"or:\\\" + field\\n filter_param = {field: [\\\"1\\\", \\\"2\\\"]}\\n serializer = OCIFilterSerializer(data=filter_param)\\n self.assertTrue(serializer.is_valid())\",\n \"def test_T2():\",\n \"def test_T2():\",\n \"def test_postorgs(self):\\n pass\",\n \"def test_trailing_data(self):\",\n \"def test_let(self):\",\n \"def _test(self):\\n pass\",\n \"def _test(self):\\n pass\",\n \"def _test(self):\\n pass\",\n \"def longest_ORF_unit_tests():\\n data_list = [\\n [\\\"ATGCGAATGTAGCATCAAA\\\", \\\"ATGCTACATTCGCAT\\\"],\\n [\\\"ATG\\\", \\\"ATG\\\"],\\n [\\\"CAT\\\", \\\"ATG\\\"],\\n [\\\"CATCAT\\\", \\\"ATGATG\\\"],\\n [\\\"CATGGGCAT\\\", \\\"ATGCCCATG\\\"],\\n [\\\"CATGCAGTGCACGGATGGCAT\\\", \\\"ATGCCATCCGTGCACTGCATG\\\"],\\n# CATGCAGTGCACGGATGGCAT\\n# CAT GCA GTG CAC GGA TGG CAT\\n# ATG CAG TGC ACG GAT GGC AT\\n# TGC AGT GCA CGG ATG GCA T\\n# ATGCCATCCGTGCACTGCATG\\n# ATG CCA TCC GTG CAC TGC ATG\\n# TGC CAT CCG TGC ACT GCA TG\\n# GCC ATC CGT GCA CTG CAT G\\n [\\\"CATATGTAG\\\", \\\"ATG\\\"],\\n [\\\"ATGGGGCATCATTAG\\\", \\\"ATGGGGCATCAT\\\"],\\n# ATGGGGCATCATTAG\\n# ATG GGG CAT CAT TAG\\n# TGG GGC ATC ATT AG\\n# GGG GCA TCA TTA G\\n# CTAATGATGCCCCAT\\n# CTA ATG ATG CCC CAT\\n# TAA TGA TGC CCC AT\\n# AAT GAT GCC CCA T\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\",\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = longest_ORF(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def test_something():\",\n \"def test_required_methods(self):\",\n \"def testApi(self):\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n input_a='ATGATTATTTGATGAATGGATTGA'\\n expected_output='[ATGATTATT,ATGGAT]'\\n actual_output=find_all_ORFs_oneframe(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\\n \\n input_a='ATGGGATTGTTT'\\n expected_output='[ATGGATTGTTT]'\\n actual_output=find_all_ORFs_oneframe(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\",\n \"def find_all_ORFs_both_strands_unit_tests():\\n data_list = [\\n [\\\"ATGCGAATGTAGCATCAAA\\\", [\\\"ATGCGAATG\\\", \\\"ATGCTACATTCGCAT\\\"]],\\n [\\\"ATG\\\", [\\\"ATG\\\"]],\\n [\\\"CAT\\\", [\\\"ATG\\\"]],\\n [\\\"CATCAT\\\", [\\\"ATGATG\\\"]],\\n [\\\"CATGGGCAT\\\", [\\\"ATGGGCAT\\\", \\\"ATGCCCATG\\\"]],\\n [\\\"CATGCAGTGCACGGATGGCAT\\\", [\\\"ATGCAGTGCACGGATGGCAT\\\", \\\"ATGGCAT\\\", \\\"ATGCCATCCGTGCACTGCATG\\\"]],\\n# CATGCAGTGCACGGATGGCAT\\n# CAT GCA GTG CAC GGA TGG CAT\\n# ATG CAG TGC ACG GAT GGC AT\\n# TGC AGT GCA CGG ATG GCA T\\n# ATGCCATCCGTGCACTGCATG\\n# ATG CCA TCC GTG CAC TGC ATG\\n# TGC CAT CCG TGC ACT GCA TG\\n# GCC ATC CGT GCA CTG CAT G\\n [\\\"CATATGTAG\\\", [\\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGGGGCATCATTAG\\\", [\\\"ATGGGGCATCAT\\\", \\\"ATGATGCCCCAT\\\"]],\\n# ATGGGGCATCATTAG\\n# ATG GGG CAT CAT TAG\\n# TGG GGC ATC ATT AG\\n# GGG GCA TCA TTA G\\n# CTAATGATGCCCCAT\\n# CTA ATG ATG CCC CAT\\n# TAA TGA TGC CCC AT\\n# AAT GAT GCC CCA T\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\",\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = find_all_ORFs_both_strands(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def find_all_ORFs_unit_tests():\\n \\n input = [\\\"dna\\\"]\\n expected_output = [\\\"all non-nested ORFs\\\"]\\n actual = []\\n for k in input:\\n actual.append(find_all_ORFs(k))\\n print input \\n print actual\\n print expected_output\",\n \"def test_prepare_bearer_request(self):\\n self.assertEqual(prepare_bearer_headers(self.token), self.bearer_headers)\\n self.assertEqual(prepare_bearer_body(self.token), self.bearer_body)\\n self.assertEqual(prepare_bearer_uri(self.token, uri=self.uri), self.bearer_uri)\",\n \"def test_process_data(self):\\n pass\",\n \"def test_get_run(self):\\n pass\",\n \"def test_T3():\",\n \"def test_T3():\",\n \"def test_if(self):\",\n \"def test(self) -> Any:\\n pass\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n data_list = [\\n [\\\"ATGCATGAATGTAGATAGATGTGCCC\\\", [\\\"ATGCATGAATGTAGA\\\", \\\"ATGTGCCC\\\"]],\\n [\\\"ATGTAGATGTAG\\\", [\\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGATGATG\\\", [\\\"ATGATGATG\\\"]],\\n [\\\"ATGGGGGATTAGATGATG\\\", [\\\"ATGGGGGAT\\\", \\\"ATGATG\\\"]],\\n [\\\"ATGTGAATGTAA\\\", [\\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGTGAATGTAAATG\\\", [\\\"ATG\\\", \\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGCGTGGTGATTAGATGGATGGGGATTGA\\\", [\\\"ATGCGTGGTGAT\\\", \\\"ATGGATGGGGAT\\\"]],\\n [\\\"ATGAAATTTCCCGGGAAATTTCCCGGG\\\", [\\\"ATGAAATTTCCCGGGAAATTTCCCGGG\\\"]],\\n [\\\"ATGAAATTTTGAATGGGGCCC\\\", [\\\"ATGAAATTT\\\", \\\"ATGGGGCCC\\\"]],\\n [\\\"ATGAAATTTTGAATGGGGCCCTAG\\\", [\\\"ATGAAATTT\\\", \\\"ATGGGGCCC\\\"]],\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\",\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = find_all_ORFs_oneframe(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def test_T0():\",\n \"def test_get2(self):\\n pass\",\n \"def func_case(self):\\n test.success(\\\"\\\")\",\n \"def test_T4():\",\n \"def test_T4():\",\n \"def test(self):\",\n \"def test(self):\",\n \"def test_4_4_1_1(self):\\n pass\",\n \"def test(self):\\n raise NotImplementedError\",\n \"def test_api_response_data(self):\",\n \"def test_dummy():\",\n \"def test_untar(self):\",\n \"def test():\",\n \"def test():\",\n \"def longest_ORF_unit_tests():\\n\\n input_a=\\\"ATGCGAATGTAGCATCAAA\\\"\\n expected_output=''\\n actual_output=longest_ORF(input_a)\\n print 'Expected Output is ' + expected_output\\n print \\\"actual output: \\\", actual_output\",\n \"def test_nothing(self):\",\n \"def test_require():\",\n \"def test_create_from_pear(self):\\n pass\",\n \"def _test_example_fragments_orca():\\n main([\\\"pnictogen/repo/split.ORCA.inp\\\", \\\"data/water-dimer.xyz\\\"])\\n assert_equals(\\n open(\\\"data/water-dimer.inp\\\").read(),\\n \\\"\\\"\\\"# data/water-dimer.xyz\\n! Opt\\n\\n* xyz 0 1\\nO(1) 0.12908 -0.26336 0.64798\\nH(1) 0.89795 0.28805 0.85518\\nH(1) 0.10833 -0.20468 -0.33302\\nO(2) 0.31020 0.07569 -2.07524\\nH(2) -0.26065 0.64232 -2.62218\\nH(2) 0.64083 -0.57862 -2.71449\\n*\\\"\\\"\\\",\\n )\",\n \"def test_T1():\",\n \"def test_T1():\",\n \"def test_retrieve_l_organizations(self):\\n pass\",\n \"def test_function(eso_from_data:callable):\\n print('Testing of eso_from_data with hardcoded data')\\n # for context, relation, concepts_source in SEQUENCE:\\n eso_from_data(0, 'site', 'contains', 'animal')\",\n \"def test_open_fill(self):\",\n \"def test_get1(self):\\n pass\",\n \"def test_searchOr(self):\\n self.assertTrue(\\n self.server.search_OR(\\n [\\\"SENTSINCE\\\"] + self.earlierQuery +\\n [\\\"SENTSINCE\\\"] + self.laterQuery,\\n self.seq, self.msg, (None, None)))\\n self.assertTrue(\\n self.server.search_OR(\\n [\\\"SENTSINCE\\\"] + self.laterQuery +\\n [\\\"SENTSINCE\\\"] + self.earlierQuery,\\n self.seq, self.msg, (None, None)))\\n self.assertFalse(\\n self.server.search_OR(\\n [\\\"SENTON\\\"] + self.laterQuery +\\n [\\\"SENTSINCE\\\"] + self.laterQuery,\\n self.seq, self.msg, (None, None)))\",\n \"def test_begin(self):\",\n \"def find_all_ORFs_unit_tests(dna, expected):\\n \\n print find_all_ORFs(\\\"ATGCATGAATGTAG\\\")\\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + find_all_ORFs(dna)\",\n \"def test():\\n pass\",\n \"def test_get_orders(self):\\n pass\",\n \"def test_get_results(self):\\n pass\",\n \"def test_OneOfEverything(self):\\n self._run(self._test_scenarios, \\\"OneOfEverything\\\")\",\n \"def test_organizations_list(self):\\n pass\",\n \"def test_orchestrator_http_simple(self):\\n pass\",\n \"def test_alien_data(self):\",\n \"def test_filter_wea_zero_entry():\\n pass\",\n \"def test_4():\",\n \"def test_01_lighting(self):\",\n \"def test_theft_and_stealing(self):\",\n \"def test_or(self):\\n\\n xy = t.Or([t.Exactly(\\\"x\\\"),\\n t.Exactly(\\\"y\\\")])\\n self.assertEqual(writePython(xy),\\n dd(\\\"\\\"\\\"\\n def _G_or_1():\\n _G_exactly_2, lastError = self.exactly('x')\\n self.considerError(lastError, None)\\n return (_G_exactly_2, self.currentError)\\n def _G_or_3():\\n _G_exactly_4, lastError = self.exactly('y')\\n self.considerError(lastError, None)\\n return (_G_exactly_4, self.currentError)\\n _G_or_5, lastError = self._or([_G_or_1, _G_or_3])\\n self.considerError(lastError, None)\\n _G_or_5\\n \\\"\\\"\\\"))\",\n \"def test_01_Init(self):\\n pass\",\n \"def orfFinder(data):\\n\\t\\n\\tORFile = getORFs(data.seqFile, \\n\\t\\t\\t\\t\\t data.queryName, \\n\\t\\t\\t\\t\\t data.o)\\n\\tsetattr(data, \\\"ORFs\\\", ORFile)\",\n \"def test_read_o_auth_client_authorization(self):\\n pass\",\n \"def test_get_details7(self):\\n pass\",\n \"def test_solareclipses_get(self):\\n pass\",\n \"def test_rpcCall(self):\\n pass\",\n \"def test_init(self):\\n assert self.route.route[\\\"transform\\\"] == \\\"transform\\\"\\n assert self.route.route[\\\"output\\\"] == \\\"output\\\"\\n assert \\\"api\\\" not in self.route.route\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7736593","0.77165705","0.68423116","0.6646262","0.6569403","0.6511477","0.6402534","0.6199879","0.61139333","0.60930383","0.6042923","0.6042923","0.59909266","0.59864223","0.597569","0.595889","0.595889","0.595889","0.595889","0.595889","0.5914845","0.58606106","0.5848827","0.58481103","0.57765454","0.5772401","0.5733021","0.5729922","0.5692589","0.5690496","0.56826437","0.56826437","0.5682491","0.5679567","0.56618816","0.5640953","0.5640953","0.5640953","0.56397575","0.5637795","0.561966","0.5611555","0.5602722","0.5597465","0.5592845","0.55856913","0.5584487","0.55809236","0.5580293","0.5580293","0.5580022","0.55757326","0.55691147","0.55668885","0.5560063","0.55574876","0.555648","0.555648","0.55487686","0.55487686","0.5480477","0.5467721","0.5463896","0.5458379","0.5457718","0.545301","0.545301","0.5446099","0.5445016","0.5441158","0.5432806","0.5428682","0.54153585","0.54153585","0.5413427","0.54119426","0.540979","0.5409448","0.53894335","0.5382114","0.5381529","0.53772765","0.5371653","0.53697914","0.5360603","0.5358044","0.5357195","0.53476095","0.53459513","0.53298587","0.5327143","0.5326409","0.5314864","0.53068405","0.530625","0.5306086","0.5305149","0.5304296","0.53000796","0.52987385"],"string":"[\n \"0.7736593\",\n \"0.77165705\",\n \"0.68423116\",\n \"0.6646262\",\n \"0.6569403\",\n \"0.6511477\",\n \"0.6402534\",\n \"0.6199879\",\n \"0.61139333\",\n \"0.60930383\",\n \"0.6042923\",\n \"0.6042923\",\n \"0.59909266\",\n \"0.59864223\",\n \"0.597569\",\n \"0.595889\",\n \"0.595889\",\n \"0.595889\",\n \"0.595889\",\n \"0.595889\",\n \"0.5914845\",\n \"0.58606106\",\n \"0.5848827\",\n \"0.58481103\",\n \"0.57765454\",\n \"0.5772401\",\n \"0.5733021\",\n \"0.5729922\",\n \"0.5692589\",\n \"0.5690496\",\n \"0.56826437\",\n \"0.56826437\",\n \"0.5682491\",\n \"0.5679567\",\n \"0.56618816\",\n \"0.5640953\",\n \"0.5640953\",\n \"0.5640953\",\n \"0.56397575\",\n \"0.5637795\",\n \"0.561966\",\n \"0.5611555\",\n \"0.5602722\",\n \"0.5597465\",\n \"0.5592845\",\n \"0.55856913\",\n \"0.5584487\",\n \"0.55809236\",\n \"0.5580293\",\n \"0.5580293\",\n \"0.5580022\",\n \"0.55757326\",\n \"0.55691147\",\n \"0.55668885\",\n \"0.5560063\",\n \"0.55574876\",\n \"0.555648\",\n \"0.555648\",\n \"0.55487686\",\n \"0.55487686\",\n \"0.5480477\",\n \"0.5467721\",\n \"0.5463896\",\n \"0.5458379\",\n \"0.5457718\",\n \"0.545301\",\n \"0.545301\",\n \"0.5446099\",\n \"0.5445016\",\n \"0.5441158\",\n \"0.5432806\",\n \"0.5428682\",\n \"0.54153585\",\n \"0.54153585\",\n \"0.5413427\",\n \"0.54119426\",\n \"0.540979\",\n \"0.5409448\",\n \"0.53894335\",\n \"0.5382114\",\n \"0.5381529\",\n \"0.53772765\",\n \"0.5371653\",\n \"0.53697914\",\n \"0.5360603\",\n \"0.5358044\",\n \"0.5357195\",\n \"0.53476095\",\n \"0.53459513\",\n \"0.53298587\",\n \"0.5327143\",\n \"0.5326409\",\n \"0.5314864\",\n \"0.53068405\",\n \"0.530625\",\n \"0.5306086\",\n \"0.5305149\",\n \"0.5304296\",\n \"0.53000796\",\n \"0.52987385\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7421392"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":92996,"cells":{"query":{"kind":"string","value":"Finds all nonnested open reading frames in the given DNA sequence and returns them as a list. This function should only find ORFs that are in the default frame of the sequence (i.e. they start on indices that are multiples of 3). By nonnested we mean that if an ORF occurs entirely within another ORF, it should not be included in the returned list of ORFs."},"document":{"kind":"string","value":"def find_all_ORFs_oneframe(dna):\n res = []\n l = len(dna)\n next_pos = 0\n while True:\n arg = dna[next_pos:]\n# orf = rest_of_ORF(arg)\n# res.append(orf)\n# if arg == orf: # if: no stop codon\n# break\n# next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\n# if next_pos >= l: # if: meet the end of dna\n# break\n if arg[0:3] == start_codon:\n orf = rest_of_ORF(arg)\n res.append(orf)\n if arg == orf: # if: no stop codon\n break\n next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\n else: # if: not start codon, see next\n next_pos += 3\n if next_pos >= l: # if: meet or go beyond the end of dna\n break\n return res"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def find_all_ORFs(dna):\n index = 0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# initialize index\n all_ORFs = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitalize empty list\n while index < 3:\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# switches throught the 3 frames\n \tall_ORFs = all_ORFs + find_all_ORFs_oneframe(dna[index:])\t# adds all ORFs oneframe to the list\n \tindex += 1\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# indexes +1\n return all_ORFs \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns list of all ORFs in all 3 frames","def find_all_ORFs(dna):\n all_ORFs=[]\n for i in range (0,3):\n \tframe=dna[i:] \n all_ORFs+=find_all_ORFs_oneframe(frame)\n return all_ORFs","def find_all_ORFs(dna):\n first_frame = find_all_ORFs_oneframe(dna[0:])\n second_frame = find_all_ORFs_oneframe(dna[1:])\n third_frame = find_all_ORFs_oneframe(dna[2:])\n list_of_frames = first_frame + second_frame + third_frame\n return list_of_frames","def find_all_ORFs(dna):\n all_ORFs = []\n for i in range(0, 3):\n dna_new = dna[i:]\n all_ORFs += find_all_ORFs_oneframe(dna_new)\n return all_ORFs","def find_all_ORFs_oneframe(dna):\n condition = 1\n dna2 = dna\n list_of_ORFs = []\n while condition == 1:\n num_codons = int(len(dna2)/3)\n num = 0\n list_codons = []\n start_index = -1\n while num < num_codons:\n num_start = int(num*3)\n num_end = int(num*3 + 3)\n list_codons.append(dna2[num_start:num_end])\n num = num + 1\n for element in list_codons:\n if element == 'ATG':\n start_index = list_codons.index(element)\n break\n if start_index != -1:\n this_orf = rest_of_ORF(dna2[start_index*3:])\n list_of_ORFs.append(this_orf)\n dna2 = dna2[start_index*3+len(this_orf)+3:]\n else:\n condition = 2\n\n return list_of_ORFs","def find_all_ORFs_oneframe(dna):\n \n\n ORFs=[]\n i=0\n while i<len(dna):\n if dna[i:i+3]==\"ATG\":\n j=i\n dna2=rest_of_ORF(dna[j:])\n \n if dna2==None:\n \tbreak\n ORFs.append(dna2)\n i=i+len(dna2)\n i=i+3\n return ORFs","def find_all_ORFs_oneframe(dna):\n dna_split = split_into_codons(dna)\n i = 0\n all_ORFs_oneframe = []\n length_of_orf = 0\n while i < len(dna_split):\n if dna_split[i] == \"ATG\":\n orf = rest_of_ORF(dna[int(i)*3:])\n all_ORFs_oneframe += [orf]\n length_of_orf = math.ceil(len(orf)/3)\n i += length_of_orf\n else:\n i += 1\n return all_ORFs_oneframe","def find_all_ORFs_oneframe(dna):\n\n ORFlist = []\n i = 0\n lend = len(dna)\n while i < lend:\n codon = dna[i:i+3]\n if codon == 'ATG':\n orf = rest_of_ORF(dna[i:])\n ORFlist.append(orf)\n i = i + len(orf)\n else:\n i = i+3\n return ORFlist","def find_all_ORFs(dna):\n ORFs = find_all_ORFs_oneframe(dna) + find_all_ORFs_oneframe(dna[1:]) + find_all_ORFs_oneframe(dna[2:])\n\n return ORFs","def find_all_ORFs_oneframe(dna):\n i=0 \n ORF_list = []\n while i<len(dna):\n if dna[i : i+3] == \"ATG\":\n start_place = i \n current_ORF = rest_of_ORF(dna[start_place:])\n i += 3 + len(current_ORF)\n ORF_list.append(current_ORF) \n return ORF_list","def find_all_ORFs_oneframe(dna):\n x = 3\n list_of_dna = []\n while (x < len(dna)):\n if dna[x-3:x] == 'ATG':\n current_dna = rest_of_ORF(dna[x-3:])\n list_of_dna.append(current_dna)\n x += len(current_dna)\n x += 3\n return list_of_dna","def find_all_ORFs(dna):\n dnatwo = dna[1:]\n dnathree = dna[2:]\n all_ORFs = find_all_ORFs_oneframe(dna)\n all_ORFs.extend(find_all_ORFs_oneframe(dnatwo))\n all_ORFs.extend(find_all_ORFs_oneframe(dnathree))\n if [] in all_ORFs:\n all_ORFs.remove([])\n return all_ORFs","def find_all_ORFs_oneframe(dna):\n\tindex = 0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# unitiate index at 0\n\tsegment = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitializes empty list\n\twhile index < len(dna):\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# given that index is smaller than length of string\n\t\tcodon = dna[index:index + 3]\t\t\t\t\t\t\t\t\t\t\t\t\t\t# creates codons from nucleotides starting with first 3 letters\n\t\tif codon == \"ATG\":\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if the codon is ATG\n\t\t\tsegment.append(rest_of_ORF(dna[index:]))\t\t\t\t\t\t\t\t\t\t# run rest_of_ORF starting at index\n\t\t\tindex = index + len(rest_of_ORF(dna[index:]))\t\t\t\t\t\t\t\t\t# new index starting at old + length of ORF output string\n\t\telse:\n\t\t\tindex += 3\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if ATG isn't found, move to next codon and check again\n\n\treturn segment\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns list of ORFs","def find_all_ORFs_oneframe(dna):\n i = 0\n list_ORF = []\n\n def search_ORF(dna,i):\n aa = dna[3*i:(3*i)+3]\n if aa == 'ATG':\n list_ORF.append(rest_of_ORF(dna,aa,i))\n i = i + 1 + len(rest_of_ORF(dna,aa,i))/3\n else:\n i = i + 1\n if len(aa) ==3:\n search_ORF(dna,i)\n \n return list_ORF\n\n return search_ORF(dna,i)\n # i = i + ((len(list_ORF[-1]))/3)\n # search_ORF(dna,i)","def find_all_ORFs(dna):\n res = []\n for i in range(0, 3):\n s = dna[i:]\n# print i, s,\n# l = len(s)\n# for j in range(0, l, 3):\n# if s[j: j + 3] == start_codon:\n# r = find_all_ORFs_oneframe(s[j:])\n# print r\n# if len(r) > 0:\n# for item in r:\n# res.append(item)\n# break # careful for indentation here!!\n r = find_all_ORFs_oneframe(s)\n if len(r) > 0:\n# for item in r:\n# res.append(item)\n res += r # [WOW] I love python!\n return res","def find_all_ORFs(dna):\n ans = find_all_ORFs_oneframe(dna)\n ans.extend(find_all_ORFs_oneframe(dna[1:]))\n ans.extend(find_all_ORFs_oneframe(dna[2:]))\n return ans","def find_all_ORFs(dna):\n all_ORFs = []\n i = 0\n\n for i in range (0,3): \n all_ORFs.extend(find_all_ORFs_oneframe(dna))\n dna = 'X' + dna\n\n return all_ORFs","def find_all_ORFs(dna):\n\n readingFrame0 = ''\n readingFrame1 = ''\n readingFrame2 = ''\n output = ''\n for k in range(0,3): \n if k ==0: \n readingFrame0 = find_all_ORFs_oneframe(dna[k:])\n elif k ==1: \n readingFrame1 = find_all_ORFs_oneframe(dna[k:])\n elif k ==2:\n readingFrame2 = find_all_ORFs_oneframe(dna[k:])\n print 'Reading Frame 1: ' + str(readingFrame0) + ', Reading Frame 2: ' + str(readingFrame1) + ', Reading Frame 3: ' + str(readingFrame2)\n output = readingFrame0 + readingFrame1 + readingFrame2\n return output","def find_all_ORFs_oneframe(dna):","def find_all_ORFs(dna):\n #these functions offset to analyze each each open frame reference\n zero_offset=find_all_ORFs_oneframe(dna[0:])\n \n one_offset=find_all_ORFs_oneframe(dna[1:])\n \n two_offset=find_all_ORFs_oneframe(dna[2:])\n \n return zero_offset+one_offset+two_offset\n \n # YOUR IMPLEMENTATION HERE","def find_all_ORFs_oneframe(dna):\n #inital conditions\n i = 0\n start_codon = ('ATG')\n end_index = len(dna)\n return_variable = []\n\n #for each codon in the set of DNA, check if it is a start codon\n #if it is a start codon, add the string until the stop codon to a list\n #then continue running\n while i < len(dna)-2:\n codon = dna[i:i+3] \n if codon in start_codon:\n orf = rest_of_ORF(dna[i:])\n return_variable.append(orf)\n i += len(orf)\n i += 3\n\n\n #return a list of strings of DNA\n return return_variable","def find_all_ORFs(dna):\n #inital conditions\n i = 0\n start_codon = ('ATG')\n end_index = len(dna)\n return_variable = []\n\n #for statement tells the code to run three times at three inital index values\n #0,1,and 2 which allows for each reading frame to be read\n for i in range (3):\n while i < (len(dna)-2):\n codon = dna[i:i+3] \n if codon in start_codon: #check if the codon the code is looking at is a start codon\n orf = rest_of_ORF(dna[i:]) #then determine that this is an orf, make it a string given the index of the start codon\n return_variable.append(orf) #and append said string to a list of ORFs\n i += len(orf) \n i += 3\n #return a list of strings of DNA from both strands\n return return_variable","def find_all_ORFs_oneframe(dna):\n strand = []\n startCodon = [\"ATG\"]\n for i in range(0,len(dna),3):\n triple = dna[i:i+3]\n if triple in startCodon: \n strand.append(rest_of_ORF(dna[i:]))\n print strand\n return strand","def ORFs(self):\n ORFStart = None\n openLeft = True\n seenStart = False\n\n for index, residue in enumerate(self.sequence):\n if residue == 'M':\n # Start codon.\n openLeft = False\n seenStart = True\n elif residue == '*':\n # Stop codon. Yield an ORF, if it has non-zero length.\n if ORFStart is not None and index - ORFStart > 0:\n # The ORF has non-zero length.\n yield AAReadORF(self, ORFStart, index, openLeft, False)\n ORFStart = None\n # After a stop codon, we can no longer be open on the left\n # and we have no longer seen a start codon.\n openLeft = seenStart = False\n else:\n if (seenStart or openLeft) and ORFStart is None:\n ORFStart = index\n\n # End of sequence. Yield the final ORF if there is one and it has\n # non-zero length.\n length = len(self.sequence)\n if ((seenStart or openLeft) and ORFStart is not None and\n length - ORFStart > 0):\n yield AAReadORF(self, ORFStart, length, openLeft, True)","def rest_of_ORF(dna):\n readingFrame = ''\n endCodons = [\"TAG\", \"TAA\", \"TGA\"]\n for i in range(0,len(dna),3):\n triple = dna[i:i+3]\n if triple in endCodons:\n readingFrame = readingFrame\n break\n else: \n readingFrame+=triple \n return readingFrame","def find_all_ORFs_oneframe_unit_tests(dna, expected):\n\n print find_all_ORFs_oneframe(\"ATGCATGAATGTAGATAGATGTGCCC\")\n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + find_all_ORFs_oneframe(dna)","def find_longest_orfs(seq,n_orfs):\n\n # Make sure there is a start codon in the sequence:\n if not 'ATG' in seq:\n raise RuntimeError(\"Your DNA sequence doesn't have a start codon.\")\n\n # Initialize orfs list:\n orfs =[]\n\n # Loop over sequence and find ORFs:\n for i, base in enumerate(seq):\n triplet = seq[i:i+3]\n if triplet == 'ATG':\n orf_seq = ''\n aa_seq = ''\n j = i\n while j+2 < len(seq):\n codon = seq[j:j+3]\n orf_seq += codon\n if bioinfo_dicts.codons[codon] == '*': # if stop codon\n orf_len = len(orf_seq)\n orfs.append((orf_len,orf_seq,aa_seq)) # j is orf len in nts\n break # this only breaks out of while loop, right?\n else:\n aa_seq += bioinfo_dicts.codons[codon]\n j+=3\n\n # Sort orf list by length\n orfs.sort()\n\n # Select n longest orfs to return:\n number = -(n_orfs+1)\n longest_orfs = orfs[:number:-1]\n\n longest_orfs = tuple(longest_orfs)\n return longest_orfs","def get_open_issues(self, owners: List[str]) -> List[EventRecord]:\n with self.session.begin() as session:\n open_issues = (\n session.query(EventRecord)\n .filter(EventRecord.owner.in_(owners))\n .filter(EventRecord.received_at >= datetime.utcnow() - timedelta(days=1))\n .all()\n )\n\n open_issues = remove_duplicate_events(open_issues)\n\n open_issues_fps = [issue.fingerprint for issue in open_issues]\n\n ignored_issues_fps_tuples = (\n session.query(IgnoreFingerprintRecord.fingerprint)\n .filter(IgnoreFingerprintRecord.fingerprint.in_(open_issues_fps))\n .filter(\n (IgnoreFingerprintRecord.expires_at > datetime.utcnow())\n | (IgnoreFingerprintRecord.expires_at.is_(None))\n )\n .all()\n )\n\n ignored_issues_fps = [t[0] for t in ignored_issues_fps_tuples]\n\n return [issue for issue in open_issues if issue.fingerprint not in ignored_issues_fps]","def reading_frames(dna):\n #the 6 types are as follows\n # the actual string and the reverse complement\n list = []\n #this is the actual string\n list.append(dna)\n #this is the reverse complement of the string\n # done reusing the fastcomplement() method that was already available.\n #others are done likewise\n list.append(fast_complement(dna[::-1]))\n list.append(dna[1:len(dna)])\n list.append(fast_complement(dna[1:len(dna)][::-1]))\n list.append(dna[2:len(dna)])\n list.append(fast_complement(dna[2:len(dna)][::-1]))\n return list","def getouterframes(frame, context=1):\r\n framelist = []\r\n while frame:\r\n framelist.append((frame,) + getframeinfo(frame, context))\r\n frame = frame.f_back\r\n return framelist","def find_all_ORFs_oneframe_unit_tests():\n\n input = [\"dna\"]\n expected_output = [\"all non-nester ORFs\"]\n actual = []\n for k in input:\n actual.append(find_all_ORFs_oneframe(k))\n print input \n print actual\n print expected_output","def get_open_cells(field: MineField, cell: Cell) -> List[Cell]:\n # TODO re-implement iteratively to safe stack space (especially for large boards)\n if cell.is_flag or cell.is_mine or not field.cell_is_safe(cell):\n return [cell]\n \n if cell.visited:\n return\n\n open_cells: list = list()\n cell.visited = True\n open_cells.append(cell)\n\n for cell in field.surrounding_cells(cell):\n open_cells.append(cell)\n if cell.is_flag or cell.visited or not field.cell_is_safe(cell):\n continue\n\n\n open_cells += get_open_cells(field, cell)\n\n return open_cells","def find_all_ORFs_oneframe_unit_tests():\n data_list = [\n [\"ATGCATGAATGTAGATAGATGTGCCC\", [\"ATGCATGAATGTAGA\", \"ATGTGCCC\"]],\n [\"ATGTAGATGTAG\", [\"ATG\", \"ATG\"]],\n [\"ATGATGATG\", [\"ATGATGATG\"]],\n [\"ATGGGGGATTAGATGATG\", [\"ATGGGGGAT\", \"ATGATG\"]],\n [\"ATGTGAATGTAA\", [\"ATG\", \"ATG\"]],\n [\"ATGTGAATGTAAATG\", [\"ATG\", \"ATG\", \"ATG\"]],\n [\"ATGCGTGGTGATTAGATGGATGGGGATTGA\", [\"ATGCGTGGTGAT\", \"ATGGATGGGGAT\"]],\n [\"ATGAAATTTCCCGGGAAATTTCCCGGG\", [\"ATGAAATTTCCCGGGAAATTTCCCGGG\"]],\n [\"ATGAAATTTTGAATGGGGCCC\", [\"ATGAAATTT\", \"ATGGGGCCC\"]],\n [\"ATGAAATTTTGAATGGGGCCCTAG\", [\"ATGAAATTT\", \"ATGGGGCCC\"]],\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs_oneframe(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def find_all_ORFs_both_strands(dna):\n orfs = []\n orfs = find_all_ORFs(dna) + find_all_ORFs(get_reverse_complement(dna))\n return orfs","def longest_ORF(dna):\n\n reverseComp = get_reverse_complement(dna)\n openFramesfromReverse = find_all_ORFs(reverseComp)\n openFramesfromNormal = find_all_ORFs(dna)\n all_ORFs = openFramesfromNormal + openFramesfromReverse\n longest = max(all_ORFs, key=len)\n return longest","def longest_ORF(dna):\n \n all_ORFs = find_all_ORFs_both_strands(dna)\n\n if len(all_ORFs) > 0:\n return max(all_ORFs, key = len)\n else:\n return []","def find_all_ORFs_oneframe(dna): \n i=0\n multiple_list=[]\n while i < len(dna):\n part = dna[i:i+3]\n if part == 'ATG': #if the first indecied are ATG then it runs the code that creates the string of DNA\n ORF=rest_of_ORF(dna[i:]) \n multiple_list.append(ORF)\n i+=len(ORF)\n else:\n i+=3\n # print multiple_list\n return multiple_list\n \n #runs fuinction to mmake list of function\n #need to save to list\n #need to continue to next ATG start \n #need to add that to list\n #need to output new list as commas between lists","def find_all_ORFs(dna):\n \n # YOUR IMPLEMENTATION HERE","def gene_finder(dna):\n orfs = find_all_ORFs_both_strands(dna)\n print(orfs)\n threshold = longest_ORF_noncoding(dna, 1000)\n print('threshold is', threshold)\n print('number of orfs:', len(orfs))\n aa_sequences = []\n i = 0\n while i < len(orfs):\n print(len(orfs[i]))\n if len(orfs[i]) > threshold:\n print('if')\n aa_sequences += [coding_strand_to_AA(orfs[i])]\n i += 1\n print(aa_sequences)","def get_orfs(genome, min_num_aa):\n allowed = \"ATGC\"\n if not isinstance(genome, str) or len(genome) == 0 or not all(c in allowed for c in genome):\n raise TypeError\n start_codon = \"ATG\"\n stop_codon = ['TAA', 'TAG', 'TGA']\n ref_dict = {\"T\" : \"A\", \"A\" : \"T\", \"G\" : \"C\", \"C\" : \"G\"}\n amino_dict = {\n 'L' : ['CTC', 'CTT', 'CTA', 'CTG', 'TTA', 'TTG'],\n 'S' : ['TCA', 'TCT', 'TCC', 'TCG', 'AGC', 'AGT'],\n 'R' : ['CGA', 'CGC', 'CGT', 'CGG', 'AGA', 'AGG'],\n 'V' : ['GTA', 'GTG', 'GTC', 'GTT'],\n 'P' : ['CCC', 'CCA', 'CCG', 'CCT'],\n 'T' : ['ACC', 'ACG', 'ACT', 'ACA'],\n 'A' : ['GCA', 'GCC', 'GCG', 'GCT'],\n 'G' : ['GGA', 'GGC', 'GGT', 'GGG'],\n 'I' : ['ATA', 'ATC', 'ATT'],\n 'F' : ['TTT', 'TTC'],\n 'Y' : ['TAT', 'TAC'],\n 'H' : ['CAC', 'CAT'],\n 'Q' : ['CAG', 'CAA'],\n 'N' : ['AAC', 'AAT'],\n 'K' : ['AAA', 'AAG'],\n 'D' : ['GAC', 'GAT'],\n 'E' : ['GAA', 'GAG'],\n 'C' : ['TGC', 'TGT'],\n 'M' : ['ATG'],\n 'W' : ['TGG']\n\n }\n comp_genome = \"\"\n for stra in genome:\n comp_genome += ref_dict[stra]\n main_orfs = find_orfs(genome, start_codon, stop_codon, min_num_aa, amino_dict, False)\n comp_orfs = find_orfs(comp_genome[::-1], start_codon, stop_codon, min_num_aa, amino_dict, True)\n circular_orfs = find_cir_orfs(genome, main_orfs, start_codon, stop_codon, min_num_aa, amino_dict, False)\n \n circular_orfs_comp = find_cir_orfs(comp_genome[::-1], comp_orfs, start_codon, stop_codon, min_num_aa, amino_dict, True)\n \n for main_orf in main_orfs:\n for cir_orf in circular_orfs:\n if main_orf[0] <= cir_orf[1] and main_orf[1] <= cir_orf[1] or len(main_orf) == 5:\n main_orfs.remove(main_orf)\n for comp_orf in comp_orfs:\n for cir_orf in circular_orfs_comp:\n if comp_orf[1] == cir_orf[1] or len(comp_orf) == 5:\n comp_orfs.remove(comp_orf)\n\n final_orf = main_orfs + comp_orfs + circular_orfs + circular_orfs_comp\n #print(len(comp_orfs))\n \n \n \n return final_orf","def find_all_ORFs_oneframe_unit_tests():\n input_a='ATGATTATTTGATGAATGGATTGA'\n expected_output='[ATGATTATT,ATGGAT]'\n actual_output=find_all_ORFs_oneframe(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output\n \n input_a='ATGGGATTGTTT'\n expected_output='[ATGGATTGTTT]'\n actual_output=find_all_ORFs_oneframe(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output","def gene_finder(dna):\n threshold = longest_ORF_noncoding(dna, 1500)\n l = []\n for i in find_all_ORFs_both_strands(dna):\n \tif len(i)>=threshold:\n \t\tl.append(coding_strand_to_AA(i))\n print l\n return l","def count_frames():\n frames = sentence.sem.frames.find_all('frame', {'name' : NEGATION_FRAME_NAME})\n frame_count = []\n for f_r in frames:\n frame_count.append(f_r)\n return len(frame_count)","def get_all_frames(self):\n #pdb.set_trace()\n frame_size=(512,512)\n frame_data = []\n variant_type = (pythoncom.VT_BYREF | pythoncom.VT_ARRAY | pythoncom.VT_UI2)\n for i in xrange(self.defaults['EXP_SEQUENTS']):\n frame_data.append(win32com.client.VARIANT(variant_type, numpy.empty(frame_size)))\n frame_data[i]=self.appdoc.GetFrame(i+1,frame_data[i])\n \n return numpy.array(frame_data, dtype=numpy.uint16)","def find_all_ORFs_both_strands(dna):\n reverse_dna = get_reverse_complement(dna)\n orfs = find_all_ORFs(dna)\n backward_orfs = find_all_ORFs(reverse_dna)\n orfs.extend(backward_orfs)\n return orfs","def rest_of_ORF(dna,aa,i):\n\n rest_of_ORF = []\n \n while len(aa) ==3 and aa not in stop_codons: #run this loop until locating a stop\n # if len(aa) == 3:\n rest_of_ORF.append (aa) #add each successive codon to list\n i = i+1\n aa = dna[3*i:(3*i)+3]\n # else:\n # rest_of_ORF.append (aa)\n # return ''.join(rest_of_ORF)\n\n return ''.join(rest_of_ORF)","def rest_of_ORF(dna):\n end_dna = len(dna)\n for group in range(0, end_dna, 3):\n strand = dna[group:group+3]\n if strand in ['TGA', 'TAA', 'TAG']:\n return dna[0:group]\n return dna","def retrieve_open_issues(self):\n return self._retrieve_issues(\"open\")","def rest_of_ORF(dna):\n\n #inital conditions\n i = 3\n end_index = len(dna)\n stop_codon = ('TAG','TAA','TGA')\n\n #for the length of the string of DNA, run through each codon and break and return the indec of the string if the codon is a stop codon\n while i < len(dna)-2:\n codon = dna[i:i+3] #takes only every third index which is the length of a codon\n if codon in stop_codon:\n end_index = i \n break\n i += 3\n #returns a list from the start codon to the index where the stop codon begins\n return dna[0:end_index]","def list_open_roi_jobs(self):\n db = self.database\n job_list = []\n\n # Database structure\n # dyad datatype camera datatype2 version\n #[\"33\"][\"motion\"][\"3\"][\"in_roi\"][\"1\"][\"coordinates\"]\n pathes = db.search_key(db.dictionary, \"coordinates\")\n for path in pathes:\n try:\n db.dictionary[path[0]][path[1]][path[2]][path[3]][path[4]][\"path\"]\n except KeyError:\n job_list.append(path[0:5])\n return job_list","def find_all_ORFs_unit_tests():\n \n input = [\"dna\"]\n expected_output = [\"all non-nested ORFs\"]\n actual = []\n for k in input:\n actual.append(find_all_ORFs(k))\n print input \n print actual\n print expected_output","def gene_finder(dna):\n threshold = longest_ORF_noncoding(dna, 1500)\n list_of_aminos = []\n list_of_ORFs = find_all_ORFs_both_strands(dna)\n for an_ORF in list_of_ORFs:\n if an_ORF > threshold:\n amino_acid_ORF = coding_strand_to_AA(an_ORF)\n list_of_aminos.append(amino_acid_ORF)\n return list_of_aminos","def longest_orf(seq):\n\n # Find possible start positions\n starts = seq_positions(seq, 'ATG')\n\n # Find possible end positions\n ends = seq_positions(seq, 'TGA') + seq_positions(seq, 'TAG') + seq_positions(seq, 'TAA')\n\n # Go through all starts and ends keeping track of longest orf\n orf = ''\n for start in starts:\n for end in ends:\n if start < end and (end - start) % 3 == 0:\n print(seq[start:end+3])\n if len(orf) < (end - start):\n orf = seq[start:end+3]\n break\n\n return orf","def gene_finder(dna):\n threshold = longest_ORF_noncoding(dna, 1500)\n orfs = find_all_ORFs_both_strands(dna)\n list1 = []\n for orf in orfs:\n if len(orf) > threshold:\n list1.append(coding_strand_to_AA(orf))\n return list1","def find_all_ORFs_unit_tests(dna, expected):\n \n print find_all_ORFs(\"ATGCATGAATGTAG\")\n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + find_all_ORFs(dna)","def rest_of_ORF(dna):\n STOP_CODONS=['TAG','TGA','TAA' ]#constants are uppercase\n for i in range(0,len(dna),3):\n codon=dna[i:i+3]\n if codon in STOP_CODONS:\n return dna[0:i]\n return dna","def read_FIREXAQ_files(path, folder='merge', var=''):\n df_list=[]\n flag_list=[]\n files2use = sorted(glob.glob(f'{path}/{folder}/*{var}*.ict'))\n for infileN, infile in enumerate( files2use ):\n with open(infile) as thefile:\n try:\n header= np.array([next(thefile) for x in range(90) ])\n except:\n continue\n start = header[6].replace(',',' ').split()\n start_date = datetime_( int( start[0] ),\n int( start[1] ),\n int( start[2] ))\n # Find where the header ends and values begin - manually narrowed down\n for nskip in range(675,680):\n try:\n fh = np.loadtxt(infile, skiprows=nskip, delimiter=',')\n break\n except:\n continue\n thefile = open(infile,'r')\n c = thefile.readlines()\n column_names = c[nskip-1].replace(' ','').split(',')\n df = pd.DataFrame(fh, index=fh[:,0], columns=column_names)\n\n # Use a different approach for\n if (var=='thru'):\n df = find_FIREXAQ_times(df, start_date, UseTimeStart=True)\n else:\n df = find_FIREXAQ_times(df, start_date, UseTimeStart=False)\n # Include the RF from the file name #\n # NOTE: research flight (RF) ID not included in filename or files,\n # so using filenumber instead. This will not work if reading\n # merge file (var = 'thru').\n df['FileNumber'] = infileN\n\n df_list.append(df)\n df = pd.concat(df_list)\n return df","def findGaps(sequence):\n patt = re.compile(r\"[Nn]+\")\n for match in patt.finditer(sequence):\n yield (match.start(), match.end())","def _read_frames(self):\n cap = self._read_file()\n\n frame_list = []\n ret_list = []\n\n while True:\n ret, frame = cap.read()\n if ret:\n frame_list.append(np.array(frame))\n ret_list.append(ret)\n else:\n break\n if self.mode==\"np\":\n frame_list = np.array(frame_list)\n return frame_list","def getFrames(job, **options):\n criteria = search.FrameSearch.criteriaFromOptions(**options)\n framesSeq = Cuebot.getStub('frame').GetFrames(\n job_pb2.FrameGetFramesRequest(job=job, r=criteria), timeout=Cuebot.Timeout).frames\n return [Frame(f) for f in framesSeq.frames]","def find_all_ORFs_both_strands(dna):\n both_strands_ORFs = []\n\n both_strands_ORFs.extend(find_all_ORFs(dna))\n both_strands_ORFs.extend(find_all_ORFs(get_reverse_complement(dna)))\n \n return both_strands_ORFs","def FrameGen(step, odb):\n # Just to inform the reader\n print(\"There are {} frames to read\".format(len(odb.steps[step].frames)))\n for i in odb.steps[step].frames:\n yield i","def find_all_ORFs_both_strands(dna):\n return find_all_ORFs(dna) + (find_all_ORFs(get_reverse_complement(dna)))","def rest_of_ORF(dna):\n index = -1\n dna_split = split_into_codons(dna)\n\n for i, j in enumerate(dna_split):\n if j == \"TAG\" or j == \"TGA\" or j == \"TAA\":\n index = i\n if index == -1:\n return ''.join(dna_split) # if there is no stop codon\n return ''.join(dna_split[:index])","def extractsequences(filename):\n\n yield (filename, 2, None)\n for m in re.finditer(r\"(?!0)[0-9]+\", filename):\n frameno = int(m.group())\n yield (makenonpaddedname(m), 0, frameno)\n for m in re.finditer(r\"[0-9]+\", filename):\n frameno = int(m.group())\n if m.end() - m.start() > 1:\n yield (makepaddedname(m), 1, frameno)","def find_first_orf(sequence,\n start_codons = ['AUG'],\n stop_codons = ['UAA', 'UAG', 'UGA']):\n \n # Make sure the sequence is valid\n vet_nucleotide_sequence(sequence)\n\n # Make sure the codons are valid\n for codon in start_codons:\n vet_codon(codon)\n for codon in stop_codons:\n vet_codon(codon)\n\n # Get copies of everything in uppercase\n seq = sequence.upper()\n starts = [c.upper() for c in start_codons]\n stops = [c.upper() for c in stop_codons]\n # Make sure seq is RNA\n seq = seq.replace('T', 'U')\n\n\n ##########################################################################\n # `orf_pattern_str` is a regular expression that will match an\n # open reading frame within a string of RNA bases. \n # Read the docstring above for additional clues.\n #I create variables as \"strings\" to take in start_codons & stop_codons \"lists\" so it can use them in the \"regex\"\n \n strt = '|'.join(start_codons) #takes the start codon provided and saves it as a string named 'strt'\n stp = '|'.join(stop_codons) #takes the stop codon provided and takes it as a string named 'stp'\n\n #here the `regex`\n orf_pattern_str = r'(' + strt +r')([AUCG]{3})*('+ stp +r')'\n #breakdown\n #the regex is in 3 groups\n #first group is the start codon\n # literarily it is 'AUG', but it is dynamic, and (' + strt +r') fixes that\n #the second group is ([AUGC]{3})* which captures zero or more sets of codon after the start codon\n #the last group is ((UAA)|(UAG)|(UGA)) dynamically captured as ('+ stp +r')\n ##########################################################################\n\n # Create the regular expression object\n orf_pattern = re.compile(orf_pattern_str)\n # Search the sequence\n match_object = orf_pattern.search(seq)\n if match_object:\n return match_object.group()\n return ''","def _find_all_top_level_non_gene_features(chrom: str, db: FeatureDB, feature_types: List[str]) -> Iterable[Feature]:\n for feature in db.region(seqid=chrom, featuretype=feature_types):\n try:\n _ = next(db.parents(feature.id))\n except StopIteration:\n yield feature","def find_all_ORFs_both_strands(dna):\n return find_all_ORFs(dna) + find_all_ORFs(get_reverse_complement(dna))","def find_all_ORFs_unit_tests():\n data_list = [\n [\"ATGCATGAATGTAG\", [\"ATGCATGAATGTAG\", \"ATGAATGTAG\", \"ATG\"]],\n [\"ATG\", [\"ATG\"]],\n [\"AATG\", [\"ATG\"]],\n [\"AAATG\", [\"ATG\"]],\n [\"ATGATG\", [\"ATGATG\"]],\n [\"ATATGGATTGA\", [\"ATGGAT\"]],\n [\"ATGAGATTAG\", [\"ATGAGATTAG\"]],\n [\"ATATGGATTAGTAGTAATGAAAGTATAG\", [\"ATGAAAGTA\", \"ATGGAT\", ]],\n# ATA TGG ATT AGT AGT AAT GAA AGT ATA G\n# TAT GGA TTA GTA GTA ATG AAA GTA TAG\n# ATG GAT TAG TAG TAA TGA AAG TAT AG\n [\"ATGTCACGCAATGTAGGATGGATGGATTAGAC\", [\"ATGTCACGCAATGTAGGATGGATGGAT\", \"ATG\", \"ATGGATGGATTAGAC\"]],\n# ATG TCA CGC AAT GTA GGA TGG ATG GAT TAG AC --> ATG TCA CGC AAT GTA GGA TGG ATG GAT\n# TGT CAC GCA ATG TAG GAT GGA TGG ATT AGA C\n# GTC ACG CAA TGT AGG ATG GAT GGA TTA GAC\n [\"ATGATGTAG\", [\"ATGATG\"]],\n [\"TCGATGC\", [\"ATGC\"]],\n [\"AAA\", []],\n# TCG ATG C\n# CGA TGC\n# GAT GC\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def longest_ORF_noncoding(dna, num_trials):\n longest_random_ORF = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# initialize empty list\n for i in range(num_trials):\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# repeats for num_trials\n \trandomized_dna = shuffle_string(dna)\t\t\t\t\t\t\t\t\t\t\t\t# finds strings of random dna\n \tlongest_random_ORF.append(longest_ORF(randomized_dna))\t\t\t\t\t\t\t\t# adds random dna to list\n\treturn max(longest_random_ORF, key=len)\t\t\t\t\t\t\t\t\t\t\t\t\t# returns longest dna string","def parse_frames(stream: BytesIO) -> Iterable[_Frame]:\n while True:\n old = stream.tell()\n try:\n yield _parse_frame(stream)\n except IncompleteData as exc:\n stream.seek(old)\n break","def longest_ORF_noncoding(dna, num_trials):\n count = 0\n orfs = []\n while count < num_trials:\n current_strand = shuffle_string(dna)\n longest_in_shuffle = longest_ORF(current_strand)\n orfs.append(longest_in_shuffle)\n count = count + 1\n longest = max(orfs, key=len)\n return len(longest)","def get_lidc_dataframes(data_path: str, num_sectors: int):\n sorted_studies = sorted(glob(os.path.join(data_path, \"*\")))\n frames = []\n for study in sorted_studies:\n df_temp = pd.read_csv(\n os.path.join(study, \"annotations.txt\"), sep=\": \", header=None, dtype=str\n )\n df_temp.columns = [\"File\", \"Label\"]\n df_temp[\"File\"] = df_temp[\"File\"].apply(lambda e: f\"{study}/{e}.png\")\n frames.append(df_temp)\n\n return [balance_frame(frame) for frame in slice_sector(frames, num_sectors)]","def iterframes(self):\n # self.check_ground_truth_availability()\n\n # Iterate through both poses and images, and construct frames\n # with look up table for filename str -> (timestamp, pose, annotation) \n for img_msg, frame in self.frame_index_.iteritems(): \n yield (frame.timestamp, img_msg, frame)","def find_frames(self, ftype, calib_ID=None, index=False):\n if 'framebit' not in self.keys():\n msgs.error('Frame types are not set. First run get_frame_types.')\n if ftype == 'None':\n return self['framebit'] == 0\n # Select frames\n indx = self.type_bitmask.flagged(self['framebit'], ftype)\n\n if calib_ID is not None:\n # Select frames in the same calibration group\n indx &= self.find_calib_group(calib_ID)\n\n # Return\n return np.where(indx)[0] if index else indx","def holes(self, test_pylos):\n availableholes = []\n for layer in range(1, 4):\n for row in range(4 - layer):\n for column in range(4 - layer):\n value = test_pylos.get(layer, row, column)\n if value is None:\n try:\n test_pylos.validPosition(layer, row, column)\n hole = [layer, row, column]\n except game.InvalidMoveException:\n pass\n else:\n availableholes.append(hole)\n return availableholes","def rest_of_ORF(dna): \n\n for i in range(3,len(dna)-2,3):\n \tstop_codon=dna[i:i+3]\n \tstart_codon=dna[:i]\n \tif stop_codon=='TAG' or stop_codon=='TAA' or stop_codon=='TGA':\n \t\treturn start_codon\n \t\tbreak\n \tif (i+3) >= len(dna)-2:\n \treturn dna","def rest_of_ORF(dna):\n num_codons = int(len(dna)/3)\n num = 0\n list_codons = []\n cut_dna = ''\n stop_index = -1\n while num < num_codons:\n num_start = int(num*3)\n num_end = int(num*3 + 3)\n list_codons.append(dna[num_start:num_end])\n num = num + 1\n for element in list_codons:\n if element == 'TAA' or element == 'TAG' or element == 'TGA':\n stop_index = list_codons.index(element)\n break\n\n if stop_index != -1:\n this_ORF = list_codons[0:stop_index]\n for element in this_ORF:\n cut_dna = cut_dna + element\n return cut_dna\n else:\n return dna","def find_all_ORFs_both_strands(dna):\n #inital conditions\n all_of_them = []\n\n #compute the all of the orfs in a DNA strand and the find their reverse complements\n #the return both of them in a list that includes all of the ORFS on both strands\n normal_ORFs = find_all_ORFs(dna)\n reverse_complement = get_reverse_complement(dna)\n reverse_ORFs = find_all_ORFs(reverse_complement)\n all_of_them = normal_ORFs + reverse_ORFs\n return all_of_them","def gene_finder(dna):\n #use longest_ORF_noncoding to determine what the longest strand of DNA could be in a random sequence\n threshold = longest_ORF_noncoding(dna,1500)\n\n #find all of the orfs on both strand and the generate an empty list\n all_orfs = find_all_ORFs_both_strands(dna)\n all_orfs_long = []\n\n #this makes a list of strings of dna that are longer than the threshold\n\n for i in range (0, len(all_orfs)):\n if len(all_orfs[i]) > threshold:\n all_orfs_long.append(all_orfs[i])\n\n #this takes each dna string in a list and converts it to an amino acid sequence\n\n aa_list = []\n\n for i in range (0, len(all_orfs_long)):\n aa_strand = coding_strand_to_AA(all_orfs_long[i])\n aa_list.append(aa_strand)\n\n #returns strings of amino acids\n return aa_list","def find_surrounding_frames(frame, frames_with):\n # If frame is missing from the beginning, return initial frame twice.\n if (frame < frames_with[0]):\n return frames_with[0], frames_with[0], frames_with[0] - frame\n # If frame is missing from the end, return last frame twice.\n elif (frame > frames_with[-1]):\n return frames_with[-1], frames_with[-1], frame - frames_with[-1]\n # If frame is missing in the middle, return surrounding frames.\n else:\n for i in range(1, len(frames_with)):\n frame_before = frames_with[i-1]\n frame_after = frames_with[i]\n if (frame > frame_before and frame < frame_after):\n return frame_before, frame_after, frame_after - frame_before - 1","def prune_decoded_seqs(seqs):\r\n out = []\r\n for s in seqs:\r\n if EOS in s:\r\n idx = s.index(EOS)\r\n out += [s[:idx]]\r\n else:\r\n out += [s]\r\n return out","def gene_finder(dna):\n viable_strings = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitialize empty list (for strings)\n viable_amino_acids = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitialize empty list (for amino acids)\n threshold = longest_ORF_noncoding(dna, 1500)\t\t\t\t\t\t\t\t\t\t\t# sets threshold to longest random dna string\n real_dna = list(find_all_ORFs_both_strands(dna))\t\t\t\t\t\t\t\t\t\t# sets real_dna equal to all the ORFs, both strands\n for i in range(len(real_dna)):\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# searches through all the elements in list real_dna\n \tif len(real_dna[i]) > len(threshold):\t\t\t\t\t\t\t\t\t\t\t\t# compares real string to random string\n \t\tviable_strings.append(real_dna[i])\t\t\t\t\t\t\t\t\t\t\t\t# if real string is longer, adds it to list\n for i in range(len(viable_strings)):\t\t\t\t\t\t\t\t\t\t\t\t\t# searches through all elements in viable_strings\n \ta = coding_strand_to_AA(viable_strings[i])\t\t\t\t\t\t\t\t\t\t\t# translates each string to amino acid sequence\n \tviable_amino_acids.append(a)\t\t\t\t\t\t\t\t\t\t\t\t\t\t# adds amino acids to list\n return viable_amino_acids\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns list","def rest_of_ORF(dna):\n\t# TODO: implement this\n\tindex = 0\n\twhile index < len(dna):\n\t\tcodon = dna[index:index + 3]\t\t\t\t\t\t\t\t\t\t\t\t\t\t# groups 3 nucleotides to make codon, index by 3\n\t\tif codon in [\"TAA\", \"TAG\", \"TGA\"]:\t\t\t\t\t\t\t\t\t\t\t\t\t# checks if stop codon is in string\n\t\t\treturn dna[:index]\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if True, returns string up to stop codon\n\t\tindex += 3\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# indexes by 3\n\treturn dna","def extract_seqrecords_from_gff3_fasta(gff3_with_fasta_handle: TextIO) -> List[SeqRecord]:\n # first, find the header\n fasta_found = False\n for row in gff3_with_fasta_handle:\n if row.rstrip() == GFF3Headers.FASTA_HEADER.value:\n fasta_found = True\n break\n\n if fasta_found is False:\n raise GFF3FastaException(\"Did not find FASTA header in the GFF3 file.\")\n\n data = StringIO(gff3_with_fasta_handle.read())\n recs = list(SeqIO.parse(data, format=\"fasta\"))\n return recs","def get_frames(gif: Image.Image) -> List[Image.Image]:\n last_frame = None\n all_frames = []\n i = 0\n try:\n while True:\n gif.seek(i)\n new_frame = gif.convert('RGBA')\n if last_frame is not None and gif.disposal_method == 1:\n updated = new_frame.crop(gif.dispose_extent)\n last_frame.paste(updated, gif.dispose_extent, updated)\n new_frame = last_frame\n else:\n last_frame = new_frame\n\n # do resizing on new_frame here...\n\n all_frames.append(new_frame.copy())\n i += 1\n except EOFError:\n gif.seek(0)\n\n return all_frames","def find_all_ORFs_both_strands(dna):\n # TODO: implement this\n all_ORFs_both_strands = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# initialize empty list\n all_ORFs_both_strands = all_ORFs_both_strands + find_all_ORFs(dna)\t\t\t\t\t\t# adds all ORFs one strand to list\n reverse_complement_dna = get_reverse_complement(dna)\t\t\t\t\t\t\t\t\t# finds 2nd strand\n all_ORFs_both_strands = all_ORFs_both_strands + find_all_ORFs(reverse_complement_dna)\t# finds all ORFs second strand\n return all_ORFs_both_strands \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns all ORFs both strands","def rest_of_ORF(dna):\n \n if dna[:3]== \"TAG\" or dna[:3]==\"TAA\" or dna[:3]==\"TGA\" or len(dna)<3:\n return \"\"\n if len(dna)<=3:\n return dna\n return dna[:3]+rest_of_ORF(dna[3:])","def fgetl_nocom(fid):\n l = fgetl(fid)\n while max(l.shape) > 0 & l[0] == '#':\n\n l = fgetl(fid)\n\n #\n return l","def find_all_ORFs_both_strands(dna):\n \n # YOUR IMPLEMENTATION HERE","def longest_ORF(dna):\n i = 0\n both_ORFs = find_all_ORFs_both_strands(dna)\n longest = both_ORFs[0]\n while i + 1 < len(both_ORFs):\n if len(both_ORFs[i+1]) > len(longest):\n longest = both_ORFs[i+1]\n i+=1\n return longest","def prune_decoded_seqs(seqs):\n out = []\n for s in seqs:\n if constant.EOS in s:\n idx = s.index(constant.EOS_TOKEN)\n out += [s[:idx]]\n else:\n out += [s]\n return out","def longestorf(args):\n p = OptionParser(longestorf.__doc__)\n p.add_option(\"--ids\", action=\"store_true\", help=\"Generate table with ORF info\")\n opts, args = p.parse_args(args)\n\n if len(args) != 1:\n sys.exit(not p.print_help())\n\n (fastafile,) = args\n pf = fastafile.rsplit(\".\", 1)[0]\n orffile = pf + \".orf.fasta\"\n idsfile = None\n if opts.ids:\n idsfile = pf + \".orf.ids\"\n fwids = open(idsfile, \"w\")\n\n f = Fasta(fastafile, lazy=True)\n fw = must_open(orffile, \"w\")\n before, after = 0, 0\n for name, rec in f.iteritems_ordered():\n cds = rec.seq\n before += len(cds)\n # Try all six frames\n orf = ORFFinder(cds)\n lorf = orf.get_longest_orf()\n newcds = Seq(lorf)\n after += len(newcds)\n newrec = SeqRecord(newcds, id=name, description=rec.description)\n SeqIO.write([newrec], fw, \"fasta\")\n if idsfile:\n print(\"\\t\".join((name, orf.info)), file=fwids)\n\n fw.close()\n if idsfile:\n fwids.close()\n\n logging.debug(\n \"Longest ORFs written to `{0}` ({1}).\".format(\n orffile, percentage(after, before)\n )\n )\n\n return orffile","def find_frame_files(self, ftype, calib_ID=None):\n return self.frame_paths(self.find_frames(ftype, calib_ID=calib_ID))","def split_frames(flat):\n \n frames = [[]]\n for expr in flat:\n # A new frame starts with a .loc expression.\n if type(expr) == Raw and expr.expr[:4] == '.loc':\n frames.append([expr])\n else:\n frames[-1].append(expr)\n return frames","def getFrameList(self):\n with self.frameLock:\n return list(self.frameList)","def find_all_ORFs_both_strands(dna):\n return find_all_ORFs(dna)+find_all_ORFs(get_reverse_complement(dna))\n \n \n # YOUR IMPLEMENTATION HERE","def get_issues(fasta,\n gff,\n feature_format=CDS_FEATURE_FORMAT,\n use_feature_name=False,\n start_codons=[START_CODON]):\n for f in [fasta, gff]:\n if not os.path.exists(f) or (not os.path.isfile(f)):\n raise FileNotFoundError(f)\n try:\n gffdb = gffutils.create_db(gff,\n dbfn='gff.db',\n force=True,\n keep_order=True,\n merge_strategy='merge',\n sort_attribute_values=True)\n except ValueError as e:\n # Wrap and rethrow exception so file name is included\n raise ValueError(\"{} ({})\".format(e, gff)) from e\n issues = []\n # Track IDs of features encountered. Each ID must be unique within\n # a GFF file. See http://gmod.org/wiki/GFF3.\n feature_ids = {}\n # Track sequences encountered and counts of features for\n # each.\n sequence_features = {}\n fasta_genes = Fasta(fasta)\n for feature in gffdb.features_of_type('CDS'):\n if feature.seqid not in sequence_features:\n sequence_features[feature.seqid] = 0\n sequence_features[feature.seqid] += 1\n\n feature_id = None\n if \"ID\" in feature.attributes:\n feature_id = feature.attributes[\"ID\"][0].strip()\n if feature_id in feature_ids:\n feature_ids[feature_id].append(feature.seqid)\n else:\n feature_ids[feature_id] = [feature.seqid]\n feature_id_name = get_feature_id(feature, use_feature_name)\n if feature_id_name is None:\n feature_id_name = feature_format.format(feature.seqid)\n issues.append((feature.seqid, feature_id_name,\n NO_ID_NAME, None))\n try:\n sequence = feature.sequence(fasta_genes)\n except KeyError as e: # Missing sequence.\n issues.append((feature.seqid,\n NOT_APPLICABLE,\n SEQUENCE_NOT_IN_FASTA,\n None))\n continue\n except FastaIndexingError as e:\n raise e\n except Exception as e:\n warnings.warn(str(e))\n continue\n seq_len_remainder = len(sequence) % 3\n if seq_len_remainder != 0:\n issues.append((feature.seqid, feature_id_name,\n INCOMPLETE_FEATURE, None))\n sequence += (\"N\" * (3 - seq_len_remainder))\n\n sequence_codons = sequence_to_codons(sequence)\n if sequence_codons[0] not in start_codons:\n issues.append((feature.seqid, feature_id_name,\n NO_START_CODON, sequence_codons[0]))\n if not sequence_codons[-1] in STOP_CODONS:\n issues.append((feature.seqid, feature_id_name,\n NO_STOP_CODON, sequence_codons[-1]))\n if any([codon in STOP_CODONS\n for codon in sequence_codons[:-1]]):\n issues.append((feature.seqid, feature_id_name,\n INTERNAL_STOP_CODON, None))\n\n for sequence, count in list(sequence_features.items()):\n if count > 1:\n # Insert issue, respect ordering by sequence ID.\n bisect.insort(issues, (sequence, WILDCARD, MULTIPLE_CDS, count))\n\n for feature_id, seq_ids in feature_ids.items():\n if len(seq_ids) > 1:\n issues.append((WILDCARD, feature_id,\n DUPLICATE_FEATURE_IDS, len(seq_ids)))\n for seq_id in seq_ids:\n # Insert issue, respect ordering by sequence ID.\n bisect.insort(issues, (seq_id, feature_id,\n DUPLICATE_FEATURE_ID, None))\n\n gff_seq_ids = set(sequence_features.keys())\n fasta_seq_ids = get_fasta_sequence_ids(fasta)\n fasta_only_seq_ids = fasta_seq_ids - gff_seq_ids\n for seq_id in fasta_only_seq_ids:\n issues.append((seq_id, NOT_APPLICABLE, SEQUENCE_NOT_IN_GFF, None))\n num_sequences = len(fasta_seq_ids)\n num_features = len(list(gffdb.all_features()))\n num_cds_features = len(list(gffdb.features_of_type('CDS')))\n return num_sequences, num_features, num_cds_features, issues","def longest_ORF_noncoding(dna, num_trials):\n org = list(dna)\n max_len = 0\n r = \"\"\n for i in range(num_trials):\n l = org\n shuffle(l)\n orf = longest_ORF(collapse(l))\n if len(orf) > max_len:\n r = orf\n max_len = len(orf)\n return r","def load_data(data_path, sequence_length, no_sequences=None):\n frames_available = 0\n # load everything in the folder\n all_data = False\n for root, dirs, files in os.walk(data_path):\n for one_file in files:\n if one_file.split(\".\")[-1] != 'npy':\n write_to_summary(f\"Skipping {root}/{one_file}\", print_red=True)\n continue\n write_to_summary(f\"Loading from:{root}/{one_file}\")\n file_path = os.path.join(root, one_file)\n if all_data is False:\n all_data = load_blob(file_path)\n frames_available += all_data.shape[0]\n else:\n more_data = load_blob(file_path)\n all_data = np.concatenate((all_data, more_data), axis=0)\n frames_available += more_data.shape[0]\n # Add 10 sequences in case some are discarded for damaged frames\n if no_sequences is not None and frames_available // sequence_length > no_sequences + 10:\n break\n if all_data is False:\n return (False,False)\n # First we check the average, and see if there are any frames to discard\n average_pixel_count = [np.sum(frame) for frame in all_data]\n average_pixel_count = np.mean(average_pixel_count)\n write_to_summary(f\"Average pixel count:{average_pixel_count}\")\n skip_limit = DISCARD_CONSTANT * average_pixel_count\n write_to_summary(f\"Pixel count skip limit:{skip_limit}\")\n skip_indexes = []\n index_counter = 0\n for frame in all_data:\n if np.sum(frame) > skip_limit:\n skip_indexes.append(index_counter)\n index_counter += 1\n write_to_summary(f\"{len(skip_indexes)} frames have a pixel count exceding the threshold:\")\n write_to_summary(skip_indexes)\n\n # Generate all indicies that will produce data\n # and use that to filter out the ones with damaged frame in them \n indicies_pairs = []\n frame_counter = 0\n while frame_counter + sequence_length + 1 < frames_available:\n all_valid_frames = True\n for damaged_frames in skip_indexes:\n if damaged_frames >= frame_counter and damaged_frames <= frame_counter + sequence_length + 1:\n all_valid_frames = False\n break\n pair = (frame_counter, frame_counter + sequence_length + 1)\n if not all_valid_frames:\n write_to_summary(f\"{pair} skipped because of damaged frame\", print_red=True)\n else:\n indicies_pairs.append(pair)\n frame_counter += sequence_length + 1\n write_to_summary(f\"{len(indicies_pairs)} valid sequences available, target is {no_sequences}\")\n\n # Check how many sequences we will get\n # final_no_sequences = frames_available // sequence_length\n final_no_sequences = len(indicies_pairs)\n if no_sequences is not None and final_no_sequences > no_sequences:\n final_no_sequences = no_sequences\n # Discard the ones we dont need\n indicies_pairs = indicies_pairs[:final_no_sequences]\n img_width = all_data.shape[1]\n img_height = all_data.shape[2]\n # -1 in sequence_length becasue the final frame is in the ground truth, no wait skip that\n # better to use sequence_length + 1 for y_train, makes more sense\n x_train = np.zeros((final_no_sequences, sequence_length, img_width, img_height, 1))\n y_train = np.zeros((final_no_sequences, 1, img_width, img_height, 1))\n current_sequence = 0\n for start_frame, end_frame in indicies_pairs:\n training_frames = all_data[start_frame: start_frame + sequence_length]\n truth_frame = all_data[start_frame + sequence_length: end_frame]\n x_train[current_sequence] = np.expand_dims(training_frames, axis=3)\n y_train[current_sequence] = np.expand_dims(truth_frame, axis=3)\n current_sequence += 1\n # No validation for now\n write_to_summary(f\"Loaded {len(x_train)} sequences of length {sequence_length}!\")\n return (x_train, y_train)"],"string":"[\n \"def find_all_ORFs(dna):\\n index = 0\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# initialize index\\n all_ORFs = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitalize empty list\\n while index < 3:\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# switches throught the 3 frames\\n \\tall_ORFs = all_ORFs + find_all_ORFs_oneframe(dna[index:])\\t# adds all ORFs oneframe to the list\\n \\tindex += 1\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# indexes +1\\n return all_ORFs \\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns list of all ORFs in all 3 frames\",\n \"def find_all_ORFs(dna):\\n all_ORFs=[]\\n for i in range (0,3):\\n \\tframe=dna[i:] \\n all_ORFs+=find_all_ORFs_oneframe(frame)\\n return all_ORFs\",\n \"def find_all_ORFs(dna):\\n first_frame = find_all_ORFs_oneframe(dna[0:])\\n second_frame = find_all_ORFs_oneframe(dna[1:])\\n third_frame = find_all_ORFs_oneframe(dna[2:])\\n list_of_frames = first_frame + second_frame + third_frame\\n return list_of_frames\",\n \"def find_all_ORFs(dna):\\n all_ORFs = []\\n for i in range(0, 3):\\n dna_new = dna[i:]\\n all_ORFs += find_all_ORFs_oneframe(dna_new)\\n return all_ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n condition = 1\\n dna2 = dna\\n list_of_ORFs = []\\n while condition == 1:\\n num_codons = int(len(dna2)/3)\\n num = 0\\n list_codons = []\\n start_index = -1\\n while num < num_codons:\\n num_start = int(num*3)\\n num_end = int(num*3 + 3)\\n list_codons.append(dna2[num_start:num_end])\\n num = num + 1\\n for element in list_codons:\\n if element == 'ATG':\\n start_index = list_codons.index(element)\\n break\\n if start_index != -1:\\n this_orf = rest_of_ORF(dna2[start_index*3:])\\n list_of_ORFs.append(this_orf)\\n dna2 = dna2[start_index*3+len(this_orf)+3:]\\n else:\\n condition = 2\\n\\n return list_of_ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n \\n\\n ORFs=[]\\n i=0\\n while i<len(dna):\\n if dna[i:i+3]==\\\"ATG\\\":\\n j=i\\n dna2=rest_of_ORF(dna[j:])\\n \\n if dna2==None:\\n \\tbreak\\n ORFs.append(dna2)\\n i=i+len(dna2)\\n i=i+3\\n return ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n dna_split = split_into_codons(dna)\\n i = 0\\n all_ORFs_oneframe = []\\n length_of_orf = 0\\n while i < len(dna_split):\\n if dna_split[i] == \\\"ATG\\\":\\n orf = rest_of_ORF(dna[int(i)*3:])\\n all_ORFs_oneframe += [orf]\\n length_of_orf = math.ceil(len(orf)/3)\\n i += length_of_orf\\n else:\\n i += 1\\n return all_ORFs_oneframe\",\n \"def find_all_ORFs_oneframe(dna):\\n\\n ORFlist = []\\n i = 0\\n lend = len(dna)\\n while i < lend:\\n codon = dna[i:i+3]\\n if codon == 'ATG':\\n orf = rest_of_ORF(dna[i:])\\n ORFlist.append(orf)\\n i = i + len(orf)\\n else:\\n i = i+3\\n return ORFlist\",\n \"def find_all_ORFs(dna):\\n ORFs = find_all_ORFs_oneframe(dna) + find_all_ORFs_oneframe(dna[1:]) + find_all_ORFs_oneframe(dna[2:])\\n\\n return ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n i=0 \\n ORF_list = []\\n while i<len(dna):\\n if dna[i : i+3] == \\\"ATG\\\":\\n start_place = i \\n current_ORF = rest_of_ORF(dna[start_place:])\\n i += 3 + len(current_ORF)\\n ORF_list.append(current_ORF) \\n return ORF_list\",\n \"def find_all_ORFs_oneframe(dna):\\n x = 3\\n list_of_dna = []\\n while (x < len(dna)):\\n if dna[x-3:x] == 'ATG':\\n current_dna = rest_of_ORF(dna[x-3:])\\n list_of_dna.append(current_dna)\\n x += len(current_dna)\\n x += 3\\n return list_of_dna\",\n \"def find_all_ORFs(dna):\\n dnatwo = dna[1:]\\n dnathree = dna[2:]\\n all_ORFs = find_all_ORFs_oneframe(dna)\\n all_ORFs.extend(find_all_ORFs_oneframe(dnatwo))\\n all_ORFs.extend(find_all_ORFs_oneframe(dnathree))\\n if [] in all_ORFs:\\n all_ORFs.remove([])\\n return all_ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n\\tindex = 0\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# unitiate index at 0\\n\\tsegment = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitializes empty list\\n\\twhile index < len(dna):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# given that index is smaller than length of string\\n\\t\\tcodon = dna[index:index + 3]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# creates codons from nucleotides starting with first 3 letters\\n\\t\\tif codon == \\\"ATG\\\":\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if the codon is ATG\\n\\t\\t\\tsegment.append(rest_of_ORF(dna[index:]))\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# run rest_of_ORF starting at index\\n\\t\\t\\tindex = index + len(rest_of_ORF(dna[index:]))\\t\\t\\t\\t\\t\\t\\t\\t\\t# new index starting at old + length of ORF output string\\n\\t\\telse:\\n\\t\\t\\tindex += 3\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if ATG isn't found, move to next codon and check again\\n\\n\\treturn segment\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns list of ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n i = 0\\n list_ORF = []\\n\\n def search_ORF(dna,i):\\n aa = dna[3*i:(3*i)+3]\\n if aa == 'ATG':\\n list_ORF.append(rest_of_ORF(dna,aa,i))\\n i = i + 1 + len(rest_of_ORF(dna,aa,i))/3\\n else:\\n i = i + 1\\n if len(aa) ==3:\\n search_ORF(dna,i)\\n \\n return list_ORF\\n\\n return search_ORF(dna,i)\\n # i = i + ((len(list_ORF[-1]))/3)\\n # search_ORF(dna,i)\",\n \"def find_all_ORFs(dna):\\n res = []\\n for i in range(0, 3):\\n s = dna[i:]\\n# print i, s,\\n# l = len(s)\\n# for j in range(0, l, 3):\\n# if s[j: j + 3] == start_codon:\\n# r = find_all_ORFs_oneframe(s[j:])\\n# print r\\n# if len(r) > 0:\\n# for item in r:\\n# res.append(item)\\n# break # careful for indentation here!!\\n r = find_all_ORFs_oneframe(s)\\n if len(r) > 0:\\n# for item in r:\\n# res.append(item)\\n res += r # [WOW] I love python!\\n return res\",\n \"def find_all_ORFs(dna):\\n ans = find_all_ORFs_oneframe(dna)\\n ans.extend(find_all_ORFs_oneframe(dna[1:]))\\n ans.extend(find_all_ORFs_oneframe(dna[2:]))\\n return ans\",\n \"def find_all_ORFs(dna):\\n all_ORFs = []\\n i = 0\\n\\n for i in range (0,3): \\n all_ORFs.extend(find_all_ORFs_oneframe(dna))\\n dna = 'X' + dna\\n\\n return all_ORFs\",\n \"def find_all_ORFs(dna):\\n\\n readingFrame0 = ''\\n readingFrame1 = ''\\n readingFrame2 = ''\\n output = ''\\n for k in range(0,3): \\n if k ==0: \\n readingFrame0 = find_all_ORFs_oneframe(dna[k:])\\n elif k ==1: \\n readingFrame1 = find_all_ORFs_oneframe(dna[k:])\\n elif k ==2:\\n readingFrame2 = find_all_ORFs_oneframe(dna[k:])\\n print 'Reading Frame 1: ' + str(readingFrame0) + ', Reading Frame 2: ' + str(readingFrame1) + ', Reading Frame 3: ' + str(readingFrame2)\\n output = readingFrame0 + readingFrame1 + readingFrame2\\n return output\",\n \"def find_all_ORFs_oneframe(dna):\",\n \"def find_all_ORFs(dna):\\n #these functions offset to analyze each each open frame reference\\n zero_offset=find_all_ORFs_oneframe(dna[0:])\\n \\n one_offset=find_all_ORFs_oneframe(dna[1:])\\n \\n two_offset=find_all_ORFs_oneframe(dna[2:])\\n \\n return zero_offset+one_offset+two_offset\\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs_oneframe(dna):\\n #inital conditions\\n i = 0\\n start_codon = ('ATG')\\n end_index = len(dna)\\n return_variable = []\\n\\n #for each codon in the set of DNA, check if it is a start codon\\n #if it is a start codon, add the string until the stop codon to a list\\n #then continue running\\n while i < len(dna)-2:\\n codon = dna[i:i+3] \\n if codon in start_codon:\\n orf = rest_of_ORF(dna[i:])\\n return_variable.append(orf)\\n i += len(orf)\\n i += 3\\n\\n\\n #return a list of strings of DNA\\n return return_variable\",\n \"def find_all_ORFs(dna):\\n #inital conditions\\n i = 0\\n start_codon = ('ATG')\\n end_index = len(dna)\\n return_variable = []\\n\\n #for statement tells the code to run three times at three inital index values\\n #0,1,and 2 which allows for each reading frame to be read\\n for i in range (3):\\n while i < (len(dna)-2):\\n codon = dna[i:i+3] \\n if codon in start_codon: #check if the codon the code is looking at is a start codon\\n orf = rest_of_ORF(dna[i:]) #then determine that this is an orf, make it a string given the index of the start codon\\n return_variable.append(orf) #and append said string to a list of ORFs\\n i += len(orf) \\n i += 3\\n #return a list of strings of DNA from both strands\\n return return_variable\",\n \"def find_all_ORFs_oneframe(dna):\\n strand = []\\n startCodon = [\\\"ATG\\\"]\\n for i in range(0,len(dna),3):\\n triple = dna[i:i+3]\\n if triple in startCodon: \\n strand.append(rest_of_ORF(dna[i:]))\\n print strand\\n return strand\",\n \"def ORFs(self):\\n ORFStart = None\\n openLeft = True\\n seenStart = False\\n\\n for index, residue in enumerate(self.sequence):\\n if residue == 'M':\\n # Start codon.\\n openLeft = False\\n seenStart = True\\n elif residue == '*':\\n # Stop codon. Yield an ORF, if it has non-zero length.\\n if ORFStart is not None and index - ORFStart > 0:\\n # The ORF has non-zero length.\\n yield AAReadORF(self, ORFStart, index, openLeft, False)\\n ORFStart = None\\n # After a stop codon, we can no longer be open on the left\\n # and we have no longer seen a start codon.\\n openLeft = seenStart = False\\n else:\\n if (seenStart or openLeft) and ORFStart is None:\\n ORFStart = index\\n\\n # End of sequence. Yield the final ORF if there is one and it has\\n # non-zero length.\\n length = len(self.sequence)\\n if ((seenStart or openLeft) and ORFStart is not None and\\n length - ORFStart > 0):\\n yield AAReadORF(self, ORFStart, length, openLeft, True)\",\n \"def rest_of_ORF(dna):\\n readingFrame = ''\\n endCodons = [\\\"TAG\\\", \\\"TAA\\\", \\\"TGA\\\"]\\n for i in range(0,len(dna),3):\\n triple = dna[i:i+3]\\n if triple in endCodons:\\n readingFrame = readingFrame\\n break\\n else: \\n readingFrame+=triple \\n return readingFrame\",\n \"def find_all_ORFs_oneframe_unit_tests(dna, expected):\\n\\n print find_all_ORFs_oneframe(\\\"ATGCATGAATGTAGATAGATGTGCCC\\\")\\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + find_all_ORFs_oneframe(dna)\",\n \"def find_longest_orfs(seq,n_orfs):\\n\\n # Make sure there is a start codon in the sequence:\\n if not 'ATG' in seq:\\n raise RuntimeError(\\\"Your DNA sequence doesn't have a start codon.\\\")\\n\\n # Initialize orfs list:\\n orfs =[]\\n\\n # Loop over sequence and find ORFs:\\n for i, base in enumerate(seq):\\n triplet = seq[i:i+3]\\n if triplet == 'ATG':\\n orf_seq = ''\\n aa_seq = ''\\n j = i\\n while j+2 < len(seq):\\n codon = seq[j:j+3]\\n orf_seq += codon\\n if bioinfo_dicts.codons[codon] == '*': # if stop codon\\n orf_len = len(orf_seq)\\n orfs.append((orf_len,orf_seq,aa_seq)) # j is orf len in nts\\n break # this only breaks out of while loop, right?\\n else:\\n aa_seq += bioinfo_dicts.codons[codon]\\n j+=3\\n\\n # Sort orf list by length\\n orfs.sort()\\n\\n # Select n longest orfs to return:\\n number = -(n_orfs+1)\\n longest_orfs = orfs[:number:-1]\\n\\n longest_orfs = tuple(longest_orfs)\\n return longest_orfs\",\n \"def get_open_issues(self, owners: List[str]) -> List[EventRecord]:\\n with self.session.begin() as session:\\n open_issues = (\\n session.query(EventRecord)\\n .filter(EventRecord.owner.in_(owners))\\n .filter(EventRecord.received_at >= datetime.utcnow() - timedelta(days=1))\\n .all()\\n )\\n\\n open_issues = remove_duplicate_events(open_issues)\\n\\n open_issues_fps = [issue.fingerprint for issue in open_issues]\\n\\n ignored_issues_fps_tuples = (\\n session.query(IgnoreFingerprintRecord.fingerprint)\\n .filter(IgnoreFingerprintRecord.fingerprint.in_(open_issues_fps))\\n .filter(\\n (IgnoreFingerprintRecord.expires_at > datetime.utcnow())\\n | (IgnoreFingerprintRecord.expires_at.is_(None))\\n )\\n .all()\\n )\\n\\n ignored_issues_fps = [t[0] for t in ignored_issues_fps_tuples]\\n\\n return [issue for issue in open_issues if issue.fingerprint not in ignored_issues_fps]\",\n \"def reading_frames(dna):\\n #the 6 types are as follows\\n # the actual string and the reverse complement\\n list = []\\n #this is the actual string\\n list.append(dna)\\n #this is the reverse complement of the string\\n # done reusing the fastcomplement() method that was already available.\\n #others are done likewise\\n list.append(fast_complement(dna[::-1]))\\n list.append(dna[1:len(dna)])\\n list.append(fast_complement(dna[1:len(dna)][::-1]))\\n list.append(dna[2:len(dna)])\\n list.append(fast_complement(dna[2:len(dna)][::-1]))\\n return list\",\n \"def getouterframes(frame, context=1):\\r\\n framelist = []\\r\\n while frame:\\r\\n framelist.append((frame,) + getframeinfo(frame, context))\\r\\n frame = frame.f_back\\r\\n return framelist\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n\\n input = [\\\"dna\\\"]\\n expected_output = [\\\"all non-nester ORFs\\\"]\\n actual = []\\n for k in input:\\n actual.append(find_all_ORFs_oneframe(k))\\n print input \\n print actual\\n print expected_output\",\n \"def get_open_cells(field: MineField, cell: Cell) -> List[Cell]:\\n # TODO re-implement iteratively to safe stack space (especially for large boards)\\n if cell.is_flag or cell.is_mine or not field.cell_is_safe(cell):\\n return [cell]\\n \\n if cell.visited:\\n return\\n\\n open_cells: list = list()\\n cell.visited = True\\n open_cells.append(cell)\\n\\n for cell in field.surrounding_cells(cell):\\n open_cells.append(cell)\\n if cell.is_flag or cell.visited or not field.cell_is_safe(cell):\\n continue\\n\\n\\n open_cells += get_open_cells(field, cell)\\n\\n return open_cells\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n data_list = [\\n [\\\"ATGCATGAATGTAGATAGATGTGCCC\\\", [\\\"ATGCATGAATGTAGA\\\", \\\"ATGTGCCC\\\"]],\\n [\\\"ATGTAGATGTAG\\\", [\\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGATGATG\\\", [\\\"ATGATGATG\\\"]],\\n [\\\"ATGGGGGATTAGATGATG\\\", [\\\"ATGGGGGAT\\\", \\\"ATGATG\\\"]],\\n [\\\"ATGTGAATGTAA\\\", [\\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGTGAATGTAAATG\\\", [\\\"ATG\\\", \\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGCGTGGTGATTAGATGGATGGGGATTGA\\\", [\\\"ATGCGTGGTGAT\\\", \\\"ATGGATGGGGAT\\\"]],\\n [\\\"ATGAAATTTCCCGGGAAATTTCCCGGG\\\", [\\\"ATGAAATTTCCCGGGAAATTTCCCGGG\\\"]],\\n [\\\"ATGAAATTTTGAATGGGGCCC\\\", [\\\"ATGAAATTT\\\", \\\"ATGGGGCCC\\\"]],\\n [\\\"ATGAAATTTTGAATGGGGCCCTAG\\\", [\\\"ATGAAATTT\\\", \\\"ATGGGGCCC\\\"]],\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\",\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = find_all_ORFs_oneframe(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def find_all_ORFs_both_strands(dna):\\n orfs = []\\n orfs = find_all_ORFs(dna) + find_all_ORFs(get_reverse_complement(dna))\\n return orfs\",\n \"def longest_ORF(dna):\\n\\n reverseComp = get_reverse_complement(dna)\\n openFramesfromReverse = find_all_ORFs(reverseComp)\\n openFramesfromNormal = find_all_ORFs(dna)\\n all_ORFs = openFramesfromNormal + openFramesfromReverse\\n longest = max(all_ORFs, key=len)\\n return longest\",\n \"def longest_ORF(dna):\\n \\n all_ORFs = find_all_ORFs_both_strands(dna)\\n\\n if len(all_ORFs) > 0:\\n return max(all_ORFs, key = len)\\n else:\\n return []\",\n \"def find_all_ORFs_oneframe(dna): \\n i=0\\n multiple_list=[]\\n while i < len(dna):\\n part = dna[i:i+3]\\n if part == 'ATG': #if the first indecied are ATG then it runs the code that creates the string of DNA\\n ORF=rest_of_ORF(dna[i:]) \\n multiple_list.append(ORF)\\n i+=len(ORF)\\n else:\\n i+=3\\n # print multiple_list\\n return multiple_list\\n \\n #runs fuinction to mmake list of function\\n #need to save to list\\n #need to continue to next ATG start \\n #need to add that to list\\n #need to output new list as commas between lists\",\n \"def find_all_ORFs(dna):\\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def gene_finder(dna):\\n orfs = find_all_ORFs_both_strands(dna)\\n print(orfs)\\n threshold = longest_ORF_noncoding(dna, 1000)\\n print('threshold is', threshold)\\n print('number of orfs:', len(orfs))\\n aa_sequences = []\\n i = 0\\n while i < len(orfs):\\n print(len(orfs[i]))\\n if len(orfs[i]) > threshold:\\n print('if')\\n aa_sequences += [coding_strand_to_AA(orfs[i])]\\n i += 1\\n print(aa_sequences)\",\n \"def get_orfs(genome, min_num_aa):\\n allowed = \\\"ATGC\\\"\\n if not isinstance(genome, str) or len(genome) == 0 or not all(c in allowed for c in genome):\\n raise TypeError\\n start_codon = \\\"ATG\\\"\\n stop_codon = ['TAA', 'TAG', 'TGA']\\n ref_dict = {\\\"T\\\" : \\\"A\\\", \\\"A\\\" : \\\"T\\\", \\\"G\\\" : \\\"C\\\", \\\"C\\\" : \\\"G\\\"}\\n amino_dict = {\\n 'L' : ['CTC', 'CTT', 'CTA', 'CTG', 'TTA', 'TTG'],\\n 'S' : ['TCA', 'TCT', 'TCC', 'TCG', 'AGC', 'AGT'],\\n 'R' : ['CGA', 'CGC', 'CGT', 'CGG', 'AGA', 'AGG'],\\n 'V' : ['GTA', 'GTG', 'GTC', 'GTT'],\\n 'P' : ['CCC', 'CCA', 'CCG', 'CCT'],\\n 'T' : ['ACC', 'ACG', 'ACT', 'ACA'],\\n 'A' : ['GCA', 'GCC', 'GCG', 'GCT'],\\n 'G' : ['GGA', 'GGC', 'GGT', 'GGG'],\\n 'I' : ['ATA', 'ATC', 'ATT'],\\n 'F' : ['TTT', 'TTC'],\\n 'Y' : ['TAT', 'TAC'],\\n 'H' : ['CAC', 'CAT'],\\n 'Q' : ['CAG', 'CAA'],\\n 'N' : ['AAC', 'AAT'],\\n 'K' : ['AAA', 'AAG'],\\n 'D' : ['GAC', 'GAT'],\\n 'E' : ['GAA', 'GAG'],\\n 'C' : ['TGC', 'TGT'],\\n 'M' : ['ATG'],\\n 'W' : ['TGG']\\n\\n }\\n comp_genome = \\\"\\\"\\n for stra in genome:\\n comp_genome += ref_dict[stra]\\n main_orfs = find_orfs(genome, start_codon, stop_codon, min_num_aa, amino_dict, False)\\n comp_orfs = find_orfs(comp_genome[::-1], start_codon, stop_codon, min_num_aa, amino_dict, True)\\n circular_orfs = find_cir_orfs(genome, main_orfs, start_codon, stop_codon, min_num_aa, amino_dict, False)\\n \\n circular_orfs_comp = find_cir_orfs(comp_genome[::-1], comp_orfs, start_codon, stop_codon, min_num_aa, amino_dict, True)\\n \\n for main_orf in main_orfs:\\n for cir_orf in circular_orfs:\\n if main_orf[0] <= cir_orf[1] and main_orf[1] <= cir_orf[1] or len(main_orf) == 5:\\n main_orfs.remove(main_orf)\\n for comp_orf in comp_orfs:\\n for cir_orf in circular_orfs_comp:\\n if comp_orf[1] == cir_orf[1] or len(comp_orf) == 5:\\n comp_orfs.remove(comp_orf)\\n\\n final_orf = main_orfs + comp_orfs + circular_orfs + circular_orfs_comp\\n #print(len(comp_orfs))\\n \\n \\n \\n return final_orf\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n input_a='ATGATTATTTGATGAATGGATTGA'\\n expected_output='[ATGATTATT,ATGGAT]'\\n actual_output=find_all_ORFs_oneframe(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\\n \\n input_a='ATGGGATTGTTT'\\n expected_output='[ATGGATTGTTT]'\\n actual_output=find_all_ORFs_oneframe(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\",\n \"def gene_finder(dna):\\n threshold = longest_ORF_noncoding(dna, 1500)\\n l = []\\n for i in find_all_ORFs_both_strands(dna):\\n \\tif len(i)>=threshold:\\n \\t\\tl.append(coding_strand_to_AA(i))\\n print l\\n return l\",\n \"def count_frames():\\n frames = sentence.sem.frames.find_all('frame', {'name' : NEGATION_FRAME_NAME})\\n frame_count = []\\n for f_r in frames:\\n frame_count.append(f_r)\\n return len(frame_count)\",\n \"def get_all_frames(self):\\n #pdb.set_trace()\\n frame_size=(512,512)\\n frame_data = []\\n variant_type = (pythoncom.VT_BYREF | pythoncom.VT_ARRAY | pythoncom.VT_UI2)\\n for i in xrange(self.defaults['EXP_SEQUENTS']):\\n frame_data.append(win32com.client.VARIANT(variant_type, numpy.empty(frame_size)))\\n frame_data[i]=self.appdoc.GetFrame(i+1,frame_data[i])\\n \\n return numpy.array(frame_data, dtype=numpy.uint16)\",\n \"def find_all_ORFs_both_strands(dna):\\n reverse_dna = get_reverse_complement(dna)\\n orfs = find_all_ORFs(dna)\\n backward_orfs = find_all_ORFs(reverse_dna)\\n orfs.extend(backward_orfs)\\n return orfs\",\n \"def rest_of_ORF(dna,aa,i):\\n\\n rest_of_ORF = []\\n \\n while len(aa) ==3 and aa not in stop_codons: #run this loop until locating a stop\\n # if len(aa) == 3:\\n rest_of_ORF.append (aa) #add each successive codon to list\\n i = i+1\\n aa = dna[3*i:(3*i)+3]\\n # else:\\n # rest_of_ORF.append (aa)\\n # return ''.join(rest_of_ORF)\\n\\n return ''.join(rest_of_ORF)\",\n \"def rest_of_ORF(dna):\\n end_dna = len(dna)\\n for group in range(0, end_dna, 3):\\n strand = dna[group:group+3]\\n if strand in ['TGA', 'TAA', 'TAG']:\\n return dna[0:group]\\n return dna\",\n \"def retrieve_open_issues(self):\\n return self._retrieve_issues(\\\"open\\\")\",\n \"def rest_of_ORF(dna):\\n\\n #inital conditions\\n i = 3\\n end_index = len(dna)\\n stop_codon = ('TAG','TAA','TGA')\\n\\n #for the length of the string of DNA, run through each codon and break and return the indec of the string if the codon is a stop codon\\n while i < len(dna)-2:\\n codon = dna[i:i+3] #takes only every third index which is the length of a codon\\n if codon in stop_codon:\\n end_index = i \\n break\\n i += 3\\n #returns a list from the start codon to the index where the stop codon begins\\n return dna[0:end_index]\",\n \"def list_open_roi_jobs(self):\\n db = self.database\\n job_list = []\\n\\n # Database structure\\n # dyad datatype camera datatype2 version\\n #[\\\"33\\\"][\\\"motion\\\"][\\\"3\\\"][\\\"in_roi\\\"][\\\"1\\\"][\\\"coordinates\\\"]\\n pathes = db.search_key(db.dictionary, \\\"coordinates\\\")\\n for path in pathes:\\n try:\\n db.dictionary[path[0]][path[1]][path[2]][path[3]][path[4]][\\\"path\\\"]\\n except KeyError:\\n job_list.append(path[0:5])\\n return job_list\",\n \"def find_all_ORFs_unit_tests():\\n \\n input = [\\\"dna\\\"]\\n expected_output = [\\\"all non-nested ORFs\\\"]\\n actual = []\\n for k in input:\\n actual.append(find_all_ORFs(k))\\n print input \\n print actual\\n print expected_output\",\n \"def gene_finder(dna):\\n threshold = longest_ORF_noncoding(dna, 1500)\\n list_of_aminos = []\\n list_of_ORFs = find_all_ORFs_both_strands(dna)\\n for an_ORF in list_of_ORFs:\\n if an_ORF > threshold:\\n amino_acid_ORF = coding_strand_to_AA(an_ORF)\\n list_of_aminos.append(amino_acid_ORF)\\n return list_of_aminos\",\n \"def longest_orf(seq):\\n\\n # Find possible start positions\\n starts = seq_positions(seq, 'ATG')\\n\\n # Find possible end positions\\n ends = seq_positions(seq, 'TGA') + seq_positions(seq, 'TAG') + seq_positions(seq, 'TAA')\\n\\n # Go through all starts and ends keeping track of longest orf\\n orf = ''\\n for start in starts:\\n for end in ends:\\n if start < end and (end - start) % 3 == 0:\\n print(seq[start:end+3])\\n if len(orf) < (end - start):\\n orf = seq[start:end+3]\\n break\\n\\n return orf\",\n \"def gene_finder(dna):\\n threshold = longest_ORF_noncoding(dna, 1500)\\n orfs = find_all_ORFs_both_strands(dna)\\n list1 = []\\n for orf in orfs:\\n if len(orf) > threshold:\\n list1.append(coding_strand_to_AA(orf))\\n return list1\",\n \"def find_all_ORFs_unit_tests(dna, expected):\\n \\n print find_all_ORFs(\\\"ATGCATGAATGTAG\\\")\\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + find_all_ORFs(dna)\",\n \"def rest_of_ORF(dna):\\n STOP_CODONS=['TAG','TGA','TAA' ]#constants are uppercase\\n for i in range(0,len(dna),3):\\n codon=dna[i:i+3]\\n if codon in STOP_CODONS:\\n return dna[0:i]\\n return dna\",\n \"def read_FIREXAQ_files(path, folder='merge', var=''):\\n df_list=[]\\n flag_list=[]\\n files2use = sorted(glob.glob(f'{path}/{folder}/*{var}*.ict'))\\n for infileN, infile in enumerate( files2use ):\\n with open(infile) as thefile:\\n try:\\n header= np.array([next(thefile) for x in range(90) ])\\n except:\\n continue\\n start = header[6].replace(',',' ').split()\\n start_date = datetime_( int( start[0] ),\\n int( start[1] ),\\n int( start[2] ))\\n # Find where the header ends and values begin - manually narrowed down\\n for nskip in range(675,680):\\n try:\\n fh = np.loadtxt(infile, skiprows=nskip, delimiter=',')\\n break\\n except:\\n continue\\n thefile = open(infile,'r')\\n c = thefile.readlines()\\n column_names = c[nskip-1].replace(' ','').split(',')\\n df = pd.DataFrame(fh, index=fh[:,0], columns=column_names)\\n\\n # Use a different approach for\\n if (var=='thru'):\\n df = find_FIREXAQ_times(df, start_date, UseTimeStart=True)\\n else:\\n df = find_FIREXAQ_times(df, start_date, UseTimeStart=False)\\n # Include the RF from the file name #\\n # NOTE: research flight (RF) ID not included in filename or files,\\n # so using filenumber instead. This will not work if reading\\n # merge file (var = 'thru').\\n df['FileNumber'] = infileN\\n\\n df_list.append(df)\\n df = pd.concat(df_list)\\n return df\",\n \"def findGaps(sequence):\\n patt = re.compile(r\\\"[Nn]+\\\")\\n for match in patt.finditer(sequence):\\n yield (match.start(), match.end())\",\n \"def _read_frames(self):\\n cap = self._read_file()\\n\\n frame_list = []\\n ret_list = []\\n\\n while True:\\n ret, frame = cap.read()\\n if ret:\\n frame_list.append(np.array(frame))\\n ret_list.append(ret)\\n else:\\n break\\n if self.mode==\\\"np\\\":\\n frame_list = np.array(frame_list)\\n return frame_list\",\n \"def getFrames(job, **options):\\n criteria = search.FrameSearch.criteriaFromOptions(**options)\\n framesSeq = Cuebot.getStub('frame').GetFrames(\\n job_pb2.FrameGetFramesRequest(job=job, r=criteria), timeout=Cuebot.Timeout).frames\\n return [Frame(f) for f in framesSeq.frames]\",\n \"def find_all_ORFs_both_strands(dna):\\n both_strands_ORFs = []\\n\\n both_strands_ORFs.extend(find_all_ORFs(dna))\\n both_strands_ORFs.extend(find_all_ORFs(get_reverse_complement(dna)))\\n \\n return both_strands_ORFs\",\n \"def FrameGen(step, odb):\\n # Just to inform the reader\\n print(\\\"There are {} frames to read\\\".format(len(odb.steps[step].frames)))\\n for i in odb.steps[step].frames:\\n yield i\",\n \"def find_all_ORFs_both_strands(dna):\\n return find_all_ORFs(dna) + (find_all_ORFs(get_reverse_complement(dna)))\",\n \"def rest_of_ORF(dna):\\n index = -1\\n dna_split = split_into_codons(dna)\\n\\n for i, j in enumerate(dna_split):\\n if j == \\\"TAG\\\" or j == \\\"TGA\\\" or j == \\\"TAA\\\":\\n index = i\\n if index == -1:\\n return ''.join(dna_split) # if there is no stop codon\\n return ''.join(dna_split[:index])\",\n \"def extractsequences(filename):\\n\\n yield (filename, 2, None)\\n for m in re.finditer(r\\\"(?!0)[0-9]+\\\", filename):\\n frameno = int(m.group())\\n yield (makenonpaddedname(m), 0, frameno)\\n for m in re.finditer(r\\\"[0-9]+\\\", filename):\\n frameno = int(m.group())\\n if m.end() - m.start() > 1:\\n yield (makepaddedname(m), 1, frameno)\",\n \"def find_first_orf(sequence,\\n start_codons = ['AUG'],\\n stop_codons = ['UAA', 'UAG', 'UGA']):\\n \\n # Make sure the sequence is valid\\n vet_nucleotide_sequence(sequence)\\n\\n # Make sure the codons are valid\\n for codon in start_codons:\\n vet_codon(codon)\\n for codon in stop_codons:\\n vet_codon(codon)\\n\\n # Get copies of everything in uppercase\\n seq = sequence.upper()\\n starts = [c.upper() for c in start_codons]\\n stops = [c.upper() for c in stop_codons]\\n # Make sure seq is RNA\\n seq = seq.replace('T', 'U')\\n\\n\\n ##########################################################################\\n # `orf_pattern_str` is a regular expression that will match an\\n # open reading frame within a string of RNA bases. \\n # Read the docstring above for additional clues.\\n #I create variables as \\\"strings\\\" to take in start_codons & stop_codons \\\"lists\\\" so it can use them in the \\\"regex\\\"\\n \\n strt = '|'.join(start_codons) #takes the start codon provided and saves it as a string named 'strt'\\n stp = '|'.join(stop_codons) #takes the stop codon provided and takes it as a string named 'stp'\\n\\n #here the `regex`\\n orf_pattern_str = r'(' + strt +r')([AUCG]{3})*('+ stp +r')'\\n #breakdown\\n #the regex is in 3 groups\\n #first group is the start codon\\n # literarily it is 'AUG', but it is dynamic, and (' + strt +r') fixes that\\n #the second group is ([AUGC]{3})* which captures zero or more sets of codon after the start codon\\n #the last group is ((UAA)|(UAG)|(UGA)) dynamically captured as ('+ stp +r')\\n ##########################################################################\\n\\n # Create the regular expression object\\n orf_pattern = re.compile(orf_pattern_str)\\n # Search the sequence\\n match_object = orf_pattern.search(seq)\\n if match_object:\\n return match_object.group()\\n return ''\",\n \"def _find_all_top_level_non_gene_features(chrom: str, db: FeatureDB, feature_types: List[str]) -> Iterable[Feature]:\\n for feature in db.region(seqid=chrom, featuretype=feature_types):\\n try:\\n _ = next(db.parents(feature.id))\\n except StopIteration:\\n yield feature\",\n \"def find_all_ORFs_both_strands(dna):\\n return find_all_ORFs(dna) + find_all_ORFs(get_reverse_complement(dna))\",\n \"def find_all_ORFs_unit_tests():\\n data_list = [\\n [\\\"ATGCATGAATGTAG\\\", [\\\"ATGCATGAATGTAG\\\", \\\"ATGAATGTAG\\\", \\\"ATG\\\"]],\\n [\\\"ATG\\\", [\\\"ATG\\\"]],\\n [\\\"AATG\\\", [\\\"ATG\\\"]],\\n [\\\"AAATG\\\", [\\\"ATG\\\"]],\\n [\\\"ATGATG\\\", [\\\"ATGATG\\\"]],\\n [\\\"ATATGGATTGA\\\", [\\\"ATGGAT\\\"]],\\n [\\\"ATGAGATTAG\\\", [\\\"ATGAGATTAG\\\"]],\\n [\\\"ATATGGATTAGTAGTAATGAAAGTATAG\\\", [\\\"ATGAAAGTA\\\", \\\"ATGGAT\\\", ]],\\n# ATA TGG ATT AGT AGT AAT GAA AGT ATA G\\n# TAT GGA TTA GTA GTA ATG AAA GTA TAG\\n# ATG GAT TAG TAG TAA TGA AAG TAT AG\\n [\\\"ATGTCACGCAATGTAGGATGGATGGATTAGAC\\\", [\\\"ATGTCACGCAATGTAGGATGGATGGAT\\\", \\\"ATG\\\", \\\"ATGGATGGATTAGAC\\\"]],\\n# ATG TCA CGC AAT GTA GGA TGG ATG GAT TAG AC --> ATG TCA CGC AAT GTA GGA TGG ATG GAT\\n# TGT CAC GCA ATG TAG GAT GGA TGG ATT AGA C\\n# GTC ACG CAA TGT AGG ATG GAT GGA TTA GAC\\n [\\\"ATGATGTAG\\\", [\\\"ATGATG\\\"]],\\n [\\\"TCGATGC\\\", [\\\"ATGC\\\"]],\\n [\\\"AAA\\\", []],\\n# TCG ATG C\\n# CGA TGC\\n# GAT GC\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\",\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = find_all_ORFs(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def longest_ORF_noncoding(dna, num_trials):\\n longest_random_ORF = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# initialize empty list\\n for i in range(num_trials):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# repeats for num_trials\\n \\trandomized_dna = shuffle_string(dna)\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# finds strings of random dna\\n \\tlongest_random_ORF.append(longest_ORF(randomized_dna))\\t\\t\\t\\t\\t\\t\\t\\t# adds random dna to list\\n\\treturn max(longest_random_ORF, key=len)\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns longest dna string\",\n \"def parse_frames(stream: BytesIO) -> Iterable[_Frame]:\\n while True:\\n old = stream.tell()\\n try:\\n yield _parse_frame(stream)\\n except IncompleteData as exc:\\n stream.seek(old)\\n break\",\n \"def longest_ORF_noncoding(dna, num_trials):\\n count = 0\\n orfs = []\\n while count < num_trials:\\n current_strand = shuffle_string(dna)\\n longest_in_shuffle = longest_ORF(current_strand)\\n orfs.append(longest_in_shuffle)\\n count = count + 1\\n longest = max(orfs, key=len)\\n return len(longest)\",\n \"def get_lidc_dataframes(data_path: str, num_sectors: int):\\n sorted_studies = sorted(glob(os.path.join(data_path, \\\"*\\\")))\\n frames = []\\n for study in sorted_studies:\\n df_temp = pd.read_csv(\\n os.path.join(study, \\\"annotations.txt\\\"), sep=\\\": \\\", header=None, dtype=str\\n )\\n df_temp.columns = [\\\"File\\\", \\\"Label\\\"]\\n df_temp[\\\"File\\\"] = df_temp[\\\"File\\\"].apply(lambda e: f\\\"{study}/{e}.png\\\")\\n frames.append(df_temp)\\n\\n return [balance_frame(frame) for frame in slice_sector(frames, num_sectors)]\",\n \"def iterframes(self):\\n # self.check_ground_truth_availability()\\n\\n # Iterate through both poses and images, and construct frames\\n # with look up table for filename str -> (timestamp, pose, annotation) \\n for img_msg, frame in self.frame_index_.iteritems(): \\n yield (frame.timestamp, img_msg, frame)\",\n \"def find_frames(self, ftype, calib_ID=None, index=False):\\n if 'framebit' not in self.keys():\\n msgs.error('Frame types are not set. First run get_frame_types.')\\n if ftype == 'None':\\n return self['framebit'] == 0\\n # Select frames\\n indx = self.type_bitmask.flagged(self['framebit'], ftype)\\n\\n if calib_ID is not None:\\n # Select frames in the same calibration group\\n indx &= self.find_calib_group(calib_ID)\\n\\n # Return\\n return np.where(indx)[0] if index else indx\",\n \"def holes(self, test_pylos):\\n availableholes = []\\n for layer in range(1, 4):\\n for row in range(4 - layer):\\n for column in range(4 - layer):\\n value = test_pylos.get(layer, row, column)\\n if value is None:\\n try:\\n test_pylos.validPosition(layer, row, column)\\n hole = [layer, row, column]\\n except game.InvalidMoveException:\\n pass\\n else:\\n availableholes.append(hole)\\n return availableholes\",\n \"def rest_of_ORF(dna): \\n\\n for i in range(3,len(dna)-2,3):\\n \\tstop_codon=dna[i:i+3]\\n \\tstart_codon=dna[:i]\\n \\tif stop_codon=='TAG' or stop_codon=='TAA' or stop_codon=='TGA':\\n \\t\\treturn start_codon\\n \\t\\tbreak\\n \\tif (i+3) >= len(dna)-2:\\n \\treturn dna\",\n \"def rest_of_ORF(dna):\\n num_codons = int(len(dna)/3)\\n num = 0\\n list_codons = []\\n cut_dna = ''\\n stop_index = -1\\n while num < num_codons:\\n num_start = int(num*3)\\n num_end = int(num*3 + 3)\\n list_codons.append(dna[num_start:num_end])\\n num = num + 1\\n for element in list_codons:\\n if element == 'TAA' or element == 'TAG' or element == 'TGA':\\n stop_index = list_codons.index(element)\\n break\\n\\n if stop_index != -1:\\n this_ORF = list_codons[0:stop_index]\\n for element in this_ORF:\\n cut_dna = cut_dna + element\\n return cut_dna\\n else:\\n return dna\",\n \"def find_all_ORFs_both_strands(dna):\\n #inital conditions\\n all_of_them = []\\n\\n #compute the all of the orfs in a DNA strand and the find their reverse complements\\n #the return both of them in a list that includes all of the ORFS on both strands\\n normal_ORFs = find_all_ORFs(dna)\\n reverse_complement = get_reverse_complement(dna)\\n reverse_ORFs = find_all_ORFs(reverse_complement)\\n all_of_them = normal_ORFs + reverse_ORFs\\n return all_of_them\",\n \"def gene_finder(dna):\\n #use longest_ORF_noncoding to determine what the longest strand of DNA could be in a random sequence\\n threshold = longest_ORF_noncoding(dna,1500)\\n\\n #find all of the orfs on both strand and the generate an empty list\\n all_orfs = find_all_ORFs_both_strands(dna)\\n all_orfs_long = []\\n\\n #this makes a list of strings of dna that are longer than the threshold\\n\\n for i in range (0, len(all_orfs)):\\n if len(all_orfs[i]) > threshold:\\n all_orfs_long.append(all_orfs[i])\\n\\n #this takes each dna string in a list and converts it to an amino acid sequence\\n\\n aa_list = []\\n\\n for i in range (0, len(all_orfs_long)):\\n aa_strand = coding_strand_to_AA(all_orfs_long[i])\\n aa_list.append(aa_strand)\\n\\n #returns strings of amino acids\\n return aa_list\",\n \"def find_surrounding_frames(frame, frames_with):\\n # If frame is missing from the beginning, return initial frame twice.\\n if (frame < frames_with[0]):\\n return frames_with[0], frames_with[0], frames_with[0] - frame\\n # If frame is missing from the end, return last frame twice.\\n elif (frame > frames_with[-1]):\\n return frames_with[-1], frames_with[-1], frame - frames_with[-1]\\n # If frame is missing in the middle, return surrounding frames.\\n else:\\n for i in range(1, len(frames_with)):\\n frame_before = frames_with[i-1]\\n frame_after = frames_with[i]\\n if (frame > frame_before and frame < frame_after):\\n return frame_before, frame_after, frame_after - frame_before - 1\",\n \"def prune_decoded_seqs(seqs):\\r\\n out = []\\r\\n for s in seqs:\\r\\n if EOS in s:\\r\\n idx = s.index(EOS)\\r\\n out += [s[:idx]]\\r\\n else:\\r\\n out += [s]\\r\\n return out\",\n \"def gene_finder(dna):\\n viable_strings = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitialize empty list (for strings)\\n viable_amino_acids = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitialize empty list (for amino acids)\\n threshold = longest_ORF_noncoding(dna, 1500)\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# sets threshold to longest random dna string\\n real_dna = list(find_all_ORFs_both_strands(dna))\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# sets real_dna equal to all the ORFs, both strands\\n for i in range(len(real_dna)):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# searches through all the elements in list real_dna\\n \\tif len(real_dna[i]) > len(threshold):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# compares real string to random string\\n \\t\\tviable_strings.append(real_dna[i])\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if real string is longer, adds it to list\\n for i in range(len(viable_strings)):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# searches through all elements in viable_strings\\n \\ta = coding_strand_to_AA(viable_strings[i])\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# translates each string to amino acid sequence\\n \\tviable_amino_acids.append(a)\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# adds amino acids to list\\n return viable_amino_acids\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns list\",\n \"def rest_of_ORF(dna):\\n\\t# TODO: implement this\\n\\tindex = 0\\n\\twhile index < len(dna):\\n\\t\\tcodon = dna[index:index + 3]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# groups 3 nucleotides to make codon, index by 3\\n\\t\\tif codon in [\\\"TAA\\\", \\\"TAG\\\", \\\"TGA\\\"]:\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# checks if stop codon is in string\\n\\t\\t\\treturn dna[:index]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if True, returns string up to stop codon\\n\\t\\tindex += 3\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# indexes by 3\\n\\treturn dna\",\n \"def extract_seqrecords_from_gff3_fasta(gff3_with_fasta_handle: TextIO) -> List[SeqRecord]:\\n # first, find the header\\n fasta_found = False\\n for row in gff3_with_fasta_handle:\\n if row.rstrip() == GFF3Headers.FASTA_HEADER.value:\\n fasta_found = True\\n break\\n\\n if fasta_found is False:\\n raise GFF3FastaException(\\\"Did not find FASTA header in the GFF3 file.\\\")\\n\\n data = StringIO(gff3_with_fasta_handle.read())\\n recs = list(SeqIO.parse(data, format=\\\"fasta\\\"))\\n return recs\",\n \"def get_frames(gif: Image.Image) -> List[Image.Image]:\\n last_frame = None\\n all_frames = []\\n i = 0\\n try:\\n while True:\\n gif.seek(i)\\n new_frame = gif.convert('RGBA')\\n if last_frame is not None and gif.disposal_method == 1:\\n updated = new_frame.crop(gif.dispose_extent)\\n last_frame.paste(updated, gif.dispose_extent, updated)\\n new_frame = last_frame\\n else:\\n last_frame = new_frame\\n\\n # do resizing on new_frame here...\\n\\n all_frames.append(new_frame.copy())\\n i += 1\\n except EOFError:\\n gif.seek(0)\\n\\n return all_frames\",\n \"def find_all_ORFs_both_strands(dna):\\n # TODO: implement this\\n all_ORFs_both_strands = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# initialize empty list\\n all_ORFs_both_strands = all_ORFs_both_strands + find_all_ORFs(dna)\\t\\t\\t\\t\\t\\t# adds all ORFs one strand to list\\n reverse_complement_dna = get_reverse_complement(dna)\\t\\t\\t\\t\\t\\t\\t\\t\\t# finds 2nd strand\\n all_ORFs_both_strands = all_ORFs_both_strands + find_all_ORFs(reverse_complement_dna)\\t# finds all ORFs second strand\\n return all_ORFs_both_strands \\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns all ORFs both strands\",\n \"def rest_of_ORF(dna):\\n \\n if dna[:3]== \\\"TAG\\\" or dna[:3]==\\\"TAA\\\" or dna[:3]==\\\"TGA\\\" or len(dna)<3:\\n return \\\"\\\"\\n if len(dna)<=3:\\n return dna\\n return dna[:3]+rest_of_ORF(dna[3:])\",\n \"def fgetl_nocom(fid):\\n l = fgetl(fid)\\n while max(l.shape) > 0 & l[0] == '#':\\n\\n l = fgetl(fid)\\n\\n #\\n return l\",\n \"def find_all_ORFs_both_strands(dna):\\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def longest_ORF(dna):\\n i = 0\\n both_ORFs = find_all_ORFs_both_strands(dna)\\n longest = both_ORFs[0]\\n while i + 1 < len(both_ORFs):\\n if len(both_ORFs[i+1]) > len(longest):\\n longest = both_ORFs[i+1]\\n i+=1\\n return longest\",\n \"def prune_decoded_seqs(seqs):\\n out = []\\n for s in seqs:\\n if constant.EOS in s:\\n idx = s.index(constant.EOS_TOKEN)\\n out += [s[:idx]]\\n else:\\n out += [s]\\n return out\",\n \"def longestorf(args):\\n p = OptionParser(longestorf.__doc__)\\n p.add_option(\\\"--ids\\\", action=\\\"store_true\\\", help=\\\"Generate table with ORF info\\\")\\n opts, args = p.parse_args(args)\\n\\n if len(args) != 1:\\n sys.exit(not p.print_help())\\n\\n (fastafile,) = args\\n pf = fastafile.rsplit(\\\".\\\", 1)[0]\\n orffile = pf + \\\".orf.fasta\\\"\\n idsfile = None\\n if opts.ids:\\n idsfile = pf + \\\".orf.ids\\\"\\n fwids = open(idsfile, \\\"w\\\")\\n\\n f = Fasta(fastafile, lazy=True)\\n fw = must_open(orffile, \\\"w\\\")\\n before, after = 0, 0\\n for name, rec in f.iteritems_ordered():\\n cds = rec.seq\\n before += len(cds)\\n # Try all six frames\\n orf = ORFFinder(cds)\\n lorf = orf.get_longest_orf()\\n newcds = Seq(lorf)\\n after += len(newcds)\\n newrec = SeqRecord(newcds, id=name, description=rec.description)\\n SeqIO.write([newrec], fw, \\\"fasta\\\")\\n if idsfile:\\n print(\\\"\\\\t\\\".join((name, orf.info)), file=fwids)\\n\\n fw.close()\\n if idsfile:\\n fwids.close()\\n\\n logging.debug(\\n \\\"Longest ORFs written to `{0}` ({1}).\\\".format(\\n orffile, percentage(after, before)\\n )\\n )\\n\\n return orffile\",\n \"def find_frame_files(self, ftype, calib_ID=None):\\n return self.frame_paths(self.find_frames(ftype, calib_ID=calib_ID))\",\n \"def split_frames(flat):\\n \\n frames = [[]]\\n for expr in flat:\\n # A new frame starts with a .loc expression.\\n if type(expr) == Raw and expr.expr[:4] == '.loc':\\n frames.append([expr])\\n else:\\n frames[-1].append(expr)\\n return frames\",\n \"def getFrameList(self):\\n with self.frameLock:\\n return list(self.frameList)\",\n \"def find_all_ORFs_both_strands(dna):\\n return find_all_ORFs(dna)+find_all_ORFs(get_reverse_complement(dna))\\n \\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def get_issues(fasta,\\n gff,\\n feature_format=CDS_FEATURE_FORMAT,\\n use_feature_name=False,\\n start_codons=[START_CODON]):\\n for f in [fasta, gff]:\\n if not os.path.exists(f) or (not os.path.isfile(f)):\\n raise FileNotFoundError(f)\\n try:\\n gffdb = gffutils.create_db(gff,\\n dbfn='gff.db',\\n force=True,\\n keep_order=True,\\n merge_strategy='merge',\\n sort_attribute_values=True)\\n except ValueError as e:\\n # Wrap and rethrow exception so file name is included\\n raise ValueError(\\\"{} ({})\\\".format(e, gff)) from e\\n issues = []\\n # Track IDs of features encountered. Each ID must be unique within\\n # a GFF file. See http://gmod.org/wiki/GFF3.\\n feature_ids = {}\\n # Track sequences encountered and counts of features for\\n # each.\\n sequence_features = {}\\n fasta_genes = Fasta(fasta)\\n for feature in gffdb.features_of_type('CDS'):\\n if feature.seqid not in sequence_features:\\n sequence_features[feature.seqid] = 0\\n sequence_features[feature.seqid] += 1\\n\\n feature_id = None\\n if \\\"ID\\\" in feature.attributes:\\n feature_id = feature.attributes[\\\"ID\\\"][0].strip()\\n if feature_id in feature_ids:\\n feature_ids[feature_id].append(feature.seqid)\\n else:\\n feature_ids[feature_id] = [feature.seqid]\\n feature_id_name = get_feature_id(feature, use_feature_name)\\n if feature_id_name is None:\\n feature_id_name = feature_format.format(feature.seqid)\\n issues.append((feature.seqid, feature_id_name,\\n NO_ID_NAME, None))\\n try:\\n sequence = feature.sequence(fasta_genes)\\n except KeyError as e: # Missing sequence.\\n issues.append((feature.seqid,\\n NOT_APPLICABLE,\\n SEQUENCE_NOT_IN_FASTA,\\n None))\\n continue\\n except FastaIndexingError as e:\\n raise e\\n except Exception as e:\\n warnings.warn(str(e))\\n continue\\n seq_len_remainder = len(sequence) % 3\\n if seq_len_remainder != 0:\\n issues.append((feature.seqid, feature_id_name,\\n INCOMPLETE_FEATURE, None))\\n sequence += (\\\"N\\\" * (3 - seq_len_remainder))\\n\\n sequence_codons = sequence_to_codons(sequence)\\n if sequence_codons[0] not in start_codons:\\n issues.append((feature.seqid, feature_id_name,\\n NO_START_CODON, sequence_codons[0]))\\n if not sequence_codons[-1] in STOP_CODONS:\\n issues.append((feature.seqid, feature_id_name,\\n NO_STOP_CODON, sequence_codons[-1]))\\n if any([codon in STOP_CODONS\\n for codon in sequence_codons[:-1]]):\\n issues.append((feature.seqid, feature_id_name,\\n INTERNAL_STOP_CODON, None))\\n\\n for sequence, count in list(sequence_features.items()):\\n if count > 1:\\n # Insert issue, respect ordering by sequence ID.\\n bisect.insort(issues, (sequence, WILDCARD, MULTIPLE_CDS, count))\\n\\n for feature_id, seq_ids in feature_ids.items():\\n if len(seq_ids) > 1:\\n issues.append((WILDCARD, feature_id,\\n DUPLICATE_FEATURE_IDS, len(seq_ids)))\\n for seq_id in seq_ids:\\n # Insert issue, respect ordering by sequence ID.\\n bisect.insort(issues, (seq_id, feature_id,\\n DUPLICATE_FEATURE_ID, None))\\n\\n gff_seq_ids = set(sequence_features.keys())\\n fasta_seq_ids = get_fasta_sequence_ids(fasta)\\n fasta_only_seq_ids = fasta_seq_ids - gff_seq_ids\\n for seq_id in fasta_only_seq_ids:\\n issues.append((seq_id, NOT_APPLICABLE, SEQUENCE_NOT_IN_GFF, None))\\n num_sequences = len(fasta_seq_ids)\\n num_features = len(list(gffdb.all_features()))\\n num_cds_features = len(list(gffdb.features_of_type('CDS')))\\n return num_sequences, num_features, num_cds_features, issues\",\n \"def longest_ORF_noncoding(dna, num_trials):\\n org = list(dna)\\n max_len = 0\\n r = \\\"\\\"\\n for i in range(num_trials):\\n l = org\\n shuffle(l)\\n orf = longest_ORF(collapse(l))\\n if len(orf) > max_len:\\n r = orf\\n max_len = len(orf)\\n return r\",\n \"def load_data(data_path, sequence_length, no_sequences=None):\\n frames_available = 0\\n # load everything in the folder\\n all_data = False\\n for root, dirs, files in os.walk(data_path):\\n for one_file in files:\\n if one_file.split(\\\".\\\")[-1] != 'npy':\\n write_to_summary(f\\\"Skipping {root}/{one_file}\\\", print_red=True)\\n continue\\n write_to_summary(f\\\"Loading from:{root}/{one_file}\\\")\\n file_path = os.path.join(root, one_file)\\n if all_data is False:\\n all_data = load_blob(file_path)\\n frames_available += all_data.shape[0]\\n else:\\n more_data = load_blob(file_path)\\n all_data = np.concatenate((all_data, more_data), axis=0)\\n frames_available += more_data.shape[0]\\n # Add 10 sequences in case some are discarded for damaged frames\\n if no_sequences is not None and frames_available // sequence_length > no_sequences + 10:\\n break\\n if all_data is False:\\n return (False,False)\\n # First we check the average, and see if there are any frames to discard\\n average_pixel_count = [np.sum(frame) for frame in all_data]\\n average_pixel_count = np.mean(average_pixel_count)\\n write_to_summary(f\\\"Average pixel count:{average_pixel_count}\\\")\\n skip_limit = DISCARD_CONSTANT * average_pixel_count\\n write_to_summary(f\\\"Pixel count skip limit:{skip_limit}\\\")\\n skip_indexes = []\\n index_counter = 0\\n for frame in all_data:\\n if np.sum(frame) > skip_limit:\\n skip_indexes.append(index_counter)\\n index_counter += 1\\n write_to_summary(f\\\"{len(skip_indexes)} frames have a pixel count exceding the threshold:\\\")\\n write_to_summary(skip_indexes)\\n\\n # Generate all indicies that will produce data\\n # and use that to filter out the ones with damaged frame in them \\n indicies_pairs = []\\n frame_counter = 0\\n while frame_counter + sequence_length + 1 < frames_available:\\n all_valid_frames = True\\n for damaged_frames in skip_indexes:\\n if damaged_frames >= frame_counter and damaged_frames <= frame_counter + sequence_length + 1:\\n all_valid_frames = False\\n break\\n pair = (frame_counter, frame_counter + sequence_length + 1)\\n if not all_valid_frames:\\n write_to_summary(f\\\"{pair} skipped because of damaged frame\\\", print_red=True)\\n else:\\n indicies_pairs.append(pair)\\n frame_counter += sequence_length + 1\\n write_to_summary(f\\\"{len(indicies_pairs)} valid sequences available, target is {no_sequences}\\\")\\n\\n # Check how many sequences we will get\\n # final_no_sequences = frames_available // sequence_length\\n final_no_sequences = len(indicies_pairs)\\n if no_sequences is not None and final_no_sequences > no_sequences:\\n final_no_sequences = no_sequences\\n # Discard the ones we dont need\\n indicies_pairs = indicies_pairs[:final_no_sequences]\\n img_width = all_data.shape[1]\\n img_height = all_data.shape[2]\\n # -1 in sequence_length becasue the final frame is in the ground truth, no wait skip that\\n # better to use sequence_length + 1 for y_train, makes more sense\\n x_train = np.zeros((final_no_sequences, sequence_length, img_width, img_height, 1))\\n y_train = np.zeros((final_no_sequences, 1, img_width, img_height, 1))\\n current_sequence = 0\\n for start_frame, end_frame in indicies_pairs:\\n training_frames = all_data[start_frame: start_frame + sequence_length]\\n truth_frame = all_data[start_frame + sequence_length: end_frame]\\n x_train[current_sequence] = np.expand_dims(training_frames, axis=3)\\n y_train[current_sequence] = np.expand_dims(truth_frame, axis=3)\\n current_sequence += 1\\n # No validation for now\\n write_to_summary(f\\\"Loaded {len(x_train)} sequences of length {sequence_length}!\\\")\\n return (x_train, y_train)\"\n]","isConversational":false},"negative_scores":{"kind":"list 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\"0.43468288\",\n \"0.4341432\",\n \"0.432573\",\n \"0.43212318\",\n \"0.43208206\",\n \"0.4317101\",\n \"0.43147317\",\n \"0.43061197\",\n \"0.4305591\",\n \"0.42818505\",\n \"0.42717305\",\n \"0.42505276\",\n \"0.424406\",\n \"0.4243384\",\n \"0.42402697\",\n \"0.4238763\",\n \"0.4238433\",\n \"0.42309123\",\n \"0.42264307\",\n \"0.42198226\",\n \"0.42140964\",\n \"0.4212249\",\n \"0.4205869\",\n \"0.4200867\",\n \"0.41940436\",\n \"0.4193453\",\n \"0.41931123\",\n \"0.41879338\",\n \"0.41791758\",\n \"0.41562083\",\n \"0.413683\",\n \"0.41343617\",\n \"0.41311133\",\n \"0.41266257\",\n \"0.41246223\",\n \"0.41218552\",\n \"0.4108952\",\n \"0.41061634\",\n \"0.410043\",\n \"0.4097933\",\n \"0.4097137\",\n \"0.40953457\",\n \"0.40939003\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.611578"},"document_rank":{"kind":"string","value":"16"}}},{"rowIdx":92997,"cells":{"query":{"kind":"string","value":"Unit tests for the find_all_ORFs_oneframe function"},"document":{"kind":"string","value":"def find_all_ORFs_oneframe_unit_tests():\n data_list = [\n [\"ATGCATGAATGTAGATAGATGTGCCC\", [\"ATGCATGAATGTAGA\", \"ATGTGCCC\"]],\n [\"ATGTAGATGTAG\", [\"ATG\", \"ATG\"]],\n [\"ATGATGATG\", [\"ATGATGATG\"]],\n [\"ATGGGGGATTAGATGATG\", [\"ATGGGGGAT\", \"ATGATG\"]],\n [\"ATGTGAATGTAA\", [\"ATG\", \"ATG\"]],\n [\"ATGTGAATGTAAATG\", [\"ATG\", \"ATG\", \"ATG\"]],\n [\"ATGCGTGGTGATTAGATGGATGGGGATTGA\", [\"ATGCGTGGTGAT\", \"ATGGATGGGGAT\"]],\n [\"ATGAAATTTCCCGGGAAATTTCCCGGG\", [\"ATGAAATTTCCCGGGAAATTTCCCGGG\"]],\n [\"ATGAAATTTTGAATGGGGCCC\", [\"ATGAAATTT\", \"ATGGGGCCC\"]],\n [\"ATGAAATTTTGAATGGGGCCCTAG\", [\"ATGAAATTT\", \"ATGGGGCCC\"]],\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs_oneframe(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\""},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def find_all_ORFs_oneframe_unit_tests():\n\n # YOUR IMPLEMENTATION HERE","def find_all_ORFs_oneframe_unit_tests():\n input_a='ATGATTATTTGATGAATGGATTGA'\n expected_output='[ATGATTATT,ATGGAT]'\n actual_output=find_all_ORFs_oneframe(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output\n \n input_a='ATGGGATTGTTT'\n expected_output='[ATGGATTGTTT]'\n actual_output=find_all_ORFs_oneframe(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output","def find_all_ORFs_both_strands_unit_tests():\n\n # YOUR IMPLEMENTATION HERE","def find_all_ORFs_oneframe_unit_tests():\n\n input = [\"dna\"]\n expected_output = [\"all non-nester ORFs\"]\n actual = []\n for k in input:\n actual.append(find_all_ORFs_oneframe(k))\n print input \n print actual\n print expected_output","def find_all_ORFs_unit_tests():\n print 'Begin Unit test Find_all_ORFs'\n input_a='ATGCATGAATGTAGATGTAG'\n expected_output='[ATGCATGAATGTAGATGTAG, ATGAATGTAGATGTAG, ATG, ATG]'\n actual_output=find_all_ORFs(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output\n \n input_a='ATGCATGAATGTAGATGCATCATTAG'\n expected_output='[ATGCATGAATGTAGATGCATCATTAG, ATGAATGTAGATGCATCATTAG, ATG, ATGCATCAT]'\n actual_output=find_all_ORFs(input_a)\n print 'Expected Output is ' + expected_output\n print \"actucal OUtput is\", actual_output\n print 'ENd Unit test Find_all_ORFs'","def find_all_ORFs_oneframe_unit_tests(dna, expected):\n\n print find_all_ORFs_oneframe(\"ATGCATGAATGTAGATAGATGTGCCC\")\n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + find_all_ORFs_oneframe(dna)","def find_all_ORFs_oneframe(dna):","def find_all_ORFs_unit_tests():\n data_list = [\n [\"ATGCATGAATGTAG\", [\"ATGCATGAATGTAG\", \"ATGAATGTAG\", \"ATG\"]],\n [\"ATG\", [\"ATG\"]],\n [\"AATG\", [\"ATG\"]],\n [\"AAATG\", [\"ATG\"]],\n [\"ATGATG\", [\"ATGATG\"]],\n [\"ATATGGATTGA\", [\"ATGGAT\"]],\n [\"ATGAGATTAG\", [\"ATGAGATTAG\"]],\n [\"ATATGGATTAGTAGTAATGAAAGTATAG\", [\"ATGAAAGTA\", \"ATGGAT\", ]],\n# ATA TGG ATT AGT AGT AAT GAA AGT ATA G\n# TAT GGA TTA GTA GTA ATG AAA GTA TAG\n# ATG GAT TAG TAG TAA TGA AAG TAT AG\n [\"ATGTCACGCAATGTAGGATGGATGGATTAGAC\", [\"ATGTCACGCAATGTAGGATGGATGGAT\", \"ATG\", \"ATGGATGGATTAGAC\"]],\n# ATG TCA CGC AAT GTA GGA TGG ATG GAT TAG AC --> ATG TCA CGC AAT GTA GGA TGG ATG GAT\n# TGT CAC GCA ATG TAG GAT GGA TGG ATT AGA C\n# GTC ACG CAA TGT AGG ATG GAT GGA TTA GAC\n [\"ATGATGTAG\", [\"ATGATG\"]],\n [\"TCGATGC\", [\"ATGC\"]],\n [\"AAA\", []],\n# TCG ATG C\n# CGA TGC\n# GAT GC\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def find_all_ORFs_unit_tests():\n \n print \"input: ATGCTA, \"+\"output: \"+ \",\".join(find_all_ORFs(\"ATGCTA\"))+\", actual output: CTA\"\n print \"input: GTCACTTATGGGTTT, \"+\"output: \"+\",\".join(find_all_ORFs(\"ATGGATGCTTAGGGATGTTT\"))+\", actual output: GTCACT,GGTTTT,TCACTTAGGGTTTT,CACTTAGGGTTTT\"\n print \"input: AAATTTTATAATGGGTGAAGTTAG, \"+\"output: \"+\",\".join(find_all_ORFs(\"AAATTTTATAATGGGTGAAGTTAG\"))+\", actual output: ATGGGTGAAGTT\"\n print \"input: TATATGGAGGATAATAGTTGATAATAG, \"+\"output: \"+ \",\".join(find_all_ORFs(\"TATATGGAGGATAATAGTTGATAATAG\"))+\", actual output: ATGGAGGATAATAGT\"","def find_all_ORFs_unit_tests():\n \n input = [\"dna\"]\n expected_output = [\"all non-nested ORFs\"]\n actual = []\n for k in input:\n actual.append(find_all_ORFs(k))\n print input \n print actual\n print expected_output","def find_all_ORFs(dna):\n all_ORFs=[]\n for i in range (0,3):\n \tframe=dna[i:] \n all_ORFs+=find_all_ORFs_oneframe(frame)\n return all_ORFs","def find_all_ORFs(dna):\n ans = find_all_ORFs_oneframe(dna)\n ans.extend(find_all_ORFs_oneframe(dna[1:]))\n ans.extend(find_all_ORFs_oneframe(dna[2:]))\n return ans","def find_all_ORFs_both_strands_unit_tests():\n print ''\n print 'Begin Unit test Find_all_ORFs both tests'\n input_a='ATGCGAGGGTAGATGGATTAG'\n expected_output='[ATGCGAGGG, ATGGAT]'\n actual_output=find_all_ORFs_both_strands(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output\n \n \n input_a='ATGCGAATGTAGCATCAAATAGATGTAG'\n expected_output='[ATGCGAATG, ATG, ATGCTACATTCGCAT]'\n actual_output=find_all_ORFs_both_strands(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output \n print 'end'\n print ''","def find_all_ORFs(dna):\n all_ORFs = []\n i = 0\n\n for i in range (0,3): \n all_ORFs.extend(find_all_ORFs_oneframe(dna))\n dna = 'X' + dna\n\n return all_ORFs","def find_all_ORFs_unit_tests(dna, expected):\n \n print find_all_ORFs(\"ATGCATGAATGTAG\")\n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + find_all_ORFs(dna)","def find_all_ORFs(dna):\n #these functions offset to analyze each each open frame reference\n zero_offset=find_all_ORFs_oneframe(dna[0:])\n \n one_offset=find_all_ORFs_oneframe(dna[1:])\n \n two_offset=find_all_ORFs_oneframe(dna[2:])\n \n return zero_offset+one_offset+two_offset\n \n # YOUR IMPLEMENTATION HERE","def find_all_ORFs(dna):\n \n # YOUR IMPLEMENTATION HERE","def find_all_ORFs(dna):\n index = 0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# initialize index\n all_ORFs = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitalize empty list\n while index < 3:\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# switches throught the 3 frames\n \tall_ORFs = all_ORFs + find_all_ORFs_oneframe(dna[index:])\t# adds all ORFs oneframe to the list\n \tindex += 1\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# indexes +1\n return all_ORFs \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns list of all ORFs in all 3 frames","def find_all(self):","def find_all_ORFs(dna):\n all_ORFs = []\n for i in range(0, 3):\n dna_new = dna[i:]\n all_ORFs += find_all_ORFs_oneframe(dna_new)\n return all_ORFs","def find_all_ORFs(dna):\n dnatwo = dna[1:]\n dnathree = dna[2:]\n all_ORFs = find_all_ORFs_oneframe(dna)\n all_ORFs.extend(find_all_ORFs_oneframe(dnatwo))\n all_ORFs.extend(find_all_ORFs_oneframe(dnathree))\n if [] in all_ORFs:\n all_ORFs.remove([])\n return all_ORFs","def find_all_ORFs_both_strands_unit_tests():\n data_list = [\n [\"ATGCGAATGTAGCATCAAA\", [\"ATGCGAATG\", \"ATGCTACATTCGCAT\"]],\n [\"ATG\", [\"ATG\"]],\n [\"CAT\", [\"ATG\"]],\n [\"CATCAT\", [\"ATGATG\"]],\n [\"CATGGGCAT\", [\"ATGGGCAT\", \"ATGCCCATG\"]],\n [\"CATGCAGTGCACGGATGGCAT\", [\"ATGCAGTGCACGGATGGCAT\", \"ATGGCAT\", \"ATGCCATCCGTGCACTGCATG\"]],\n# CATGCAGTGCACGGATGGCAT\n# CAT GCA GTG CAC GGA TGG CAT\n# ATG CAG TGC ACG GAT GGC AT\n# TGC AGT GCA CGG ATG GCA T\n# ATGCCATCCGTGCACTGCATG\n# ATG CCA TCC GTG CAC TGC ATG\n# TGC CAT CCG TGC ACT GCA TG\n# GCC ATC CGT GCA CTG CAT G\n [\"CATATGTAG\", [\"ATG\", \"ATG\"]],\n [\"ATGGGGCATCATTAG\", [\"ATGGGGCATCAT\", \"ATGATGCCCCAT\"]],\n# ATGGGGCATCATTAG\n# ATG GGG CAT CAT TAG\n# TGG GGC ATC ATT AG\n# GGG GCA TCA TTA G\n# CTAATGATGCCCCAT\n# CTA ATG ATG CCC CAT\n# TAA TGA TGC CCC AT\n# AAT GAT GCC CCA T\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs_both_strands(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def find_all_ORFs_oneframe(dna):\n condition = 1\n dna2 = dna\n list_of_ORFs = []\n while condition == 1:\n num_codons = int(len(dna2)/3)\n num = 0\n list_codons = []\n start_index = -1\n while num < num_codons:\n num_start = int(num*3)\n num_end = int(num*3 + 3)\n list_codons.append(dna2[num_start:num_end])\n num = num + 1\n for element in list_codons:\n if element == 'ATG':\n start_index = list_codons.index(element)\n break\n if start_index != -1:\n this_orf = rest_of_ORF(dna2[start_index*3:])\n list_of_ORFs.append(this_orf)\n dna2 = dna2[start_index*3+len(this_orf)+3:]\n else:\n condition = 2\n\n return list_of_ORFs","def find_all_ORFs_oneframe(dna):\n i = 0\n list_ORF = []\n\n def search_ORF(dna,i):\n aa = dna[3*i:(3*i)+3]\n if aa == 'ATG':\n list_ORF.append(rest_of_ORF(dna,aa,i))\n i = i + 1 + len(rest_of_ORF(dna,aa,i))/3\n else:\n i = i + 1\n if len(aa) ==3:\n search_ORF(dna,i)\n \n return list_ORF\n\n return search_ORF(dna,i)\n # i = i + ((len(list_ORF[-1]))/3)\n # search_ORF(dna,i)","def orfFinder(data):\n\t\n\tORFile = getORFs(data.seqFile, \n\t\t\t\t\t data.queryName, \n\t\t\t\t\t data.o)\n\tsetattr(data, \"ORFs\", ORFile)","def find_all_ORFs(dna):\n ORFs = find_all_ORFs_oneframe(dna) + find_all_ORFs_oneframe(dna[1:]) + find_all_ORFs_oneframe(dna[2:])\n\n return ORFs","def find_all(self):\n pass","def test_get_parsed_files(self):\n files = Historical_ROAs_Parser()._get_parsed_files()\n with Historical_ROAs_Parsed_Table() as t:\n for f in files:\n sql = f\"SELECT * FROM {t.name} WHERE file = '{f}'\"\n assert len(t.execute(sql)) == 1","def find_all_ORFs(dna):\n first_frame = find_all_ORFs_oneframe(dna[0:])\n second_frame = find_all_ORFs_oneframe(dna[1:])\n third_frame = find_all_ORFs_oneframe(dna[2:])\n list_of_frames = first_frame + second_frame + third_frame\n return list_of_frames","def rest_of_ORF_unit_tests():\n data_list = [\n [\"ATGTGAA\", \"ATG\"],\n [\"ATGAGATAGG\", \"ATGAGA\"],\n [\"ATG\", \"ATG\"],\n [\"ATGTAG\", \"ATG\"],\n [\"ATGTAA\", \"ATG\"],\n [\"ATGTGA\", \"ATG\"],\n [\"ATGAAATTTGGGAAATTTGGGTAG\", \"ATGAAATTTGGGAAATTTGGG\"],\n [\"ATGAAATTTGGG\", \"ATGAAATTTGGG\"],\n [\"ATGAGAAGGAAATTTGATGGGGATGGAAGATT\", \"ATGAGAAGGAAATTTGATGGGGATGGAAGATT\"],\n [\"ATGAGAAGGAAATTTGATGGGGATGGAAGATAA\", \"ATGAGAAGGAAATTTGATGGGGATGGAAGA\"],\n [\"ATGAA\", \"ATGAA\"],\n [\"ATGATGATG\", \"ATGATGATG\"],\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\" ,\n print \"expected output: \" + str(data[1]) + \",\",\n o = rest_of_ORF(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def find_all_ORFs_oneframe(dna):\n \n\n ORFs=[]\n i=0\n while i<len(dna):\n if dna[i:i+3]==\"ATG\":\n j=i\n dna2=rest_of_ORF(dna[j:])\n \n if dna2==None:\n \tbreak\n ORFs.append(dna2)\n i=i+len(dna2)\n i=i+3\n return ORFs","def find_all_ORFs_oneframe(dna):\n dna_split = split_into_codons(dna)\n i = 0\n all_ORFs_oneframe = []\n length_of_orf = 0\n while i < len(dna_split):\n if dna_split[i] == \"ATG\":\n orf = rest_of_ORF(dna[int(i)*3:])\n all_ORFs_oneframe += [orf]\n length_of_orf = math.ceil(len(orf)/3)\n i += length_of_orf\n else:\n i += 1\n return all_ORFs_oneframe","def find_all_ORFs_oneframe(dna):\n res = []\n l = len(dna)\n next_pos = 0\n while True:\n arg = dna[next_pos:]\n# orf = rest_of_ORF(arg)\n# res.append(orf)\n# if arg == orf: # if: no stop codon\n# break\n# next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\n# if next_pos >= l: # if: meet the end of dna\n# break\n if arg[0:3] == start_codon:\n orf = rest_of_ORF(arg)\n res.append(orf)\n if arg == orf: # if: no stop codon\n break\n next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\n else: # if: not start codon, see next\n next_pos += 3\n if next_pos >= l: # if: meet or go beyond the end of dna\n break\n return res","def find_all_ORFs_oneframe(dna):\n\n ORFlist = []\n i = 0\n lend = len(dna)\n while i < lend:\n codon = dna[i:i+3]\n if codon == 'ATG':\n orf = rest_of_ORF(dna[i:])\n ORFlist.append(orf)\n i = i + len(orf)\n else:\n i = i+3\n return ORFlist","def find_all_ORFs_both_strands(dna):\n \n # YOUR IMPLEMENTATION HERE","def test_otoroshi_controllers_adminapi_tcp_service_api_controller_find_all_entities_action(self):\n pass","def find_all_ORFs(dna):\n res = []\n for i in range(0, 3):\n s = dna[i:]\n# print i, s,\n# l = len(s)\n# for j in range(0, l, 3):\n# if s[j: j + 3] == start_codon:\n# r = find_all_ORFs_oneframe(s[j:])\n# print r\n# if len(r) > 0:\n# for item in r:\n# res.append(item)\n# break # careful for indentation here!!\n r = find_all_ORFs_oneframe(s)\n if len(r) > 0:\n# for item in r:\n# res.append(item)\n res += r # [WOW] I love python!\n return res","def find_all_ORFs_both_strands_unit_tests(dna, expected):\n\n print find_all_ORFs_both_strands(\"ATGCGAATGTAGCATCAAA\")\n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + find_all_ORFs_both_strands(dna)","def test_find_all(self):\n # arrange\n movie_id = MovieId('123')\n character = character_random_with_movie_ids(MovieIds([movie_id]))\n people = People([character])\n movie = movie_random_with_movie_id_and_people(movie_id, people)\n expected = Movies([movie])\n\n self.ghibli_client_mock__people([{'id': character.character_id, 'name': character.name,\n 'gender': character.gender, 'age': character.age,\n 'eye_color': character.eye_color, 'hair_color': character.hair_color,\n 'films': [f'http://url/{movie_id}']}])\n self.ghibli_client_mock__movies([{'id': movie_id, 'title': movie.title,\n 'description': movie.description, 'director': movie.director,\n 'producer': movie.producer, 'release_date': movie.release_date,\n 'rt_score': movie.rt_score}])\n\n # act\n repository = self.ghibli_movie_repository()\n movies = repository.find_all()\n\n # assert\n self.assertEqual(expected, movies)","def rest_of_ORF_unit_tests():\n input = [\"dna\"]\n expected_output = [\"rest of ORFs\"]\n actual = []\n for k in input:\n actual.append(rest_of_ORF(k))\n print input \n print actual\n print expected_output","def find_all_ORFs_both_strands_unit_tests():\n print \"input: CTA, \"+\"output: \"+ \",\".join(find_all_ORFs_both_strands(\"CTA\"))+\", actual output: CTA,TA,A,AG,G\"\n print \"input: GTCACTTAGGGTTTT, \"+\"output: \"+\",\".join(find_all_ORFs_both_strands(\"GTCACTTAGGGTTTT\"))+\", actual output: GTCACT,GGTTTT,TCACTTAGGGTTTT,CACTTAGGGTTTT,AAAACCCTAAGTGAC,AAACCC,GTGAC,AACCCTAAG\"\n print \"input: AAATTTTATAATGGGTGAAGTTAG, \"+\"output: \"+\",\".join(find_all_ORFs_both_strands(\"AAATTTTATAATGGGTGAAGTTAG\"))+\", actual output: AAATTTTATAATGGG,AGT,AATTTTATAATGGGTGAAGTTAG,ATTTTA,TGGGTGAAGTTAG,CTAACTTCACCCATTATAAAATTT,CTTCACCCATTA,AATTT,AACTTCACCCATTATAAAATTT\"\n print \"input: TATATGGAGGATAATAGTTGATAATAG, \"+\"output: \"+ \",\".join(find_all_ORFs_both_strands(\"TATATGGAGGATAATAGTTGATAATAG\"))+\", actual output: TATATGGAGGATAATAGT,ATATGGAGGATAATAGTTGATAATAG,TATGGAGGA,TTGATAATAG,CTATTATCAACTATTATCCTCCATATA,TATTATCAACTATTATCCTCCATATA,ATTATCAACTATTATCCTCCATATA\"","def find_all_ORFs(dna):\n\n readingFrame0 = ''\n readingFrame1 = ''\n readingFrame2 = ''\n output = ''\n for k in range(0,3): \n if k ==0: \n readingFrame0 = find_all_ORFs_oneframe(dna[k:])\n elif k ==1: \n readingFrame1 = find_all_ORFs_oneframe(dna[k:])\n elif k ==2:\n readingFrame2 = find_all_ORFs_oneframe(dna[k:])\n print 'Reading Frame 1: ' + str(readingFrame0) + ', Reading Frame 2: ' + str(readingFrame1) + ', Reading Frame 3: ' + str(readingFrame2)\n output = readingFrame0 + readingFrame1 + readingFrame2\n return output","def test_objects(self):\n\n obj = FBO(\n path=TEST_FILES_ROOT,\n metadata=FileObject.MetadataInFileHead,\n ).objects.all().filter(\n name__glob='*.rst',\n ).get(\n name='test2.rst',\n )\n\n self.assertEqual(\n 'Second in the alphabet',\n obj.title,\n )","def find_all_ORFs_oneframe(dna):\n #inital conditions\n i = 0\n start_codon = ('ATG')\n end_index = len(dna)\n return_variable = []\n\n #for each codon in the set of DNA, check if it is a start codon\n #if it is a start codon, add the string until the stop codon to a list\n #then continue running\n while i < len(dna)-2:\n codon = dna[i:i+3] \n if codon in start_codon:\n orf = rest_of_ORF(dna[i:])\n return_variable.append(orf)\n i += len(orf)\n i += 3\n\n\n #return a list of strings of DNA\n return return_variable","def find_all_ORFs_oneframe(dna):\n\tindex = 0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# unitiate index at 0\n\tsegment = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitializes empty list\n\twhile index < len(dna):\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# given that index is smaller than length of string\n\t\tcodon = dna[index:index + 3]\t\t\t\t\t\t\t\t\t\t\t\t\t\t# creates codons from nucleotides starting with first 3 letters\n\t\tif codon == \"ATG\":\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if the codon is ATG\n\t\t\tsegment.append(rest_of_ORF(dna[index:]))\t\t\t\t\t\t\t\t\t\t# run rest_of_ORF starting at index\n\t\t\tindex = index + len(rest_of_ORF(dna[index:]))\t\t\t\t\t\t\t\t\t# new index starting at old + length of ORF output string\n\t\telse:\n\t\t\tindex += 3\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if ATG isn't found, move to next codon and check again\n\n\treturn segment\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns list of ORFs","def rest_of_ORF_unit_tests():\n print \"input: CTA, \"+\"output: \"+rest_of_ORF(\"CTA\")+\", actual output: CTA\"\n print \"input: GTCACTTAGGGTTTT, \"+\"output: \"+rest_of_ORF(\"GTCACTTAGGGTTTT\")+\", actual output: GTCACT\"\n print \"input: AAATTTTATAATGGGTGAAGTTAG, \"+\"output: \"+rest_of_ORF(\"AAATTTTATAATGGGTGAAGTTAG\")+\", actual output: AAATTTTATAATGGG\"\n print \"input: TATATGGAGGATAATAGTTGATAATAG, \"+\"output: \"+rest_of_ORF(\"TATATGGAGGATAATAGTTGATAATAG\")+\", actual output: TATATGGAGGATAATAGT\"","def test_get_foods_search(self):\n pass","def find_all_ORFs_oneframe(dna):\n i=0 \n ORF_list = []\n while i<len(dna):\n if dna[i : i+3] == \"ATG\":\n start_place = i \n current_ORF = rest_of_ORF(dna[start_place:])\n i += 3 + len(current_ORF)\n ORF_list.append(current_ORF) \n return ORF_list","def test_fetch_open_frame(self):\n import requests\n pesummary_data = StrainData.fetch_open_frame(\n \"GW190412\", IFO=\"L1\", duration=32, sampling_rate=4096.,\n channel=\"L1:GWOSC-4KHZ_R1_STRAIN\", format=\"hdf5\"\n )\n N = len(pesummary_data)\n np.testing.assert_almost_equal(N * pesummary_data.dt.value, 32.)\n np.testing.assert_almost_equal(1. / pesummary_data.dt.value, 4096.)\n assert pesummary_data.IFO == \"L1\"\n _data = requests.get(\n \"https://www.gw-openscience.org/eventapi/html/GWTC-2/GW190412/v3/\"\n \"L-L1_GWOSC_4KHZ_R1-1239082247-32.gwf\"\n )\n with open(\"L-L1_GWOSC_4KHZ_R1-1239082247-32.gwf\", \"wb\") as f:\n f.write(_data.content)\n data2 = TimeSeries.read(\n \"L-L1_GWOSC_4KHZ_R1-1239082247-32.gwf\",\n channel=\"L1:GWOSC-4KHZ_R1_STRAIN\"\n )\n np.testing.assert_almost_equal(pesummary_data.value, data2.value)\n np.testing.assert_almost_equal(\n pesummary_data.times.value, data2.times.value\n )","def test_all_documents(self):","def test_everything(self):\n\n qs = FBO(\n path=TEST_FILES_ROOT,\n ).exclude(\n name__glob='*~',\n ).exclude(\n name__glob='*.meta',\n )\n\n self.assertEqual(\n 7,\n qs.count(),\n )\n self.assertEqual(\n {\n 'index.md',\n 'subdir/index.md',\n 'test1.md',\n 'test2.md',\n 'test1.rst',\n 'test2.rst',\n 'test3.rst',\n },\n {o.name for o in qs},\n )","def test_search_or(self):\n pkgs = [\n make_package(factory=SQLPackage),\n make_package(\n \"somepackage\",\n version=\"1.3\",\n filename=\"mypath3\",\n summary=\"this is mypkg\",\n factory=SQLPackage,\n ),\n make_package(\"mypkg2\", \"1.3.4\", \"my/other/path\", factory=SQLPackage),\n make_package(\"package\", factory=SQLPackage),\n ]\n for pkg in pkgs:\n self.db.save(pkg)\n criteria = {\"name\": [\"mypkg\"], \"summary\": [\"mypkg\"]}\n packages = self.db.search(criteria, \"or\")\n self.assertCountEqual(packages, pkgs[:-1])","def rest_of_ORF_unit_tests():\n input_a='ATTCATTAG'\n expected_output='ATTCAT'\n actual_output=rest_of_ORF(input_a)\n print 'Expected Output is ' + expected_output\n print 'Actual Output is ' +actual_output\n \n input_a='ATTCATCATCATCATTAG'\n expected_output='ATTCATCATCATCAT'\n actual_output=rest_of_ORF(input_a)\n print 'Expected Output is ' + expected_output\n print 'Actual Output is ' +actual_output","def test_get_records(self):\n pass","def test_organization_all(self):\n gryffindor = models.Organization(name='gryffindor')\n ravenclaw = models.Organization(name='ravenclaw')\n db.session.add(gryffindor)\n db.session.add(ravenclaw)\n db.session.commit()\n # scenario 1: when neither buids nor names are given\n self.assertEqual(models.Organization.all(), [])\n # scenario 2: when buids are passed\n orglist = [gryffindor, ravenclaw]\n orgids = [gryffindor.buid, ravenclaw.buid]\n all_by_buids = models.Organization.all(buids=orgids)\n self.assertIsInstance(all_by_buids, list)\n self.assertCountEqual(all_by_buids, orglist)\n # scenario 3: when org names are passed\n names = [gryffindor.name, ravenclaw.name]\n all_by_names = models.Organization.all(names=names)\n self.assertIsInstance(all_by_names, list)\n self.assertCountEqual(all_by_names, orglist)\n # scenario 4: when defercols is set to True for names\n all_by_names_with_defercols = models.Organization.all(names=names)\n self.assertIsInstance(all_by_names_with_defercols, list)\n self.assertCountEqual(all_by_names_with_defercols, orglist)\n # scenario 5: when defercols is set to True for buids\n all_by_buids_with_defercols = models.Organization.all(buids=orgids)\n self.assertIsInstance(all_by_buids_with_defercols, list)\n self.assertCountEqual(all_by_buids_with_defercols, orglist)","def find_all_ORFs_oneframe(dna):\n x = 3\n list_of_dna = []\n while (x < len(dna)):\n if dna[x-3:x] == 'ATG':\n current_dna = rest_of_ORF(dna[x-3:])\n list_of_dna.append(current_dna)\n x += len(current_dna)\n x += 3\n return list_of_dna","def find_all_ORFs_oneframe(dna):\n strand = []\n startCodon = [\"ATG\"]\n for i in range(0,len(dna),3):\n triple = dna[i:i+3]\n if triple in startCodon: \n strand.append(rest_of_ORF(dna[i:]))\n print strand\n return strand","def test_get_foods(self):\n pass","def test_find_all(self):\n result = Project.objects.find(['test'], project_type=None)\n self.assertEqual(len(result), 2)\n result = Project.objects.find(['ThisFails'], project_type=None)\n self.assertEqual(len(result), 0)","def find_all_ORFs(dna):\n #inital conditions\n i = 0\n start_codon = ('ATG')\n end_index = len(dna)\n return_variable = []\n\n #for statement tells the code to run three times at three inital index values\n #0,1,and 2 which allows for each reading frame to be read\n for i in range (3):\n while i < (len(dna)-2):\n codon = dna[i:i+3] \n if codon in start_codon: #check if the codon the code is looking at is a start codon\n orf = rest_of_ORF(dna[i:]) #then determine that this is an orf, make it a string given the index of the start codon\n return_variable.append(orf) #and append said string to a list of ORFs\n i += len(orf) \n i += 3\n #return a list of strings of DNA from both strands\n return return_variable","def test_all_finder_methods(self):\n methods = ['all', 'first', 'find']\n\n for method in methods:\n result = getattr(self.Test, method)\n self.assertEqual(type(result).__name__, 'instancemethod')\n self.assertEqual(result.im_class.__name__, 'Relation')","def test_return_all(self):\n self.data.return_all()","def test_search_or(self):\n pkgs = [\n make_package(factory=SQLPackage),\n make_package(\n \"somepackage\",\n version=\"1.3\",\n filename=\"mypath3\",\n summary=\"this is mypkg\",\n factory=SQLPackage,\n ),\n make_package(\"mypkg2\", \"1.3.4\", \"my/other/path\", factory=SQLPackage),\n make_package(\"package\", factory=SQLPackage),\n ]\n self.sql.add_all(pkgs)\n criteria = {\"name\": [\"mypkg\"], \"summary\": [\"mypkg\"]}\n packages = self.db.search(criteria, \"or\")\n self.assertCountEqual(packages, pkgs[:-1])","def test_multiple(self):\n\n with self.assertRaises(MultipleObjectsReturned):\n RST_FBO().get()","def test_get_foods_list(self):\n pass","def test_query_algorithms_ORqueryfrom200Algorithms(self):\n query_string = 'displayName102 OR algorithmId23'\n upload_data_list = []\n create_test_algorithm_list(upload_data_list, 200)\n documents = []\n create_test_documents_list(upload_data_list, documents, 200)\n index = search.Index(name=search_algorithm._INDEX_STRING)\n index.put(documents)\n # end of data preparation\n numbers = ['23', '102']\n right_answer_list = []\n for number in numbers:\n data = {}\n data['algorithmId'] = 'algorithmId' + number\n data['algorithmSummary'] = 'algorithmSummary' + number\n data['displayName'] = 'displayName' + number\n data['linkURL'] = 'linkURL' + number\n right_answer_list.append(data)\n # end right answer list preparation\n result = search_algorithm.query_algorithms(index, query_string)\n self.assertEqual(len(right_answer_list), len(result), msg='Wrong number of algorithms')\n self.assertItemsEqual(right_answer_list, result, msg='Discrepancy in returned algorithms')","def test_get_df(mocker):\n spy_load_metadata = mocker.spy(MetaData, 'load_document')\n expected_df = pd.read_json('tests/odata/fixtures/records.json', orient='records')\n\n provider = ODataConnector(\n name='test',\n baseroute='http://services.odata.org/V4/Northwind/Northwind.svc/',\n auth={'type': 'basic', 'args': ['u', 'p']},\n )\n\n data_source = ODataDataSource(\n domain='test',\n name='test',\n entity='Orders',\n query={\n '$filter': \"ShipCountry eq 'France'\",\n '$orderby': 'Freight desc',\n '$skip': 50,\n '$top': 3,\n },\n )\n\n try:\n df = provider.get_df(data_source)\n sl = ['CustomerID', 'EmployeeID', 'Freight']\n assert df[sl].equals(expected_df[sl])\n except socket.error:\n pytest.skip('Could not connect to the standard example OData service.')\n\n assert spy_load_metadata.call_count == 1\n args, _ = spy_load_metadata.call_args\n assert args[0].url.endswith('/$metadata')\n\n provider.auth = None\n try:\n provider.get_df(data_source)\n except socket.error:\n pytest.skip('Could not connect to the standard example OData service.')","def test_ipam_vrfs_list(self):\n pass","def test_get_list8(self):\n pass","def getORFs(catFile, queryName, geneDir):\n\n\toutORFraw = geneDir+catFile.split(\"/\")[-1].split(\".\")[0]+\"_allORFs.fasta\"\n\tlogger = logging.getLogger(\"main.orf\")\n\t\n\tlogger.debug(\"getorf -sequence {:s} -outseq {:s} -table 0 -find 3 -noreverse\".format(catFile, outORFraw))\n\tcmd(\"getorf -sequence {:s} -outseq {:s} -table 0 -find 3 -noreverse\".format(catFile, outORFraw), False)\n\t\n\tdId2ORFs = defaultdict(list)\n\tf = SeqIO.parse(open(outORFraw),'fasta')\n\tfor fasta in f:\n\t\tfname, fseq = fasta.id, str(fasta.seq)\n\t\tif len(fname.split(\"_\")) > 2:\n\t\t\tfname2 = \"_\".join(fname.split(\"_\")[0:-1])\n\t\telse:\n\t\t\tfname2 = fname.split(\"_\")[0]\n\t\tdId2ORFs[fname2].append(fseq)\n\t\n\tdId2Longest = {}\n\tfor k, v in dId2ORFs.items():\n\t\tdId2Longest[k] = max(v, key=len)\n\t\t\n\t# delete duplicate sequences\n\tdRev = {}\n\tfor k, v in dId2Longest.items():\n\t\tdRev.setdefault(v, set()).add(k)\n\t\t\n\tAllDupl = [values for key, values in dRev.items() if len(values) > 1]\n\tn = 0\n\tfor dupl in AllDupl:\n\t\tspecies = set([x.split(\"_\")[0] for x in dupl])\n\t\t\n\t\tfor sp in species:\n\t\t\tif queryName in dupl:\n\t\t\t\tfirstOcc = queryName\n\t\t\telse:\n\t\t\t\tlOcc = [x for x in dupl if sp in x]\n\t\t\t\t\n\t\t\t\tif len(lOcc) > 0:\n\t\t\t\t\tfirstOcc = lOcc[0]\n\t\t\t\telse:\n\t\t\t\t\tfirstOcc = str(lOcc)\n\t\t\t\t\t\n\t\t\tdupl.remove(firstOcc)\n\t\t\n\t\tfor i in dupl:\n\t\t\tdId2Longest.pop(i, None)\n\t\t\tn += 1\n\t\t\tlogger.debug(\"Deleted sequence {:s} (duplicate)\".format(i))\n\t\t\n\tlogger.info(\"Deleted {} sequences as duplicates\".format(n))\n\t\n\toutORF = outORFraw.replace(\"_allORFs.fasta\",\"_longestORFs.fasta\")\n\n\twith open(outORF, \"w\") as outO:\n\t outO.write(FastaResFunc.dict2fasta(dId2Longest))\n\t outO.close()\n\t \n\tlogger.info(\"Extracted longest ORFs: {:s}\".format(outORF))\n\n\treturn(outORF)","def test_create_doc(self):\r\n function_name = sys._getframe().f_code.co_name\r\n db_name = \"{}_{}\".format(function_name, \"db\")\r\n db_name_illegal_by_rdb = \"{}_{}\".format(\r\n db_name,\r\n self.ILLEGAL_BY_RDB\r\n )\r\n db_name_illegal_by_this_program = \"{}_{}\".format(\r\n db_name,\r\n self.ILLEGAL_BY_THIS_PROGRAM\r\n )\r\n table_name = \"{}_{}\".format(function_name, \"table\")\r\n table_name_illegal_by_rdb = \"{}_{}\".format(\r\n table_name,\r\n self.ILLEGAL_BY_RDB\r\n )\r\n table_name_illegal_by_this_program = \"{}_{}\".format(\r\n table_name,\r\n self.ILLEGAL_BY_THIS_PROGRAM\r\n )\r\n doc_1 = {\"name\": \"alpha\", \"no\":\"1\"}\r\n doc_2 = {\"name\": \"beta\", \"no\":\"2\"}\r\n doc_3 = {\"name\": \"charlie\", \"no\":\"1\"}\r\n doc_4 = {\"name\": \"charlie\", \"no\":\"3\"}\r\n\r\n test_list_1 = [\r\n db_name,\r\n table_name,\r\n doc_1,\r\n [\"no\"],\r\n False,\r\n None,\r\n None,\r\n False\r\n ]\r\n test_list_2 = [\r\n test_list_1[0],\r\n test_list_1[1],\r\n doc_2,\r\n [\"no\"],\r\n None\r\n ]\r\n test_list_3 = [\r\n test_list_1[0],\r\n test_list_1[1],\r\n doc_3,\r\n [\"no\"],\r\n None\r\n ]\r\n test_list_4 = [\r\n test_list_1[0],\r\n test_list_1[1],\r\n doc_4,\r\n [\"name\", \"no\"],\r\n None\r\n ]\r\n test_list_5 = [\r\n db_name_illegal_by_rdb,\r\n table_name_illegal_by_rdb,\r\n doc_1,\r\n None\r\n ]\r\n test_list_6 = [\r\n db_name_illegal_by_rdb,\r\n table_name_illegal_by_this_program,\r\n doc_1,\r\n None\r\n ]\r\n test_list_7 = [\r\n db_name_illegal_by_this_program,\r\n table_name_illegal_by_rdb,\r\n doc_1,\r\n None\r\n ]\r\n test_list_8 = [\r\n db_name_illegal_by_this_program,\r\n table_name_illegal_by_this_program,\r\n doc_1,\r\n None\r\n ]\r\n\r\n crd(self.c, test_list_1[0])\r\n crt(self.c, test_list_1[1], test_list_1[0])\r\n test_list_1[len(test_list_1) - 1] = isinstance(\r\n crdoc(\r\n self.c,\r\n test_list_1[2],\r\n test_list_1[1],\r\n test_list_1[0],\r\n _expr=True\r\n ),\r\n r.ast.Insert\r\n )\r\n test_list_1[len(test_list_1) - 2] = crdoc(\r\n self.c,\r\n test_list_1[2],\r\n test_list_1[1],\r\n test_list_1[0]\r\n )\r\n test_list_1[len(test_list_1) - 3] = crdoc(\r\n self.c,\r\n test_list_1[2],\r\n test_list_1[1],\r\n test_list_1[0],\r\n test_list_1[3]\r\n )\r\n test_list_1[len(test_list_1) - 4] = isinstance(\r\n crdoc(\r\n self.c,\r\n test_list_1[2],\r\n test_list_1[1],\r\n test_list_1[0],\r\n [\"name\", \"no\"],\r\n True\r\n ),\r\n r.ast.Insert\r\n )\r\n test_list_2[len(test_list_2) - 1] = crdoc(\r\n self.c,\r\n test_list_2[2],\r\n test_list_2[1],\r\n test_list_2[0],\r\n test_list_2[3]\r\n )\r\n crt(self.c, test_list_3[1], test_list_3[0])\r\n test_list_3[len(test_list_3) - 1] = crdoc(\r\n self.c,\r\n test_list_3[2],\r\n test_list_3[1],\r\n test_list_3[0],\r\n test_list_3[3]\r\n )\r\n test_list_4[len(test_list_4) - 1] = crdoc(\r\n self.c,\r\n test_list_4[2],\r\n test_list_4[1],\r\n test_list_4[0],\r\n test_list_4[3]\r\n )\r\n dd(self.c, test_list_1[0])\r\n\r\n \"\"\"Test 1.\"\"\"\r\n with self.assertWarns(CDW):\r\n test_list_5[len(test_list_5) - 1] = crdoc(\r\n self.c,\r\n test_list_5[2],\r\n test_list_5[1],\r\n test_list_5[0]\r\n )\r\n\r\n \"\"\"Test 2.\"\"\"\r\n with self.assertWarns(CDW):\r\n test_list_6[len(test_list_6) - 1] = crdoc(\r\n self.c,\r\n test_list_6[2],\r\n test_list_6[1],\r\n test_list_6[0]\r\n )\r\n\r\n r.db_create(test_list_7[0]).run(self.c)\r\n \"\"\"Test 3.\"\"\"\r\n with self.assertWarns(CDW):\r\n test_list_7[len(test_list_7) - 1] = crdoc(\r\n self.c,\r\n test_list_7[2],\r\n test_list_7[1],\r\n test_list_7[0]\r\n )\r\n r.db_drop(test_list_7[0]).run(self.c)\r\n\r\n r.db_create(test_list_8[0]).run(self.c)\r\n r.db(test_list_8[0]).table_create(test_list_8[0]).run(self.c)\r\n \"\"\"Test 4.\"\"\"\r\n with self.assertWarns(CDW):\r\n test_list_8[len(test_list_8) - 1] = crdoc(\r\n self.c,\r\n test_list_8[2],\r\n test_list_8[1],\r\n test_list_8[0]\r\n )\r\n r.db_drop(test_list_8[0]).run(self.c)\r\n\r\n self.assertTrue(test_list_1[len(test_list_1) - 1]) # Test 5.\r\n self.assertIsNotNone(test_list_1[len(test_list_1) - 2]) # Test 6.\r\n self.assertIsNone(test_list_1[len(test_list_1) - 3]) # Test 7.\r\n self.assertFalse(test_list_1[len(test_list_1) - 4]) # Test 8\r\n self.assertIsNotNone(test_list_2[len(test_list_2) - 1]) # Test 9.\r\n self.assertIsNone(test_list_3[len(test_list_3) - 1]) # Test 10.\r\n self.assertIsNotNone(test_list_4[len(test_list_4) - 1]) # Test 11.\r\n self.assertIsNone(test_list_5[len(test_list_5) - 1]) # Test 12.\r\n self.assertIsNone(test_list_6[len(test_list_6) - 1]) # Test 13.\r\n self.assertIsNone(test_list_7[len(test_list_7) - 1]) # Test 14.\r\n self.assertIsNone(test_list_8[len(test_list_8) - 1]) # Test 15.\r","def longest_ORF_unit_tests():\n\n # YOUR IMPLEMENTATION HERE","def longest_ORF_unit_tests():\n\n # YOUR IMPLEMENTATION HERE","def test_get_bios_unit_list(self):\n pass","def test_data_object_get_names_all(self):\n pass","def test_find_all(self):\n\n # Test valid empty inputs\n\n self.assertEqual(find_all(None, None), [])\n self.assertEqual(find_all('', None), [])\n self.assertEqual(find_all(None, ''), [])\n\n self.assertEqual(find_all(b'', b''), [])\n self.assertEqual(find_all(b'', ''), [])\n\n self.assertEqual(find_all('', b''), [])\n self.assertEqual(find_all('', ''), [])\n\n # Test with missing or invalid inputs\n\n self.assertEqual(find_all('abc', '123'), [])\n self.assertEqual(find_all('abc', 'abcabc'), [])\n\n self.assertEqual(find_all('abc', 'abc', limit=0), [])\n self.assertEqual(find_all('abc', 'abc', limit=0, reverse=True), [])\n self.assertEqual(find_all('abc', 'abc', limit=0, start=0, end=3), [])\n self.assertEqual(find_all('abc', 'abc', limit=0, start=0, end=3, reverse=True), [])\n\n self.assertEqual(find_all('abc', 'abc', start=3, end=0), [])\n self.assertEqual(find_all('abc', 'abc', start=3, end=0, limit=1), [])\n self.assertEqual(find_all('abc', 'abc', start=3, end=0, reverse=True), [])\n self.assertEqual(find_all('abc', 'abc', start=3, end=0, limit=1, reverse=True), [])\n\n # Test with valid, non-empty inputs\n\n self._test_find_all(\n s='ab?cdef?ghijkl?mnopqrstuv?wxy?z?',\n sub='?',\n out=[2, 7, 14, 25, 29, 31]\n )\n self._test_find_all(\n s='ab??cdef??ghijkl??mnopqrstuv??wxy??z??',\n sub='??',\n out=[2, 8, 16, 28, 33, 36]\n )\n self._test_find_all(\n s='ab???cdef???ghijkl???mnopqrstuv???wxy???z???',\n sub='???',\n out=[2, 9, 18, 31, 37, 41]\n )","def test_fetch_all():\n response = requests.get('http://localhost:5000/api/persons')\n data = response.json()\n\n assert response.status_code == 200\n for field in FIELDS:\n assert field in data[0]","def test_search_or(self):\n pkgs = [\n make_package(factory=DynamoPackage),\n make_package(\n \"somepackage\",\n version=\"1.3\",\n filename=\"mypath3\",\n summary=\"this is mypkg\",\n factory=DynamoPackage,\n ),\n make_package(\"mypkg2\", \"1.3.4\", \"my/other/path\", factory=DynamoPackage),\n make_package(\"package\", factory=DynamoPackage),\n ]\n self._save_pkgs(*pkgs)\n criteria = {\"name\": [\"mypkg\"], \"summary\": [\"mypkg\"]}\n packages = self.db.search(criteria, \"or\")\n self.assertCountEqual(packages, pkgs[:-1])","def test_all_filter_op_fields(self):\n for field in OCIFilterSerializer._opfields:\n field = \"and:\" + field\n filter_param = {field: [\"1\", \"2\"]}\n serializer = OCIFilterSerializer(data=filter_param)\n self.assertTrue(serializer.is_valid())\n for field in OCIFilterSerializer._opfields:\n field = \"or:\" + field\n filter_param = {field: [\"1\", \"2\"]}\n serializer = OCIFilterSerializer(data=filter_param)\n self.assertTrue(serializer.is_valid())","def test_run_all_searches(): # ***Incomplete test\n ##########################\n # Arrange.\n query_file_list = \"query_file_list\"\n\n ##########################\n # Act.\n #x = run_all_searches(query_file_list)\n\n ##########################\n # Assert.\n assert True == True # ***Temporary.","def test():\n\t\treturn [\"vice.core.dataframe\",\n\t\t\t[\n\t\t\t\ttests.test(run = False),\n\t\t\t\t_builtin_dataframes.test(run = False)\n\t\t\t]\n\t\t]","def test_eia860_output(live_pudl_db, start_date_eia923, end_date_eia923):\n testing = (not live_pudl_db)\n dates = [(None, None), (start_date_eia923, end_date_eia923)]\n print('\\n')\n for (start_date, end_date) in dates:\n print(\"start_date={}, end_date={}\". format(start_date, end_date))\n utils_out = outputs.utilities_eia860(testing=testing,\n start_date=start_date,\n end_date=end_date)\n print(\" utils_eia860: {} records found\".format(len(utils_out)))\n\n plants_out = outputs.plants_eia860(testing=testing,\n start_date=start_date,\n end_date=end_date)\n print(\" plants_eia860: {} records found\".format(len(plants_out)))\n\n gens_out = outputs.generators_eia860(testing=testing,\n start_date=start_date,\n end_date=end_date)\n print(\" gens_eia860: {} records found\".format(len(gens_out)))\n\n own_out = outputs.ownership_eia860(testing=testing,\n start_date=start_date,\n end_date=end_date)\n print(\" own_eia860: {} records found\".format(len(own_out)))","def test_get_data_for_specific_dates(self):\n # setup\n start_date = \"3/10/2019\"\n end_date = \"15/10/2019\"\n result = {\"abs_pressure\": 100, \"hum_in\": 20}\n\n start_dt = datetime.datetime.strptime(start_date, \"%d/%m/%Y\")\n end_dt = datetime.datetime.strptime(end_date, \"%d/%m/%Y\")\n\n start = int((start_dt - datetime.datetime.fromtimestamp(0)).total_seconds())\n end = int((end_dt - datetime.datetime.fromtimestamp(0)).total_seconds())\n\n mocked_conn = Mock(wrap=sqlite3.Connection)\n mocked_cursor = Mock(wraps=sqlite3.Cursor)\n\n # operation\n with patch.object(\n self.db, \"db_connection\", return_value=mocked_conn\n ) as mock_conn:\n with patch.object(\n mocked_conn, \"cursor\", return_value=mocked_cursor\n ) as mock_curs:\n with patch.object(mocked_cursor, \"execute\") as mock_exe:\n with patch.object(\n mocked_cursor, \"fetchall\", return_value=result\n ) as mock_fetchall:\n with patch.object(mocked_cursor, \"close\") as mock_cur_close:\n with patch.object(mocked_conn, \"close\") as mock_con_close:\n actual_result = self.db.get_data_for_specific_dates(\n start_date, end_date\n )\n\n # after\n mock_conn.assert_called_once()\n mock_curs.assert_called_once()\n mock_fetchall.assert_called_once()\n mock_exe.assert_any_call(\n \"SELECT * FROM data WHERE idx BETWEEN ? AND ?\",\n (str(start), str(end)),\n )\n mock_cur_close.assert_called_once()\n mock_con_close.assert_called_once()\n assert actual_result == result","def test_get_table_list(self):\n db_introspection = DatabaseIntrospection(self.connection)\n cursor = mock.MagicMock()\n\n def list_tables(*args, **kwargs):\n return [[\"Table_1\", \"t\"], [\"Table_2\", \"t\"]]\n\n cursor.run_sql_in_snapshot = list_tables\n table_list = db_introspection.get_table_list(cursor=cursor)\n self.assertEqual(\n table_list,\n [\n TableInfo(name=\"Table_1\", type=\"t\"),\n TableInfo(name=\"Table_2\", type=\"t\"),\n ],\n )","def test_ocas():\n path_here = Path(__file__).resolve().parent\n for dirpath, _, filenames in os.walk(path_here):\n fns_oca = [fn for fn in filenames if fn.endswith(\".oca\")]\n fns_oca.sort(key=lambda fn: fn != 'foundproblems.oca')\n for fn_oca in fns_oca:\n print()\n print(fn_oca)\n do_test_oca_file(os.path.join(dirpath, fn_oca))","def test_fetchall(self):\n result = export.processExport(houseId=1)\n #We should have 2 locations * 1 sensor * 10 days of data here\n # 2 * 1 * (288 * 10) == 5670\n #print result.shape\n\n #result.to_csv(\"temp.csv\")\n #Do we get the right object\n self.assertEqual(type(result), pandas.DataFrame)\n #And is it the right size\n self.assertEqual(result.shape, (2880, 2)) #So 2880 samples from two sensors\n #And the right range of data\n self.assertEqual(result.index[0], datetime.datetime(2013, 01, 01))\n self.assertEqual(result.index[-1], datetime.datetime(2013, 01, 10, 23, 55))","def object_finder(\n self, datatable, objectlist, ralist, declist, radius,\n longquery=True\n ):\n pass","def test_get_waivers(league):\n pass","def query_and_read_frame(frame_type, channels, start_time, end_time):\n logging.info('querying datafind server')\n paths = frame_paths(frame_type, start_time, end_time)\n logging.info('found files: %s' % (' '.join(paths)))\n return read_frame(paths, channels, \n start_time=start_time, \n end_time=end_time)","def test_frame_to_rows(self):\n pass","def test_do_select_all(test_dao):\r\n DUT = dtmFunction(test_dao, test=True)\r\n\r\n assert DUT.do_select_all(revision_id=1) is None\r\n assert isinstance(DUT.tree, Tree)\r\n assert isinstance(DUT.tree.get_node(1).data, RAMSTKFunction)","def test_FRAME_DUoperations():\n tmFrame0 = CCSDS.FRAME.TMframe()\n print(\"tmFrame0 =\", tmFrame0)\n print(\"\")\n tmFrame1 = CCSDS.FRAME.TMframe(testData.TM_FRAME_01)\n print(\"tmFrame1 =\", tmFrame1)\n if tmFrame1.versionNumber != testData.TM_FRAME_01_versionNumber:\n print(\"tmFrame1 versionNumber wrong:\", tmFrame1.versionNumber, \"- should be\", testData.TM_FRAME_01_versionNumber)\n return False\n if tmFrame1.spacecraftId != testData.TM_FRAME_01_spacecraftId:\n print(\"tmFrame1 spacecraftId wrong:\", tmFrame1.spacecraftId, \"- should be\", testData.TM_FRAME_01_spacecraftId)\n return False\n if tmFrame1.virtualChannelId != testData.TM_FRAME_01_virtualChannelId:\n print(\"tmFrame1 virtualChannelId wrong:\", tmFrame1.virtualChannelId, \"- should be\", testData.TM_FRAME_01_virtualChannelId)\n return False\n if tmFrame1.operationalControlField != testData.TM_FRAME_01_operationalControlField:\n print(\"tmFrame1 operationalControlField wrong:\", tmFrame1.operationalControlField, \"- should be\", testData.TM_FRAME_01_operationalControlField)\n return False\n if tmFrame1.masterChannelFrameCount != testData.TM_FRAME_01_masterChannelFrameCount:\n print(\"tmFrame1 masterChannelFrameCount wrong:\", tmFrame1.masterChannelFrameCount, \"- should be\", testData.TM_FRAME_01_masterChannelFrameCount)\n return False\n if tmFrame1.virtualChannelFCountLow != testData.TM_FRAME_01_virtualChannelFCountLow:\n print(\"tmFrame1 virtualChannelFCountLow wrong:\", tmFrame1.virtualChannelFCountLow, \"- should be\", testData.TM_FRAME_01_virtualChannelFCountLow)\n return False\n if tmFrame1.secondaryHeaderFlag != testData.TM_FRAME_01_secondaryHeaderFlag:\n print(\"tmFrame1 secondaryHeaderFlag wrong:\", tmFrame1.secondaryHeaderFlag, \"- should be\", testData.TM_FRAME_01_secondaryHeaderFlag)\n return False\n if tmFrame1.synchronisationFlag != testData.TM_FRAME_01_synchronisationFlag:\n print(\"tmFrame1 synchronisationFlag wrong:\", tmFrame1.synchronisationFlag, \"- should be\", testData.TM_FRAME_01_synchronisationFlag)\n return False\n if tmFrame1.packetOrderFlag != testData.TM_FRAME_01_packetOrderFlag:\n print(\"tmFrame1 packetOrderFlag wrong:\", tmFrame1.packetOrderFlag, \"- should be\", testData.TM_FRAME_01_packetOrderFlag)\n return False\n if tmFrame1.segmentLengthId != testData.TM_FRAME_01_segmentLengthId:\n print(\"tmFrame1 segmentLengthId wrong:\", tmFrame1.segmentLengthId, \"- should be\", testData.TM_FRAME_01_segmentLengthId)\n return False\n if tmFrame1.firstHeaderPointer != testData.TM_FRAME_01_firstHeaderPointer:\n print(\"tmFrame1 firstHeaderPointer wrong:\", tmFrame1.firstHeaderPointer, \"- should be\", testData.TM_FRAME_01_firstHeaderPointer)\n return False\n # extract packets and check it\n leadingFragment, packets, trailingFragment = tmFrame1.getPackets()\n if leadingFragment != testData.TM_FRAME_01_leadingFragment:\n print(\"tmFrame1 leadingFragment wrong:\", leadingFragment, \"- should be\", testData.TM_FRAME_01_leadingFragment)\n return False\n if len(packets) != testData.TM_FRAME_01_nrPackets:\n print(\"tmFrame1 nr. of packets wrong:\", len(packets), \"- should be\", testData.TM_FRAME_01_nrPackets)\n return False\n if trailingFragment != testData.TM_FRAME_01_trailingFragment:\n print(\"tmFrame1 trailingFragment wrong:\", trailingFragment, \"- should be\", testData.TM_FRAME_01_trailingFragment)\n return False\n print(\"\")\n tcFrame1 = CCSDS.FRAME.TCframe(testData.TC_FRAME_01)\n print(\"tcFrame1 =\", tcFrame1)\n if tcFrame1.versionNumber != testData.TC_FRAME_01_versionNumber:\n print(\"tcFrame1 versionNumber wrong:\", tcFrame1.versionNumber, \"- should be\", testData.TC_FRAME_01_versionNumber)\n return False\n if tcFrame1.reservedFieldB != testData.TC_FRAME_01_reservedFieldB:\n print(\"tcFrame1 reservedFieldB wrong:\", tcFrame1.reservedFieldB, \"- should be\", testData.TC_FRAME_01_reservedFieldB)\n return False\n if tcFrame1.virtualChannelId != testData.TC_FRAME_01_virtualChannelId:\n print(\"tcFrame1 virtualChannelId wrong:\", tcFrame1.virtualChannelId, \"- should be\", testData.TC_FRAME_01_virtualChannelId)\n return False\n if tcFrame1.controlCommandFlag != testData.TC_FRAME_01_controlCommandFlag:\n print(\"tcFrame1 controlCommandFlag wrong:\", tcFrame1.controlCommandFlag, \"- should be\", testData.TC_FRAME_01_controlCommandFlag)\n return False\n if tcFrame1.reservedFieldA != testData.TC_FRAME_01_reservedFieldA:\n print(\"tcFrame1 reservedFieldA wrong:\", tcFrame1.reservedFieldA, \"- should be\", testData.TC_FRAME_01_reservedFieldA)\n return False\n if tcFrame1.frameLength != testData.TC_FRAME_01_frameLength:\n print(\"tcFrame1 frameLength wrong:\", tcFrame1.frameLength, \"- should be\", testData.TC_FRAME_01_frameLength)\n return False\n if tcFrame1.sequenceNumber != testData.TC_FRAME_01_sequenceNumber:\n print(\"tcFrame1 sequenceNumber wrong:\", tcFrame1.sequenceNumber, \"- should be\", testData.TC_FRAME_01_sequenceNumber)\n return False\n if tcFrame1.spacecraftId != testData.TC_FRAME_01_spacecraftId:\n print(\"tcFrame1 spacecraftId wrong:\", tcFrame1.spacecraftId, \"- should be\", testData.TC_FRAME_01_spacecraftId)\n return False\n if tcFrame1.bypassFlag != testData.TC_FRAME_01_bypassFlag:\n print(\"tcFrame1 bypassFlag wrong:\", tcFrame1.bypassFlag, \"- should be\", testData.TC_FRAME_01_bypassFlag)\n return False\n tcFrame2 = CCSDS.FRAME.TCframe(testData.TC_FRAME_02)\n if tcFrame2.versionNumber != testData.TC_FRAME_02_versionNumber:\n print(\"tcFrame2 versionNumber wrong:\", tcFrame2.versionNumber, \"- should be\", testData.TC_FRAME_02_versionNumber)\n return False\n if tcFrame2.reservedFieldB != testData.TC_FRAME_02_reservedFieldB:\n print(\"tcFrame2 reservedFieldB wrong:\", tcFrame2.reservedFieldB, \"- should be\", testData.TC_FRAME_02_reservedFieldB)\n return False\n if tcFrame2.virtualChannelId != testData.TC_FRAME_02_virtualChannelId:\n print(\"tcFrame2 virtualChannelId wrong:\", tcFrame2.virtualChannelId, \"- should be\", testData.TC_FRAME_02_virtualChannelId)\n return False\n if tcFrame2.controlCommandFlag != testData.TC_FRAME_02_controlCommandFlag:\n print(\"tcFrame2 controlCommandFlag wrong:\", tcFrame2.controlCommandFlag, \"- should be\", testData.TC_FRAME_02_controlCommandFlag)\n return False\n if tcFrame2.reservedFieldA != testData.TC_FRAME_02_reservedFieldA:\n print(\"tcFrame2 reservedFieldA wrong:\", tcFrame2.reservedFieldA, \"- should be\", testData.TC_FRAME_02_reservedFieldA)\n return False\n if tcFrame2.frameLength != testData.TC_FRAME_02_frameLength:\n print(\"tcFrame2 frameLength wrong:\", tcFrame2.frameLength, \"- should be\", testData.TC_FRAME_02_frameLength)\n return False\n if tcFrame2.sequenceNumber != testData.TC_FRAME_02_sequenceNumber:\n print(\"tcFrame2 sequenceNumber wrong:\", tcFrame2.sequenceNumber, \"- should be\", testData.TC_FRAME_02_sequenceNumber)\n return False\n if tcFrame2.spacecraftId != testData.TC_FRAME_02_spacecraftId:\n print(\"tcFrame2 spacecraftId wrong:\", tcFrame2.spacecraftId, \"- should be\", testData.TC_FRAME_02_spacecraftId)\n return False\n if tcFrame2.bypassFlag != testData.TC_FRAME_02_bypassFlag:\n print(\"tcFrame2 bypassFlag wrong:\", tcFrame2.bypassFlag, \"- should be\", testData.TC_FRAME_02_bypassFlag)\n return False\n clcw = CCSDS.FRAME.CLCW()\n print(\"clcw =\", clcw)\n return True","def test_get_list(self):\n pass","def test_return_all_names(self):\n test = self.data.return_all(first_name='Nik', last_name='Silver')\n self.assertEqual(test[0].first_name, 'Nik')\n\n test_2 = self.data.return_all(first_name='Trevor', last_name='Harvey')\n self.assertEqual(test_2[0].last_name, 'Harvey')","def test_index(self):","def test_run_any_search(): # ***Incomplete test\n ##########################\n # Arrange.\n queryfile = \"queryfile\"\n\n ##########################\n # Act.\n #x = run_any_search(queryfile)\n\n ##########################\n # Assert.\n assert True == True # ***Temporary.","def all(self):","def all(self):","def test_findbymembers(self):\n p1, p2, p3 = self.create3persons()\n model.Team(name='Tigers', persons=[p1, p2, p3]).store()\n model.Team(name='Lions', persons=[p1,p2]).store()\n model.Team(name='Snakes', persons=[p2, p3]).store()\n\n teams = model.Team.find_teams_by_members(p1) # find all teams with p1 (2)\n self.assertEqual(len(teams), 2)","def test_get_file_accessors(self):\n pass"],"string":"[\n \"def find_all_ORFs_oneframe_unit_tests():\\n\\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n input_a='ATGATTATTTGATGAATGGATTGA'\\n expected_output='[ATGATTATT,ATGGAT]'\\n actual_output=find_all_ORFs_oneframe(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\\n \\n input_a='ATGGGATTGTTT'\\n expected_output='[ATGGATTGTTT]'\\n actual_output=find_all_ORFs_oneframe(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\",\n \"def find_all_ORFs_both_strands_unit_tests():\\n\\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n\\n input = [\\\"dna\\\"]\\n expected_output = [\\\"all non-nester ORFs\\\"]\\n actual = []\\n for k in input:\\n actual.append(find_all_ORFs_oneframe(k))\\n print input \\n print actual\\n print expected_output\",\n \"def find_all_ORFs_unit_tests():\\n print 'Begin Unit test Find_all_ORFs'\\n input_a='ATGCATGAATGTAGATGTAG'\\n expected_output='[ATGCATGAATGTAGATGTAG, ATGAATGTAGATGTAG, ATG, ATG]'\\n actual_output=find_all_ORFs(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\\n \\n input_a='ATGCATGAATGTAGATGCATCATTAG'\\n expected_output='[ATGCATGAATGTAGATGCATCATTAG, ATGAATGTAGATGCATCATTAG, ATG, ATGCATCAT]'\\n actual_output=find_all_ORFs(input_a)\\n print 'Expected Output is ' + expected_output\\n print \\\"actucal OUtput is\\\", actual_output\\n print 'ENd Unit test Find_all_ORFs'\",\n \"def find_all_ORFs_oneframe_unit_tests(dna, expected):\\n\\n print find_all_ORFs_oneframe(\\\"ATGCATGAATGTAGATAGATGTGCCC\\\")\\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + find_all_ORFs_oneframe(dna)\",\n \"def find_all_ORFs_oneframe(dna):\",\n \"def find_all_ORFs_unit_tests():\\n data_list = [\\n [\\\"ATGCATGAATGTAG\\\", [\\\"ATGCATGAATGTAG\\\", \\\"ATGAATGTAG\\\", \\\"ATG\\\"]],\\n [\\\"ATG\\\", [\\\"ATG\\\"]],\\n [\\\"AATG\\\", [\\\"ATG\\\"]],\\n [\\\"AAATG\\\", [\\\"ATG\\\"]],\\n [\\\"ATGATG\\\", [\\\"ATGATG\\\"]],\\n [\\\"ATATGGATTGA\\\", [\\\"ATGGAT\\\"]],\\n [\\\"ATGAGATTAG\\\", [\\\"ATGAGATTAG\\\"]],\\n [\\\"ATATGGATTAGTAGTAATGAAAGTATAG\\\", [\\\"ATGAAAGTA\\\", \\\"ATGGAT\\\", ]],\\n# ATA TGG ATT AGT AGT AAT GAA AGT ATA G\\n# TAT GGA TTA GTA GTA ATG AAA GTA TAG\\n# ATG GAT TAG TAG TAA TGA AAG TAT AG\\n [\\\"ATGTCACGCAATGTAGGATGGATGGATTAGAC\\\", [\\\"ATGTCACGCAATGTAGGATGGATGGAT\\\", \\\"ATG\\\", \\\"ATGGATGGATTAGAC\\\"]],\\n# ATG TCA CGC AAT GTA GGA TGG ATG GAT TAG AC --> ATG TCA CGC AAT GTA GGA TGG ATG GAT\\n# TGT CAC GCA ATG TAG GAT GGA TGG ATT AGA C\\n# GTC ACG CAA TGT AGG ATG GAT GGA TTA GAC\\n [\\\"ATGATGTAG\\\", [\\\"ATGATG\\\"]],\\n [\\\"TCGATGC\\\", [\\\"ATGC\\\"]],\\n [\\\"AAA\\\", []],\\n# TCG ATG C\\n# CGA TGC\\n# GAT GC\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\",\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = find_all_ORFs(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def find_all_ORFs_unit_tests():\\n \\n print \\\"input: ATGCTA, \\\"+\\\"output: \\\"+ \\\",\\\".join(find_all_ORFs(\\\"ATGCTA\\\"))+\\\", actual output: CTA\\\"\\n print \\\"input: GTCACTTATGGGTTT, \\\"+\\\"output: \\\"+\\\",\\\".join(find_all_ORFs(\\\"ATGGATGCTTAGGGATGTTT\\\"))+\\\", actual output: GTCACT,GGTTTT,TCACTTAGGGTTTT,CACTTAGGGTTTT\\\"\\n print \\\"input: AAATTTTATAATGGGTGAAGTTAG, \\\"+\\\"output: \\\"+\\\",\\\".join(find_all_ORFs(\\\"AAATTTTATAATGGGTGAAGTTAG\\\"))+\\\", actual output: ATGGGTGAAGTT\\\"\\n print \\\"input: TATATGGAGGATAATAGTTGATAATAG, \\\"+\\\"output: \\\"+ \\\",\\\".join(find_all_ORFs(\\\"TATATGGAGGATAATAGTTGATAATAG\\\"))+\\\", actual output: ATGGAGGATAATAGT\\\"\",\n \"def find_all_ORFs_unit_tests():\\n \\n input = [\\\"dna\\\"]\\n expected_output = [\\\"all non-nested ORFs\\\"]\\n actual = []\\n for k in input:\\n actual.append(find_all_ORFs(k))\\n print input \\n print actual\\n print expected_output\",\n \"def find_all_ORFs(dna):\\n all_ORFs=[]\\n for i in range (0,3):\\n \\tframe=dna[i:] \\n all_ORFs+=find_all_ORFs_oneframe(frame)\\n return all_ORFs\",\n \"def find_all_ORFs(dna):\\n ans = find_all_ORFs_oneframe(dna)\\n ans.extend(find_all_ORFs_oneframe(dna[1:]))\\n ans.extend(find_all_ORFs_oneframe(dna[2:]))\\n return ans\",\n \"def find_all_ORFs_both_strands_unit_tests():\\n print ''\\n print 'Begin Unit test Find_all_ORFs both tests'\\n input_a='ATGCGAGGGTAGATGGATTAG'\\n expected_output='[ATGCGAGGG, ATGGAT]'\\n actual_output=find_all_ORFs_both_strands(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\\n \\n \\n input_a='ATGCGAATGTAGCATCAAATAGATGTAG'\\n expected_output='[ATGCGAATG, ATG, ATGCTACATTCGCAT]'\\n actual_output=find_all_ORFs_both_strands(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output \\n print 'end'\\n print ''\",\n \"def find_all_ORFs(dna):\\n all_ORFs = []\\n i = 0\\n\\n for i in range (0,3): \\n all_ORFs.extend(find_all_ORFs_oneframe(dna))\\n dna = 'X' + dna\\n\\n return all_ORFs\",\n \"def find_all_ORFs_unit_tests(dna, expected):\\n \\n print find_all_ORFs(\\\"ATGCATGAATGTAG\\\")\\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + find_all_ORFs(dna)\",\n \"def find_all_ORFs(dna):\\n #these functions offset to analyze each each open frame reference\\n zero_offset=find_all_ORFs_oneframe(dna[0:])\\n \\n one_offset=find_all_ORFs_oneframe(dna[1:])\\n \\n two_offset=find_all_ORFs_oneframe(dna[2:])\\n \\n return zero_offset+one_offset+two_offset\\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs(dna):\\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs(dna):\\n index = 0\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# initialize index\\n all_ORFs = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitalize empty list\\n while index < 3:\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# switches throught the 3 frames\\n \\tall_ORFs = all_ORFs + find_all_ORFs_oneframe(dna[index:])\\t# adds all ORFs oneframe to the list\\n \\tindex += 1\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# indexes +1\\n return all_ORFs \\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns list of all ORFs in all 3 frames\",\n \"def find_all(self):\",\n \"def find_all_ORFs(dna):\\n all_ORFs = []\\n for i in range(0, 3):\\n dna_new = dna[i:]\\n all_ORFs += find_all_ORFs_oneframe(dna_new)\\n return all_ORFs\",\n \"def find_all_ORFs(dna):\\n dnatwo = dna[1:]\\n dnathree = dna[2:]\\n all_ORFs = find_all_ORFs_oneframe(dna)\\n all_ORFs.extend(find_all_ORFs_oneframe(dnatwo))\\n all_ORFs.extend(find_all_ORFs_oneframe(dnathree))\\n if [] in all_ORFs:\\n all_ORFs.remove([])\\n return all_ORFs\",\n \"def find_all_ORFs_both_strands_unit_tests():\\n data_list = [\\n [\\\"ATGCGAATGTAGCATCAAA\\\", [\\\"ATGCGAATG\\\", \\\"ATGCTACATTCGCAT\\\"]],\\n [\\\"ATG\\\", [\\\"ATG\\\"]],\\n [\\\"CAT\\\", [\\\"ATG\\\"]],\\n [\\\"CATCAT\\\", [\\\"ATGATG\\\"]],\\n [\\\"CATGGGCAT\\\", [\\\"ATGGGCAT\\\", \\\"ATGCCCATG\\\"]],\\n [\\\"CATGCAGTGCACGGATGGCAT\\\", [\\\"ATGCAGTGCACGGATGGCAT\\\", \\\"ATGGCAT\\\", \\\"ATGCCATCCGTGCACTGCATG\\\"]],\\n# CATGCAGTGCACGGATGGCAT\\n# CAT GCA GTG CAC GGA TGG CAT\\n# ATG CAG TGC ACG GAT GGC AT\\n# TGC AGT GCA CGG ATG GCA T\\n# ATGCCATCCGTGCACTGCATG\\n# ATG CCA TCC GTG CAC TGC ATG\\n# TGC CAT CCG TGC ACT GCA TG\\n# GCC ATC CGT GCA CTG CAT G\\n [\\\"CATATGTAG\\\", [\\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGGGGCATCATTAG\\\", [\\\"ATGGGGCATCAT\\\", \\\"ATGATGCCCCAT\\\"]],\\n# ATGGGGCATCATTAG\\n# ATG GGG CAT CAT TAG\\n# TGG GGC ATC ATT AG\\n# GGG GCA TCA TTA G\\n# CTAATGATGCCCCAT\\n# CTA ATG ATG CCC CAT\\n# TAA TGA TGC CCC AT\\n# AAT GAT GCC CCA T\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\",\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = find_all_ORFs_both_strands(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def find_all_ORFs_oneframe(dna):\\n condition = 1\\n dna2 = dna\\n list_of_ORFs = []\\n while condition == 1:\\n num_codons = int(len(dna2)/3)\\n num = 0\\n list_codons = []\\n start_index = -1\\n while num < num_codons:\\n num_start = int(num*3)\\n num_end = int(num*3 + 3)\\n list_codons.append(dna2[num_start:num_end])\\n num = num + 1\\n for element in list_codons:\\n if element == 'ATG':\\n start_index = list_codons.index(element)\\n break\\n if start_index != -1:\\n this_orf = rest_of_ORF(dna2[start_index*3:])\\n list_of_ORFs.append(this_orf)\\n dna2 = dna2[start_index*3+len(this_orf)+3:]\\n else:\\n condition = 2\\n\\n return list_of_ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n i = 0\\n list_ORF = []\\n\\n def search_ORF(dna,i):\\n aa = dna[3*i:(3*i)+3]\\n if aa == 'ATG':\\n list_ORF.append(rest_of_ORF(dna,aa,i))\\n i = i + 1 + len(rest_of_ORF(dna,aa,i))/3\\n else:\\n i = i + 1\\n if len(aa) ==3:\\n search_ORF(dna,i)\\n \\n return list_ORF\\n\\n return search_ORF(dna,i)\\n # i = i + ((len(list_ORF[-1]))/3)\\n # search_ORF(dna,i)\",\n \"def orfFinder(data):\\n\\t\\n\\tORFile = getORFs(data.seqFile, \\n\\t\\t\\t\\t\\t data.queryName, \\n\\t\\t\\t\\t\\t data.o)\\n\\tsetattr(data, \\\"ORFs\\\", ORFile)\",\n \"def find_all_ORFs(dna):\\n ORFs = find_all_ORFs_oneframe(dna) + find_all_ORFs_oneframe(dna[1:]) + find_all_ORFs_oneframe(dna[2:])\\n\\n return ORFs\",\n \"def find_all(self):\\n pass\",\n \"def test_get_parsed_files(self):\\n files = Historical_ROAs_Parser()._get_parsed_files()\\n with Historical_ROAs_Parsed_Table() as t:\\n for f in files:\\n sql = f\\\"SELECT * FROM {t.name} WHERE file = '{f}'\\\"\\n assert len(t.execute(sql)) == 1\",\n \"def find_all_ORFs(dna):\\n first_frame = find_all_ORFs_oneframe(dna[0:])\\n second_frame = find_all_ORFs_oneframe(dna[1:])\\n third_frame = find_all_ORFs_oneframe(dna[2:])\\n list_of_frames = first_frame + second_frame + third_frame\\n return list_of_frames\",\n \"def rest_of_ORF_unit_tests():\\n data_list = [\\n [\\\"ATGTGAA\\\", \\\"ATG\\\"],\\n [\\\"ATGAGATAGG\\\", \\\"ATGAGA\\\"],\\n [\\\"ATG\\\", \\\"ATG\\\"],\\n [\\\"ATGTAG\\\", \\\"ATG\\\"],\\n [\\\"ATGTAA\\\", \\\"ATG\\\"],\\n [\\\"ATGTGA\\\", \\\"ATG\\\"],\\n [\\\"ATGAAATTTGGGAAATTTGGGTAG\\\", \\\"ATGAAATTTGGGAAATTTGGG\\\"],\\n [\\\"ATGAAATTTGGG\\\", \\\"ATGAAATTTGGG\\\"],\\n [\\\"ATGAGAAGGAAATTTGATGGGGATGGAAGATT\\\", \\\"ATGAGAAGGAAATTTGATGGGGATGGAAGATT\\\"],\\n [\\\"ATGAGAAGGAAATTTGATGGGGATGGAAGATAA\\\", \\\"ATGAGAAGGAAATTTGATGGGGATGGAAGA\\\"],\\n [\\\"ATGAA\\\", \\\"ATGAA\\\"],\\n [\\\"ATGATGATG\\\", \\\"ATGATGATG\\\"],\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\" ,\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = rest_of_ORF(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def find_all_ORFs_oneframe(dna):\\n \\n\\n ORFs=[]\\n i=0\\n while i<len(dna):\\n if dna[i:i+3]==\\\"ATG\\\":\\n j=i\\n dna2=rest_of_ORF(dna[j:])\\n \\n if dna2==None:\\n \\tbreak\\n ORFs.append(dna2)\\n i=i+len(dna2)\\n i=i+3\\n return ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n dna_split = split_into_codons(dna)\\n i = 0\\n all_ORFs_oneframe = []\\n length_of_orf = 0\\n while i < len(dna_split):\\n if dna_split[i] == \\\"ATG\\\":\\n orf = rest_of_ORF(dna[int(i)*3:])\\n all_ORFs_oneframe += [orf]\\n length_of_orf = math.ceil(len(orf)/3)\\n i += length_of_orf\\n else:\\n i += 1\\n return all_ORFs_oneframe\",\n \"def find_all_ORFs_oneframe(dna):\\n res = []\\n l = len(dna)\\n next_pos = 0\\n while True:\\n arg = dna[next_pos:]\\n# orf = rest_of_ORF(arg)\\n# res.append(orf)\\n# if arg == orf: # if: no stop codon\\n# break\\n# next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\\n# if next_pos >= l: # if: meet the end of dna\\n# break\\n if arg[0:3] == start_codon:\\n orf = rest_of_ORF(arg)\\n res.append(orf)\\n if arg == orf: # if: no stop codon\\n break\\n next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\\n else: # if: not start codon, see next\\n next_pos += 3\\n if next_pos >= l: # if: meet or go beyond the end of dna\\n break\\n return res\",\n \"def find_all_ORFs_oneframe(dna):\\n\\n ORFlist = []\\n i = 0\\n lend = len(dna)\\n while i < lend:\\n codon = dna[i:i+3]\\n if codon == 'ATG':\\n orf = rest_of_ORF(dna[i:])\\n ORFlist.append(orf)\\n i = i + len(orf)\\n else:\\n i = i+3\\n return ORFlist\",\n \"def find_all_ORFs_both_strands(dna):\\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def test_otoroshi_controllers_adminapi_tcp_service_api_controller_find_all_entities_action(self):\\n pass\",\n \"def find_all_ORFs(dna):\\n res = []\\n for i in range(0, 3):\\n s = dna[i:]\\n# print i, s,\\n# l = len(s)\\n# for j in range(0, l, 3):\\n# if s[j: j + 3] == start_codon:\\n# r = find_all_ORFs_oneframe(s[j:])\\n# print r\\n# if len(r) > 0:\\n# for item in r:\\n# res.append(item)\\n# break # careful for indentation here!!\\n r = find_all_ORFs_oneframe(s)\\n if len(r) > 0:\\n# for item in r:\\n# res.append(item)\\n res += r # [WOW] I love python!\\n return res\",\n \"def find_all_ORFs_both_strands_unit_tests(dna, expected):\\n\\n print find_all_ORFs_both_strands(\\\"ATGCGAATGTAGCATCAAA\\\")\\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + find_all_ORFs_both_strands(dna)\",\n \"def test_find_all(self):\\n # arrange\\n movie_id = MovieId('123')\\n character = character_random_with_movie_ids(MovieIds([movie_id]))\\n people = People([character])\\n movie = movie_random_with_movie_id_and_people(movie_id, people)\\n expected = Movies([movie])\\n\\n self.ghibli_client_mock__people([{'id': character.character_id, 'name': character.name,\\n 'gender': character.gender, 'age': character.age,\\n 'eye_color': character.eye_color, 'hair_color': character.hair_color,\\n 'films': [f'http://url/{movie_id}']}])\\n self.ghibli_client_mock__movies([{'id': movie_id, 'title': movie.title,\\n 'description': movie.description, 'director': movie.director,\\n 'producer': movie.producer, 'release_date': movie.release_date,\\n 'rt_score': movie.rt_score}])\\n\\n # act\\n repository = self.ghibli_movie_repository()\\n movies = repository.find_all()\\n\\n # assert\\n self.assertEqual(expected, movies)\",\n \"def rest_of_ORF_unit_tests():\\n input = [\\\"dna\\\"]\\n expected_output = [\\\"rest of ORFs\\\"]\\n actual = []\\n for k in input:\\n actual.append(rest_of_ORF(k))\\n print input \\n print actual\\n print expected_output\",\n \"def find_all_ORFs_both_strands_unit_tests():\\n print \\\"input: CTA, \\\"+\\\"output: \\\"+ \\\",\\\".join(find_all_ORFs_both_strands(\\\"CTA\\\"))+\\\", actual output: CTA,TA,A,AG,G\\\"\\n print \\\"input: GTCACTTAGGGTTTT, \\\"+\\\"output: \\\"+\\\",\\\".join(find_all_ORFs_both_strands(\\\"GTCACTTAGGGTTTT\\\"))+\\\", actual output: GTCACT,GGTTTT,TCACTTAGGGTTTT,CACTTAGGGTTTT,AAAACCCTAAGTGAC,AAACCC,GTGAC,AACCCTAAG\\\"\\n print \\\"input: AAATTTTATAATGGGTGAAGTTAG, \\\"+\\\"output: \\\"+\\\",\\\".join(find_all_ORFs_both_strands(\\\"AAATTTTATAATGGGTGAAGTTAG\\\"))+\\\", actual output: AAATTTTATAATGGG,AGT,AATTTTATAATGGGTGAAGTTAG,ATTTTA,TGGGTGAAGTTAG,CTAACTTCACCCATTATAAAATTT,CTTCACCCATTA,AATTT,AACTTCACCCATTATAAAATTT\\\"\\n print \\\"input: TATATGGAGGATAATAGTTGATAATAG, \\\"+\\\"output: \\\"+ \\\",\\\".join(find_all_ORFs_both_strands(\\\"TATATGGAGGATAATAGTTGATAATAG\\\"))+\\\", actual output: TATATGGAGGATAATAGT,ATATGGAGGATAATAGTTGATAATAG,TATGGAGGA,TTGATAATAG,CTATTATCAACTATTATCCTCCATATA,TATTATCAACTATTATCCTCCATATA,ATTATCAACTATTATCCTCCATATA\\\"\",\n \"def find_all_ORFs(dna):\\n\\n readingFrame0 = ''\\n readingFrame1 = ''\\n readingFrame2 = ''\\n output = ''\\n for k in range(0,3): \\n if k ==0: \\n readingFrame0 = find_all_ORFs_oneframe(dna[k:])\\n elif k ==1: \\n readingFrame1 = find_all_ORFs_oneframe(dna[k:])\\n elif k ==2:\\n readingFrame2 = find_all_ORFs_oneframe(dna[k:])\\n print 'Reading Frame 1: ' + str(readingFrame0) + ', Reading Frame 2: ' + str(readingFrame1) + ', Reading Frame 3: ' + str(readingFrame2)\\n output = readingFrame0 + readingFrame1 + readingFrame2\\n return output\",\n \"def test_objects(self):\\n\\n obj = FBO(\\n path=TEST_FILES_ROOT,\\n metadata=FileObject.MetadataInFileHead,\\n ).objects.all().filter(\\n name__glob='*.rst',\\n ).get(\\n name='test2.rst',\\n )\\n\\n self.assertEqual(\\n 'Second in the alphabet',\\n obj.title,\\n )\",\n \"def find_all_ORFs_oneframe(dna):\\n #inital conditions\\n i = 0\\n start_codon = ('ATG')\\n end_index = len(dna)\\n return_variable = []\\n\\n #for each codon in the set of DNA, check if it is a start codon\\n #if it is a start codon, add the string until the stop codon to a list\\n #then continue running\\n while i < len(dna)-2:\\n codon = dna[i:i+3] \\n if codon in start_codon:\\n orf = rest_of_ORF(dna[i:])\\n return_variable.append(orf)\\n i += len(orf)\\n i += 3\\n\\n\\n #return a list of strings of DNA\\n return return_variable\",\n \"def find_all_ORFs_oneframe(dna):\\n\\tindex = 0\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# unitiate index at 0\\n\\tsegment = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitializes empty list\\n\\twhile index < len(dna):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# given that index is smaller than length of string\\n\\t\\tcodon = dna[index:index + 3]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# creates codons from nucleotides starting with first 3 letters\\n\\t\\tif codon == \\\"ATG\\\":\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if the codon is ATG\\n\\t\\t\\tsegment.append(rest_of_ORF(dna[index:]))\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# run rest_of_ORF starting at index\\n\\t\\t\\tindex = index + len(rest_of_ORF(dna[index:]))\\t\\t\\t\\t\\t\\t\\t\\t\\t# new index starting at old + length of ORF output string\\n\\t\\telse:\\n\\t\\t\\tindex += 3\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if ATG isn't found, move to next codon and check again\\n\\n\\treturn segment\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns list of ORFs\",\n \"def rest_of_ORF_unit_tests():\\n print \\\"input: CTA, \\\"+\\\"output: \\\"+rest_of_ORF(\\\"CTA\\\")+\\\", actual output: CTA\\\"\\n print \\\"input: GTCACTTAGGGTTTT, \\\"+\\\"output: \\\"+rest_of_ORF(\\\"GTCACTTAGGGTTTT\\\")+\\\", actual output: GTCACT\\\"\\n print \\\"input: AAATTTTATAATGGGTGAAGTTAG, \\\"+\\\"output: \\\"+rest_of_ORF(\\\"AAATTTTATAATGGGTGAAGTTAG\\\")+\\\", actual output: AAATTTTATAATGGG\\\"\\n print \\\"input: TATATGGAGGATAATAGTTGATAATAG, \\\"+\\\"output: \\\"+rest_of_ORF(\\\"TATATGGAGGATAATAGTTGATAATAG\\\")+\\\", actual output: TATATGGAGGATAATAGT\\\"\",\n \"def test_get_foods_search(self):\\n pass\",\n \"def find_all_ORFs_oneframe(dna):\\n i=0 \\n ORF_list = []\\n while i<len(dna):\\n if dna[i : i+3] == \\\"ATG\\\":\\n start_place = i \\n current_ORF = rest_of_ORF(dna[start_place:])\\n i += 3 + len(current_ORF)\\n ORF_list.append(current_ORF) \\n return ORF_list\",\n \"def test_fetch_open_frame(self):\\n import requests\\n pesummary_data = StrainData.fetch_open_frame(\\n \\\"GW190412\\\", IFO=\\\"L1\\\", duration=32, sampling_rate=4096.,\\n channel=\\\"L1:GWOSC-4KHZ_R1_STRAIN\\\", format=\\\"hdf5\\\"\\n )\\n N = len(pesummary_data)\\n np.testing.assert_almost_equal(N * pesummary_data.dt.value, 32.)\\n np.testing.assert_almost_equal(1. / pesummary_data.dt.value, 4096.)\\n assert pesummary_data.IFO == \\\"L1\\\"\\n _data = requests.get(\\n \\\"https://www.gw-openscience.org/eventapi/html/GWTC-2/GW190412/v3/\\\"\\n \\\"L-L1_GWOSC_4KHZ_R1-1239082247-32.gwf\\\"\\n )\\n with open(\\\"L-L1_GWOSC_4KHZ_R1-1239082247-32.gwf\\\", \\\"wb\\\") as f:\\n f.write(_data.content)\\n data2 = TimeSeries.read(\\n \\\"L-L1_GWOSC_4KHZ_R1-1239082247-32.gwf\\\",\\n channel=\\\"L1:GWOSC-4KHZ_R1_STRAIN\\\"\\n )\\n np.testing.assert_almost_equal(pesummary_data.value, data2.value)\\n np.testing.assert_almost_equal(\\n pesummary_data.times.value, data2.times.value\\n )\",\n \"def test_all_documents(self):\",\n \"def test_everything(self):\\n\\n qs = FBO(\\n path=TEST_FILES_ROOT,\\n ).exclude(\\n name__glob='*~',\\n ).exclude(\\n name__glob='*.meta',\\n )\\n\\n self.assertEqual(\\n 7,\\n qs.count(),\\n )\\n self.assertEqual(\\n {\\n 'index.md',\\n 'subdir/index.md',\\n 'test1.md',\\n 'test2.md',\\n 'test1.rst',\\n 'test2.rst',\\n 'test3.rst',\\n },\\n {o.name for o in qs},\\n )\",\n \"def test_search_or(self):\\n pkgs = [\\n make_package(factory=SQLPackage),\\n make_package(\\n \\\"somepackage\\\",\\n version=\\\"1.3\\\",\\n filename=\\\"mypath3\\\",\\n summary=\\\"this is mypkg\\\",\\n factory=SQLPackage,\\n ),\\n make_package(\\\"mypkg2\\\", \\\"1.3.4\\\", \\\"my/other/path\\\", factory=SQLPackage),\\n make_package(\\\"package\\\", factory=SQLPackage),\\n ]\\n for pkg in pkgs:\\n self.db.save(pkg)\\n criteria = {\\\"name\\\": [\\\"mypkg\\\"], \\\"summary\\\": [\\\"mypkg\\\"]}\\n packages = self.db.search(criteria, \\\"or\\\")\\n self.assertCountEqual(packages, pkgs[:-1])\",\n \"def rest_of_ORF_unit_tests():\\n input_a='ATTCATTAG'\\n expected_output='ATTCAT'\\n actual_output=rest_of_ORF(input_a)\\n print 'Expected Output is ' + expected_output\\n print 'Actual Output is ' +actual_output\\n \\n input_a='ATTCATCATCATCATTAG'\\n expected_output='ATTCATCATCATCAT'\\n actual_output=rest_of_ORF(input_a)\\n print 'Expected Output is ' + expected_output\\n print 'Actual Output is ' +actual_output\",\n \"def test_get_records(self):\\n pass\",\n \"def test_organization_all(self):\\n gryffindor = models.Organization(name='gryffindor')\\n ravenclaw = models.Organization(name='ravenclaw')\\n db.session.add(gryffindor)\\n db.session.add(ravenclaw)\\n db.session.commit()\\n # scenario 1: when neither buids nor names are given\\n self.assertEqual(models.Organization.all(), [])\\n # scenario 2: when buids are passed\\n orglist = [gryffindor, ravenclaw]\\n orgids = [gryffindor.buid, ravenclaw.buid]\\n all_by_buids = models.Organization.all(buids=orgids)\\n self.assertIsInstance(all_by_buids, list)\\n self.assertCountEqual(all_by_buids, orglist)\\n # scenario 3: when org names are passed\\n names = [gryffindor.name, ravenclaw.name]\\n all_by_names = models.Organization.all(names=names)\\n self.assertIsInstance(all_by_names, list)\\n self.assertCountEqual(all_by_names, orglist)\\n # scenario 4: when defercols is set to True for names\\n all_by_names_with_defercols = models.Organization.all(names=names)\\n self.assertIsInstance(all_by_names_with_defercols, list)\\n self.assertCountEqual(all_by_names_with_defercols, orglist)\\n # scenario 5: when defercols is set to True for buids\\n all_by_buids_with_defercols = models.Organization.all(buids=orgids)\\n self.assertIsInstance(all_by_buids_with_defercols, list)\\n self.assertCountEqual(all_by_buids_with_defercols, orglist)\",\n \"def find_all_ORFs_oneframe(dna):\\n x = 3\\n list_of_dna = []\\n while (x < len(dna)):\\n if dna[x-3:x] == 'ATG':\\n current_dna = rest_of_ORF(dna[x-3:])\\n list_of_dna.append(current_dna)\\n x += len(current_dna)\\n x += 3\\n return list_of_dna\",\n \"def find_all_ORFs_oneframe(dna):\\n strand = []\\n startCodon = [\\\"ATG\\\"]\\n for i in range(0,len(dna),3):\\n triple = dna[i:i+3]\\n if triple in startCodon: \\n strand.append(rest_of_ORF(dna[i:]))\\n print strand\\n return strand\",\n \"def test_get_foods(self):\\n pass\",\n \"def test_find_all(self):\\n result = Project.objects.find(['test'], project_type=None)\\n self.assertEqual(len(result), 2)\\n result = Project.objects.find(['ThisFails'], project_type=None)\\n self.assertEqual(len(result), 0)\",\n \"def find_all_ORFs(dna):\\n #inital conditions\\n i = 0\\n start_codon = ('ATG')\\n end_index = len(dna)\\n return_variable = []\\n\\n #for statement tells the code to run three times at three inital index values\\n #0,1,and 2 which allows for each reading frame to be read\\n for i in range (3):\\n while i < (len(dna)-2):\\n codon = dna[i:i+3] \\n if codon in start_codon: #check if the codon the code is looking at is a start codon\\n orf = rest_of_ORF(dna[i:]) #then determine that this is an orf, make it a string given the index of the start codon\\n return_variable.append(orf) #and append said string to a list of ORFs\\n i += len(orf) \\n i += 3\\n #return a list of strings of DNA from both strands\\n return return_variable\",\n \"def test_all_finder_methods(self):\\n methods = ['all', 'first', 'find']\\n\\n for method in methods:\\n result = getattr(self.Test, method)\\n self.assertEqual(type(result).__name__, 'instancemethod')\\n self.assertEqual(result.im_class.__name__, 'Relation')\",\n \"def test_return_all(self):\\n self.data.return_all()\",\n \"def test_search_or(self):\\n pkgs = [\\n make_package(factory=SQLPackage),\\n make_package(\\n \\\"somepackage\\\",\\n version=\\\"1.3\\\",\\n filename=\\\"mypath3\\\",\\n summary=\\\"this is mypkg\\\",\\n factory=SQLPackage,\\n ),\\n make_package(\\\"mypkg2\\\", \\\"1.3.4\\\", \\\"my/other/path\\\", factory=SQLPackage),\\n make_package(\\\"package\\\", factory=SQLPackage),\\n ]\\n self.sql.add_all(pkgs)\\n criteria = {\\\"name\\\": [\\\"mypkg\\\"], \\\"summary\\\": [\\\"mypkg\\\"]}\\n packages = self.db.search(criteria, \\\"or\\\")\\n self.assertCountEqual(packages, pkgs[:-1])\",\n \"def test_multiple(self):\\n\\n with self.assertRaises(MultipleObjectsReturned):\\n RST_FBO().get()\",\n \"def test_get_foods_list(self):\\n pass\",\n \"def test_query_algorithms_ORqueryfrom200Algorithms(self):\\n query_string = 'displayName102 OR algorithmId23'\\n upload_data_list = []\\n create_test_algorithm_list(upload_data_list, 200)\\n documents = []\\n create_test_documents_list(upload_data_list, documents, 200)\\n index = search.Index(name=search_algorithm._INDEX_STRING)\\n index.put(documents)\\n # end of data preparation\\n numbers = ['23', '102']\\n right_answer_list = []\\n for number in numbers:\\n data = {}\\n data['algorithmId'] = 'algorithmId' + number\\n data['algorithmSummary'] = 'algorithmSummary' + number\\n data['displayName'] = 'displayName' + number\\n data['linkURL'] = 'linkURL' + number\\n right_answer_list.append(data)\\n # end right answer list preparation\\n result = search_algorithm.query_algorithms(index, query_string)\\n self.assertEqual(len(right_answer_list), len(result), msg='Wrong number of algorithms')\\n self.assertItemsEqual(right_answer_list, result, msg='Discrepancy in returned algorithms')\",\n \"def test_get_df(mocker):\\n spy_load_metadata = mocker.spy(MetaData, 'load_document')\\n expected_df = pd.read_json('tests/odata/fixtures/records.json', orient='records')\\n\\n provider = ODataConnector(\\n name='test',\\n baseroute='http://services.odata.org/V4/Northwind/Northwind.svc/',\\n auth={'type': 'basic', 'args': ['u', 'p']},\\n )\\n\\n data_source = ODataDataSource(\\n domain='test',\\n name='test',\\n entity='Orders',\\n query={\\n '$filter': \\\"ShipCountry eq 'France'\\\",\\n '$orderby': 'Freight desc',\\n '$skip': 50,\\n '$top': 3,\\n },\\n )\\n\\n try:\\n df = provider.get_df(data_source)\\n sl = ['CustomerID', 'EmployeeID', 'Freight']\\n assert df[sl].equals(expected_df[sl])\\n except socket.error:\\n pytest.skip('Could not connect to the standard example OData service.')\\n\\n assert spy_load_metadata.call_count == 1\\n args, _ = spy_load_metadata.call_args\\n assert args[0].url.endswith('/$metadata')\\n\\n provider.auth = None\\n try:\\n provider.get_df(data_source)\\n except socket.error:\\n pytest.skip('Could not connect to the standard example OData service.')\",\n \"def test_ipam_vrfs_list(self):\\n pass\",\n \"def test_get_list8(self):\\n pass\",\n \"def getORFs(catFile, queryName, geneDir):\\n\\n\\toutORFraw = geneDir+catFile.split(\\\"/\\\")[-1].split(\\\".\\\")[0]+\\\"_allORFs.fasta\\\"\\n\\tlogger = logging.getLogger(\\\"main.orf\\\")\\n\\t\\n\\tlogger.debug(\\\"getorf -sequence {:s} -outseq {:s} -table 0 -find 3 -noreverse\\\".format(catFile, outORFraw))\\n\\tcmd(\\\"getorf -sequence {:s} -outseq {:s} -table 0 -find 3 -noreverse\\\".format(catFile, outORFraw), False)\\n\\t\\n\\tdId2ORFs = defaultdict(list)\\n\\tf = SeqIO.parse(open(outORFraw),'fasta')\\n\\tfor fasta in f:\\n\\t\\tfname, fseq = fasta.id, str(fasta.seq)\\n\\t\\tif len(fname.split(\\\"_\\\")) > 2:\\n\\t\\t\\tfname2 = \\\"_\\\".join(fname.split(\\\"_\\\")[0:-1])\\n\\t\\telse:\\n\\t\\t\\tfname2 = fname.split(\\\"_\\\")[0]\\n\\t\\tdId2ORFs[fname2].append(fseq)\\n\\t\\n\\tdId2Longest = {}\\n\\tfor k, v in dId2ORFs.items():\\n\\t\\tdId2Longest[k] = max(v, key=len)\\n\\t\\t\\n\\t# delete duplicate sequences\\n\\tdRev = {}\\n\\tfor k, v in dId2Longest.items():\\n\\t\\tdRev.setdefault(v, set()).add(k)\\n\\t\\t\\n\\tAllDupl = [values for key, values in dRev.items() if len(values) > 1]\\n\\tn = 0\\n\\tfor dupl in AllDupl:\\n\\t\\tspecies = set([x.split(\\\"_\\\")[0] for x in dupl])\\n\\t\\t\\n\\t\\tfor sp in species:\\n\\t\\t\\tif queryName in dupl:\\n\\t\\t\\t\\tfirstOcc = queryName\\n\\t\\t\\telse:\\n\\t\\t\\t\\tlOcc = [x for x in dupl if sp in x]\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif len(lOcc) > 0:\\n\\t\\t\\t\\t\\tfirstOcc = lOcc[0]\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tfirstOcc = str(lOcc)\\n\\t\\t\\t\\t\\t\\n\\t\\t\\tdupl.remove(firstOcc)\\n\\t\\t\\n\\t\\tfor i in dupl:\\n\\t\\t\\tdId2Longest.pop(i, None)\\n\\t\\t\\tn += 1\\n\\t\\t\\tlogger.debug(\\\"Deleted sequence {:s} (duplicate)\\\".format(i))\\n\\t\\t\\n\\tlogger.info(\\\"Deleted {} sequences as duplicates\\\".format(n))\\n\\t\\n\\toutORF = outORFraw.replace(\\\"_allORFs.fasta\\\",\\\"_longestORFs.fasta\\\")\\n\\n\\twith open(outORF, \\\"w\\\") as outO:\\n\\t outO.write(FastaResFunc.dict2fasta(dId2Longest))\\n\\t outO.close()\\n\\t \\n\\tlogger.info(\\\"Extracted longest ORFs: {:s}\\\".format(outORF))\\n\\n\\treturn(outORF)\",\n \"def test_create_doc(self):\\r\\n function_name = sys._getframe().f_code.co_name\\r\\n db_name = \\\"{}_{}\\\".format(function_name, \\\"db\\\")\\r\\n db_name_illegal_by_rdb = \\\"{}_{}\\\".format(\\r\\n db_name,\\r\\n self.ILLEGAL_BY_RDB\\r\\n )\\r\\n db_name_illegal_by_this_program = \\\"{}_{}\\\".format(\\r\\n db_name,\\r\\n self.ILLEGAL_BY_THIS_PROGRAM\\r\\n )\\r\\n table_name = \\\"{}_{}\\\".format(function_name, \\\"table\\\")\\r\\n table_name_illegal_by_rdb = \\\"{}_{}\\\".format(\\r\\n table_name,\\r\\n self.ILLEGAL_BY_RDB\\r\\n )\\r\\n table_name_illegal_by_this_program = \\\"{}_{}\\\".format(\\r\\n table_name,\\r\\n self.ILLEGAL_BY_THIS_PROGRAM\\r\\n )\\r\\n doc_1 = {\\\"name\\\": \\\"alpha\\\", \\\"no\\\":\\\"1\\\"}\\r\\n doc_2 = {\\\"name\\\": \\\"beta\\\", \\\"no\\\":\\\"2\\\"}\\r\\n doc_3 = {\\\"name\\\": \\\"charlie\\\", \\\"no\\\":\\\"1\\\"}\\r\\n doc_4 = {\\\"name\\\": \\\"charlie\\\", \\\"no\\\":\\\"3\\\"}\\r\\n\\r\\n test_list_1 = [\\r\\n db_name,\\r\\n table_name,\\r\\n doc_1,\\r\\n [\\\"no\\\"],\\r\\n False,\\r\\n None,\\r\\n None,\\r\\n False\\r\\n ]\\r\\n test_list_2 = [\\r\\n test_list_1[0],\\r\\n test_list_1[1],\\r\\n doc_2,\\r\\n [\\\"no\\\"],\\r\\n None\\r\\n ]\\r\\n test_list_3 = [\\r\\n test_list_1[0],\\r\\n test_list_1[1],\\r\\n doc_3,\\r\\n [\\\"no\\\"],\\r\\n None\\r\\n ]\\r\\n test_list_4 = [\\r\\n test_list_1[0],\\r\\n test_list_1[1],\\r\\n doc_4,\\r\\n [\\\"name\\\", \\\"no\\\"],\\r\\n None\\r\\n ]\\r\\n test_list_5 = [\\r\\n db_name_illegal_by_rdb,\\r\\n table_name_illegal_by_rdb,\\r\\n doc_1,\\r\\n None\\r\\n ]\\r\\n test_list_6 = [\\r\\n db_name_illegal_by_rdb,\\r\\n table_name_illegal_by_this_program,\\r\\n doc_1,\\r\\n None\\r\\n ]\\r\\n test_list_7 = [\\r\\n db_name_illegal_by_this_program,\\r\\n table_name_illegal_by_rdb,\\r\\n doc_1,\\r\\n None\\r\\n ]\\r\\n test_list_8 = [\\r\\n db_name_illegal_by_this_program,\\r\\n table_name_illegal_by_this_program,\\r\\n doc_1,\\r\\n None\\r\\n ]\\r\\n\\r\\n crd(self.c, test_list_1[0])\\r\\n crt(self.c, test_list_1[1], test_list_1[0])\\r\\n test_list_1[len(test_list_1) - 1] = isinstance(\\r\\n crdoc(\\r\\n self.c,\\r\\n test_list_1[2],\\r\\n test_list_1[1],\\r\\n test_list_1[0],\\r\\n _expr=True\\r\\n ),\\r\\n r.ast.Insert\\r\\n )\\r\\n test_list_1[len(test_list_1) - 2] = crdoc(\\r\\n self.c,\\r\\n test_list_1[2],\\r\\n test_list_1[1],\\r\\n test_list_1[0]\\r\\n )\\r\\n test_list_1[len(test_list_1) - 3] = crdoc(\\r\\n self.c,\\r\\n test_list_1[2],\\r\\n test_list_1[1],\\r\\n test_list_1[0],\\r\\n test_list_1[3]\\r\\n )\\r\\n test_list_1[len(test_list_1) - 4] = isinstance(\\r\\n crdoc(\\r\\n self.c,\\r\\n test_list_1[2],\\r\\n test_list_1[1],\\r\\n test_list_1[0],\\r\\n [\\\"name\\\", \\\"no\\\"],\\r\\n True\\r\\n ),\\r\\n r.ast.Insert\\r\\n )\\r\\n test_list_2[len(test_list_2) - 1] = crdoc(\\r\\n self.c,\\r\\n test_list_2[2],\\r\\n test_list_2[1],\\r\\n test_list_2[0],\\r\\n test_list_2[3]\\r\\n )\\r\\n crt(self.c, test_list_3[1], test_list_3[0])\\r\\n test_list_3[len(test_list_3) - 1] = crdoc(\\r\\n self.c,\\r\\n test_list_3[2],\\r\\n test_list_3[1],\\r\\n test_list_3[0],\\r\\n test_list_3[3]\\r\\n )\\r\\n test_list_4[len(test_list_4) - 1] = crdoc(\\r\\n self.c,\\r\\n test_list_4[2],\\r\\n test_list_4[1],\\r\\n test_list_4[0],\\r\\n test_list_4[3]\\r\\n )\\r\\n dd(self.c, test_list_1[0])\\r\\n\\r\\n \\\"\\\"\\\"Test 1.\\\"\\\"\\\"\\r\\n with self.assertWarns(CDW):\\r\\n test_list_5[len(test_list_5) - 1] = crdoc(\\r\\n self.c,\\r\\n test_list_5[2],\\r\\n test_list_5[1],\\r\\n test_list_5[0]\\r\\n )\\r\\n\\r\\n \\\"\\\"\\\"Test 2.\\\"\\\"\\\"\\r\\n with self.assertWarns(CDW):\\r\\n test_list_6[len(test_list_6) - 1] = crdoc(\\r\\n self.c,\\r\\n test_list_6[2],\\r\\n test_list_6[1],\\r\\n test_list_6[0]\\r\\n )\\r\\n\\r\\n r.db_create(test_list_7[0]).run(self.c)\\r\\n \\\"\\\"\\\"Test 3.\\\"\\\"\\\"\\r\\n with self.assertWarns(CDW):\\r\\n test_list_7[len(test_list_7) - 1] = crdoc(\\r\\n self.c,\\r\\n test_list_7[2],\\r\\n test_list_7[1],\\r\\n test_list_7[0]\\r\\n )\\r\\n r.db_drop(test_list_7[0]).run(self.c)\\r\\n\\r\\n r.db_create(test_list_8[0]).run(self.c)\\r\\n r.db(test_list_8[0]).table_create(test_list_8[0]).run(self.c)\\r\\n \\\"\\\"\\\"Test 4.\\\"\\\"\\\"\\r\\n with self.assertWarns(CDW):\\r\\n test_list_8[len(test_list_8) - 1] = crdoc(\\r\\n self.c,\\r\\n test_list_8[2],\\r\\n test_list_8[1],\\r\\n test_list_8[0]\\r\\n )\\r\\n r.db_drop(test_list_8[0]).run(self.c)\\r\\n\\r\\n self.assertTrue(test_list_1[len(test_list_1) - 1]) # Test 5.\\r\\n self.assertIsNotNone(test_list_1[len(test_list_1) - 2]) # Test 6.\\r\\n self.assertIsNone(test_list_1[len(test_list_1) - 3]) # Test 7.\\r\\n self.assertFalse(test_list_1[len(test_list_1) - 4]) # Test 8\\r\\n self.assertIsNotNone(test_list_2[len(test_list_2) - 1]) # Test 9.\\r\\n self.assertIsNone(test_list_3[len(test_list_3) - 1]) # Test 10.\\r\\n self.assertIsNotNone(test_list_4[len(test_list_4) - 1]) # Test 11.\\r\\n self.assertIsNone(test_list_5[len(test_list_5) - 1]) # Test 12.\\r\\n self.assertIsNone(test_list_6[len(test_list_6) - 1]) # Test 13.\\r\\n self.assertIsNone(test_list_7[len(test_list_7) - 1]) # Test 14.\\r\\n self.assertIsNone(test_list_8[len(test_list_8) - 1]) # Test 15.\\r\",\n \"def longest_ORF_unit_tests():\\n\\n # YOUR IMPLEMENTATION HERE\",\n \"def longest_ORF_unit_tests():\\n\\n # YOUR IMPLEMENTATION HERE\",\n \"def test_get_bios_unit_list(self):\\n pass\",\n \"def test_data_object_get_names_all(self):\\n pass\",\n \"def test_find_all(self):\\n\\n # Test valid empty inputs\\n\\n self.assertEqual(find_all(None, None), [])\\n self.assertEqual(find_all('', None), [])\\n self.assertEqual(find_all(None, ''), [])\\n\\n self.assertEqual(find_all(b'', b''), [])\\n self.assertEqual(find_all(b'', ''), [])\\n\\n self.assertEqual(find_all('', b''), [])\\n self.assertEqual(find_all('', ''), [])\\n\\n # Test with missing or invalid inputs\\n\\n self.assertEqual(find_all('abc', '123'), [])\\n self.assertEqual(find_all('abc', 'abcabc'), [])\\n\\n self.assertEqual(find_all('abc', 'abc', limit=0), [])\\n self.assertEqual(find_all('abc', 'abc', limit=0, reverse=True), [])\\n self.assertEqual(find_all('abc', 'abc', limit=0, start=0, end=3), [])\\n self.assertEqual(find_all('abc', 'abc', limit=0, start=0, end=3, reverse=True), [])\\n\\n self.assertEqual(find_all('abc', 'abc', start=3, end=0), [])\\n self.assertEqual(find_all('abc', 'abc', start=3, end=0, limit=1), [])\\n self.assertEqual(find_all('abc', 'abc', start=3, end=0, reverse=True), [])\\n self.assertEqual(find_all('abc', 'abc', start=3, end=0, limit=1, reverse=True), [])\\n\\n # Test with valid, non-empty inputs\\n\\n self._test_find_all(\\n s='ab?cdef?ghijkl?mnopqrstuv?wxy?z?',\\n sub='?',\\n out=[2, 7, 14, 25, 29, 31]\\n )\\n self._test_find_all(\\n s='ab??cdef??ghijkl??mnopqrstuv??wxy??z??',\\n sub='??',\\n out=[2, 8, 16, 28, 33, 36]\\n )\\n self._test_find_all(\\n s='ab???cdef???ghijkl???mnopqrstuv???wxy???z???',\\n sub='???',\\n out=[2, 9, 18, 31, 37, 41]\\n )\",\n \"def test_fetch_all():\\n response = requests.get('http://localhost:5000/api/persons')\\n data = response.json()\\n\\n assert response.status_code == 200\\n for field in FIELDS:\\n assert field in data[0]\",\n \"def test_search_or(self):\\n pkgs = [\\n make_package(factory=DynamoPackage),\\n make_package(\\n \\\"somepackage\\\",\\n version=\\\"1.3\\\",\\n filename=\\\"mypath3\\\",\\n summary=\\\"this is mypkg\\\",\\n factory=DynamoPackage,\\n ),\\n make_package(\\\"mypkg2\\\", \\\"1.3.4\\\", \\\"my/other/path\\\", factory=DynamoPackage),\\n make_package(\\\"package\\\", factory=DynamoPackage),\\n ]\\n self._save_pkgs(*pkgs)\\n criteria = {\\\"name\\\": [\\\"mypkg\\\"], \\\"summary\\\": [\\\"mypkg\\\"]}\\n packages = self.db.search(criteria, \\\"or\\\")\\n self.assertCountEqual(packages, pkgs[:-1])\",\n \"def test_all_filter_op_fields(self):\\n for field in OCIFilterSerializer._opfields:\\n field = \\\"and:\\\" + field\\n filter_param = {field: [\\\"1\\\", \\\"2\\\"]}\\n serializer = OCIFilterSerializer(data=filter_param)\\n self.assertTrue(serializer.is_valid())\\n for field in OCIFilterSerializer._opfields:\\n field = \\\"or:\\\" + field\\n filter_param = {field: [\\\"1\\\", \\\"2\\\"]}\\n serializer = OCIFilterSerializer(data=filter_param)\\n self.assertTrue(serializer.is_valid())\",\n \"def test_run_all_searches(): # ***Incomplete test\\n ##########################\\n # Arrange.\\n query_file_list = \\\"query_file_list\\\"\\n\\n ##########################\\n # Act.\\n #x = run_all_searches(query_file_list)\\n\\n ##########################\\n # Assert.\\n assert True == True # ***Temporary.\",\n \"def test():\\n\\t\\treturn [\\\"vice.core.dataframe\\\",\\n\\t\\t\\t[\\n\\t\\t\\t\\ttests.test(run = False),\\n\\t\\t\\t\\t_builtin_dataframes.test(run = False)\\n\\t\\t\\t]\\n\\t\\t]\",\n \"def test_eia860_output(live_pudl_db, start_date_eia923, end_date_eia923):\\n testing = (not live_pudl_db)\\n dates = [(None, None), (start_date_eia923, end_date_eia923)]\\n print('\\\\n')\\n for (start_date, end_date) in dates:\\n print(\\\"start_date={}, end_date={}\\\". format(start_date, end_date))\\n utils_out = outputs.utilities_eia860(testing=testing,\\n start_date=start_date,\\n end_date=end_date)\\n print(\\\" utils_eia860: {} records found\\\".format(len(utils_out)))\\n\\n plants_out = outputs.plants_eia860(testing=testing,\\n start_date=start_date,\\n end_date=end_date)\\n print(\\\" plants_eia860: {} records found\\\".format(len(plants_out)))\\n\\n gens_out = outputs.generators_eia860(testing=testing,\\n start_date=start_date,\\n end_date=end_date)\\n print(\\\" gens_eia860: {} records found\\\".format(len(gens_out)))\\n\\n own_out = outputs.ownership_eia860(testing=testing,\\n start_date=start_date,\\n end_date=end_date)\\n print(\\\" own_eia860: {} records found\\\".format(len(own_out)))\",\n \"def test_get_data_for_specific_dates(self):\\n # setup\\n start_date = \\\"3/10/2019\\\"\\n end_date = \\\"15/10/2019\\\"\\n result = {\\\"abs_pressure\\\": 100, \\\"hum_in\\\": 20}\\n\\n start_dt = datetime.datetime.strptime(start_date, \\\"%d/%m/%Y\\\")\\n end_dt = datetime.datetime.strptime(end_date, \\\"%d/%m/%Y\\\")\\n\\n start = int((start_dt - datetime.datetime.fromtimestamp(0)).total_seconds())\\n end = int((end_dt - datetime.datetime.fromtimestamp(0)).total_seconds())\\n\\n mocked_conn = Mock(wrap=sqlite3.Connection)\\n mocked_cursor = Mock(wraps=sqlite3.Cursor)\\n\\n # operation\\n with patch.object(\\n self.db, \\\"db_connection\\\", return_value=mocked_conn\\n ) as mock_conn:\\n with patch.object(\\n mocked_conn, \\\"cursor\\\", return_value=mocked_cursor\\n ) as mock_curs:\\n with patch.object(mocked_cursor, \\\"execute\\\") as mock_exe:\\n with patch.object(\\n mocked_cursor, \\\"fetchall\\\", return_value=result\\n ) as mock_fetchall:\\n with patch.object(mocked_cursor, \\\"close\\\") as mock_cur_close:\\n with patch.object(mocked_conn, \\\"close\\\") as mock_con_close:\\n actual_result = self.db.get_data_for_specific_dates(\\n start_date, end_date\\n )\\n\\n # after\\n mock_conn.assert_called_once()\\n mock_curs.assert_called_once()\\n mock_fetchall.assert_called_once()\\n mock_exe.assert_any_call(\\n \\\"SELECT * FROM data WHERE idx BETWEEN ? AND ?\\\",\\n (str(start), str(end)),\\n )\\n mock_cur_close.assert_called_once()\\n mock_con_close.assert_called_once()\\n assert actual_result == result\",\n \"def test_get_table_list(self):\\n db_introspection = DatabaseIntrospection(self.connection)\\n cursor = mock.MagicMock()\\n\\n def list_tables(*args, **kwargs):\\n return [[\\\"Table_1\\\", \\\"t\\\"], [\\\"Table_2\\\", \\\"t\\\"]]\\n\\n cursor.run_sql_in_snapshot = list_tables\\n table_list = db_introspection.get_table_list(cursor=cursor)\\n self.assertEqual(\\n table_list,\\n [\\n TableInfo(name=\\\"Table_1\\\", type=\\\"t\\\"),\\n TableInfo(name=\\\"Table_2\\\", type=\\\"t\\\"),\\n ],\\n )\",\n \"def test_ocas():\\n path_here = Path(__file__).resolve().parent\\n for dirpath, _, filenames in os.walk(path_here):\\n fns_oca = [fn for fn in filenames if fn.endswith(\\\".oca\\\")]\\n fns_oca.sort(key=lambda fn: fn != 'foundproblems.oca')\\n for fn_oca in fns_oca:\\n print()\\n print(fn_oca)\\n do_test_oca_file(os.path.join(dirpath, fn_oca))\",\n \"def test_fetchall(self):\\n result = export.processExport(houseId=1)\\n #We should have 2 locations * 1 sensor * 10 days of data here\\n # 2 * 1 * (288 * 10) == 5670\\n #print result.shape\\n\\n #result.to_csv(\\\"temp.csv\\\")\\n #Do we get the right object\\n self.assertEqual(type(result), pandas.DataFrame)\\n #And is it the right size\\n self.assertEqual(result.shape, (2880, 2)) #So 2880 samples from two sensors\\n #And the right range of data\\n self.assertEqual(result.index[0], datetime.datetime(2013, 01, 01))\\n self.assertEqual(result.index[-1], datetime.datetime(2013, 01, 10, 23, 55))\",\n \"def object_finder(\\n self, datatable, objectlist, ralist, declist, radius,\\n longquery=True\\n ):\\n pass\",\n \"def test_get_waivers(league):\\n pass\",\n \"def query_and_read_frame(frame_type, channels, start_time, end_time):\\n logging.info('querying datafind server')\\n paths = frame_paths(frame_type, start_time, end_time)\\n logging.info('found files: %s' % (' '.join(paths)))\\n return read_frame(paths, channels, \\n start_time=start_time, \\n end_time=end_time)\",\n \"def test_frame_to_rows(self):\\n pass\",\n \"def test_do_select_all(test_dao):\\r\\n DUT = dtmFunction(test_dao, test=True)\\r\\n\\r\\n assert DUT.do_select_all(revision_id=1) is None\\r\\n assert isinstance(DUT.tree, Tree)\\r\\n assert isinstance(DUT.tree.get_node(1).data, RAMSTKFunction)\",\n \"def test_FRAME_DUoperations():\\n tmFrame0 = CCSDS.FRAME.TMframe()\\n print(\\\"tmFrame0 =\\\", tmFrame0)\\n print(\\\"\\\")\\n tmFrame1 = CCSDS.FRAME.TMframe(testData.TM_FRAME_01)\\n print(\\\"tmFrame1 =\\\", tmFrame1)\\n if tmFrame1.versionNumber != testData.TM_FRAME_01_versionNumber:\\n print(\\\"tmFrame1 versionNumber wrong:\\\", tmFrame1.versionNumber, \\\"- should be\\\", testData.TM_FRAME_01_versionNumber)\\n return False\\n if tmFrame1.spacecraftId != testData.TM_FRAME_01_spacecraftId:\\n print(\\\"tmFrame1 spacecraftId wrong:\\\", tmFrame1.spacecraftId, \\\"- should be\\\", testData.TM_FRAME_01_spacecraftId)\\n return False\\n if tmFrame1.virtualChannelId != testData.TM_FRAME_01_virtualChannelId:\\n print(\\\"tmFrame1 virtualChannelId wrong:\\\", tmFrame1.virtualChannelId, \\\"- should be\\\", testData.TM_FRAME_01_virtualChannelId)\\n return False\\n if tmFrame1.operationalControlField != testData.TM_FRAME_01_operationalControlField:\\n print(\\\"tmFrame1 operationalControlField wrong:\\\", tmFrame1.operationalControlField, \\\"- should be\\\", testData.TM_FRAME_01_operationalControlField)\\n return False\\n if tmFrame1.masterChannelFrameCount != testData.TM_FRAME_01_masterChannelFrameCount:\\n print(\\\"tmFrame1 masterChannelFrameCount wrong:\\\", tmFrame1.masterChannelFrameCount, \\\"- should be\\\", testData.TM_FRAME_01_masterChannelFrameCount)\\n return False\\n if tmFrame1.virtualChannelFCountLow != testData.TM_FRAME_01_virtualChannelFCountLow:\\n print(\\\"tmFrame1 virtualChannelFCountLow wrong:\\\", tmFrame1.virtualChannelFCountLow, \\\"- should be\\\", testData.TM_FRAME_01_virtualChannelFCountLow)\\n return False\\n if tmFrame1.secondaryHeaderFlag != testData.TM_FRAME_01_secondaryHeaderFlag:\\n print(\\\"tmFrame1 secondaryHeaderFlag wrong:\\\", tmFrame1.secondaryHeaderFlag, \\\"- should be\\\", testData.TM_FRAME_01_secondaryHeaderFlag)\\n return False\\n if tmFrame1.synchronisationFlag != testData.TM_FRAME_01_synchronisationFlag:\\n print(\\\"tmFrame1 synchronisationFlag wrong:\\\", tmFrame1.synchronisationFlag, \\\"- should be\\\", testData.TM_FRAME_01_synchronisationFlag)\\n return False\\n if tmFrame1.packetOrderFlag != testData.TM_FRAME_01_packetOrderFlag:\\n print(\\\"tmFrame1 packetOrderFlag wrong:\\\", tmFrame1.packetOrderFlag, \\\"- should be\\\", testData.TM_FRAME_01_packetOrderFlag)\\n return False\\n if tmFrame1.segmentLengthId != testData.TM_FRAME_01_segmentLengthId:\\n print(\\\"tmFrame1 segmentLengthId wrong:\\\", tmFrame1.segmentLengthId, \\\"- should be\\\", testData.TM_FRAME_01_segmentLengthId)\\n return False\\n if tmFrame1.firstHeaderPointer != testData.TM_FRAME_01_firstHeaderPointer:\\n print(\\\"tmFrame1 firstHeaderPointer wrong:\\\", tmFrame1.firstHeaderPointer, \\\"- should be\\\", testData.TM_FRAME_01_firstHeaderPointer)\\n return False\\n # extract packets and check it\\n leadingFragment, packets, trailingFragment = tmFrame1.getPackets()\\n if leadingFragment != testData.TM_FRAME_01_leadingFragment:\\n print(\\\"tmFrame1 leadingFragment wrong:\\\", leadingFragment, \\\"- should be\\\", testData.TM_FRAME_01_leadingFragment)\\n return False\\n if len(packets) != testData.TM_FRAME_01_nrPackets:\\n print(\\\"tmFrame1 nr. of packets wrong:\\\", len(packets), \\\"- should be\\\", testData.TM_FRAME_01_nrPackets)\\n return False\\n if trailingFragment != testData.TM_FRAME_01_trailingFragment:\\n print(\\\"tmFrame1 trailingFragment wrong:\\\", trailingFragment, \\\"- should be\\\", testData.TM_FRAME_01_trailingFragment)\\n return False\\n print(\\\"\\\")\\n tcFrame1 = CCSDS.FRAME.TCframe(testData.TC_FRAME_01)\\n print(\\\"tcFrame1 =\\\", tcFrame1)\\n if tcFrame1.versionNumber != testData.TC_FRAME_01_versionNumber:\\n print(\\\"tcFrame1 versionNumber wrong:\\\", tcFrame1.versionNumber, \\\"- should be\\\", testData.TC_FRAME_01_versionNumber)\\n return False\\n if tcFrame1.reservedFieldB != testData.TC_FRAME_01_reservedFieldB:\\n print(\\\"tcFrame1 reservedFieldB wrong:\\\", tcFrame1.reservedFieldB, \\\"- should be\\\", testData.TC_FRAME_01_reservedFieldB)\\n return False\\n if tcFrame1.virtualChannelId != testData.TC_FRAME_01_virtualChannelId:\\n print(\\\"tcFrame1 virtualChannelId wrong:\\\", tcFrame1.virtualChannelId, \\\"- should be\\\", testData.TC_FRAME_01_virtualChannelId)\\n return False\\n if tcFrame1.controlCommandFlag != testData.TC_FRAME_01_controlCommandFlag:\\n print(\\\"tcFrame1 controlCommandFlag wrong:\\\", tcFrame1.controlCommandFlag, \\\"- should be\\\", testData.TC_FRAME_01_controlCommandFlag)\\n return False\\n if tcFrame1.reservedFieldA != testData.TC_FRAME_01_reservedFieldA:\\n print(\\\"tcFrame1 reservedFieldA wrong:\\\", tcFrame1.reservedFieldA, \\\"- should be\\\", testData.TC_FRAME_01_reservedFieldA)\\n return False\\n if tcFrame1.frameLength != testData.TC_FRAME_01_frameLength:\\n print(\\\"tcFrame1 frameLength wrong:\\\", tcFrame1.frameLength, \\\"- should be\\\", testData.TC_FRAME_01_frameLength)\\n return False\\n if tcFrame1.sequenceNumber != testData.TC_FRAME_01_sequenceNumber:\\n print(\\\"tcFrame1 sequenceNumber wrong:\\\", tcFrame1.sequenceNumber, \\\"- should be\\\", testData.TC_FRAME_01_sequenceNumber)\\n return False\\n if tcFrame1.spacecraftId != testData.TC_FRAME_01_spacecraftId:\\n print(\\\"tcFrame1 spacecraftId wrong:\\\", tcFrame1.spacecraftId, \\\"- should be\\\", testData.TC_FRAME_01_spacecraftId)\\n return False\\n if tcFrame1.bypassFlag != testData.TC_FRAME_01_bypassFlag:\\n print(\\\"tcFrame1 bypassFlag wrong:\\\", tcFrame1.bypassFlag, \\\"- should be\\\", testData.TC_FRAME_01_bypassFlag)\\n return False\\n tcFrame2 = CCSDS.FRAME.TCframe(testData.TC_FRAME_02)\\n if tcFrame2.versionNumber != testData.TC_FRAME_02_versionNumber:\\n print(\\\"tcFrame2 versionNumber wrong:\\\", tcFrame2.versionNumber, \\\"- should be\\\", testData.TC_FRAME_02_versionNumber)\\n return False\\n if tcFrame2.reservedFieldB != testData.TC_FRAME_02_reservedFieldB:\\n print(\\\"tcFrame2 reservedFieldB wrong:\\\", tcFrame2.reservedFieldB, \\\"- should be\\\", testData.TC_FRAME_02_reservedFieldB)\\n return False\\n if tcFrame2.virtualChannelId != testData.TC_FRAME_02_virtualChannelId:\\n print(\\\"tcFrame2 virtualChannelId wrong:\\\", tcFrame2.virtualChannelId, \\\"- should be\\\", testData.TC_FRAME_02_virtualChannelId)\\n return False\\n if tcFrame2.controlCommandFlag != testData.TC_FRAME_02_controlCommandFlag:\\n print(\\\"tcFrame2 controlCommandFlag wrong:\\\", tcFrame2.controlCommandFlag, \\\"- should be\\\", testData.TC_FRAME_02_controlCommandFlag)\\n return False\\n if tcFrame2.reservedFieldA != testData.TC_FRAME_02_reservedFieldA:\\n print(\\\"tcFrame2 reservedFieldA wrong:\\\", tcFrame2.reservedFieldA, \\\"- should be\\\", testData.TC_FRAME_02_reservedFieldA)\\n return False\\n if tcFrame2.frameLength != testData.TC_FRAME_02_frameLength:\\n print(\\\"tcFrame2 frameLength wrong:\\\", tcFrame2.frameLength, \\\"- should be\\\", testData.TC_FRAME_02_frameLength)\\n return False\\n if tcFrame2.sequenceNumber != testData.TC_FRAME_02_sequenceNumber:\\n print(\\\"tcFrame2 sequenceNumber wrong:\\\", tcFrame2.sequenceNumber, \\\"- should be\\\", testData.TC_FRAME_02_sequenceNumber)\\n return False\\n if tcFrame2.spacecraftId != testData.TC_FRAME_02_spacecraftId:\\n print(\\\"tcFrame2 spacecraftId wrong:\\\", tcFrame2.spacecraftId, \\\"- should be\\\", testData.TC_FRAME_02_spacecraftId)\\n return False\\n if tcFrame2.bypassFlag != testData.TC_FRAME_02_bypassFlag:\\n print(\\\"tcFrame2 bypassFlag wrong:\\\", tcFrame2.bypassFlag, \\\"- should be\\\", testData.TC_FRAME_02_bypassFlag)\\n return False\\n clcw = CCSDS.FRAME.CLCW()\\n print(\\\"clcw =\\\", clcw)\\n return True\",\n \"def test_get_list(self):\\n pass\",\n \"def test_return_all_names(self):\\n test = self.data.return_all(first_name='Nik', last_name='Silver')\\n self.assertEqual(test[0].first_name, 'Nik')\\n\\n test_2 = self.data.return_all(first_name='Trevor', last_name='Harvey')\\n self.assertEqual(test_2[0].last_name, 'Harvey')\",\n \"def test_index(self):\",\n \"def test_run_any_search(): # ***Incomplete test\\n ##########################\\n # Arrange.\\n queryfile = \\\"queryfile\\\"\\n\\n ##########################\\n # Act.\\n #x = run_any_search(queryfile)\\n\\n ##########################\\n # Assert.\\n assert True == True # ***Temporary.\",\n \"def all(self):\",\n \"def all(self):\",\n \"def test_findbymembers(self):\\n p1, p2, p3 = self.create3persons()\\n model.Team(name='Tigers', persons=[p1, p2, p3]).store()\\n model.Team(name='Lions', persons=[p1,p2]).store()\\n model.Team(name='Snakes', persons=[p2, p3]).store()\\n\\n teams = model.Team.find_teams_by_members(p1) # find all teams with p1 (2)\\n self.assertEqual(len(teams), 2)\",\n \"def test_get_file_accessors(self):\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8545172","0.7348566","0.73415834","0.7203369","0.7158465","0.6796761","0.6632994","0.6604659","0.6478488","0.6478216","0.62701315","0.62148196","0.6200575","0.61729914","0.61653095","0.61079854","0.607584","0.60689676","0.6063073","0.59820056","0.5940945","0.5938584","0.5920173","0.59193087","0.5897583","0.5893709","0.58741325","0.5872574","0.5755047","0.574134","0.573938","0.5698506","0.5685897","0.5647886","0.5555679","0.55520207","0.5523512","0.550234","0.547626","0.54729366","0.5452576","0.5450327","0.54483956","0.54341537","0.5427446","0.5408679","0.5391256","0.53845364","0.53713197","0.5353744","0.5348185","0.5326139","0.53237545","0.53229946","0.5322284","0.5294794","0.5291926","0.526484","0.52593356","0.52348584","0.5222839","0.52156","0.5212007","0.5162645","0.5150729","0.5140521","0.5138857","0.5138172","0.50876135","0.5083207","0.508026","0.50441265","0.50441265","0.50362706","0.5031989","0.5031485","0.5013586","0.50074226","0.49907202","0.49736655","0.49642","0.49640393","0.4962746","0.49604127","0.4949384","0.49391836","0.49340862","0.49335733","0.49334717","0.49312416","0.49255028","0.4924766","0.49198088","0.49152556","0.49101102","0.49062335","0.49051774","0.49051774","0.49002403","0.48972934"],"string":"[\n \"0.8545172\",\n \"0.7348566\",\n \"0.73415834\",\n \"0.7203369\",\n \"0.7158465\",\n \"0.6796761\",\n \"0.6632994\",\n \"0.6604659\",\n \"0.6478488\",\n \"0.6478216\",\n \"0.62701315\",\n \"0.62148196\",\n \"0.6200575\",\n \"0.61729914\",\n \"0.61653095\",\n \"0.61079854\",\n \"0.607584\",\n \"0.60689676\",\n \"0.6063073\",\n \"0.59820056\",\n \"0.5940945\",\n \"0.5938584\",\n \"0.5920173\",\n \"0.59193087\",\n \"0.5897583\",\n \"0.5893709\",\n \"0.58741325\",\n \"0.5872574\",\n \"0.5755047\",\n \"0.574134\",\n \"0.573938\",\n \"0.5698506\",\n \"0.5685897\",\n \"0.5647886\",\n \"0.5555679\",\n \"0.55520207\",\n \"0.5523512\",\n \"0.550234\",\n \"0.547626\",\n \"0.54729366\",\n \"0.5452576\",\n \"0.5450327\",\n \"0.54483956\",\n \"0.54341537\",\n \"0.5427446\",\n \"0.5408679\",\n \"0.5391256\",\n \"0.53845364\",\n \"0.53713197\",\n \"0.5353744\",\n \"0.5348185\",\n \"0.5326139\",\n \"0.53237545\",\n \"0.53229946\",\n \"0.5322284\",\n \"0.5294794\",\n \"0.5291926\",\n \"0.526484\",\n \"0.52593356\",\n \"0.52348584\",\n \"0.5222839\",\n \"0.52156\",\n \"0.5212007\",\n \"0.5162645\",\n \"0.5150729\",\n \"0.5140521\",\n \"0.5138857\",\n \"0.5138172\",\n \"0.50876135\",\n \"0.5083207\",\n \"0.508026\",\n \"0.50441265\",\n \"0.50441265\",\n \"0.50362706\",\n \"0.5031989\",\n \"0.5031485\",\n \"0.5013586\",\n \"0.50074226\",\n \"0.49907202\",\n \"0.49736655\",\n \"0.49642\",\n \"0.49640393\",\n \"0.4962746\",\n \"0.49604127\",\n \"0.4949384\",\n \"0.49391836\",\n \"0.49340862\",\n \"0.49335733\",\n \"0.49334717\",\n \"0.49312416\",\n \"0.49255028\",\n \"0.4924766\",\n \"0.49198088\",\n \"0.49152556\",\n \"0.49101102\",\n \"0.49062335\",\n \"0.49051774\",\n \"0.49051774\",\n \"0.49002403\",\n \"0.48972934\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.76647025"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":92998,"cells":{"query":{"kind":"string","value":"Finds all nonnested open reading frames in the given DNA sequence in all 3 possible frames and returns them as a list. By nonnested we mean that if an ORF occurs entirely within another ORF and they are both in the same frame, it should not be included in the returned list of ORFs."},"document":{"kind":"string","value":"def find_all_ORFs(dna):\n res = []\n for i in range(0, 3):\n s = dna[i:]\n# print i, s,\n# l = len(s)\n# for j in range(0, l, 3):\n# if s[j: j + 3] == start_codon:\n# r = find_all_ORFs_oneframe(s[j:])\n# print r\n# if len(r) > 0:\n# for item in r:\n# res.append(item)\n# break # careful for indentation here!!\n r = find_all_ORFs_oneframe(s)\n if len(r) > 0:\n# for item in r:\n# res.append(item)\n res += r # [WOW] I love python!\n return res"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def find_all_ORFs(dna):\n index = 0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# initialize index\n all_ORFs = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitalize empty list\n while index < 3:\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# switches throught the 3 frames\n \tall_ORFs = all_ORFs + find_all_ORFs_oneframe(dna[index:])\t# adds all ORFs oneframe to the list\n \tindex += 1\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# indexes +1\n return all_ORFs \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns list of all ORFs in all 3 frames","def find_all_ORFs(dna):\n all_ORFs=[]\n for i in range (0,3):\n \tframe=dna[i:] \n all_ORFs+=find_all_ORFs_oneframe(frame)\n return all_ORFs","def find_all_ORFs_oneframe(dna):\n condition = 1\n dna2 = dna\n list_of_ORFs = []\n while condition == 1:\n num_codons = int(len(dna2)/3)\n num = 0\n list_codons = []\n start_index = -1\n while num < num_codons:\n num_start = int(num*3)\n num_end = int(num*3 + 3)\n list_codons.append(dna2[num_start:num_end])\n num = num + 1\n for element in list_codons:\n if element == 'ATG':\n start_index = list_codons.index(element)\n break\n if start_index != -1:\n this_orf = rest_of_ORF(dna2[start_index*3:])\n list_of_ORFs.append(this_orf)\n dna2 = dna2[start_index*3+len(this_orf)+3:]\n else:\n condition = 2\n\n return list_of_ORFs","def find_all_ORFs(dna):\n first_frame = find_all_ORFs_oneframe(dna[0:])\n second_frame = find_all_ORFs_oneframe(dna[1:])\n third_frame = find_all_ORFs_oneframe(dna[2:])\n list_of_frames = first_frame + second_frame + third_frame\n return list_of_frames","def find_all_ORFs(dna):\n all_ORFs = []\n for i in range(0, 3):\n dna_new = dna[i:]\n all_ORFs += find_all_ORFs_oneframe(dna_new)\n return all_ORFs","def find_all_ORFs_oneframe(dna):\n \n\n ORFs=[]\n i=0\n while i<len(dna):\n if dna[i:i+3]==\"ATG\":\n j=i\n dna2=rest_of_ORF(dna[j:])\n \n if dna2==None:\n \tbreak\n ORFs.append(dna2)\n i=i+len(dna2)\n i=i+3\n return ORFs","def find_all_ORFs_oneframe(dna):\n dna_split = split_into_codons(dna)\n i = 0\n all_ORFs_oneframe = []\n length_of_orf = 0\n while i < len(dna_split):\n if dna_split[i] == \"ATG\":\n orf = rest_of_ORF(dna[int(i)*3:])\n all_ORFs_oneframe += [orf]\n length_of_orf = math.ceil(len(orf)/3)\n i += length_of_orf\n else:\n i += 1\n return all_ORFs_oneframe","def find_all_ORFs_oneframe(dna):\n\n ORFlist = []\n i = 0\n lend = len(dna)\n while i < lend:\n codon = dna[i:i+3]\n if codon == 'ATG':\n orf = rest_of_ORF(dna[i:])\n ORFlist.append(orf)\n i = i + len(orf)\n else:\n i = i+3\n return ORFlist","def find_all_ORFs_oneframe(dna):\n x = 3\n list_of_dna = []\n while (x < len(dna)):\n if dna[x-3:x] == 'ATG':\n current_dna = rest_of_ORF(dna[x-3:])\n list_of_dna.append(current_dna)\n x += len(current_dna)\n x += 3\n return list_of_dna","def find_all_ORFs(dna):\n dnatwo = dna[1:]\n dnathree = dna[2:]\n all_ORFs = find_all_ORFs_oneframe(dna)\n all_ORFs.extend(find_all_ORFs_oneframe(dnatwo))\n all_ORFs.extend(find_all_ORFs_oneframe(dnathree))\n if [] in all_ORFs:\n all_ORFs.remove([])\n return all_ORFs","def find_all_ORFs_oneframe(dna):\n i=0 \n ORF_list = []\n while i<len(dna):\n if dna[i : i+3] == \"ATG\":\n start_place = i \n current_ORF = rest_of_ORF(dna[start_place:])\n i += 3 + len(current_ORF)\n ORF_list.append(current_ORF) \n return ORF_list","def find_all_ORFs_oneframe(dna):\n i = 0\n list_ORF = []\n\n def search_ORF(dna,i):\n aa = dna[3*i:(3*i)+3]\n if aa == 'ATG':\n list_ORF.append(rest_of_ORF(dna,aa,i))\n i = i + 1 + len(rest_of_ORF(dna,aa,i))/3\n else:\n i = i + 1\n if len(aa) ==3:\n search_ORF(dna,i)\n \n return list_ORF\n\n return search_ORF(dna,i)\n # i = i + ((len(list_ORF[-1]))/3)\n # search_ORF(dna,i)","def find_all_ORFs_oneframe(dna):\n\tindex = 0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# unitiate index at 0\n\tsegment = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitializes empty list\n\twhile index < len(dna):\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# given that index is smaller than length of string\n\t\tcodon = dna[index:index + 3]\t\t\t\t\t\t\t\t\t\t\t\t\t\t# creates codons from nucleotides starting with first 3 letters\n\t\tif codon == \"ATG\":\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if the codon is ATG\n\t\t\tsegment.append(rest_of_ORF(dna[index:]))\t\t\t\t\t\t\t\t\t\t# run rest_of_ORF starting at index\n\t\t\tindex = index + len(rest_of_ORF(dna[index:]))\t\t\t\t\t\t\t\t\t# new index starting at old + length of ORF output string\n\t\telse:\n\t\t\tindex += 3\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if ATG isn't found, move to next codon and check again\n\n\treturn segment\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns list of ORFs","def find_all_ORFs(dna):\n\n readingFrame0 = ''\n readingFrame1 = ''\n readingFrame2 = ''\n output = ''\n for k in range(0,3): \n if k ==0: \n readingFrame0 = find_all_ORFs_oneframe(dna[k:])\n elif k ==1: \n readingFrame1 = find_all_ORFs_oneframe(dna[k:])\n elif k ==2:\n readingFrame2 = find_all_ORFs_oneframe(dna[k:])\n print 'Reading Frame 1: ' + str(readingFrame0) + ', Reading Frame 2: ' + str(readingFrame1) + ', Reading Frame 3: ' + str(readingFrame2)\n output = readingFrame0 + readingFrame1 + readingFrame2\n return output","def find_all_ORFs(dna):\n ORFs = find_all_ORFs_oneframe(dna) + find_all_ORFs_oneframe(dna[1:]) + find_all_ORFs_oneframe(dna[2:])\n\n return ORFs","def find_all_ORFs_oneframe(dna):\n res = []\n l = len(dna)\n next_pos = 0\n while True:\n arg = dna[next_pos:]\n# orf = rest_of_ORF(arg)\n# res.append(orf)\n# if arg == orf: # if: no stop codon\n# break\n# next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\n# if next_pos >= l: # if: meet the end of dna\n# break\n if arg[0:3] == start_codon:\n orf = rest_of_ORF(arg)\n res.append(orf)\n if arg == orf: # if: no stop codon\n break\n next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\n else: # if: not start codon, see next\n next_pos += 3\n if next_pos >= l: # if: meet or go beyond the end of dna\n break\n return res","def find_all_ORFs_oneframe(dna):","def find_all_ORFs(dna):\n ans = find_all_ORFs_oneframe(dna)\n ans.extend(find_all_ORFs_oneframe(dna[1:]))\n ans.extend(find_all_ORFs_oneframe(dna[2:]))\n return ans","def find_all_ORFs(dna):\n all_ORFs = []\n i = 0\n\n for i in range (0,3): \n all_ORFs.extend(find_all_ORFs_oneframe(dna))\n dna = 'X' + dna\n\n return all_ORFs","def find_all_ORFs_oneframe(dna):\n #inital conditions\n i = 0\n start_codon = ('ATG')\n end_index = len(dna)\n return_variable = []\n\n #for each codon in the set of DNA, check if it is a start codon\n #if it is a start codon, add the string until the stop codon to a list\n #then continue running\n while i < len(dna)-2:\n codon = dna[i:i+3] \n if codon in start_codon:\n orf = rest_of_ORF(dna[i:])\n return_variable.append(orf)\n i += len(orf)\n i += 3\n\n\n #return a list of strings of DNA\n return return_variable","def find_all_ORFs(dna):\n #inital conditions\n i = 0\n start_codon = ('ATG')\n end_index = len(dna)\n return_variable = []\n\n #for statement tells the code to run three times at three inital index values\n #0,1,and 2 which allows for each reading frame to be read\n for i in range (3):\n while i < (len(dna)-2):\n codon = dna[i:i+3] \n if codon in start_codon: #check if the codon the code is looking at is a start codon\n orf = rest_of_ORF(dna[i:]) #then determine that this is an orf, make it a string given the index of the start codon\n return_variable.append(orf) #and append said string to a list of ORFs\n i += len(orf) \n i += 3\n #return a list of strings of DNA from both strands\n return return_variable","def find_all_ORFs_oneframe(dna):\n strand = []\n startCodon = [\"ATG\"]\n for i in range(0,len(dna),3):\n triple = dna[i:i+3]\n if triple in startCodon: \n strand.append(rest_of_ORF(dna[i:]))\n print strand\n return strand","def find_all_ORFs(dna):\n #these functions offset to analyze each each open frame reference\n zero_offset=find_all_ORFs_oneframe(dna[0:])\n \n one_offset=find_all_ORFs_oneframe(dna[1:])\n \n two_offset=find_all_ORFs_oneframe(dna[2:])\n \n return zero_offset+one_offset+two_offset\n \n # YOUR IMPLEMENTATION HERE","def rest_of_ORF(dna):\n readingFrame = ''\n endCodons = [\"TAG\", \"TAA\", \"TGA\"]\n for i in range(0,len(dna),3):\n triple = dna[i:i+3]\n if triple in endCodons:\n readingFrame = readingFrame\n break\n else: \n readingFrame+=triple \n return readingFrame","def reading_frames(dna):\n #the 6 types are as follows\n # the actual string and the reverse complement\n list = []\n #this is the actual string\n list.append(dna)\n #this is the reverse complement of the string\n # done reusing the fastcomplement() method that was already available.\n #others are done likewise\n list.append(fast_complement(dna[::-1]))\n list.append(dna[1:len(dna)])\n list.append(fast_complement(dna[1:len(dna)][::-1]))\n list.append(dna[2:len(dna)])\n list.append(fast_complement(dna[2:len(dna)][::-1]))\n return list","def find_all_ORFs_oneframe_unit_tests(dna, expected):\n\n print find_all_ORFs_oneframe(\"ATGCATGAATGTAGATAGATGTGCCC\")\n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + find_all_ORFs_oneframe(dna)","def find_all_ORFs_oneframe_unit_tests():\n\n input = [\"dna\"]\n expected_output = [\"all non-nester ORFs\"]\n actual = []\n for k in input:\n actual.append(find_all_ORFs_oneframe(k))\n print input \n print actual\n print expected_output","def getouterframes(frame, context=1):\r\n framelist = []\r\n while frame:\r\n framelist.append((frame,) + getframeinfo(frame, context))\r\n frame = frame.f_back\r\n return framelist","def find_all_ORFs_oneframe_unit_tests():\n data_list = [\n [\"ATGCATGAATGTAGATAGATGTGCCC\", [\"ATGCATGAATGTAGA\", \"ATGTGCCC\"]],\n [\"ATGTAGATGTAG\", [\"ATG\", \"ATG\"]],\n [\"ATGATGATG\", [\"ATGATGATG\"]],\n [\"ATGGGGGATTAGATGATG\", [\"ATGGGGGAT\", \"ATGATG\"]],\n [\"ATGTGAATGTAA\", [\"ATG\", \"ATG\"]],\n [\"ATGTGAATGTAAATG\", [\"ATG\", \"ATG\", \"ATG\"]],\n [\"ATGCGTGGTGATTAGATGGATGGGGATTGA\", [\"ATGCGTGGTGAT\", \"ATGGATGGGGAT\"]],\n [\"ATGAAATTTCCCGGGAAATTTCCCGGG\", [\"ATGAAATTTCCCGGGAAATTTCCCGGG\"]],\n [\"ATGAAATTTTGAATGGGGCCC\", [\"ATGAAATTT\", \"ATGGGGCCC\"]],\n [\"ATGAAATTTTGAATGGGGCCCTAG\", [\"ATGAAATTT\", \"ATGGGGCCC\"]],\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs_oneframe(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def ORFs(self):\n ORFStart = None\n openLeft = True\n seenStart = False\n\n for index, residue in enumerate(self.sequence):\n if residue == 'M':\n # Start codon.\n openLeft = False\n seenStart = True\n elif residue == '*':\n # Stop codon. Yield an ORF, if it has non-zero length.\n if ORFStart is not None and index - ORFStart > 0:\n # The ORF has non-zero length.\n yield AAReadORF(self, ORFStart, index, openLeft, False)\n ORFStart = None\n # After a stop codon, we can no longer be open on the left\n # and we have no longer seen a start codon.\n openLeft = seenStart = False\n else:\n if (seenStart or openLeft) and ORFStart is None:\n ORFStart = index\n\n # End of sequence. Yield the final ORF if there is one and it has\n # non-zero length.\n length = len(self.sequence)\n if ((seenStart or openLeft) and ORFStart is not None and\n length - ORFStart > 0):\n yield AAReadORF(self, ORFStart, length, openLeft, True)","def find_longest_orfs(seq,n_orfs):\n\n # Make sure there is a start codon in the sequence:\n if not 'ATG' in seq:\n raise RuntimeError(\"Your DNA sequence doesn't have a start codon.\")\n\n # Initialize orfs list:\n orfs =[]\n\n # Loop over sequence and find ORFs:\n for i, base in enumerate(seq):\n triplet = seq[i:i+3]\n if triplet == 'ATG':\n orf_seq = ''\n aa_seq = ''\n j = i\n while j+2 < len(seq):\n codon = seq[j:j+3]\n orf_seq += codon\n if bioinfo_dicts.codons[codon] == '*': # if stop codon\n orf_len = len(orf_seq)\n orfs.append((orf_len,orf_seq,aa_seq)) # j is orf len in nts\n break # this only breaks out of while loop, right?\n else:\n aa_seq += bioinfo_dicts.codons[codon]\n j+=3\n\n # Sort orf list by length\n orfs.sort()\n\n # Select n longest orfs to return:\n number = -(n_orfs+1)\n longest_orfs = orfs[:number:-1]\n\n longest_orfs = tuple(longest_orfs)\n return longest_orfs","def find_all_ORFs_oneframe(dna): \n i=0\n multiple_list=[]\n while i < len(dna):\n part = dna[i:i+3]\n if part == 'ATG': #if the first indecied are ATG then it runs the code that creates the string of DNA\n ORF=rest_of_ORF(dna[i:]) \n multiple_list.append(ORF)\n i+=len(ORF)\n else:\n i+=3\n # print multiple_list\n return multiple_list\n \n #runs fuinction to mmake list of function\n #need to save to list\n #need to continue to next ATG start \n #need to add that to list\n #need to output new list as commas between lists","def find_all_ORFs_both_strands(dna):\n orfs = []\n orfs = find_all_ORFs(dna) + find_all_ORFs(get_reverse_complement(dna))\n return orfs","def get_open_issues(self, owners: List[str]) -> List[EventRecord]:\n with self.session.begin() as session:\n open_issues = (\n session.query(EventRecord)\n .filter(EventRecord.owner.in_(owners))\n .filter(EventRecord.received_at >= datetime.utcnow() - timedelta(days=1))\n .all()\n )\n\n open_issues = remove_duplicate_events(open_issues)\n\n open_issues_fps = [issue.fingerprint for issue in open_issues]\n\n ignored_issues_fps_tuples = (\n session.query(IgnoreFingerprintRecord.fingerprint)\n .filter(IgnoreFingerprintRecord.fingerprint.in_(open_issues_fps))\n .filter(\n (IgnoreFingerprintRecord.expires_at > datetime.utcnow())\n | (IgnoreFingerprintRecord.expires_at.is_(None))\n )\n .all()\n )\n\n ignored_issues_fps = [t[0] for t in ignored_issues_fps_tuples]\n\n return [issue for issue in open_issues if issue.fingerprint not in ignored_issues_fps]","def find_all_ORFs_oneframe_unit_tests():\n input_a='ATGATTATTTGATGAATGGATTGA'\n expected_output='[ATGATTATT,ATGGAT]'\n actual_output=find_all_ORFs_oneframe(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output\n \n input_a='ATGGGATTGTTT'\n expected_output='[ATGGATTGTTT]'\n actual_output=find_all_ORFs_oneframe(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output","def rest_of_ORF(dna):\n\n #inital conditions\n i = 3\n end_index = len(dna)\n stop_codon = ('TAG','TAA','TGA')\n\n #for the length of the string of DNA, run through each codon and break and return the indec of the string if the codon is a stop codon\n while i < len(dna)-2:\n codon = dna[i:i+3] #takes only every third index which is the length of a codon\n if codon in stop_codon:\n end_index = i \n break\n i += 3\n #returns a list from the start codon to the index where the stop codon begins\n return dna[0:end_index]","def test_fasta_get_codon_info_from_seq_all_frames(self):\r\n\r\n codon_info_f1, codon_info_f2, codon_info_f3 = mfau.get_codons_from_sequence_three_framed(\"AGGTGACACCGCAAGCCTTATATTAGC\")\r\n\r\n if debug:\r\n print \"condons in frame1:\"\r\n for codon in codon_info_f1.codons:\r\n print \"\\t\" + codon\r\n\r\n self.assertGreaterEqual(len(codon_info_f1.codons), 0)\r\n\r\n if debug:\r\n print \"condons in frame2:\"\r\n for codon in codon_info_f2.codons:\r\n print \"\\t\" + codon\r\n\r\n self.assertGreaterEqual(len(codon_info_f2.codons), 0)\r\n\r\n if debug:\r\n print \"condons in frame3:\"\r\n for codon in codon_info_f3.codons:\r\n print \"\\t\" + codon\r\n\r\n self.assertGreaterEqual(len(codon_info_f3.codons), 0)","def rest_of_ORF(dna):\n end_dna = len(dna)\n for group in range(0, end_dna, 3):\n strand = dna[group:group+3]\n if strand in ['TGA', 'TAA', 'TAG']:\n return dna[0:group]\n return dna","def rest_of_ORF(dna,aa,i):\n\n rest_of_ORF = []\n \n while len(aa) ==3 and aa not in stop_codons: #run this loop until locating a stop\n # if len(aa) == 3:\n rest_of_ORF.append (aa) #add each successive codon to list\n i = i+1\n aa = dna[3*i:(3*i)+3]\n # else:\n # rest_of_ORF.append (aa)\n # return ''.join(rest_of_ORF)\n\n return ''.join(rest_of_ORF)","def longest_ORF(dna):\n\n reverseComp = get_reverse_complement(dna)\n openFramesfromReverse = find_all_ORFs(reverseComp)\n openFramesfromNormal = find_all_ORFs(dna)\n all_ORFs = openFramesfromNormal + openFramesfromReverse\n longest = max(all_ORFs, key=len)\n return longest","def find_all_ORFs(dna):\n \n # YOUR IMPLEMENTATION HERE","def find_all_ORFs_both_strands(dna):\n reverse_dna = get_reverse_complement(dna)\n orfs = find_all_ORFs(dna)\n backward_orfs = find_all_ORFs(reverse_dna)\n orfs.extend(backward_orfs)\n return orfs","def find_surrounding_frames(frame, frames_with):\n # If frame is missing from the beginning, return initial frame twice.\n if (frame < frames_with[0]):\n return frames_with[0], frames_with[0], frames_with[0] - frame\n # If frame is missing from the end, return last frame twice.\n elif (frame > frames_with[-1]):\n return frames_with[-1], frames_with[-1], frame - frames_with[-1]\n # If frame is missing in the middle, return surrounding frames.\n else:\n for i in range(1, len(frames_with)):\n frame_before = frames_with[i-1]\n frame_after = frames_with[i]\n if (frame > frame_before and frame < frame_after):\n return frame_before, frame_after, frame_after - frame_before - 1","def find_all_ORFs_both_strands(dna):\n return find_all_ORFs(dna) + (find_all_ORFs(get_reverse_complement(dna)))","def find_all_ORFs_both_strands(dna):\n both_strands_ORFs = []\n\n both_strands_ORFs.extend(find_all_ORFs(dna))\n both_strands_ORFs.extend(find_all_ORFs(get_reverse_complement(dna)))\n \n return both_strands_ORFs","def find_all_ORFs_unit_tests():\n \n input = [\"dna\"]\n expected_output = [\"all non-nested ORFs\"]\n actual = []\n for k in input:\n actual.append(find_all_ORFs(k))\n print input \n print actual\n print expected_output","def rest_of_ORF(dna):\n STOP_CODONS=['TAG','TGA','TAA' ]#constants are uppercase\n for i in range(0,len(dna),3):\n codon=dna[i:i+3]\n if codon in STOP_CODONS:\n return dna[0:i]\n return dna","def find_all_ORFs_both_strands(dna):\n return find_all_ORFs(dna) + find_all_ORFs(get_reverse_complement(dna))","def rest_of_ORF(dna):\n\t# TODO: implement this\n\tindex = 0\n\twhile index < len(dna):\n\t\tcodon = dna[index:index + 3]\t\t\t\t\t\t\t\t\t\t\t\t\t\t# groups 3 nucleotides to make codon, index by 3\n\t\tif codon in [\"TAA\", \"TAG\", \"TGA\"]:\t\t\t\t\t\t\t\t\t\t\t\t\t# checks if stop codon is in string\n\t\t\treturn dna[:index]\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if True, returns string up to stop codon\n\t\tindex += 3\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# indexes by 3\n\treturn dna","def find_all_ORFs_unit_tests(dna, expected):\n \n print find_all_ORFs(\"ATGCATGAATGTAG\")\n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + find_all_ORFs(dna)","def rest_of_ORF(dna):\n num_codons = int(len(dna)/3)\n num = 0\n list_codons = []\n cut_dna = ''\n stop_index = -1\n while num < num_codons:\n num_start = int(num*3)\n num_end = int(num*3 + 3)\n list_codons.append(dna[num_start:num_end])\n num = num + 1\n for element in list_codons:\n if element == 'TAA' or element == 'TAG' or element == 'TGA':\n stop_index = list_codons.index(element)\n break\n\n if stop_index != -1:\n this_ORF = list_codons[0:stop_index]\n for element in this_ORF:\n cut_dna = cut_dna + element\n return cut_dna\n else:\n return dna","def count_frames():\n frames = sentence.sem.frames.find_all('frame', {'name' : NEGATION_FRAME_NAME})\n frame_count = []\n for f_r in frames:\n frame_count.append(f_r)\n return len(frame_count)","def test_multi_line_missing_frames():\n\n for protocol in LEGACY_PROTOCOLS:\n p = protocol([])\n\n\n test_case = [\n \"48 6B 10 49 02 01 00 01 02 03 FF\",\n \"48 6B 10 49 02 02 04 05 06 07 FF\",\n \"48 6B 10 49 02 03 08 09 0A 0B FF\",\n ]\n\n for n in range(len(test_case) - 1):\n sub_test = list(test_case)\n del sub_test[n]\n\n r = p(sub_test)\n assert len(r) == 0","def gene_finder(dna):\n threshold = longest_ORF_noncoding(dna, 1500)\n l = []\n for i in find_all_ORFs_both_strands(dna):\n \tif len(i)>=threshold:\n \t\tl.append(coding_strand_to_AA(i))\n print l\n return l","def rest_of_ORF(dna):\n \n if dna[:3]== \"TAG\" or dna[:3]==\"TAA\" or dna[:3]==\"TGA\" or len(dna)<3:\n return \"\"\n if len(dna)<=3:\n return dna\n return dna[:3]+rest_of_ORF(dna[3:])","def rest_of_ORF(dna):\n index = -1\n dna_split = split_into_codons(dna)\n\n for i, j in enumerate(dna_split):\n if j == \"TAG\" or j == \"TGA\" or j == \"TAA\":\n index = i\n if index == -1:\n return ''.join(dna_split) # if there is no stop codon\n return ''.join(dna_split[:index])","def longest_ORF(dna):\n \n all_ORFs = find_all_ORFs_both_strands(dna)\n\n if len(all_ORFs) > 0:\n return max(all_ORFs, key = len)\n else:\n return []","def findGaps(sequence):\n patt = re.compile(r\"[Nn]+\")\n for match in patt.finditer(sequence):\n yield (match.start(), match.end())","def find_all_ORFs_unit_tests():\n data_list = [\n [\"ATGCATGAATGTAG\", [\"ATGCATGAATGTAG\", \"ATGAATGTAG\", \"ATG\"]],\n [\"ATG\", [\"ATG\"]],\n [\"AATG\", [\"ATG\"]],\n [\"AAATG\", [\"ATG\"]],\n [\"ATGATG\", [\"ATGATG\"]],\n [\"ATATGGATTGA\", [\"ATGGAT\"]],\n [\"ATGAGATTAG\", [\"ATGAGATTAG\"]],\n [\"ATATGGATTAGTAGTAATGAAAGTATAG\", [\"ATGAAAGTA\", \"ATGGAT\", ]],\n# ATA TGG ATT AGT AGT AAT GAA AGT ATA G\n# TAT GGA TTA GTA GTA ATG AAA GTA TAG\n# ATG GAT TAG TAG TAA TGA AAG TAT AG\n [\"ATGTCACGCAATGTAGGATGGATGGATTAGAC\", [\"ATGTCACGCAATGTAGGATGGATGGAT\", \"ATG\", \"ATGGATGGATTAGAC\"]],\n# ATG TCA CGC AAT GTA GGA TGG ATG GAT TAG AC --> ATG TCA CGC AAT GTA GGA TGG ATG GAT\n# TGT CAC GCA ATG TAG GAT GGA TGG ATT AGA C\n# GTC ACG CAA TGT AGG ATG GAT GGA TTA GAC\n [\"ATGATGTAG\", [\"ATGATG\"]],\n [\"TCGATGC\", [\"ATGC\"]],\n [\"AAA\", []],\n# TCG ATG C\n# CGA TGC\n# GAT GC\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def prune_decoded_seqs(seqs):\r\n out = []\r\n for s in seqs:\r\n if EOS in s:\r\n idx = s.index(EOS)\r\n out += [s[:idx]]\r\n else:\r\n out += [s]\r\n return out","def get_open_cells(field: MineField, cell: Cell) -> List[Cell]:\n # TODO re-implement iteratively to safe stack space (especially for large boards)\n if cell.is_flag or cell.is_mine or not field.cell_is_safe(cell):\n return [cell]\n \n if cell.visited:\n return\n\n open_cells: list = list()\n cell.visited = True\n open_cells.append(cell)\n\n for cell in field.surrounding_cells(cell):\n open_cells.append(cell)\n if cell.is_flag or cell.visited or not field.cell_is_safe(cell):\n continue\n\n\n open_cells += get_open_cells(field, cell)\n\n return open_cells","def find_all_ORFs_both_strands(dna):\n \n # YOUR IMPLEMENTATION HERE","def find_all_ORFs_both_strands(dna):\n #inital conditions\n all_of_them = []\n\n #compute the all of the orfs in a DNA strand and the find their reverse complements\n #the return both of them in a list that includes all of the ORFS on both strands\n normal_ORFs = find_all_ORFs(dna)\n reverse_complement = get_reverse_complement(dna)\n reverse_ORFs = find_all_ORFs(reverse_complement)\n all_of_them = normal_ORFs + reverse_ORFs\n return all_of_them","def split_frames(flat):\n \n frames = [[]]\n for expr in flat:\n # A new frame starts with a .loc expression.\n if type(expr) == Raw and expr.expr[:4] == '.loc':\n frames.append([expr])\n else:\n frames[-1].append(expr)\n return frames","def gene_finder(dna):\n orfs = find_all_ORFs_both_strands(dna)\n print(orfs)\n threshold = longest_ORF_noncoding(dna, 1000)\n print('threshold is', threshold)\n print('number of orfs:', len(orfs))\n aa_sequences = []\n i = 0\n while i < len(orfs):\n print(len(orfs[i]))\n if len(orfs[i]) > threshold:\n print('if')\n aa_sequences += [coding_strand_to_AA(orfs[i])]\n i += 1\n print(aa_sequences)","def get_orfs(genome, min_num_aa):\n allowed = \"ATGC\"\n if not isinstance(genome, str) or len(genome) == 0 or not all(c in allowed for c in genome):\n raise TypeError\n start_codon = \"ATG\"\n stop_codon = ['TAA', 'TAG', 'TGA']\n ref_dict = {\"T\" : \"A\", \"A\" : \"T\", \"G\" : \"C\", \"C\" : \"G\"}\n amino_dict = {\n 'L' : ['CTC', 'CTT', 'CTA', 'CTG', 'TTA', 'TTG'],\n 'S' : ['TCA', 'TCT', 'TCC', 'TCG', 'AGC', 'AGT'],\n 'R' : ['CGA', 'CGC', 'CGT', 'CGG', 'AGA', 'AGG'],\n 'V' : ['GTA', 'GTG', 'GTC', 'GTT'],\n 'P' : ['CCC', 'CCA', 'CCG', 'CCT'],\n 'T' : ['ACC', 'ACG', 'ACT', 'ACA'],\n 'A' : ['GCA', 'GCC', 'GCG', 'GCT'],\n 'G' : ['GGA', 'GGC', 'GGT', 'GGG'],\n 'I' : ['ATA', 'ATC', 'ATT'],\n 'F' : ['TTT', 'TTC'],\n 'Y' : ['TAT', 'TAC'],\n 'H' : ['CAC', 'CAT'],\n 'Q' : ['CAG', 'CAA'],\n 'N' : ['AAC', 'AAT'],\n 'K' : ['AAA', 'AAG'],\n 'D' : ['GAC', 'GAT'],\n 'E' : ['GAA', 'GAG'],\n 'C' : ['TGC', 'TGT'],\n 'M' : ['ATG'],\n 'W' : ['TGG']\n\n }\n comp_genome = \"\"\n for stra in genome:\n comp_genome += ref_dict[stra]\n main_orfs = find_orfs(genome, start_codon, stop_codon, min_num_aa, amino_dict, False)\n comp_orfs = find_orfs(comp_genome[::-1], start_codon, stop_codon, min_num_aa, amino_dict, True)\n circular_orfs = find_cir_orfs(genome, main_orfs, start_codon, stop_codon, min_num_aa, amino_dict, False)\n \n circular_orfs_comp = find_cir_orfs(comp_genome[::-1], comp_orfs, start_codon, stop_codon, min_num_aa, amino_dict, True)\n \n for main_orf in main_orfs:\n for cir_orf in circular_orfs:\n if main_orf[0] <= cir_orf[1] and main_orf[1] <= cir_orf[1] or len(main_orf) == 5:\n main_orfs.remove(main_orf)\n for comp_orf in comp_orfs:\n for cir_orf in circular_orfs_comp:\n if comp_orf[1] == cir_orf[1] or len(comp_orf) == 5:\n comp_orfs.remove(comp_orf)\n\n final_orf = main_orfs + comp_orfs + circular_orfs + circular_orfs_comp\n #print(len(comp_orfs))\n \n \n \n return final_orf","def find_all_ORFs_both_strands(dna):\n \n #reverse first \n #then take compliment \n #then find ORF \n reverseStrand = [] \n original = [] \n new = []\n reverseStrand.append(get_reverse_complement(dna)) \n original.append(find_all_ORFs(dna))\n new.append(find_all_ORFs(reverseStrand))\n return original + new","def rest_of_ORF(dna):\n string = ''\n for i in xrange(0, len(dna), 3):\n codon = dna[i:i+3]\n if codon == 'TAG' or codon =='TAA' or codon =='TGA':\n return string\n else:\n string += codon\n return string","def longest_orf(seq):\n\n # Find possible start positions\n starts = seq_positions(seq, 'ATG')\n\n # Find possible end positions\n ends = seq_positions(seq, 'TGA') + seq_positions(seq, 'TAG') + seq_positions(seq, 'TAA')\n\n # Go through all starts and ends keeping track of longest orf\n orf = ''\n for start in starts:\n for end in ends:\n if start < end and (end - start) % 3 == 0:\n print(seq[start:end+3])\n if len(orf) < (end - start):\n orf = seq[start:end+3]\n break\n\n return orf","def longest_ORF_noncoding(dna, num_trials):\n org = list(dna)\n max_len = 0\n r = \"\"\n for i in range(num_trials):\n l = org\n shuffle(l)\n orf = longest_ORF(collapse(l))\n if len(orf) > max_len:\n r = orf\n max_len = len(orf)\n return r","def find_noncoding_genes(geneDict, df):\n\n\t### tRNA's not part of the annotation, separate GTF file for these... \n\tnoncoding_types = ['Mt_rRNA', \n\t\t\t\t\t 'Mt_tRNA',\n\t\t\t\t\t 'rRNA',\n\t\t\t\t\t 'miRNA',\n\t\t\t\t\t 'scRNA',\n\t\t\t\t\t 'scaRNA',\n\t\t\t\t\t 'snoRNA',\n\t\t\t\t\t 'snRNA',\n\t\t\t\t\t 'sRNA',\n\t\t\t\t\t 'vaultRNA'\n\t\t\t\t\t ]\n\n\tgeneDictNonCoding = OrderedDict() ### store noncoding transcripts only\n\n\tfor gene in geneDict:\n\t\ttr = df.loc[geneDict[gene][0], 'transcript_id']\n\n\t\ttrdict = parse_entry(tr)\n\n\t\tif trdict['gene_type'][0] in noncoding_types:\n\t\t\tgeneDictNonCoding[gene] = geneDict[gene]\n\n\treturn geneDictNonCoding","def frame_strand(strand):\n logging.info(\"Framing strand: \" + strand)\n framed_strand = []\n rolling_frame = ['','','']\n frame_begin = -1\n for i in range(0, len(strand)):\n rolling_frame[0] = rolling_frame[1]\n rolling_frame[1] = rolling_frame[2]\n rolling_frame[2] = strand[i]\n if rolling_frame[0]+rolling_frame[1]+rolling_frame[2] == start_codon:\n # We have the frame at this point. Prune the beginning of the string:\n # We are at a pos+2 (c ccc atg ccc ccc c) so cut back 2 and then break\n # ^\n frame_begin = i - 2\n logging.debug(\"Found start codon, strand is now framed at \" + str(frame_begin) + \".\")\n break\n if frame_begin == -1:\n # In this case, there is no valid frame in the strand. Return an empty list.\n logging.info(\"No valid frame in strand.\")\n return [], 0\n pruned_strand = strand[frame_begin:]\n framed_strand = [pruned_strand[i:i+3] for i in range(0, len(pruned_strand), 3)] # Make triples\n logging.debug(\"Framed strand is: \" + str(framed_strand))\n if len(framed_strand[-1]) < 3:\n logging.info(\"Newly framed sequence terminates with non-codon: \" + framed_strand[-1])\n return framed_strand, frame_begin","def parse_frames(self):\r\n done = False\r\n self._ip = 13 + self.ct_len\r\n while not done:\r\n code = self.next_byte()\r\n if not code:\r\n raise ValueError(\"Unexcepted end of file\")\r\n if code == b\"\\x2C\":\r\n self.parse_frame()\r\n elif code == b\"\\x21\":\r\n code = self.next_byte()\r\n if code == b\"\\xF9\":\r\n self.g_ext.append(self.parse_gce())\r\n elif code == b\"\\xFF\":\r\n self.next_byte()\r\n app = self.next_bytes(11)\r\n if app == b\"NETSCAPE2.0\":\r\n self.parse_ne()\r\n else:\r\n self.skip()\r\n elif code == b\"\\xFE\":\r\n self.comments.append(self.parse_ce())\r\n else:\r\n self.next_bytes(13)\r\n self.skip()\r\n elif code == b\"\\x3B\":\r\n done = True","def longest_ORF_noncoding(dna, num_trials):\n count = 0\n orfs = []\n while count < num_trials:\n current_strand = shuffle_string(dna)\n longest_in_shuffle = longest_ORF(current_strand)\n orfs.append(longest_in_shuffle)\n count = count + 1\n longest = max(orfs, key=len)\n return len(longest)","def rest_of_ORF(dna): \n\n for i in range(3,len(dna)-2,3):\n \tstop_codon=dna[i:i+3]\n \tstart_codon=dna[:i]\n \tif stop_codon=='TAG' or stop_codon=='TAA' or stop_codon=='TGA':\n \t\treturn start_codon\n \t\tbreak\n \tif (i+3) >= len(dna)-2:\n \treturn dna","def prune_decoded_seqs(seqs):\n out = []\n for s in seqs:\n if constant.EOS in s:\n idx = s.index(constant.EOS_TOKEN)\n out += [s[:idx]]\n else:\n out += [s]\n return out","def find_all_ORFs_both_strands(dna):\n return find_all_ORFs(dna)+find_all_ORFs(get_reverse_complement(dna))\n \n \n # YOUR IMPLEMENTATION HERE","def close_frames(depth: int) -> None:\n d = current_depth - depth\n for i in range(d):\n j = depth + d - (i + 1) # Current depth\n line = f'· {\"│ \" * j}└{\"┄\" * 3}' # * depth_widths[j]\n print(c.BRIGHT_WHITE + line.ljust(0, '━') + c.ENDC) # 80 also work","def longest_ORF_noncoding(dna, num_trials):\n longest_random_ORF = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# initialize empty list\n for i in range(num_trials):\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# repeats for num_trials\n \trandomized_dna = shuffle_string(dna)\t\t\t\t\t\t\t\t\t\t\t\t# finds strings of random dna\n \tlongest_random_ORF.append(longest_ORF(randomized_dna))\t\t\t\t\t\t\t\t# adds random dna to list\n\treturn max(longest_random_ORF, key=len)\t\t\t\t\t\t\t\t\t\t\t\t\t# returns longest dna string","def find_first_orf(sequence,\n start_codons = ['AUG'],\n stop_codons = ['UAA', 'UAG', 'UGA']):\n \n # Make sure the sequence is valid\n vet_nucleotide_sequence(sequence)\n\n # Make sure the codons are valid\n for codon in start_codons:\n vet_codon(codon)\n for codon in stop_codons:\n vet_codon(codon)\n\n # Get copies of everything in uppercase\n seq = sequence.upper()\n starts = [c.upper() for c in start_codons]\n stops = [c.upper() for c in stop_codons]\n # Make sure seq is RNA\n seq = seq.replace('T', 'U')\n\n\n ##########################################################################\n # `orf_pattern_str` is a regular expression that will match an\n # open reading frame within a string of RNA bases. \n # Read the docstring above for additional clues.\n #I create variables as \"strings\" to take in start_codons & stop_codons \"lists\" so it can use them in the \"regex\"\n \n strt = '|'.join(start_codons) #takes the start codon provided and saves it as a string named 'strt'\n stp = '|'.join(stop_codons) #takes the stop codon provided and takes it as a string named 'stp'\n\n #here the `regex`\n orf_pattern_str = r'(' + strt +r')([AUCG]{3})*('+ stp +r')'\n #breakdown\n #the regex is in 3 groups\n #first group is the start codon\n # literarily it is 'AUG', but it is dynamic, and (' + strt +r') fixes that\n #the second group is ([AUGC]{3})* which captures zero or more sets of codon after the start codon\n #the last group is ((UAA)|(UAG)|(UGA)) dynamically captured as ('+ stp +r')\n ##########################################################################\n\n # Create the regular expression object\n orf_pattern = re.compile(orf_pattern_str)\n # Search the sequence\n match_object = orf_pattern.search(seq)\n if match_object:\n return match_object.group()\n return ''","def longest_ORF_noncoding(dna, num_trials):\n\n # YOUR IMPLEMENTATION HERE","def find_all_ORFs_both_strands(dna):\n normal_dna = find_all_ORFs(dna)\n reverse_dna = find_all_ORFs(get_reverse_complement(dna))\n list_of_both_strands = normal_dna + reverse_dna\n return list_of_both_strands","def read_FIREXAQ_files(path, folder='merge', var=''):\n df_list=[]\n flag_list=[]\n files2use = sorted(glob.glob(f'{path}/{folder}/*{var}*.ict'))\n for infileN, infile in enumerate( files2use ):\n with open(infile) as thefile:\n try:\n header= np.array([next(thefile) for x in range(90) ])\n except:\n continue\n start = header[6].replace(',',' ').split()\n start_date = datetime_( int( start[0] ),\n int( start[1] ),\n int( start[2] ))\n # Find where the header ends and values begin - manually narrowed down\n for nskip in range(675,680):\n try:\n fh = np.loadtxt(infile, skiprows=nskip, delimiter=',')\n break\n except:\n continue\n thefile = open(infile,'r')\n c = thefile.readlines()\n column_names = c[nskip-1].replace(' ','').split(',')\n df = pd.DataFrame(fh, index=fh[:,0], columns=column_names)\n\n # Use a different approach for\n if (var=='thru'):\n df = find_FIREXAQ_times(df, start_date, UseTimeStart=True)\n else:\n df = find_FIREXAQ_times(df, start_date, UseTimeStart=False)\n # Include the RF from the file name #\n # NOTE: research flight (RF) ID not included in filename or files,\n # so using filenumber instead. This will not work if reading\n # merge file (var = 'thru').\n df['FileNumber'] = infileN\n\n df_list.append(df)\n df = pd.concat(df_list)\n return df","def find_all_ORFs_both_strands(dna):\n reverse_strand = get_reverse_complement(dna)\n return find_all_ORFs(dna) + find_all_ORFs(reverse_strand)","def find_all_ORFs_both_strands(dna):\n # TODO: implement this\n all_ORFs_both_strands = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# initialize empty list\n all_ORFs_both_strands = all_ORFs_both_strands + find_all_ORFs(dna)\t\t\t\t\t\t# adds all ORFs one strand to list\n reverse_complement_dna = get_reverse_complement(dna)\t\t\t\t\t\t\t\t\t# finds 2nd strand\n all_ORFs_both_strands = all_ORFs_both_strands + find_all_ORFs(reverse_complement_dna)\t# finds all ORFs second strand\n return all_ORFs_both_strands \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns all ORFs both strands","def rest_of_ORF(dna):\n # [???] 'assumed to begin with a start codon': doesn't need to check input?\n# if len(dna) < 3:\n# return \"\"\n# if dna[0:3] != start_codon:\n# return \"\"\n\n l = len(dna)\n for i in range(3, l, 3):\n if dna[i: i + 3] in stop_codons:\n return dna[0: i]\n return dna","def find_missing_pos_in_motif(motifs, motname_li):\n motifs_def=[]\n n=0\n for motname in motname_li:\n found=[]\n found_ranges=[]\n not_found=[]\n for e in motifs:\n if e[0]==motname:\n if not e[2]:\n not_found.append(e[1])\n else:\n found.append(e[1])\n found_ranges.append(e[3])\n \n num_nf=len(not_found)\n ranges_all=\",\".join(found_ranges)\n if num_nf ==0:\n motifs_def.append([motname,\" , \".join(found),(ranges_all)])\n elif num_nf ==3:\n motifs_def.append([motname,\"Motif not found\",\"None\"])\n else:\n motifs_def.append([motname,(\" , \".join(not_found)+\" not found\"),(ranges_all)])\n n+=1\n return motifs_def","def extractsequences(filename):\n\n yield (filename, 2, None)\n for m in re.finditer(r\"(?!0)[0-9]+\", filename):\n frameno = int(m.group())\n yield (makenonpaddedname(m), 0, frameno)\n for m in re.finditer(r\"[0-9]+\", filename):\n frameno = int(m.group())\n if m.end() - m.start() > 1:\n yield (makepaddedname(m), 1, frameno)","def filter_sequences(parent_directory, filename, label = 'Pfam:'):\n uniprot, repeated_seqs = load_uniprot('{}/{}'.format(parent_directory, filename))\n seq_fam = {}\n \n for u in uniprot:\n # Only select those sequences\n # - With the correct label\n # - That do not contain illegal characters\n # - Do not include sequences that are in multiple families\n index = find_index(u.dbxrefs, lambda x: x.startswith(label))\n if index != -1 and len(set(u._seq._data) - set(alphabet)) == 0 and u._seq._data not in repeated_seqs:\n seq_fam[u._seq._data] = u.dbxrefs[index][len(label):]\n \n filtered_fam = filtered_families(seq_fam)\n \n # Write processed output to a separate file\n with open('{}/processed.txt'.format(parent_directory), 'w') as f:\n f.write('\\n'.join(' '.join((fam, seq))\n for seq, fam in seq_fam.items()\n if fam in filtered_fam))","def rest_of_ORF(dna):\n for h in range(0, len(dna), 3):\n curr_triplet = dna[h : h + 3] \n #for n in range(0, len(amino_acids.codons),1):\n if curr_triplet in amino_acids.codons[10]:\n return dna[0 : h] \n return dna","def _find_all_top_level_non_gene_features(chrom: str, db: FeatureDB, feature_types: List[str]) -> Iterable[Feature]:\n for feature in db.region(seqid=chrom, featuretype=feature_types):\n try:\n _ = next(db.parents(feature.id))\n except StopIteration:\n yield feature","def _extractFrames_(self, wordRulesFlag):\n\t\t#pdb.set_trace()\n\t\tsimplifyTree(self.srcTree)\n\t\tsimplifyTree(self.tgtTree)\n\n\t\tsDic, tDic = {}, {}\n\t\tframeSet = set() \n\t\tfor sSubtr in self.srcTree.subtrees():\n\t\t\tif sSubtr.height() <= 2:\n\t\t\t\tcontinue\n\n\t\t\tsTreePos = sSubtr.treeposition()\n\t\t\tsOffset = treePosition2offset(sTreePos, self.srcTree)\n\t\t\tsDic[sTreePos] = scanBlock(sOffset, 'src', self.waMatrix)\n\n\t\t\tfor tSubtr in self.tgtTree.subtrees():\n\t\t\t\tif tSubtr.height() <= 2:\n\t\t\t\t\tcontinue\n\n\t\t\t\ttTreePos = tSubtr.treeposition()\n\t\t\t\tif tTreePos not in tDic:\n\t\t\t\t\ttOffset = treePosition2offset(tTreePos, self.tgtTree)\n\t\t\t\t\ttDic[tTreePos] = scanBlock(tOffset, 'tgt', self.waMatrix)\n\t\t\t\telse:\n\t\t\t\t\ttOffset = tDic[tTreePos]\n\n\t\t\t\t#print >> debug_log, self.srcTree[sTreePos]\n\t\t\t\t#print >> debug_log, self.tgtTree[tTreePos]\n\t\t\t\tif sDic[sTreePos] == tDic[tTreePos] and -1 not in sDic[sTreePos] and -1 not in tDic[tTreePos]:\n\t\t\t\t\t#print >> debug_log, 'paird up!!'\n\t\t\t\t\tframeSet.add(Frame([sTreePos], [tTreePos], self.srcTree, self.tgtTree))\n\t\t\t\t#print >> debug_log\n\n\t\t'''\n\t\tsrcSubtreeSpanDict = self._extractSubtreeSpan_(self.srcTree, wordRulesFlag)\n\t\ttgtSubtreeSpanDict = self._extractSubtreeSpan_(self.tgtTree, wordRulesFlag)\n\n\t\tframeSet = set() \n\t\tfor span in srcSubtreeSpanDict:\n\t\t\tif not self._consistentWithWA_(span, 'src'):\n\t\t\t\tcontinue\n\t\t\ttgtSpanList = self._scanSpan_(span, 'src')\n\t\t\tfor tgtSpan in tgtSpanList:\n\t\t\t\tif tgtSpan in tgtSubtreeSpanDict:\n\t\t\t\t\t#print >> debug_log, span, tgtSpan\n\t\t\t\t\tframeSet.add(Frame([srcSubtreeSpanDict[span]], [tgtSubtreeSpanDict[tgtSpan]], self.srcTree, self.tgtTree))\n\n\t\t#print >> debug_log, '\\n'\n\t\tfor span in tgtSubtreeSpanDict:\n\t\t\tif not self._consistentWithWA_(span, 'tgt'):\n\t\t\t\tcontinue\n\t\t\tsrcSpanList = self._scanSpan_(span, 'tgt')\n\t\t\tfor srcSpan in srcSpanList:\n\t\t\t\tif srcSpan in srcSubtreeSpanDict:\n\t\t\t\t\t#print >> debug_log, srcSpan, span\n\t\t\t\t\tframeSet.add(Frame([srcSubtreeSpanDict[srcSpan]], [tgtSubtreeSpanDict[span]], self.srcTree, self.tgtTree))\n\t\t'''\n\t\t#pdb.set_trace()\n\t\tframeList = self._mergeFrames_(frameSet)\n\t\t#print >> debug_log, len(frameList)\n\t\treturn frameList","def get_all_frames(self):\n #pdb.set_trace()\n frame_size=(512,512)\n frame_data = []\n variant_type = (pythoncom.VT_BYREF | pythoncom.VT_ARRAY | pythoncom.VT_UI2)\n for i in xrange(self.defaults['EXP_SEQUENTS']):\n frame_data.append(win32com.client.VARIANT(variant_type, numpy.empty(frame_size)))\n frame_data[i]=self.appdoc.GetFrame(i+1,frame_data[i])\n \n return numpy.array(frame_data, dtype=numpy.uint16)","def get_all_translations(rna_sequence, genetic_code):\n #Convert all rna_sequence to upper case:\n rna_sequence=rna_sequence.upper()\n #get the lengh of RNA seq.\n total_rna_bases=len(rna_sequence)\n #Create an empty list to store all possible AA seq.\n polypeptide_list = []\n #Looping through all the RNA bases, selecting all 3 possible reading frames to scan for tranlation.\n for i in range(total_rna_bases):\n i_end= i +3\n next_three=rna_sequence[i:i_end]\n #Condition to check if the condon is start codon\n if next_three=='AUG':\n #If condition satisfies, translate all rna seq from start to stop codon using first function,\n #translate_sequence\n polypeptide=translate_sequence(rna_sequence[i:], genetic_code)\n polypeptide_list.append(polypeptide)\n #Return all 3 possible reading frames as a list in polypeptide_list\n return polypeptide_list","def getinnerframes(tb, context=1):\r\n framelist = []\r\n while tb:\r\n framelist.append((tb.tb_frame,) + getframeinfo(tb, context))\r\n tb = tb.tb_next\r\n return framelist","def longest_ORF_noncoding(dna, num_trials):\n longest=[]\n for i in range(0,num_trials):\n \tshuffled_str=shuffle_string(dna)\n \tlongest.append(longest_ORF(shuffled_str))\n long_ORF=max(longest,key=len)\n return len(long_ORF)","def _read_frame_batch(frames: list, *, format):\n frame_count = len(frames)\n assert frame_count > 0\n\n f1_idx = 0\n f1 = None\n while f1_idx < frame_count and f1 is None:\n try:\n f1 = _read_frame(frames[f1_idx], format=format)\n except SkipFrameException:\n f1 = None\n f1_idx += 1\n ret = [[] for _ in range(len(f1))]\n\n for idx in range(len(f1)):\n # ret[idx] = np.empty(shape=(frame_count,)+np.shape(f1[idx]), dtype=f1[idx].dtype)\n ret[idx].append(f1[idx])\n\n for frameidx in range(1+f1_idx, frame_count):\n try:\n fn = _read_frame(frames[frameidx], format=format)\n except SkipFrameException:\n continue\n for compidx in range(len(fn)):\n # ret[compidx][frameidx] = fn[compidx]\n ret[compidx].append(fn[compidx])\n\n # return ret\n return [np.array(comp, dtype=comp[0].dtype) for comp in ret]","def _read_frames(self):\n cap = self._read_file()\n\n frame_list = []\n ret_list = []\n\n while True:\n ret, frame = cap.read()\n if ret:\n frame_list.append(np.array(frame))\n ret_list.append(ret)\n else:\n break\n if self.mode==\"np\":\n frame_list = np.array(frame_list)\n return frame_list","def gene_finder(dna):\n threshold = longest_ORF_noncoding(dna, 1500)\n orfs = find_all_ORFs_both_strands(dna)\n list1 = []\n for orf in orfs:\n if len(orf) > threshold:\n list1.append(coding_strand_to_AA(orf))\n return list1","def longest_ORF_noncoding(dna, num_trials):\n list_dna=list(dna)\n random.shuffle(list_dna)#just shuffles original list, doesn't return, not fruitful\n random_string_dna=collapse(list_dna)\n longest_dna=longest_ORF(random_string_dna)\n return longest_dna\n dna= 'ATGATGTGAATGATTGCTTGA'"],"string":"[\n \"def find_all_ORFs(dna):\\n index = 0\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# initialize index\\n all_ORFs = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitalize empty list\\n while index < 3:\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# switches throught the 3 frames\\n \\tall_ORFs = all_ORFs + find_all_ORFs_oneframe(dna[index:])\\t# adds all ORFs oneframe to the list\\n \\tindex += 1\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# indexes +1\\n return all_ORFs \\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns list of all ORFs in all 3 frames\",\n \"def find_all_ORFs(dna):\\n all_ORFs=[]\\n for i in range (0,3):\\n \\tframe=dna[i:] \\n all_ORFs+=find_all_ORFs_oneframe(frame)\\n return all_ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n condition = 1\\n dna2 = dna\\n list_of_ORFs = []\\n while condition == 1:\\n num_codons = int(len(dna2)/3)\\n num = 0\\n list_codons = []\\n start_index = -1\\n while num < num_codons:\\n num_start = int(num*3)\\n num_end = int(num*3 + 3)\\n list_codons.append(dna2[num_start:num_end])\\n num = num + 1\\n for element in list_codons:\\n if element == 'ATG':\\n start_index = list_codons.index(element)\\n break\\n if start_index != -1:\\n this_orf = rest_of_ORF(dna2[start_index*3:])\\n list_of_ORFs.append(this_orf)\\n dna2 = dna2[start_index*3+len(this_orf)+3:]\\n else:\\n condition = 2\\n\\n return list_of_ORFs\",\n \"def find_all_ORFs(dna):\\n first_frame = find_all_ORFs_oneframe(dna[0:])\\n second_frame = find_all_ORFs_oneframe(dna[1:])\\n third_frame = find_all_ORFs_oneframe(dna[2:])\\n list_of_frames = first_frame + second_frame + third_frame\\n return list_of_frames\",\n \"def find_all_ORFs(dna):\\n all_ORFs = []\\n for i in range(0, 3):\\n dna_new = dna[i:]\\n all_ORFs += find_all_ORFs_oneframe(dna_new)\\n return all_ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n \\n\\n ORFs=[]\\n i=0\\n while i<len(dna):\\n if dna[i:i+3]==\\\"ATG\\\":\\n j=i\\n dna2=rest_of_ORF(dna[j:])\\n \\n if dna2==None:\\n \\tbreak\\n ORFs.append(dna2)\\n i=i+len(dna2)\\n i=i+3\\n return ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n dna_split = split_into_codons(dna)\\n i = 0\\n all_ORFs_oneframe = []\\n length_of_orf = 0\\n while i < len(dna_split):\\n if dna_split[i] == \\\"ATG\\\":\\n orf = rest_of_ORF(dna[int(i)*3:])\\n all_ORFs_oneframe += [orf]\\n length_of_orf = math.ceil(len(orf)/3)\\n i += length_of_orf\\n else:\\n i += 1\\n return all_ORFs_oneframe\",\n \"def find_all_ORFs_oneframe(dna):\\n\\n ORFlist = []\\n i = 0\\n lend = len(dna)\\n while i < lend:\\n codon = dna[i:i+3]\\n if codon == 'ATG':\\n orf = rest_of_ORF(dna[i:])\\n ORFlist.append(orf)\\n i = i + len(orf)\\n else:\\n i = i+3\\n return ORFlist\",\n \"def find_all_ORFs_oneframe(dna):\\n x = 3\\n list_of_dna = []\\n while (x < len(dna)):\\n if dna[x-3:x] == 'ATG':\\n current_dna = rest_of_ORF(dna[x-3:])\\n list_of_dna.append(current_dna)\\n x += len(current_dna)\\n x += 3\\n return list_of_dna\",\n \"def find_all_ORFs(dna):\\n dnatwo = dna[1:]\\n dnathree = dna[2:]\\n all_ORFs = find_all_ORFs_oneframe(dna)\\n all_ORFs.extend(find_all_ORFs_oneframe(dnatwo))\\n all_ORFs.extend(find_all_ORFs_oneframe(dnathree))\\n if [] in all_ORFs:\\n all_ORFs.remove([])\\n return all_ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n i=0 \\n ORF_list = []\\n while i<len(dna):\\n if dna[i : i+3] == \\\"ATG\\\":\\n start_place = i \\n current_ORF = rest_of_ORF(dna[start_place:])\\n i += 3 + len(current_ORF)\\n ORF_list.append(current_ORF) \\n return ORF_list\",\n \"def find_all_ORFs_oneframe(dna):\\n i = 0\\n list_ORF = []\\n\\n def search_ORF(dna,i):\\n aa = dna[3*i:(3*i)+3]\\n if aa == 'ATG':\\n list_ORF.append(rest_of_ORF(dna,aa,i))\\n i = i + 1 + len(rest_of_ORF(dna,aa,i))/3\\n else:\\n i = i + 1\\n if len(aa) ==3:\\n search_ORF(dna,i)\\n \\n return list_ORF\\n\\n return search_ORF(dna,i)\\n # i = i + ((len(list_ORF[-1]))/3)\\n # search_ORF(dna,i)\",\n \"def find_all_ORFs_oneframe(dna):\\n\\tindex = 0\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# unitiate index at 0\\n\\tsegment = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitializes empty list\\n\\twhile index < len(dna):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# given that index is smaller than length of string\\n\\t\\tcodon = dna[index:index + 3]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# creates codons from nucleotides starting with first 3 letters\\n\\t\\tif codon == \\\"ATG\\\":\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if the codon is ATG\\n\\t\\t\\tsegment.append(rest_of_ORF(dna[index:]))\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# run rest_of_ORF starting at index\\n\\t\\t\\tindex = index + len(rest_of_ORF(dna[index:]))\\t\\t\\t\\t\\t\\t\\t\\t\\t# new index starting at old + length of ORF output string\\n\\t\\telse:\\n\\t\\t\\tindex += 3\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if ATG isn't found, move to next codon and check again\\n\\n\\treturn segment\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns list of ORFs\",\n \"def find_all_ORFs(dna):\\n\\n readingFrame0 = ''\\n readingFrame1 = ''\\n readingFrame2 = ''\\n output = ''\\n for k in range(0,3): \\n if k ==0: \\n readingFrame0 = find_all_ORFs_oneframe(dna[k:])\\n elif k ==1: \\n readingFrame1 = find_all_ORFs_oneframe(dna[k:])\\n elif k ==2:\\n readingFrame2 = find_all_ORFs_oneframe(dna[k:])\\n print 'Reading Frame 1: ' + str(readingFrame0) + ', Reading Frame 2: ' + str(readingFrame1) + ', Reading Frame 3: ' + str(readingFrame2)\\n output = readingFrame0 + readingFrame1 + readingFrame2\\n return output\",\n \"def find_all_ORFs(dna):\\n ORFs = find_all_ORFs_oneframe(dna) + find_all_ORFs_oneframe(dna[1:]) + find_all_ORFs_oneframe(dna[2:])\\n\\n return ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n res = []\\n l = len(dna)\\n next_pos = 0\\n while True:\\n arg = dna[next_pos:]\\n# orf = rest_of_ORF(arg)\\n# res.append(orf)\\n# if arg == orf: # if: no stop codon\\n# break\\n# next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\\n# if next_pos >= l: # if: meet the end of dna\\n# break\\n if arg[0:3] == start_codon:\\n orf = rest_of_ORF(arg)\\n res.append(orf)\\n if arg == orf: # if: no stop codon\\n break\\n next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next position\\n else: # if: not start codon, see next\\n next_pos += 3\\n if next_pos >= l: # if: meet or go beyond the end of dna\\n break\\n return res\",\n \"def find_all_ORFs_oneframe(dna):\",\n \"def find_all_ORFs(dna):\\n ans = find_all_ORFs_oneframe(dna)\\n ans.extend(find_all_ORFs_oneframe(dna[1:]))\\n ans.extend(find_all_ORFs_oneframe(dna[2:]))\\n return ans\",\n \"def find_all_ORFs(dna):\\n all_ORFs = []\\n i = 0\\n\\n for i in range (0,3): \\n all_ORFs.extend(find_all_ORFs_oneframe(dna))\\n dna = 'X' + dna\\n\\n return all_ORFs\",\n \"def find_all_ORFs_oneframe(dna):\\n #inital conditions\\n i = 0\\n start_codon = ('ATG')\\n end_index = len(dna)\\n return_variable = []\\n\\n #for each codon in the set of DNA, check if it is a start codon\\n #if it is a start codon, add the string until the stop codon to a list\\n #then continue running\\n while i < len(dna)-2:\\n codon = dna[i:i+3] \\n if codon in start_codon:\\n orf = rest_of_ORF(dna[i:])\\n return_variable.append(orf)\\n i += len(orf)\\n i += 3\\n\\n\\n #return a list of strings of DNA\\n return return_variable\",\n \"def find_all_ORFs(dna):\\n #inital conditions\\n i = 0\\n start_codon = ('ATG')\\n end_index = len(dna)\\n return_variable = []\\n\\n #for statement tells the code to run three times at three inital index values\\n #0,1,and 2 which allows for each reading frame to be read\\n for i in range (3):\\n while i < (len(dna)-2):\\n codon = dna[i:i+3] \\n if codon in start_codon: #check if the codon the code is looking at is a start codon\\n orf = rest_of_ORF(dna[i:]) #then determine that this is an orf, make it a string given the index of the start codon\\n return_variable.append(orf) #and append said string to a list of ORFs\\n i += len(orf) \\n i += 3\\n #return a list of strings of DNA from both strands\\n return return_variable\",\n \"def find_all_ORFs_oneframe(dna):\\n strand = []\\n startCodon = [\\\"ATG\\\"]\\n for i in range(0,len(dna),3):\\n triple = dna[i:i+3]\\n if triple in startCodon: \\n strand.append(rest_of_ORF(dna[i:]))\\n print strand\\n return strand\",\n \"def find_all_ORFs(dna):\\n #these functions offset to analyze each each open frame reference\\n zero_offset=find_all_ORFs_oneframe(dna[0:])\\n \\n one_offset=find_all_ORFs_oneframe(dna[1:])\\n \\n two_offset=find_all_ORFs_oneframe(dna[2:])\\n \\n return zero_offset+one_offset+two_offset\\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def rest_of_ORF(dna):\\n readingFrame = ''\\n endCodons = [\\\"TAG\\\", \\\"TAA\\\", \\\"TGA\\\"]\\n for i in range(0,len(dna),3):\\n triple = dna[i:i+3]\\n if triple in endCodons:\\n readingFrame = readingFrame\\n break\\n else: \\n readingFrame+=triple \\n return readingFrame\",\n \"def reading_frames(dna):\\n #the 6 types are as follows\\n # the actual string and the reverse complement\\n list = []\\n #this is the actual string\\n list.append(dna)\\n #this is the reverse complement of the string\\n # done reusing the fastcomplement() method that was already available.\\n #others are done likewise\\n list.append(fast_complement(dna[::-1]))\\n list.append(dna[1:len(dna)])\\n list.append(fast_complement(dna[1:len(dna)][::-1]))\\n list.append(dna[2:len(dna)])\\n list.append(fast_complement(dna[2:len(dna)][::-1]))\\n return list\",\n \"def find_all_ORFs_oneframe_unit_tests(dna, expected):\\n\\n print find_all_ORFs_oneframe(\\\"ATGCATGAATGTAGATAGATGTGCCC\\\")\\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + find_all_ORFs_oneframe(dna)\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n\\n input = [\\\"dna\\\"]\\n expected_output = [\\\"all non-nester ORFs\\\"]\\n actual = []\\n for k in input:\\n actual.append(find_all_ORFs_oneframe(k))\\n print input \\n print actual\\n print expected_output\",\n \"def getouterframes(frame, context=1):\\r\\n framelist = []\\r\\n while frame:\\r\\n framelist.append((frame,) + getframeinfo(frame, context))\\r\\n frame = frame.f_back\\r\\n return framelist\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n data_list = [\\n [\\\"ATGCATGAATGTAGATAGATGTGCCC\\\", [\\\"ATGCATGAATGTAGA\\\", \\\"ATGTGCCC\\\"]],\\n [\\\"ATGTAGATGTAG\\\", [\\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGATGATG\\\", [\\\"ATGATGATG\\\"]],\\n [\\\"ATGGGGGATTAGATGATG\\\", [\\\"ATGGGGGAT\\\", \\\"ATGATG\\\"]],\\n [\\\"ATGTGAATGTAA\\\", [\\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGTGAATGTAAATG\\\", [\\\"ATG\\\", \\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGCGTGGTGATTAGATGGATGGGGATTGA\\\", [\\\"ATGCGTGGTGAT\\\", \\\"ATGGATGGGGAT\\\"]],\\n [\\\"ATGAAATTTCCCGGGAAATTTCCCGGG\\\", [\\\"ATGAAATTTCCCGGGAAATTTCCCGGG\\\"]],\\n [\\\"ATGAAATTTTGAATGGGGCCC\\\", [\\\"ATGAAATTT\\\", \\\"ATGGGGCCC\\\"]],\\n [\\\"ATGAAATTTTGAATGGGGCCCTAG\\\", [\\\"ATGAAATTT\\\", \\\"ATGGGGCCC\\\"]],\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\",\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = find_all_ORFs_oneframe(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def ORFs(self):\\n ORFStart = None\\n openLeft = True\\n seenStart = False\\n\\n for index, residue in enumerate(self.sequence):\\n if residue == 'M':\\n # Start codon.\\n openLeft = False\\n seenStart = True\\n elif residue == '*':\\n # Stop codon. Yield an ORF, if it has non-zero length.\\n if ORFStart is not None and index - ORFStart > 0:\\n # The ORF has non-zero length.\\n yield AAReadORF(self, ORFStart, index, openLeft, False)\\n ORFStart = None\\n # After a stop codon, we can no longer be open on the left\\n # and we have no longer seen a start codon.\\n openLeft = seenStart = False\\n else:\\n if (seenStart or openLeft) and ORFStart is None:\\n ORFStart = index\\n\\n # End of sequence. Yield the final ORF if there is one and it has\\n # non-zero length.\\n length = len(self.sequence)\\n if ((seenStart or openLeft) and ORFStart is not None and\\n length - ORFStart > 0):\\n yield AAReadORF(self, ORFStart, length, openLeft, True)\",\n \"def find_longest_orfs(seq,n_orfs):\\n\\n # Make sure there is a start codon in the sequence:\\n if not 'ATG' in seq:\\n raise RuntimeError(\\\"Your DNA sequence doesn't have a start codon.\\\")\\n\\n # Initialize orfs list:\\n orfs =[]\\n\\n # Loop over sequence and find ORFs:\\n for i, base in enumerate(seq):\\n triplet = seq[i:i+3]\\n if triplet == 'ATG':\\n orf_seq = ''\\n aa_seq = ''\\n j = i\\n while j+2 < len(seq):\\n codon = seq[j:j+3]\\n orf_seq += codon\\n if bioinfo_dicts.codons[codon] == '*': # if stop codon\\n orf_len = len(orf_seq)\\n orfs.append((orf_len,orf_seq,aa_seq)) # j is orf len in nts\\n break # this only breaks out of while loop, right?\\n else:\\n aa_seq += bioinfo_dicts.codons[codon]\\n j+=3\\n\\n # Sort orf list by length\\n orfs.sort()\\n\\n # Select n longest orfs to return:\\n number = -(n_orfs+1)\\n longest_orfs = orfs[:number:-1]\\n\\n longest_orfs = tuple(longest_orfs)\\n return longest_orfs\",\n \"def find_all_ORFs_oneframe(dna): \\n i=0\\n multiple_list=[]\\n while i < len(dna):\\n part = dna[i:i+3]\\n if part == 'ATG': #if the first indecied are ATG then it runs the code that creates the string of DNA\\n ORF=rest_of_ORF(dna[i:]) \\n multiple_list.append(ORF)\\n i+=len(ORF)\\n else:\\n i+=3\\n # print multiple_list\\n return multiple_list\\n \\n #runs fuinction to mmake list of function\\n #need to save to list\\n #need to continue to next ATG start \\n #need to add that to list\\n #need to output new list as commas between lists\",\n \"def find_all_ORFs_both_strands(dna):\\n orfs = []\\n orfs = find_all_ORFs(dna) + find_all_ORFs(get_reverse_complement(dna))\\n return orfs\",\n \"def get_open_issues(self, owners: List[str]) -> List[EventRecord]:\\n with self.session.begin() as session:\\n open_issues = (\\n session.query(EventRecord)\\n .filter(EventRecord.owner.in_(owners))\\n .filter(EventRecord.received_at >= datetime.utcnow() - timedelta(days=1))\\n .all()\\n )\\n\\n open_issues = remove_duplicate_events(open_issues)\\n\\n open_issues_fps = [issue.fingerprint for issue in open_issues]\\n\\n ignored_issues_fps_tuples = (\\n session.query(IgnoreFingerprintRecord.fingerprint)\\n .filter(IgnoreFingerprintRecord.fingerprint.in_(open_issues_fps))\\n .filter(\\n (IgnoreFingerprintRecord.expires_at > datetime.utcnow())\\n | (IgnoreFingerprintRecord.expires_at.is_(None))\\n )\\n .all()\\n )\\n\\n ignored_issues_fps = [t[0] for t in ignored_issues_fps_tuples]\\n\\n return [issue for issue in open_issues if issue.fingerprint not in ignored_issues_fps]\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n input_a='ATGATTATTTGATGAATGGATTGA'\\n expected_output='[ATGATTATT,ATGGAT]'\\n actual_output=find_all_ORFs_oneframe(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\\n \\n input_a='ATGGGATTGTTT'\\n expected_output='[ATGGATTGTTT]'\\n actual_output=find_all_ORFs_oneframe(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\",\n \"def rest_of_ORF(dna):\\n\\n #inital conditions\\n i = 3\\n end_index = len(dna)\\n stop_codon = ('TAG','TAA','TGA')\\n\\n #for the length of the string of DNA, run through each codon and break and return the indec of the string if the codon is a stop codon\\n while i < len(dna)-2:\\n codon = dna[i:i+3] #takes only every third index which is the length of a codon\\n if codon in stop_codon:\\n end_index = i \\n break\\n i += 3\\n #returns a list from the start codon to the index where the stop codon begins\\n return dna[0:end_index]\",\n \"def test_fasta_get_codon_info_from_seq_all_frames(self):\\r\\n\\r\\n codon_info_f1, codon_info_f2, codon_info_f3 = mfau.get_codons_from_sequence_three_framed(\\\"AGGTGACACCGCAAGCCTTATATTAGC\\\")\\r\\n\\r\\n if debug:\\r\\n print \\\"condons in frame1:\\\"\\r\\n for codon in codon_info_f1.codons:\\r\\n print \\\"\\\\t\\\" + codon\\r\\n\\r\\n self.assertGreaterEqual(len(codon_info_f1.codons), 0)\\r\\n\\r\\n if debug:\\r\\n print \\\"condons in frame2:\\\"\\r\\n for codon in codon_info_f2.codons:\\r\\n print \\\"\\\\t\\\" + codon\\r\\n\\r\\n self.assertGreaterEqual(len(codon_info_f2.codons), 0)\\r\\n\\r\\n if debug:\\r\\n print \\\"condons in frame3:\\\"\\r\\n for codon in codon_info_f3.codons:\\r\\n print \\\"\\\\t\\\" + codon\\r\\n\\r\\n self.assertGreaterEqual(len(codon_info_f3.codons), 0)\",\n \"def rest_of_ORF(dna):\\n end_dna = len(dna)\\n for group in range(0, end_dna, 3):\\n strand = dna[group:group+3]\\n if strand in ['TGA', 'TAA', 'TAG']:\\n return dna[0:group]\\n return dna\",\n \"def rest_of_ORF(dna,aa,i):\\n\\n rest_of_ORF = []\\n \\n while len(aa) ==3 and aa not in stop_codons: #run this loop until locating a stop\\n # if len(aa) == 3:\\n rest_of_ORF.append (aa) #add each successive codon to list\\n i = i+1\\n aa = dna[3*i:(3*i)+3]\\n # else:\\n # rest_of_ORF.append (aa)\\n # return ''.join(rest_of_ORF)\\n\\n return ''.join(rest_of_ORF)\",\n \"def longest_ORF(dna):\\n\\n reverseComp = get_reverse_complement(dna)\\n openFramesfromReverse = find_all_ORFs(reverseComp)\\n openFramesfromNormal = find_all_ORFs(dna)\\n all_ORFs = openFramesfromNormal + openFramesfromReverse\\n longest = max(all_ORFs, key=len)\\n return longest\",\n \"def find_all_ORFs(dna):\\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs_both_strands(dna):\\n reverse_dna = get_reverse_complement(dna)\\n orfs = find_all_ORFs(dna)\\n backward_orfs = find_all_ORFs(reverse_dna)\\n orfs.extend(backward_orfs)\\n return orfs\",\n \"def find_surrounding_frames(frame, frames_with):\\n # If frame is missing from the beginning, return initial frame twice.\\n if (frame < frames_with[0]):\\n return frames_with[0], frames_with[0], frames_with[0] - frame\\n # If frame is missing from the end, return last frame twice.\\n elif (frame > frames_with[-1]):\\n return frames_with[-1], frames_with[-1], frame - frames_with[-1]\\n # If frame is missing in the middle, return surrounding frames.\\n else:\\n for i in range(1, len(frames_with)):\\n frame_before = frames_with[i-1]\\n frame_after = frames_with[i]\\n if (frame > frame_before and frame < frame_after):\\n return frame_before, frame_after, frame_after - frame_before - 1\",\n \"def find_all_ORFs_both_strands(dna):\\n return find_all_ORFs(dna) + (find_all_ORFs(get_reverse_complement(dna)))\",\n \"def find_all_ORFs_both_strands(dna):\\n both_strands_ORFs = []\\n\\n both_strands_ORFs.extend(find_all_ORFs(dna))\\n both_strands_ORFs.extend(find_all_ORFs(get_reverse_complement(dna)))\\n \\n return both_strands_ORFs\",\n \"def find_all_ORFs_unit_tests():\\n \\n input = [\\\"dna\\\"]\\n expected_output = [\\\"all non-nested ORFs\\\"]\\n actual = []\\n for k in input:\\n actual.append(find_all_ORFs(k))\\n print input \\n print actual\\n print expected_output\",\n \"def rest_of_ORF(dna):\\n STOP_CODONS=['TAG','TGA','TAA' ]#constants are uppercase\\n for i in range(0,len(dna),3):\\n codon=dna[i:i+3]\\n if codon in STOP_CODONS:\\n return dna[0:i]\\n return dna\",\n \"def find_all_ORFs_both_strands(dna):\\n return find_all_ORFs(dna) + find_all_ORFs(get_reverse_complement(dna))\",\n \"def rest_of_ORF(dna):\\n\\t# TODO: implement this\\n\\tindex = 0\\n\\twhile index < len(dna):\\n\\t\\tcodon = dna[index:index + 3]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# groups 3 nucleotides to make codon, index by 3\\n\\t\\tif codon in [\\\"TAA\\\", \\\"TAG\\\", \\\"TGA\\\"]:\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# checks if stop codon is in string\\n\\t\\t\\treturn dna[:index]\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# if True, returns string up to stop codon\\n\\t\\tindex += 3\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# indexes by 3\\n\\treturn dna\",\n \"def find_all_ORFs_unit_tests(dna, expected):\\n \\n print find_all_ORFs(\\\"ATGCATGAATGTAG\\\")\\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + find_all_ORFs(dna)\",\n \"def rest_of_ORF(dna):\\n num_codons = int(len(dna)/3)\\n num = 0\\n list_codons = []\\n cut_dna = ''\\n stop_index = -1\\n while num < num_codons:\\n num_start = int(num*3)\\n num_end = int(num*3 + 3)\\n list_codons.append(dna[num_start:num_end])\\n num = num + 1\\n for element in list_codons:\\n if element == 'TAA' or element == 'TAG' or element == 'TGA':\\n stop_index = list_codons.index(element)\\n break\\n\\n if stop_index != -1:\\n this_ORF = list_codons[0:stop_index]\\n for element in this_ORF:\\n cut_dna = cut_dna + element\\n return cut_dna\\n else:\\n return dna\",\n \"def count_frames():\\n frames = sentence.sem.frames.find_all('frame', {'name' : NEGATION_FRAME_NAME})\\n frame_count = []\\n for f_r in frames:\\n frame_count.append(f_r)\\n return len(frame_count)\",\n \"def test_multi_line_missing_frames():\\n\\n for protocol in LEGACY_PROTOCOLS:\\n p = protocol([])\\n\\n\\n test_case = [\\n \\\"48 6B 10 49 02 01 00 01 02 03 FF\\\",\\n \\\"48 6B 10 49 02 02 04 05 06 07 FF\\\",\\n \\\"48 6B 10 49 02 03 08 09 0A 0B FF\\\",\\n ]\\n\\n for n in range(len(test_case) - 1):\\n sub_test = list(test_case)\\n del sub_test[n]\\n\\n r = p(sub_test)\\n assert len(r) == 0\",\n \"def gene_finder(dna):\\n threshold = longest_ORF_noncoding(dna, 1500)\\n l = []\\n for i in find_all_ORFs_both_strands(dna):\\n \\tif len(i)>=threshold:\\n \\t\\tl.append(coding_strand_to_AA(i))\\n print l\\n return l\",\n \"def rest_of_ORF(dna):\\n \\n if dna[:3]== \\\"TAG\\\" or dna[:3]==\\\"TAA\\\" or dna[:3]==\\\"TGA\\\" or len(dna)<3:\\n return \\\"\\\"\\n if len(dna)<=3:\\n return dna\\n return dna[:3]+rest_of_ORF(dna[3:])\",\n \"def rest_of_ORF(dna):\\n index = -1\\n dna_split = split_into_codons(dna)\\n\\n for i, j in enumerate(dna_split):\\n if j == \\\"TAG\\\" or j == \\\"TGA\\\" or j == \\\"TAA\\\":\\n index = i\\n if index == -1:\\n return ''.join(dna_split) # if there is no stop codon\\n return ''.join(dna_split[:index])\",\n \"def longest_ORF(dna):\\n \\n all_ORFs = find_all_ORFs_both_strands(dna)\\n\\n if len(all_ORFs) > 0:\\n return max(all_ORFs, key = len)\\n else:\\n return []\",\n \"def findGaps(sequence):\\n patt = re.compile(r\\\"[Nn]+\\\")\\n for match in patt.finditer(sequence):\\n yield (match.start(), match.end())\",\n \"def find_all_ORFs_unit_tests():\\n data_list = [\\n [\\\"ATGCATGAATGTAG\\\", [\\\"ATGCATGAATGTAG\\\", \\\"ATGAATGTAG\\\", \\\"ATG\\\"]],\\n [\\\"ATG\\\", [\\\"ATG\\\"]],\\n [\\\"AATG\\\", [\\\"ATG\\\"]],\\n [\\\"AAATG\\\", [\\\"ATG\\\"]],\\n [\\\"ATGATG\\\", [\\\"ATGATG\\\"]],\\n [\\\"ATATGGATTGA\\\", [\\\"ATGGAT\\\"]],\\n [\\\"ATGAGATTAG\\\", [\\\"ATGAGATTAG\\\"]],\\n [\\\"ATATGGATTAGTAGTAATGAAAGTATAG\\\", [\\\"ATGAAAGTA\\\", \\\"ATGGAT\\\", ]],\\n# ATA TGG ATT AGT AGT AAT GAA AGT ATA G\\n# TAT GGA TTA GTA GTA ATG AAA GTA TAG\\n# ATG GAT TAG TAG TAA TGA AAG TAT AG\\n [\\\"ATGTCACGCAATGTAGGATGGATGGATTAGAC\\\", [\\\"ATGTCACGCAATGTAGGATGGATGGAT\\\", \\\"ATG\\\", \\\"ATGGATGGATTAGAC\\\"]],\\n# ATG TCA CGC AAT GTA GGA TGG ATG GAT TAG AC --> ATG TCA CGC AAT GTA GGA TGG ATG GAT\\n# TGT CAC GCA ATG TAG GAT GGA TGG ATT AGA C\\n# GTC ACG CAA TGT AGG ATG GAT GGA TTA GAC\\n [\\\"ATGATGTAG\\\", [\\\"ATGATG\\\"]],\\n [\\\"TCGATGC\\\", [\\\"ATGC\\\"]],\\n [\\\"AAA\\\", []],\\n# TCG ATG C\\n# CGA TGC\\n# GAT GC\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\",\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = find_all_ORFs(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def prune_decoded_seqs(seqs):\\r\\n out = []\\r\\n for s in seqs:\\r\\n if EOS in s:\\r\\n idx = s.index(EOS)\\r\\n out += [s[:idx]]\\r\\n else:\\r\\n out += [s]\\r\\n return out\",\n \"def get_open_cells(field: MineField, cell: Cell) -> List[Cell]:\\n # TODO re-implement iteratively to safe stack space (especially for large boards)\\n if cell.is_flag or cell.is_mine or not field.cell_is_safe(cell):\\n return [cell]\\n \\n if cell.visited:\\n return\\n\\n open_cells: list = list()\\n cell.visited = True\\n open_cells.append(cell)\\n\\n for cell in field.surrounding_cells(cell):\\n open_cells.append(cell)\\n if cell.is_flag or cell.visited or not field.cell_is_safe(cell):\\n continue\\n\\n\\n open_cells += get_open_cells(field, cell)\\n\\n return open_cells\",\n \"def find_all_ORFs_both_strands(dna):\\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs_both_strands(dna):\\n #inital conditions\\n all_of_them = []\\n\\n #compute the all of the orfs in a DNA strand and the find their reverse complements\\n #the return both of them in a list that includes all of the ORFS on both strands\\n normal_ORFs = find_all_ORFs(dna)\\n reverse_complement = get_reverse_complement(dna)\\n reverse_ORFs = find_all_ORFs(reverse_complement)\\n all_of_them = normal_ORFs + reverse_ORFs\\n return all_of_them\",\n \"def split_frames(flat):\\n \\n frames = [[]]\\n for expr in flat:\\n # A new frame starts with a .loc expression.\\n if type(expr) == Raw and expr.expr[:4] == '.loc':\\n frames.append([expr])\\n else:\\n frames[-1].append(expr)\\n return frames\",\n \"def gene_finder(dna):\\n orfs = find_all_ORFs_both_strands(dna)\\n print(orfs)\\n threshold = longest_ORF_noncoding(dna, 1000)\\n print('threshold is', threshold)\\n print('number of orfs:', len(orfs))\\n aa_sequences = []\\n i = 0\\n while i < len(orfs):\\n print(len(orfs[i]))\\n if len(orfs[i]) > threshold:\\n print('if')\\n aa_sequences += [coding_strand_to_AA(orfs[i])]\\n i += 1\\n print(aa_sequences)\",\n \"def get_orfs(genome, min_num_aa):\\n allowed = \\\"ATGC\\\"\\n if not isinstance(genome, str) or len(genome) == 0 or not all(c in allowed for c in genome):\\n raise TypeError\\n start_codon = \\\"ATG\\\"\\n stop_codon = ['TAA', 'TAG', 'TGA']\\n ref_dict = {\\\"T\\\" : \\\"A\\\", \\\"A\\\" : \\\"T\\\", \\\"G\\\" : \\\"C\\\", \\\"C\\\" : \\\"G\\\"}\\n amino_dict = {\\n 'L' : ['CTC', 'CTT', 'CTA', 'CTG', 'TTA', 'TTG'],\\n 'S' : ['TCA', 'TCT', 'TCC', 'TCG', 'AGC', 'AGT'],\\n 'R' : ['CGA', 'CGC', 'CGT', 'CGG', 'AGA', 'AGG'],\\n 'V' : ['GTA', 'GTG', 'GTC', 'GTT'],\\n 'P' : ['CCC', 'CCA', 'CCG', 'CCT'],\\n 'T' : ['ACC', 'ACG', 'ACT', 'ACA'],\\n 'A' : ['GCA', 'GCC', 'GCG', 'GCT'],\\n 'G' : ['GGA', 'GGC', 'GGT', 'GGG'],\\n 'I' : ['ATA', 'ATC', 'ATT'],\\n 'F' : ['TTT', 'TTC'],\\n 'Y' : ['TAT', 'TAC'],\\n 'H' : ['CAC', 'CAT'],\\n 'Q' : ['CAG', 'CAA'],\\n 'N' : ['AAC', 'AAT'],\\n 'K' : ['AAA', 'AAG'],\\n 'D' : ['GAC', 'GAT'],\\n 'E' : ['GAA', 'GAG'],\\n 'C' : ['TGC', 'TGT'],\\n 'M' : ['ATG'],\\n 'W' : ['TGG']\\n\\n }\\n comp_genome = \\\"\\\"\\n for stra in genome:\\n comp_genome += ref_dict[stra]\\n main_orfs = find_orfs(genome, start_codon, stop_codon, min_num_aa, amino_dict, False)\\n comp_orfs = find_orfs(comp_genome[::-1], start_codon, stop_codon, min_num_aa, amino_dict, True)\\n circular_orfs = find_cir_orfs(genome, main_orfs, start_codon, stop_codon, min_num_aa, amino_dict, False)\\n \\n circular_orfs_comp = find_cir_orfs(comp_genome[::-1], comp_orfs, start_codon, stop_codon, min_num_aa, amino_dict, True)\\n \\n for main_orf in main_orfs:\\n for cir_orf in circular_orfs:\\n if main_orf[0] <= cir_orf[1] and main_orf[1] <= cir_orf[1] or len(main_orf) == 5:\\n main_orfs.remove(main_orf)\\n for comp_orf in comp_orfs:\\n for cir_orf in circular_orfs_comp:\\n if comp_orf[1] == cir_orf[1] or len(comp_orf) == 5:\\n comp_orfs.remove(comp_orf)\\n\\n final_orf = main_orfs + comp_orfs + circular_orfs + circular_orfs_comp\\n #print(len(comp_orfs))\\n \\n \\n \\n return final_orf\",\n \"def find_all_ORFs_both_strands(dna):\\n \\n #reverse first \\n #then take compliment \\n #then find ORF \\n reverseStrand = [] \\n original = [] \\n new = []\\n reverseStrand.append(get_reverse_complement(dna)) \\n original.append(find_all_ORFs(dna))\\n new.append(find_all_ORFs(reverseStrand))\\n return original + new\",\n \"def rest_of_ORF(dna):\\n string = ''\\n for i in xrange(0, len(dna), 3):\\n codon = dna[i:i+3]\\n if codon == 'TAG' or codon =='TAA' or codon =='TGA':\\n return string\\n else:\\n string += codon\\n return string\",\n \"def longest_orf(seq):\\n\\n # Find possible start positions\\n starts = seq_positions(seq, 'ATG')\\n\\n # Find possible end positions\\n ends = seq_positions(seq, 'TGA') + seq_positions(seq, 'TAG') + seq_positions(seq, 'TAA')\\n\\n # Go through all starts and ends keeping track of longest orf\\n orf = ''\\n for start in starts:\\n for end in ends:\\n if start < end and (end - start) % 3 == 0:\\n print(seq[start:end+3])\\n if len(orf) < (end - start):\\n orf = seq[start:end+3]\\n break\\n\\n return orf\",\n \"def longest_ORF_noncoding(dna, num_trials):\\n org = list(dna)\\n max_len = 0\\n r = \\\"\\\"\\n for i in range(num_trials):\\n l = org\\n shuffle(l)\\n orf = longest_ORF(collapse(l))\\n if len(orf) > max_len:\\n r = orf\\n max_len = len(orf)\\n return r\",\n \"def find_noncoding_genes(geneDict, df):\\n\\n\\t### tRNA's not part of the annotation, separate GTF file for these... \\n\\tnoncoding_types = ['Mt_rRNA', \\n\\t\\t\\t\\t\\t 'Mt_tRNA',\\n\\t\\t\\t\\t\\t 'rRNA',\\n\\t\\t\\t\\t\\t 'miRNA',\\n\\t\\t\\t\\t\\t 'scRNA',\\n\\t\\t\\t\\t\\t 'scaRNA',\\n\\t\\t\\t\\t\\t 'snoRNA',\\n\\t\\t\\t\\t\\t 'snRNA',\\n\\t\\t\\t\\t\\t 'sRNA',\\n\\t\\t\\t\\t\\t 'vaultRNA'\\n\\t\\t\\t\\t\\t ]\\n\\n\\tgeneDictNonCoding = OrderedDict() ### store noncoding transcripts only\\n\\n\\tfor gene in geneDict:\\n\\t\\ttr = df.loc[geneDict[gene][0], 'transcript_id']\\n\\n\\t\\ttrdict = parse_entry(tr)\\n\\n\\t\\tif trdict['gene_type'][0] in noncoding_types:\\n\\t\\t\\tgeneDictNonCoding[gene] = geneDict[gene]\\n\\n\\treturn geneDictNonCoding\",\n \"def frame_strand(strand):\\n logging.info(\\\"Framing strand: \\\" + strand)\\n framed_strand = []\\n rolling_frame = ['','','']\\n frame_begin = -1\\n for i in range(0, len(strand)):\\n rolling_frame[0] = rolling_frame[1]\\n rolling_frame[1] = rolling_frame[2]\\n rolling_frame[2] = strand[i]\\n if rolling_frame[0]+rolling_frame[1]+rolling_frame[2] == start_codon:\\n # We have the frame at this point. Prune the beginning of the string:\\n # We are at a pos+2 (c ccc atg ccc ccc c) so cut back 2 and then break\\n # ^\\n frame_begin = i - 2\\n logging.debug(\\\"Found start codon, strand is now framed at \\\" + str(frame_begin) + \\\".\\\")\\n break\\n if frame_begin == -1:\\n # In this case, there is no valid frame in the strand. Return an empty list.\\n logging.info(\\\"No valid frame in strand.\\\")\\n return [], 0\\n pruned_strand = strand[frame_begin:]\\n framed_strand = [pruned_strand[i:i+3] for i in range(0, len(pruned_strand), 3)] # Make triples\\n logging.debug(\\\"Framed strand is: \\\" + str(framed_strand))\\n if len(framed_strand[-1]) < 3:\\n logging.info(\\\"Newly framed sequence terminates with non-codon: \\\" + framed_strand[-1])\\n return framed_strand, frame_begin\",\n \"def parse_frames(self):\\r\\n done = False\\r\\n self._ip = 13 + self.ct_len\\r\\n while not done:\\r\\n code = self.next_byte()\\r\\n if not code:\\r\\n raise ValueError(\\\"Unexcepted end of file\\\")\\r\\n if code == b\\\"\\\\x2C\\\":\\r\\n self.parse_frame()\\r\\n elif code == b\\\"\\\\x21\\\":\\r\\n code = self.next_byte()\\r\\n if code == b\\\"\\\\xF9\\\":\\r\\n self.g_ext.append(self.parse_gce())\\r\\n elif code == b\\\"\\\\xFF\\\":\\r\\n self.next_byte()\\r\\n app = self.next_bytes(11)\\r\\n if app == b\\\"NETSCAPE2.0\\\":\\r\\n self.parse_ne()\\r\\n else:\\r\\n self.skip()\\r\\n elif code == b\\\"\\\\xFE\\\":\\r\\n self.comments.append(self.parse_ce())\\r\\n else:\\r\\n self.next_bytes(13)\\r\\n self.skip()\\r\\n elif code == b\\\"\\\\x3B\\\":\\r\\n done = True\",\n \"def longest_ORF_noncoding(dna, num_trials):\\n count = 0\\n orfs = []\\n while count < num_trials:\\n current_strand = shuffle_string(dna)\\n longest_in_shuffle = longest_ORF(current_strand)\\n orfs.append(longest_in_shuffle)\\n count = count + 1\\n longest = max(orfs, key=len)\\n return len(longest)\",\n \"def rest_of_ORF(dna): \\n\\n for i in range(3,len(dna)-2,3):\\n \\tstop_codon=dna[i:i+3]\\n \\tstart_codon=dna[:i]\\n \\tif stop_codon=='TAG' or stop_codon=='TAA' or stop_codon=='TGA':\\n \\t\\treturn start_codon\\n \\t\\tbreak\\n \\tif (i+3) >= len(dna)-2:\\n \\treturn dna\",\n \"def prune_decoded_seqs(seqs):\\n out = []\\n for s in seqs:\\n if constant.EOS in s:\\n idx = s.index(constant.EOS_TOKEN)\\n out += [s[:idx]]\\n else:\\n out += [s]\\n return out\",\n \"def find_all_ORFs_both_strands(dna):\\n return find_all_ORFs(dna)+find_all_ORFs(get_reverse_complement(dna))\\n \\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def close_frames(depth: int) -> None:\\n d = current_depth - depth\\n for i in range(d):\\n j = depth + d - (i + 1) # Current depth\\n line = f'· {\\\"│ \\\" * j}└{\\\"┄\\\" * 3}' # * depth_widths[j]\\n print(c.BRIGHT_WHITE + line.ljust(0, '━') + c.ENDC) # 80 also work\",\n \"def longest_ORF_noncoding(dna, num_trials):\\n longest_random_ORF = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# initialize empty list\\n for i in range(num_trials):\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# repeats for num_trials\\n \\trandomized_dna = shuffle_string(dna)\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# finds strings of random dna\\n \\tlongest_random_ORF.append(longest_ORF(randomized_dna))\\t\\t\\t\\t\\t\\t\\t\\t# adds random dna to list\\n\\treturn max(longest_random_ORF, key=len)\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns longest dna string\",\n \"def find_first_orf(sequence,\\n start_codons = ['AUG'],\\n stop_codons = ['UAA', 'UAG', 'UGA']):\\n \\n # Make sure the sequence is valid\\n vet_nucleotide_sequence(sequence)\\n\\n # Make sure the codons are valid\\n for codon in start_codons:\\n vet_codon(codon)\\n for codon in stop_codons:\\n vet_codon(codon)\\n\\n # Get copies of everything in uppercase\\n seq = sequence.upper()\\n starts = [c.upper() for c in start_codons]\\n stops = [c.upper() for c in stop_codons]\\n # Make sure seq is RNA\\n seq = seq.replace('T', 'U')\\n\\n\\n ##########################################################################\\n # `orf_pattern_str` is a regular expression that will match an\\n # open reading frame within a string of RNA bases. \\n # Read the docstring above for additional clues.\\n #I create variables as \\\"strings\\\" to take in start_codons & stop_codons \\\"lists\\\" so it can use them in the \\\"regex\\\"\\n \\n strt = '|'.join(start_codons) #takes the start codon provided and saves it as a string named 'strt'\\n stp = '|'.join(stop_codons) #takes the stop codon provided and takes it as a string named 'stp'\\n\\n #here the `regex`\\n orf_pattern_str = r'(' + strt +r')([AUCG]{3})*('+ stp +r')'\\n #breakdown\\n #the regex is in 3 groups\\n #first group is the start codon\\n # literarily it is 'AUG', but it is dynamic, and (' + strt +r') fixes that\\n #the second group is ([AUGC]{3})* which captures zero or more sets of codon after the start codon\\n #the last group is ((UAA)|(UAG)|(UGA)) dynamically captured as ('+ stp +r')\\n ##########################################################################\\n\\n # Create the regular expression object\\n orf_pattern = re.compile(orf_pattern_str)\\n # Search the sequence\\n match_object = orf_pattern.search(seq)\\n if match_object:\\n return match_object.group()\\n return ''\",\n \"def longest_ORF_noncoding(dna, num_trials):\\n\\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs_both_strands(dna):\\n normal_dna = find_all_ORFs(dna)\\n reverse_dna = find_all_ORFs(get_reverse_complement(dna))\\n list_of_both_strands = normal_dna + reverse_dna\\n return list_of_both_strands\",\n \"def read_FIREXAQ_files(path, folder='merge', var=''):\\n df_list=[]\\n flag_list=[]\\n files2use = sorted(glob.glob(f'{path}/{folder}/*{var}*.ict'))\\n for infileN, infile in enumerate( files2use ):\\n with open(infile) as thefile:\\n try:\\n header= np.array([next(thefile) for x in range(90) ])\\n except:\\n continue\\n start = header[6].replace(',',' ').split()\\n start_date = datetime_( int( start[0] ),\\n int( start[1] ),\\n int( start[2] ))\\n # Find where the header ends and values begin - manually narrowed down\\n for nskip in range(675,680):\\n try:\\n fh = np.loadtxt(infile, skiprows=nskip, delimiter=',')\\n break\\n except:\\n continue\\n thefile = open(infile,'r')\\n c = thefile.readlines()\\n column_names = c[nskip-1].replace(' ','').split(',')\\n df = pd.DataFrame(fh, index=fh[:,0], columns=column_names)\\n\\n # Use a different approach for\\n if (var=='thru'):\\n df = find_FIREXAQ_times(df, start_date, UseTimeStart=True)\\n else:\\n df = find_FIREXAQ_times(df, start_date, UseTimeStart=False)\\n # Include the RF from the file name #\\n # NOTE: research flight (RF) ID not included in filename or files,\\n # so using filenumber instead. This will not work if reading\\n # merge file (var = 'thru').\\n df['FileNumber'] = infileN\\n\\n df_list.append(df)\\n df = pd.concat(df_list)\\n return df\",\n \"def find_all_ORFs_both_strands(dna):\\n reverse_strand = get_reverse_complement(dna)\\n return find_all_ORFs(dna) + find_all_ORFs(reverse_strand)\",\n \"def find_all_ORFs_both_strands(dna):\\n # TODO: implement this\\n all_ORFs_both_strands = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# initialize empty list\\n all_ORFs_both_strands = all_ORFs_both_strands + find_all_ORFs(dna)\\t\\t\\t\\t\\t\\t# adds all ORFs one strand to list\\n reverse_complement_dna = get_reverse_complement(dna)\\t\\t\\t\\t\\t\\t\\t\\t\\t# finds 2nd strand\\n all_ORFs_both_strands = all_ORFs_both_strands + find_all_ORFs(reverse_complement_dna)\\t# finds all ORFs second strand\\n return all_ORFs_both_strands \\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns all ORFs both strands\",\n \"def rest_of_ORF(dna):\\n # [???] 'assumed to begin with a start codon': doesn't need to check input?\\n# if len(dna) < 3:\\n# return \\\"\\\"\\n# if dna[0:3] != start_codon:\\n# return \\\"\\\"\\n\\n l = len(dna)\\n for i in range(3, l, 3):\\n if dna[i: i + 3] in stop_codons:\\n return dna[0: i]\\n return dna\",\n \"def find_missing_pos_in_motif(motifs, motname_li):\\n motifs_def=[]\\n n=0\\n for motname in motname_li:\\n found=[]\\n found_ranges=[]\\n not_found=[]\\n for e in motifs:\\n if e[0]==motname:\\n if not e[2]:\\n not_found.append(e[1])\\n else:\\n found.append(e[1])\\n found_ranges.append(e[3])\\n \\n num_nf=len(not_found)\\n ranges_all=\\\",\\\".join(found_ranges)\\n if num_nf ==0:\\n motifs_def.append([motname,\\\" , \\\".join(found),(ranges_all)])\\n elif num_nf ==3:\\n motifs_def.append([motname,\\\"Motif not found\\\",\\\"None\\\"])\\n else:\\n motifs_def.append([motname,(\\\" , \\\".join(not_found)+\\\" not found\\\"),(ranges_all)])\\n n+=1\\n return motifs_def\",\n \"def extractsequences(filename):\\n\\n yield (filename, 2, None)\\n for m in re.finditer(r\\\"(?!0)[0-9]+\\\", filename):\\n frameno = int(m.group())\\n yield (makenonpaddedname(m), 0, frameno)\\n for m in re.finditer(r\\\"[0-9]+\\\", filename):\\n frameno = int(m.group())\\n if m.end() - m.start() > 1:\\n yield (makepaddedname(m), 1, frameno)\",\n \"def filter_sequences(parent_directory, filename, label = 'Pfam:'):\\n uniprot, repeated_seqs = load_uniprot('{}/{}'.format(parent_directory, filename))\\n seq_fam = {}\\n \\n for u in uniprot:\\n # Only select those sequences\\n # - With the correct label\\n # - That do not contain illegal characters\\n # - Do not include sequences that are in multiple families\\n index = find_index(u.dbxrefs, lambda x: x.startswith(label))\\n if index != -1 and len(set(u._seq._data) - set(alphabet)) == 0 and u._seq._data not in repeated_seqs:\\n seq_fam[u._seq._data] = u.dbxrefs[index][len(label):]\\n \\n filtered_fam = filtered_families(seq_fam)\\n \\n # Write processed output to a separate file\\n with open('{}/processed.txt'.format(parent_directory), 'w') as f:\\n f.write('\\\\n'.join(' '.join((fam, seq))\\n for seq, fam in seq_fam.items()\\n if fam in filtered_fam))\",\n \"def rest_of_ORF(dna):\\n for h in range(0, len(dna), 3):\\n curr_triplet = dna[h : h + 3] \\n #for n in range(0, len(amino_acids.codons),1):\\n if curr_triplet in amino_acids.codons[10]:\\n return dna[0 : h] \\n return dna\",\n \"def _find_all_top_level_non_gene_features(chrom: str, db: FeatureDB, feature_types: List[str]) -> Iterable[Feature]:\\n for feature in db.region(seqid=chrom, featuretype=feature_types):\\n try:\\n _ = next(db.parents(feature.id))\\n except StopIteration:\\n yield feature\",\n \"def _extractFrames_(self, wordRulesFlag):\\n\\t\\t#pdb.set_trace()\\n\\t\\tsimplifyTree(self.srcTree)\\n\\t\\tsimplifyTree(self.tgtTree)\\n\\n\\t\\tsDic, tDic = {}, {}\\n\\t\\tframeSet = set() \\n\\t\\tfor sSubtr in self.srcTree.subtrees():\\n\\t\\t\\tif sSubtr.height() <= 2:\\n\\t\\t\\t\\tcontinue\\n\\n\\t\\t\\tsTreePos = sSubtr.treeposition()\\n\\t\\t\\tsOffset = treePosition2offset(sTreePos, self.srcTree)\\n\\t\\t\\tsDic[sTreePos] = scanBlock(sOffset, 'src', self.waMatrix)\\n\\n\\t\\t\\tfor tSubtr in self.tgtTree.subtrees():\\n\\t\\t\\t\\tif tSubtr.height() <= 2:\\n\\t\\t\\t\\t\\tcontinue\\n\\n\\t\\t\\t\\ttTreePos = tSubtr.treeposition()\\n\\t\\t\\t\\tif tTreePos not in tDic:\\n\\t\\t\\t\\t\\ttOffset = treePosition2offset(tTreePos, self.tgtTree)\\n\\t\\t\\t\\t\\ttDic[tTreePos] = scanBlock(tOffset, 'tgt', self.waMatrix)\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\ttOffset = tDic[tTreePos]\\n\\n\\t\\t\\t\\t#print >> debug_log, self.srcTree[sTreePos]\\n\\t\\t\\t\\t#print >> debug_log, self.tgtTree[tTreePos]\\n\\t\\t\\t\\tif sDic[sTreePos] == tDic[tTreePos] and -1 not in sDic[sTreePos] and -1 not in tDic[tTreePos]:\\n\\t\\t\\t\\t\\t#print >> debug_log, 'paird up!!'\\n\\t\\t\\t\\t\\tframeSet.add(Frame([sTreePos], [tTreePos], self.srcTree, self.tgtTree))\\n\\t\\t\\t\\t#print >> debug_log\\n\\n\\t\\t'''\\n\\t\\tsrcSubtreeSpanDict = self._extractSubtreeSpan_(self.srcTree, wordRulesFlag)\\n\\t\\ttgtSubtreeSpanDict = self._extractSubtreeSpan_(self.tgtTree, wordRulesFlag)\\n\\n\\t\\tframeSet = set() \\n\\t\\tfor span in srcSubtreeSpanDict:\\n\\t\\t\\tif not self._consistentWithWA_(span, 'src'):\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\ttgtSpanList = self._scanSpan_(span, 'src')\\n\\t\\t\\tfor tgtSpan in tgtSpanList:\\n\\t\\t\\t\\tif tgtSpan in tgtSubtreeSpanDict:\\n\\t\\t\\t\\t\\t#print >> debug_log, span, tgtSpan\\n\\t\\t\\t\\t\\tframeSet.add(Frame([srcSubtreeSpanDict[span]], [tgtSubtreeSpanDict[tgtSpan]], self.srcTree, self.tgtTree))\\n\\n\\t\\t#print >> debug_log, '\\\\n'\\n\\t\\tfor span in tgtSubtreeSpanDict:\\n\\t\\t\\tif not self._consistentWithWA_(span, 'tgt'):\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\tsrcSpanList = self._scanSpan_(span, 'tgt')\\n\\t\\t\\tfor srcSpan in srcSpanList:\\n\\t\\t\\t\\tif srcSpan in srcSubtreeSpanDict:\\n\\t\\t\\t\\t\\t#print >> debug_log, srcSpan, span\\n\\t\\t\\t\\t\\tframeSet.add(Frame([srcSubtreeSpanDict[srcSpan]], [tgtSubtreeSpanDict[span]], self.srcTree, self.tgtTree))\\n\\t\\t'''\\n\\t\\t#pdb.set_trace()\\n\\t\\tframeList = self._mergeFrames_(frameSet)\\n\\t\\t#print >> debug_log, len(frameList)\\n\\t\\treturn frameList\",\n \"def get_all_frames(self):\\n #pdb.set_trace()\\n frame_size=(512,512)\\n frame_data = []\\n variant_type = (pythoncom.VT_BYREF | pythoncom.VT_ARRAY | pythoncom.VT_UI2)\\n for i in xrange(self.defaults['EXP_SEQUENTS']):\\n frame_data.append(win32com.client.VARIANT(variant_type, numpy.empty(frame_size)))\\n frame_data[i]=self.appdoc.GetFrame(i+1,frame_data[i])\\n \\n return numpy.array(frame_data, dtype=numpy.uint16)\",\n \"def get_all_translations(rna_sequence, genetic_code):\\n #Convert all rna_sequence to upper case:\\n rna_sequence=rna_sequence.upper()\\n #get the lengh of RNA seq.\\n total_rna_bases=len(rna_sequence)\\n #Create an empty list to store all possible AA seq.\\n polypeptide_list = []\\n #Looping through all the RNA bases, selecting all 3 possible reading frames to scan for tranlation.\\n for i in range(total_rna_bases):\\n i_end= i +3\\n next_three=rna_sequence[i:i_end]\\n #Condition to check if the condon is start codon\\n if next_three=='AUG':\\n #If condition satisfies, translate all rna seq from start to stop codon using first function,\\n #translate_sequence\\n polypeptide=translate_sequence(rna_sequence[i:], genetic_code)\\n polypeptide_list.append(polypeptide)\\n #Return all 3 possible reading frames as a list in polypeptide_list\\n return polypeptide_list\",\n \"def getinnerframes(tb, context=1):\\r\\n framelist = []\\r\\n while tb:\\r\\n framelist.append((tb.tb_frame,) + getframeinfo(tb, context))\\r\\n tb = tb.tb_next\\r\\n return framelist\",\n \"def longest_ORF_noncoding(dna, num_trials):\\n longest=[]\\n for i in range(0,num_trials):\\n \\tshuffled_str=shuffle_string(dna)\\n \\tlongest.append(longest_ORF(shuffled_str))\\n long_ORF=max(longest,key=len)\\n return len(long_ORF)\",\n \"def _read_frame_batch(frames: list, *, format):\\n frame_count = len(frames)\\n assert frame_count > 0\\n\\n f1_idx = 0\\n f1 = None\\n while f1_idx < frame_count and f1 is None:\\n try:\\n f1 = _read_frame(frames[f1_idx], format=format)\\n except SkipFrameException:\\n f1 = None\\n f1_idx += 1\\n ret = [[] for _ in range(len(f1))]\\n\\n for idx in range(len(f1)):\\n # ret[idx] = np.empty(shape=(frame_count,)+np.shape(f1[idx]), dtype=f1[idx].dtype)\\n ret[idx].append(f1[idx])\\n\\n for frameidx in range(1+f1_idx, frame_count):\\n try:\\n fn = _read_frame(frames[frameidx], format=format)\\n except SkipFrameException:\\n continue\\n for compidx in range(len(fn)):\\n # ret[compidx][frameidx] = fn[compidx]\\n ret[compidx].append(fn[compidx])\\n\\n # return ret\\n return [np.array(comp, dtype=comp[0].dtype) for comp in ret]\",\n \"def _read_frames(self):\\n cap = self._read_file()\\n\\n frame_list = []\\n ret_list = []\\n\\n while True:\\n ret, frame = cap.read()\\n if ret:\\n frame_list.append(np.array(frame))\\n ret_list.append(ret)\\n else:\\n break\\n if self.mode==\\\"np\\\":\\n frame_list = np.array(frame_list)\\n return frame_list\",\n \"def gene_finder(dna):\\n threshold = longest_ORF_noncoding(dna, 1500)\\n orfs = find_all_ORFs_both_strands(dna)\\n list1 = []\\n for orf in orfs:\\n if len(orf) > threshold:\\n list1.append(coding_strand_to_AA(orf))\\n return list1\",\n \"def longest_ORF_noncoding(dna, num_trials):\\n list_dna=list(dna)\\n random.shuffle(list_dna)#just shuffles original list, doesn't return, not fruitful\\n random_string_dna=collapse(list_dna)\\n longest_dna=longest_ORF(random_string_dna)\\n return longest_dna\\n dna= 'ATGATGTGAATGATTGCTTGA'\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6846477","0.67647403","0.67115307","0.66981316","0.6597111","0.65776366","0.64758587","0.6420567","0.6389022","0.6327249","0.62816936","0.6255243","0.62321466","0.6223571","0.6206","0.6151061","0.61308336","0.6083877","0.6025945","0.5896849","0.5860287","0.5829243","0.5740269","0.5612716","0.54231083","0.5364995","0.5180579","0.51422","0.51240176","0.5106804","0.504756","0.50434905","0.48159394","0.4805463","0.47856113","0.47190452","0.47036275","0.46812847","0.46729726","0.46681425","0.4662155","0.46412224","0.4640596","0.46358114","0.4614269","0.4610484","0.4579725","0.45726568","0.45589092","0.45504194","0.45259163","0.452555","0.45219797","0.45189473","0.45016658","0.44969708","0.44968507","0.44892082","0.44880918","0.44859546","0.44831434","0.44587135","0.44551215","0.44533214","0.44473544","0.44432154","0.44401103","0.44392794","0.44259787","0.44213045","0.44070828","0.4396365","0.43946806","0.43905288","0.43857643","0.4379394","0.4379371","0.4378256","0.43739438","0.4361355","0.43559003","0.43417814","0.43366486","0.43327892","0.4330618","0.42714807","0.42671245","0.4262787","0.42593536","0.42583278","0.4254779","0.42450017","0.42411998","0.4233062","0.42319322","0.42276114","0.4217248","0.42168725","0.4214464","0.4207483"],"string":"[\n \"0.6846477\",\n \"0.67647403\",\n \"0.67115307\",\n \"0.66981316\",\n \"0.6597111\",\n \"0.65776366\",\n \"0.64758587\",\n \"0.6420567\",\n \"0.6389022\",\n \"0.6327249\",\n \"0.62816936\",\n \"0.6255243\",\n \"0.62321466\",\n \"0.6223571\",\n \"0.6206\",\n \"0.6151061\",\n \"0.61308336\",\n \"0.6083877\",\n \"0.6025945\",\n \"0.5896849\",\n \"0.5860287\",\n \"0.5829243\",\n \"0.5740269\",\n \"0.5612716\",\n \"0.54231083\",\n \"0.5364995\",\n \"0.5180579\",\n \"0.51422\",\n \"0.51240176\",\n \"0.5106804\",\n \"0.504756\",\n \"0.50434905\",\n \"0.48159394\",\n \"0.4805463\",\n \"0.47856113\",\n \"0.47190452\",\n \"0.47036275\",\n \"0.46812847\",\n \"0.46729726\",\n \"0.46681425\",\n \"0.4662155\",\n \"0.46412224\",\n \"0.4640596\",\n \"0.46358114\",\n \"0.4614269\",\n \"0.4610484\",\n \"0.4579725\",\n \"0.45726568\",\n \"0.45589092\",\n \"0.45504194\",\n \"0.45259163\",\n \"0.452555\",\n \"0.45219797\",\n \"0.45189473\",\n \"0.45016658\",\n \"0.44969708\",\n \"0.44968507\",\n \"0.44892082\",\n \"0.44880918\",\n \"0.44859546\",\n \"0.44831434\",\n \"0.44587135\",\n \"0.44551215\",\n \"0.44533214\",\n \"0.44473544\",\n \"0.44432154\",\n \"0.44401103\",\n \"0.44392794\",\n \"0.44259787\",\n \"0.44213045\",\n \"0.44070828\",\n \"0.4396365\",\n \"0.43946806\",\n \"0.43905288\",\n \"0.43857643\",\n \"0.4379394\",\n \"0.4379371\",\n \"0.4378256\",\n \"0.43739438\",\n \"0.4361355\",\n \"0.43559003\",\n \"0.43417814\",\n \"0.43366486\",\n \"0.43327892\",\n \"0.4330618\",\n \"0.42714807\",\n \"0.42671245\",\n \"0.4262787\",\n \"0.42593536\",\n \"0.42583278\",\n \"0.4254779\",\n \"0.42450017\",\n \"0.42411998\",\n \"0.4233062\",\n \"0.42319322\",\n \"0.42276114\",\n \"0.4217248\",\n \"0.42168725\",\n \"0.4214464\",\n \"0.4207483\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.63819563"},"document_rank":{"kind":"string","value":"9"}}},{"rowIdx":92999,"cells":{"query":{"kind":"string","value":"Unit tests for the find_all_ORFs function"},"document":{"kind":"string","value":"def find_all_ORFs_unit_tests():\n data_list = [\n [\"ATGCATGAATGTAG\", [\"ATGCATGAATGTAG\", \"ATGAATGTAG\", \"ATG\"]],\n [\"ATG\", [\"ATG\"]],\n [\"AATG\", [\"ATG\"]],\n [\"AAATG\", [\"ATG\"]],\n [\"ATGATG\", [\"ATGATG\"]],\n [\"ATATGGATTGA\", [\"ATGGAT\"]],\n [\"ATGAGATTAG\", [\"ATGAGATTAG\"]],\n [\"ATATGGATTAGTAGTAATGAAAGTATAG\", [\"ATGAAAGTA\", \"ATGGAT\", ]],\n# ATA TGG ATT AGT AGT AAT GAA AGT ATA G\n# TAT GGA TTA GTA GTA ATG AAA GTA TAG\n# ATG GAT TAG TAG TAA TGA AAG TAT AG\n [\"ATGTCACGCAATGTAGGATGGATGGATTAGAC\", [\"ATGTCACGCAATGTAGGATGGATGGAT\", \"ATG\", \"ATGGATGGATTAGAC\"]],\n# ATG TCA CGC AAT GTA GGA TGG ATG GAT TAG AC --> ATG TCA CGC AAT GTA GGA TGG ATG GAT\n# TGT CAC GCA ATG TAG GAT GGA TGG ATT AGA C\n# GTC ACG CAA TGT AGG ATG GAT GGA TTA GAC\n [\"ATGATGTAG\", [\"ATGATG\"]],\n [\"TCGATGC\", [\"ATGC\"]],\n [\"AAA\", []],\n# TCG ATG C\n# CGA TGC\n# GAT GC\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\""},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def find_all_ORFs_both_strands_unit_tests():\n\n # YOUR IMPLEMENTATION HERE","def find_all_ORFs_unit_tests():\n print 'Begin Unit test Find_all_ORFs'\n input_a='ATGCATGAATGTAGATGTAG'\n expected_output='[ATGCATGAATGTAGATGTAG, ATGAATGTAGATGTAG, ATG, ATG]'\n actual_output=find_all_ORFs(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output\n \n input_a='ATGCATGAATGTAGATGCATCATTAG'\n expected_output='[ATGCATGAATGTAGATGCATCATTAG, ATGAATGTAGATGCATCATTAG, ATG, ATGCATCAT]'\n actual_output=find_all_ORFs(input_a)\n print 'Expected Output is ' + expected_output\n print \"actucal OUtput is\", actual_output\n print 'ENd Unit test Find_all_ORFs'","def find_all(self):","def find_all(self):\n pass","def find_all_ORFs_oneframe_unit_tests():\n\n # YOUR IMPLEMENTATION HERE","def find_all_ORFs_unit_tests():\n \n input = [\"dna\"]\n expected_output = [\"all non-nested ORFs\"]\n actual = []\n for k in input:\n actual.append(find_all_ORFs(k))\n print input \n print actual\n print expected_output","def find_all_ORFs_unit_tests():\n \n print \"input: ATGCTA, \"+\"output: \"+ \",\".join(find_all_ORFs(\"ATGCTA\"))+\", actual output: CTA\"\n print \"input: GTCACTTATGGGTTT, \"+\"output: \"+\",\".join(find_all_ORFs(\"ATGGATGCTTAGGGATGTTT\"))+\", actual output: GTCACT,GGTTTT,TCACTTAGGGTTTT,CACTTAGGGTTTT\"\n print \"input: AAATTTTATAATGGGTGAAGTTAG, \"+\"output: \"+\",\".join(find_all_ORFs(\"AAATTTTATAATGGGTGAAGTTAG\"))+\", actual output: ATGGGTGAAGTT\"\n print \"input: TATATGGAGGATAATAGTTGATAATAG, \"+\"output: \"+ \",\".join(find_all_ORFs(\"TATATGGAGGATAATAGTTGATAATAG\"))+\", actual output: ATGGAGGATAATAGT\"","def test_otoroshi_controllers_adminapi_tcp_service_api_controller_find_all_entities_action(self):\n pass","def test_find_all(self):\n result = Project.objects.find(['test'], project_type=None)\n self.assertEqual(len(result), 2)\n result = Project.objects.find(['ThisFails'], project_type=None)\n self.assertEqual(len(result), 0)","def find_all_ORFs(dna):\n \n # YOUR IMPLEMENTATION HERE","def test_search_or(self):\n pkgs = [\n make_package(factory=SQLPackage),\n make_package(\n \"somepackage\",\n version=\"1.3\",\n filename=\"mypath3\",\n summary=\"this is mypkg\",\n factory=SQLPackage,\n ),\n make_package(\"mypkg2\", \"1.3.4\", \"my/other/path\", factory=SQLPackage),\n make_package(\"package\", factory=SQLPackage),\n ]\n for pkg in pkgs:\n self.db.save(pkg)\n criteria = {\"name\": [\"mypkg\"], \"summary\": [\"mypkg\"]}\n packages = self.db.search(criteria, \"or\")\n self.assertCountEqual(packages, pkgs[:-1])","def find_all_ORFs_both_strands_unit_tests():\n print ''\n print 'Begin Unit test Find_all_ORFs both tests'\n input_a='ATGCGAGGGTAGATGGATTAG'\n expected_output='[ATGCGAGGG, ATGGAT]'\n actual_output=find_all_ORFs_both_strands(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output\n \n \n input_a='ATGCGAATGTAGCATCAAATAGATGTAG'\n expected_output='[ATGCGAATG, ATG, ATGCTACATTCGCAT]'\n actual_output=find_all_ORFs_both_strands(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output \n print 'end'\n print ''","def find_all_ORFs_unit_tests(dna, expected):\n \n print find_all_ORFs(\"ATGCATGAATGTAG\")\n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + find_all_ORFs(dna)","def orfFinder(data):\n\t\n\tORFile = getORFs(data.seqFile, \n\t\t\t\t\t data.queryName, \n\t\t\t\t\t data.o)\n\tsetattr(data, \"ORFs\", ORFile)","def test_search_or(self):\n pkgs = [\n make_package(factory=SQLPackage),\n make_package(\n \"somepackage\",\n version=\"1.3\",\n filename=\"mypath3\",\n summary=\"this is mypkg\",\n factory=SQLPackage,\n ),\n make_package(\"mypkg2\", \"1.3.4\", \"my/other/path\", factory=SQLPackage),\n make_package(\"package\", factory=SQLPackage),\n ]\n self.sql.add_all(pkgs)\n criteria = {\"name\": [\"mypkg\"], \"summary\": [\"mypkg\"]}\n packages = self.db.search(criteria, \"or\")\n self.assertCountEqual(packages, pkgs[:-1])","def test_find_all(self):\n # arrange\n movie_id = MovieId('123')\n character = character_random_with_movie_ids(MovieIds([movie_id]))\n people = People([character])\n movie = movie_random_with_movie_id_and_people(movie_id, people)\n expected = Movies([movie])\n\n self.ghibli_client_mock__people([{'id': character.character_id, 'name': character.name,\n 'gender': character.gender, 'age': character.age,\n 'eye_color': character.eye_color, 'hair_color': character.hair_color,\n 'films': [f'http://url/{movie_id}']}])\n self.ghibli_client_mock__movies([{'id': movie_id, 'title': movie.title,\n 'description': movie.description, 'director': movie.director,\n 'producer': movie.producer, 'release_date': movie.release_date,\n 'rt_score': movie.rt_score}])\n\n # act\n repository = self.ghibli_movie_repository()\n movies = repository.find_all()\n\n # assert\n self.assertEqual(expected, movies)","def test_search_or(self):\n pkgs = [\n make_package(factory=DynamoPackage),\n make_package(\n \"somepackage\",\n version=\"1.3\",\n filename=\"mypath3\",\n summary=\"this is mypkg\",\n factory=DynamoPackage,\n ),\n make_package(\"mypkg2\", \"1.3.4\", \"my/other/path\", factory=DynamoPackage),\n make_package(\"package\", factory=DynamoPackage),\n ]\n self._save_pkgs(*pkgs)\n criteria = {\"name\": [\"mypkg\"], \"summary\": [\"mypkg\"]}\n packages = self.db.search(criteria, \"or\")\n self.assertCountEqual(packages, pkgs[:-1])","def test_find_all(self):\n\n # Test valid empty inputs\n\n self.assertEqual(find_all(None, None), [])\n self.assertEqual(find_all('', None), [])\n self.assertEqual(find_all(None, ''), [])\n\n self.assertEqual(find_all(b'', b''), [])\n self.assertEqual(find_all(b'', ''), [])\n\n self.assertEqual(find_all('', b''), [])\n self.assertEqual(find_all('', ''), [])\n\n # Test with missing or invalid inputs\n\n self.assertEqual(find_all('abc', '123'), [])\n self.assertEqual(find_all('abc', 'abcabc'), [])\n\n self.assertEqual(find_all('abc', 'abc', limit=0), [])\n self.assertEqual(find_all('abc', 'abc', limit=0, reverse=True), [])\n self.assertEqual(find_all('abc', 'abc', limit=0, start=0, end=3), [])\n self.assertEqual(find_all('abc', 'abc', limit=0, start=0, end=3, reverse=True), [])\n\n self.assertEqual(find_all('abc', 'abc', start=3, end=0), [])\n self.assertEqual(find_all('abc', 'abc', start=3, end=0, limit=1), [])\n self.assertEqual(find_all('abc', 'abc', start=3, end=0, reverse=True), [])\n self.assertEqual(find_all('abc', 'abc', start=3, end=0, limit=1, reverse=True), [])\n\n # Test with valid, non-empty inputs\n\n self._test_find_all(\n s='ab?cdef?ghijkl?mnopqrstuv?wxy?z?',\n sub='?',\n out=[2, 7, 14, 25, 29, 31]\n )\n self._test_find_all(\n s='ab??cdef??ghijkl??mnopqrstuv??wxy??z??',\n sub='??',\n out=[2, 8, 16, 28, 33, 36]\n )\n self._test_find_all(\n s='ab???cdef???ghijkl???mnopqrstuv???wxy???z???',\n sub='???',\n out=[2, 9, 18, 31, 37, 41]\n )","def find_all_ORFs_both_strands_unit_tests():\n data_list = [\n [\"ATGCGAATGTAGCATCAAA\", [\"ATGCGAATG\", \"ATGCTACATTCGCAT\"]],\n [\"ATG\", [\"ATG\"]],\n [\"CAT\", [\"ATG\"]],\n [\"CATCAT\", [\"ATGATG\"]],\n [\"CATGGGCAT\", [\"ATGGGCAT\", \"ATGCCCATG\"]],\n [\"CATGCAGTGCACGGATGGCAT\", [\"ATGCAGTGCACGGATGGCAT\", \"ATGGCAT\", \"ATGCCATCCGTGCACTGCATG\"]],\n# CATGCAGTGCACGGATGGCAT\n# CAT GCA GTG CAC GGA TGG CAT\n# ATG CAG TGC ACG GAT GGC AT\n# TGC AGT GCA CGG ATG GCA T\n# ATGCCATCCGTGCACTGCATG\n# ATG CCA TCC GTG CAC TGC ATG\n# TGC CAT CCG TGC ACT GCA TG\n# GCC ATC CGT GCA CTG CAT G\n [\"CATATGTAG\", [\"ATG\", \"ATG\"]],\n [\"ATGGGGCATCATTAG\", [\"ATGGGGCATCAT\", \"ATGATGCCCCAT\"]],\n# ATGGGGCATCATTAG\n# ATG GGG CAT CAT TAG\n# TGG GGC ATC ATT AG\n# GGG GCA TCA TTA G\n# CTAATGATGCCCCAT\n# CTA ATG ATG CCC CAT\n# TAA TGA TGC CCC AT\n# AAT GAT GCC CCA T\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs_both_strands(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def test_get_foods_search(self):\n pass","def test_all_finder_methods(self):\n methods = ['all', 'first', 'find']\n\n for method in methods:\n result = getattr(self.Test, method)\n self.assertEqual(type(result).__name__, 'instancemethod')\n self.assertEqual(result.im_class.__name__, 'Relation')","def test_organization_all(self):\n gryffindor = models.Organization(name='gryffindor')\n ravenclaw = models.Organization(name='ravenclaw')\n db.session.add(gryffindor)\n db.session.add(ravenclaw)\n db.session.commit()\n # scenario 1: when neither buids nor names are given\n self.assertEqual(models.Organization.all(), [])\n # scenario 2: when buids are passed\n orglist = [gryffindor, ravenclaw]\n orgids = [gryffindor.buid, ravenclaw.buid]\n all_by_buids = models.Organization.all(buids=orgids)\n self.assertIsInstance(all_by_buids, list)\n self.assertCountEqual(all_by_buids, orglist)\n # scenario 3: when org names are passed\n names = [gryffindor.name, ravenclaw.name]\n all_by_names = models.Organization.all(names=names)\n self.assertIsInstance(all_by_names, list)\n self.assertCountEqual(all_by_names, orglist)\n # scenario 4: when defercols is set to True for names\n all_by_names_with_defercols = models.Organization.all(names=names)\n self.assertIsInstance(all_by_names_with_defercols, list)\n self.assertCountEqual(all_by_names_with_defercols, orglist)\n # scenario 5: when defercols is set to True for buids\n all_by_buids_with_defercols = models.Organization.all(buids=orgids)\n self.assertIsInstance(all_by_buids_with_defercols, list)\n self.assertCountEqual(all_by_buids_with_defercols, orglist)","def test_all_documents(self):","def find_all_ORFs_oneframe_unit_tests():\n\n input = [\"dna\"]\n expected_output = [\"all non-nester ORFs\"]\n actual = []\n for k in input:\n actual.append(find_all_ORFs_oneframe(k))\n print input \n print actual\n print expected_output","def find_all(session=None):\n return find(session=session)","def test_retrieve_l_organizations(self):\n pass","def test_find(self):\n user_a = self.Person.objects.create(name=\"User A\", age=20)\n user_b = self.Person.objects.create(name=\"User B\", age=30)\n\n # Find all people in the collection\n people = self.Person.objects\n assert people.count() == 2\n results = list(people)\n\n assert isinstance(results[0], self.Person)\n assert isinstance(results[0].id, ObjectId)\n\n assert results[0] == user_a\n assert results[0].name == \"User A\"\n assert results[0].age == 20\n\n assert results[1] == user_b\n assert results[1].name == \"User B\"\n assert results[1].age == 30\n\n # Filter people by age\n people = self.Person.objects(age=20)\n assert people.count() == 1\n person = next(people)\n assert person == user_a\n assert person.name == \"User A\"\n assert person.age == 20","def find_all_ORFs_both_strands(dna):\n \n # YOUR IMPLEMENTATION HERE","def find_all_ORFs_oneframe_unit_tests():\n data_list = [\n [\"ATGCATGAATGTAGATAGATGTGCCC\", [\"ATGCATGAATGTAGA\", \"ATGTGCCC\"]],\n [\"ATGTAGATGTAG\", [\"ATG\", \"ATG\"]],\n [\"ATGATGATG\", [\"ATGATGATG\"]],\n [\"ATGGGGGATTAGATGATG\", [\"ATGGGGGAT\", \"ATGATG\"]],\n [\"ATGTGAATGTAA\", [\"ATG\", \"ATG\"]],\n [\"ATGTGAATGTAAATG\", [\"ATG\", \"ATG\", \"ATG\"]],\n [\"ATGCGTGGTGATTAGATGGATGGGGATTGA\", [\"ATGCGTGGTGAT\", \"ATGGATGGGGAT\"]],\n [\"ATGAAATTTCCCGGGAAATTTCCCGGG\", [\"ATGAAATTTCCCGGGAAATTTCCCGGG\"]],\n [\"ATGAAATTTTGAATGGGGCCC\", [\"ATGAAATTT\", \"ATGGGGCCC\"]],\n [\"ATGAAATTTTGAATGGGGCCCTAG\", [\"ATGAAATTT\", \"ATGGGGCCC\"]],\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\",\n print \"expected output: \" + str(data[1]) + \",\",\n o = find_all_ORFs_oneframe(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def test_return_all(self):\n self.data.return_all()","def find_all_ORFs(dna):\n ans = find_all_ORFs_oneframe(dna)\n ans.extend(find_all_ORFs_oneframe(dna[1:]))\n ans.extend(find_all_ORFs_oneframe(dna[2:]))\n return ans","def test_query_algorithms_ORqueryfrom200Algorithms(self):\n query_string = 'displayName102 OR algorithmId23'\n upload_data_list = []\n create_test_algorithm_list(upload_data_list, 200)\n documents = []\n create_test_documents_list(upload_data_list, documents, 200)\n index = search.Index(name=search_algorithm._INDEX_STRING)\n index.put(documents)\n # end of data preparation\n numbers = ['23', '102']\n right_answer_list = []\n for number in numbers:\n data = {}\n data['algorithmId'] = 'algorithmId' + number\n data['algorithmSummary'] = 'algorithmSummary' + number\n data['displayName'] = 'displayName' + number\n data['linkURL'] = 'linkURL' + number\n right_answer_list.append(data)\n # end right answer list preparation\n result = search_algorithm.query_algorithms(index, query_string)\n self.assertEqual(len(right_answer_list), len(result), msg='Wrong number of algorithms')\n self.assertItemsEqual(right_answer_list, result, msg='Discrepancy in returned algorithms')","def test_getorgs(self):\n pass","def test_status_find_all(session, result_count, model_class, enum_class):\n results = model_class.find_all()\n assert results\n assert len(results) == result_count\n for result in results:\n assert result.status_type in enum_class\n assert result.status_type_desc\n assert result.legacy_status_type","def find_all_ORFs(dna):\n all_ORFs = []\n i = 0\n\n for i in range (0,3): \n all_ORFs.extend(find_all_ORFs_oneframe(dna))\n dna = 'X' + dna\n\n return all_ORFs","def test_find_multi_two(self):\n result = Project.objects.find(['category', 'project'])\n self.assertEqual(len(result), 2)","def test_get_foods(self):\n pass","def test_searchCar(self):\n make = \"Toyota\"\n body_type = \"Seden\"\n colour = \"Black\"\n seats = \"5\"\n cost_per_hour = \"10.5\"\n booked = True\n cars = db.session.query(Car).filter(or_(Car.make == make, \n Car.body_type == body_type,\n Car.colour == colour,\n Car.seats == seats,\n Car.cost_per_hour == cost_per_hour,\n Car.booked == booked)).all()\n self.assertTrue((cars is not None))","def test_find_relation_types(self):\n pass","def test_organizations_list(self):\n pass","def test_get_list(self):\n pass","def test_get_records(self):\n pass","def test_search(self):\n pass","def test_search(self):\n pass","def test_search(self):\n pass","def test_fetch_all():\n response = requests.get('http://localhost:5000/api/persons')\n data = response.json()\n\n assert response.status_code == 200\n for field in FIELDS:\n assert field in data[0]","def all(klass):\n return klass.find()","def find_all_ORFs(dna):\n dnatwo = dna[1:]\n dnathree = dna[2:]\n all_ORFs = find_all_ORFs_oneframe(dna)\n all_ORFs.extend(find_all_ORFs_oneframe(dnatwo))\n all_ORFs.extend(find_all_ORFs_oneframe(dnathree))\n if [] in all_ORFs:\n all_ORFs.remove([])\n return all_ORFs","def object_finder(\n self, datatable, objectlist, ralist, declist, radius,\n longquery=True\n ):\n pass","def test_organizations_read(self):\n pass","def test_find_multi_fields(self):\n result = Project.objects.find(['project', 'xxx'])\n self.assertEqual(len(result), 2)","def rest_of_ORF_unit_tests():\n data_list = [\n [\"ATGTGAA\", \"ATG\"],\n [\"ATGAGATAGG\", \"ATGAGA\"],\n [\"ATG\", \"ATG\"],\n [\"ATGTAG\", \"ATG\"],\n [\"ATGTAA\", \"ATG\"],\n [\"ATGTGA\", \"ATG\"],\n [\"ATGAAATTTGGGAAATTTGGGTAG\", \"ATGAAATTTGGGAAATTTGGG\"],\n [\"ATGAAATTTGGG\", \"ATGAAATTTGGG\"],\n [\"ATGAGAAGGAAATTTGATGGGGATGGAAGATT\", \"ATGAGAAGGAAATTTGATGGGGATGGAAGATT\"],\n [\"ATGAGAAGGAAATTTGATGGGGATGGAAGATAA\", \"ATGAGAAGGAAATTTGATGGGGATGGAAGA\"],\n [\"ATGAA\", \"ATGAA\"],\n [\"ATGATGATG\", \"ATGATGATG\"],\n ]\n for data in data_list:\n if len(data) == 2:\n print \"input: \" + str(data[0]) + \",\" ,\n print \"expected output: \" + str(data[1]) + \",\",\n o = rest_of_ORF(data[0])\n print \"actual output: \" + str(o)\n if o != data[1]:\n print \"## Test Fail Here!\"","def test_find_description_multi_two(self):\n result = Project.objects.find(['xxx', 'yyy'], project_type=None)\n self.assertEqual(len(result), 2)","def test_get_foods_list(self):\n pass","def find_all_ORFs_oneframe_unit_tests():\n input_a='ATGATTATTTGATGAATGGATTGA'\n expected_output='[ATGATTATT,ATGGAT]'\n actual_output=find_all_ORFs_oneframe(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output\n \n input_a='ATGGGATTGTTT'\n expected_output='[ATGGATTGTTT]'\n actual_output=find_all_ORFs_oneframe(input_a)\n print 'Expected Output is ' + expected_output\n print actual_output","def test_all():\n assert(hasattr(tekel, '__all__'))\n assert(isinstance(tekel.__all__, list))\n assert(len(tekel.__all__) >= 0)","def rest_of_ORF_unit_tests():\n input = [\"dna\"]\n expected_output = [\"rest of ORFs\"]\n actual = []\n for k in input:\n actual.append(rest_of_ORF(k))\n print input \n print actual\n print expected_output","def test_xmlrpc_ir_model_search(self):\n o = self.xmlrpc_object\n db_name = common.get_db_name()\n ids = o.execute(db_name, self.admin_uid, 'admin', 'ir.model', 'search', [])\n self.assertIsInstance(ids, list)\n ids = o.execute(db_name, self.admin_uid, 'admin', 'ir.model', 'search', [], {})\n self.assertIsInstance(ids, list)","def find_all_ORFs(dna):\n all_ORFs=[]\n for i in range (0,3):\n \tframe=dna[i:] \n all_ORFs+=find_all_ORFs_oneframe(frame)\n return all_ORFs","def find_all_ORFs(dna):\n all_ORFs = []\n for i in range(0, 3):\n dna_new = dna[i:]\n all_ORFs += find_all_ORFs_oneframe(dna_new)\n return all_ORFs","def find_all(self, collection):\n obj = getattr(self.db, collection)\n result = obj.find()\n return result","def test_resource_user_resource_find_users_get(self):\n pass","def test_all_filter_op_fields(self):\n for field in OCIFilterSerializer._opfields:\n field = \"and:\" + field\n filter_param = {field: [\"1\", \"2\"]}\n serializer = OCIFilterSerializer(data=filter_param)\n self.assertTrue(serializer.is_valid())\n for field in OCIFilterSerializer._opfields:\n field = \"or:\" + field\n filter_param = {field: [\"1\", \"2\"]}\n serializer = OCIFilterSerializer(data=filter_param)\n self.assertTrue(serializer.is_valid())","def test_query_all(test_store, andy, pandy, candy):\n items = list(test_store.get_by())\n assert len(items) == 3\n assert andy in items\n assert pandy in items\n assert candy in items","def find_all_ORFs_both_strands_unit_tests(dna, expected):\n\n print find_all_ORFs_both_strands(\"ATGCGAATGTAGCATCAAA\")\n print \"input: \" + str(dna) + \", expected output: \" + str(expected) + \", actual output: \" + find_all_ORFs_both_strands(dna)","def test_get_all(self):\n\n # Select on empty set\n selected = self.user_api.get_all()\n self.assertTrue(selected.success)\n self.assertFalse(selected.documents)\n\n # Inserting several users\n inserted = self.user_api.insert_user(MAGEN_USER)\n self.assertTrue(inserted.success)\n another_user = MAGEN_USER.copy()\n another_user.pop('user_uuid')\n another_user['username'] = 'test_another_username'\n another_user['first_name'] = 'test_another_f_name'\n inserted = self.user_api.insert_user(another_user)\n self.assertTrue(inserted.success)\n\n # Select all users from Database\n selected = self.user_api.get_all()\n self.assertTrue(selected.success)\n self.assertEqual(len(selected.documents), 2)\n self.assertEqual(selected.documents[0], MAGEN_USER)\n # Verify that user_uuid was generated\n self.assertIn('user_uuid', selected.documents[1])\n # Verify that other keys were inserted\n self.assertEqual(selected.documents[1], another_user)","def test_success_with_all_orgs(self):\n auth_client = self.create_auth_client()\n all_orgs = ListOrgSerializer(Org.objects.all(), many=True)\n response = auth_client.get(self.search_org_api)\n self.assertEqual(response.data, all_orgs.data)","def find_all_ORFs(dna):\n ORFs = find_all_ORFs_oneframe(dna) + find_all_ORFs_oneframe(dna[1:]) + find_all_ORFs_oneframe(dna[2:])\n\n return ORFs","def test_get_parsed_files(self):\n files = Historical_ROAs_Parser()._get_parsed_files()\n with Historical_ROAs_Parsed_Table() as t:\n for f in files:\n sql = f\"SELECT * FROM {t.name} WHERE file = '{f}'\"\n assert len(t.execute(sql)) == 1","def test_apply_endorsements(self):","def find_all_ORFs_both_strands_unit_tests():\n print \"input: CTA, \"+\"output: \"+ \",\".join(find_all_ORFs_both_strands(\"CTA\"))+\", actual output: CTA,TA,A,AG,G\"\n print \"input: GTCACTTAGGGTTTT, \"+\"output: \"+\",\".join(find_all_ORFs_both_strands(\"GTCACTTAGGGTTTT\"))+\", actual output: GTCACT,GGTTTT,TCACTTAGGGTTTT,CACTTAGGGTTTT,AAAACCCTAAGTGAC,AAACCC,GTGAC,AACCCTAAG\"\n print \"input: AAATTTTATAATGGGTGAAGTTAG, \"+\"output: \"+\",\".join(find_all_ORFs_both_strands(\"AAATTTTATAATGGGTGAAGTTAG\"))+\", actual output: AAATTTTATAATGGG,AGT,AATTTTATAATGGGTGAAGTTAG,ATTTTA,TGGGTGAAGTTAG,CTAACTTCACCCATTATAAAATTT,CTTCACCCATTA,AATTT,AACTTCACCCATTATAAAATTT\"\n print \"input: TATATGGAGGATAATAGTTGATAATAG, \"+\"output: \"+ \",\".join(find_all_ORFs_both_strands(\"TATATGGAGGATAATAGTTGATAATAG\"))+\", actual output: TATATGGAGGATAATAGT,ATATGGAGGATAATAGTTGATAATAG,TATGGAGGA,TTGATAATAG,CTATTATCAACTATTATCCTCCATATA,TATTATCAACTATTATCCTCCATATA,ATTATCAACTATTATCCTCCATATA\"","def test_get_all_ordes(self):\n test_client = app.test_client()\n test_client.post('/api/v1/orders', data=json.dumps(dict(\n order_number=\"order_number\", order_description=\"order_description\",\n order_price=\"order_price\", size=\"size\")), content_type='application/json')\n response = test_client.get('/api/v1/orders')\n self.assertEqual(len(json.loads(response.data)), 1)","def test_get_bios_unit_list(self):\n pass","def test_run_all_searches(): # ***Incomplete test\n ##########################\n # Arrange.\n query_file_list = \"query_file_list\"\n\n ##########################\n # Act.\n #x = run_all_searches(query_file_list)\n\n ##########################\n # Assert.\n assert True == True # ***Temporary.","def findall(cls, *lst, **dct):\n query = cls.where(*lst, **dct).select()\n result = query.execute()\n return result.fetchall()","def find_all():\n return ItopapiPrototype.find_all(ItopapiOSLicence)","def test_get_all_objects(self):\n url = '/product/xml/'\n response = self.client.get(url, **self.headers)\n # Request should not be validated by a 401\n self.failUnlessEqual(response.status_code, 401)\n response = self.client.get(url, **self.advancedheaders)\n # Request should be validated by a 200\n self.failUnlessEqual(response.status_code, 200)\n xml_response = parseString(response.content)\n\n product_tags =[elt for elt in xml_response.getElementsByTagName('object') if elt.getAttribute('model') == 'product.product']\n # check that all product are displayed\n self.failUnlessEqual(len(product_tags), Product.objects.count())","def test_get_results(self):\n pass","def test_searchOr(self):\n return self._messageSetSearchTest('OR 1 2', [1, 2])","def test_get_list8(self):\n pass","def test_get_users(self):\n pass","def test_all(self):\n self.assertEqual(type(self.vehicle_list), type([]))\n [self.assertEqual(type(i), BusVehicle) for i in self.vehicle_list]","def findAll(self) -> \"Stream<MatchResult>\":\n raise NotImplementedError","def test_execute(self):\n self.mocked_cursor.fetchall.return_value = []\n\n db = database.Database()\n result = db.execute(sql=\"SELECT * from FOO WHERE bar LIKE 'baz'\")\n self.assertTrue(isinstance(result, list))","def __call__(self, *args, **kwargs):\r\n return apply(self.findAll, args, kwargs)","def test_everything(self):\n\n qs = FBO(\n path=TEST_FILES_ROOT,\n ).exclude(\n name__glob='*~',\n ).exclude(\n name__glob='*.meta',\n )\n\n self.assertEqual(\n 7,\n qs.count(),\n )\n self.assertEqual(\n {\n 'index.md',\n 'subdir/index.md',\n 'test1.md',\n 'test2.md',\n 'test1.rst',\n 'test2.rst',\n 'test3.rst',\n },\n {o.name for o in qs},\n )","def test_get_all_boats(self):\n pass","def test_get_insumo(self):","def test_find_all_miss_cache(self):\n # arrange\n movie_id = MovieId('123')\n character = character_random_with_movie_ids(MovieIds([movie_id]))\n people = People([character])\n movie = movie_random_with_movie_id_and_people(movie_id, people)\n expected = Movies([movie])\n self.movie_repository_mock__find_all(expected)\n\n # act\n repository = self.cache_movie_repository_decorator()\n response = repository.find_all()\n\n # assert\n self.assertEqual(expected, response)\n self.assertEqual(1, self.movie_repository_mock().find_all.call_count)","def test_search_and(self):\n pkgs = [\n make_package(factory=SQLPackage),\n make_package(\n \"somepackage\",\n version=\"1.3\",\n filename=\"mypath3\",\n summary=\"this is mypkg\",\n factory=SQLPackage,\n ),\n make_package(\"mypkg2\", \"1.3.4\", \"my/other/path\", factory=SQLPackage),\n make_package(\"package\", factory=SQLPackage),\n ]\n for pkg in pkgs:\n self.db.save(pkg)\n criteria = {\"name\": [\"my\", \"pkg\"], \"summary\": [\"this\", \"mypkg\"]}\n packages = self.db.search(criteria, \"and\")\n self.assertCountEqual(packages, pkgs[:-1])","def test_ipam_rirs_list(self):\n pass","def find_all_ORFs(dna):\n index = 0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# initialize index\n all_ORFs = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitalize empty list\n while index < 3:\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# switches throught the 3 frames\n \tall_ORFs = all_ORFs + find_all_ORFs_oneframe(dna[index:])\t# adds all ORFs oneframe to the list\n \tindex += 1\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# indexes +1\n return all_ORFs \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# returns list of all ORFs in all 3 frames","def test_regex_query_shortcuts(self):\n person = self.Person(name=\"Guido van Rossum\")\n person.save()\n\n # Test contains\n obj = self.Person.objects(name__contains=\"van\").first()\n assert obj == person\n obj = self.Person.objects(name__contains=\"Van\").first()\n assert obj is None\n\n # Test icontains\n obj = self.Person.objects(name__icontains=\"Van\").first()\n assert obj == person\n\n # Test startswith\n obj = self.Person.objects(name__startswith=\"Guido\").first()\n assert obj == person\n obj = self.Person.objects(name__startswith=\"guido\").first()\n assert obj is None\n\n # Test istartswith\n obj = self.Person.objects(name__istartswith=\"guido\").first()\n assert obj == person\n\n # Test endswith\n obj = self.Person.objects(name__endswith=\"Rossum\").first()\n assert obj == person\n obj = self.Person.objects(name__endswith=\"rossuM\").first()\n assert obj is None\n\n # Test iendswith\n obj = self.Person.objects(name__iendswith=\"rossuM\").first()\n assert obj == person\n\n # Test exact\n obj = self.Person.objects(name__exact=\"Guido van Rossum\").first()\n assert obj == person\n obj = self.Person.objects(name__exact=\"Guido van rossum\").first()\n assert obj is None\n obj = self.Person.objects(name__exact=\"Guido van Rossu\").first()\n assert obj is None\n\n # Test iexact\n obj = self.Person.objects(name__iexact=\"gUIDO VAN rOSSUM\").first()\n assert obj == person\n obj = self.Person.objects(name__iexact=\"gUIDO VAN rOSSU\").first()\n assert obj is None\n\n # Test wholeword\n obj = self.Person.objects(name__wholeword=\"Guido\").first()\n assert obj == person\n obj = self.Person.objects(name__wholeword=\"rossum\").first()\n assert obj is None\n obj = self.Person.objects(name__wholeword=\"Rossu\").first()\n assert obj is None\n\n # Test iwholeword\n obj = self.Person.objects(name__iwholeword=\"rOSSUM\").first()\n assert obj == person\n obj = self.Person.objects(name__iwholeword=\"rOSSU\").first()\n assert obj is None\n\n # Test regex\n obj = self.Person.objects(name__regex=\"^[Guido].*[Rossum]$\").first()\n assert obj == person\n obj = self.Person.objects(name__regex=\"^[guido].*[rossum]$\").first()\n assert obj is None\n obj = self.Person.objects(name__regex=\"^[uido].*[Rossum]$\").first()\n assert obj is None\n\n # Test iregex\n obj = self.Person.objects(name__iregex=\"^[guido].*[rossum]$\").first()\n assert obj == person\n obj = self.Person.objects(name__iregex=\"^[Uido].*[Rossum]$\").first()\n assert obj is None\n\n # Test unsafe expressions\n person = self.Person(name=\"Guido van Rossum [.'Geek']\")\n person.save()\n\n obj = self.Person.objects(name__icontains=\"[.'Geek\").first()\n assert obj == person","def test_basic_av_by_tags_op_all(self):\n doc1 = Document.objects.create_document(\n title=\"doc1\",\n user=self.testcase_user,\n page_count=2,\n file_name=\"koko.pdf\",\n size='1111',\n lang='ENG',\n )\n doc2 = Document.objects.create_document(\n title=\"doc2\",\n user=self.testcase_user,\n page_count=2,\n file_name=\"kuku.pdf\",\n size='1111',\n lang='ENG',\n )\n doc3 = Document.objects.create_document(\n title=\"doc3\",\n user=self.testcase_user,\n page_count=2,\n file_name=\"momo.pdf\",\n size='1111',\n lang='ENG',\n )\n doc1.tags.add(\n \"green\",\n \"blue\",\n tag_kwargs={'user': self.testcase_user}\n )\n doc2.tags.add(\n \"blue\",\n tag_kwargs={'user': self.testcase_user}\n )\n doc3.tags.add(\n \"green\",\n \"blue\",\n \"red\",\n tag_kwargs={'user': self.testcase_user}\n )\n\n base_url = reverse('admin:search')\n args = \"tag=green&tag=blue&tags_op=all\"\n url = f\"{base_url}?{args}\"\n\n ret = self.client.get(url)\n\n self.assertEqual(\n ret.status_code,\n 200\n )\n self.assertEqual(\n len(ret.context['results_docs']),\n 2\n )\n result_ids = set(\n [doc_.id for doc_ in ret.context['results_docs']]\n )\n self.assertEqual(\n result_ids,\n set([doc1.id, doc3.id])\n )","def test_AlgorithmsHandler_GETORqueryfrom200Algorithms(self):\n query_string = 'displayName102 OR algorithmId23'\n upload_data_list = []\n create_test_algorithm_list(upload_data_list, 200)\n documents = []\n create_test_documents_list(upload_data_list, documents, 200)\n index = search.Index(name=search_algorithm._INDEX_STRING)\n index.put(documents)\n # end of data preparation\n numbers = ['23', '102']\n right_answer_list = []\n for number in numbers:\n data = {}\n data['algorithmId'] = 'algorithmId' + number\n data['algorithmSummary'] = 'algorithmSummary' + number\n data['displayName'] = 'displayName' + number\n data['linkURL'] = 'linkURL' + number\n right_answer_list.append(data)\n # end right answer list preparation\n response = self.testapp.get('/algorithms/?query=' + query_string)\n self.assertIsNotNone(response.charset)\n result = json.loads(response.normal_body.decode(encoding=response.charset))\n self.assertEqual(len(right_answer_list), len(result), msg='Wrong number of algorithms')\n self.assertItemsEqual(right_answer_list, result, msg='Discrepancy in returned algorithms')","def rest_of_ORF_unit_tests():\n input_a='ATTCATTAG'\n expected_output='ATTCAT'\n actual_output=rest_of_ORF(input_a)\n print 'Expected Output is ' + expected_output\n print 'Actual Output is ' +actual_output\n \n input_a='ATTCATCATCATCATTAG'\n expected_output='ATTCATCATCATCAT'\n actual_output=rest_of_ORF(input_a)\n print 'Expected Output is ' + expected_output\n print 'Actual Output is ' +actual_output","def test_list(self):\n pass","def test_list(self):\n pass","def test_all_group_by_op_fields(self):\n for field in OCIGroupBySerializer._opfields:\n field = \"and:\" + field\n filter_param = {field: [\"1\", \"2\"]}\n serializer = OCIGroupBySerializer(data=filter_param)\n self.assertTrue(serializer.is_valid())\n for field in OCIGroupBySerializer._opfields:\n field = \"or:\" + field\n filter_param = {field: [\"1\", \"2\"]}\n serializer = OCIGroupBySerializer(data=filter_param)\n self.assertTrue(serializer.is_valid())","def test_get_all(self, mock_helio_finder, mock_exists):\n static_paths = self.finder.find('path/to/component/component.ext', all=True)\n self.assertEqual(static_paths, ['MOCK_BASE_DIR/path/to/component/static/component.ext',\n 'MOCK_BASE_DIR_2/path/to/component/static/component.ext'])"],"string":"[\n \"def find_all_ORFs_both_strands_unit_tests():\\n\\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs_unit_tests():\\n print 'Begin Unit test Find_all_ORFs'\\n input_a='ATGCATGAATGTAGATGTAG'\\n expected_output='[ATGCATGAATGTAGATGTAG, ATGAATGTAGATGTAG, ATG, ATG]'\\n actual_output=find_all_ORFs(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\\n \\n input_a='ATGCATGAATGTAGATGCATCATTAG'\\n expected_output='[ATGCATGAATGTAGATGCATCATTAG, ATGAATGTAGATGCATCATTAG, ATG, ATGCATCAT]'\\n actual_output=find_all_ORFs(input_a)\\n print 'Expected Output is ' + expected_output\\n print \\\"actucal OUtput is\\\", actual_output\\n print 'ENd Unit test Find_all_ORFs'\",\n \"def find_all(self):\",\n \"def find_all(self):\\n pass\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n\\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs_unit_tests():\\n \\n input = [\\\"dna\\\"]\\n expected_output = [\\\"all non-nested ORFs\\\"]\\n actual = []\\n for k in input:\\n actual.append(find_all_ORFs(k))\\n print input \\n print actual\\n print expected_output\",\n \"def find_all_ORFs_unit_tests():\\n \\n print \\\"input: ATGCTA, \\\"+\\\"output: \\\"+ \\\",\\\".join(find_all_ORFs(\\\"ATGCTA\\\"))+\\\", actual output: CTA\\\"\\n print \\\"input: GTCACTTATGGGTTT, \\\"+\\\"output: \\\"+\\\",\\\".join(find_all_ORFs(\\\"ATGGATGCTTAGGGATGTTT\\\"))+\\\", actual output: GTCACT,GGTTTT,TCACTTAGGGTTTT,CACTTAGGGTTTT\\\"\\n print \\\"input: AAATTTTATAATGGGTGAAGTTAG, \\\"+\\\"output: \\\"+\\\",\\\".join(find_all_ORFs(\\\"AAATTTTATAATGGGTGAAGTTAG\\\"))+\\\", actual output: ATGGGTGAAGTT\\\"\\n print \\\"input: TATATGGAGGATAATAGTTGATAATAG, \\\"+\\\"output: \\\"+ \\\",\\\".join(find_all_ORFs(\\\"TATATGGAGGATAATAGTTGATAATAG\\\"))+\\\", actual output: ATGGAGGATAATAGT\\\"\",\n \"def test_otoroshi_controllers_adminapi_tcp_service_api_controller_find_all_entities_action(self):\\n pass\",\n \"def test_find_all(self):\\n result = Project.objects.find(['test'], project_type=None)\\n self.assertEqual(len(result), 2)\\n result = Project.objects.find(['ThisFails'], project_type=None)\\n self.assertEqual(len(result), 0)\",\n \"def find_all_ORFs(dna):\\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def test_search_or(self):\\n pkgs = [\\n make_package(factory=SQLPackage),\\n make_package(\\n \\\"somepackage\\\",\\n version=\\\"1.3\\\",\\n filename=\\\"mypath3\\\",\\n summary=\\\"this is mypkg\\\",\\n factory=SQLPackage,\\n ),\\n make_package(\\\"mypkg2\\\", \\\"1.3.4\\\", \\\"my/other/path\\\", factory=SQLPackage),\\n make_package(\\\"package\\\", factory=SQLPackage),\\n ]\\n for pkg in pkgs:\\n self.db.save(pkg)\\n criteria = {\\\"name\\\": [\\\"mypkg\\\"], \\\"summary\\\": [\\\"mypkg\\\"]}\\n packages = self.db.search(criteria, \\\"or\\\")\\n self.assertCountEqual(packages, pkgs[:-1])\",\n \"def find_all_ORFs_both_strands_unit_tests():\\n print ''\\n print 'Begin Unit test Find_all_ORFs both tests'\\n input_a='ATGCGAGGGTAGATGGATTAG'\\n expected_output='[ATGCGAGGG, ATGGAT]'\\n actual_output=find_all_ORFs_both_strands(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\\n \\n \\n input_a='ATGCGAATGTAGCATCAAATAGATGTAG'\\n expected_output='[ATGCGAATG, ATG, ATGCTACATTCGCAT]'\\n actual_output=find_all_ORFs_both_strands(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output \\n print 'end'\\n print ''\",\n \"def find_all_ORFs_unit_tests(dna, expected):\\n \\n print find_all_ORFs(\\\"ATGCATGAATGTAG\\\")\\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + find_all_ORFs(dna)\",\n \"def orfFinder(data):\\n\\t\\n\\tORFile = getORFs(data.seqFile, \\n\\t\\t\\t\\t\\t data.queryName, \\n\\t\\t\\t\\t\\t data.o)\\n\\tsetattr(data, \\\"ORFs\\\", ORFile)\",\n \"def test_search_or(self):\\n pkgs = [\\n make_package(factory=SQLPackage),\\n make_package(\\n \\\"somepackage\\\",\\n version=\\\"1.3\\\",\\n filename=\\\"mypath3\\\",\\n summary=\\\"this is mypkg\\\",\\n factory=SQLPackage,\\n ),\\n make_package(\\\"mypkg2\\\", \\\"1.3.4\\\", \\\"my/other/path\\\", factory=SQLPackage),\\n make_package(\\\"package\\\", factory=SQLPackage),\\n ]\\n self.sql.add_all(pkgs)\\n criteria = {\\\"name\\\": [\\\"mypkg\\\"], \\\"summary\\\": [\\\"mypkg\\\"]}\\n packages = self.db.search(criteria, \\\"or\\\")\\n self.assertCountEqual(packages, pkgs[:-1])\",\n \"def test_find_all(self):\\n # arrange\\n movie_id = MovieId('123')\\n character = character_random_with_movie_ids(MovieIds([movie_id]))\\n people = People([character])\\n movie = movie_random_with_movie_id_and_people(movie_id, people)\\n expected = Movies([movie])\\n\\n self.ghibli_client_mock__people([{'id': character.character_id, 'name': character.name,\\n 'gender': character.gender, 'age': character.age,\\n 'eye_color': character.eye_color, 'hair_color': character.hair_color,\\n 'films': [f'http://url/{movie_id}']}])\\n self.ghibli_client_mock__movies([{'id': movie_id, 'title': movie.title,\\n 'description': movie.description, 'director': movie.director,\\n 'producer': movie.producer, 'release_date': movie.release_date,\\n 'rt_score': movie.rt_score}])\\n\\n # act\\n repository = self.ghibli_movie_repository()\\n movies = repository.find_all()\\n\\n # assert\\n self.assertEqual(expected, movies)\",\n \"def test_search_or(self):\\n pkgs = [\\n make_package(factory=DynamoPackage),\\n make_package(\\n \\\"somepackage\\\",\\n version=\\\"1.3\\\",\\n filename=\\\"mypath3\\\",\\n summary=\\\"this is mypkg\\\",\\n factory=DynamoPackage,\\n ),\\n make_package(\\\"mypkg2\\\", \\\"1.3.4\\\", \\\"my/other/path\\\", factory=DynamoPackage),\\n make_package(\\\"package\\\", factory=DynamoPackage),\\n ]\\n self._save_pkgs(*pkgs)\\n criteria = {\\\"name\\\": [\\\"mypkg\\\"], \\\"summary\\\": [\\\"mypkg\\\"]}\\n packages = self.db.search(criteria, \\\"or\\\")\\n self.assertCountEqual(packages, pkgs[:-1])\",\n \"def test_find_all(self):\\n\\n # Test valid empty inputs\\n\\n self.assertEqual(find_all(None, None), [])\\n self.assertEqual(find_all('', None), [])\\n self.assertEqual(find_all(None, ''), [])\\n\\n self.assertEqual(find_all(b'', b''), [])\\n self.assertEqual(find_all(b'', ''), [])\\n\\n self.assertEqual(find_all('', b''), [])\\n self.assertEqual(find_all('', ''), [])\\n\\n # Test with missing or invalid inputs\\n\\n self.assertEqual(find_all('abc', '123'), [])\\n self.assertEqual(find_all('abc', 'abcabc'), [])\\n\\n self.assertEqual(find_all('abc', 'abc', limit=0), [])\\n self.assertEqual(find_all('abc', 'abc', limit=0, reverse=True), [])\\n self.assertEqual(find_all('abc', 'abc', limit=0, start=0, end=3), [])\\n self.assertEqual(find_all('abc', 'abc', limit=0, start=0, end=3, reverse=True), [])\\n\\n self.assertEqual(find_all('abc', 'abc', start=3, end=0), [])\\n self.assertEqual(find_all('abc', 'abc', start=3, end=0, limit=1), [])\\n self.assertEqual(find_all('abc', 'abc', start=3, end=0, reverse=True), [])\\n self.assertEqual(find_all('abc', 'abc', start=3, end=0, limit=1, reverse=True), [])\\n\\n # Test with valid, non-empty inputs\\n\\n self._test_find_all(\\n s='ab?cdef?ghijkl?mnopqrstuv?wxy?z?',\\n sub='?',\\n out=[2, 7, 14, 25, 29, 31]\\n )\\n self._test_find_all(\\n s='ab??cdef??ghijkl??mnopqrstuv??wxy??z??',\\n sub='??',\\n out=[2, 8, 16, 28, 33, 36]\\n )\\n self._test_find_all(\\n s='ab???cdef???ghijkl???mnopqrstuv???wxy???z???',\\n sub='???',\\n out=[2, 9, 18, 31, 37, 41]\\n )\",\n \"def find_all_ORFs_both_strands_unit_tests():\\n data_list = [\\n [\\\"ATGCGAATGTAGCATCAAA\\\", [\\\"ATGCGAATG\\\", \\\"ATGCTACATTCGCAT\\\"]],\\n [\\\"ATG\\\", [\\\"ATG\\\"]],\\n [\\\"CAT\\\", [\\\"ATG\\\"]],\\n [\\\"CATCAT\\\", [\\\"ATGATG\\\"]],\\n [\\\"CATGGGCAT\\\", [\\\"ATGGGCAT\\\", \\\"ATGCCCATG\\\"]],\\n [\\\"CATGCAGTGCACGGATGGCAT\\\", [\\\"ATGCAGTGCACGGATGGCAT\\\", \\\"ATGGCAT\\\", \\\"ATGCCATCCGTGCACTGCATG\\\"]],\\n# CATGCAGTGCACGGATGGCAT\\n# CAT GCA GTG CAC GGA TGG CAT\\n# ATG CAG TGC ACG GAT GGC AT\\n# TGC AGT GCA CGG ATG GCA T\\n# ATGCCATCCGTGCACTGCATG\\n# ATG CCA TCC GTG CAC TGC ATG\\n# TGC CAT CCG TGC ACT GCA TG\\n# GCC ATC CGT GCA CTG CAT G\\n [\\\"CATATGTAG\\\", [\\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGGGGCATCATTAG\\\", [\\\"ATGGGGCATCAT\\\", \\\"ATGATGCCCCAT\\\"]],\\n# ATGGGGCATCATTAG\\n# ATG GGG CAT CAT TAG\\n# TGG GGC ATC ATT AG\\n# GGG GCA TCA TTA G\\n# CTAATGATGCCCCAT\\n# CTA ATG ATG CCC CAT\\n# TAA TGA TGC CCC AT\\n# AAT GAT GCC CCA T\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\",\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = find_all_ORFs_both_strands(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def test_get_foods_search(self):\\n pass\",\n \"def test_all_finder_methods(self):\\n methods = ['all', 'first', 'find']\\n\\n for method in methods:\\n result = getattr(self.Test, method)\\n self.assertEqual(type(result).__name__, 'instancemethod')\\n self.assertEqual(result.im_class.__name__, 'Relation')\",\n \"def test_organization_all(self):\\n gryffindor = models.Organization(name='gryffindor')\\n ravenclaw = models.Organization(name='ravenclaw')\\n db.session.add(gryffindor)\\n db.session.add(ravenclaw)\\n db.session.commit()\\n # scenario 1: when neither buids nor names are given\\n self.assertEqual(models.Organization.all(), [])\\n # scenario 2: when buids are passed\\n orglist = [gryffindor, ravenclaw]\\n orgids = [gryffindor.buid, ravenclaw.buid]\\n all_by_buids = models.Organization.all(buids=orgids)\\n self.assertIsInstance(all_by_buids, list)\\n self.assertCountEqual(all_by_buids, orglist)\\n # scenario 3: when org names are passed\\n names = [gryffindor.name, ravenclaw.name]\\n all_by_names = models.Organization.all(names=names)\\n self.assertIsInstance(all_by_names, list)\\n self.assertCountEqual(all_by_names, orglist)\\n # scenario 4: when defercols is set to True for names\\n all_by_names_with_defercols = models.Organization.all(names=names)\\n self.assertIsInstance(all_by_names_with_defercols, list)\\n self.assertCountEqual(all_by_names_with_defercols, orglist)\\n # scenario 5: when defercols is set to True for buids\\n all_by_buids_with_defercols = models.Organization.all(buids=orgids)\\n self.assertIsInstance(all_by_buids_with_defercols, list)\\n self.assertCountEqual(all_by_buids_with_defercols, orglist)\",\n \"def test_all_documents(self):\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n\\n input = [\\\"dna\\\"]\\n expected_output = [\\\"all non-nester ORFs\\\"]\\n actual = []\\n for k in input:\\n actual.append(find_all_ORFs_oneframe(k))\\n print input \\n print actual\\n print expected_output\",\n \"def find_all(session=None):\\n return find(session=session)\",\n \"def test_retrieve_l_organizations(self):\\n pass\",\n \"def test_find(self):\\n user_a = self.Person.objects.create(name=\\\"User A\\\", age=20)\\n user_b = self.Person.objects.create(name=\\\"User B\\\", age=30)\\n\\n # Find all people in the collection\\n people = self.Person.objects\\n assert people.count() == 2\\n results = list(people)\\n\\n assert isinstance(results[0], self.Person)\\n assert isinstance(results[0].id, ObjectId)\\n\\n assert results[0] == user_a\\n assert results[0].name == \\\"User A\\\"\\n assert results[0].age == 20\\n\\n assert results[1] == user_b\\n assert results[1].name == \\\"User B\\\"\\n assert results[1].age == 30\\n\\n # Filter people by age\\n people = self.Person.objects(age=20)\\n assert people.count() == 1\\n person = next(people)\\n assert person == user_a\\n assert person.name == \\\"User A\\\"\\n assert person.age == 20\",\n \"def find_all_ORFs_both_strands(dna):\\n \\n # YOUR IMPLEMENTATION HERE\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n data_list = [\\n [\\\"ATGCATGAATGTAGATAGATGTGCCC\\\", [\\\"ATGCATGAATGTAGA\\\", \\\"ATGTGCCC\\\"]],\\n [\\\"ATGTAGATGTAG\\\", [\\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGATGATG\\\", [\\\"ATGATGATG\\\"]],\\n [\\\"ATGGGGGATTAGATGATG\\\", [\\\"ATGGGGGAT\\\", \\\"ATGATG\\\"]],\\n [\\\"ATGTGAATGTAA\\\", [\\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGTGAATGTAAATG\\\", [\\\"ATG\\\", \\\"ATG\\\", \\\"ATG\\\"]],\\n [\\\"ATGCGTGGTGATTAGATGGATGGGGATTGA\\\", [\\\"ATGCGTGGTGAT\\\", \\\"ATGGATGGGGAT\\\"]],\\n [\\\"ATGAAATTTCCCGGGAAATTTCCCGGG\\\", [\\\"ATGAAATTTCCCGGGAAATTTCCCGGG\\\"]],\\n [\\\"ATGAAATTTTGAATGGGGCCC\\\", [\\\"ATGAAATTT\\\", \\\"ATGGGGCCC\\\"]],\\n [\\\"ATGAAATTTTGAATGGGGCCCTAG\\\", [\\\"ATGAAATTT\\\", \\\"ATGGGGCCC\\\"]],\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\",\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = find_all_ORFs_oneframe(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def test_return_all(self):\\n self.data.return_all()\",\n \"def find_all_ORFs(dna):\\n ans = find_all_ORFs_oneframe(dna)\\n ans.extend(find_all_ORFs_oneframe(dna[1:]))\\n ans.extend(find_all_ORFs_oneframe(dna[2:]))\\n return ans\",\n \"def test_query_algorithms_ORqueryfrom200Algorithms(self):\\n query_string = 'displayName102 OR algorithmId23'\\n upload_data_list = []\\n create_test_algorithm_list(upload_data_list, 200)\\n documents = []\\n create_test_documents_list(upload_data_list, documents, 200)\\n index = search.Index(name=search_algorithm._INDEX_STRING)\\n index.put(documents)\\n # end of data preparation\\n numbers = ['23', '102']\\n right_answer_list = []\\n for number in numbers:\\n data = {}\\n data['algorithmId'] = 'algorithmId' + number\\n data['algorithmSummary'] = 'algorithmSummary' + number\\n data['displayName'] = 'displayName' + number\\n data['linkURL'] = 'linkURL' + number\\n right_answer_list.append(data)\\n # end right answer list preparation\\n result = search_algorithm.query_algorithms(index, query_string)\\n self.assertEqual(len(right_answer_list), len(result), msg='Wrong number of algorithms')\\n self.assertItemsEqual(right_answer_list, result, msg='Discrepancy in returned algorithms')\",\n \"def test_getorgs(self):\\n pass\",\n \"def test_status_find_all(session, result_count, model_class, enum_class):\\n results = model_class.find_all()\\n assert results\\n assert len(results) == result_count\\n for result in results:\\n assert result.status_type in enum_class\\n assert result.status_type_desc\\n assert result.legacy_status_type\",\n \"def find_all_ORFs(dna):\\n all_ORFs = []\\n i = 0\\n\\n for i in range (0,3): \\n all_ORFs.extend(find_all_ORFs_oneframe(dna))\\n dna = 'X' + dna\\n\\n return all_ORFs\",\n \"def test_find_multi_two(self):\\n result = Project.objects.find(['category', 'project'])\\n self.assertEqual(len(result), 2)\",\n \"def test_get_foods(self):\\n pass\",\n \"def test_searchCar(self):\\n make = \\\"Toyota\\\"\\n body_type = \\\"Seden\\\"\\n colour = \\\"Black\\\"\\n seats = \\\"5\\\"\\n cost_per_hour = \\\"10.5\\\"\\n booked = True\\n cars = db.session.query(Car).filter(or_(Car.make == make, \\n Car.body_type == body_type,\\n Car.colour == colour,\\n Car.seats == seats,\\n Car.cost_per_hour == cost_per_hour,\\n Car.booked == booked)).all()\\n self.assertTrue((cars is not None))\",\n \"def test_find_relation_types(self):\\n pass\",\n \"def test_organizations_list(self):\\n pass\",\n \"def test_get_list(self):\\n pass\",\n \"def test_get_records(self):\\n pass\",\n \"def test_search(self):\\n pass\",\n \"def test_search(self):\\n pass\",\n \"def test_search(self):\\n pass\",\n \"def test_fetch_all():\\n response = requests.get('http://localhost:5000/api/persons')\\n data = response.json()\\n\\n assert response.status_code == 200\\n for field in FIELDS:\\n assert field in data[0]\",\n \"def all(klass):\\n return klass.find()\",\n \"def find_all_ORFs(dna):\\n dnatwo = dna[1:]\\n dnathree = dna[2:]\\n all_ORFs = find_all_ORFs_oneframe(dna)\\n all_ORFs.extend(find_all_ORFs_oneframe(dnatwo))\\n all_ORFs.extend(find_all_ORFs_oneframe(dnathree))\\n if [] in all_ORFs:\\n all_ORFs.remove([])\\n return all_ORFs\",\n \"def object_finder(\\n self, datatable, objectlist, ralist, declist, radius,\\n longquery=True\\n ):\\n pass\",\n \"def test_organizations_read(self):\\n pass\",\n \"def test_find_multi_fields(self):\\n result = Project.objects.find(['project', 'xxx'])\\n self.assertEqual(len(result), 2)\",\n \"def rest_of_ORF_unit_tests():\\n data_list = [\\n [\\\"ATGTGAA\\\", \\\"ATG\\\"],\\n [\\\"ATGAGATAGG\\\", \\\"ATGAGA\\\"],\\n [\\\"ATG\\\", \\\"ATG\\\"],\\n [\\\"ATGTAG\\\", \\\"ATG\\\"],\\n [\\\"ATGTAA\\\", \\\"ATG\\\"],\\n [\\\"ATGTGA\\\", \\\"ATG\\\"],\\n [\\\"ATGAAATTTGGGAAATTTGGGTAG\\\", \\\"ATGAAATTTGGGAAATTTGGG\\\"],\\n [\\\"ATGAAATTTGGG\\\", \\\"ATGAAATTTGGG\\\"],\\n [\\\"ATGAGAAGGAAATTTGATGGGGATGGAAGATT\\\", \\\"ATGAGAAGGAAATTTGATGGGGATGGAAGATT\\\"],\\n [\\\"ATGAGAAGGAAATTTGATGGGGATGGAAGATAA\\\", \\\"ATGAGAAGGAAATTTGATGGGGATGGAAGA\\\"],\\n [\\\"ATGAA\\\", \\\"ATGAA\\\"],\\n [\\\"ATGATGATG\\\", \\\"ATGATGATG\\\"],\\n ]\\n for data in data_list:\\n if len(data) == 2:\\n print \\\"input: \\\" + str(data[0]) + \\\",\\\" ,\\n print \\\"expected output: \\\" + str(data[1]) + \\\",\\\",\\n o = rest_of_ORF(data[0])\\n print \\\"actual output: \\\" + str(o)\\n if o != data[1]:\\n print \\\"## Test Fail Here!\\\"\",\n \"def test_find_description_multi_two(self):\\n result = Project.objects.find(['xxx', 'yyy'], project_type=None)\\n self.assertEqual(len(result), 2)\",\n \"def test_get_foods_list(self):\\n pass\",\n \"def find_all_ORFs_oneframe_unit_tests():\\n input_a='ATGATTATTTGATGAATGGATTGA'\\n expected_output='[ATGATTATT,ATGGAT]'\\n actual_output=find_all_ORFs_oneframe(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\\n \\n input_a='ATGGGATTGTTT'\\n expected_output='[ATGGATTGTTT]'\\n actual_output=find_all_ORFs_oneframe(input_a)\\n print 'Expected Output is ' + expected_output\\n print actual_output\",\n \"def test_all():\\n assert(hasattr(tekel, '__all__'))\\n assert(isinstance(tekel.__all__, list))\\n assert(len(tekel.__all__) >= 0)\",\n \"def rest_of_ORF_unit_tests():\\n input = [\\\"dna\\\"]\\n expected_output = [\\\"rest of ORFs\\\"]\\n actual = []\\n for k in input:\\n actual.append(rest_of_ORF(k))\\n print input \\n print actual\\n print expected_output\",\n \"def test_xmlrpc_ir_model_search(self):\\n o = self.xmlrpc_object\\n db_name = common.get_db_name()\\n ids = o.execute(db_name, self.admin_uid, 'admin', 'ir.model', 'search', [])\\n self.assertIsInstance(ids, list)\\n ids = o.execute(db_name, self.admin_uid, 'admin', 'ir.model', 'search', [], {})\\n self.assertIsInstance(ids, list)\",\n \"def find_all_ORFs(dna):\\n all_ORFs=[]\\n for i in range (0,3):\\n \\tframe=dna[i:] \\n all_ORFs+=find_all_ORFs_oneframe(frame)\\n return all_ORFs\",\n \"def find_all_ORFs(dna):\\n all_ORFs = []\\n for i in range(0, 3):\\n dna_new = dna[i:]\\n all_ORFs += find_all_ORFs_oneframe(dna_new)\\n return all_ORFs\",\n \"def find_all(self, collection):\\n obj = getattr(self.db, collection)\\n result = obj.find()\\n return result\",\n \"def test_resource_user_resource_find_users_get(self):\\n pass\",\n \"def test_all_filter_op_fields(self):\\n for field in OCIFilterSerializer._opfields:\\n field = \\\"and:\\\" + field\\n filter_param = {field: [\\\"1\\\", \\\"2\\\"]}\\n serializer = OCIFilterSerializer(data=filter_param)\\n self.assertTrue(serializer.is_valid())\\n for field in OCIFilterSerializer._opfields:\\n field = \\\"or:\\\" + field\\n filter_param = {field: [\\\"1\\\", \\\"2\\\"]}\\n serializer = OCIFilterSerializer(data=filter_param)\\n self.assertTrue(serializer.is_valid())\",\n \"def test_query_all(test_store, andy, pandy, candy):\\n items = list(test_store.get_by())\\n assert len(items) == 3\\n assert andy in items\\n assert pandy in items\\n assert candy in items\",\n \"def find_all_ORFs_both_strands_unit_tests(dna, expected):\\n\\n print find_all_ORFs_both_strands(\\\"ATGCGAATGTAGCATCAAA\\\")\\n print \\\"input: \\\" + str(dna) + \\\", expected output: \\\" + str(expected) + \\\", actual output: \\\" + find_all_ORFs_both_strands(dna)\",\n \"def test_get_all(self):\\n\\n # Select on empty set\\n selected = self.user_api.get_all()\\n self.assertTrue(selected.success)\\n self.assertFalse(selected.documents)\\n\\n # Inserting several users\\n inserted = self.user_api.insert_user(MAGEN_USER)\\n self.assertTrue(inserted.success)\\n another_user = MAGEN_USER.copy()\\n another_user.pop('user_uuid')\\n another_user['username'] = 'test_another_username'\\n another_user['first_name'] = 'test_another_f_name'\\n inserted = self.user_api.insert_user(another_user)\\n self.assertTrue(inserted.success)\\n\\n # Select all users from Database\\n selected = self.user_api.get_all()\\n self.assertTrue(selected.success)\\n self.assertEqual(len(selected.documents), 2)\\n self.assertEqual(selected.documents[0], MAGEN_USER)\\n # Verify that user_uuid was generated\\n self.assertIn('user_uuid', selected.documents[1])\\n # Verify that other keys were inserted\\n self.assertEqual(selected.documents[1], another_user)\",\n \"def test_success_with_all_orgs(self):\\n auth_client = self.create_auth_client()\\n all_orgs = ListOrgSerializer(Org.objects.all(), many=True)\\n response = auth_client.get(self.search_org_api)\\n self.assertEqual(response.data, all_orgs.data)\",\n \"def find_all_ORFs(dna):\\n ORFs = find_all_ORFs_oneframe(dna) + find_all_ORFs_oneframe(dna[1:]) + find_all_ORFs_oneframe(dna[2:])\\n\\n return ORFs\",\n \"def test_get_parsed_files(self):\\n files = Historical_ROAs_Parser()._get_parsed_files()\\n with Historical_ROAs_Parsed_Table() as t:\\n for f in files:\\n sql = f\\\"SELECT * FROM {t.name} WHERE file = '{f}'\\\"\\n assert len(t.execute(sql)) == 1\",\n \"def test_apply_endorsements(self):\",\n \"def find_all_ORFs_both_strands_unit_tests():\\n print \\\"input: CTA, \\\"+\\\"output: \\\"+ \\\",\\\".join(find_all_ORFs_both_strands(\\\"CTA\\\"))+\\\", actual output: CTA,TA,A,AG,G\\\"\\n print \\\"input: GTCACTTAGGGTTTT, \\\"+\\\"output: \\\"+\\\",\\\".join(find_all_ORFs_both_strands(\\\"GTCACTTAGGGTTTT\\\"))+\\\", actual output: GTCACT,GGTTTT,TCACTTAGGGTTTT,CACTTAGGGTTTT,AAAACCCTAAGTGAC,AAACCC,GTGAC,AACCCTAAG\\\"\\n print \\\"input: AAATTTTATAATGGGTGAAGTTAG, \\\"+\\\"output: \\\"+\\\",\\\".join(find_all_ORFs_both_strands(\\\"AAATTTTATAATGGGTGAAGTTAG\\\"))+\\\", actual output: AAATTTTATAATGGG,AGT,AATTTTATAATGGGTGAAGTTAG,ATTTTA,TGGGTGAAGTTAG,CTAACTTCACCCATTATAAAATTT,CTTCACCCATTA,AATTT,AACTTCACCCATTATAAAATTT\\\"\\n print \\\"input: TATATGGAGGATAATAGTTGATAATAG, \\\"+\\\"output: \\\"+ \\\",\\\".join(find_all_ORFs_both_strands(\\\"TATATGGAGGATAATAGTTGATAATAG\\\"))+\\\", actual output: TATATGGAGGATAATAGT,ATATGGAGGATAATAGTTGATAATAG,TATGGAGGA,TTGATAATAG,CTATTATCAACTATTATCCTCCATATA,TATTATCAACTATTATCCTCCATATA,ATTATCAACTATTATCCTCCATATA\\\"\",\n \"def test_get_all_ordes(self):\\n test_client = app.test_client()\\n test_client.post('/api/v1/orders', data=json.dumps(dict(\\n order_number=\\\"order_number\\\", order_description=\\\"order_description\\\",\\n order_price=\\\"order_price\\\", size=\\\"size\\\")), content_type='application/json')\\n response = test_client.get('/api/v1/orders')\\n self.assertEqual(len(json.loads(response.data)), 1)\",\n \"def test_get_bios_unit_list(self):\\n pass\",\n \"def test_run_all_searches(): # ***Incomplete test\\n ##########################\\n # Arrange.\\n query_file_list = \\\"query_file_list\\\"\\n\\n ##########################\\n # Act.\\n #x = run_all_searches(query_file_list)\\n\\n ##########################\\n # Assert.\\n assert True == True # ***Temporary.\",\n \"def findall(cls, *lst, **dct):\\n query = cls.where(*lst, **dct).select()\\n result = query.execute()\\n return result.fetchall()\",\n \"def find_all():\\n return ItopapiPrototype.find_all(ItopapiOSLicence)\",\n \"def test_get_all_objects(self):\\n url = '/product/xml/'\\n response = self.client.get(url, **self.headers)\\n # Request should not be validated by a 401\\n self.failUnlessEqual(response.status_code, 401)\\n response = self.client.get(url, **self.advancedheaders)\\n # Request should be validated by a 200\\n self.failUnlessEqual(response.status_code, 200)\\n xml_response = parseString(response.content)\\n\\n product_tags =[elt for elt in xml_response.getElementsByTagName('object') if elt.getAttribute('model') == 'product.product']\\n # check that all product are displayed\\n self.failUnlessEqual(len(product_tags), Product.objects.count())\",\n \"def test_get_results(self):\\n pass\",\n \"def test_searchOr(self):\\n return self._messageSetSearchTest('OR 1 2', [1, 2])\",\n \"def test_get_list8(self):\\n pass\",\n \"def test_get_users(self):\\n pass\",\n \"def test_all(self):\\n self.assertEqual(type(self.vehicle_list), type([]))\\n [self.assertEqual(type(i), BusVehicle) for i in self.vehicle_list]\",\n \"def findAll(self) -> \\\"Stream<MatchResult>\\\":\\n raise NotImplementedError\",\n \"def test_execute(self):\\n self.mocked_cursor.fetchall.return_value = []\\n\\n db = database.Database()\\n result = db.execute(sql=\\\"SELECT * from FOO WHERE bar LIKE 'baz'\\\")\\n self.assertTrue(isinstance(result, list))\",\n \"def __call__(self, *args, **kwargs):\\r\\n return apply(self.findAll, args, kwargs)\",\n \"def test_everything(self):\\n\\n qs = FBO(\\n path=TEST_FILES_ROOT,\\n ).exclude(\\n name__glob='*~',\\n ).exclude(\\n name__glob='*.meta',\\n )\\n\\n self.assertEqual(\\n 7,\\n qs.count(),\\n )\\n self.assertEqual(\\n {\\n 'index.md',\\n 'subdir/index.md',\\n 'test1.md',\\n 'test2.md',\\n 'test1.rst',\\n 'test2.rst',\\n 'test3.rst',\\n },\\n {o.name for o in qs},\\n )\",\n \"def test_get_all_boats(self):\\n pass\",\n \"def test_get_insumo(self):\",\n \"def test_find_all_miss_cache(self):\\n # arrange\\n movie_id = MovieId('123')\\n character = character_random_with_movie_ids(MovieIds([movie_id]))\\n people = People([character])\\n movie = movie_random_with_movie_id_and_people(movie_id, people)\\n expected = Movies([movie])\\n self.movie_repository_mock__find_all(expected)\\n\\n # act\\n repository = self.cache_movie_repository_decorator()\\n response = repository.find_all()\\n\\n # assert\\n self.assertEqual(expected, response)\\n self.assertEqual(1, self.movie_repository_mock().find_all.call_count)\",\n \"def test_search_and(self):\\n pkgs = [\\n make_package(factory=SQLPackage),\\n make_package(\\n \\\"somepackage\\\",\\n version=\\\"1.3\\\",\\n filename=\\\"mypath3\\\",\\n summary=\\\"this is mypkg\\\",\\n factory=SQLPackage,\\n ),\\n make_package(\\\"mypkg2\\\", \\\"1.3.4\\\", \\\"my/other/path\\\", factory=SQLPackage),\\n make_package(\\\"package\\\", factory=SQLPackage),\\n ]\\n for pkg in pkgs:\\n self.db.save(pkg)\\n criteria = {\\\"name\\\": [\\\"my\\\", \\\"pkg\\\"], \\\"summary\\\": [\\\"this\\\", \\\"mypkg\\\"]}\\n packages = self.db.search(criteria, \\\"and\\\")\\n self.assertCountEqual(packages, pkgs[:-1])\",\n \"def test_ipam_rirs_list(self):\\n pass\",\n \"def find_all_ORFs(dna):\\n index = 0\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# initialize index\\n all_ORFs = []\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# intitalize empty list\\n while index < 3:\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# switches throught the 3 frames\\n \\tall_ORFs = all_ORFs + find_all_ORFs_oneframe(dna[index:])\\t# adds all ORFs oneframe to the list\\n \\tindex += 1\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# indexes +1\\n return all_ORFs \\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t# returns list of all ORFs in all 3 frames\",\n \"def test_regex_query_shortcuts(self):\\n person = self.Person(name=\\\"Guido van Rossum\\\")\\n person.save()\\n\\n # Test contains\\n obj = self.Person.objects(name__contains=\\\"van\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__contains=\\\"Van\\\").first()\\n assert obj is None\\n\\n # Test icontains\\n obj = self.Person.objects(name__icontains=\\\"Van\\\").first()\\n assert obj == person\\n\\n # Test startswith\\n obj = self.Person.objects(name__startswith=\\\"Guido\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__startswith=\\\"guido\\\").first()\\n assert obj is None\\n\\n # Test istartswith\\n obj = self.Person.objects(name__istartswith=\\\"guido\\\").first()\\n assert obj == person\\n\\n # Test endswith\\n obj = self.Person.objects(name__endswith=\\\"Rossum\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__endswith=\\\"rossuM\\\").first()\\n assert obj is None\\n\\n # Test iendswith\\n obj = self.Person.objects(name__iendswith=\\\"rossuM\\\").first()\\n assert obj == person\\n\\n # Test exact\\n obj = self.Person.objects(name__exact=\\\"Guido van Rossum\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__exact=\\\"Guido van rossum\\\").first()\\n assert obj is None\\n obj = self.Person.objects(name__exact=\\\"Guido van Rossu\\\").first()\\n assert obj is None\\n\\n # Test iexact\\n obj = self.Person.objects(name__iexact=\\\"gUIDO VAN rOSSUM\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__iexact=\\\"gUIDO VAN rOSSU\\\").first()\\n assert obj is None\\n\\n # Test wholeword\\n obj = self.Person.objects(name__wholeword=\\\"Guido\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__wholeword=\\\"rossum\\\").first()\\n assert obj is None\\n obj = self.Person.objects(name__wholeword=\\\"Rossu\\\").first()\\n assert obj is None\\n\\n # Test iwholeword\\n obj = self.Person.objects(name__iwholeword=\\\"rOSSUM\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__iwholeword=\\\"rOSSU\\\").first()\\n assert obj is None\\n\\n # Test regex\\n obj = self.Person.objects(name__regex=\\\"^[Guido].*[Rossum]$\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__regex=\\\"^[guido].*[rossum]$\\\").first()\\n assert obj is None\\n obj = self.Person.objects(name__regex=\\\"^[uido].*[Rossum]$\\\").first()\\n assert obj is None\\n\\n # Test iregex\\n obj = self.Person.objects(name__iregex=\\\"^[guido].*[rossum]$\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__iregex=\\\"^[Uido].*[Rossum]$\\\").first()\\n assert obj is None\\n\\n # Test unsafe expressions\\n person = self.Person(name=\\\"Guido van Rossum [.'Geek']\\\")\\n person.save()\\n\\n obj = self.Person.objects(name__icontains=\\\"[.'Geek\\\").first()\\n assert obj == person\",\n \"def test_basic_av_by_tags_op_all(self):\\n doc1 = Document.objects.create_document(\\n title=\\\"doc1\\\",\\n user=self.testcase_user,\\n page_count=2,\\n file_name=\\\"koko.pdf\\\",\\n size='1111',\\n lang='ENG',\\n )\\n doc2 = Document.objects.create_document(\\n title=\\\"doc2\\\",\\n user=self.testcase_user,\\n page_count=2,\\n file_name=\\\"kuku.pdf\\\",\\n size='1111',\\n lang='ENG',\\n )\\n doc3 = Document.objects.create_document(\\n title=\\\"doc3\\\",\\n user=self.testcase_user,\\n page_count=2,\\n file_name=\\\"momo.pdf\\\",\\n size='1111',\\n lang='ENG',\\n )\\n doc1.tags.add(\\n \\\"green\\\",\\n \\\"blue\\\",\\n tag_kwargs={'user': self.testcase_user}\\n )\\n doc2.tags.add(\\n \\\"blue\\\",\\n tag_kwargs={'user': self.testcase_user}\\n )\\n doc3.tags.add(\\n \\\"green\\\",\\n \\\"blue\\\",\\n \\\"red\\\",\\n tag_kwargs={'user': self.testcase_user}\\n )\\n\\n base_url = reverse('admin:search')\\n args = \\\"tag=green&tag=blue&tags_op=all\\\"\\n url = f\\\"{base_url}?{args}\\\"\\n\\n ret = self.client.get(url)\\n\\n self.assertEqual(\\n ret.status_code,\\n 200\\n )\\n self.assertEqual(\\n len(ret.context['results_docs']),\\n 2\\n )\\n result_ids = set(\\n [doc_.id for doc_ in ret.context['results_docs']]\\n )\\n self.assertEqual(\\n result_ids,\\n set([doc1.id, doc3.id])\\n )\",\n \"def test_AlgorithmsHandler_GETORqueryfrom200Algorithms(self):\\n query_string = 'displayName102 OR algorithmId23'\\n upload_data_list = []\\n create_test_algorithm_list(upload_data_list, 200)\\n documents = []\\n create_test_documents_list(upload_data_list, documents, 200)\\n index = search.Index(name=search_algorithm._INDEX_STRING)\\n index.put(documents)\\n # end of data preparation\\n numbers = ['23', '102']\\n right_answer_list = []\\n for number in numbers:\\n data = {}\\n data['algorithmId'] = 'algorithmId' + number\\n data['algorithmSummary'] = 'algorithmSummary' + number\\n data['displayName'] = 'displayName' + number\\n data['linkURL'] = 'linkURL' + number\\n right_answer_list.append(data)\\n # end right answer list preparation\\n response = self.testapp.get('/algorithms/?query=' + query_string)\\n self.assertIsNotNone(response.charset)\\n result = json.loads(response.normal_body.decode(encoding=response.charset))\\n self.assertEqual(len(right_answer_list), len(result), msg='Wrong number of algorithms')\\n self.assertItemsEqual(right_answer_list, result, msg='Discrepancy in returned algorithms')\",\n \"def rest_of_ORF_unit_tests():\\n input_a='ATTCATTAG'\\n expected_output='ATTCAT'\\n actual_output=rest_of_ORF(input_a)\\n print 'Expected Output is ' + expected_output\\n print 'Actual Output is ' +actual_output\\n \\n input_a='ATTCATCATCATCATTAG'\\n expected_output='ATTCATCATCATCAT'\\n actual_output=rest_of_ORF(input_a)\\n print 'Expected Output is ' + expected_output\\n print 'Actual Output is ' +actual_output\",\n \"def test_list(self):\\n pass\",\n \"def test_list(self):\\n pass\",\n \"def test_all_group_by_op_fields(self):\\n for field in OCIGroupBySerializer._opfields:\\n field = \\\"and:\\\" + field\\n filter_param = {field: [\\\"1\\\", \\\"2\\\"]}\\n serializer = OCIGroupBySerializer(data=filter_param)\\n self.assertTrue(serializer.is_valid())\\n for field in OCIGroupBySerializer._opfields:\\n field = \\\"or:\\\" + field\\n filter_param = {field: [\\\"1\\\", \\\"2\\\"]}\\n serializer = OCIGroupBySerializer(data=filter_param)\\n self.assertTrue(serializer.is_valid())\",\n \"def test_get_all(self, mock_helio_finder, mock_exists):\\n static_paths = self.finder.find('path/to/component/component.ext', all=True)\\n self.assertEqual(static_paths, ['MOCK_BASE_DIR/path/to/component/static/component.ext',\\n 'MOCK_BASE_DIR_2/path/to/component/static/component.ext'])\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7691884","0.7465497","0.71547097","0.7034157","0.70336044","0.70111084","0.6656426","0.659269","0.65738535","0.6469719","0.6363958","0.6361521","0.6306454","0.6261688","0.62254024","0.6223877","0.6080115","0.6066479","0.6003871","0.597892","0.5960407","0.59191275","0.5915954","0.5915246","0.58373195","0.5802463","0.5785651","0.5735543","0.5734048","0.57339126","0.5708311","0.5687429","0.56869453","0.5671601","0.56715626","0.56513613","0.5628807","0.56273586","0.56145847","0.55912715","0.5580996","0.5573787","0.5569422","0.5569422","0.5569422","0.55507505","0.55382115","0.5531756","0.55264395","0.5523729","0.5503734","0.5502875","0.54956657","0.5481293","0.54785085","0.54774153","0.5464534","0.54643697","0.54575473","0.5450368","0.5439175","0.5436585","0.5434885","0.54209226","0.5414837","0.54140496","0.5403506","0.53973264","0.5388031","0.53873867","0.53788453","0.5372047","0.536443","0.536339","0.53604317","0.53527474","0.5350856","0.5342783","0.53381675","0.53306055","0.5313819","0.53088903","0.53074396","0.5290829","0.5287938","0.52864766","0.5283305","0.5279048","0.5269778","0.52694577","0.5261803","0.5259699","0.52580976","0.5247976","0.5245323","0.5243442","0.5239951","0.5239951","0.5230862","0.5229168"],"string":"[\n \"0.7691884\",\n \"0.7465497\",\n \"0.71547097\",\n \"0.7034157\",\n \"0.70336044\",\n \"0.70111084\",\n \"0.6656426\",\n \"0.659269\",\n \"0.65738535\",\n \"0.6469719\",\n \"0.6363958\",\n \"0.6361521\",\n \"0.6306454\",\n \"0.6261688\",\n \"0.62254024\",\n \"0.6223877\",\n \"0.6080115\",\n \"0.6066479\",\n \"0.6003871\",\n \"0.597892\",\n \"0.5960407\",\n \"0.59191275\",\n \"0.5915954\",\n \"0.5915246\",\n \"0.58373195\",\n \"0.5802463\",\n \"0.5785651\",\n \"0.5735543\",\n \"0.5734048\",\n \"0.57339126\",\n \"0.5708311\",\n \"0.5687429\",\n \"0.56869453\",\n \"0.5671601\",\n \"0.56715626\",\n \"0.56513613\",\n \"0.5628807\",\n \"0.56273586\",\n \"0.56145847\",\n \"0.55912715\",\n \"0.5580996\",\n \"0.5573787\",\n \"0.5569422\",\n \"0.5569422\",\n \"0.5569422\",\n \"0.55507505\",\n \"0.55382115\",\n \"0.5531756\",\n \"0.55264395\",\n \"0.5523729\",\n \"0.5503734\",\n \"0.5502875\",\n \"0.54956657\",\n \"0.5481293\",\n \"0.54785085\",\n \"0.54774153\",\n \"0.5464534\",\n \"0.54643697\",\n \"0.54575473\",\n \"0.5450368\",\n \"0.5439175\",\n \"0.5436585\",\n \"0.5434885\",\n \"0.54209226\",\n \"0.5414837\",\n \"0.54140496\",\n \"0.5403506\",\n \"0.53973264\",\n \"0.5388031\",\n \"0.53873867\",\n \"0.53788453\",\n \"0.5372047\",\n \"0.536443\",\n \"0.536339\",\n \"0.53604317\",\n \"0.53527474\",\n \"0.5350856\",\n \"0.5342783\",\n \"0.53381675\",\n \"0.53306055\",\n \"0.5313819\",\n \"0.53088903\",\n \"0.53074396\",\n \"0.5290829\",\n \"0.5287938\",\n \"0.52864766\",\n \"0.5283305\",\n \"0.5279048\",\n \"0.5269778\",\n \"0.52694577\",\n \"0.5261803\",\n \"0.5259699\",\n \"0.52580976\",\n \"0.5247976\",\n \"0.5245323\",\n \"0.5243442\",\n \"0.5239951\",\n \"0.5239951\",\n \"0.5230862\",\n \"0.5229168\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6763755"},"document_rank":{"kind":"string","value":"6"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":929,"numItemsPerPage":100,"numTotalItems":95772,"offset":92900,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6IjVHZDBvd0g5MTM2eDZjc1FvbE1zcktNWUZoRVFoUm5PVVVybEpjOUhaUEEifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc4NTU2MDgwMCwianRpIjoiYWM1OTU4YjMtZTAxNC00YzVhLWI4MzYtZDBmNWYyYzBlY2ExIiwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3ODU1NjQ0MDAsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.E7Q17IqusndSCEixO3RtLuq8ZkjZWPuX1wqEyA0JmmB66-12WIDv3_qpbOQ5qkuTzw70l1Y2ldZ4mNrdolcIDQ","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":95772,"numBytesParquet":1928375891}]},"discussionsStats":{"closed":1,"open":1,"total":2},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
Sample from model predictions, and evaluate outputs | def evaluate(self, model_idx,
max_eval_batches=None,
write_results=False,
write_to_summary=True):
# write_summary needs global_step
self._step_collections["GlobalStep"] = (
self._sess.run(self._global_step_tensor))
# evalua... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def evaluate(model, test_files):\n print(\"Running predictions.\")\n models = load_model(model)\n predictions = predict(models, test_files)\n\n # # write predictions to file\n # write_predictions(\"evaluate_out.json\",predictions)\n evaluate_individual(predictions, test_files, models)\n evalua... | [
"0.7101722",
"0.69548494",
"0.6852271",
"0.68520606",
"0.674203",
"0.6641309",
"0.6640077",
"0.6571293",
"0.6543363",
"0.6491229",
"0.64878094",
"0.64876974",
"0.6486447",
"0.6455267",
"0.6448493",
"0.6428464",
"0.6425249",
"0.64173007",
"0.6415146",
"0.64122653",
"0.64120877... | 0.0 | -1 |
BiLSTM with max pooling, but ignore sequence_2 | def _build_single_stream_model(self,
data,
embedding_fn,
encoder_fn_1,
encoder_fn_2,
logits_fn):
# Build the Model
# ---... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Bilstm(self):\n # Model.\n model = Sequential()\n # model.add(Bidirectional(LSTM(2048, return_sequences=True),input_shape=self.input_shape))\n # model.add(Bidirectional(LSTM(2048))) id identification is 2048\n model.add(Bidirectional(LSTM(2048, return_sequences=True), input_... | [
"0.65396965",
"0.61001",
"0.5983156",
"0.59826714",
"0.59388393",
"0.5922987",
"0.5872958",
"0.581099",
"0.5691466",
"0.565373",
"0.5635273",
"0.56306946",
"0.557437",
"0.5521328",
"0.5492911",
"0.5480712",
"0.54760426",
"0.54644793",
"0.5460992",
"0.54517883",
"0.5438166",
... | 0.0 | -1 |
BiLSTM with max pooling from | def _build_dual_stream_model(self,
data,
embedding_fn,
encoder_fn_1,
encoder_fn_2,
logits_fn):
# Build the Model
# ------------------------... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Bilstm(self):\n # Model.\n model = Sequential()\n # model.add(Bidirectional(LSTM(2048, return_sequences=True),input_shape=self.input_shape))\n # model.add(Bidirectional(LSTM(2048))) id identification is 2048\n model.add(Bidirectional(LSTM(2048, return_sequences=True), input_... | [
"0.6490568",
"0.6294879",
"0.6215612",
"0.61869",
"0.6159668",
"0.6138382",
"0.61137885",
"0.60936844",
"0.60936844",
"0.6069494",
"0.6038459",
"0.60350174",
"0.6011682",
"0.60092825",
"0.6007879",
"0.6004979",
"0.6004979",
"0.6004979",
"0.5997644",
"0.59830004",
"0.594934",
... | 0.0 | -1 |
Run python version inside of a docker image and get its semantic version number. | def get_python_version(self, dock_image: str) -> str:
# version string typically looks like: "Python 3.9.2"
# But other variations exist such as: "Python 3.6.9 :: Anaconda, Inc."
# and for whatever reason, the conda version prints to stderr instead...
python_version_string: str = check_o... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def _get_python_version(user_image, python_binary) -> packaging.version.Version:\n\n proc = await asyncio.create_subprocess_exec(\n \"docker\",\n \"run\",\n \"--rm\",\n user_image,\n python_binary,\n \"--version\",\n stdout=subprocess.PIPE,\n stderr=... | [
"0.7416897",
"0.6631516",
"0.6582976",
"0.65689105",
"0.65503365",
"0.6505324",
"0.6406864",
"0.6402115",
"0.6245161",
"0.62432474",
"0.62357765",
"0.6217067",
"0.6191909",
"0.613984",
"0.6055866",
"0.6053228",
"0.5995903",
"0.5990503",
"0.5981206",
"0.59631395",
"0.59099054"... | 0.67462885 | 1 |
Attempt to find the resource directory for the python package of the ChRIS plugin. It usually looks like /usr/local/lib/python3.9/sitepackages/something If unsuccessful, return empty string. | def find_resource_dir(self, dock_image: str, meta: dict) -> str:
try:
return self.interrogate_python_package_location(dock_image, meta)
except CalledProcessError:
return '' | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_resource(self, rsc_path):\n\n\t\ttry:\n\t\t\tfrom pkg_resources import resource_filename\n\t\t\treturn resource_filename(__name__, rsc_path)\n\t\texcept ImportError:\n\t\t\treturn os.path.join(os.path.dirname(__file__), rsc_path)",
"def get_package_dir():\n return Path(__file__).parent",
"def _get_d... | [
"0.6721056",
"0.6668326",
"0.6601748",
"0.6568538",
"0.6526997",
"0.64291966",
"0.63636035",
"0.63410276",
"0.62239856",
"0.6217715",
"0.6213123",
"0.6172258",
"0.6157969",
"0.61543185",
"0.613424",
"0.61182326",
"0.60999566",
"0.6063436",
"0.6055837",
"0.60502505",
"0.604980... | 0.70710635 | 0 |
Generate a shell script for running a dockerized ChRIS plugin. | def compile_plugin(self, dock_image: str, linking='dynamic') -> str:
if linking not in ['static', 'dynamic']:
raise ValueError('linking must be either "static" or "dynamic"')
api = ShellBuilderApi(self.config)
engine = api.engine()
info = PythonImageInfo(engine)
# TO... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def docker_sh():\n docker_exec('/bin/bash')",
"def dockerfile() -> co.Exec:\n image = co.Image(dockerfile=\"./docker/Dockerfile.simple\")\n return co.Exec(\n f\"python -c '{pretty_table_script}'\", image=image, doc=co.util.magic_doc()\n )",
"def docker_build(c):\n cli_tasks.docker_build.r... | [
"0.5865527",
"0.5817266",
"0.5726802",
"0.56655383",
"0.56499326",
"0.56055737",
"0.5604115",
"0.55538315",
"0.554898",
"0.5518906",
"0.54707164",
"0.546558",
"0.5464381",
"0.5380448",
"0.5358491",
"0.5346705",
"0.5340719",
"0.5312728",
"0.53005457",
"0.52647114",
"0.5260788"... | 0.52670395 | 19 |
Same as get_plugin_cmd but if unsuccessful, print some advice and exit. | def test_the_waters(self, dock_image: str):
engine = ShellBuilderApi(self.config).engine()
try:
return PythonImageInfo(engine).get_plugin_cmd(dock_image)
except PluginMetaLookupError as e:
print('Failed to get plugin meta', end=': ')
print(e)
prin... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_specific_plugin_not_installed(self):\n self._add_plugin(self.jigconfig, 'plugin01')\n set_jigconfig(self.gitrepodir, config=self.jigconfig)\n\n # Create staged\n self.commit(self.gitrepodir, 'a.txt', 'a')\n self.stage(self.gitrepodir, 'b.txt', 'b')\n\n with nested... | [
"0.65437466",
"0.62526155",
"0.619401",
"0.6043565",
"0.5989061",
"0.59795517",
"0.5834357",
"0.57178366",
"0.5651055",
"0.5617419",
"0.5535857",
"0.5530768",
"0.55039674",
"0.5490266",
"0.5488291",
"0.54774445",
"0.54476714",
"0.5432186",
"0.5428482",
"0.5412004",
"0.5407408... | 0.0 | -1 |
Script to clean a given case. | def main():
args = read_inputs()
Case(args.path)
print 'case path: %s' % Case.path
print '[info]: cleaning mesh and force coefficients'
os.system('rm -f '+Case.path+'/*.dat')
print '[info]: cleaning solution folders'
for i in xrange(10):
os.system('rm -rf '+Case.path+'/'+str(i)+'*')
print '[info]: cleanin... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def clean(c):",
"def RemoveCase(dirc):\n if os.path.exists(dirc):\n shutil.rmtree(dirc)\n #subprocess.call(['rm', '-r', dirc])",
"def clean(_context):",
"def hxlclean():\n run_script(hxlclean_main)",
"async def clearcases(self, ctx, problem_name):\n if not await problem_exists(ctx, p... | [
"0.6394602",
"0.6388809",
"0.5800998",
"0.56710964",
"0.56026864",
"0.5589458",
"0.5588989",
"0.55696267",
"0.55633765",
"0.55631894",
"0.55501896",
"0.5522124",
"0.5501598",
"0.54972",
"0.543099",
"0.53682435",
"0.530929",
"0.53045577",
"0.52781314",
"0.52335",
"0.5228231",
... | 0.669353 | 0 |
Remove a file or a directory. | def remove(src):
if os.path.isfile(src):
os.remove(src)
elif os.path.isdir(src):
shutil.rmtree(src) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def remove(file_or_dirname: str):\n if osp.exists(file_or_dirname):\n if osp.isdir(file_or_dirname):\n shutil.rmtree(file_or_dirname, ignore_errors=True)\n if osp.isfile(file_or_dirname):\n os.remove(file_or_dirname)",
"def remove(path):\n if os.path.isdir(path):\n ... | [
"0.7849267",
"0.78304523",
"0.7714936",
"0.7685656",
"0.7685656",
"0.7676818",
"0.7676818",
"0.7666824",
"0.76544356",
"0.7637967",
"0.76119035",
"0.7565476",
"0.7549089",
"0.7525484",
"0.75132424",
"0.75080544",
"0.7471931",
"0.74607474",
"0.731739",
"0.7316478",
"0.730325",... | 0.74683315 | 17 |
Copy a file or directory to a future destination. | def copy(src, dst, ignore=False, force=False):
if not os.path.exists(src) and not ignore:
raise FileNotFoundError("'%s' is not found." % src)
if os.path.isfile(src):
if os.path.exists(dst):
if not ignore and not force:
raise FileExistsError("'%s' is exist." % dst)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _copy_file ( self, source, dest ):\n return",
"def copyfile(self, destination, **kwargs):\n assert _os.path.isfile(self.__str__()) == True\n _shutil.copyfile(self.__str__(), destination, **kwargs)",
"def cp(self, src, dest):\r\n return self._call(\"-cp\", src, dest, suppress_output=Tr... | [
"0.73302346",
"0.70401216",
"0.6996331",
"0.6920589",
"0.6886142",
"0.67921764",
"0.6729284",
"0.66975254",
"0.66690886",
"0.66571426",
"0.66570395",
"0.6654941",
"0.66509396",
"0.6587886",
"0.658738",
"0.6567847",
"0.65257835",
"0.65162915",
"0.6507118",
"0.649342",
"0.64763... | 0.0 | -1 |
Move a file or directory to a future destination. | def move(src, dst, ignore=False, force=False):
copy(src, dst, ignore, force)
remove(src) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def move_file(source, destination):\n shutil.move(source, destination)",
"def move_file(self, path: PathLike, dest: PathLike, force: bool = False):",
"def move(self, destination, **kwargs):\n assert _os.path.exists(self.__str__()) == True\n _shutil.move(self.__str__(), destination, **kwargs)",... | [
"0.74208075",
"0.7298211",
"0.70145404",
"0.69194704",
"0.68873274",
"0.6720547",
"0.66964126",
"0.6631833",
"0.66137534",
"0.6604414",
"0.65643126",
"0.6534053",
"0.65298843",
"0.6515625",
"0.6511343",
"0.64865124",
"0.6470165",
"0.64249253",
"0.6424211",
"0.64221215",
"0.64... | 0.6062482 | 41 |
Create a new API class for your application. 'root' shoudl be your base route, and routes is a mapping of routeshortname > path suffix for your API. | def API(root, **routes):
# this creats a dict of properties that create Senders for
# all the friendly name --> suffix combidantions passed in
props = {'root': Route(root)}
for (short, path) in routes.iteritems():
props[short] = lambda self, content: self.sender.send_path(path, content)
re... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_app():\r\n app = Flask(__name__, instance_relative_config=False)\r\n app.config.from_object('config.Config') \r\n \r\n api = Api(app) \r\n \r\n with app.app_context():\r\n from .flights import TicketRoute, FlightRoute\r\n api.add_resource(TicketRoute,\"/api/ticket... | [
"0.73801404",
"0.7200694",
"0.71829164",
"0.6970352",
"0.671085",
"0.67097706",
"0.67093503",
"0.6705557",
"0.6694073",
"0.66517067",
"0.6583034",
"0.6547196",
"0.64564484",
"0.64072907",
"0.6406355",
"0.6401527",
"0.63456136",
"0.63084906",
"0.62602186",
"0.6221953",
"0.6214... | 0.75148106 | 0 |
function to patch over exit_json; package return data into an exception | def exit_json(*args, **kwargs):
if 'changed' not in kwargs:
kwargs['changed'] = False
raise AnsibleExitJson(kwargs) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_cli_format_error_handler_broken_json():\n resp = MagicMock()\n resp.json.side_effect = ValueError(\"\")\n resp.text = \"Not JSON\"\n output = format_utils.cli_format_error_handler(resp)\n assert 'Error: Unable to decode response. Value: Not JSON' in output",
"def test_cli_format_error_han... | [
"0.6422005",
"0.6011262",
"0.58930314",
"0.5873814",
"0.5736965",
"0.5635676",
"0.55465096",
"0.5507798",
"0.55060387",
"0.5482061",
"0.54793316",
"0.547902",
"0.54240453",
"0.5421341",
"0.5397868",
"0.539718",
"0.53748244",
"0.53737676",
"0.5362257",
"0.53568584",
"0.5345366... | 0.70887923 | 0 |
function to patch over fail_json; package return data into an exception | def fail_json(*args, **kwargs):
kwargs['failed'] = True
raise AnsibleFailJson(kwargs) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_cli_format_error_handler_broken_json():\n resp = MagicMock()\n resp.json.side_effect = ValueError(\"\")\n resp.text = \"Not JSON\"\n output = format_utils.cli_format_error_handler(resp)\n assert 'Error: Unable to decode response. Value: Not JSON' in output",
"def process_json(self, data):... | [
"0.7065039",
"0.6566227",
"0.655377",
"0.6433542",
"0.6402148",
"0.6363974",
"0.63553065",
"0.63401806",
"0.62943906",
"0.6246136",
"0.6231559",
"0.62160605",
"0.6212979",
"0.61676127",
"0.6163638",
"0.6131823",
"0.60966325",
"0.6095224",
"0.60862505",
"0.60569715",
"0.604183... | 0.71612245 | 0 |
prepare arguments so that they will be picked up during module creation | def set_module_args(args):
args = json.dumps({'ANSIBLE_MODULE_ARGS': args})
basic._ANSIBLE_ARGS = to_bytes(args) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def prepare_arguments(self, parser):\n pass",
"def _prepare(self):\n # Customize commandline arguments\n parser = argparse.ArgumentParser()\n self.initArgumentParser(parser, defaults=self.default_binding_overrides)\n self.__options = parser.parse_args()\n self.__bindings.update(args_util.pa... | [
"0.76967007",
"0.71010435",
"0.6964001",
"0.6887841",
"0.669962",
"0.6676757",
"0.657058",
"0.6560541",
"0.6521241",
"0.6517541",
"0.65066904",
"0.64621484",
"0.6457191",
"0.6456913",
"0.6422021",
"0.631883",
"0.6316088",
"0.63051707",
"0.63043374",
"0.6299369",
"0.6293147",
... | 0.6311913 | 17 |
Create a new yard. | def __init__(self, name: str) -> None:
logger.debug(f'Executing Yard __init__ with name:{name}')
self._name = name | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create(request: YardRequestCreate) -> Yard:\n logger.debug(f'Executing Yard create with request:{request}')\n return Yard(request.name)",
"def __init__(self, name: str, yard_id: Optional[int] = None) -> None:\n self._name = name\n if yard_id:\n self._yard_id = yard_id",... | [
"0.7494531",
"0.568594",
"0.5662496",
"0.56039697",
"0.56039697",
"0.54037803",
"0.53043294",
"0.52780956",
"0.5270102",
"0.5120752",
"0.5120752",
"0.5120752",
"0.5114537",
"0.510326",
"0.50686073",
"0.50561523",
"0.502217",
"0.5009028",
"0.49991226",
"0.4990616",
"0.49758244... | 0.52229035 | 9 |
Return a new yard. | def create(request: YardRequestCreate) -> Yard:
logger.debug(f'Executing Yard create with request:{request}')
return Yard(request.name) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_rythm(self, dev):\n new_rythm = rythm.Rythm()\n new_rythm.rythm_from_distr(duration, self.density)\n\n return new_rythm",
"def __init__(self, name: str, yard_id: Optional[int] = None) -> None:\n self._name = name\n if yard_id:\n self._yard_id = yard_id",
... | [
"0.5590437",
"0.54014885",
"0.5362551",
"0.53325903",
"0.5188523",
"0.5162973",
"0.50443614",
"0.50316876",
"0.50179154",
"0.50179154",
"0.49858508",
"0.49775422",
"0.49506262",
"0.4945812",
"0.48390582",
"0.48362887",
"0.48228404",
"0.482089",
"0.48181245",
"0.47931927",
"0.... | 0.7020021 | 0 |
Create a new garden. | def __init__(self, name: str, yard_id: Optional[int] = None) -> None:
self._name = name
if yard_id:
self._yard_id = yard_id | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create(request: GardenRequestCreate) -> Garden:\n if request.yard_id:\n garden = Garden(request.name, request.yard_id)\n else:\n garden = Garden(request.name)\n return garden",
"def create(request: BedRequestCreate) -> Bed:\n if request.garden_id:\n ... | [
"0.8164369",
"0.6483629",
"0.5973436",
"0.5973436",
"0.58737355",
"0.5726",
"0.5716766",
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"0.5716766",
"0.56845754",
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"0.5414858",
"0.5364724",
"0.535799",
"0.5349133",
"0.5321988",
"0.5304222",
"0.... | 0.0 | -1 |
Return a new garden. | def create(request: GardenRequestCreate) -> Garden:
if request.yard_id:
garden = Garden(request.name, request.yard_id)
else:
garden = Garden(request.name)
return garden | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create(request: BedRequestCreate) -> Bed:\n if request.garden_id:\n bed = Bed(request.name, request.yard_id, request.garden_id)\n else:\n bed = Bed(request.name, request.yard_id)\n return bed",
"def new(cls):\n return cls()",
"def new_room(self):\r\n ... | [
"0.5969182",
"0.55627793",
"0.53683287",
"0.53473854",
"0.53283143",
"0.5322329",
"0.52581275",
"0.5212227",
"0.5196043",
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"0.5069754",
"0.50693375",
"0.50672984",
"0.5046749",
"0.5021479",
"0.5010107",
"0.4999... | 0.7625244 | 0 |
Create a new bed. | def __init__(
self,
name: str,
yard_id: int,
garden_id: Optional[int] = None,
) -> None:
logger.debug(
f'Executing Bed __init__ with name: {name},'
f'yard_id: {yard_id} and garden_id: {garden_id}',
)
self._name = name
self._yard... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create(request: BedRequestCreate) -> Bed:\n if request.garden_id:\n bed = Bed(request.name, request.yard_id, request.garden_id)\n else:\n bed = Bed(request.name, request.yard_id)\n return bed",
"def make_bed(lines, num):\n f = get_prereqs(num)\n with open(f, '... | [
"0.6885664",
"0.5910571",
"0.5840972",
"0.5840972",
"0.57267797",
"0.56706005",
"0.56522185",
"0.55992997",
"0.5547432",
"0.55409247",
"0.5525808",
"0.55080783",
"0.5500319",
"0.54551196",
"0.54484475",
"0.5447523",
"0.54355776",
"0.54355776",
"0.54355776",
"0.5376025",
"0.53... | 0.4990907 | 68 |
Return a new bed. | def create(request: BedRequestCreate) -> Bed:
if request.garden_id:
bed = Bed(request.name, request.yard_id, request.garden_id)
else:
bed = Bed(request.name, request.yard_id)
return bed | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def simplify_bed(fbed, has_header):\n line_gen = reader(fbed, header=False)\n header = line_gen.next() if has_header else None\n fh = open(BedTool._tmp(), \"w\")\n for toks in line_gen:\n new_toks = toks[:3] + [\"Z_Z\".join(toks), \".\",\n toks[5] if len(toks) > 5 ... | [
"0.58296984",
"0.5644907",
"0.5551764",
"0.5321915",
"0.53026086",
"0.52609533",
"0.5244851",
"0.52361184",
"0.51136595",
"0.5104737",
"0.5095381",
"0.50601125",
"0.50565517",
"0.50565517",
"0.50280887",
"0.502569",
"0.49909022",
"0.49824548",
"0.4973729",
"0.49398288",
"0.49... | 0.65561134 | 0 |
Create a new plant. | def __init__(self, name, bed_id) -> None:
logger.debug(
f'Executing Plant __init with name:{name}, bed_id:{bed_id} ',
)
self._name = name
self._bed_id = bed_id | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create(request: PlantRequestCreate) -> Plant:\n logger.debug(f'Executing Plant create with request:{request}')\n return Plant(request.name, request.bed_id)",
"def create_unit(name, plant_id):\n Sections.create(name=name, plant=plant_id)",
"def add_plant(plant_type): # noqa: E501\n glob... | [
"0.7776638",
"0.68671316",
"0.6758583",
"0.6535089",
"0.6380151",
"0.63326854",
"0.6307291",
"0.6208937",
"0.6197248",
"0.60928243",
"0.59974295",
"0.59974295",
"0.59476334",
"0.5884455",
"0.58510983",
"0.5839649",
"0.5767345",
"0.57539916",
"0.57097006",
"0.5665074",
"0.5663... | 0.5987805 | 12 |
Return a new Plant. | def create(request: PlantRequestCreate) -> Plant:
logger.debug(f'Executing Plant create with request:{request}')
return Plant(request.name, request.bed_id) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_plant(plant_type): # noqa: E501\n global seededPlants\n global tasks\n\n if not seededPlants.get(plant_type):\n seededPlants[plant_type] = 0\n \n pid = db.addPlant(plant_type)\n plant = Plant(plant_id=pid, plant_type=plant_type)\n seededPlants[plant_type] += 1\n\n #clean up ... | [
"0.62443143",
"0.60929143",
"0.6055948",
"0.5976038",
"0.5604454",
"0.558746",
"0.55310094",
"0.54382646",
"0.54322815",
"0.53988934",
"0.53903615",
"0.5373456",
"0.537302",
"0.5348257",
"0.5344622",
"0.5341449",
"0.53242874",
"0.5299267",
"0.52762425",
"0.52678794",
"0.52597... | 0.7463095 | 0 |
Compute the lowrank operator, the eigenquantities and slow modes. | def compute_operator(self, Xc, Yc):
U, s, V = self._compute_svd(Xc)
self._Atilde = (np.linalg.multi_dot([U.T.conj(), (Yc), (V)])
* np.reciprocal(s))
self._compute_eigenquantities()
self._compute_modes(Yc, U, s, V)
self._slow_modes = (np.abs(old_div(np.log(self.eig... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def low_rank_approximation(LinearOperator: Union[ToeplitzMatrixFree, LinearOperatorFromMatrix], rank: int,\n hermitian: bool = False, tol: float = 0., backend='scipy') -> np.ndarray:\n if rank >= np.min(LinearOperator.shape):\n return LinearOperator.mat\n elif backend == 'num... | [
"0.59569466",
"0.53253007",
"0.526049",
"0.5103837",
"0.5011966",
"0.4989868",
"0.49648058",
"0.49209514",
"0.49070564",
"0.4901999",
"0.48523378",
"0.48302522",
"0.47786745",
"0.47545192",
"0.47301328",
"0.47296545",
"0.47243336",
"0.47148207",
"0.4714738",
"0.47038925",
"0.... | 0.48401913 | 11 |
Compute the ampltitudes for slow modes of this sub DMD operator. | def compute_sub_amplitudes(self, Xc, opt):
if opt:
# compute the vandermonde matrix
omega = old_div(np.log(self.eigs), self.original_time['dt'])
vander = np.exp(
np.multiply(*np.meshgrid(omega, self.dmd_timesteps))).T
# perform svd on all the sna... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def idealOpAmp():",
"def amplitudes(self,dataset):\n if ((dataset ==\"GPCP\") or (dataset == \"CMAP\")):\n start = '1979-1-1'\n stop = '2014-12-31'\n else:\n start = '1984-1-1'\n if dataset == \"ISCCP_raw\":\n stop = '2007-12-31'\n ... | [
"0.64523596",
"0.6316284",
"0.6023735",
"0.59572893",
"0.57390773",
"0.5645965",
"0.55997556",
"0.5442499",
"0.5416894",
"0.5408983",
"0.53514624",
"0.53022027",
"0.5294435",
"0.5264709",
"0.5228918",
"0.5207272",
"0.5185819",
"0.5171698",
"0.50277674",
"0.5026909",
"0.502029... | 0.47320998 | 57 |
Compute the MrDMD operator, modes, amplitudes and eigenvalues. | def compute_operator(self, snapshots):
# To avoid recursion function, use FIFO list to simulate the tree
# structure
data_queue = [snapshots.copy()]
current_bin = 0
while data_queue:
Xraw = data_queue.pop(0)
n_samples = Xraw.shape[1]
step =... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_rdm(self): \n\n # Check if CCSD calculation is performed\n if not self.cc_fragment:\n raise RuntimeError(\"Cannot retrieve RDM because no simulation has been run.\")\n\n # Solve the lambda equation and obtain the reduced density matrix from CC calculation\n sel... | [
"0.5778966",
"0.56038797",
"0.5406194",
"0.53687596",
"0.5319528",
"0.5314805",
"0.52992195",
"0.52947414",
"0.5274281",
"0.52448976",
"0.51809436",
"0.516814",
"0.51606435",
"0.51417494",
"0.5101703",
"0.5083811",
"0.5064862",
"0.5062005",
"0.4986676",
"0.4984563",
"0.498320... | 0.45844302 | 90 |
Private method that return the right index element from a given level and node. | def _index_list(self, level, node):
if level >= self._max_level:
raise ValueError("Invalid level: greater than `max_level`")
if node >= 2**level:
raise ValueError("Invalid node")
return 2**level + node - 1 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def level_to_index(level: int) -> int:\n\n level_data = {\n 15: 1,\n 25: 2,\n 30: 3,\n 35: 4,\n 40: 5,\n 45: 6,\n 50: 7,\n }\n return level_data[level]",
"def right_child_idx(idx):\n return (idx + 1) << 1",
"def tree_idx(tree,j1,J1,J2):\n j = j1\n... | [
"0.6774914",
"0.65624154",
"0.6238155",
"0.62297726",
"0.61812085",
"0.61276853",
"0.61116254",
"0.6070355",
"0.6063867",
"0.60625076",
"0.6038421",
"0.59762305",
"0.5957084",
"0.5940464",
"0.592238",
"0.59021884",
"0.58770186",
"0.5868177",
"0.58489066",
"0.5830463",
"0.5815... | 0.77435327 | 0 |
Method that return the level and node given the index of the bin. | def _index_list_reversed(self, index):
if index > 2**self._max_level - 2:
raise ValueError("Invalid index: maximum index is ({})".format(2**self._max_level - 2))
for lvl in range(self._max_level + 1):
if index < 2**lvl - 1:
break
level = lvl - 1
no... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def what_level(index):\n if index == [1,1] or [1,2]:\n level = 1\n else:\n level = 0\n return level",
"def get_node_indices_and_levels(nd: np.ndarray):\n indices = []\n lvs = []\n for j in range(1, nd.shape[0]):\n if j == 1:\n indices = nd[j]\n lvs = n... | [
"0.6595346",
"0.63736695",
"0.610129",
"0.6084127",
"0.60095966",
"0.59009176",
"0.57808703",
"0.57083344",
"0.568954",
"0.56878525",
"0.5673797",
"0.5669853",
"0.5658403",
"0.56557393",
"0.56169474",
"0.55956525",
"0.55331624",
"0.55331624",
"0.547583",
"0.5472164",
"0.54666... | 0.59511775 | 5 |
Evaluate the start and end time and the period of a given bin. | def partial_time_interval(self, level, node):
if level >= self._max_level:
raise ValueError(
'The level input parameter ({}) has to be less than the '
'max_level ({}). Remember that the starting index is 0'.format(
level, self._max_level))
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def bintime(s,tunit,timebin,nanval): \r\n #same functionality can make use of pandas.cut\r\n #but have to convert column to seconds and bin accordingly i.e:\r\n #pd.cut(test.dt.seconds,[i*3600 for i in [1,2,3,4,5]],labels=[1,2,3,4])\r\n #and use pd.fillna(lastbin) for stuff outside bin\r\n #.cat.... | [
"0.6374719",
"0.6116384",
"0.61071175",
"0.58316433",
"0.5764144",
"0.552417",
"0.5509737",
"0.5422938",
"0.54196686",
"0.53205734",
"0.53093106",
"0.52903247",
"0.5272032",
"0.5247645",
"0.5236844",
"0.5235189",
"0.5226849",
"0.51880866",
"0.51742667",
"0.5172404",
"0.516558... | 0.0 | -1 |
Find which bins are embedded (partially or totally) in a given time window. | def time_window_bins(self, t0, tend):
indexes = []
for level in range(self._max_level):
for i in range(2**level):
local_times = self.partial_time_interval(level, i)
if t0 >= local_times['t0'] and t0 < local_times['tend']:
indexes.append(sel... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def findBins(): \n\n df = pd.read_csv('significantData.csv')\n df = df.sort_values('RecordingTimestamp')\n df.to_csv('significantData.csv', index=False)\n read_in = pd.read_csv('significantData.csv')\n count = 0\n this = []\n return_bins = {}\n word = (read_in['AOI[Neutral_Left]Hit_0']).tol... | [
"0.6001422",
"0.5979062",
"0.594558",
"0.594434",
"0.5746636",
"0.5718944",
"0.57073534",
"0.5705244",
"0.56227374",
"0.56131464",
"0.5604326",
"0.5554541",
"0.54681987",
"0.5468194",
"0.54643685",
"0.5439552",
"0.5434822",
"0.54274553",
"0.54239434",
"0.54058325",
"0.5384072... | 0.66132635 | 0 |
Get the eigenvalues relative to the modes of the bins embedded (partially or totally) in a given time window. | def time_window_eigs(self, t0, tend):
indexes = self.time_window_bins(t0, tend)
return np.concatenate([self.operator.eigenvalues[idx]
for idx in indexes]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def eigenvalues(self) -> ndarray:\n return self._vals",
"def energies_kev(self):\n\n if not self.is_calibrated:\n raise UncalibratedError('Spectrum is not calibrated')\n else:\n return bin_centers_from_edges(self.bin_edges_kev)",
"def get_energy_per_eigenmode(self, A,... | [
"0.58370894",
"0.55990386",
"0.5529404",
"0.55293566",
"0.54781204",
"0.5472124",
"0.54494846",
"0.5428456",
"0.5418676",
"0.5387911",
"0.536809",
"0.5356477",
"0.5334652",
"0.5331583",
"0.53295034",
"0.53018385",
"0.5245877",
"0.52443105",
"0.5238841",
"0.5225844",
"0.521438... | 0.65667236 | 0 |
Get the frequencies relative to the modes of the bins embedded (partially or totally) in a given time window. | def time_window_frequency(self, t0, tend):
eigs = self.time_window_eigs(t0, tend)
return np.log(eigs).imag/(2*np.pi*self.original_time['dt']) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_freq_grid():\n (bins_per_octave, n_octaves, _, _, f_min, _) = get_hcqt_params()\n freq_grid = librosa.cqt_frequencies(\n bins_per_octave*n_octaves, f_min, bins_per_octave=bins_per_octave\n )\n return freq_grid",
"def get_frequencies(self):\n num_seconds = float(self.timestamps[-... | [
"0.64852643",
"0.6022063",
"0.600808",
"0.5990645",
"0.5934242",
"0.58441705",
"0.5806996",
"0.5801756",
"0.5784977",
"0.5745337",
"0.5737657",
"0.5725346",
"0.5717773",
"0.5688955",
"0.5539359",
"0.5526732",
"0.5491822",
"0.5462235",
"0.5460768",
"0.5458569",
"0.5438181",
... | 0.56093067 | 14 |
Get the growth rate values relative to the modes of the bins embedded (partially or totally) in a given time window. | def time_window_growth_rate(self, t0, tend):
return self.time_window_eigs(t0, tend).real/self.original_time['dt'] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def agg_angular_difference_timebins(\n data: np.ndarray, fps: int, time_windows: np.ndarray\n ):\n\n data = np.deg2rad(data)\n results = np.full((data.shape[0], time_windows.shape[0]), 0.0)\n for time_window_cnt in prange(time_windows.shape[0]):\n window_size = int(time_wi... | [
"0.5529094",
"0.5523554",
"0.5503484",
"0.54993916",
"0.5434323",
"0.53816473",
"0.5339452",
"0.53023434",
"0.52874565",
"0.52680075",
"0.52517766",
"0.52330875",
"0.5208008",
"0.51964575",
"0.5183654",
"0.5037942",
"0.5031358",
"0.5001336",
"0.49898788",
"0.49898517",
"0.498... | 0.597104 | 0 |
Get the amplitudes relative to the modes of the bins embedded (partially or totally) in a given time window. | def time_window_amplitudes(self, t0, tend):
indexes = self.time_window_bins(t0, tend)
return np.concatenate([self._b[idx] for idx in indexes]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_delta_amplitude_map(self, timeWindow=(0, 0.5)):\n\n windowIndex = np.logical_and(self.time >= timeWindow[0], self.time <= timeWindow[1])\n\n baseline_index = self.time < 0\n\n indON, indOFF, allAltPos, allAziPos = self._sort_index()\n\n ampON = np.zeros(indON.shape);\n am... | [
"0.61568254",
"0.614928",
"0.60325503",
"0.5697051",
"0.5682277",
"0.5591686",
"0.5508283",
"0.5396303",
"0.5369054",
"0.5282058",
"0.5267988",
"0.51722425",
"0.51637036",
"0.51363",
"0.51329863",
"0.51173633",
"0.5084328",
"0.5062478",
"0.50547963",
"0.5042427",
"0.50259316"... | 0.5973946 | 3 |
Get the reconstructed data. | def reconstructed_data(self):
try:
data = np.sum(
np.array([
self.partial_reconstructed_data(i)
for i in range(self._max_level)
]),
axis=0)
except MemoryError:
data = np.array(self.partial_rec... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_data(self):\r\n return self.data.copy()",
"def get_data(self):\n return self.parsed_data",
"def get_data(self): # TODO: add smooth possibility\n return self.data",
"def get_data(self):\n return self.data",
"def get_data(self):\n return self.data",
"def get_data... | [
"0.7384807",
"0.71945983",
"0.71018094",
"0.70430684",
"0.70430684",
"0.70430684",
"0.69570875",
"0.69570875",
"0.6895617",
"0.68922836",
"0.68922836",
"0.68922836",
"0.68922836",
"0.68888223",
"0.6882917",
"0.6882917",
"0.6856862",
"0.6804822",
"0.67907304",
"0.67694813",
"0... | 0.72060883 | 1 |
Get the matrix containing the DMD modes, stored by column. | def modes(self):
return np.hstack(tuple(self.operator.modes)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Dmat(self):\n return self._Dmat_cache",
"def matrix(self):\n return np.matrix(list(self._columns.values()))",
"def all_modes(self):\n\n # Find \"post-proj all modes\"\n # Jump to first value, ignoring text.\n # Move through data, adding it to a list\n # continue o... | [
"0.5767924",
"0.5739843",
"0.56482184",
"0.5603151",
"0.5537699",
"0.55024064",
"0.5490287",
"0.5476487",
"0.546271",
"0.5382778",
"0.5382778",
"0.5339894",
"0.53048295",
"0.5280998",
"0.526192",
"0.5253967",
"0.5238287",
"0.5233126",
"0.52254516",
"0.521381",
"0.52133495",
... | 0.5954592 | 0 |
Get the time evolution of each mode. | def dynamics(self):
return np.vstack(
tuple([self.partial_dynamics(i) for i in range(self._max_level)])) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __getTimeEvolution(self, target):\n omega = np.log(self._eigs[target]) / self.timeScales['training']['dt']\n van = np.exp(np.multiply(*np.meshgrid(omega, self._getTimeScale())))\n timeEvol = (van * self._amplitudes[target]).T\n return timeEvol",
"def evolution_time(self) -> float:\n return... | [
"0.6839359",
"0.6549283",
"0.6227073",
"0.6013248",
"0.5949761",
"0.5684334",
"0.56656706",
"0.5637081",
"0.5608758",
"0.55948883",
"0.55948883",
"0.55948883",
"0.55287373",
"0.54801244",
"0.5432319",
"0.5413853",
"0.5387543",
"0.53859884",
"0.53819513",
"0.53752744",
"0.5368... | 0.0 | -1 |
Get the eigenvalues of A tilde. | def eigs(self):
return np.concatenate(self.operator.eigenvalues) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def analytical_eig(A):\n n = len(A)\n h = 1/float(n)\n d = 2/float(h)**2\n a = -1/float(h)**2\n eigenval = np.empty(n)\n for j in range(1,n+1):\n eigenval[j-1] = d + 2*a*np.cos((j*np.pi)/(float(n)+1)) # Analytic solution\n \n return eigenval",
"def eigenvalues(self) -> ndarray:... | [
"0.72104555",
"0.7190363",
"0.70601994",
"0.7048385",
"0.7045235",
"0.67723763",
"0.6767977",
"0.6764434",
"0.6653182",
"0.6632767",
"0.66069925",
"0.6577262",
"0.65724695",
"0.65546983",
"0.65340793",
"0.6508823",
"0.6507871",
"0.65059394",
"0.6457978",
"0.64440125",
"0.6336... | 0.62570524 | 24 |
Return the modes at the specific `level` and at the specific `node`; if `node` is not specified, the method returns all the modes of the given `level` (all the nodes). | def partial_modes(self, level, node=None):
if node:
return self.operator.modes[self._index_list(level, node)]
indeces = [self._index_list(level, i) for i in range(2**level)]
return np.hstack(tuple([self.operator.modes[idx] for idx in indeces])) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getnodelevels(self, node_p=None):\n node_p = self.getnodenamed(node_p) # Verify pointer.\n\n node_type = self.getnodetype(node_p)\n nstates = self.getnodenumberstates(node_p)\n if node_type == 1:\n # CONTINUOUS_TYPE\n nlevels = nstates + 1\n else:\n ... | [
"0.5354951",
"0.5319307",
"0.5265018",
"0.5101411",
"0.49746078",
"0.49388418",
"0.48589152",
"0.4831829",
"0.4802974",
"0.47775087",
"0.47509822",
"0.46844825",
"0.4642154",
"0.4642027",
"0.4636629",
"0.46062893",
"0.4591814",
"0.45781466",
"0.45590946",
"0.4550383",
"0.4544... | 0.70844233 | 0 |
Return the time evolution of the specific `level` and of the specific `node`; if `node` is not specified, the method returns the time evolution of the given `level` (all the nodes). | def partial_dynamics(self, level, node=None):
def dynamic(eigs, amplitudes, step, nsamples):
omega = old_div(
np.log(np.power(eigs, old_div(1., step))),
self.original_time['dt'])
partial_timestep = np.arange(nsamples) * self.dmd_time['dt']
van... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def partial_time_interval(self, level, node):\n if level >= self._max_level:\n raise ValueError(\n 'The level input parameter ({}) has to be less than the '\n 'max_level ({}). Remember that the starting index is 0'.format(\n level, self._max_level)... | [
"0.59325534",
"0.52588916",
"0.5043633",
"0.495186",
"0.47398475",
"0.47092786",
"0.4535963",
"0.45331597",
"0.45329937",
"0.4521009",
"0.45167947",
"0.45030764",
"0.4470893",
"0.44635814",
"0.44450474",
"0.44365618",
"0.4435239",
"0.43837228",
"0.4378065",
"0.43257716",
"0.4... | 0.45204026 | 10 |
Return the eigenvalues of the specific `level` and of the specific `node`; if `node` is not specified, the method returns the eigenvalues of the given `level` (all the nodes). | def partial_eigs(self, level, node=None):
if level >= self._max_level:
raise ValueError(
'The level input parameter ({}) has to be less than the'
'max_level ({}). Remember that the starting index is 0'.format(
level, self._max_level))
if no... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def eigenvalues(self, expand=False, factor=False, simplify=False):\n raise NotImplementedError",
"def eigen_decomp(matrix):\n w = None\n v = None\n ### YOUR CODE HERE\n w,v=np.linalg.eig(matrix)\n ### END YOUR CODE\n return w, v",
"def eigensystem(mat):\n e, v = numpy.linalg.eig(mat... | [
"0.5242461",
"0.5114825",
"0.50866956",
"0.5004184",
"0.49853173",
"0.49390775",
"0.4933429",
"0.4927228",
"0.48673382",
"0.48499873",
"0.48347157",
"0.47743538",
"0.4752944",
"0.47522292",
"0.4748588",
"0.46996492",
"0.46762186",
"0.46594122",
"0.46453482",
"0.4602194",
"0.4... | 0.7101437 | 0 |
Return the reconstructed data computed using the modes and the time evolution at the specific `level` and at the specific `node`; if `node` is not specified, the method returns the reconstructed data of the given `level` (all the nodes). | def partial_reconstructed_data(self, level, node=None):
if level >= self._max_level:
raise ValueError(
'The level input parameter ({}) has to be less than the '
'max_level ({}). Remember that the starting index is 0'.format(
level, self._max_level)... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def read(node):\n shapes = list()\n\n # -- If we have a transform, add any nurbs curves\n # -- from it\n for shape in node.getShapes():\n if isinstance(shape, pm.nt.NurbsCurve):\n shapes.append(shape)\n\n if not shapes:\n return None\n\n # -- Define out output data. Right... | [
"0.48708206",
"0.48325694",
"0.4717103",
"0.46905452",
"0.46058008",
"0.45872766",
"0.45579225",
"0.4549462",
"0.45096028",
"0.45037228",
"0.4485179",
"0.4482341",
"0.44601327",
"0.44452712",
"0.4380473",
"0.43233997",
"0.42929927",
"0.42859843",
"0.42788714",
"0.42265484",
"... | 0.6255533 | 0 |
Compute the Dynamic Modes Decomposition to the input data. | def fit(self, X):
self._snapshots, self._snapshots_shape = self._col_major_2darray(X)
# Redefine max level if it is too big.
lvl_threshold = int(np.log(self._snapshots.shape[1]/4.)/np.log(2.)) + 1
if self._max_level > lvl_threshold:
self._max_level = lvl_threshold
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _reconstructData(self, target):\n data = self._modes[target].dot(self.__getTimeEvolution(target))\n return data",
"def decomposition(self, *args, **kwds):\n if not self.is_endomorphism():\n raise ArithmeticError(\"Matrix morphism must be an endomorphism.\")\n D = self.domain()\... | [
"0.5453213",
"0.52758074",
"0.5223547",
"0.51681143",
"0.51529014",
"0.5142907",
"0.50792956",
"0.5053362",
"0.5050135",
"0.50399166",
"0.5007684",
"0.49988356",
"0.49975812",
"0.49966964",
"0.49902576",
"0.4976227",
"0.49488717",
"0.49458563",
"0.49439144",
"0.4908942",
"0.4... | 0.0 | -1 |
Returns a normalize matrix | def normalize(X, m, s):
return (X - m)/s | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def normalize(self,matrix):\n for i in range(self.N):\n matrix[self.N-1][i] = 0\n for i in range(self.n):\n matrix[self.N - 1][self.index(i,i)] = 1\n return matrix",
"def normalize(self):\r\n max = np.amax(self.matrix)\r\n min = np.amin(self.matrix)\r\n\r\... | [
"0.7715446",
"0.7613959",
"0.75945044",
"0.74469215",
"0.72762185",
"0.7221286",
"0.7218722",
"0.7197787",
"0.71780825",
"0.71014005",
"0.69856745",
"0.6975971",
"0.6939313",
"0.6927247",
"0.6898473",
"0.68966824",
"0.68903077",
"0.6872301",
"0.68695444",
"0.6867305",
"0.6862... | 0.6534378 | 47 |
Test to check that constants specified as inputs aren't interpreted as an encoded constant. | def test_constant_as_input():
def get_graph():
dtype = "uint8"
ifm = relay.var("ifm", shape=(1, 16, 16, 32), dtype=dtype)
conv1 = make_ethosu_conv2d(
ifm,
32,
16,
(1, 1),
(0, 0),
(1, 1),
(1, 1),
)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_negative_values_not_allowed(self, test_input, expected, sc):\n expected_err_msg = f'negatives not allowed {expected}'\n with pytest.raises(ValueError):\n sc.add(test_input)\n\n try:\n sc.add(test_input)\n except ValueError as e:\n assert str(e) ... | [
"0.5949847",
"0.5904232",
"0.58766985",
"0.5792848",
"0.5781268",
"0.573758",
"0.57277274",
"0.57156056",
"0.57077456",
"0.56987315",
"0.5657231",
"0.56558204",
"0.5646676",
"0.56368077",
"0.5625566",
"0.56166357",
"0.561552",
"0.5598536",
"0.55874467",
"0.55759317",
"0.55703... | 0.56215614 | 15 |
Embeds an mp4 file in the notebook. | def embed_mp4(filename):
video = open(filename,'rb').read()
b64 = base64.b64encode(video)
tag = '''
<video width="640" height="480" controls>
<source src="data:video/mp4;base64,{0}" type="video/mp4">
Your browser does not support the video tag.
</video>'''.format(b64.decode())
return IPython.display.... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def in_show_video(name, vext='.mp4', ext='.png', loop=True, autoplay=True, controls=True, embed=False, figpath=figpath, **kwargs):\n import os\n from IPython.core.display import display, Image, HTML\n from base64 import b64encode\n\n opts = 'playsinline '\n if loop: opts += 'loop '\n if autoplay:... | [
"0.6405056",
"0.6389918",
"0.624613",
"0.58332616",
"0.5745402",
"0.5608184",
"0.5495171",
"0.547484",
"0.54442585",
"0.53840584",
"0.5354212",
"0.53239614",
"0.5266749",
"0.5199485",
"0.5187718",
"0.51537603",
"0.5122003",
"0.5109699",
"0.5109699",
"0.5109699",
"0.5081165",
... | 0.7854064 | 1 |
Returns a single string summary of the address, separating fields using commas. | def summary(self):
return u", ".join(self.active_address_fields()) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_address_string(self):\n output = ''\n if self.address_line_1:\n output += '{}'.format(self.address_line_1)\n if self.address_line_2:\n output += ', {}'.format(self.address_line_2)\n if self.city:\n output += ', {}'.format(self.city)\n if s... | [
"0.78189707",
"0.75865847",
"0.72340244",
"0.7221318",
"0.70897835",
"0.7086217",
"0.7069089",
"0.6952058",
"0.69167846",
"0.6916324",
"0.66950196",
"0.6601282",
"0.6566898",
"0.655473",
"0.65395886",
"0.65120167",
"0.640262",
"0.6396874",
"0.6348964",
"0.6314561",
"0.6234863... | 0.8051104 | 0 |
Join a sequence of fields using the specified separator | def join_fields(self, fields, separator=u", "):
field_values = []
for field in fields:
# Title is special case
if field == 'title':
value = self.get_title_display()
else:
value = getattr(self, field)
field_values.append(valu... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def join(sep, xs):\n return str(sep).join(xs)",
"def join(sep, seq):\n return _to_bytes_or_str_array(\n _vec_string(sep, object_, 'join', (seq,)), seq)",
"def join(items, sep=' ', prefix=None, suffix=None, target=None):\n if target is None:\n target = SQLQuery()\n\n target... | [
"0.69708467",
"0.674667",
"0.65593576",
"0.64647615",
"0.6429916",
"0.6410351",
"0.6325085",
"0.62385356",
"0.6212414",
"0.6085514",
"0.59461766",
"0.59388465",
"0.59145224",
"0.58975995",
"0.5858211",
"0.5847662",
"0.5796375",
"0.5794207",
"0.57875186",
"0.5756469",
"0.57317... | 0.7043287 | 0 |
Return the nonempty components of the address, but merging the title, first_name and last_name into a single line. | def active_address_fields(self, include_salutation=True):
fields = [self.line1, self.line2, self.line3,
self.line4, self.state, self.postcode]
if include_salutation:
fields = [self.salutation] + fields
fields = [f.strip() for f in fields if f]
try:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_address(self):\n\n return \"{}\\n{}\\n{},\\n{},\\n{}\".format(\n self.address_line_1, self.city, self.state, self.postal_code, self.country\n )",
"def format_address(line1, line2, city, state, zipcode):\n\t\n\tstreetlines = line1\n\tcityline = city\n\t\n\tif len(streetlines) > ... | [
"0.6954609",
"0.69253814",
"0.6911354",
"0.6881644",
"0.6759665",
"0.6734344",
"0.6643338",
"0.66044575",
"0.6474396",
"0.6452316",
"0.6411441",
"0.6401364",
"0.63200545",
"0.6319923",
"0.62194943",
"0.62148166",
"0.6207265",
"0.61958236",
"0.6132151",
"0.6110019",
"0.6110019... | 0.5777581 | 32 |
Return the order linked to this shipping address | def order(self):
try:
return self.order_set.all()[0]
except IndexError:
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def shipping_address(self):\n return Address(self._dict.get('shipping_address'))",
"def shipping_address(self) -> 'outputs.ShippingAddressResponse':\n return pulumi.get(self, \"shipping_address\")",
"def shipping_address(self) -> 'outputs.ShippingAddressResponse':\n return pulumi.get(self,... | [
"0.6902648",
"0.6399106",
"0.6399106",
"0.6399106",
"0.62057763",
"0.62034076",
"0.59340125",
"0.5929395",
"0.5901829",
"0.58613276",
"0.5810267",
"0.57903624",
"0.5780459",
"0.5767802",
"0.5753719",
"0.57446367",
"0.57325596",
"0.5718112",
"0.5695351",
"0.5687422",
"0.565242... | 0.57930714 | 11 |
Save a hash of the address fields | def save(self, *args, **kwargs):
# Save a hash of the address fields so we can check whether two
# addresses are the same to avoid saving duplicates
# self.hash = self.generate_hash()
# Ensure that each user only has one default shipping address
# and billing address
sel... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save_object(self, data):\n return Address(**data)",
"def store_address(intent, session):\n sess_data = session.setdefault('attributes', {})\n if not sess_data.get('add_address') and \\\n not sess_data['next_step'] == 'store_address':\n raise RuntimeError('Something went wrong.')\... | [
"0.6370817",
"0.6088569",
"0.60453266",
"0.60335714",
"0.598078",
"0.5959527",
"0.5934991",
"0.5910224",
"0.5907966",
"0.5855384",
"0.58534986",
"0.5826116",
"0.5799289",
"0.5788313",
"0.5712779",
"0.5688992",
"0.5621706",
"0.56182045",
"0.5589447",
"0.5579695",
"0.5579695",
... | 0.69221675 | 0 |
Init function. This first defines the network compression model that implements layer removal/shrinkage and training to get reward. It also obtains the number of layers, and the network state shape, number_of_layers x number_of_parameters_for_each_layer. This method also defines action_space and observation_space for G... | def __init__(self, config={}):
_, fileprefix = mkstemp()
idx = fileprefix.rfind('/')
fileprefix = fileprefix[idx + 1:]
self.network = NetworkCompression(prefix = fileprefix)
self.num_actions = self.network.get_action_space()
self.input_shape = self.network.get_observatio... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, device, state_space, action_space, num_actions):\n # initialize all parameters\n super(DQN_MLP_model, self).__init__(device, state_space, action_space,\n num_actions)\n # architecture\n self.layer_sizes = [(768, 768), (768, 7... | [
"0.6963171",
"0.67967623",
"0.6782904",
"0.67258465",
"0.66817856",
"0.66595465",
"0.66574657",
"0.6555321",
"0.655193",
"0.6515325",
"0.64991766",
"0.648771",
"0.6485449",
"0.6467087",
"0.6460257",
"0.64164853",
"0.64157426",
"0.6414727",
"0.6405644",
"0.6402848",
"0.6392700... | 0.6200549 | 50 |
This is an helper function that obtains the state of the network in number_of_layers x number_of_parameters_for_each_layer. However, coach does not like 2D array as input and hence recast it to 1D array | def _get_current_pos_in_1d(self):
pos = self.network.get_current_pos()
pos = np.squeeze(np.reshape(pos, (self.input_shape[0]*self.input_shape[1],1)))
return pos | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _cnn(self, state):\n\n x = self.relu(self.bn1(self.conv1(state)))\n x = self.relu(self.bn2(self.conv2(x)))\n x = self.relu(self.bn3(self.conv3(x)))\n x = x.reshape(x.size(0), -1)\n\n return x",
"def getstate(self):\r\n return Parameterized.getstate(self) + [self.part... | [
"0.62808293",
"0.6241918",
"0.6179134",
"0.6049776",
"0.6034651",
"0.5932981",
"0.5924396",
"0.59014106",
"0.58887464",
"0.5868812",
"0.5858823",
"0.5846273",
"0.5844779",
"0.58178574",
"0.5808643",
"0.57904416",
"0.5740947",
"0.57272613",
"0.5708938",
"0.5705436",
"0.570316"... | 0.0 | -1 |
Gym reset interface. Sets the current position of the simulation which is always the parent network state | def reset(self):
self.cur_pos = self._get_current_pos_in_1d()
return self.cur_pos | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def specific_reset(self) -> None:\n self.agent.specific_reset() # reset joints\n new_pos = self.agent.init_xyz\n new_pos[:2] = np.random.uniform(-0.01, 0.01, 2)\n self.agent.set_position(new_pos)\n self.old_potential = self.calculate_task_potential()",
"def reset(self):\n ... | [
"0.7264109",
"0.72616",
"0.70819384",
"0.70433414",
"0.69963706",
"0.6988895",
"0.696318",
"0.693653",
"0.69319737",
"0.6903858",
"0.68340075",
"0.68227863",
"0.68126225",
"0.68004537",
"0.67911285",
"0.6752854",
"0.6727614",
"0.6702409",
"0.66944015",
"0.66908115",
"0.668374... | 0.0 | -1 |
Gym step interface. Receives a set of binary actions (1d array) that determines whether to keep/remove each layer in the child network. This method also determines the reward obtained based on the action. Since we run only one step, the calculated reward is the final reward and we are done with an episode | def step(self, actions):
assert (len(actions) == self.num_actions)
actions = np.around(actions)
actions = np.clip(actions, 0, 1)
self.done = self.network.perform_actions(actions)
self.cur_pos = self._get_current_pos_in_1d()
self.reward = self.network.get_reward()
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def step(self, action:list) -> (np.ndarray, float, bool, dict):\n\n\n action[0] = (action[0] + 1)/2 # Done to be compatible with RL algorithms that require symmetric action spaces\n if np.isnan(action).any(): action = np.zeros(action.shape)\n self.main_vessel.step(action)\n\n for vessel... | [
"0.6944296",
"0.6848718",
"0.6799359",
"0.67124534",
"0.6680303",
"0.6627744",
"0.6627547",
"0.66090447",
"0.65186137",
"0.6489625",
"0.64750123",
"0.6471681",
"0.64692414",
"0.6450281",
"0.6441195",
"0.6427716",
"0.640443",
"0.6381965",
"0.63770854",
"0.6363568",
"0.6342039"... | 0.6566457 | 8 |
This method is used to retreive all environments. | def getEnvironments(request):
environments = Environment.objects.all()
serializer = environmentSerializer(environments, many=True)
result = {'data':serializer.data, 'code':HTTP_200_OK, 'message':OK}
return result | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_all_environments():\n return ENVIRONMENTS",
"def envs():\n\n # update and grab the envs from the metadata keys\n metadata = _init()\n return list(metadata.keys())",
"def environments(self):\n envs = self.config[\"tox\"][\"envlist\"]\n #result = re.split(\"[^a-zA-Z0-9]\", envs)... | [
"0.8714086",
"0.75199974",
"0.74426425",
"0.72617525",
"0.7142985",
"0.71147597",
"0.7099694",
"0.7068136",
"0.6949923",
"0.69379425",
"0.69020444",
"0.67948884",
"0.6783139",
"0.67773885",
"0.6774582",
"0.6730243",
"0.67123854",
"0.6709814",
"0.6692068",
"0.6645223",
"0.6605... | 0.7421862 | 3 |
'''Print the first paragraph of the docstring of the decorated function. The paragraph will be printed as a oneliner. May be invoked as a simple, argumentless decorator (i.e. ````) or with named arguments ``color``, ``bold``, ``prefix`` of ``tail`` (eg. ``(color=utils.red, bold=True, prefix=' ')``). | def print_doc1(*args, **kwargs):
# output settings from kwargs or take defaults
color = kwargs.get('color', blue)
bold = kwargs.get('bold', False)
prefix = kwargs.get('prefix', '')
tail = kwargs.get('tail', '\n')
def real_decorator(func):
'''real decorator function'''
@wraps(fun... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def printHelpFunc(self, func, leadingstrings=None):\n if leadingstrings is None:\n leadingstrings = ['- ', ' ']\n a, idx = 0, None\n for line in func.__doc__.split('\\n'):\n if len(line) == 0:\n continue\n if idx is None:\n idx = ... | [
"0.6182041",
"0.56835043",
"0.5528549",
"0.54951614",
"0.5478067",
"0.54739696",
"0.54724956",
"0.5464363",
"0.5463609",
"0.54350126",
"0.5416408",
"0.5416105",
"0.54136",
"0.53923166",
"0.53778976",
"0.5367521",
"0.5367521",
"0.5367521",
"0.5337481",
"0.5322726",
"0.53079075... | 0.7592692 | 1 |
Uses the supplied training inputs and labels to make predictions for validation data using the Knearest neighbours algorithm. | def knn(k, train_data, train_labels, valid_data):
dist = l2_distance(valid_data.T, train_data.T)
nearest = np.argsort(dist, axis=1)[:, :k]
train_labels = train_labels.reshape(-1)
valid_labels = train_labels[nearest]
# Note this only works for binary labels:
valid_labels = (np.mean(valid_labels... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run_knn(k, train_data, train_labels, valid_data):\n\n dist = l2_distance(valid_data.T, train_data.T)\n nearest = np.argsort(dist, axis=1)[:,:k]\n\n train_labels = train_labels.reshape(-1)\n valid_labels = train_labels[nearest]\n\n # note this only works for binary labels\n valid_labels = (np.... | [
"0.7216491",
"0.70995784",
"0.70012844",
"0.6901809",
"0.6870604",
"0.68224275",
"0.68148446",
"0.6792868",
"0.6734792",
"0.67107177",
"0.6665414",
"0.6601499",
"0.6598747",
"0.6598747",
"0.6598747",
"0.6597325",
"0.6596465",
"0.65924454",
"0.6582011",
"0.6581457",
"0.6571299... | 0.70062023 | 2 |
try to determine if a test suite should run or not given a set files in a diff | def check_should_run_suite(suite, diff_files):
if suite in always_run_jobs:
# you gotta do what you gotta do
return True
all_ignore = True
any_docs = False
all_docs = True
any_console = False
all_console = True
any_java = False
any_testable_script = False
all_testab... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def has_test(args):\n return (args.test_set or args.test_source or args.test_dataset or\n args.test_stdin or args.test_datasets)",
"def test_check():\n for f in cfg.required_files:\n assert os.path.isfile(f)",
"def run_test(standart_app, testing_app, *scenario_files):\n passed = True... | [
"0.60675377",
"0.6027447",
"0.59727937",
"0.58538693",
"0.58520204",
"0.58372957",
"0.58365786",
"0.5804472",
"0.58039814",
"0.5785943",
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"0.57812536",
"0.57245654",
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"0.57147026",
"0.56915843",
"0.56442523",
"0.5639239",
"0.5628038",
"0.5621098",
"0.5... | 0.7907135 | 0 |
Call in a loop to create terminal progress bar | def printProgressBar (iteration, total, prefix = '', suffix = '', decimals = 1, length = 100, fill = '█', printEnd = "\r"):
percent = ("{0:." + str(decimals) + "f}").format(100 * (iteration / float(total)))
filledLength = int(length * iteration // total)
bar = fill * filledLength + '-' * (length - filledLen... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_progress_bar():\n\n if simple_tregex_mode:\n total_files = len(list(to_iterate_over.keys()))\n else:\n total_files = sum(len(x) for x in list(to_iterate_over.values()))\n\n par_args = {'printstatus': kwargs.get('printstatus', True),\n 'root': r... | [
"0.73996055",
"0.73339546",
"0.7302448",
"0.7211271",
"0.7152014",
"0.7069114",
"0.7064241",
"0.70030713",
"0.6975914",
"0.6972206",
"0.6962635",
"0.69542474",
"0.69375116",
"0.6929309",
"0.6929309",
"0.6929309",
"0.6927648",
"0.6922987",
"0.6918861",
"0.6918861",
"0.69157404... | 0.67729735 | 50 |
Reconstructs the momentum of the neutrino and antineutrino, given the momentum of the muons and bottom quarks. | def reconstruct(edata, mwm=80.4, cme=1000):
assert len(edata) == 12, 'edata should have length 12.'
degree = 4 # The degree of the interpolating polynomial.
rbar_threshold = 0.95
mwm2 = mwm**2
domain_func, func1s, func2s = _getFuncs(edata, mwm2, cme)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def muontrg_efficiencies():\r\n# to be updated with new numbers:\r\n ejpsi_trg = Jpsi_trg\r\n ejpsi_trg.add_relative_error(0.03) # TISTOS Justine 140711\r\n ebsmm_trg.add_relative_error(0.02) # Extra lines Justine 140711\r\n ebsmm_trg = BmmE_trg\r\n ebsmm_trg.add_relative_error(0.03) # TISTOS Justin... | [
"0.5613315",
"0.53698575",
"0.5369027",
"0.5289094",
"0.52887803",
"0.52873486",
"0.5220959",
"0.5208002",
"0.5190982",
"0.51466244",
"0.50938475",
"0.5089522",
"0.5043566",
"0.50237817",
"0.49700487",
"0.49457595",
"0.48842022",
"0.48757416",
"0.48726192",
"0.48666868",
"0.4... | 0.0 | -1 |
Takes in a motion, and sends the bound key signal | def pressBoundKey(motion):
if bindings[motion]:
autopy.key.tap(bindings[motion], []) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _on_key_press(self, event):",
"def _on_key_release(self, event):",
"def press_bound_key(self, event):\n if event.key in self.key_bindings:\n self.press()\n elif (event.key, pg.key.get_mods()) in self.key_bindings:\n self.press()",
"def ev_KEYUP(self, event):",
"def k... | [
"0.68667006",
"0.67747253",
"0.6757369",
"0.6677286",
"0.6660343",
"0.6565812",
"0.65357596",
"0.6482535",
"0.6442972",
"0.638499",
"0.6371723",
"0.6342939",
"0.63109654",
"0.62828064",
"0.6278564",
"0.6200766",
"0.6191682",
"0.61816347",
"0.6171723",
"0.6170504",
"0.6152393"... | 0.7920645 | 0 |
Binds a character key to a motion in the bindings table | def bind(motion, character):
bindings[motion] = character | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def bind_key(self, key, command):\n self.key_bindings[key] = command",
"def pressBoundKey(motion):\n if bindings[motion]:\n autopy.key.tap(bindings[motion], [])",
"def bind_key(self, key):\n self.key_bindings.append(key)",
"def bindKeyboardKeysToFunctions(self):\n self.keyboard... | [
"0.73948914",
"0.717898",
"0.6787276",
"0.6590862",
"0.65523916",
"0.6453969",
"0.63455117",
"0.6275753",
"0.6270246",
"0.6268342",
"0.6202153",
"0.62004995",
"0.6192932",
"0.6180448",
"0.6134238",
"0.61339384",
"0.60985154",
"0.60825276",
"0.6080745",
"0.60624856",
"0.606173... | 0.80695057 | 0 |
Genera una ventana con la funcionalidad de generar un FileDialog. | def __init__(self):
tk.Tk.__init__(self)
self.title('Graficar datos')
# Configuración basica de componentes de interfaz
self.quitButton = tk.Button(self, width=12, text='Abrir archivo', bg='grey',command=self.buscar_archivo)
self.quitButton.grid(row=0, column=0, padx=8, pady=8)
self.lbl_archivo = tk.Label... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def openFileDialog(self): \n self.dialog = ocempgui.widgets.Box(373, 372)\n self.dialog.topleft = 528, 205\n\n background = guiobjects.OcempImageMapTransparent(GG.genteguada.GenteGuada.getInstance().getDataPath(WINDOW_UPLOAD))\n self.dialog.add_child(background)\n \n self.listDir = guiobjects.Oc... | [
"0.6843026",
"0.66493344",
"0.65278006",
"0.6506434",
"0.6504894",
"0.64873946",
"0.641618",
"0.640353",
"0.62047625",
"0.6195347",
"0.6175586",
"0.61684096",
"0.6079808",
"0.6068441",
"0.6013226",
"0.59823745",
"0.59658766",
"0.5941334",
"0.5917424",
"0.5914274",
"0.59101975... | 0.0 | -1 |
creates an exgaussian CDF lookup table that will be used to interpolate values | def create_exgauss_lookup_table(self):
return self.exgauss_cdf_nparray(range(self.xmin,self.xmax, self.dx)).tolist(), range(self.xmin,self.xmax, self.dx) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_smarter_lookup_table(self, y=0.95):\n # First determine an approximate starting point for the lookup taqble by halving the max value till the point \n # where the cdf value is less than the cdf value we are looking for\n xold = self.xmax\n xnew = self.xmax\n y_calc = self.exgauss_cdf(xnew)\n ... | [
"0.68857044",
"0.5776785",
"0.5618758",
"0.55740803",
"0.55609",
"0.5537735",
"0.5410309",
"0.5400205",
"0.53806585",
"0.53747016",
"0.53696406",
"0.5324577",
"0.5312523",
"0.52905965",
"0.52819836",
"0.5277198",
"0.5264599",
"0.52586555",
"0.5256953",
"0.5254281",
"0.5247637... | 0.75694865 | 0 |
creates an exgaussian CDF lookup table but in a smarter way in that it creates a leaner lookup table with more values stacked closer to where the cdf value we are searching for is | def create_smarter_lookup_table(self, y=0.95):
# First determine an approximate starting point for the lookup taqble by halving the max value till the point
# where the cdf value is less than the cdf value we are looking for
xold = self.xmax
xnew = self.xmax
y_calc = self.exgauss_cdf(xnew)
while y_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_exgauss_lookup_table(self):\n return self.exgauss_cdf_nparray(range(self.xmin,self.xmax, self.dx)).tolist(), range(self.xmin,self.xmax, self.dx)",
"def _calc_ecdf(self):\n for numerator, vals in self.lift.items():\n for denominator, lift in vals.items():\n raw_data ... | [
"0.66475147",
"0.5811636",
"0.5665929",
"0.5633998",
"0.55846995",
"0.5386738",
"0.5367499",
"0.53664035",
"0.5290156",
"0.52471405",
"0.5237261",
"0.5190163",
"0.51828945",
"0.5166558",
"0.51589215",
"0.51433057",
"0.5126065",
"0.5123258",
"0.5092755",
"0.50826335",
"0.50671... | 0.72736365 | 0 |
1. Hide the root window 2. Draw the login window 3. Close the entire application when login window is closed 4. Lock the rest of the program until the correct password is given 5. Add widgets to the login window | def __init__(self, root):
root.withdraw()
self.widgets['Login Window'] = subwindow.draw_subwindow(root, self.w, self.h, self.title)
self.widgets['Login Window'].protocol('WM_DELETE_WINDOW', lambda: subwindow.on_exit(root))
self.widgets['Login Window'].grab_set()
self.create_w... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def LoadLogInWindow(self):\n \n def CreateAccount():\n \"\"\"Erase 'Log In' widgets to load 'Account Creation' widgets.\n \n This function is called by the 'Create New Account' button.\n \"\"\"\n login_frame.forget()\n self.LoadCreateA... | [
"0.7726316",
"0.76516026",
"0.7324264",
"0.71482766",
"0.71319604",
"0.7108741",
"0.70845526",
"0.70725036",
"0.7013036",
"0.6962864",
"0.69238645",
"0.6832125",
"0.6776213",
"0.6681016",
"0.66242844",
"0.661402",
"0.6568176",
"0.6503089",
"0.6480701",
"0.6401318",
"0.6358778... | 0.69373995 | 10 |
1. Create and display a Frame for the widgets 2. Create and display a password prompt Label 3. Create and display an input Frame 4. Create and display a password Entry 5. Create and display an enter Button 6. Bind key to enter Button 7. Create a message Label | def create_widgets(self, root):
self.widgets['Main Frame'] = Frame(self.widgets['Login Window'], borderwidth=20)
self.widgets['Main Frame'].pack(expand=YES, fill=BOTH)
Label(self.widgets['Main Frame'], text='Enter password:').pack(side=TOP, expand=YES)
self.widgets['Input Frame'] = Fr... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_widgets(self):\n self.instruction = Label(self, text=\"Enter the password \")\n self.instruction.grid(row=0, column=0, columnspan=2, sticky=W)\n\n self.password_entry = Entry(self)\n self.password_entry.grid(row=0, column=1, sticky=W)\n\n self.submit_button = Button(se... | [
"0.8136624",
"0.7529008",
"0.74277",
"0.7223204",
"0.7031169",
"0.6925377",
"0.6852082",
"0.6676885",
"0.6617138",
"0.6586638",
"0.65417933",
"0.6515163",
"0.64958483",
"0.64647",
"0.6382624",
"0.6367032",
"0.634605",
"0.63396925",
"0.6337783",
"0.63201666",
"0.6295827",
"0... | 0.7642204 | 1 |
1. Get the user input from the Password Entry | def verify_password_input(self, root):
ui = self.widgets['Password Entry'].get()
if ui == self.password[0]:
self.widgets['Login Window'].destroy()
root.deiconify()
menu.define_workspace(root)
else:
widgets.edit_message(self.widgets['Message'], se... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def enter_password(self):",
"def prompt_pass():\n msg = \"Enter Password: \"\n password = getpass.getpass(msg)\n return password",
"def password(self) -> str:",
"def getpass(self, prompt):\r\n return getpass.getpass(prompt)",
"def get_password_from_user():\n pwd = ''\n keyboard = xbmc... | [
"0.81052965",
"0.77915996",
"0.7512173",
"0.7433339",
"0.7430234",
"0.73654836",
"0.7329979",
"0.7324449",
"0.72566116",
"0.7251749",
"0.7206463",
"0.720326",
"0.720326",
"0.720326",
"0.720326",
"0.720326",
"0.720326",
"0.720326",
"0.720326",
"0.720326",
"0.720326",
"0.7203... | 0.68862444 | 52 |
Simulate the main task. Do something (compute a result), and send a message to the saver | def main_task_handler():
context = zmq.Context()
# socket to sending messages to save
save_sender = context.socket(zmq.PUSH)
save_sender.connect(SAVE_PUSH_QUEUE_ADDR)
c = 0
while (True):
# simulate some very complex computation
(x, y) = (random.gauss(0, 1), random.gauss(0, 1))
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run():\n\n # Set up environment and agent\n e = Environment() # create environment (also adds some dummy traffic)\n a = e.create_agent(LearningAgent) # create agent\n e.set_primary_agent(a, enforce_deadline=False) # set agent to track\n\n # Now simulate it\n sim = Simulator(e, update_delay... | [
"0.6379486",
"0.6375426",
"0.6371881",
"0.63712204",
"0.629279",
"0.6278951",
"0.6243851",
"0.6223295",
"0.6182957",
"0.6136574",
"0.60471547",
"0.60366166",
"0.60341793",
"0.60041267",
"0.6000432",
"0.5988411",
"0.5983482",
"0.59803426",
"0.59710443",
"0.5966627",
"0.5954777... | 0.6512541 | 0 |
Simulate listening to a cmd sent by the master, and replying to it | def cmd_handler():
context = zmq.Context()
# socket to receive commands (a subscription to ELECTION_CODE channel)
cmd_socket = context.socket(zmq.SUB)
cmd_socket.connect ("tcp://%s:5556" % SERVER_HOST)
topicfilter = "politiche2013"
cmd_socket.setsockopt(zmq.SUBSCRIBE, topicfilter)
# socket... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _sendingCommand(self): \n\n while True:\n self.tello.send_command('command') \n time.sleep(5)",
"def do_command(command):\n send_command(command)\n # time.sleep(0.1) # may be required on slow machines\n response = get_response()\n print(\"Rcvd: <<< \" + resp... | [
"0.69502234",
"0.6697658",
"0.64755666",
"0.6336326",
"0.62877846",
"0.6227407",
"0.6196379",
"0.6194214",
"0.618218",
"0.6180899",
"0.6173779",
"0.61692375",
"0.61592835",
"0.61553776",
"0.6124696",
"0.6112446",
"0.6090134",
"0.60835063",
"0.60796964",
"0.60646766",
"0.60618... | 0.64755476 | 3 |
generate successive prime numbers (trial by division) | def Primes():
candidate = 1
_primes_so_far = [2] # first prime, only even prime
yield _primes_so_far[-1]
while True:
candidate += 2 # check odds only from now on
for prev in _primes_so_far:
if prev**2 > candidate:
yield candidate
_pr... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def primes():\n yield 1\n primes = []\n for n in itertools.count(2):\n if not any(n % p == 0 for p in primes):\n # No divisor found among previous primes\n yield n\n primes.append(n)",
"def primes():\n yield 2\n candidate = 3\n while True:\n for i ... | [
"0.7673731",
"0.767177",
"0.767177",
"0.7644096",
"0.7614384",
"0.758533",
"0.75068355",
"0.7456537",
"0.72594345",
"0.71743274",
"0.7161902",
"0.71163714",
"0.7084194",
"0.6997164",
"0.69905466",
"0.6985653",
"0.6959174",
"0.69511086",
"0.6947724",
"0.69435084",
"0.69297296"... | 0.7058044 | 13 |
prints company names for the given year | def get_titles(year, basepath=None):
# create a day file reader
dr = None
try:
if basepath is not None:
dr = dayToDF.DayReader(year, basepath=basepath)
else:
dr = dayToDF.DayReader(year)
except FileNotFoundError as err:
logging.fatal("Could not create DayR... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def yearname(self):\n return self.strftime(\"%Y\")",
"def full_name(self, year=None):\n return \"%d%s\" % (self.index(year), self.name)",
"def formatyear(self, theyear):\n\t\tv = []\n\t\ta = v.append\n\t\ta('<table border=\"0\" cellpadding=\"0\" cellspacing=\"0\" class=\"year\">')\n\t\ta('\\n')\n... | [
"0.6591413",
"0.6297006",
"0.61307436",
"0.5971754",
"0.5817641",
"0.5769102",
"0.5757908",
"0.5753845",
"0.5740012",
"0.5704324",
"0.56821907",
"0.56579894",
"0.56541425",
"0.5653108",
"0.5635096",
"0.56150603",
"0.56144917",
"0.56038475",
"0.5547933",
"0.5513544",
"0.548851... | 0.51956016 | 56 |
Tests if not having any parameters in the init call raises a TypeError | def test_001_init(self):
self.assertRaises(TypeError,rawdata.rawdata) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_constructor_invalid():\n with pytest.raises(TypeError, match='missing 1 required positional argument'):\n PseudoPotentialData() # pylint: disable=no-value-for-parameter",
"def check_params(self):\n raise NotImplementedError",
"def _check_params(self):\n pass",
"def test_init_rai... | [
"0.70104694",
"0.6926359",
"0.6900749",
"0.6805929",
"0.6801639",
"0.67635816",
"0.67625475",
"0.6702001",
"0.66861004",
"0.66850466",
"0.66674775",
"0.66362405",
"0.65991765",
"0.65822953",
"0.65713227",
"0.6533889",
"0.6526928",
"0.6504825",
"0.6481195",
"0.64775735",
"0.64... | 0.62806404 | 37 |
Tests if having only id parameter in the init call raises a TypeError | def test_002_init(self):
self.assertRaises(TypeError,rawdata.rawdata,"id") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_init_id_type(self):\n self.assertIsInstance(Rectangle(1, 1).id, int)\n self.assertIsInstance(Rectangle(1, 1, id=None).id, int)",
"def test_non_int_arg(self):\n obj = Base('id')\n self.assertTrue(obj.id is 'id')",
"def check_id(self, id):",
"def test_id_type_none(self):\n ... | [
"0.76953214",
"0.7402727",
"0.7265812",
"0.7121857",
"0.70339227",
"0.69546986",
"0.6857017",
"0.67979646",
"0.67748326",
"0.6755924",
"0.6710613",
"0.66996866",
"0.66996866",
"0.66996866",
"0.66996866",
"0.6673032",
"0.6602561",
"0.6554279",
"0.6554279",
"0.6554279",
"0.6554... | 0.71551645 | 3 |
Tests if having id and ionchrom parameter in the init call raises a TypeError | def test_003_init(self):
self.assertRaises(TypeError,rawdata.rawdata,"id",testRawdata.ioc) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_002_init(self):\n self.assertIsInstance(ionchrom.ionchrom(\"id\"),ionchrom.ionchrom)",
"def test_001_init(self):\n self.assertRaises(TypeError,ionchrom.ionchrom)",
"def test_002_init(self):\n self.assertRaises(TypeError,rawdata.rawdata,\"id\")",
"def test_init_id_type(self):\n ... | [
"0.75527525",
"0.74423254",
"0.6566925",
"0.61732787",
"0.6122854",
"0.60900694",
"0.59359056",
"0.5932252",
"0.5904741",
"0.5903323",
"0.5900798",
"0.5861291",
"0.57611066",
"0.5745521",
"0.5739906",
"0.5716416",
"0.5645096",
"0.5621805",
"0.5605678",
"0.56036425",
"0.559107... | 0.65853083 | 2 |
Tests if passing the id, ionchrom and sample parameters generates a new object of type sample | def test_004_init(self):
self.assertIsInstance(rawdata.rawdata("id",testRawdata.ioc,testRawdata.sam),rawdata.rawdata) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sample(self, sample_id: str):\n\n class LimsSample:\n \"\"\" A mock class for a sample coming from LIMS. It only needs a comment \"\"\"\n\n def __init__(self, sample_id):\n self.sample_id = sample_id\n self.sample_data = {\"comment\": \"a comment in Li... | [
"0.6396938",
"0.63250375",
"0.61931926",
"0.6181083",
"0.60503036",
"0.6019446",
"0.597",
"0.5902527",
"0.58856195",
"0.5864737",
"0.58281857",
"0.57671076",
"0.57660705",
"0.5757237",
"0.573097",
"0.57248074",
"0.57248074",
"0.57069016",
"0.56881464",
"0.5687392",
"0.5686203... | 0.5674374 | 23 |
Try to find nfo file in movie directory and search in nfo IMDB idetifier | def IMDB_idenifier_search(self):
dir_list = os.listdir(self.MovieDir)
dir_count = 0
for x in dir_list:
if x.split(".")[-1].lower()=="nfo":
print "find NFO in %i list" % dir_count
break
dir_count=dir_count+1
try:
nfo_file = open(self.MovieDir+"/"+dir_list[dir_count],"r")
buffor = nfo_file.re... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def MovieScan():\r\n for root, dirnames, filenames in os.walk(dlPath):\r\n for extend in movtypes:\r\n for filename in fnmatch.filter(filenames, extend):\r\n matches.append(os.path.join(root, filename))\r\n print(os.path.join(root, filename))\r\n sh... | [
"0.5898576",
"0.58694935",
"0.5622307",
"0.5614593",
"0.55535376",
"0.5487656",
"0.5487184",
"0.5405422",
"0.5401638",
"0.51820374",
"0.511373",
"0.5113248",
"0.510091",
"0.5017189",
"0.5016573",
"0.5016369",
"0.5010073",
"0.5002005",
"0.50001943",
"0.49860036",
"0.49847925",... | 0.77056664 | 0 |
Function connect with server and downloades avaliable subtitle list or avaliable subtitle zip file | def __connect_with_server(self,get_operatoin,server_reuest_type):
what_is_downloaded = server_reuest_type
self.XML_String = None
self.zip_string = None
try:
conn = httplib.HTTPConnection(self.NAPISY24_url)
conn.request("GET", get_operatoin)
r1 = conn.getresponse()
print r1.status, r1.reason
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def download(self):\n if not os.path.isdir(self.save_path):\n try:\n os.mkdir(self.save_path)\n except IOError:\n print(\"Can't create subfolder. \"\n \"Check that you have write access for \"\n \"{}\".format(self.... | [
"0.6728568",
"0.6727653",
"0.63100266",
"0.60740006",
"0.5940395",
"0.5809924",
"0.5798153",
"0.56826454",
"0.5632426",
"0.560139",
"0.55641836",
"0.5529447",
"0.53975224",
"0.5332132",
"0.5298177",
"0.5249126",
"0.520643",
"0.5179963",
"0.51734734",
"0.51577014",
"0.5155442"... | 0.62584805 | 3 |
Downloaded XML string isn't compatybil with XML standard in which minidom is written. | def Correct_MultiRoot_XML(self):
if self.XML_String[0] == "\n":
self.XML_String=self.XML_String[1:]
SECONDLINE_CHAR = 0
for x in self.XML_String:
SECONDLINE_CHAR = SECONDLINE_CHAR+1
if x =="\n":
break
self.XML_String = self.XML_String[0... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_with_no_encoding(self):\n xml = (\n u'<?xml version=\"1.0\"?>'\n u'<DocRoot>'\n u'<Elem1>默认جذ</Elem1>'\n u'<Elem2/>'\n u'</DocRoot>'\n )\n io_string = six.StringIO()\n self.builder.dom_element.write_doc(io_string, encod... | [
"0.6344099",
"0.6286215",
"0.6196129",
"0.6091438",
"0.60381323",
"0.6027413",
"0.60088193",
"0.59996015",
"0.589542",
"0.58318496",
"0.5826632",
"0.58164376",
"0.57975066",
"0.57491887",
"0.5740025",
"0.57227606",
"0.5715181",
"0.5678621",
"0.5669144",
"0.56683767",
"0.56330... | 0.0 | -1 |
Function returns subtitle dictionary which is computed from correct xml string. | def return_xml_dict(self):
try:
self.Correct_MultiRoot_XML()
self.subtitle_dict = sorted(self.xmltodict(self.XML_String)['subtitle'],key=itemgetter('imdb','cd'))
#self.subtitle_dict = self.xmltodict(self.XML_String)['subtitle']
print "XML subtitle list downloaded and converted to dict"
return ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _from_origin_to_dict(self):\n try:\n for elem in self._xml_tree.getchildren():\n if elem.tag == \"info\":\n for subelem in elem.xpath(\"//Metadata/General/Metas/Titulo\"):\n self._translated_dict[\"root\"][\"title\"] = subelem.text\n ... | [
"0.5741043",
"0.56276953",
"0.55804926",
"0.54216254",
"0.5318582",
"0.5317567",
"0.53144175",
"0.53124976",
"0.53016436",
"0.5292441",
"0.52581465",
"0.5189917",
"0.51402706",
"0.5140158",
"0.51315385",
"0.5113792",
"0.51061213",
"0.5029709",
"0.50141513",
"0.5013694",
"0.50... | 0.67018545 | 0 |
From subtitle dictionary function returns value. | def return_xml_dict_entry_value(self,dict_entry, dict_entry_position):
value = self.subtitle_dict[dict_entry][dict_entry_position]
return value[0] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def edx_get_subtitle(url, headers):\n \"\"\" or None if no subtitles are available \"\"\"\n try:\n jsonString = get_page_contents(url, headers)\n jsonObject = json.loads(jsonString)\n return edx_json2srt(jsonObject)\n except URLError as e:\n print('[warning] edX subtitles (erro... | [
"0.6290816",
"0.61481214",
"0.60934126",
"0.59526104",
"0.5819839",
"0.5644419",
"0.5638596",
"0.5580923",
"0.5557902",
"0.53163785",
"0.5266296",
"0.5250043",
"0.51997524",
"0.51850265",
"0.51807094",
"0.5156665",
"0.51562893",
"0.5116406",
"0.50712675",
"0.503532",
"0.49858... | 0.6423573 | 0 |
Function saves downloaded zip string on given path anf destroy self.zip_string if saveing is succesfull. | def save_downloaded_zip(self, dict_entry_to_download):
if self.download_subtitle_zip(dict_entry_to_download) == True:
try:
zip_file = open(self.ZipFilePath,"wb")
zip_file.write(self.zip_string)
zip_file.close
print "Zipfile: %s saved on hdd." % self.ZipFilePath
del self.zip_string
return True
e... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def zipsave(self):\n\n filename = filedialog.asksaveasfilename(initialdir=self.root.cache_dir,\n title='Save As',\n filetypes=[('Zip', '.zip')],\n defaultextension='')... | [
"0.69184697",
"0.6477389",
"0.6425179",
"0.63842976",
"0.6137987",
"0.6123069",
"0.5896687",
"0.5882788",
"0.5697541",
"0.5678088",
"0.5674914",
"0.5637382",
"0.56089973",
"0.5559134",
"0.5541039",
"0.5518614",
"0.55055565",
"0.54959124",
"0.5464814",
"0.54589176",
"0.5444477... | 0.7418616 | 0 |
Napisy 24 GET request for subtitle zip downloading. Data is stored in self.zip_string. | def download_subtitle_zip(self, dict_entry_to_download):
request_subtitle_list = "http://napisy24.pl/download/%s/" % str(self.return_xml_dict_entry_value(dict_entry_to_download,'id'))
repeat = 3
while repeat > 0:
repeat = repeat - 1
#request_subtitle_list = "/libs/webapi.php?title=%s" % self.Movie... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def download(self):\n if not os.path.isdir(self.save_path):\n try:\n os.mkdir(self.save_path)\n except IOError:\n print(\"Can't create subfolder. \"\n \"Check that you have write access for \"\n \"{}\".format(self.... | [
"0.62294996",
"0.573122",
"0.5613491",
"0.56069106",
"0.54558396",
"0.53945196",
"0.5256225",
"0.5209892",
"0.5174074",
"0.5155498",
"0.51524377",
"0.5145467",
"0.5109938",
"0.51030266",
"0.51014733",
"0.50734365",
"0.50671315",
"0.50465274",
"0.50144225",
"0.5005846",
"0.498... | 0.6889805 | 0 |
Funstion takes movie file path and based on EXTENSIONS from myListy.pl returns list of movies in movie file directory | def __return_movie_file_list(self, movie_path):
movie_dir = movie_path.rsplit("/",1)[0]
movie_file_list =[]
movie_extentionds = self.__movie_file_extensions(self.__file_extentions)
for x in os.listdir(movie_dir):
if x.rsplit(".",1)[-1]in movie_extentionds:
mov... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_movies(path):\n movies_list = []\n \n \n for f in os.listdir(path):\n \n full_file_path = join(path,f)\n if isdir(full_file_path):\n \n movies_list.extend( get_movies(full_file_path) )\n \n elif isfile(full_file_path) and full_file_pa... | [
"0.77624446",
"0.69705206",
"0.6920418",
"0.65718144",
"0.65128",
"0.64938384",
"0.6462537",
"0.6437294",
"0.6373601",
"0.63549864",
"0.6350856",
"0.6319466",
"0.629446",
"0.6210759",
"0.6183799",
"0.61389726",
"0.6127222",
"0.61024976",
"0.6081276",
"0.60760933",
"0.607265",... | 0.7945257 | 0 |
Function returns structure (file_path, {guesseFileData}) | def subtitlePath_and_subtitleFileData(self,file_path_list):
subtile_file_data = []
for x in file_path_list:
subtile_file_data.append((x, self.guessFileData(x)))
return subtile_file_data | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_file_data(filename):",
"def raw_file_structure(self):\n return None",
"def get_data(found_file, created_file):\n\n try:\n fh_f = fits.open(found_file)\n print('Found file has: ', fh_f.info())\n except Exception:\n print(' FATAL ERROR: Unable to open found file ', found... | [
"0.5878077",
"0.5440457",
"0.53874904",
"0.53820133",
"0.53557533",
"0.53333783",
"0.53244895",
"0.5290351",
"0.52806115",
"0.52697927",
"0.5260802",
"0.52478737",
"0.524652",
"0.523822",
"0.52320105",
"0.52174884",
"0.5207511",
"0.51975965",
"0.5183999",
"0.51685417",
"0.514... | 0.0 | -1 |
Returns best matching movie subtitle table. | def give_movie_subtitle_consistent_data(self, movie_file_data, subtitle_file_data):
m_s_temp_data = []
preliminary_movie_subtitle_list = self.compare_movie_and_subtitle_FileData(movie_file_data, subtitle_file_data)
for x in preliminary_movie_subtitle_list:
""" Delete 0 'propability' ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _best_matching_movie(movie):\n return (Levenshtein.distance(movie_name, movie.get('title').lower()),\n (0 - movie.get('votes', 0)),\n )",
"def download_subtitle(search, results, filename, min_match=0,\n force=0, debug=0):\n s = Subseek()\n subti... | [
"0.618252",
"0.5965921",
"0.57754785",
"0.5734618",
"0.57143825",
"0.5659548",
"0.5541539",
"0.5518001",
"0.5478379",
"0.5466522",
"0.543087",
"0.53836876",
"0.5375327",
"0.52907383",
"0.52813095",
"0.5275028",
"0.52749276",
"0.52622724",
"0.5237285",
"0.5202462",
"0.5175123"... | 0.65964955 | 0 |
Generate a .tgz archive from the contents of the web_static. | def do_pack():
now = datetime.now()
# format the name of the file with the timestamps
now_year = now.year
now_month = now.month
now_day = now.day
now_hour = now.hour
now_minute = now.minute
now_second = now.second
# apply the format
file_name = 'versions/web_static_{}{}{}{}{}{}.... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def do_pack():\n now = datetime.datetime.now()\n path = 'versions/web_static_' +\\\n '{}{}{}{}{}{}'.format(now.year, now.month,\n now.day, now.hour,\n now.minute, now.second) + '.tgz'\n\n local('mkdir -p versions')\n success = lo... | [
"0.7631921",
"0.75582755",
"0.75560766",
"0.75341463",
"0.7505679",
"0.7504223",
"0.7474274",
"0.74703455",
"0.74594927",
"0.7432596",
"0.74290574",
"0.7389648",
"0.7334055",
"0.7259239",
"0.72502697",
"0.72062916",
"0.72048455",
"0.71769315",
"0.71692425",
"0.7156065",
"0.71... | 0.73877853 | 12 |
check the previous day for viable departures | def test_check_yesterday(self):
# the service calendar has two weekdays, back to back
sc = ServiceCalendar()
sc.add_period( 0, 3600*24, ["WKDY"] )
sc.add_period( 3600*24, 2*3600*24, ["WKDY"] )
# the timezone lasts for two days and has no offset
# this is... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_if_up_to_date():\n last_daily = get_latest_dl_date()\n last_trading_day = get_last_open_trading_day()",
"def check_absent_pre_date(self, cr, uid, att, context=None):\n if att:\n # check employee absent pre date\n pre_att_ids = self.search(cr, uid, [('employee_id', '='... | [
"0.65856576",
"0.60677063",
"0.5963223",
"0.59185475",
"0.5852571",
"0.5852219",
"0.5837756",
"0.5755815",
"0.57509553",
"0.56721824",
"0.56598383",
"0.56210434",
"0.56133294",
"0.55789524",
"0.5559235",
"0.55514705",
"0.5542802",
"0.5537821",
"0.5515126",
"0.5511169",
"0.547... | 0.57666147 | 7 |
Converts a list of strings to a string by concatenating all elements of the list | def collapse(L):
output = ""
for s in L:
output = output + s
return output | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def stringer(list):\n\tstring = \"\"\n\tfor x in list:\n\t\tstring = string + str(x)\n\treturn string",
"def list2string(a_list):\n\n the_string = ''\n for elem in a_list:\n the_string += str(elem)\n return the_string",
"def list_to_str(list_to_convert):\n return ' '.join(to_str(item) for it... | [
"0.845377",
"0.7836319",
"0.7773371",
"0.7705512",
"0.7661951",
"0.7658474",
"0.7595569",
"0.7587454",
"0.7479857",
"0.7459654",
"0.74586385",
"0.7406689",
"0.7406689",
"0.7394045",
"0.7386286",
"0.7349678",
"0.7333463",
"0.733121",
"0.7291625",
"0.7260772",
"0.71728444",
"... | 0.652098 | 56 |
Computes the Protein encoded by a sequence of DNA. This function does not check for start and stop codons (it assumes that the input DNA sequence represents an protein coding region). | def coding_strand_to_AA(dna):
l = len(dna)
res = []
for i in range(0, l, 3):
s = dna[i: i + 3]
for j in range(len(codons)):
# for codon in codons[j]:
# if codon == s:
# res.append(aa[j])
# break;
if s in codons[j]: ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def dna_to_protein(seq):\n\n # Verify a convertible sequence\n if len(seq) % 3 != 0:\n raise RuntimeError('Total number of bases must be a multiple of 3')\n\n # Iterate through adding the proteins\n protein = ''\n for i in range(0, len(seq), 3):\n protein += bioinfo_dicts.codons[seq[i:... | [
"0.79057974",
"0.76611775",
"0.7121469",
"0.6961111",
"0.68622816",
"0.68331707",
"0.6547189",
"0.64678174",
"0.6421204",
"0.62824553",
"0.6257737",
"0.62457687",
"0.62001413",
"0.6168047",
"0.6160185",
"0.6150737",
"0.60523367",
"0.60273343",
"0.5976103",
"0.5961816",
"0.593... | 0.53833807 | 43 |
Unit tests for the coding_strand_to_AA function | def coding_strand_to_AA_unit_tests():
# list of [input, expected output]
data_list = [
# pass cases
["ATGCGA", "MR"],
["ATGCCCGCTTT", "MPA"],
["AAA", "K"],
["TTT", "F"],
["CCC", "P"],
["GGG", "G"],
["AAAA", "K"],
["AAAAA", "K"],
["A... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def coding_strand_to_AA_unit_tests():\n print \"input: GTTGACAGTACGTACAGGGAA, \"+\"output: \"+coding_strand_to_AA(\"GTTGACAGTACGTACAGGGAA\")+\", actual output: VDSTYRE\"\n print \"input: TTATTGCTTATTATCATG, \"+\"output: \"+coding_strand_to_AA(\"TTATTGCTTATTATCATG\")+\", actual output: LLLIIM\"\n print \"i... | [
"0.87473875",
"0.87198865",
"0.8259528",
"0.80338943",
"0.7117547",
"0.7100833",
"0.7016442",
"0.6978917",
"0.6892497",
"0.68684465",
"0.68575025",
"0.6806628",
"0.68016726",
"0.6616816",
"0.6553702",
"0.6507176",
"0.64127254",
"0.6405748",
"0.6327928",
"0.6140289",
"0.612837... | 0.83976924 | 2 |
Computes the reverse complementary sequence of DNA for the specfied DNA sequence | def get_reverse_complement(dna):
res = "";
for c in dna:
if c == 'A':
res = 'T' + res
elif c == 'T':
res = 'A' + res
elif c == 'G':
res = 'C' + res
elif c == 'C':
res = 'G' + res
return res | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_reverse_complement(dna):\n rev_comp = ''\n for i in range(0, len(dna)):\n nucleo = dna[i]\n comp = get_complement(nucleo)\n rev_comp = comp + rev_comp\n return rev_comp",
"def reverse_complement_strand(dna):\n reverse_complement = \"\"\n\n for character in dna[::-1]:\n... | [
"0.7621168",
"0.75488645",
"0.74943614",
"0.7489699",
"0.74795413",
"0.7419932",
"0.73843974",
"0.73704416",
"0.73488766",
"0.7339861",
"0.7338994",
"0.7278367",
"0.7258061",
"0.7248897",
"0.72437245",
"0.7231113",
"0.72207266",
"0.7216731",
"0.72124445",
"0.7201928",
"0.7174... | 0.75032 | 2 |
Unit tests for the get_complement function | def get_reverse_complement_unit_tests():
# list of [input, expected output]
data_list = [
["ATGCCCGCTTT", "AAAGCGGGCAT"],
["AAAGCGGGCAT", "ATGCCCGCTTT"],
["CCGCGTTCA", "TGAACGCGG"],
["AAAA", "TTTT"],
["TTTT", "AAAA"],
["CCCC", "GGGG"],
["GGGG", "CCCC"],
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_reverse_complement_unit_tests():\n \n print get_reverse_complement(\"ATGCCCGCTTT\")\n print get_reverse_complement(\"CCGCGTTCA\")\n print get_reverse_complement(\"ACCTTGGAAAATTT\")",
"def get_reverse_complement_unit_tests():\n input_a='ATTATTATT'\n expected_output='AATAATAAT'\n a... | [
"0.78032184",
"0.7330259",
"0.7222587",
"0.7113062",
"0.69564736",
"0.69260347",
"0.6924214",
"0.68408453",
"0.6719885",
"0.6579124",
"0.65708894",
"0.65301526",
"0.6491171",
"0.64767414",
"0.6465325",
"0.6416435",
"0.6400825",
"0.63780624",
"0.6311535",
"0.6303076",
"0.62991... | 0.68050754 | 8 |
Takes a DNA sequence that is assumed to begin with a start codon and returns the sequence up to but not including the first in frame stop codon. If there is no in frame stop codon, returns the whole string. | def rest_of_ORF(dna):
# [???] 'assumed to begin with a start codon': doesn't need to check input?
# if len(dna) < 3:
# return ""
# if dna[0:3] != start_codon:
# return ""
l = len(dna)
for i in range(3, l, 3):
if dna[i: i + 3] in stop_codons:
return dna[0: i]
retu... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def remove_stop_from_end(codonseq, codon_table):\n if str(codonseq[-3:]) in codon_table.stop_codons:\n #print(\"chopped\", len(CodonSeq().from_seq(codonseq[:-3])))\n return CodonSeq().from_seq(codonseq[:-3])\n elif str(codonseq[-3:]) == '---':\n #print(\"chopped\", len(CodonSeq().from_se... | [
"0.71757495",
"0.65072894",
"0.64979345",
"0.6329644",
"0.6183206",
"0.61209697",
"0.61035204",
"0.6082251",
"0.6023832",
"0.6007573",
"0.59589094",
"0.59459716",
"0.591217",
"0.5907929",
"0.57332164",
"0.57254994",
"0.5674605",
"0.563355",
"0.5596707",
"0.55794567",
"0.55748... | 0.67012167 | 1 |
Unit tests for the rest_of_ORF function | def rest_of_ORF_unit_tests():
data_list = [
["ATGTGAA", "ATG"],
["ATGAGATAGG", "ATGAGA"],
["ATG", "ATG"],
["ATGTAG", "ATG"],
["ATGTAA", "ATG"],
["ATGTGA", "ATG"],
["ATGAAATTTGGGAAATTTGGGTAG", "ATGAAATTTGGGAAATTTGGG"],
["ATGAAATTTGGG", "ATGAAATTTGGG"],
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rest_of_ORF_unit_tests():\n input_a='ATTCATTAG'\n expected_output='ATTCAT'\n actual_output=rest_of_ORF(input_a)\n print 'Expected Output is ' + expected_output\n print 'Actual Output is ' +actual_output\n \n input_a='ATTCATCATCATCATTAG'\n expected_output='ATTCATCATCATCAT'\n actual_ou... | [
"0.7736593",
"0.77165705",
"0.68423116",
"0.6646262",
"0.6569403",
"0.6511477",
"0.6402534",
"0.6199879",
"0.61139333",
"0.60930383",
"0.6042923",
"0.6042923",
"0.59909266",
"0.59864223",
"0.597569",
"0.595889",
"0.595889",
"0.595889",
"0.595889",
"0.595889",
"0.5914845",
"... | 0.7421392 | 2 |
Finds all nonnested open reading frames in the given DNA sequence and returns them as a list. This function should only find ORFs that are in the default frame of the sequence (i.e. they start on indices that are multiples of 3). By nonnested we mean that if an ORF occurs entirely within another ORF, it should not be i... | def find_all_ORFs_oneframe(dna):
res = []
l = len(dna)
next_pos = 0
while True:
arg = dna[next_pos:]
# orf = rest_of_ORF(arg)
# res.append(orf)
# if arg == orf: # if: no stop codon
# break
# next_pos = dna.index(orf, next_pos) + len(orf) + 3 # point next ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def find_all_ORFs(dna):\n index = 0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# initialize index\n all_ORFs = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitalize empty list\n while index < 3:\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# switches throught the 3 frames\n \tall_ORFs = all_ORFs + find_all_ORFs_onefr... | [
"0.69020236",
"0.67974",
"0.670461",
"0.6622766",
"0.65280724",
"0.65106666",
"0.6510072",
"0.64129376",
"0.6357248",
"0.6330139",
"0.63298523",
"0.6307531",
"0.63005555",
"0.6295105",
"0.62282884",
"0.61387193",
"0.61064196",
"0.60724497",
"0.6032787",
"0.5994004",
"0.577432... | 0.611578 | 16 |
Unit tests for the find_all_ORFs_oneframe function | def find_all_ORFs_oneframe_unit_tests():
data_list = [
["ATGCATGAATGTAGATAGATGTGCCC", ["ATGCATGAATGTAGA", "ATGTGCCC"]],
["ATGTAGATGTAG", ["ATG", "ATG"]],
["ATGATGATG", ["ATGATGATG"]],
["ATGGGGGATTAGATGATG", ["ATGGGGGAT", "ATGATG"]],
["ATGTGAATGTAA", ["ATG", "ATG"]],
[... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def find_all_ORFs_oneframe_unit_tests():\n\n # YOUR IMPLEMENTATION HERE",
"def find_all_ORFs_oneframe_unit_tests():\n input_a='ATGATTATTTGATGAATGGATTGA'\n expected_output='[ATGATTATT,ATGGAT]'\n actual_output=find_all_ORFs_oneframe(input_a)\n print 'Expected Output is ' + expected_output\n print... | [
"0.8545172",
"0.7348566",
"0.73415834",
"0.7203369",
"0.7158465",
"0.6796761",
"0.6632994",
"0.6604659",
"0.6478488",
"0.6478216",
"0.62701315",
"0.62148196",
"0.6200575",
"0.61729914",
"0.61653095",
"0.61079854",
"0.607584",
"0.60689676",
"0.6063073",
"0.59820056",
"0.594094... | 0.76647025 | 1 |
Finds all nonnested open reading frames in the given DNA sequence in all 3 possible frames and returns them as a list. By nonnested we mean that if an ORF occurs entirely within another ORF and they are both in the same frame, it should not be included in the returned list of ORFs. | def find_all_ORFs(dna):
res = []
for i in range(0, 3):
s = dna[i:]
# print i, s,
# l = len(s)
# for j in range(0, l, 3):
# if s[j: j + 3] == start_codon:
# r = find_all_ORFs_oneframe(s[j:])
# print r
# if len(r) > 0:
# ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def find_all_ORFs(dna):\n index = 0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# initialize index\n all_ORFs = []\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# intitalize empty list\n while index < 3:\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# switches throught the 3 frames\n \tall_ORFs = all_ORFs + find_all_ORFs_onefr... | [
"0.6846477",
"0.67647403",
"0.67115307",
"0.66981316",
"0.6597111",
"0.65776366",
"0.64758587",
"0.6420567",
"0.6389022",
"0.6327249",
"0.62816936",
"0.6255243",
"0.62321466",
"0.6223571",
"0.6206",
"0.6151061",
"0.61308336",
"0.6083877",
"0.6025945",
"0.5896849",
"0.5860287"... | 0.63819563 | 9 |
Unit tests for the find_all_ORFs function | def find_all_ORFs_unit_tests():
data_list = [
["ATGCATGAATGTAG", ["ATGCATGAATGTAG", "ATGAATGTAG", "ATG"]],
["ATG", ["ATG"]],
["AATG", ["ATG"]],
["AAATG", ["ATG"]],
["ATGATG", ["ATGATG"]],
["ATATGGATTGA", ["ATGGAT"]],
["ATGAGATTAG", ["ATGAGATTAG"]],
["A... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def find_all_ORFs_both_strands_unit_tests():\n\n # YOUR IMPLEMENTATION HERE",
"def find_all_ORFs_unit_tests():\n print 'Begin Unit test Find_all_ORFs'\n input_a='ATGCATGAATGTAGATGTAG'\n expected_output='[ATGCATGAATGTAGATGTAG, ATGAATGTAGATGTAG, ATG, ATG]'\n actual_output=find_all_ORFs(input_a)\n ... | [
"0.7691884",
"0.7465497",
"0.71547097",
"0.7034157",
"0.70336044",
"0.70111084",
"0.6656426",
"0.659269",
"0.65738535",
"0.6469719",
"0.6363958",
"0.6361521",
"0.6306454",
"0.6261688",
"0.62254024",
"0.6223877",
"0.6080115",
"0.6066479",
"0.6003871",
"0.597892",
"0.5960407",
... | 0.6763755 | 6 |
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