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q39100
ids_from_seqs_iterative
train
def ids_from_seqs_iterative(seqs, app, query_parser, \ scorer=keep_everything_scorer, max_iterations=None, blast_db=None,\ max_seqs=None, ): """Gets the ids from each seq, then does each additional id until all done. If scorer is passed in as an int, uses shotgun scorer with that # hits. """ if isinstance(scorer, int): scorer = make_shotgun_scorer(scorer) seqs_to_check = list(seqs) checked_ids = {} curr_iteration = 0 while seqs_to_check: unchecked_ids = {} #pass seqs to command all_output = app(seqs_to_check) output = all_output.get('BlastOut', all_output['StdOut']) for query_id, match_id, match_score in query_parser(output): if query_id not in checked_ids: checked_ids[query_id] = {} checked_ids[query_id][match_id] = match_score if match_id not in checked_ids: unchecked_ids[match_id] = True all_output.cleanUp() if unchecked_ids: seq_file = fasta_cmd_get_seqs(unchecked_ids.keys(), app.Parameters['-d'].Value)['StdOut'] seqs_to_check = [] for s in FastaCmdFinder(fasta_cmd_get_seqs(\ unchecked_ids.keys(), app.Parameters['-d'].Value)['StdOut']): seqs_to_check.extend(s) else: seqs_to_check = [] #bail out if max iterations or max seqs was defined and we've reached it curr_iteration += 1 if max_iterations and (curr_iteration >= max_iterations): break if max_seqs: curr = scorer(checked_ids) if len(curr) >= max_seqs: return curr return scorer(checked_ids)
python
{ "resource": "" }
q39101
blastp
train
def blastp(seqs, blast_db="nr", e_value="1e-20", max_hits=200, working_dir=tempfile.gettempdir(), blast_mat_root=None, extra_params={}): """ Returns BlastResult from input seqs, using blastp. Need to add doc string """ # set up params to use with blastp params = { # matrix "-M":"BLOSUM62", # max procs "-a":"1", # expectation "-e":e_value, # max seqs to show "-b":max_hits, # max one line descriptions "-v":max_hits, # program "-p":"blastp" } params.update(extra_params) # blast blast_res = blast_seqs(seqs, Blastall, blast_mat_root=blast_mat_root, blast_db=blast_db, params=params, add_seq_names=False, WorkingDir=working_dir ) # get prot id map if blast_res['StdOut']: lines = [x for x in blast_res['StdOut']] return BlastResult(lines) return None
python
{ "resource": "" }
q39102
set_lock
train
def set_lock(fname): """ Try to lock file and write PID. Return the status of operation. """ global fh fh = open(fname, 'w') if os.name == 'nt': # Code for NT systems got from: http://code.activestate.com/recipes/65203/ import win32con import win32file import pywintypes LOCK_EX = win32con.LOCKFILE_EXCLUSIVE_LOCK LOCK_SH = 0 # the default LOCK_NB = win32con.LOCKFILE_FAIL_IMMEDIATELY # is there any reason not to reuse the following structure? __overlapped = pywintypes.OVERLAPPED() hfile = win32file._get_osfhandle(fh.fileno()) try: win32file.LockFileEx(hfile, LOCK_EX | LOCK_NB, 0, -0x10000, __overlapped) except pywintypes.error as exc_value: # error: (33, 'LockFileEx', 'The process cannot access # the file because another process has locked a portion # of the file.') if exc_value[0] == 33: return False else: from fcntl import flock, LOCK_EX, LOCK_NB try: flock(fh.fileno(), LOCK_EX | LOCK_NB) except Exception as ex: return False fh.write(str(os.getpid())) fh.flush() return True
python
{ "resource": "" }
q39103
assert_lock
train
def assert_lock(fname): """ If file is locked then terminate program else lock file. """ if not set_lock(fname): logger.error('File {} is already locked. Terminating.'.format(fname)) sys.exit()
python
{ "resource": "" }
q39104
build_blast_db_from_seqs
train
def build_blast_db_from_seqs(seqs, is_protein=False, output_dir='./', HALT_EXEC=False): """Build blast db from seqs; return db name and list of files created **If using to create temporary blast databases, you can call cogent.util.misc.remove_files(db_filepaths) to clean up all the files created by formatdb when you're done with the database. seqs: sequence collection or alignment object is_protein: True if working on protein seqs (default: False) output_dir: directory where output should be written (default: current directory) HALT_EXEC: halt just before running the formatdb command and print the command -- useful for debugging """ # Build a temp filepath _, tmp_fasta_filepath = mkstemp(prefix='Blast_tmp_db', suffix='.fasta') # open the temp file tmp_fasta_file = open(tmp_fasta_filepath, 'w') # write the sequence collection to file tmp_fasta_file.write(seqs.toFasta()) tmp_fasta_file.close() # build the bast database db_name, db_filepaths = build_blast_db_from_fasta_path(tmp_fasta_filepath, is_protein=is_protein, output_dir=output_dir, HALT_EXEC=HALT_EXEC) # clean-up the temporary file remove(tmp_fasta_filepath) # return the results return db_name, db_filepaths
python
{ "resource": "" }
q39105
RedisSessionMiddleware._session_key
train
def _session_key(self): """Gets the redis key for a session""" if not hasattr(self, "_cached_session_key"): session_id_bytes = self.get_secure_cookie("session_id") session_id = None if session_id_bytes: try: session_id = session_id_bytes.decode('utf-8') except: pass if not session_id: session_id = oz.redis_sessions.random_hex(20) session_time = oz.settings["session_time"] kwargs = dict( name="session_id", value=session_id.encode('utf-8'), domain=oz.settings.get("cookie_domain"), httponly=True, ) if session_time: kwargs["expires_days"] = round(session_time/60/60/24) self.set_secure_cookie(**kwargs) password_salt = oz.settings["session_salt"] self._cached_session_key = "session:%s:v4" % oz.redis_sessions.password_hash(session_id, password_salt=password_salt) return self._cached_session_key
python
{ "resource": "" }
q39106
RedisSessionMiddleware._update_session_expiration
train
def _update_session_expiration(self): """ Updates a redis item to expire later since it has been interacted with recently """ session_time = oz.settings["session_time"] if session_time: self.redis().expire(self._session_key, session_time)
python
{ "resource": "" }
q39107
RedisSessionMiddleware.get_session_value
train
def get_session_value(self, name, default=None): """Gets a session value""" value = self.redis().hget(self._session_key, name) or default self._update_session_expiration() return value
python
{ "resource": "" }
q39108
RedisSessionMiddleware.set_session_value
train
def set_session_value(self, name, value): """Sets a session value""" self.redis().hset(self._session_key, name, value) self._update_session_expiration()
python
{ "resource": "" }
q39109
RedisSessionMiddleware.clear_session_value
train
def clear_session_value(self, name): """Removes a session value""" self.redis().hdel(self._session_key, name) self._update_session_expiration()
python
{ "resource": "" }
q39110
rewrite_middleware
train
async def rewrite_middleware(server, request): ''' Sanic middleware that utilizes a security class's "rewrite" method to check ''' if singletons.settings.SECURITY is not None: security_class = singletons.settings.load('SECURITY') else: security_class = DummySecurity security = security_class() try: new_path = await security.rewrite(request) except SecurityException as e: msg = '' if DEBUG: msg = str(e) return server.response.text(msg, status=400) request.path = new_path
python
{ "resource": "" }
q39111
Commit.get_objects
train
def get_objects(self, uri, pull=True, **kwargs): ''' Walk through repo commits to generate a list of repo commit objects. Each object has the following properties: * repo uri * general commit info * files added, removed fnames * lines added, removed * acked_by * signed_off_by * resolves * related ''' self.repo = repo = git_clone(uri, pull=pull, reflect=True) # get a full list of all commit SHAs in the repo (all branches) cmd = 'git rev-list --all' output = sys_call(cmd, cwd=repo.path) repo_shas = set(x.strip() for x in output.split('\n') if x) logger.debug("Total Commits: %s" % len(repo_shas)) cmd = 'git --no-pager log --all --format=sha:%H --numstat' output = sys_call(cmd) all_logs = re.sub('\n+', '\n', output) c_logs = [x for x in [s.strip() for s in all_logs.split('sha:')] if x] _end = None # once was true, always is true... objs = [] for c_log in c_logs: sha, s, all_changes = c_log.partition('\n') #try: c = repo.get_object(sha) # FIXME: not normalizing to UTC _start = ts2dt(c.commit_time) #except Exception as e: # _start = now # obj = dict(_oid=sha, _start=_start, _end=_end, # repo_uri=uri, _e={sha: to_encoding(e)}) # self.objects.add(obj) # continue # and some basic stuff... obj = dict(_oid=sha, _start=_start, _end=_end, repo_uri=uri, tree=c.tree, parents=c.parents, author=c.author, committer=c.committer, author_time=c.author_time, message=c.message, mergetag=c.mergetag, extra=c.extra) for _file in all_changes.split('\n'): _file = _file.strip() obj.setdefault('files', {}) if not _file: added, removed, fname = 0, 0, None else: added, removed, fname = _file.split('\t') added = 0 if added == '-' else int(added) removed = 0 if removed == '-' else int(removed) # FIXME: sql doesn't nest well.. changes = {'added': added, 'removed': removed} obj['files'][fname] = changes # file +/- totals obj['added'] = sum( [v.get('added', 0) for v in obj['files'].itervalues()]) obj['removed'] = sum( [v.get('removed', 0) for v in obj['files'].itervalues()]) # extract interesting bits from the message obj['acked_by'] = acked_by_re.findall(c.message) obj['signed_off_by'] = signed_off_by_re.findall(c.message) obj['resolves'] = resolves_re.findall(c.message) obj['related'] = related_re.findall(c.message) objs.append(obj) self.objects.extend(objs) return super(Commit, self).get_objects(**kwargs)
python
{ "resource": "" }
q39112
_dict_values_sorted_by_key
train
def _dict_values_sorted_by_key(dictionary): # This should be a yield from instead. """Internal helper to return the values of a dictionary, sorted by key. """ for _, value in sorted(dictionary.iteritems(), key=operator.itemgetter(0)): yield value
python
{ "resource": "" }
q39113
_ondemand
train
def _ondemand(f): """Decorator to only request information if not in cache already. """ name = f.__name__ def func(self, *args, **kwargs): if not args and not kwargs: if hasattr(self, '_%s' % name): return getattr(self, '_%s' % name) a = f(self, *args, **kwargs) setattr(self, '_%s' % name, a) return a else: return f(self, *args, **kwargs) func.__name__ = name return func
python
{ "resource": "" }
q39114
CachedIDAMemory.get_memory
train
def get_memory(self, start, size): """Retrieve an area of memory from IDA. Returns a sparse dictionary of address -> value. """ LOG.debug('get_memory: %d bytes from %x', size, start) return get_memory(self.ida.idaapi, start, size, default_byte=self.default_byte)
python
{ "resource": "" }
q39115
handle_404
train
def handle_404(request, exception): '''Handle 404 Not Found This handler should be used to handle error http 404 not found for all endpoints or if resource not available. ''' error = format_error(title='Resource not found', detail=str(exception)) return json(return_an_error(error), status=HTTPStatus.NOT_FOUND)
python
{ "resource": "" }
q39116
_add_to_dict
train
def _add_to_dict(t, container, name, value): """ Adds an item to a dictionary, or raises an exception if an item with the specified key already exists in the dictionary. """ if name in container: raise Exception("%s '%s' already exists" % (t, name)) else: container[name] = value
python
{ "resource": "" }
q39117
RequestHandler.trigger
train
def trigger(self, name, *args, **kwargs): """ Triggers an event to run through middleware. This method will execute a chain of relevant trigger callbacks, until one of the callbacks returns the `break_trigger`. """ # Relevant middleware is cached so we don't have to rediscover it # every time. Fetch the cached value if possible. listeners = self._triggers.get(name, []) # Execute each piece of middleware for listener in listeners: result = listener(*args, **kwargs) if result == break_trigger: return False return True
python
{ "resource": "" }
q39118
Resource.cache_makedirs
train
def cache_makedirs(self, subdir=None): ''' Make necessary directories to hold cache value ''' if subdir is not None: dirname = self.cache_path if subdir: dirname = os.path.join(dirname, subdir) else: dirname = os.path.dirname(self.cache_path) os.makedirs(dirname, exist_ok=True)
python
{ "resource": "" }
q39119
session
train
def session(connection_string=None): """Gets a SQLAlchemy session""" global _session_makers connection_string = connection_string or oz.settings["db"] if not connection_string in _session_makers: _session_makers[connection_string] = sessionmaker(bind=engine(connection_string=connection_string)) return _session_makers[connection_string]()
python
{ "resource": "" }
q39120
assign_dna_reads_to_dna_database
train
def assign_dna_reads_to_dna_database(query_fasta_fp, database_fasta_fp, output_fp, params=None): """Assign DNA reads to a database fasta of DNA sequences. Wraps assign_reads_to_database, setting database and query types. All parameters are set to default unless params is passed. query_fasta_fp: absolute path to the query fasta file containing DNA sequences. database_fasta_fp: absolute path to the database fasta file containing DNA sequences. output_fp: absolute path where the output file will be generated. params: optional. dict containing parameter settings to be used instead of default values. Cannot change database or query file types from dna and dna, respectively. This method returns an open file object. The output format defaults to blast9 and should be parsable by the PyCogent BLAST parsers. """ if params is None: params = {} my_params = {'-t': 'dna', '-q': 'dna' } # if the user specified parameters other than default, then use them. # However, if they try to change the database or query types, raise an # applciation error. if '-t' in params or '-q' in params: raise ApplicationError("Cannot change database or query types when " + "using assign_dna_reads_to_dna_database. " + "Use assign_reads_to_database instead.\n") my_params.update(params) result = assign_reads_to_database(query_fasta_fp, database_fasta_fp, output_fp, my_params) return result
python
{ "resource": "" }
q39121
assign_dna_reads_to_protein_database
train
def assign_dna_reads_to_protein_database(query_fasta_fp, database_fasta_fp, output_fp, temp_dir="/tmp", params=None): """Assign DNA reads to a database fasta of protein sequences. Wraps assign_reads_to_database, setting database and query types. All parameters are set to default unless params is passed. A temporary file must be written containing the translated sequences from the input query fasta file because BLAT cannot do this automatically. query_fasta_fp: absolute path to the query fasta file containing DNA sequences. database_fasta_fp: absolute path to the database fasta file containing protein sequences. output_fp: absolute path where the output file will be generated. temp_dir: optional. Change the location where the translated sequences will be written before being used as the query. Defaults to /tmp. params: optional. dict containing parameter settings to be used instead of default values. Cannot change database or query file types from protein and dna, respectively. This method returns an open file object. The output format defaults to blast9 and should be parsable by the PyCogent BLAST parsers. """ if params is None: params = {} my_params = {'-t': 'prot', '-q': 'prot'} # make sure temp_dir specifies an absolute path if not isabs(temp_dir): raise ApplicationError("temp_dir must be an absolute path.") # if the user specified parameters other than default, then use them. # However, if they try to change the database or query types, raise an # applciation error. if '-t' in params or '-q' in params: raise ApplicationError("Cannot change database or query types " "when using assign_dna_reads_to_dna_database. Use " "assign_reads_to_database instead.") if 'genetic_code' in params: my_genetic_code = GeneticCodes[params['genetic_code']] del params['genetic_code'] else: my_genetic_code = GeneticCodes[1] my_params.update(params) # get six-frame translation of the input DNA sequences and write them to # temporary file. _, tmp = mkstemp(dir=temp_dir) tmp_out = open(tmp, 'w') for label, sequence in parse_fasta(open(query_fasta_fp)): seq_id = label.split()[0] s = DNA.makeSequence(sequence) translations = my_genetic_code.sixframes(s) frames = [1, 2, 3, -1, -2, -3] translations = dict(zip(frames, translations)) for frame, translation in sorted(translations.iteritems()): entry = '>{seq_id}_frame_{frame}\n{trans}\n' entry = entry.format(seq_id=seq_id, frame=frame, trans=translation) tmp_out.write(entry) tmp_out.close() result = assign_reads_to_database(tmp, database_fasta_fp, output_fp, params=my_params) remove(tmp) return result
python
{ "resource": "" }
q39122
Blat._get_base_command
train
def _get_base_command(self): """Gets the command that will be run when the app controller is called. """ command_parts = [] cd_command = ''.join(['cd ', str(self.WorkingDir), ';']) if self._command is None: raise ApplicationError('_command has not been set.') command = self._command parameters = sorted([str(x) for x in self.Parameters.values() if str(x)]) synonyms = self._synonyms command_parts.append(cd_command) command_parts.append(command) command_parts.append(self._database) # Positional argument command_parts.append(self._query) # Positional argument command_parts += parameters if self._output: command_parts.append(self._output.Path) # Positional return ( self._command_delimiter.join(filter(None, command_parts)).strip() )
python
{ "resource": "" }
q39123
woa_profile_from_dap
train
def woa_profile_from_dap(var, d, lat, lon, depth, cfg): """ Monthly Climatologic Mean and Standard Deviation from WOA, used either for temperature or salinity. INPUTS time: [day of the year] lat: [-90<lat<90] lon: [-180<lon<180] depth: [meters] Reads the WOA Monthly Climatology NetCDF file and returns the corresponding WOA values of salinity or temperature mean and standard deviation for the given time, lat, lon, depth. """ if lon < 0: lon = lon+360 url = cfg['url'] doy = int(d.strftime('%j')) dataset = open_url(url) dn = (np.abs(doy-dataset['time'][:])).argmin() xn = (np.abs(lon-dataset['lon'][:])).argmin() yn = (np.abs(lat-dataset['lat'][:])).argmin() if re.match("temperature\d?$", var): mn = ma.masked_values(dataset.t_mn.t_mn[dn, :, yn, xn].reshape( dataset['depth'].shape[0]), dataset.t_mn.attributes['_FillValue']) sd = ma.masked_values(dataset.t_sd.t_sd[dn, :, yn, xn].reshape( dataset['depth'].shape[0]), dataset.t_sd.attributes['_FillValue']) # se = ma.masked_values(dataset.t_se.t_se[dn, :, yn, xn].reshape( # dataset['depth'].shape[0]), dataset.t_se.attributes['_FillValue']) # Use this in the future. A minimum # of samples # dd = ma.masked_values(dataset.t_dd.t_dd[dn, :, yn, xn].reshape( # dataset['depth'].shape[0]), dataset.t_dd.attributes['_FillValue']) elif re.match("salinity\d?$", var): mn = ma.masked_values(dataset.s_mn.s_mn[dn, :, yn, xn].reshape( dataset['depth'].shape[0]), dataset.s_mn.attributes['_FillValue']) sd = ma.masked_values(dataset.s_sd.s_sd[dn, :, yn, xn].reshape( dataset['depth'].shape[0]), dataset.s_sd.attributes['_FillValue']) # dd = ma.masked_values(dataset.s_dd.s_dd[dn, :, yn, xn].reshape( # dataset['depth'].shape[0]), dataset.s_dd.attributes['_FillValue']) zwoa = ma.array(dataset.depth[:]) ind = (depth <= zwoa.max()) & (depth >= zwoa.min()) # Mean value profile f = interp1d(zwoa[~ma.getmaskarray(mn)].compressed(), mn.compressed()) mn_interp = ma.masked_all(depth.shape) mn_interp[ind] = f(depth[ind]) # The stdev profile f = interp1d(zwoa[~ma.getmaskarray(sd)].compressed(), sd.compressed()) sd_interp = ma.masked_all(depth.shape) sd_interp[ind] = f(depth[ind]) output = {'woa_an': mn_interp, 'woa_sd': sd_interp} return output
python
{ "resource": "" }
q39124
DatabaseCollection.iterator
train
def iterator(cls, path=None, objtype=None, query=None, page_size=1000, **kwargs): """" Linear time, constant memory, iterator for a mongo collection. @param path: the path of the database to query, in the form "database.colletion"; pass None to use the value of the PATH property of the object or, if that is none, the PATH property of OBJTYPE @param objtype: the object type to use for these DatabaseObjects; pass None to use the OBJTYPE property of the class @param query: a dictionary specifying key-value pairs that the result must match. If query is None, use kwargs in it's place @param page_size: the number of items to fetch per page of iteration @param **kwargs: used as query parameters if query is None """ if not objtype: objtype = cls.OBJTYPE if not path: path = cls.PATH db = objtype.db(path) if not query: query = kwargs results = list(db.find(query).sort(ID_KEY, ASCENDING).limit(page_size)) while results: page = [objtype(path=path, _new_object=result) for result in results] for obj in page: yield obj query[ID_KEY] = {GT: results[-1][ID_KEY]} results = list(db.find(query).sort(ID_KEY, ASCENDING).limit(page_size))
python
{ "resource": "" }
q39125
pair_hmm_align_unaligned_seqs
train
def pair_hmm_align_unaligned_seqs(seqs, moltype=DNA_cogent, params={}): """ Checks parameters for pairwise alignment, returns alignment. Code from Greg Caporaso. """ seqs = LoadSeqs(data=seqs, moltype=moltype, aligned=False) try: s1, s2 = seqs.values() except ValueError: raise ValueError( "Pairwise aligning of seqs requires exactly two seqs.") try: gap_open = params['gap_open'] except KeyError: gap_open = 5 try: gap_extend = params['gap_extend'] except KeyError: gap_extend = 2 try: score_matrix = params['score_matrix'] except KeyError: score_matrix = make_dna_scoring_dict( match=1, transition=-1, transversion=-1) return local_pairwise(s1, s2, score_matrix, gap_open, gap_extend)
python
{ "resource": "" }
q39126
viewers_js
train
async def viewers_js(request): ''' Viewers determines the viewers installed based on settings, then uses the conversion infrastructure to convert all these JS files into a single JS bundle, that is then served. As with media, it will simply serve a cached version if necessary. ''' # Generates single bundle as such: # BytesResource -> ViewerNodePackageBuilder -> nodepackage -> ... -> min.js response = singletons.server.response # Create a viewers resource, which is simply a JSON encoded description of # the viewers necessary for this viewers bundle. viewers_resource = singletons.viewers.get_resource() url_string = viewers_resource.url_string target_ts = TypeString('min.js') # get a minified JS bundle target_resource = TypedResource(url_string, target_ts) if target_resource.cache_exists(): return await response.file(target_resource.cache_path, headers={ 'Content-Type': 'application/javascript', }) # Otherwise, does not exist, save this descriptor to cache and kick off # conversion process if not viewers_resource.cache_exists(): viewers_resource.save() # Queue up a single function that will in turn queue up conversion process await singletons.workers.async_enqueue_sync( enqueue_conversion_path, url_string, str(target_ts), singletons.workers.enqueue_convert ) return response.text(NOT_LOADED_JS, headers={ 'Content-Type': 'application/javascript', })
python
{ "resource": "" }
q39127
Rows.get_objects
train
def get_objects(self, uri, _oid=None, _start=None, _end=None, load_kwargs=None, **kwargs): ''' Load and transform csv data into a list of dictionaries. Each row in the csv will result in one dictionary in the list. :param uri: uri (file://, http(s)://) of csv file to load :param _oid: column or func to apply to map _oid in all resulting objects :param _start: column or func to apply to map _start in all resulting objects :param _end: column or func to apply to map _end in all resulting objects :param kwargs: kwargs to pass to pandas.read_csv method _start and _oid arguments can be a column name or a function which accepts a single argument -- the row being extracted. If either is a column name (string) then that column will be applied as _oid for each object generated. If either is a function, the function will be applied per each row and the result of the function will be assigned to the _start or _oid, respectively. ''' load_kwargs = load_kwargs or {} objects = load(path=uri, filetype='csv', **load_kwargs) k = itertools.count(1) now = utcnow() __oid = lambda o: k.next() _oid = _oid or __oid _start = _start or now _end = _end or None def is_callable(v): _v = type(v) _ = True if _v is type or hasattr(v, '__call__') else False return _ for obj in objects: obj['_oid'] = _oid(obj) if is_callable(_oid) else _oid obj['_start'] = _start(obj) if is_callable(_start) else _start obj['_end'] = _end(obj) if is_callable(_end) else _end self.container.add(obj) return super(Rows, self).get_objects(**kwargs)
python
{ "resource": "" }
q39128
vsearch_dereplicate_exact_seqs
train
def vsearch_dereplicate_exact_seqs( fasta_filepath, output_filepath, output_uc=False, working_dir=None, strand="both", maxuniquesize=None, minuniquesize=None, sizein=False, sizeout=True, log_name="derep.log", HALT_EXEC=False): """ Generates clusters and fasta file of dereplicated subsequences Parameters ---------- fasta_filepath : string input filepath of fasta file to be dereplicated output_filepath : string write the dereplicated sequences to output_filepath working_dir : string, optional directory path for storing intermediate output output_uc : boolean, optional uutput dereplication results in a file using a uclust-like format strand : string, optional when searching for strictly identical sequences, check the 'strand' only (default: both) or check the plus strand only maxuniquesize : integer, optional discard sequences with an abundance value greater than maxuniquesize minuniquesize : integer, optional discard sequences with an abundance value smaller than integer sizein : boolean, optional take into account the abundance annotations present in the input fasta file, (search for the pattern "[>;]size=integer[;]" in sequence headers) sizeout : boolean, optional add abundance annotations to the output fasta file (add the pattern ";size=integer;" to sequence headers) log_name : string, optional specifies log filename HALT_EXEC : boolean, optional used for debugging app controller Return ------ output_filepath : string filepath to dereplicated fasta file uc_filepath : string filepath to dereplication results in uclust-like format log_filepath : string filepath to log file """ # write all vsearch output files to same directory # as output_filepath if working_dir is not specified if not working_dir: working_dir = dirname(abspath(output_filepath)) app = Vsearch(WorkingDir=working_dir, HALT_EXEC=HALT_EXEC) log_filepath = join(working_dir, log_name) uc_filepath = None if output_uc: root_name = splitext(abspath(output_filepath))[0] uc_filepath = join(working_dir, '%s.uc' % root_name) app.Parameters['--uc'].on(uc_filepath) if maxuniquesize: app.Parameters['--maxuniquesize'].on(maxuniquesize) if minuniquesize: app.Parameters['--minuniquesize'].on(minuniquesize) if sizein: app.Parameters['--sizein'].on() if sizeout: app.Parameters['--sizeout'].on() if (strand == "both" or strand == "plus"): app.Parameters['--strand'].on(strand) else: raise ValueError("Option --strand accepts only 'both'" "or 'plus' values") app.Parameters['--derep_fulllength'].on(fasta_filepath) app.Parameters['--output'].on(output_filepath) app.Parameters['--log'].on(log_filepath) app_result = app() return output_filepath, uc_filepath, log_filepath
python
{ "resource": "" }
q39129
PaaSProvider.init
train
def init(cls, site): """ put site settings in the header of the script """ bash_header = "" for k,v in site.items(): bash_header += "%s=%s" % (k.upper(), v) bash_header += '\n' site['bash_header'] = bash_header # TODO: execute before_deploy # P.S. running init_before seems like impossible, because the file hasn't been rendered. if cls.git_template: # do render from git repo print "Cloning template files..." repo_local_copy = utils.clone_git_repo(cls.git_template_url) print "Rendering files from templates..." target_path = os.getcwd() settings_dir = '/'.join(site['django_settings'].split('.')[:-1]) site['project_name'] = settings_dir.replace('/', '.') settings_dir_path = target_path if settings_dir: settings_dir_path += '/' + settings_dir utils.render_from_repo(repo_local_copy, target_path, site, settings_dir_path) else: cls._create_configs(site) print cls.setup_instructions # TODO: execute after_deploy run_hooks('init_after')
python
{ "resource": "" }
q39130
PaaSProvider._render_config
train
def _render_config(cls, dest, template_name, template_args): """ Renders and writes a template_name to a dest given some template_args. This is for platform-specific configurations """ template_args = template_args.copy() # Substitute values here pyversion = template_args['pyversion'] template_args['pyversion'] = cls.PYVERSIONS[pyversion] template = template_env.get_template(template_name) contents = template.render(**template_args) _write_file(dest, contents)
python
{ "resource": "" }
q39131
CommandParser.parse_args_to_action_args
train
def parse_args_to_action_args(self, argv=None): ''' Parses args and returns an action and the args that were parsed ''' args = self.parse_args(argv) action = self.subcommands[args.subcommand][1] return action, args
python
{ "resource": "" }
q39132
CommandParser.register_subparser
train
def register_subparser(self, action, name, description='', arguments={}): ''' Registers a new subcommand with a given function action. If the function action is synchronous ''' action = coerce_to_synchronous(action) opts = [] for flags, kwargs in arguments.items(): if isinstance(flags, str): flags = tuple([flags]) opts.append((flags, kwargs)) self.subcommands[name] = (description, action, opts)
python
{ "resource": "" }
q39133
CommandParser.subcommand
train
def subcommand(self, description='', arguments={}): ''' Decorator for quickly adding subcommands to the omnic CLI ''' def decorator(func): self.register_subparser( func, func.__name__.replace('_', '-'), description=description, arguments=arguments, ) return func return decorator
python
{ "resource": "" }
q39134
CommandParser.print
train
def print(self, *args, **kwargs): ''' Utility function that behaves identically to 'print' except it only prints if verbose ''' if self._last_args and self._last_args.verbose: print(*args, **kwargs)
python
{ "resource": "" }
q39135
process_uclust_pw_alignment_results
train
def process_uclust_pw_alignment_results(fasta_pairs_lines, uc_lines): """ Process results of uclust search and align """ alignments = get_next_two_fasta_records(fasta_pairs_lines) for hit in get_next_record_type(uc_lines, 'H'): matching_strand = hit[4] if matching_strand == '-': strand_id = '-' target_rev_match = True elif matching_strand == '+': strand_id = '+' target_rev_match = False elif matching_strand == '.': # protein sequence, so no strand information strand_id = '' target_rev_match = False else: raise UclustParseError("Unknown strand type: %s" % matching_strand) uc_query_id = hit[8] uc_target_id = hit[9] percent_id = float(hit[3]) fasta_pair = alignments.next() fasta_query_id = fasta_pair[0][0] aligned_query = fasta_pair[0][1] if fasta_query_id != uc_query_id: raise UclustParseError("Order of fasta and uc files do not match." + " Got query %s but expected %s." % (fasta_query_id, uc_query_id)) fasta_target_id = fasta_pair[1][0] aligned_target = fasta_pair[1][1] if fasta_target_id != uc_target_id + strand_id: raise UclustParseError("Order of fasta and uc files do not match." + " Got target %s but expected %s." % (fasta_target_id, uc_target_id + strand_id)) if target_rev_match: query_id = uc_query_id + ' RC' aligned_query = DNA.rc(aligned_query) target_id = uc_target_id aligned_target = DNA.rc(aligned_target) else: query_id = uc_query_id aligned_query = aligned_query target_id = uc_target_id aligned_target = aligned_target yield (query_id, target_id, aligned_query, aligned_target, percent_id)
python
{ "resource": "" }
q39136
uclust_search_and_align_from_fasta_filepath
train
def uclust_search_and_align_from_fasta_filepath( query_fasta_filepath, subject_fasta_filepath, percent_ID=0.75, enable_rev_strand_matching=True, max_accepts=8, max_rejects=32, tmp_dir=gettempdir(), HALT_EXEC=False): """ query seqs against subject fasta using uclust, return global pw alignment of best match """ # Explanation of parameter settings # id - min percent id to count a match # maxaccepts = 8 , searches for best match rather than first match # (0 => infinite accepts, or good matches before # quitting search) # maxaccepts = 32, # libonly = True , does not add sequences to the library if they don't # match something there already. this effectively makes # uclust a search tool rather than a clustering tool params = {'--id': percent_ID, '--maxaccepts': max_accepts, '--maxrejects': max_rejects, '--libonly': True, '--lib': subject_fasta_filepath, '--tmpdir': tmp_dir} if enable_rev_strand_matching: params['--rev'] = True # instantiate the application controller app = Uclust(params, TmpDir=tmp_dir, HALT_EXEC=HALT_EXEC) # apply uclust _, alignment_filepath = mkstemp(dir=tmp_dir, prefix='uclust_alignments', suffix='.fasta') _, uc_filepath = mkstemp(dir=tmp_dir, prefix='uclust_results', suffix='.uc') input_data = {'--input': query_fasta_filepath, '--fastapairs': alignment_filepath, '--uc': uc_filepath} app_result = app(input_data) # yield the pairwise alignments for result in process_uclust_pw_alignment_results( app_result['PairwiseAlignments'], app_result['ClusterFile']): try: yield result except GeneratorExit: break # clean up the temp files that were generated app_result.cleanUp() return
python
{ "resource": "" }
q39137
uclust_cluster_from_sorted_fasta_filepath
train
def uclust_cluster_from_sorted_fasta_filepath( fasta_filepath, uc_save_filepath=None, percent_ID=0.97, max_accepts=1, max_rejects=8, stepwords=8, word_length=8, optimal=False, exact=False, suppress_sort=False, enable_rev_strand_matching=False, subject_fasta_filepath=None, suppress_new_clusters=False, stable_sort=False, tmp_dir=gettempdir(), HALT_EXEC=False): """ Returns clustered uclust file from sorted fasta""" output_filepath = uc_save_filepath if not output_filepath: _, output_filepath = mkstemp(dir=tmp_dir, prefix='uclust_clusters', suffix='.uc') params = {'--id': percent_ID, '--maxaccepts': max_accepts, '--maxrejects': max_rejects, '--stepwords': stepwords, '--w': word_length, '--tmpdir': tmp_dir} app = Uclust(params, TmpDir=tmp_dir, HALT_EXEC=HALT_EXEC) # Set any additional parameters specified by the user if enable_rev_strand_matching: app.Parameters['--rev'].on() if optimal: app.Parameters['--optimal'].on() if exact: app.Parameters['--exact'].on() if suppress_sort: app.Parameters['--usersort'].on() if subject_fasta_filepath: app.Parameters['--lib'].on(subject_fasta_filepath) if suppress_new_clusters: app.Parameters['--libonly'].on() if stable_sort: app.Parameters['--stable_sort'].on() app_result = app({'--input': fasta_filepath, '--uc': output_filepath}) return app_result
python
{ "resource": "" }
q39138
get_clusters_from_fasta_filepath
train
def get_clusters_from_fasta_filepath( fasta_filepath, original_fasta_path, percent_ID=0.97, max_accepts=1, max_rejects=8, stepwords=8, word_length=8, optimal=False, exact=False, suppress_sort=False, output_dir=None, enable_rev_strand_matching=False, subject_fasta_filepath=None, suppress_new_clusters=False, return_cluster_maps=False, stable_sort=False, tmp_dir=gettempdir(), save_uc_files=True, HALT_EXEC=False): """ Main convenience wrapper for using uclust to generate cluster files A source fasta file is required for the fasta_filepath. This will be sorted to be in order of longest to shortest length sequences. Following this, the sorted fasta file is used to generate a cluster file in the uclust (.uc) format. Next the .uc file is converted to cd-hit format (.clstr). Finally this file is parsed and returned as a list of lists, where each sublist a cluster of sequences. If an output_dir is specified, the intermediate files will be preserved, otherwise all files created are temporary and will be deleted at the end of this function The percent_ID parameter specifies the percent identity for a clusters, i.e., if 99% were the parameter, all sequences that were 99% identical would be grouped as a cluster. """ # Create readable intermediate filenames if they are to be kept fasta_output_filepath = None uc_output_filepath = None cd_hit_filepath = None if output_dir and not output_dir.endswith('/'): output_dir += '/' if save_uc_files: uc_save_filepath = get_output_filepaths( output_dir, original_fasta_path) else: uc_save_filepath = None sorted_fasta_filepath = "" uc_filepath = "" clstr_filepath = "" # Error check in case any app controller fails files_to_remove = [] try: if not suppress_sort: # Sort fasta input file from largest to smallest sequence sort_fasta = uclust_fasta_sort_from_filepath(fasta_filepath, output_filepath=fasta_output_filepath) # Get sorted fasta name from application wrapper sorted_fasta_filepath = sort_fasta['Output'].name files_to_remove.append(sorted_fasta_filepath) else: sort_fasta = None sorted_fasta_filepath = fasta_filepath # Generate uclust cluster file (.uc format) uclust_cluster = uclust_cluster_from_sorted_fasta_filepath( sorted_fasta_filepath, uc_save_filepath, percent_ID=percent_ID, max_accepts=max_accepts, max_rejects=max_rejects, stepwords=stepwords, word_length=word_length, optimal=optimal, exact=exact, suppress_sort=suppress_sort, enable_rev_strand_matching=enable_rev_strand_matching, subject_fasta_filepath=subject_fasta_filepath, suppress_new_clusters=suppress_new_clusters, stable_sort=stable_sort, tmp_dir=tmp_dir, HALT_EXEC=HALT_EXEC) # Get cluster file name from application wrapper remove_files(files_to_remove) except ApplicationError: remove_files(files_to_remove) raise ApplicationError('Error running uclust. Possible causes are ' 'unsupported version (current supported version is v1.2.22) is installed or ' 'improperly formatted input file was provided') except ApplicationNotFoundError: remove_files(files_to_remove) raise ApplicationNotFoundError('uclust not found, is it properly ' + 'installed?') # Get list of lists for each cluster clusters, failures, seeds = \ clusters_from_uc_file(uclust_cluster['ClusterFile']) # Remove temp files unless user specifies output filepath if not save_uc_files: uclust_cluster.cleanUp() if return_cluster_maps: return clusters, failures, seeds else: return clusters.values(), failures, seeds
python
{ "resource": "" }
q39139
Generic._activity_import_doc
train
def _activity_import_doc(self, time_doc, activities): ''' Import activities for a single document into timeline. ''' batch_updates = [time_doc] # We want to consider only activities that happend before time_doc # do not move this, because time_doc._start changes # time_doc['_start'] is a timestamp, whereas act[0] is a datetime # we need to be sure to convert act[0] (when) to timestamp! td_start = time_doc['_start'] activities = filter(lambda act: (act[0] < td_start and act[1] in time_doc), activities) creation_field = self.lconfig.get('cfield') # make sure that activities are sorted by when descending activities.sort(reverse=True, key=lambda o: o[0]) new_doc = {} for when, field, removed, added in activities: last_doc = batch_updates.pop() # check if this activity happened at the same time as the last one, # if it did then we need to group them together if last_doc['_end'] == when: new_doc = deepcopy(last_doc) last_doc = batch_updates.pop() else: new_doc = deepcopy(last_doc) new_doc['_start'] = when new_doc['_end'] = when last_doc['_start'] = when last_val = last_doc[field] new_val, inconsistent = self._activity_backwards(new_doc[field], removed, added) new_doc[field] = new_val # Check if the object has the correct field value. if inconsistent: self._log_inconsistency(last_doc, last_val, field, removed, added, when) new_doc['_e'] = {} if not new_doc.get('_e') else new_doc['_e'] # set curreupted field value to the the value that was added # and continue processing as if that issue didn't exist new_doc['_e'][field] = added # Add the objects to the batch batch_updates.extend([last_doc, new_doc]) # try to set the _start of the first version to the creation time try: # set start to creation time if available last_doc = batch_updates[-1] if creation_field: # again, we expect _start to be epoch float... creation_ts = dt2ts(last_doc[creation_field]) if creation_ts < last_doc['_start']: last_doc['_start'] = creation_ts elif len(batch_updates) == 1: # we have only one version, that we did not change return [] else: pass # leave as-is except Exception as e: logger.error('Error updating creation time; %s' % e) return batch_updates
python
{ "resource": "" }
q39140
Generic.get_changed_oids
train
def get_changed_oids(self, last_update=None): ''' Returns a list of object ids of those objects that have changed since `mtime`. This method expects that the changed objects can be determined based on the `delta_mtime` property of the cube which specifies the field name that carries the time of the last change. This method is expected to be overriden in the cube if it is not possible to use a single field to determine the time of the change and if another approach of determining the oids is available. In such cubes the `delta_mtime` property is expected to be set to `True`. If `delta_mtime` evaluates to False then this method is not expected to be used. :param mtime: datetime string used as 'change since date' ''' mtime_columns = self.lconfig.get('delta_mtime', []) if not (mtime_columns and last_update): return [] mtime_columns = str2list(mtime_columns) where = [] for _column in mtime_columns: _sql = "%s >= %s" % (_column, last_update) where.append(_sql) return self.sql_get_oids(where)
python
{ "resource": "" }
q39141
Generic.get_objects
train
def get_objects(self, force=None, last_update=None, flush=False): ''' Extract routine for SQL based cubes. :param force: for querying for all objects (True) or only those passed in as list :param last_update: manual override for 'changed since date' ''' return self._run_object_import(force=force, last_update=last_update, flush=flush, full_history=False)
python
{ "resource": "" }
q39142
Generic.get_new_oids
train
def get_new_oids(self): ''' Returns a list of unique oids that have not been extracted yet. Essentially, a diff of distinct oids in the source database compared to cube. ''' table = self.lconfig.get('table') _oid = self.lconfig.get('_oid') if is_array(_oid): _oid = _oid[0] # get the db column, not the field alias last_id = self.container.get_last_field(field='_oid') ids = [] if last_id: try: # try to convert to integer... if not, assume unicode value last_id = float(last_id) where = "%s.%s > %s" % (table, _oid, last_id) except (TypeError, ValueError): where = "%s.%s > '%s'" % (table, _oid, last_id) ids = self.sql_get_oids(where) return ids
python
{ "resource": "" }
q39143
Generic.get_full_history
train
def get_full_history(self, force=None, last_update=None, flush=False): ''' Fields change depending on when you run activity_import, such as "last_updated" type fields which don't have activity being tracked, which means we'll always end up with different hash values, so we need to always remove all existing object states and import fresh ''' return self._run_object_import(force=force, last_update=last_update, flush=flush, full_history=True)
python
{ "resource": "" }
q39144
Generic.sql_get_oids
train
def sql_get_oids(self, where=None): ''' Query source database for a distinct list of oids. ''' table = self.lconfig.get('table') db = self.lconfig.get('db_schema_name') or self.lconfig.get('db') _oid = self.lconfig.get('_oid') if is_array(_oid): _oid = _oid[0] # get the db column, not the field alias sql = 'SELECT DISTINCT %s.%s FROM %s.%s' % (table, _oid, db, table) if where: where = [where] if isinstance(where, basestring) else list(where) sql += ' WHERE %s' % ' OR '.join(where) result = sorted([r[_oid] for r in self._load_sql(sql)]) return result
python
{ "resource": "" }
q39145
Pplacer.getTmpFilename
train
def getTmpFilename(self, tmp_dir="/tmp",prefix='tmp',suffix='.fasta',\ include_class_id=False,result_constructor=FilePath): """ Define Tmp filename to contain .fasta suffix, since pplacer requires the suffix to be .fasta """ return super(Pplacer,self).getTmpFilename(tmp_dir=tmp_dir, prefix=prefix, suffix=suffix, include_class_id=include_class_id, result_constructor=result_constructor)
python
{ "resource": "" }
q39146
Pplacer._get_result_paths
train
def _get_result_paths(self,data): """ Define the output filepaths """ output_dir = self.Parameters['--out-dir'].Value result = {} result['json'] = ResultPath(Path=join(output_dir, splitext(split(self._input_filename)[-1])[0] + \ '.jplace')) return result
python
{ "resource": "" }
q39147
chi_squared
train
def chi_squared(*choices): """Calculates the chi squared""" term = lambda expected, observed: float((expected - observed) ** 2) / max(expected, 1) mean_success_rate = float(sum([c.rewards for c in choices])) / max(sum([c.plays for c in choices]), 1) mean_failure_rate = 1 - mean_success_rate return sum([ term(mean_success_rate * c.plays, c.rewards) + term(mean_failure_rate * c.plays, c.plays - c.rewards ) for c in choices])
python
{ "resource": "" }
q39148
get_experiments
train
def get_experiments(redis, active=True): """Gets the full list of experiments""" key = ACTIVE_EXPERIMENTS_REDIS_KEY if active else ARCHIVED_EXPERIMENTS_REDIS_KEY return [Experiment(redis, escape.to_unicode(name)) for name in redis.smembers(key)]
python
{ "resource": "" }
q39149
Experiment.choices
train
def choices(self): """Gets the experiment choices""" if self._choices == None: self._choices = [ExperimentChoice(self, choice_name) for choice_name in self.choice_names] return self._choices
python
{ "resource": "" }
q39150
Experiment.add_play
train
def add_play(self, choice, count=1): """Increments the play count for a given experiment choice""" self.redis.hincrby(EXPERIMENT_REDIS_KEY_TEMPLATE % self.name, "%s:plays" % choice, count) self._choices = None
python
{ "resource": "" }
q39151
Experiment.compute_default_choice
train
def compute_default_choice(self): """Computes and sets the default choice""" choices = self.choices if len(choices) == 0: return None high_choice = max(choices, key=lambda choice: choice.performance) self.redis.hset(EXPERIMENT_REDIS_KEY_TEMPLATE % self.name, "default-choice", high_choice.name) self.refresh() return high_choice
python
{ "resource": "" }
q39152
await_all
train
async def await_all(): ''' Simple utility function that drains all pending tasks ''' tasks = asyncio.Task.all_tasks() for task in tasks: try: await task except RuntimeError as e: # Python 3.5.x: Error if attempting to await parent task if 'Task cannot await on itself' not in str(e): raise e except AssertionError as e: # Python 3.6.x: Error if attempting to await parent task if 'yield from wasn\'t used with future' not in str(e): raise e
python
{ "resource": "" }
q39153
coerce_to_synchronous
train
def coerce_to_synchronous(func): ''' Given a function that might be async, wrap it in an explicit loop so it can be run in a synchronous context. ''' if inspect.iscoroutinefunction(func): @functools.wraps(func) def sync_wrapper(*args, **kwargs): loop = asyncio.get_event_loop() try: loop.run_until_complete(func(*args, **kwargs)) finally: loop.close() return sync_wrapper return func
python
{ "resource": "" }
q39154
_get_matchable_segments
train
def _get_matchable_segments(segments): """ Performs a depth-first search of the segment tree to get all matchable segments. """ for subsegment in segments: if isinstance(subsegment, Token): break # No tokens allowed next to segments if isinstance(subsegment, Segment): if isinstance(subsegment, MatchableSegment): yield subsegment for matchable_subsegment in _get_matchable_segments(subsegment): yield matchable_subsegment
python
{ "resource": "" }
q39155
VW._get_response
train
def _get_response(self, parse_result=True): """If 'parse_result' is False, ignore the received output and return None.""" # expect_exact is faster than just exact, and fine for our purpose # (http://pexpect.readthedocs.org/en/latest/api/pexpect.html#pexpect.spawn.expect_exact) # searchwindowsize and other attributes may also affect efficiency self.vw_process.expect_exact('\r\n', searchwindowsize=-1) # Wait until process outputs a complete line if parse_result: output = self.vw_process.before result_struct = VWResult(output, active_mode=self.active_mode) else: result_struct = None return result_struct
python
{ "resource": "" }
q39156
VW.send_example
train
def send_example(self, *args, **kwargs ): """Send a labeled or unlabeled example to the VW instance. If 'parse_result' kwarg is False, ignore the result and return None. All other parameters are passed to self.send_line(). Returns a VWResult object. """ # Pop out the keyword argument 'parse_result' if given parse_result = kwargs.pop('parse_result', True) line = self.make_line(*args, **kwargs) result = self.send_line(line, parse_result=parse_result) return result
python
{ "resource": "" }
q39157
VW.save_model
train
def save_model(self, model_filename): """Pass a "command example" to the VW subprocess requesting that the current model be serialized to model_filename immediately. """ line = "save_{}|".format(model_filename) self.vw_process.sendline(line)
python
{ "resource": "" }
q39158
WebServer.route_path
train
def route_path(self, path): ''' Hacky function that's presently only useful for testing, gets the view that handles the given path. Later may be incorporated into the URL routing ''' path = path.strip('/') name, _, subpath = path.partition('/') for service in singletons.settings.load_all('SERVICES'): if service.SERVICE_NAME == name: # Found service! break else: return [], None # found no service for partial_url, view in service.urls.items(): partial_url = partial_url.strip('/') if isinstance(view, str): view = getattr(service, view) regexp = re.sub(r'<[^>]+>', r'([^/]+)', partial_url) matches = re.findall('^%s$' % regexp, subpath) if matches: if '(' not in regexp: matches = [] return matches, view return [], None
python
{ "resource": "" }
q39159
pair_looper
train
def pair_looper(iterator): ''' Loop through iterator yielding items in adjacent pairs ''' left = START for item in iterator: if left is not START: yield (left, item) left = item
python
{ "resource": "" }
q39160
clear_stale_pids
train
def clear_stale_pids(pids, pid_dir='/tmp', prefix='', multi=False): 'check for and remove any pids which have no corresponding process' if isinstance(pids, (int, float, long)): pids = [pids] pids = str2list(pids, map_=unicode) procs = map(unicode, os.listdir('/proc')) running = [pid for pid in pids if pid in procs] logger.warn( "Found %s pids running: %s" % (len(running), running)) prefix = prefix.rstrip('.') if prefix else None for pid in pids: if prefix: _prefix = prefix else: _prefix = unicode(pid) # remove non-running procs if pid in running: continue if multi: pid_file = '%s%s.pid' % (_prefix, pid) else: pid_file = '%s.pid' % (_prefix) path = os.path.join(pid_dir, pid_file) if os.path.exists(path): logger.debug("Removing pidfile: %s" % path) try: remove_file(path) except OSError as e: logger.warn(e) return running
python
{ "resource": "" }
q39161
cube_pkg_mod_cls
train
def cube_pkg_mod_cls(cube): ''' Used to dynamically importing cube classes based on string slug name. Converts 'pkg_mod' -> pkg, mod, Cls eg: tw_tweet -> tw, tweet, Tweet Assumes `Metrique Cube Naming Convention` is used :param cube: cube name to use when searching for cube pkg.mod.class to load ''' _cube = cube.split('_') pkg = _cube[0] mod = '_'.join(_cube[1:]) _cls = ''.join([s[0].upper() + s[1:] for s in _cube[1:]]) return pkg, mod, _cls
python
{ "resource": "" }
q39162
debug_setup
train
def debug_setup(logger=None, level=None, log2file=None, log_file=None, log_format=None, log_dir=None, log2stdout=None, truncate=False): ''' Local object instance logger setup. Verbosity levels are determined as such:: if level in [-1, False]: logger.setLevel(logging.WARN) elif level in [0, None]: logger.setLevel(logging.INFO) elif level in [True, 1, 2]: logger.setLevel(logging.DEBUG) If (level == 2) `logging.DEBUG` will be set even for the "root logger". Configuration options available for customized logger behaivor: * debug (bool) * log2stdout (bool) * log2file (bool) * log_file (path) ''' log2stdout = False if log2stdout is None else log2stdout _log_format = "%(levelname)s.%(name)s.%(process)s:%(asctime)s:%(message)s" log_format = log_format or _log_format if isinstance(log_format, basestring): log_format = logging.Formatter(log_format, "%Y%m%dT%H%M%S") log2file = True if log2file is None else log2file logger = logger or 'metrique' if isinstance(logger, basestring): logger = logging.getLogger(logger) else: logger = logger or logging.getLogger(logger) logger.propagate = 0 logger.handlers = [] if log2file: log_dir = log_dir or LOGS_DIR log_file = log_file or 'metrique' log_file = os.path.join(log_dir, log_file) if truncate: # clear the existing data before writing (truncate) open(log_file, 'w+').close() hdlr = logging.FileHandler(log_file) hdlr.setFormatter(log_format) logger.addHandler(hdlr) else: log2stdout = True if log2stdout: hdlr = logging.StreamHandler() hdlr.setFormatter(log_format) logger.addHandler(hdlr) logger = _debug_set_level(logger, level) return logger
python
{ "resource": "" }
q39163
get_cube
train
def get_cube(cube, init=False, pkgs=None, cube_paths=None, config=None, backends=None, **kwargs): ''' Dynamically locate and load a metrique cube :param cube: name of the cube class to import from given module :param init: flag to request initialized instance or uninitialized class :param config: config dict to pass on initialization (implies init=True) :param pkgs: list of package names to search for the cubes in :param cube_path: additional paths to search for modules in (sys.path) :param kwargs: additional kwargs to pass to cube during initialization ''' pkgs = pkgs or ['cubes'] pkgs = [pkgs] if isinstance(pkgs, basestring) else pkgs # search in the given path too, if provided cube_paths = cube_paths or [] cube_paths_is_basestring = isinstance(cube_paths, basestring) cube_paths = [cube_paths] if cube_paths_is_basestring else cube_paths cube_paths = [os.path.expanduser(path) for path in cube_paths] # append paths which don't already exist in sys.path to sys.path [sys.path.append(path) for path in cube_paths if path not in sys.path] pkgs = pkgs + DEFAULT_PKGS err = False for pkg in pkgs: try: _cube = _load_cube_pkg(pkg, cube) except ImportError as err: _cube = None if _cube: break else: logger.error(err) raise RuntimeError('"%s" not found! %s; %s \n%s)' % ( cube, pkgs, cube_paths, sys.path)) if init: _cube = _cube(config=config, **kwargs) return _cube
python
{ "resource": "" }
q39164
get_timezone_converter
train
def get_timezone_converter(from_timezone, to_tz=None, tz_aware=False): ''' return a function that converts a given datetime object from a timezone to utc :param from_timezone: timezone name as string ''' if not from_timezone: return None is_true(HAS_DATEUTIL, "`pip install python_dateutil` required") is_true(HAS_PYTZ, "`pip install pytz` required") from_tz = pytz.timezone(from_timezone) return partial(_get_timezone_converter, from_tz=from_tz, to_tz=to_tz, tz_aware=tz_aware)
python
{ "resource": "" }
q39165
is_empty
train
def is_empty(value, msg=None, except_=None, inc_zeros=True): ''' is defined, but null or empty like value ''' if hasattr(value, 'empty'): # dataframes must check for .empty # since they don't define truth value attr # take the negative, since below we're # checking for cases where value 'is_null' value = not bool(value.empty) elif inc_zeros and value in ZEROS: # also consider 0, 0.0, 0L as 'empty' # will check for the negative below value = True else: pass _is_null = is_null(value, except_=False) result = bool(_is_null or not value) if except_: return is_true(result, msg=msg, except_=except_) else: return bool(result)
python
{ "resource": "" }
q39166
is_null
train
def is_null(value, msg=None, except_=None): ''' ie, "is not defined" ''' # dataframes, even if empty, are not considered null value = False if hasattr(value, 'empty') else value result = bool( value is None or value != value or repr(value) == 'NaT') if except_: return is_true(result, msg=msg, except_=except_) else: return bool(result)
python
{ "resource": "" }
q39167
json_encode_default
train
def json_encode_default(obj): ''' Convert datetime.datetime to timestamp :param obj: value to (possibly) convert ''' if isinstance(obj, (datetime, date)): result = dt2ts(obj) else: result = json_encoder.default(obj) return to_encoding(result)
python
{ "resource": "" }
q39168
jsonhash
train
def jsonhash(obj, root=True, exclude=None, hash_func=_jsonhash_sha1): ''' calculate the objects hash based on all field values ''' if isinstance(obj, Mapping): # assumption: using in against set() is faster than in against list() if root and exclude: obj = {k: v for k, v in obj.iteritems() if k not in exclude} # frozenset's don't guarantee order; use sorted tuples # which means different python interpreters can return # back frozensets with different hash values even when # the content of the object is exactly the same result = sorted( (k, jsonhash(v, False)) for k, v in obj.iteritems()) elif isinstance(obj, list): # FIXME: should lists be sorted for consistent hashes? # when the object is the same, just different list order? result = tuple(jsonhash(e, False) for e in obj) else: result = obj if root: result = unicode(hash_func(result)) return result
python
{ "resource": "" }
q39169
load
train
def load(path, filetype=None, as_df=False, retries=None, _oid=None, quiet=False, **kwargs): '''Load multiple files from various file types automatically. Supports glob paths, eg:: path = 'data/*.csv' Filetypes are autodetected by common extension strings. Currently supports loadings from: * csv (pd.read_csv) * json (pd.read_json) :param path: path to config json file :param filetype: override filetype autodetection :param kwargs: additional filetype loader method kwargs ''' is_true(HAS_PANDAS, "`pip install pandas` required") set_oid = set_oid_func(_oid) # kwargs are for passing ftype load options (csv.delimiter, etc) # expect the use of globs; eg, file* might result in fileN (file1, # file2, file3), etc if not isinstance(path, basestring): # assume we're getting a raw dataframe objects = path if not isinstance(objects, pd.DataFrame): raise ValueError("loading raw values must be DataFrames") elif re.match('https?://', path): logger.debug('Saving %s to tmp file' % path) _path = urlretrieve(path, retries) logger.debug('%s saved to tmp file: %s' % (path, _path)) try: objects = load_file(_path, filetype, **kwargs) finally: remove_file(_path) else: path = re.sub('^file://', '', path) path = os.path.expanduser(path) # assume relative to cwd if not already absolute path path = path if os.path.isabs(path) else pjoin(os.getcwd(), path) files = sorted(glob.glob(os.path.expanduser(path))) if not files: raise IOError("failed to load: %s" % path) # buid up a single dataframe by concatting # all globbed files together objects = [] [objects.extend(load_file(ds, filetype, **kwargs)) for ds in files] if is_empty(objects, except_=False) and not quiet: raise RuntimeError("no objects extracted!") else: logger.debug("Data loaded successfully from %s" % path) if set_oid: # set _oids, if we have a _oid generator func defined objects = [set_oid(o) for o in objects] if as_df: return pd.DataFrame(objects) else: return objects
python
{ "resource": "" }
q39170
read_file
train
def read_file(rel_path, paths=None, raw=False, as_list=False, as_iter=False, *args, **kwargs): ''' find a file that lives somewhere within a set of paths and return its contents. Default paths include 'static_dir' ''' if not rel_path: raise ValueError("rel_path can not be null!") paths = str2list(paths) # try looking the file up in a directory called static relative # to SRC_DIR, eg assuming metrique git repo is in ~/metrique # we'd look in ~/metrique/static paths.extend([STATIC_DIR, os.path.join(SRC_DIR, 'static')]) paths = [os.path.expanduser(p) for p in set(paths)] for path in paths: path = os.path.join(path, rel_path) logger.debug("trying to read: %s " % path) if os.path.exists(path): break else: raise IOError("path %s does not exist!" % rel_path) args = args if args else ['rU'] fd = open(path, *args, **kwargs) if raw: return fd if as_iter: return read_in_chunks(fd) else: fd_lines = fd.readlines() if as_list: return fd_lines else: return ''.join(fd_lines)
python
{ "resource": "" }
q39171
safestr
train
def safestr(str_): ''' get back an alphanumeric only version of source ''' str_ = str_ or "" return "".join(x for x in str_ if x.isalnum())
python
{ "resource": "" }
q39172
urlretrieve
train
def urlretrieve(uri, saveas=None, retries=3, cache_dir=None): '''urllib.urlretrieve wrapper''' retries = int(retries) if retries else 3 # FIXME: make random filename (saveas) in cache_dir... # cache_dir = cache_dir or CACHE_DIR while retries: try: _path, headers = urllib.urlretrieve(uri, saveas) except Exception as e: retries -= 1 logger.warn( 'Failed getting uri "%s": %s (retry:%s in 1s)' % ( uri, e, retries)) time.sleep(.2) continue else: break else: raise RuntimeError("Failed to retrieve uri: %s" % uri) return _path
python
{ "resource": "" }
q39173
reverse_media_url
train
def reverse_media_url(target_type, url_string, *args, **kwargs): ''' Given a target type and an resource URL, generates a valid URL to this via ''' args_str = '<%s>' % '><'.join(args) kwargs_str = '<%s>' % '><'.join('%s:%s' % pair for pair in kwargs.items()) url_str = ''.join([url_string, args_str, kwargs_str]) normalized_url = str(ResourceURL(url_str)) query_tuples = [] if singletons.settings.SECURITY and 'Sha1' in singletons.settings.SECURITY: secret = singletons.settings.HMAC_SECRET digest = get_hmac_sha1_digest(secret, normalized_url, target_type) query_tuples.append(('digest', digest)) # Add in URL as last querystring argument query_tuples.append(('url', normalized_url)) querystring = urlencode(query_tuples) scheme = singletons.settings.EXTERNAL_SCHEME host = singletons.settings.EXTERNAL_HOST port = singletons.settings.EXTERNAL_PORT if not host: host = singletons.settings.HOST if not port: port = singletons.settings.PORT port_suffix = ':%s' % port if port != 80 else '' typestring_normalized = str(TypeString(target_type)) return '%s://%s%s/media/%s/?%s' % ( scheme, host, port_suffix, typestring_normalized, querystring, )
python
{ "resource": "" }
q39174
_isbn_cleanse
train
def _isbn_cleanse(isbn, checksum=True): """Check ISBN is a string, and passes basic sanity checks. Args: isbn (str): SBN, ISBN-10 or ISBN-13 checksum (bool): ``True`` if ``isbn`` includes checksum character Returns: ``str``: ISBN with hyphenation removed, including when called with a SBN Raises: TypeError: ``isbn`` is not a ``str`` type IsbnError: Incorrect length for ``isbn`` IsbnError: Incorrect SBN or ISBN formatting """ if not isinstance(isbn, string_types): raise TypeError('ISBN must be a string, received %r' % isbn) if PY2 and isinstance(isbn, str): # pragma: Python 2 isbn = unicode(isbn) uni_input = False else: # pragma: Python 3 uni_input = True for dash in DASHES: isbn = isbn.replace(dash, unicode()) if checksum: if not isbn[:-1].isdigit(): raise IsbnError('non-digit parts') if len(isbn) == 9: isbn = '0' + isbn if len(isbn) == 10: if not (isbn[-1].isdigit() or isbn[-1] in 'Xx'): raise IsbnError('non-digit or X checksum') elif len(isbn) == 13: if not isbn[-1].isdigit(): raise IsbnError('non-digit checksum') if not isbn.startswith(('978', '979')): raise IsbnError('invalid Bookland region') else: raise IsbnError('ISBN must be either 10 or 13 characters long') else: if len(isbn) == 8: isbn = '0' + isbn elif len(isbn) == 12 and not isbn[:3].startswith(('978', '979')): raise IsbnError('invalid Bookland region') if not isbn.isdigit(): raise IsbnError('non-digit parts') if not len(isbn) in (9, 12): raise IsbnError('ISBN must be either 9 or 12 characters long ' 'without checksum') if PY2 and not uni_input: # pragma: Python 2 # Sadly, type ping-pong is required to maintain backwards compatibility # with previous pyisbn releases for Python 2 users. return str(isbn) else: # pragma: Python 3 return isbn
python
{ "resource": "" }
q39175
convert
train
def convert(isbn, code='978'): """Convert ISBNs between ISBN-10 and ISBN-13. Note: No attempt to hyphenate converted ISBNs is made, because the specification requires that *any* hyphenation must be correct but allows ISBNs without hyphenation. Args: isbn (str): SBN, ISBN-10 or ISBN-13 code (str): EAN Bookland code Returns: ``str``: Converted ISBN-10 or ISBN-13 Raise: IsbnError: When ISBN-13 isn't convertible to an ISBN-10 """ isbn = _isbn_cleanse(isbn) if len(isbn) == 10: isbn = code + isbn[:-1] return isbn + calculate_checksum(isbn) else: if isbn.startswith('978'): return isbn[3:-1] + calculate_checksum(isbn[3:-1]) else: raise IsbnError('Only ISBN-13s with 978 Bookland code can be ' 'converted to ISBN-10.')
python
{ "resource": "" }
q39176
Isbn.to_url
train
def to_url(self, site='amazon', country='us'): """Generate a link to an online book site. Args: site (str): Site to create link to country (str): Country specific version of ``site`` Returns: ``str``: URL on ``site`` for book Raises: SiteError: Unknown site value CountryError: Unknown country value """ try: try: url, tlds = URL_MAP[site] except ValueError: tlds = None url = URL_MAP[site] except KeyError: raise SiteError(site) inject = {'isbn': self._isbn} if tlds: if country not in tlds: raise CountryError(country) tld = tlds[country] if not tld: tld = country inject['tld'] = tld return url % inject
python
{ "resource": "" }
q39177
RegexTokenizer._tokenize
train
def _tokenize(self, text, token_class=None): """ Tokenizes a text :Returns: A `list` of tokens """ token_class = token_class or Token tokens = {} for i, match in enumerate(self.regex.finditer(text)): value = match.group(0) try: token = tokens[value] except KeyError: type = match.lastgroup token = token_class(value, type=type) tokens[value] = token yield token
python
{ "resource": "" }
q39178
_parse_cli_facter_results
train
def _parse_cli_facter_results(facter_results): '''Parse key value pairs printed with "=>" separators. YAML is preferred output scheme for facter. >>> list(_parse_cli_facter_results("""foo => bar ... baz => 1 ... foo_bar => True""")) [('foo', 'bar'), ('baz', '1'), ('foo_bar', 'True')] >>> list(_parse_cli_facter_results("""foo => bar ... babababababababab ... baz => 2""")) [('foo', 'bar\nbabababababababab'), ('baz', '2')] >>> list(_parse_cli_facter_results("""3434""")) Traceback (most recent call last): ... ValueError: parse error Uses a generator interface: >>> _parse_cli_facter_results("foo => bar").next() ('foo', 'bar') ''' last_key, last_value = None, [] for line in filter(None, facter_results.splitlines()): res = line.split(six.u(" => "), 1) if len(res)==1: if not last_key: raise ValueError("parse error") else: last_value.append(res[0]) else: if last_key: yield last_key, os.linesep.join(last_value) last_key, last_value = res[0], [res[1]] else: if last_key: yield last_key, os.linesep.join(last_value)
python
{ "resource": "" }
q39179
Facter.run_facter
train
def run_facter(self, key=None): """Run the facter executable with an optional specfic fact. Output is parsed to yaml if available and selected. Puppet facts are always selected. Returns a dictionary if no key is given, and the value if a key is passed.""" args = [self.facter_path] #this seems to not cause problems, but leaving it separate args.append("--puppet") if self.external_dir is not None: args.append('--external-dir') args.append(self.external_dir) if self.uses_yaml: args.append("--yaml") if key is not None: args.append(key) proc = subprocess.Popen(args, stdout=subprocess.PIPE) results = proc.stdout.read() if self.uses_yaml: parsed_results = yaml.load(results) if key is not None: return parsed_results[key] else: return parsed_results results = results.decode() if key is not None: return results.strip() else: return dict(_parse_cli_facter_results(results))
python
{ "resource": "" }
q39180
Facter.has_cache
train
def has_cache(self): """Intended to be called before any call that might access the cache. If the cache is not selected, then returns False, otherwise the cache is build if needed and returns True.""" if not self.cache_enabled: return False if self._cache is None: self.build_cache() return True
python
{ "resource": "" }
q39181
Facter.lookup
train
def lookup(self, fact, cache=True): """Return the value of a given fact and raise a KeyError if it is not available. If `cache` is False, force the lookup of the fact.""" if (not cache) or (not self.has_cache()): val = self.run_facter(fact) if val is None or val == '': raise KeyError(fact) return val return self._cache[fact]
python
{ "resource": "" }
q39182
Frisbee._reset
train
def _reset(self) -> None: """Reset some of the state in the class for multi-searches.""" self.project: str = namesgenerator.get_random_name() self._processed: List = list() self.results: List = list()
python
{ "resource": "" }
q39183
Frisbee._config_bootstrap
train
def _config_bootstrap(self) -> None: """Handle the basic setup of the tool prior to user control. Bootstrap will load all the available modules for searching and set them up for use by this main class. """ if self.output: self.folder: str = os.getcwd() + "/" + self.project os.mkdir(self.folder)
python
{ "resource": "" }
q39184
Frisbee._dyn_loader
train
def _dyn_loader(self, module: str, kwargs: str): """Dynamically load a specific module instance.""" package_directory: str = os.path.dirname(os.path.abspath(__file__)) modules: str = package_directory + "/modules" module = module + ".py" if module not in os.listdir(modules): raise Exception("Module %s is not valid" % module) module_name: str = module[:-3] import_path: str = "%s.%s" % (self.MODULE_PATH, module_name) imported = import_module(import_path) obj = getattr(imported, 'Module') return obj(**kwargs)
python
{ "resource": "" }
q39185
Frisbee._job_handler
train
def _job_handler(self) -> bool: """Process the work items.""" while True: try: task = self._unfullfilled.get_nowait() except queue.Empty: break else: self._log.debug("Job: %s" % str(task)) engine = self._dyn_loader(task['engine'], task) task['start_time'] = now_time() results = engine.search() task['end_time'] = now_time() duration: str = str((task['end_time'] - task['start_time']).seconds) task['duration'] = duration task.update({'results': results}) self._fulfilled.put(task) return True
python
{ "resource": "" }
q39186
Frisbee._save
train
def _save(self) -> None: """Save output to a directory.""" self._log.info("Saving results to '%s'" % self.folder) path: str = self.folder + "/" for job in self.results: if job['domain'] in self.saved: continue job['start_time'] = str_datetime(job['start_time']) job['end_time'] = str_datetime(job['end_time']) jid: int = random.randint(100000, 999999) filename: str = "%s_%s_%d_job.json" % (self.project, job['domain'], jid) handle = open(path + filename, 'w') handle.write(json.dumps(job, indent=4)) handle.close() filename = "%s_%s_%d_emails.txt" % (self.project, job['domain'], jid) handle = open(path + filename, 'w') for email in job['results']['emails']: handle.write(email + "\n") handle.close() self.saved.append(job['domain'])
python
{ "resource": "" }
q39187
Frisbee.search
train
def search(self, jobs: List[Dict[str, str]]) -> None: """Perform searches based on job orders.""" if not isinstance(jobs, list): raise Exception("Jobs must be of type list.") self._log.info("Project: %s" % self.project) self._log.info("Processing jobs: %d", len(jobs)) for _, job in enumerate(jobs): self._unfullfilled.put(job) for _ in range(self.PROCESSES): proc: Process = Process(target=self._job_handler) self._processes.append(proc) proc.start() for proc in self._processes: proc.join() while not self._fulfilled.empty(): output: Dict = self._fulfilled.get() output.update({'project': self.project}) self._processed.append(output['domain']) self.results.append(output) if output['greedy']: bonus_jobs: List = list() observed: List = list() for item in output['results']['emails']: found: str = item.split('@')[1] if found in self._processed or found in observed: continue observed.append(found) base: Dict = dict() base['limit'] = output['limit'] base['modifier'] = output['modifier'] base['engine'] = output['engine'] base['greedy'] = False base['domain'] = found bonus_jobs.append(base) if len(bonus_jobs) > 0: self.search(bonus_jobs) self._log.info("All jobs processed") if self.output: self._save()
python
{ "resource": "" }
q39188
step_along_mag_unit_vector
train
def step_along_mag_unit_vector(x, y, z, date, direction=None, num_steps=5., step_size=5., scalar=1): """ Move along 'lines' formed by following the magnetic unit vector directions. Moving along the field is effectively the same as a field line trace though extended movement along a field should use the specific field_line_trace method. Parameters ---------- x : ECEF-x (km) Location to step from in ECEF (km). Scalar input. y : ECEF-y (km) Location to step from in ECEF (km). Scalar input. z : ECEF-z (km) Location to step from in ECEF (km). Scalar input. date : list-like of datetimes Date and time for magnetic field direction : string String identifier for which unit vector directino to move along. Supported inputs, 'meridional', 'zonal', 'aligned' num_steps : int Number of steps to take along unit vector direction step_size = float Distance taken for each step (km) scalar : int Scalar modifier for step size distance. Input a -1 to move along negative unit vector direction. Returns ------- np.array [x, y, z] of ECEF location after taking num_steps along direction, each step_size long. """ # set parameters for the field line tracing routines field_step_size = 100. field_max_steps = 1000 field_steps = np.arange(field_max_steps) for i in np.arange(num_steps): # x, y, z in ECEF # convert to geodetic lat, lon, alt = ecef_to_geodetic(x, y, z) # get unit vector directions zvx, zvy, zvz, bx, by, bz, mx, my, mz = calculate_mag_drift_unit_vectors_ecef( [lat], [lon], [alt], [date], steps=field_steps, max_steps=field_max_steps, step_size=field_step_size, ref_height=0.) # pull out the direction we need if direction == 'meridional': ux, uy, uz = mx, my, mz elif direction == 'zonal': ux, uy, uz = zvx, zvy, zvz elif direction == 'aligned': ux, uy, uz = bx, by, bz # take steps along direction x = x + step_size*ux[0]*scalar y = y + step_size*uy[0]*scalar z = z + step_size*uz[0]*scalar return np.array([x, y, z])
python
{ "resource": "" }
q39189
add_fabfile
train
def add_fabfile(): """ Copy the base fabfile.py to the current working directory. """ fabfile_src = os.path.join(PACKAGE_ROOT, 'fabfile.py') fabfile_dest = os.path.join(os.getcwd(), 'fabfile_deployer.py') if os.path.exists(fabfile_dest): print "`fabfile.py` exists in the current directory. " \ "Please remove or rename it and try again." return shutil.copyfile(fabfile_src, fabfile_dest)
python
{ "resource": "" }
q39190
Record.delete
train
def delete(self): """Remove the item from the infoblox server. :rtype: bool :raises: AssertionError :raises: ValueError :raises: infoblox.exceptions.ProtocolError """ if not self._ref: raise ValueError('Object has no reference id for deletion') if 'save' not in self._supports: raise AssertionError('Can not save this object type') response = self._session.delete(self._path) if response.status_code == 200: self._ref = None self.clear() return True try: error = response.json() raise exceptions.ProtocolError(error['text']) except ValueError: raise exceptions.ProtocolError(response.content)
python
{ "resource": "" }
q39191
Record.fetch
train
def fetch(self): """Attempt to fetch the object from the Infoblox device. If successful the object will be updated and the method will return True. :rtype: bool :raises: infoblox.exceptions.ProtocolError """ LOGGER.debug('Fetching %s, %s', self._path, self._search_values) response = self._session.get(self._path, self._search_values, {'_return_fields': self._return_fields}) if response.status_code == 200: values = response.json() self._assign(values) return bool(values) elif response.status_code >= 400: try: error = response.json() raise exceptions.ProtocolError(error['text']) except ValueError: raise exceptions.ProtocolError(response.content) return False
python
{ "resource": "" }
q39192
Record.save
train
def save(self): """Update the infoblox with new values for the specified object, or add the values if it's a new object all together. :raises: AssertionError :raises: infoblox.exceptions.ProtocolError """ if 'save' not in self._supports: raise AssertionError('Can not save this object type') values = {} for key in [key for key in self.keys() if key not in self._save_ignore]: if not getattr(self, key) and getattr(self, key) != False: continue if isinstance(getattr(self, key, None), list): value = list() for item in getattr(self, key): if isinstance(item, dict): value.append(item) elif hasattr(item, '_save_as'): value.append(item._save_as()) elif hasattr(item, '_ref') and getattr(item, '_ref'): value.append(getattr(item, '_ref')) else: LOGGER.warning('Cant assign %r', item) values[key] = value elif getattr(self, key, None): values[key] = getattr(self, key) if not self._ref: response = self._session.post(self._path, values) else: values['_ref'] = self._ref response = self._session.put(self._path, values) LOGGER.debug('Response: %r, %r', response.status_code, response.content) if 200 <= response.status_code <= 201: self.fetch() return True else: try: error = response.json() raise exceptions.ProtocolError(error['text']) except ValueError: raise exceptions.ProtocolError(response.content)
python
{ "resource": "" }
q39193
Record._assign
train
def _assign(self, values): """Assign the values passed as either a dict or list to the object if the key for each value matches an available attribute on the object. :param dict values: The values to assign """ LOGGER.debug('Assigning values: %r', values) if not values: return keys = self.keys() if not self._ref: keys.append('_ref') if isinstance(values, dict): for key in keys: if values.get(key): if isinstance(values.get(key), list): items = list() for item in values[key]: if isinstance(item, dict): if '_ref' in item: obj_class = get_class(item['_ref']) if obj_class: items.append(obj_class(self._session, **item)) else: items.append(item) setattr(self, key, items) else: setattr(self, key, values[key]) elif isinstance(values, list): self._assign(values[0]) else: LOGGER.critical('Unhandled return type: %r', values)
python
{ "resource": "" }
q39194
Record._build_search_values
train
def _build_search_values(self, kwargs): """Build the search criteria dictionary. It will first try and build the values from already set attributes on the object, falling back to the passed in kwargs. :param dict kwargs: Values to build the dict from :rtype: dict """ criteria = {} for key in self._search_by: if getattr(self, key, None): criteria[key] = getattr(self, key) elif key in kwargs and kwargs.get(key): criteria[key] = kwargs.get(key) return criteria
python
{ "resource": "" }
q39195
Host.add_ipv4addr
train
def add_ipv4addr(self, ipv4addr): """Add an IPv4 address to the host. :param str ipv4addr: The IP address to add. :raises: ValueError """ for addr in self.ipv4addrs: if ((isinstance(addr, dict) and addr['ipv4addr'] == ipv4addr) or (isinstance(addr, HostIPv4) and addr.ipv4addr == ipv4addr)): raise ValueError('Already exists') self.ipv4addrs.append({'ipv4addr': ipv4addr})
python
{ "resource": "" }
q39196
Host.remove_ipv4addr
train
def remove_ipv4addr(self, ipv4addr): """Remove an IPv4 address from the host. :param str ipv4addr: The IP address to remove """ for addr in self.ipv4addrs: if ((isinstance(addr, dict) and addr['ipv4addr'] == ipv4addr) or (isinstance(addr, HostIPv4) and addr.ipv4addr == ipv4addr)): self.ipv4addrs.remove(addr) break
python
{ "resource": "" }
q39197
Host.add_ipv6addr
train
def add_ipv6addr(self, ipv6addr): """Add an IPv6 address to the host. :param str ipv6addr: The IP address to add. :raises: ValueError """ for addr in self.ipv6addrs: if ((isinstance(addr, dict) and addr['ipv6addr'] == ipv6addr) or (isinstance(addr, HostIPv4) and addr.ipv6addr == ipv6addr)): raise ValueError('Already exists') self.ipv6addrs.append({'ipv6addr': ipv6addr})
python
{ "resource": "" }
q39198
Host.remove_ipv6addr
train
def remove_ipv6addr(self, ipv6addr): """Remove an IPv6 address from the host. :param str ipv6addr: The IP address to remove """ for addr in self.ipv6addrs: if ((isinstance(addr, dict) and addr['ipv6addr'] == ipv6addr) or (isinstance(addr, HostIPv4) and addr.ipv6addr == ipv6addr)): self.ipv6addrs.remove(addr) break
python
{ "resource": "" }
q39199
SQLAlchemyProxy.autoschema
train
def autoschema(self, objects, **kwargs): ''' wrapper around utils.autoschema function ''' return autoschema(objects=objects, exclude_keys=self.RESTRICTED_KEYS, **kwargs)
python
{ "resource": "" }