http[s]?://[^\\\\s]+)\\\", ctx.message.content)\\n\\n if not links:\\n await ctx.channel.send('`Useage: [p]galaddlinkuwl <startoflink>, [Bot Owner] Adds a link from gallery link whitelist.`')\\n \\n # ===== ADD THE NEW LINKS TO THE WHITELIST\\n new_gal_link_wl = list(set(self.cogset['link_wl']) + set(links))\\n\\n if Gallery.compare(new_gal_link_wl, self.cogset['link_wl']):\\n await ctx.channel.send(content=\\\"{}\\\\n are already in the gallery link whitelist.\\\".format('\\\\n'.join(links)), delete_after=Gallery.delete_after)\\n return \\n \\n else:\\n self.cogset['link_wl'] = new_gal_link_wl\\n\\n # ===== WRITE TO THE DATABASE\\n await cogset.SAVE(self.cogset, cogname=self.qualified_name)\\n\\n # ===== RETURN\\n await ctx.channel.send(content=\\\"{}\\\\n have been added to the gallery link whitelist.\\\".format('\\\\n'.join(links)), delete_after=Gallery.delete_after)\\n return\",\n \"def get(self, request, slug=None):\\n if (slug):\\n email_link = EmailLinks.objects.get(link_tracking_id=slug)\\n email_link.clicked_time = datetime.now()\\n email_link.clicked_status = True\\n email_link.save()\\n redirect_url = email_link.link_url\\n return HttpResponseRedirect(redirect_to=redirect_url)\",\n \"def _visit_a(self, elem):\\n\\n dest_url = self._fix_url(self._curr_url, attr(elem,\\\"href\\\"))\\n\\n #print \\\"href=\\\"+repr(dest_url), \\\\\\n # \\\"title=\\\"+repr(attr(elem,\\\"title\\\")), \\\\\\n # \\\"alt=\\\"+repr(attr(elem,\\\"alt\\\")), \\\\\\n # \\\"text=\\\"+repr(self._text_of(elem))\\n\\n # add the just found URL to the url queue\\n self._url_queue.append((dest_url, self._curr_depth))\\n\\n # add a link entry into the database from the current document to the\\n # other document\\n self.add_link(self._curr_doc_id, self.document_id(dest_url))\\n\\n # TODO add title/alt/text to index for destination url\",\n \"def update_row(self):\\n self.current_row = self.next_row\\n self.next_row = self.get_row()\",\n \"def insert_value_rdf(url, atdm_row, col_name, domain_url):\\n filled_url = UriTemplateUtils.insert_value(url, atdm_row, col_name, domain_url)\\n return URIRef(filled_url) if filled_url.startswith('http') else Literal(filled_url)\",\n \"def add_data(self, site: str, pid: int, formatted_pid: str, image_url: str) -> bool:\\n try:\\n self._cursor.execute(f\\\"INSERT INTO {site} VALUES ({pid}, '{formatted_pid}', '{image_url}', {datetime.now().timestamp()});\\\")\\n self._connection.commit()\\n return True\\n \\n except sqlite3.IntegrityError:\\n print(f'Failed to add {pid} ({formatted_pid}) - PID already exists in table \\\"{site}\\\".')\\n \\n return False\",\n \"def insert_url(info,url):\\n sql = \\\"\\\"\\\"INSERT INTO main.myurls (description,url)\\n VALUES(%s,%s);\\\"\\\"\\\"\\n conn = None\\n vendor_id = None\\n try:\\n # read database configuration\\n params = config()\\n # connect to the PostgreSQL database\\n conn = psycopg2.connect(**params)\\n # create a new cursor\\n cur = conn.cursor()\\n # execute the INSERT statement\\n cur.execute(sql, (info,url,))\\n # get the generated id back\\n # commit the changes to the database\\n conn.commit()\\n # close communication with the database\\n cur.close()\\n except (Exception, psycopg2.DatabaseError) as error:\\n print(error)\\n finally:\\n if conn is not None:\\n conn.close()\",\n \"def put(self, key: int, value: int) -> None:\\n hashKey = key % 1000\\n if not self.bucket[hashKey]:\\n self.bucket[hashKey] = LinkNode(key, value)\\n else:\\n node = self.bucket[hashKey]\\n while node:\\n if node.pair[0] == key:\\n node.pair[1] = value\\n return\\n if not node.next:\\n node.next = LinkNode(key, value)\\n node = node.next\",\n \"def update_link(self, target, dest):\\n if not target:\\n self.remove_link(dest)\\n return\\n\\n reltarget = os.path.relpath(\\n target, os.path.join(self.dirname, os.path.dirname(dest)))\\n\\n for link in self.runscript.links:\\n if link[1] == dest:\\n link[0] = reltarget\\n break\\n else:\\n self.runscript.add_link(reltarget, dest)\",\n \"def update(self, **kwargs):\\n _url = (\\n f\\\"{self.connector.base_url}/projects/{self.project_id}/links/{self.link_id}\\\"\\n )\\n\\n # TODO: Verify that the passed kwargs are supported ones\\n _response = self.connector.http_call(\\\"put\\\", _url, json_data=kwargs)\\n\\n # Update object\\n self._update(_response.json())\",\n \"def touch(self, connection=None):\\n self.create_marker_table()\\n\\n if connection is None:\\n connection = self.connect()\\n connection.autocommit = True # if connection created here, we commit it here\\n\\n connection.cursor().execute(\\n \\\"\\\"\\\"INSERT INTO {marker_table} (update_id, target_table)\\n VALUES (%s, %s)\\n ON DUPLICATE KEY UPDATE\\n update_id = VALUES(update_id)\\n \\\"\\\"\\\".format(marker_table=self.marker_table),\\n (self.update_id, self.table)\\n )\\n # make sure update is properly marked\\n assert self.exists(connection)\",\n \"def update_table(table_name, url):\\r\\n if table_name == \\\"on_progress_pages\\\":\\r\\n sql_query = \\\"UPDATE on_progress_pages SET is_scrapped=1 WHERE page_url = %s\\\"\\r\\n elif table_name == \\\"on_progress_domains\\\":\\r\\n sql_query = \\\"UPDATE on_progress_domains SET is_scrapped=1 WHERE url = %s\\\"\\r\\n else:\\r\\n print \\\"unknown ERROR\\\"\\r\\n return\\r\\n db = connect()\\r\\n cursor = db.cursor()\\r\\n try:\\r\\n cursor.execute(sql_query, (url,))\\r\\n db.commit()\\r\\n except:\\r\\n cursor.close()\\r\\n raise RuntimeError(\\\"An Exception happened with the Database, make sure you are connected\\\")\\r\\n cursor.close()\\r\\n db.close()\",\n \"def new_link(self, key, link, default):\\n\\n s = self._new_link()\\n s.key = key\\n s.link = link\\n s.default = default\\n return s\",\n \"def _update_linked_table(table, col_name, added, copied, removed):\\n logger.debug('start: update linked table after transition')\\n\\n # handle removals\\n table = table.loc[~table[col_name].isin(set(removed))]\\n if (added is None or len(added) == 0):\\n return table\\n\\n # map new IDs to the IDs from which they were copied\\n id_map = pd.concat([pd.Series(copied, name=col_name), pd.Series(added, name='temp_id')], axis=1)\\n\\n # join to linked table and assign new id\\n new_rows = id_map.merge(table, on=col_name)\\n new_rows.drop(col_name, axis=1, inplace=True)\\n new_rows.rename(columns={'temp_id': col_name}, inplace=True)\\n\\n # index the new rows\\n starting_index = table.index.values.max() + 1\\n new_rows.index = np.arange(starting_index, starting_index + len(new_rows), dtype=np.int)\\n\\n logger.debug('finish: update linked table after transition')\\n return pd.concat([table, new_rows])\",\n \"def update():\\n query = db.session.query(db.Series).filter_by(following=True).all()\\n output.series('Updating {} series'.format(len(query)))\\n for follow in query:\\n series = series_by_url(follow.url)\\n series.update()\\n list_new()\",\n \"def save(self):\\n cur = get_cursor()\\n args = (self.associated_page, self.associated_name, self.title,\\n self.author, self.author_mail, self.comment_body, self.pub_date)\\n if self.comment_id is None:\\n cur.execute('''insert into comments (associated_page, associated_name,\\n title,\\n author, author_mail,\\n comment_body, pub_date)\\n values (?, ?, ?, ?, ?, ?, ?)''', args)\\n self.comment_id = cur.lastrowid\\n else:\\n args += (self.comment_id,)\\n cur.execute('''update comments set associated_page=?,\\n associated_name=?,\\n title=?, author=?,\\n author_mail=?, comment_body=?,\\n pub_date=? where comment_id = ?''', args)\\n cur.close()\",\n \"def requery(self, link_value=None):\\r\\n if link_value and self.link_field:\\r\\n sql = self.sql_select + \\\" WHERE \\\" + self.link_field + \\\"=?\\\" + self.sql_sort\\r\\n print(sql) # TODO delete this line\\r\\n self.cursor.execute(sql, (link_value,))\\r\\n else:\\r\\n print(self.sql_select + self.sql_sort) # TODO delete this line\\r\\n self.cursor.execute(self.sql_select + self.sql_sort) # executing query\\r\\n\\r\\n self.clear() # clear the listbox contents before re-loading\\r\\n for value in self.cursor:\\r\\n self.insert(tkinter.END, value[0]) # looping through the values one by one\\r\\n # and then actually adding each one to the listbox. We get a tuple representing\\r\\n # each row. As our query specified the column we want, and the id, we add th first\\r\\n # item from the tuple into the list and that's why we use the value 0.\\r\\n\\r\\n if self.linked_box:\\r\\n self.linked_box.clear()\",\n \"def process_new_links(period = media_period, force = False):\\r\\n links = Link._query(Link.c._date > timeago(period), sort = desc('_date'),\\r\\n data = True)\\r\\n results = {}\\r\\n jobs = []\\r\\n for link in fetch_things2(links):\\r\\n if link.is_self or link.promoted:\\r\\n continue\\r\\n elif not force and (link.has_thumbnail or link.media_object):\\r\\n continue\\r\\n\\r\\n jobs.append(make_link_info_job(results, link, g.useragent))\\r\\n\\r\\n #send links to a queue\\r\\n wq = WorkQueue(jobs, num_workers = 20, timeout = 30)\\r\\n wq.start()\\r\\n wq.jobs.join()\\r\\n\\r\\n #when the queue is finished, do the db writes in this thread\\r\\n for link, info in results.items():\\r\\n update_link(link, info[0], info[1])\",\n \"def link(self):\\n\\t\\tif self.next_row:\\n\\t\\t\\tprint(\\n\\t\\t\\t\\t\\\"Linking Row \\\" + str(\\n\\t\\t\\t\\t\\tself.num\\n\\t\\t\\t\\t) + \\\" to \\\" + str(\\n\\t\\t\\t\\t\\tself.next_row.num\\n\\t\\t\\t\\t)\\n\\t\\t\\t)\\n\\t\\t\\tfor key in self.next_row.neurons.keys():\\n\\t\\t\\t\\tself.linklst.append(key)\\n\\t\\t\\tfor key, neuron in self.neurons.items():\\n\\t\\t\\t\\tneuron.linkto = self.linklst\\n\\t\\t\\t\\tneuron.give(self.next_row.neurons)\\n\\t\\t\\tself.next_row.link()\\n\\n\\t\\telse:\\n\\t\\t\\tprint(\\\"All Rows Linked\\\")\",\n \"def add_to_index(index, keyword, url):\\n for entry in index:\\n if entry[0] == keyword:\\n for link in entry[1]:\\n if link[0] == url:\\n return\\n entry[1].append([url, 0])\\n return\\n # not found, add new keyword to index\\n index.append([keyword, [[url, 0]]])\",\n \"def link_data(self, link_data):\\n\\n self._link_data = link_data\",\n \"def articleAlreadyStored(self, curr_url):\\n\\n table = self.dynamodb.Table('Articles-Table') \\n\\n try:\\n response = table.get_item(\\n Key={\\n 'article-url': curr_url\\n }\\n )\\n except Exception as e:\\n log_line = \\\"Failed to access DynamoDB table: Articles-Table with following exception:\\\\n\\\"\\n log_line += str(e)\\n self.logger.writeToLog(log_line, False)\\n log_line = \\\"Exited prematurely at: \\\"\\n self.logger.writeToLog(log_line, True)\\n exit(0)\\n else:\\n try:\\n item = response['Item']\\n except:\\n return False # no item means article doesn't exist in database\\n else:\\n self.curr_url_stored_time = datetime.datetime.strptime(item[\\\"most-recent-update\\\"], \\\"%d/%m/%Y, %H:%M:%S\\\")\\n return True\",\n \"def save(self, request, item, linked_item, linked_item_form):\\n\\t\\tlinked_item.url = linked_item_form.cleaned_data['url']\\n\\t\\titem.description = linked_item_form.cleaned_data['subject']\\n\\t\\titem.priority = Priority.objects.get(id = linked_item_form.cleaned_data['priority'])\\n\\t\\tlinked_item.delivery_notes = linked_item_form.cleaned_data['delivery_notes']\\n\\t\\t#\\n\\t\\t# Look for actions other than save\\n\\t\\t#\\n\\t\\tif request.POST.get('update', '') == 'Completed':\\n\\t\\t\\titem.fixed = True\\n\\t\\t\\titem.validated = False\\n\\t\\tif request.POST.get('update', '') == 'Failed':\\n\\t\\t\\titem.fixed = False\\n\\t\\t\\titem.validated = True\\n\\t\\t\\titem.location = Location.objects.get(name = 'Production')\\n\\t\\tif request.POST.get('update', '') == 'Verified':\\n\\t\\t\\titem.fixed = True\\n\\t\\t\\titem.validated = True\\n\\n\\t\\titem.save()\\n\\t\\tlinked_item.save()\\n\\n\\t\\t#\\n\\t\\t# Check for comments and add\\n\\t\\t#\\n\\t\\tcomment_text = linked_item_form.cleaned_data['comments'].strip()\\n\\t\\tif comment_text != '':\\n\\t\\t\\tpost_comment(request, item, comment_text)\",\n \"def save(self, media):\\n if self.exists(media):\\n self.update(media)\\n else:\\n self.insert(media)\",\n \"def link(self, s_id):\\r\\n\\r\\n # Take the link entires from TOML file\\r\\n schedules = self.cfg.get('payload',{}).get('schedule')\\r\\n # Check for valid entires\\r\\n if schedules:\\r\\n for entries in schedules:\\r\\n # Construct payload \\r\\n for payload in entries.get('link'):\\r\\n # Check the entry vs a json schema\\r\\n check.check_entry(path='schemas/link.json', test=payload)\\r\\n # Post request\\r\\n if 'id' in self.schedules[-1]:\\r\\n payload['schedule'] = self.schedules[-1].get('id')\\r\\n if 'id' in self.workouts[-1]:\\r\\n payload['workout'] = self.workouts[-1].get('id')\\r\\n return self.add_post(payload, API.url_link, self.links)\",\n \"def update(self, links: list = None, **kwargs) -> None:\\n links = links if links else []\\n for link in self.links:\\n self.session.delete(link)\\n new_objs = [\\n DbCollectionLink(collection_id=self.id, collection_visibility=self.visibility, **link) for link in links\\n ]\\n self.session.add_all(new_objs)\\n self.session.flush()\\n\\n super().update(**kwargs)\",\n \"def link(address):\",\n \"def test_link_attribute_update(self):\\n entries = {\\n 'cn=huidige leden,ou=groups,dc=esmgquadrivium,dc=nl': {'cn': ['Huidige leden']},\\n 'cn=agroup,ou=groups,dc=esmgquadrivium,dc=nl': {'cn': ['agroup']},\\n 'uid=aperson,ou=people,dc=esmgquadrivium,dc=nl': {'uid': ['aperson']},\\n }\\n actual = clone(entries, link_attribute='linkID')\\n person_id = Person.objects.first().id\\n group1_id = QGroup.objects.get(name='Huidige leden').id\\n group2_id = QGroup.objects.get(~Q(name='Huidige leden')).id\\n\\n expect = [ModifyOperation('uid=aperson,ou=people,dc=esmgquadrivium,dc=nl', 'linkID', [person_id]),\\n ModifyOperation('cn=huidige leden,ou=groups,dc=esmgquadrivium,dc=nl', 'linkID', [group1_id]),\\n ModifyOperation('cn=agroup,ou=groups,dc=esmgquadrivium,dc=nl', 'linkID', [group2_id])]\\n self.assertCountEqual(expect, actual)\",\n \"def test_update_pci_link(self):\\n pass\",\n \"def oe_update(self, cr, uid, external_session, existing_rec_id, vals, resource, defaults, context=None):\\n if context is None: context={}\\n context['referential_id'] = external_session.referential_id.id #did it's needed somewhere?\\n return self.write(cr, uid, existing_rec_id, vals, context)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.623239","0.6042356","0.60063356","0.591801","0.5868072","0.58506054","0.5849309","0.5798199","0.5755617","0.5753384","0.573804","0.5720427","0.56632406","0.5543761","0.55327636","0.55120534","0.5490153","0.54851514","0.5463551","0.5451651","0.5436525","0.54263484","0.5421508","0.5413706","0.54044217","0.5372134","0.5360561","0.5335322","0.53250045","0.53120106","0.53044015","0.5286449","0.5277951","0.5261099","0.5259832","0.52533644","0.52453834","0.52411157","0.5233613","0.5201324","0.5188143","0.5147686","0.5147128","0.5131382","0.5109674","0.51055205","0.50993454","0.50987583","0.50987583","0.50987583","0.50987583","0.50987583","0.50987583","0.50987583","0.5090089","0.50858516","0.50820404","0.50756645","0.50751764","0.50744194","0.5067401","0.5059213","0.5058638","0.5047328","0.50471014","0.50329626","0.503129","0.50251687","0.50012624","0.5000997","0.5000724","0.49841043","0.49730533","0.49700567","0.49539915","0.4946628","0.49411273","0.49376372","0.4922716","0.4915243","0.48892874","0.48856005","0.48828077","0.4871369","0.48627824","0.48590207","0.4853877","0.48502058","0.4843651","0.48405713","0.48290807","0.48255372","0.4815733","0.4811244","0.48092288","0.4808282","0.48064074","0.4798383","0.47960532","0.47936788"],"string":"[\n \"0.623239\",\n \"0.6042356\",\n \"0.60063356\",\n \"0.591801\",\n \"0.5868072\",\n \"0.58506054\",\n \"0.5849309\",\n \"0.5798199\",\n \"0.5755617\",\n \"0.5753384\",\n \"0.573804\",\n \"0.5720427\",\n \"0.56632406\",\n \"0.5543761\",\n \"0.55327636\",\n \"0.55120534\",\n \"0.5490153\",\n \"0.54851514\",\n \"0.5463551\",\n \"0.5451651\",\n \"0.5436525\",\n \"0.54263484\",\n \"0.5421508\",\n \"0.5413706\",\n \"0.54044217\",\n \"0.5372134\",\n \"0.5360561\",\n \"0.5335322\",\n \"0.53250045\",\n \"0.53120106\",\n \"0.53044015\",\n \"0.5286449\",\n \"0.5277951\",\n \"0.5261099\",\n \"0.5259832\",\n \"0.52533644\",\n \"0.52453834\",\n \"0.52411157\",\n \"0.5233613\",\n \"0.5201324\",\n \"0.5188143\",\n \"0.5147686\",\n \"0.5147128\",\n \"0.5131382\",\n \"0.5109674\",\n \"0.51055205\",\n \"0.50993454\",\n \"0.50987583\",\n \"0.50987583\",\n \"0.50987583\",\n \"0.50987583\",\n \"0.50987583\",\n \"0.50987583\",\n \"0.50987583\",\n \"0.5090089\",\n \"0.50858516\",\n \"0.50820404\",\n \"0.50756645\",\n \"0.50751764\",\n \"0.50744194\",\n \"0.5067401\",\n \"0.5059213\",\n \"0.5058638\",\n \"0.5047328\",\n \"0.50471014\",\n \"0.50329626\",\n \"0.503129\",\n \"0.50251687\",\n \"0.50012624\",\n \"0.5000997\",\n \"0.5000724\",\n \"0.49841043\",\n \"0.49730533\",\n \"0.49700567\",\n \"0.49539915\",\n \"0.4946628\",\n \"0.49411273\",\n \"0.49376372\",\n \"0.4922716\",\n \"0.4915243\",\n \"0.48892874\",\n \"0.48856005\",\n \"0.48828077\",\n \"0.4871369\",\n \"0.48627824\",\n \"0.48590207\",\n \"0.4853877\",\n \"0.48502058\",\n \"0.4843651\",\n \"0.48405713\",\n \"0.48290807\",\n \"0.48255372\",\n \"0.4815733\",\n \"0.4811244\",\n \"0.48092288\",\n \"0.4808282\",\n \"0.48064074\",\n \"0.4798383\",\n \"0.47960532\",\n \"0.47936788\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7612958"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":83490,"cells":{"query":{"kind":"string","value":"Update fields on existing link"},"document":{"kind":"string","value":"def update(self, linkData):\n for field, value in linkData.items():\n if field == 'flags':\n setattr(self, field, value)\n elif(value is not None and value.strip() != ''):\n setattr(self, field, value)"},"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 relink(self, link_id):","def put(self):\n if jwthandler.authorize_action(self, 1) == False:\n return None\n\n userdata = jwthandler.decode_userdata(self.request.headers[\"Authorization\"])\n\n body_categories = {\"link_id\": 1, \"view_id\": 0, \"node_id_1\": 0, \"node_id_2\": 0, \"relationship_id\":0}\n link_dict = errorutil.check_fields(self.request.body.decode(), body_categories, self)\n\n print(link_dict)\n\n if link_dict == False:\n return None\n\n link_id = link_dict[\"link_id\"]\n del link_dict[\"link_id\"]\n\n if linkutil.change_link(link_id, link_dict, self) == False:\n return None\n\n formatted_message = loggerhandler.form_message_dictionary(userdata, \n \"links\", \n link_id,\n link_dict)\n\n\n loggerhandler.log_message(\"change\", formatted_message)\n\n self.write({\"message\":\"Success\"})","def update_links(self, new_link):\r\n self.__links = new_link","def links_update(link_from: str, link_to: str):\n if len(link_from) < 6:\n raise RuntimeError(\"from length must be at least 6\")\n if len(link_to) < 6:\n raise RuntimeError(\"to length must be at least 6\")\n base_link = get_short_link(link_from)\n if not base_link:\n raise RuntimeError(\"Couldn't find base link {}\".format(link_from))\n link_to_update = get_short_link(link_to)\n if not link_to_update:\n raise RuntimeError(\"Couldn't find existing short link {}\".format(link_to))\n link_to_update[\"full_hash\"] = base_link[\"full_hash\"]\n print(\"New link: {}\".format(pformat(link_to_update)))\n if are_you_sure(\"update link named {}\".format(link_to)):\n put_short_link(link_to_update)","def update_link(link, thumbnail, media_object):\r\n if thumbnail:\r\n link.has_thumbnail = True\r\n\r\n if media_object:\r\n link.media_object = media_object\r\n\r\n link._commit()","def update_link_id(self, data):\n\n self.data[data['project_name']]['nodes'][data['first']]['ports'][data['first_port']]['link_id'] = data['link_id']\n self.data[data['project_name']]['nodes'][data['second']]['ports'][data['second_port']]['link_id'] = data['link_id']","def link(self, link):\n\n self._set_field(\"link\", link)","def update(self, **kwargs):\n _url = (\n f\"{self.connector.base_url}/projects/{self.project_id}/links/{self.link_id}\"\n )\n\n # TODO: Verify that the passed kwargs are supported ones\n _response = self.connector.http_call(\"put\", _url, json_data=kwargs)\n\n # Update object\n self._update(_response.json())","def feed_link_decorator(context, feed):\n for item in feed.items:\n current_link = item['link']\n # print(current_link)\n new_link = current_link + FUD_DEFAULT['parameters']\n item['link'] = new_link\n # print(item)\n return feed","def _updateLinkDataRecord(self, record, columns=None):\n if columns is None:\n columns = self.getModelObj().getChildren()\n return model_navigator.iqModelNavigatorManager._updateLinkDataRecord(self, record=record, columns=columns)","def companylink_update(request, slug):\n\n #verifies if the company exists if not returns a 404 page\n company =get_object_or_404(Company,slug=slug)\n companylink_reference = get_object_or_404(CompanyLink, company=company)\n companylink_form = CompanyLinkForm(instance=companylink_reference)\n\n #verifies the person has access to the company or is an incubator employee\n edit = validate_user_company_access_or_redirect(request,company)\n\n #if the request is GET presents info, \n if request.method == 'GET':\n return render_to_response('companylink_form.html',{'form':companylink_form, 'info': companylink_reference},context_instance=RequestContext(request))\n else:\n companylink_form = CompanyLinkForm(request.POST, instance=companylink_reference)\n #if is POST Validates the form is well filled and save it redirecting to the company page \n if companylink_form.is_valid():\n companylink_form.save()\n\n return HttpResponseRedirect('/company/'+str(slug))\n #if not well filled redirect to the original update page and display error\n else:\n return render_to_response('companylink_form.html', \n {'form': companylink_form, 'form_errors': companylink_form.errors, 'info': companylink_reference},\n context_instance=RequestContext(request))","def test_link_attribute_update(self):\n entries = {\n 'cn=huidige leden,ou=groups,dc=esmgquadrivium,dc=nl': {'cn': ['Huidige leden']},\n 'cn=agroup,ou=groups,dc=esmgquadrivium,dc=nl': {'cn': ['agroup']},\n 'uid=aperson,ou=people,dc=esmgquadrivium,dc=nl': {'uid': ['aperson']},\n }\n actual = clone(entries, link_attribute='linkID')\n person_id = Person.objects.first().id\n group1_id = QGroup.objects.get(name='Huidige leden').id\n group2_id = QGroup.objects.get(~Q(name='Huidige leden')).id\n\n expect = [ModifyOperation('uid=aperson,ou=people,dc=esmgquadrivium,dc=nl', 'linkID', [person_id]),\n ModifyOperation('cn=huidige leden,ou=groups,dc=esmgquadrivium,dc=nl', 'linkID', [group1_id]),\n ModifyOperation('cn=agroup,ou=groups,dc=esmgquadrivium,dc=nl', 'linkID', [group2_id])]\n self.assertCountEqual(expect, actual)","def link_edit_callback(self):\n pass","def update(self):\n # TO DO for updating urls if changed\n pass","def update_link(self, link):\n if self not in (link.endpoint_a, link.endpoint_b):\n return False\n\n if self.link is None or self.link != link:\n self.link = link\n\n if link.endpoint_a == self:\n endpoint = link.endpoint_b\n else:\n endpoint = link.endpoint_a\n\n if endpoint.link is None or endpoint.link != link:\n endpoint.link = link\n\n return True","def updateOrInsert(cls, session, link, model, recordID):\n outLink = Link.lookupLink(session, link, model, recordID)\n if outLink is None: outLink = Link(**link)\n else: outLink.update(link)\n \n return outLink","def edit_link(db_object, text=None):\n if text is None:\n text = 'edit'\n return _make_link(db_object.update_url(), text)","def test_records_upload_links(self):\n link_data = {'protocol': 'http'}\n self.jwp_client.videos.update.return_value.update({'link': link_data})\n with mock.patch('mediaplatform_jwp.upload.record_link_response') as rlr_mock:\n management._perform_item_update(self.jwp_item)\n rlr_mock.assert_called_once_with(link_data, self.jwp_item)","def update_url_record(short_url, long_url, sidecar_text = None, owner = None):\r\n updated_record = {}\r\n updated_record['deleted'] = False\r\n updated_record['long_url'] = long_url\r\n updated_record['sidecar_text'] = sidecar_text\r\n updated_record['owner'] = owner\r\n updated_record['last_updated'] = datetime.now(timezone.utc)\r\n\r\n db_filter = {'name': short_url }\r\n\r\n db_collection.update_one(db_filter, { \"$set\": updated_record }, upsert=True)","def fusion_api_edit_uplink_set(self, body, uri, api=None, headers=None):\n return self.uplink_set.update(body, uri, api, headers)","def link(self, link):\n\n self.container['link'] = link","def post_add_link(self):\n course = courses.Course(self)\n link = course.add_link()\n link.href = ''\n course.save()\n self.redirect(self.get_action_url(\n 'edit_link', key=link.unit_id, extra_args={'is_newly_created': 1}))","def link(self, link):\n\n self._link = link","def link(self, link):\n\n self._link = link","def link(self, link):\n\n self._link = link","def link(self, link):\n\n self._link = link","def link(self, link):\n\n self._link = link","def link(self, link):\n\n self._link = link","def link(self, link):\n\n self._link = link","def generate_link_attr(d: Dict):\n d.update({\"link\": urljoin(\"https://vdb-kasf1i23nr1kl2j4.rapid7.com/v1/content/\", d.get(\"identifier\"))})","def edit_link(parser, token):\n return EditLinkTag(parser, token)","def update_url(url):\n url_db = select(u for u in Url if u.id == url.id).get()\n url_db.date_scanned = datetime.now()","def link_data(self, link_data):\n\n self._link_data = link_data","def set_info(self, link_url, blog_url, title, body):\n self.title = title\n self.body = body\n self.blog_url = blog_url\n self.link_url = link_url","def setLink(self, link):\n if type(link)==Member or link==None:\n self.link = link\n return True\n else:\n return False","def update(self, instance, validated_data):\n instance.href = validated_data.get('href', instance.href)\n instance.title = validated_data.get('title', instance.title)\n instance.datetime = validated_data.get('datetime', instance.datetime)\n instance.content = validated_data.get('content', instance.content)\n instance.coverimg = validated_data.get('coverimg', instance.title)\n instance.save()\n return instance","def update(self, params):","def update_link_attributes(self, tls,\n update_params: List[UpdateObjectParams],\n schema=None) -> Dict[str, Any]:\n if not schema:\n schema = self.schema\n updates = [\n {\n 'AttributeKey': {\n 'SchemaArn': schema,\n 'FacetName': i.facet,\n 'Name': i.attribute\n },\n 'AttributeAction': {\n 'AttributeActionType': i.action.name,\n 'AttributeUpdateValue': {\n i.value_type.name: i.value\n }\n }\n } for i in update_params]\n return cd_client.update_link_attributes(\n DirectoryArn=self._dir_arn,\n TypedLinkSpecifier=tls,\n AttributeUpdates=updates\n )","def save(self, *args, **kwargs):\n super(LinkBrand, self).save(*args, **kwargs)\n\n existing_links = UserLink.objects.filter(url__contains=self.domain)\n\n # Filter out any false positives\n for link in existing_links:\n domain = urlsplit(link.url).netloc\n\n if domain != self.domain:\n existing_links = existing_links.exclude(pk=link.pk)\n\n existing_links.update(icon=self)","def expand_link(update: Update, context: CallbackContext):\n query = update.callback_query\n link_id = query.data.split(\"expand:\")[1]\n\n with db.connect() as connection:\n link = db.get_link(connection, link_id)\n\n context.bot.edit_message_text(\n chat_id=query.message.chat_id,\n message_id=query.message.message_id,\n text=f\"Here it is: {link.title}\",\n reply_markup=keyboards.link_expand(link),\n )\n\n query.answer()","def link_iterable_by_fields(source_data, target_data, link_field, source_fields=None, target_fields=None, relink=False):\n if not relink:\n filter_func = lambda x: True\n else:\n filter_func = lambda x: not x.get(link_field)\n\n duplicates, candidates = {}, {}\n\n if source_fields and target_fields is None:\n target_fields = source_fields\n else:\n if source_fields is None:\n source_fields = DEFAULT_FIELDS\n if target_fields is None:\n target_fields = DEFAULT_FIELDS\n\n for obj in source_data:\n if 'id' not in obj:\n raise StrategyError(f\"Missing id field for object: {obj}\")\n key = activity_hash(obj, source_fields)\n if key in candidates:\n duplicates.setdefault(key, []).append(obj)\n else:\n candidates[key] = obj\n\n for obj in filter(filter_func, target_data):\n key = activity_hash(obj, target_fields)\n if key in duplicates:\n raise StrategyError(format_nonunique_key_error(obj, target_fields, duplicates[key]))\n elif key in candidates:\n obj[link_field] = candidates[key]['id']\n return target_data","def link_id(self, link_id):\n\n self._link_id = link_id","def _update(self, data: Dict[str, Any], fields_to_modify: List[str]):\n pass","def save(self, *args, **kwargs):\n domain = urlsplit(self.url).netloc\n\n try:\n self.icon = LinkBrand.objects.get(domain=domain)\n except ObjectDoesNotExist:\n pass\n\n super(UserLink, self).save(*args, **kwargs)","def UpdateRow(self, entry, new_row_data):\n entry.custom = {}\n for k, v in new_row_data.items():\n new_custom = gdata.spreadsheet.Custom()\n new_custom.column = k\n new_custom.text = v\n entry.custom[k] = new_custom\n for a_link in entry.link:\n if a_link.rel == 'edit':\n return self.Put(entry, a_link.href, \n converter=gdata.spreadsheet.SpreadsheetsListFromString)","def update_metadata(sess, asset_link):\n get_json = sess.get(asset_link).json()\n update_metadata = get_json['customFields']\n update_metadata['SANDAG Last Access Date'] = datetime.datetime.today().strftime('%D')\n\n sess.patch(asset_link, \n data=json.dumps(update_metadata)).json()","def update(table,record_id='',message='',next='',\n readonly_fields='',hidden_fields='',default_fields=''):\n\n PluginWikiWidgets._set_field_attributes(table, readonly_fields,hidden_fields,default_fields)\n if not record_id: record_id=request.args(-1)\n if not record_id.isdigit(): record_id=None\n return crud.update(db[table],record_id,message=message,next=next)","def test_link_serializer_update_success(self):\n link = Link(title=\"old\", clicks=1)\n data = {\"title\": \"abc\", \"clicks\": 123}\n serializer = LinkSerializer(link, data)\n self.assertTrue(serializer.is_valid(raise_exception=True))\n updated_link = serializer.save()\n self.assertEqual(link.id, updated_link.id)\n self.assertEqual(link.title, data[\"title\"])\n self.assertEqual(link.clicks, data[\"clicks\"])","def _update_from_rest_data(self) -> None:","def updateReferenceField(self, field): \n if not field.reference: return\n decoded = self.__dict__[field.name]\n if not decoded: self._references[field.name] = None; return\n if self._resolvereference == \"none\":\n self._references[field.name] = decoded\n elif self._resolvereference == \"text\":\n self._references[field.name] = self.TextCache[decoded] or \"(null)\" \n elif self._resolvereference == \"record\":\n self._references[field.name] = Record.ID (decoded)","def update(self, *args, **kwargs):","def add_links(update: Update, context: CallbackContext):\n urls = update.message.parse_entities([\"url\", \"text_link\"]).values()\n\n if urls:\n logging.info(f\"Got content of type url, text_link: {urls}\")\n\n with db.connect() as connection:\n existing_links = db.get_links(connection, update.message.from_user.id)\n if existing_links:\n distinct_links = set([url.casefold() for url in urls]) - set(\n [link.url for link in existing_links]\n )\n else:\n distinct_links = set([url.casefold() for url in urls])\n\n if distinct_links:\n success = context.bot.send_message(\n chat_id=update.message.chat_id,\n text=f\"⏳ Saving your link{'s' if len(distinct_links) > 1 else ''}... ⏳\",\n disable_notification=True,\n )\n\n db.add_links(connection, distinct_links, update.message.from_user.id)\n\n context.bot.edit_message_text(\n chat_id=update.message.chat_id,\n message_id=success.message_id,\n text=f\"✨ {len(distinct_links)} link{'s' if len(distinct_links) > 1 else ''} saved ✨\",\n )\n else:\n context.bot.send_message(\n chat_id=update.message.chat_id,\n text=f\"You already have that link saved! Look it up with *View all* or */all*\",\n parse_mode=telegram.ParseMode.MARKDOWN,\n )","def test_update_pci_link(self):\n pass","def update_item(self, table, item):","def update_link(self, index, center):\n if not self.destroyed:\n self.links[index].update(center, self.center)","def set_media(link):\r\n results = {}\r\n make_link_info_job(results, link, g.useragent)()\r\n update_link(link, *results[link])","def save(self, request, item, linked_item, linked_item_form):\n\t\tlinked_item.url = linked_item_form.cleaned_data['url']\n\t\titem.description = linked_item_form.cleaned_data['subject']\n\t\titem.priority = Priority.objects.get(id = linked_item_form.cleaned_data['priority'])\n\t\tlinked_item.delivery_notes = linked_item_form.cleaned_data['delivery_notes']\n\t\t#\n\t\t# Look for actions other than save\n\t\t#\n\t\tif request.POST.get('update', '') == 'Completed':\n\t\t\titem.fixed = True\n\t\t\titem.validated = False\n\t\tif request.POST.get('update', '') == 'Failed':\n\t\t\titem.fixed = False\n\t\t\titem.validated = True\n\t\t\titem.location = Location.objects.get(name = 'Production')\n\t\tif request.POST.get('update', '') == 'Verified':\n\t\t\titem.fixed = True\n\t\t\titem.validated = True\n\n\t\titem.save()\n\t\tlinked_item.save()\n\n\t\t#\n\t\t# Check for comments and add\n\t\t#\n\t\tcomment_text = linked_item_form.cleaned_data['comments'].strip()\n\t\tif comment_text != '':\n\t\t\tpost_comment(request, item, comment_text)","def update(self, links: list = None, **kwargs) -> None:\n links = links if links else []\n for link in self.links:\n self.session.delete(link)\n new_objs = [\n DbCollectionLink(collection_id=self.id, collection_visibility=self.visibility, **link) for link in links\n ]\n self.session.add_all(new_objs)\n self.session.flush()\n\n super().update(**kwargs)","def update(self, instance, validated_data):\n instance.avatar = validated_data.get('avatar', instance.avatar)\n instance.biography = validated_data.get('biography', instance.biography)\n instance.link = validated_data.get('link', instance.link)\n instance.save()\n return instance","def update_links(self):\n for a in self.book.xpath(\"//a[@href]\"):\n href = a.xpath(\"@href\")[0]\n index_list = a.xpath(\"@data-index\")\n \n ### If there is no data-index it is assumed link comes from initial book landing page (the index page)\n if index_list == []:\n index = self.manager.get_page_index(\"index.html\")\n else:\n index = index_list[0]\n \n ### Fix people who are bad at links\n if href.startswith(\"www.\"):\n href = \"https://\" + href\n a.set(\"href\", href)\n \n ## Correct for ambiguity (Naive assumption that this error only occours on index page)\n if href == \"./\":\n href = \"index.html\"\n \n if not href:\n return None\n \n href = self.manager.convert_link(href, index)\n a.set(\"href\", href)","def linkify(field_name):\n def _linkify(obj):\n linked_obj = getattr(obj, field_name)\n if linked_obj is None:\n return '-'\n app_label = linked_obj._meta.app_label\n model_name = linked_obj._meta.model_name\n view_name = f'admin:{app_label}_{model_name}_change'\n link_url = reverse(view_name, args=[linked_obj.pk])\n return format_html('<a href=\"{}\">{}</a>', link_url, linked_obj)\n\n _linkify.short_description = field_name # Sets column name\n return _linkify","def update_url(self):\n url = urljoin(getattr(self.parent, 'url', '') + '/', self.slug)\n if url != self.url:\n self.url = url\n self.save()\n\n for child in self.get_children():\n child.update_url()","def operate_on_link_relation(self, function, link, chunk_id=None, state='pending'):\n try:\n conn = psycopg2.connect(\"dbname='{0}'\".format(DATABASE))\n\n\n cur = conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor)\n\n if function == 'INSERT':\n cur.execute(\"INSERT INTO link (link, state) VALUES (%s, %s);\", (link, state))\n elif function == 'UPDATE_CHUNK_ID':\n cur.execute(\"UPDATE link SET chunk_id = %s WHERE link = %s;\", (chunk_id, link,))\n elif function == 'UPDATE_STATE':\n cur.execute(\"UPDATE link SET state = %s WHERE link = %s;\", (state, link,))\n elif function == 'DELETE':\n cur.execute(\"DELETE FROM link WHERE link = %s;\", (link,))\n else:\n print('NO FUNCTION FOUND')\n\n conn.commit()\n cur.close()\n except Exception as e:\n print(e)","def partial_update(self, request, *args, **kwargs):\n self.is_review_body_valid(self.get_serializer(instance=self.get_object(), data=request.data, partial=True))\n\n if \"shop_link\" in request.data:\n shop_pk = self.get_shop_pk(request.data.pop(\"shop_link\"))\n request.data[\"shop\"] = shop_pk\n\n return super().partial_update(request, *args, **kwargs)","def _updateLinkDataDataset(self, dataset, columns=None):\n if columns is None:\n columns = self.getModelObj().getChildren()\n return model_navigator.iqModelNavigatorManager._updateLinkDataDataset(self, dataset=dataset, columns=columns)","def linkify(field_name):\n\n def _linkify(obj):\n linked_obj = getattr(obj, field_name)\n if linked_obj is None:\n return '-'\n app_label = linked_obj._meta.app_label\n model_name = linked_obj._meta.model_name\n view_name = f'admin:{app_label}_{model_name}_change'\n link_url = reverse(view_name, args=[linked_obj.pk])\n return format_html('<a href=\"{}\">{}</a>', link_url, linked_obj)\n\n _linkify.short_description = field_name # Sets column name\n return _linkify","def add_link(self, link):\n raise NotImplementedError","def unlink(self, link_id):","def updateMacroLink(self):\n self.welcomePage.updateMacroLink()","def upsert_link_set(self, link_type, link_set):\n if link_set is None:\n self.links.pop(link_type, None)\n return\n links = copy.deepcopy(self.links)\n links.update({link_type: link_set})\n self.links = links","def _set_link(\n meta: Dict,\n link: Optional[Union[type(None), str, bool, KEChainPages]] = None,\n link_value: Optional[CardWidgetLinkValue] = None,\n link_target: Optional[Union[str, LinkTargets]] = LinkTargets.SAME_TAB,\n **kwargs,\n) -> Dict:\n meta[\"linkTarget\"] = check_enum(link_target, LinkTargets, \"link_target\")\n\n from pykechain.models import Activity\n\n if isinstance(link, Activity):\n if link.activity_type == ActivityType.TASK:\n default_link_value = CardWidgetLinkValue.TASK_LINK\n else:\n default_link_value = CardWidgetLinkValue.TREE_VIEW\n\n meta.update(\n {\n MetaWidget.CUSTOM_LINK: link.id,\n MetaWidget.SHOW_LINK_VALUE: default_link_value,\n }\n )\n elif isinstance(link, str) and is_uuid(link):\n meta.update(\n {\n MetaWidget.CUSTOM_LINK: link,\n MetaWidget.SHOW_LINK_VALUE: CardWidgetLinkValue.TASK_LINK,\n }\n )\n elif link is None or link is False:\n meta.update(\n {\n MetaWidget.CUSTOM_LINK: None,\n MetaWidget.SHOW_LINK_VALUE: CardWidgetLinkValue.NO_LINK,\n }\n )\n elif link in KEChainPages.values():\n meta.update(\n {\n MetaWidget.CUSTOM_LINK: \"\",\n MetaWidget.SHOW_LINK_VALUE: CardWidgetKEChainPageLink[link],\n }\n )\n else:\n meta.update(\n {\n MetaWidget.CUSTOM_LINK: link,\n MetaWidget.SHOW_LINK_VALUE: CardWidgetLinkValue.EXTERNAL_LINK,\n }\n )\n\n if link_value is not None:\n meta.update(\n {\n MetaWidget.SHOW_LINK_VALUE: check_enum(\n link_value, CardWidgetLinkValue, \"link_value\"\n ),\n }\n )\n\n return meta","def update_query(self, **updates):\r\n self._url_updates.update(updates)","def update(self, *args, **kwargs):\n pass","def update(self, *args, **kwargs):\n pass","def update(self, *args, **kwargs):\n pass","def updateContent(content, **kwargs):","def update_link_info_path(path_to_link_info):\n if not systeminfo.file_exists(path_to_link_info):\n print(\"File \"+str(path_to_link_info)+\" does not exist\")\n exit(1)\n else:\n try:\n with open(Constants.path_to_config_file, \"r\") as jsonFile:\n data = json.load(jsonFile)\n\n data[\"PathToLinkInfo\"] = path_to_link_info\n\n with open(Constants.path_to_config_file, \"w\") as jsonFile:\n json.dump(data, jsonFile, indent=4)\n except json.JSONDecodeError as e:\n print(\"Updating the path in config.json failed!\")\n exit(1)","def update(self, info):\n self.is_active = info.p.active\n self.rev_info = info.rev_info","def update(self, instance, validated_data):","def oe_update(self, cr, uid, external_session, existing_rec_id, vals, resource, defaults, context=None):\n if context is None: context={}\n context['referential_id'] = external_session.referential_id.id #did it's needed somewhere?\n return self.write(cr, uid, existing_rec_id, vals, context)","def add_link_setting(self, key, link, default):\n\n setting = self.settings().new_link(key, link, default)\n self._add_to_list_field(\"settings\", setting)","def link(request, link_id):\n link = Link.objects.get(id=link_id)\n link.visualization += 1\n link.save()\n return HttpResponseRedirect(link.url)","def edit_entry(self, id, body=None, link=None, **args):\n args.update(id=id)\n if body: args.update(body=body)\n if link: args.update(link=link)\n return self.fetch(\"/entry\", post_args=args)","def field_updater(request):\n model_pk = request.POST.get('model') # content-type\n model_ct = ContentType.objects.get(pk=model_pk)\n Model = model_ct.model_class()\n logger.debug(\"Updater model ID: %s, model: %s\" % (\n model_pk, model_ct\n ))\n\n if not request.user.is_superuser and \\\n not user_has_access(model_ct, request.user):\n return http_response({\n \"status\": \"FAILURE\",\n \"message\": \"Access denied.\",\n }, status=403)\n\n object_pk = request.POST.get('object')\n object = Model.objects.get(pk=object_pk)\n logger.debug(\"Object ID=%s, object=%s\" % (object_pk, object))\n if not object:\n return http_response({\n \"status\": \"FAILURE\",\n \"message\": \"Row %s not found.\" % (object_pk),\n }, status=400)\n\n field_name = request.POST.get('field')\n new_value = request.POST.get('value')\n logger.debug(\"field_name=%s, new_value=%s\" % (field_name, new_value))\n\n if \"__\" not in field_name:\n setattr(object, field_name, new_value)\n object.save()\n return http_response({\"status\": \"OK\", \"message\": \"Saved!\"})\n\n # NOTE: we _do not_ support many-to-many here. we\n # assume ForeignKey (with single value) as the only\n # possible relation type. (that's the only relation\n # field supported by dynamic models)\n field_parts = field_name.split(\"__\")\n last_part = field_parts.pop()\n path = object\n for rel in field_parts:\n logger.debug(\"Relation part: %s\" % (rel))\n path = getattr(path, rel).first()\n logger.debug(\"New relation path: %s\" % (path))\n\n logger.debug(\"Setting field=%s to value=%s\" % (last_part, new_value))\n if last_part != \"tags\":\n setattr(path, last_part, new_value)\n path.save()\n return http_response({\"status\": \"OK\", \"message\": \"Saved!\"})\n\n # handle tags separately\n fk_operation = request.POST.get(\"fk_operation\", \"add\")\n tagger = getattr(path, last_part)\n if fk_operation == \"add\" and tagger.filter(name=new_value).count():\n return http_response({\n \"status\": \"OK\", \"message\": \"Tag already exists.\"\n })\n\n if fk_operation == \"add\":\n tag, _ = Tag.objects.get_or_create(name=new_value)\n tagger.add(tag)\n return http_response({\n \"status\": \"OK\",\n \"object\": object_pk,\n \"message\": \"Tag added.\"\n })\n elif fk_operation == \"remove\":\n try:\n tag = Tag.objects.get(name=new_value)\n except Tag.DoesNotExist:\n return http_response({\n \"status\": \"OK\",\n \"message\": \"Non-existant tag, ignoring remove\"\n })\n tagger.remove(tag)\n # remove any tags that aren't being used anywhere\n n_tagged = tag.taggit_taggeditem_items.count()\n if not n_tagged:\n tag.delete()\n return http_response({\n \"status\": \"OK\",\n \"object\": object_pk,\n \"message\": \"Tag removed.\"\n })\n\n return http_response({\n \"status\": \"Failure\", \"message\": \"Bad tag operation.\"\n }, status=400)","def update_item(self, id: str, user: User, **kwargs) -> None:","def edit_link(instance):\n\n try:\n content_type = ContentType.objects.get_for_model(instance.__class__)\n except AttributeError:\n raise ValueError('Passed value must be registered model instance')\n else:\n model_admin_change_link = 'admin:{app}_{model}_change'.format(\n app=content_type.app_label,\n model=content_type.model\n )\n return reverse(model_admin_change_link, args=(instance.id,))","def set_property_setters_for_actions_and_links(self, meta):\n\t\tfor doctype, fieldname, field_map in (\n\t\t\t(\"DocType Link\", \"links\", doctype_link_properties),\n\t\t\t(\"DocType Action\", \"actions\", doctype_action_properties),\n\t\t\t(\"DocType State\", \"states\", doctype_state_properties),\n\t\t):\n\t\t\thas_custom = False\n\t\t\titems = []\n\t\t\tfor i, d in enumerate(self.get(fieldname) or []):\n\t\t\t\td.idx = i\n\t\t\t\tif frappe.db.exists(doctype, d.name) and not d.custom:\n\t\t\t\t\t# check property and apply property setter\n\t\t\t\t\toriginal = frappe.get_doc(doctype, d.name)\n\t\t\t\t\tfor prop, prop_type in field_map.items():\n\t\t\t\t\t\tif d.get(prop) != original.get(prop):\n\t\t\t\t\t\t\tself.make_property_setter(prop, d.get(prop), prop_type, apply_on=doctype, row_name=d.name)\n\t\t\t\t\titems.append(d.name)\n\t\t\t\telse:\n\t\t\t\t\t# custom - just insert/update\n\t\t\t\t\td.parent = self.doc_type\n\t\t\t\t\td.custom = 1\n\t\t\t\t\td.save(ignore_permissions=True)\n\t\t\t\t\thas_custom = True\n\t\t\t\t\titems.append(d.name)\n\n\t\t\tself.update_order_property_setter(has_custom, fieldname)\n\t\t\tself.clear_removed_items(doctype, items)","def link_apply(self, link):\n new_inputs = [\n self.remappers[\"grad_fprop\"].get(link.graph, inp)\n for inp in link.node.inputs\n ]\n link.new_node.inputs = new_inputs","def update_to(self, new):\r\n if self.idhex != new.idhex:\r\n plog(\"ERROR\", \"Update of router \"+self.nickname+\"changes idhex!\")\r\n for i in new.__dict__.iterkeys():\r\n if i == \"refcount\" or i == \"_generated\": continue\r\n self.__dict__[i] = new.__dict__[i]","def share_link(cls, user, link):","def share_link(cls, user, link):","def add_url(p_id, url):\n for product in all_products:\n if product['id'] == p_id:\n product['url'] = url\n product['product_id'] = p_id\n product.move_to_end('product_id', last=False)","def _update_link(self, site, d, links=None):\n if links is None:\n links = self.links\n\n if links.shape != self.links.shape:\n links = tf.reshape(links, self.links.shape)\n\n shape = self.site_idxs\n\n staples = self._get_staples(site, d, links)\n\n current_link = self.get_link(site, d, shape, links)\n proposed_link = current_link + np.random.choice(RANDOM_PHASES)\n\n minus_current_action = np.sum(\n [np.cos(current_link + s) for s in staples]\n )\n minus_proposed_action = np.sum(\n [np.cos(proposed_link + s) for s in staples]\n )\n\n # note that if the proposed action is smaller than the current action,\n # prob > 1 and we accept the new link\n prob = min(1, np.exp(self.beta * (minus_proposed_action\n - minus_current_action)))\n accept = 0\n if np.random.uniform() < prob:\n self.links[tuple(pbc(site, shape) + [d])] = proposed_link\n accept = 1\n return accept","def link_information_source(self, link_information_source):\n\n self._link_information_source = link_information_source","def mutate_urls(self, mutator):","def get_link(self, conf, link_id):\n\t\tpass","def updateFields(self, table_fullpath, fields_dict, options):\r\n \r\n rows = arcpy.UpdateCursor(table_fullpath, options.get('where_clause',''), options.get('spatial_reference',''),options.get('fields',''), options.get('sort_fields',''))\r\n try: \r\n for row in rows:\r\n for field_name in fields_dict:\r\n print \"updating field...\", str(field_name), fields_dict[field_name]\r\n row.setValue(str(field_name), fields_dict[field_name])\r\n rows.updateRow(row)\r\n finally:\r\n del rows","def update_flow_metadata(self, update_with):\n if update_with:\n source, clone = self._fetch_flowdetail(clone=True)\n clone.meta.update(update_with)\n self._with_connection(self._save_flow_detail, source, clone)","def test_link_serializer_update_validation(self):\n link = Link(title=\"old\", clicks=1)\n link.save()\n data = {\n \"title\": \"super duper long title that is more than the character length\",\n \"clicks\": 123,\n }\n serializer = LinkSerializer(link, data)\n self.assertFalse(serializer.is_valid())\n self.assertEqual(\n serializer.errors,\n {\n \"title\": [\n ErrorDetail(\n string=\"Ensure this field has no more than 36 characters.\",\n code=\"max_length\",\n )\n ]\n },\n )\n old_link = Link.objects.get(id=link.id)\n self.assertEqual(1, len(Link.objects.all()))\n self.assertEqual(link, old_link)","def price_link(self, price_link):\n\n self._price_link = price_link"],"string":"[\n \"def relink(self, link_id):\",\n \"def put(self):\\n if jwthandler.authorize_action(self, 1) == False:\\n return None\\n\\n userdata = jwthandler.decode_userdata(self.request.headers[\\\"Authorization\\\"])\\n\\n body_categories = {\\\"link_id\\\": 1, \\\"view_id\\\": 0, \\\"node_id_1\\\": 0, \\\"node_id_2\\\": 0, \\\"relationship_id\\\":0}\\n link_dict = errorutil.check_fields(self.request.body.decode(), body_categories, self)\\n\\n print(link_dict)\\n\\n if link_dict == False:\\n return None\\n\\n link_id = link_dict[\\\"link_id\\\"]\\n del link_dict[\\\"link_id\\\"]\\n\\n if linkutil.change_link(link_id, link_dict, self) == False:\\n return None\\n\\n formatted_message = loggerhandler.form_message_dictionary(userdata, \\n \\\"links\\\", \\n link_id,\\n link_dict)\\n\\n\\n loggerhandler.log_message(\\\"change\\\", formatted_message)\\n\\n self.write({\\\"message\\\":\\\"Success\\\"})\",\n \"def update_links(self, new_link):\\r\\n self.__links = new_link\",\n \"def links_update(link_from: str, link_to: str):\\n if len(link_from) < 6:\\n raise RuntimeError(\\\"from length must be at least 6\\\")\\n if len(link_to) < 6:\\n raise RuntimeError(\\\"to length must be at least 6\\\")\\n base_link = get_short_link(link_from)\\n if not base_link:\\n raise RuntimeError(\\\"Couldn't find base link {}\\\".format(link_from))\\n link_to_update = get_short_link(link_to)\\n if not link_to_update:\\n raise RuntimeError(\\\"Couldn't find existing short link {}\\\".format(link_to))\\n link_to_update[\\\"full_hash\\\"] = base_link[\\\"full_hash\\\"]\\n print(\\\"New link: {}\\\".format(pformat(link_to_update)))\\n if are_you_sure(\\\"update link named {}\\\".format(link_to)):\\n put_short_link(link_to_update)\",\n \"def update_link(link, thumbnail, media_object):\\r\\n if thumbnail:\\r\\n link.has_thumbnail = True\\r\\n\\r\\n if media_object:\\r\\n link.media_object = media_object\\r\\n\\r\\n link._commit()\",\n \"def update_link_id(self, data):\\n\\n self.data[data['project_name']]['nodes'][data['first']]['ports'][data['first_port']]['link_id'] = data['link_id']\\n self.data[data['project_name']]['nodes'][data['second']]['ports'][data['second_port']]['link_id'] = data['link_id']\",\n \"def link(self, link):\\n\\n self._set_field(\\\"link\\\", link)\",\n \"def update(self, **kwargs):\\n _url = (\\n f\\\"{self.connector.base_url}/projects/{self.project_id}/links/{self.link_id}\\\"\\n )\\n\\n # TODO: Verify that the passed kwargs are supported ones\\n _response = self.connector.http_call(\\\"put\\\", _url, json_data=kwargs)\\n\\n # Update object\\n self._update(_response.json())\",\n \"def feed_link_decorator(context, feed):\\n for item in feed.items:\\n current_link = item['link']\\n # print(current_link)\\n new_link = current_link + FUD_DEFAULT['parameters']\\n item['link'] = new_link\\n # print(item)\\n return feed\",\n \"def _updateLinkDataRecord(self, record, columns=None):\\n if columns is None:\\n columns = self.getModelObj().getChildren()\\n return model_navigator.iqModelNavigatorManager._updateLinkDataRecord(self, record=record, columns=columns)\",\n \"def companylink_update(request, slug):\\n\\n #verifies if the company exists if not returns a 404 page\\n company =get_object_or_404(Company,slug=slug)\\n companylink_reference = get_object_or_404(CompanyLink, company=company)\\n companylink_form = CompanyLinkForm(instance=companylink_reference)\\n\\n #verifies the person has access to the company or is an incubator employee\\n edit = validate_user_company_access_or_redirect(request,company)\\n\\n #if the request is GET presents info, \\n if request.method == 'GET':\\n return render_to_response('companylink_form.html',{'form':companylink_form, 'info': companylink_reference},context_instance=RequestContext(request))\\n else:\\n companylink_form = CompanyLinkForm(request.POST, instance=companylink_reference)\\n #if is POST Validates the form is well filled and save it redirecting to the company page \\n if companylink_form.is_valid():\\n companylink_form.save()\\n\\n return HttpResponseRedirect('/company/'+str(slug))\\n #if not well filled redirect to the original update page and display error\\n else:\\n return render_to_response('companylink_form.html', \\n {'form': companylink_form, 'form_errors': companylink_form.errors, 'info': companylink_reference},\\n context_instance=RequestContext(request))\",\n \"def test_link_attribute_update(self):\\n entries = {\\n 'cn=huidige leden,ou=groups,dc=esmgquadrivium,dc=nl': {'cn': ['Huidige leden']},\\n 'cn=agroup,ou=groups,dc=esmgquadrivium,dc=nl': {'cn': ['agroup']},\\n 'uid=aperson,ou=people,dc=esmgquadrivium,dc=nl': {'uid': ['aperson']},\\n }\\n actual = clone(entries, link_attribute='linkID')\\n person_id = Person.objects.first().id\\n group1_id = QGroup.objects.get(name='Huidige leden').id\\n group2_id = QGroup.objects.get(~Q(name='Huidige leden')).id\\n\\n expect = [ModifyOperation('uid=aperson,ou=people,dc=esmgquadrivium,dc=nl', 'linkID', [person_id]),\\n ModifyOperation('cn=huidige leden,ou=groups,dc=esmgquadrivium,dc=nl', 'linkID', [group1_id]),\\n ModifyOperation('cn=agroup,ou=groups,dc=esmgquadrivium,dc=nl', 'linkID', [group2_id])]\\n self.assertCountEqual(expect, actual)\",\n \"def link_edit_callback(self):\\n pass\",\n \"def update(self):\\n # TO DO for updating urls if changed\\n pass\",\n \"def update_link(self, link):\\n if self not in (link.endpoint_a, link.endpoint_b):\\n return False\\n\\n if self.link is None or self.link != link:\\n self.link = link\\n\\n if link.endpoint_a == self:\\n endpoint = link.endpoint_b\\n else:\\n endpoint = link.endpoint_a\\n\\n if endpoint.link is None or endpoint.link != link:\\n endpoint.link = link\\n\\n return True\",\n \"def updateOrInsert(cls, session, link, model, recordID):\\n outLink = Link.lookupLink(session, link, model, recordID)\\n if outLink is None: outLink = Link(**link)\\n else: outLink.update(link)\\n \\n return outLink\",\n \"def edit_link(db_object, text=None):\\n if text is None:\\n text = 'edit'\\n return _make_link(db_object.update_url(), text)\",\n \"def test_records_upload_links(self):\\n link_data = {'protocol': 'http'}\\n self.jwp_client.videos.update.return_value.update({'link': link_data})\\n with mock.patch('mediaplatform_jwp.upload.record_link_response') as rlr_mock:\\n management._perform_item_update(self.jwp_item)\\n rlr_mock.assert_called_once_with(link_data, self.jwp_item)\",\n \"def update_url_record(short_url, long_url, sidecar_text = None, owner = None):\\r\\n updated_record = {}\\r\\n updated_record['deleted'] = False\\r\\n updated_record['long_url'] = long_url\\r\\n updated_record['sidecar_text'] = sidecar_text\\r\\n updated_record['owner'] = owner\\r\\n updated_record['last_updated'] = datetime.now(timezone.utc)\\r\\n\\r\\n db_filter = {'name': short_url }\\r\\n\\r\\n db_collection.update_one(db_filter, { \\\"$set\\\": updated_record }, upsert=True)\",\n \"def fusion_api_edit_uplink_set(self, body, uri, api=None, headers=None):\\n return self.uplink_set.update(body, uri, api, headers)\",\n \"def link(self, link):\\n\\n self.container['link'] = link\",\n \"def post_add_link(self):\\n course = courses.Course(self)\\n link = course.add_link()\\n link.href = ''\\n course.save()\\n self.redirect(self.get_action_url(\\n 'edit_link', key=link.unit_id, extra_args={'is_newly_created': 1}))\",\n \"def link(self, link):\\n\\n self._link = link\",\n \"def link(self, link):\\n\\n self._link = link\",\n \"def link(self, link):\\n\\n self._link = link\",\n \"def link(self, link):\\n\\n self._link = link\",\n \"def link(self, link):\\n\\n self._link = link\",\n \"def link(self, link):\\n\\n self._link = link\",\n \"def link(self, link):\\n\\n self._link = link\",\n \"def generate_link_attr(d: Dict):\\n d.update({\\\"link\\\": urljoin(\\\"https://vdb-kasf1i23nr1kl2j4.rapid7.com/v1/content/\\\", d.get(\\\"identifier\\\"))})\",\n \"def edit_link(parser, token):\\n return EditLinkTag(parser, token)\",\n \"def update_url(url):\\n url_db = select(u for u in Url if u.id == url.id).get()\\n url_db.date_scanned = datetime.now()\",\n \"def link_data(self, link_data):\\n\\n self._link_data = link_data\",\n \"def set_info(self, link_url, blog_url, title, body):\\n self.title = title\\n self.body = body\\n self.blog_url = blog_url\\n self.link_url = link_url\",\n \"def setLink(self, link):\\n if type(link)==Member or link==None:\\n self.link = link\\n return True\\n else:\\n return False\",\n \"def update(self, instance, validated_data):\\n instance.href = validated_data.get('href', instance.href)\\n instance.title = validated_data.get('title', instance.title)\\n instance.datetime = validated_data.get('datetime', instance.datetime)\\n instance.content = validated_data.get('content', instance.content)\\n instance.coverimg = validated_data.get('coverimg', instance.title)\\n instance.save()\\n return instance\",\n \"def update(self, params):\",\n \"def update_link_attributes(self, tls,\\n update_params: List[UpdateObjectParams],\\n schema=None) -> Dict[str, Any]:\\n if not schema:\\n schema = self.schema\\n updates = [\\n {\\n 'AttributeKey': {\\n 'SchemaArn': schema,\\n 'FacetName': i.facet,\\n 'Name': i.attribute\\n },\\n 'AttributeAction': {\\n 'AttributeActionType': i.action.name,\\n 'AttributeUpdateValue': {\\n i.value_type.name: i.value\\n }\\n }\\n } for i in update_params]\\n return cd_client.update_link_attributes(\\n DirectoryArn=self._dir_arn,\\n TypedLinkSpecifier=tls,\\n AttributeUpdates=updates\\n )\",\n \"def save(self, *args, **kwargs):\\n super(LinkBrand, self).save(*args, **kwargs)\\n\\n existing_links = UserLink.objects.filter(url__contains=self.domain)\\n\\n # Filter out any false positives\\n for link in existing_links:\\n domain = urlsplit(link.url).netloc\\n\\n if domain != self.domain:\\n existing_links = existing_links.exclude(pk=link.pk)\\n\\n existing_links.update(icon=self)\",\n \"def expand_link(update: Update, context: CallbackContext):\\n query = update.callback_query\\n link_id = query.data.split(\\\"expand:\\\")[1]\\n\\n with db.connect() as connection:\\n link = db.get_link(connection, link_id)\\n\\n context.bot.edit_message_text(\\n chat_id=query.message.chat_id,\\n message_id=query.message.message_id,\\n text=f\\\"Here it is: {link.title}\\\",\\n reply_markup=keyboards.link_expand(link),\\n )\\n\\n query.answer()\",\n \"def link_iterable_by_fields(source_data, target_data, link_field, source_fields=None, target_fields=None, relink=False):\\n if not relink:\\n filter_func = lambda x: True\\n else:\\n filter_func = lambda x: not x.get(link_field)\\n\\n duplicates, candidates = {}, {}\\n\\n if source_fields and target_fields is None:\\n target_fields = source_fields\\n else:\\n if source_fields is None:\\n source_fields = DEFAULT_FIELDS\\n if target_fields is None:\\n target_fields = DEFAULT_FIELDS\\n\\n for obj in source_data:\\n if 'id' not in obj:\\n raise StrategyError(f\\\"Missing id field for object: {obj}\\\")\\n key = activity_hash(obj, source_fields)\\n if key in candidates:\\n duplicates.setdefault(key, []).append(obj)\\n else:\\n candidates[key] = obj\\n\\n for obj in filter(filter_func, target_data):\\n key = activity_hash(obj, target_fields)\\n if key in duplicates:\\n raise StrategyError(format_nonunique_key_error(obj, target_fields, duplicates[key]))\\n elif key in candidates:\\n obj[link_field] = candidates[key]['id']\\n return target_data\",\n \"def link_id(self, link_id):\\n\\n self._link_id = link_id\",\n \"def _update(self, data: Dict[str, Any], fields_to_modify: List[str]):\\n pass\",\n \"def save(self, *args, **kwargs):\\n domain = urlsplit(self.url).netloc\\n\\n try:\\n self.icon = LinkBrand.objects.get(domain=domain)\\n except ObjectDoesNotExist:\\n pass\\n\\n super(UserLink, self).save(*args, **kwargs)\",\n \"def UpdateRow(self, entry, new_row_data):\\n entry.custom = {}\\n for k, v in new_row_data.items():\\n new_custom = gdata.spreadsheet.Custom()\\n new_custom.column = k\\n new_custom.text = v\\n entry.custom[k] = new_custom\\n for a_link in entry.link:\\n if a_link.rel == 'edit':\\n return self.Put(entry, a_link.href, \\n converter=gdata.spreadsheet.SpreadsheetsListFromString)\",\n \"def update_metadata(sess, asset_link):\\n get_json = sess.get(asset_link).json()\\n update_metadata = get_json['customFields']\\n update_metadata['SANDAG Last Access Date'] = datetime.datetime.today().strftime('%D')\\n\\n sess.patch(asset_link, \\n data=json.dumps(update_metadata)).json()\",\n \"def update(table,record_id='',message='',next='',\\n readonly_fields='',hidden_fields='',default_fields=''):\\n\\n PluginWikiWidgets._set_field_attributes(table, readonly_fields,hidden_fields,default_fields)\\n if not record_id: record_id=request.args(-1)\\n if not record_id.isdigit(): record_id=None\\n return crud.update(db[table],record_id,message=message,next=next)\",\n \"def test_link_serializer_update_success(self):\\n link = Link(title=\\\"old\\\", clicks=1)\\n data = {\\\"title\\\": \\\"abc\\\", \\\"clicks\\\": 123}\\n serializer = LinkSerializer(link, data)\\n self.assertTrue(serializer.is_valid(raise_exception=True))\\n updated_link = serializer.save()\\n self.assertEqual(link.id, updated_link.id)\\n self.assertEqual(link.title, data[\\\"title\\\"])\\n self.assertEqual(link.clicks, data[\\\"clicks\\\"])\",\n \"def _update_from_rest_data(self) -> None:\",\n \"def updateReferenceField(self, field): \\n if not field.reference: return\\n decoded = self.__dict__[field.name]\\n if not decoded: self._references[field.name] = None; return\\n if self._resolvereference == \\\"none\\\":\\n self._references[field.name] = decoded\\n elif self._resolvereference == \\\"text\\\":\\n self._references[field.name] = self.TextCache[decoded] or \\\"(null)\\\" \\n elif self._resolvereference == \\\"record\\\":\\n self._references[field.name] = Record.ID (decoded)\",\n \"def update(self, *args, **kwargs):\",\n \"def add_links(update: Update, context: CallbackContext):\\n urls = update.message.parse_entities([\\\"url\\\", \\\"text_link\\\"]).values()\\n\\n if urls:\\n logging.info(f\\\"Got content of type url, text_link: {urls}\\\")\\n\\n with db.connect() as connection:\\n existing_links = db.get_links(connection, update.message.from_user.id)\\n if existing_links:\\n distinct_links = set([url.casefold() for url in urls]) - set(\\n [link.url for link in existing_links]\\n )\\n else:\\n distinct_links = set([url.casefold() for url in urls])\\n\\n if distinct_links:\\n success = context.bot.send_message(\\n chat_id=update.message.chat_id,\\n text=f\\\"⏳ Saving your link{'s' if len(distinct_links) > 1 else ''}... ⏳\\\",\\n disable_notification=True,\\n )\\n\\n db.add_links(connection, distinct_links, update.message.from_user.id)\\n\\n context.bot.edit_message_text(\\n chat_id=update.message.chat_id,\\n message_id=success.message_id,\\n text=f\\\"✨ {len(distinct_links)} link{'s' if len(distinct_links) > 1 else ''} saved ✨\\\",\\n )\\n else:\\n context.bot.send_message(\\n chat_id=update.message.chat_id,\\n text=f\\\"You already have that link saved! Look it up with *View all* or */all*\\\",\\n parse_mode=telegram.ParseMode.MARKDOWN,\\n )\",\n \"def test_update_pci_link(self):\\n pass\",\n \"def update_item(self, table, item):\",\n \"def update_link(self, index, center):\\n if not self.destroyed:\\n self.links[index].update(center, self.center)\",\n \"def set_media(link):\\r\\n results = {}\\r\\n make_link_info_job(results, link, g.useragent)()\\r\\n update_link(link, *results[link])\",\n \"def save(self, request, item, linked_item, linked_item_form):\\n\\t\\tlinked_item.url = linked_item_form.cleaned_data['url']\\n\\t\\titem.description = linked_item_form.cleaned_data['subject']\\n\\t\\titem.priority = Priority.objects.get(id = linked_item_form.cleaned_data['priority'])\\n\\t\\tlinked_item.delivery_notes = linked_item_form.cleaned_data['delivery_notes']\\n\\t\\t#\\n\\t\\t# Look for actions other than save\\n\\t\\t#\\n\\t\\tif request.POST.get('update', '') == 'Completed':\\n\\t\\t\\titem.fixed = True\\n\\t\\t\\titem.validated = False\\n\\t\\tif request.POST.get('update', '') == 'Failed':\\n\\t\\t\\titem.fixed = False\\n\\t\\t\\titem.validated = True\\n\\t\\t\\titem.location = Location.objects.get(name = 'Production')\\n\\t\\tif request.POST.get('update', '') == 'Verified':\\n\\t\\t\\titem.fixed = True\\n\\t\\t\\titem.validated = True\\n\\n\\t\\titem.save()\\n\\t\\tlinked_item.save()\\n\\n\\t\\t#\\n\\t\\t# Check for comments and add\\n\\t\\t#\\n\\t\\tcomment_text = linked_item_form.cleaned_data['comments'].strip()\\n\\t\\tif comment_text != '':\\n\\t\\t\\tpost_comment(request, item, comment_text)\",\n \"def update(self, links: list = None, **kwargs) -> None:\\n links = links if links else []\\n for link in self.links:\\n self.session.delete(link)\\n new_objs = [\\n DbCollectionLink(collection_id=self.id, collection_visibility=self.visibility, **link) for link in links\\n ]\\n self.session.add_all(new_objs)\\n self.session.flush()\\n\\n super().update(**kwargs)\",\n \"def update(self, instance, validated_data):\\n instance.avatar = validated_data.get('avatar', instance.avatar)\\n instance.biography = validated_data.get('biography', instance.biography)\\n instance.link = validated_data.get('link', instance.link)\\n instance.save()\\n return instance\",\n \"def update_links(self):\\n for a in self.book.xpath(\\\"//a[@href]\\\"):\\n href = a.xpath(\\\"@href\\\")[0]\\n index_list = a.xpath(\\\"@data-index\\\")\\n \\n ### If there is no data-index it is assumed link comes from initial book landing page (the index page)\\n if index_list == []:\\n index = self.manager.get_page_index(\\\"index.html\\\")\\n else:\\n index = index_list[0]\\n \\n ### Fix people who are bad at links\\n if href.startswith(\\\"www.\\\"):\\n href = \\\"https://\\\" + href\\n a.set(\\\"href\\\", href)\\n \\n ## Correct for ambiguity (Naive assumption that this error only occours on index page)\\n if href == \\\"./\\\":\\n href = \\\"index.html\\\"\\n \\n if not href:\\n return None\\n \\n href = self.manager.convert_link(href, index)\\n a.set(\\\"href\\\", href)\",\n \"def linkify(field_name):\\n def _linkify(obj):\\n linked_obj = getattr(obj, field_name)\\n if linked_obj is None:\\n return '-'\\n app_label = linked_obj._meta.app_label\\n model_name = linked_obj._meta.model_name\\n view_name = f'admin:{app_label}_{model_name}_change'\\n link_url = reverse(view_name, args=[linked_obj.pk])\\n return format_html('<a href=\\\"{}\\\">{}</a>', link_url, linked_obj)\\n\\n _linkify.short_description = field_name # Sets column name\\n return _linkify\",\n \"def update_url(self):\\n url = urljoin(getattr(self.parent, 'url', '') + '/', self.slug)\\n if url != self.url:\\n self.url = url\\n self.save()\\n\\n for child in self.get_children():\\n child.update_url()\",\n \"def operate_on_link_relation(self, function, link, chunk_id=None, state='pending'):\\n try:\\n conn = psycopg2.connect(\\\"dbname='{0}'\\\".format(DATABASE))\\n\\n\\n cur = conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor)\\n\\n if function == 'INSERT':\\n cur.execute(\\\"INSERT INTO link (link, state) VALUES (%s, %s);\\\", (link, state))\\n elif function == 'UPDATE_CHUNK_ID':\\n cur.execute(\\\"UPDATE link SET chunk_id = %s WHERE link = %s;\\\", (chunk_id, link,))\\n elif function == 'UPDATE_STATE':\\n cur.execute(\\\"UPDATE link SET state = %s WHERE link = %s;\\\", (state, link,))\\n elif function == 'DELETE':\\n cur.execute(\\\"DELETE FROM link WHERE link = %s;\\\", (link,))\\n else:\\n print('NO FUNCTION FOUND')\\n\\n conn.commit()\\n cur.close()\\n except Exception as e:\\n print(e)\",\n \"def partial_update(self, request, *args, **kwargs):\\n self.is_review_body_valid(self.get_serializer(instance=self.get_object(), data=request.data, partial=True))\\n\\n if \\\"shop_link\\\" in request.data:\\n shop_pk = self.get_shop_pk(request.data.pop(\\\"shop_link\\\"))\\n request.data[\\\"shop\\\"] = shop_pk\\n\\n return super().partial_update(request, *args, **kwargs)\",\n \"def _updateLinkDataDataset(self, dataset, columns=None):\\n if columns is None:\\n columns = self.getModelObj().getChildren()\\n return model_navigator.iqModelNavigatorManager._updateLinkDataDataset(self, dataset=dataset, columns=columns)\",\n \"def linkify(field_name):\\n\\n def _linkify(obj):\\n linked_obj = getattr(obj, field_name)\\n if linked_obj is None:\\n return '-'\\n app_label = linked_obj._meta.app_label\\n model_name = linked_obj._meta.model_name\\n view_name = f'admin:{app_label}_{model_name}_change'\\n link_url = reverse(view_name, args=[linked_obj.pk])\\n return format_html('<a href=\\\"{}\\\">{}</a>', link_url, linked_obj)\\n\\n _linkify.short_description = field_name # Sets column name\\n return _linkify\",\n \"def add_link(self, link):\\n raise NotImplementedError\",\n \"def unlink(self, link_id):\",\n \"def updateMacroLink(self):\\n self.welcomePage.updateMacroLink()\",\n \"def upsert_link_set(self, link_type, link_set):\\n if link_set is None:\\n self.links.pop(link_type, None)\\n return\\n links = copy.deepcopy(self.links)\\n links.update({link_type: link_set})\\n self.links = links\",\n \"def _set_link(\\n meta: Dict,\\n link: Optional[Union[type(None), str, bool, KEChainPages]] = None,\\n link_value: Optional[CardWidgetLinkValue] = None,\\n link_target: Optional[Union[str, LinkTargets]] = LinkTargets.SAME_TAB,\\n **kwargs,\\n) -> Dict:\\n meta[\\\"linkTarget\\\"] = check_enum(link_target, LinkTargets, \\\"link_target\\\")\\n\\n from pykechain.models import Activity\\n\\n if isinstance(link, Activity):\\n if link.activity_type == ActivityType.TASK:\\n default_link_value = CardWidgetLinkValue.TASK_LINK\\n else:\\n default_link_value = CardWidgetLinkValue.TREE_VIEW\\n\\n meta.update(\\n {\\n MetaWidget.CUSTOM_LINK: link.id,\\n MetaWidget.SHOW_LINK_VALUE: default_link_value,\\n }\\n )\\n elif isinstance(link, str) and is_uuid(link):\\n meta.update(\\n {\\n MetaWidget.CUSTOM_LINK: link,\\n MetaWidget.SHOW_LINK_VALUE: CardWidgetLinkValue.TASK_LINK,\\n }\\n )\\n elif link is None or link is False:\\n meta.update(\\n {\\n MetaWidget.CUSTOM_LINK: None,\\n MetaWidget.SHOW_LINK_VALUE: CardWidgetLinkValue.NO_LINK,\\n }\\n )\\n elif link in KEChainPages.values():\\n meta.update(\\n {\\n MetaWidget.CUSTOM_LINK: \\\"\\\",\\n MetaWidget.SHOW_LINK_VALUE: CardWidgetKEChainPageLink[link],\\n }\\n )\\n else:\\n meta.update(\\n {\\n MetaWidget.CUSTOM_LINK: link,\\n MetaWidget.SHOW_LINK_VALUE: CardWidgetLinkValue.EXTERNAL_LINK,\\n }\\n )\\n\\n if link_value is not None:\\n meta.update(\\n {\\n MetaWidget.SHOW_LINK_VALUE: check_enum(\\n link_value, CardWidgetLinkValue, \\\"link_value\\\"\\n ),\\n }\\n )\\n\\n return meta\",\n \"def update_query(self, **updates):\\r\\n self._url_updates.update(updates)\",\n \"def update(self, *args, **kwargs):\\n pass\",\n \"def update(self, *args, **kwargs):\\n pass\",\n \"def update(self, *args, **kwargs):\\n pass\",\n \"def updateContent(content, **kwargs):\",\n \"def update_link_info_path(path_to_link_info):\\n if not systeminfo.file_exists(path_to_link_info):\\n print(\\\"File \\\"+str(path_to_link_info)+\\\" does not exist\\\")\\n exit(1)\\n else:\\n try:\\n with open(Constants.path_to_config_file, \\\"r\\\") as jsonFile:\\n data = json.load(jsonFile)\\n\\n data[\\\"PathToLinkInfo\\\"] = path_to_link_info\\n\\n with open(Constants.path_to_config_file, \\\"w\\\") as jsonFile:\\n json.dump(data, jsonFile, indent=4)\\n except json.JSONDecodeError as e:\\n print(\\\"Updating the path in config.json failed!\\\")\\n exit(1)\",\n \"def update(self, info):\\n self.is_active = info.p.active\\n self.rev_info = info.rev_info\",\n \"def update(self, instance, validated_data):\",\n \"def oe_update(self, cr, uid, external_session, existing_rec_id, vals, resource, defaults, context=None):\\n if context is None: context={}\\n context['referential_id'] = external_session.referential_id.id #did it's needed somewhere?\\n return self.write(cr, uid, existing_rec_id, vals, context)\",\n \"def add_link_setting(self, key, link, default):\\n\\n setting = self.settings().new_link(key, link, default)\\n self._add_to_list_field(\\\"settings\\\", setting)\",\n \"def link(request, link_id):\\n link = Link.objects.get(id=link_id)\\n link.visualization += 1\\n link.save()\\n return HttpResponseRedirect(link.url)\",\n \"def edit_entry(self, id, body=None, link=None, **args):\\n args.update(id=id)\\n if body: args.update(body=body)\\n if link: args.update(link=link)\\n return self.fetch(\\\"/entry\\\", post_args=args)\",\n \"def field_updater(request):\\n model_pk = request.POST.get('model') # content-type\\n model_ct = ContentType.objects.get(pk=model_pk)\\n Model = model_ct.model_class()\\n logger.debug(\\\"Updater model ID: %s, model: %s\\\" % (\\n model_pk, model_ct\\n ))\\n\\n if not request.user.is_superuser and \\\\\\n not user_has_access(model_ct, request.user):\\n return http_response({\\n \\\"status\\\": \\\"FAILURE\\\",\\n \\\"message\\\": \\\"Access denied.\\\",\\n }, status=403)\\n\\n object_pk = request.POST.get('object')\\n object = Model.objects.get(pk=object_pk)\\n logger.debug(\\\"Object ID=%s, object=%s\\\" % (object_pk, object))\\n if not object:\\n return http_response({\\n \\\"status\\\": \\\"FAILURE\\\",\\n \\\"message\\\": \\\"Row %s not found.\\\" % (object_pk),\\n }, status=400)\\n\\n field_name = request.POST.get('field')\\n new_value = request.POST.get('value')\\n logger.debug(\\\"field_name=%s, new_value=%s\\\" % (field_name, new_value))\\n\\n if \\\"__\\\" not in field_name:\\n setattr(object, field_name, new_value)\\n object.save()\\n return http_response({\\\"status\\\": \\\"OK\\\", \\\"message\\\": \\\"Saved!\\\"})\\n\\n # NOTE: we _do not_ support many-to-many here. we\\n # assume ForeignKey (with single value) as the only\\n # possible relation type. (that's the only relation\\n # field supported by dynamic models)\\n field_parts = field_name.split(\\\"__\\\")\\n last_part = field_parts.pop()\\n path = object\\n for rel in field_parts:\\n logger.debug(\\\"Relation part: %s\\\" % (rel))\\n path = getattr(path, rel).first()\\n logger.debug(\\\"New relation path: %s\\\" % (path))\\n\\n logger.debug(\\\"Setting field=%s to value=%s\\\" % (last_part, new_value))\\n if last_part != \\\"tags\\\":\\n setattr(path, last_part, new_value)\\n path.save()\\n return http_response({\\\"status\\\": \\\"OK\\\", \\\"message\\\": \\\"Saved!\\\"})\\n\\n # handle tags separately\\n fk_operation = request.POST.get(\\\"fk_operation\\\", \\\"add\\\")\\n tagger = getattr(path, last_part)\\n if fk_operation == \\\"add\\\" and tagger.filter(name=new_value).count():\\n return http_response({\\n \\\"status\\\": \\\"OK\\\", \\\"message\\\": \\\"Tag already exists.\\\"\\n })\\n\\n if fk_operation == \\\"add\\\":\\n tag, _ = Tag.objects.get_or_create(name=new_value)\\n tagger.add(tag)\\n return http_response({\\n \\\"status\\\": \\\"OK\\\",\\n \\\"object\\\": object_pk,\\n \\\"message\\\": \\\"Tag added.\\\"\\n })\\n elif fk_operation == \\\"remove\\\":\\n try:\\n tag = Tag.objects.get(name=new_value)\\n except Tag.DoesNotExist:\\n return http_response({\\n \\\"status\\\": \\\"OK\\\",\\n \\\"message\\\": \\\"Non-existant tag, ignoring remove\\\"\\n })\\n tagger.remove(tag)\\n # remove any tags that aren't being used anywhere\\n n_tagged = tag.taggit_taggeditem_items.count()\\n if not n_tagged:\\n tag.delete()\\n return http_response({\\n \\\"status\\\": \\\"OK\\\",\\n \\\"object\\\": object_pk,\\n \\\"message\\\": \\\"Tag removed.\\\"\\n })\\n\\n return http_response({\\n \\\"status\\\": \\\"Failure\\\", \\\"message\\\": \\\"Bad tag operation.\\\"\\n }, status=400)\",\n \"def update_item(self, id: str, user: User, **kwargs) -> None:\",\n \"def edit_link(instance):\\n\\n try:\\n content_type = ContentType.objects.get_for_model(instance.__class__)\\n except AttributeError:\\n raise ValueError('Passed value must be registered model instance')\\n else:\\n model_admin_change_link = 'admin:{app}_{model}_change'.format(\\n app=content_type.app_label,\\n model=content_type.model\\n )\\n return reverse(model_admin_change_link, args=(instance.id,))\",\n \"def set_property_setters_for_actions_and_links(self, meta):\\n\\t\\tfor doctype, fieldname, field_map in (\\n\\t\\t\\t(\\\"DocType Link\\\", \\\"links\\\", doctype_link_properties),\\n\\t\\t\\t(\\\"DocType Action\\\", \\\"actions\\\", doctype_action_properties),\\n\\t\\t\\t(\\\"DocType State\\\", \\\"states\\\", doctype_state_properties),\\n\\t\\t):\\n\\t\\t\\thas_custom = False\\n\\t\\t\\titems = []\\n\\t\\t\\tfor i, d in enumerate(self.get(fieldname) or []):\\n\\t\\t\\t\\td.idx = i\\n\\t\\t\\t\\tif frappe.db.exists(doctype, d.name) and not d.custom:\\n\\t\\t\\t\\t\\t# check property and apply property setter\\n\\t\\t\\t\\t\\toriginal = frappe.get_doc(doctype, d.name)\\n\\t\\t\\t\\t\\tfor prop, prop_type in field_map.items():\\n\\t\\t\\t\\t\\t\\tif d.get(prop) != original.get(prop):\\n\\t\\t\\t\\t\\t\\t\\tself.make_property_setter(prop, d.get(prop), prop_type, apply_on=doctype, row_name=d.name)\\n\\t\\t\\t\\t\\titems.append(d.name)\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t# custom - just insert/update\\n\\t\\t\\t\\t\\td.parent = self.doc_type\\n\\t\\t\\t\\t\\td.custom = 1\\n\\t\\t\\t\\t\\td.save(ignore_permissions=True)\\n\\t\\t\\t\\t\\thas_custom = True\\n\\t\\t\\t\\t\\titems.append(d.name)\\n\\n\\t\\t\\tself.update_order_property_setter(has_custom, fieldname)\\n\\t\\t\\tself.clear_removed_items(doctype, items)\",\n \"def link_apply(self, link):\\n new_inputs = [\\n self.remappers[\\\"grad_fprop\\\"].get(link.graph, inp)\\n for inp in link.node.inputs\\n ]\\n link.new_node.inputs = new_inputs\",\n \"def update_to(self, new):\\r\\n if self.idhex != new.idhex:\\r\\n plog(\\\"ERROR\\\", \\\"Update of router \\\"+self.nickname+\\\"changes idhex!\\\")\\r\\n for i in new.__dict__.iterkeys():\\r\\n if i == \\\"refcount\\\" or i == \\\"_generated\\\": continue\\r\\n self.__dict__[i] = new.__dict__[i]\",\n \"def share_link(cls, user, link):\",\n \"def share_link(cls, user, link):\",\n \"def add_url(p_id, url):\\n for product in all_products:\\n if product['id'] == p_id:\\n product['url'] = url\\n product['product_id'] = p_id\\n product.move_to_end('product_id', last=False)\",\n \"def _update_link(self, site, d, links=None):\\n if links is None:\\n links = self.links\\n\\n if links.shape != self.links.shape:\\n links = tf.reshape(links, self.links.shape)\\n\\n shape = self.site_idxs\\n\\n staples = self._get_staples(site, d, links)\\n\\n current_link = self.get_link(site, d, shape, links)\\n proposed_link = current_link + np.random.choice(RANDOM_PHASES)\\n\\n minus_current_action = np.sum(\\n [np.cos(current_link + s) for s in staples]\\n )\\n minus_proposed_action = np.sum(\\n [np.cos(proposed_link + s) for s in staples]\\n )\\n\\n # note that if the proposed action is smaller than the current action,\\n # prob > 1 and we accept the new link\\n prob = min(1, np.exp(self.beta * (minus_proposed_action\\n - minus_current_action)))\\n accept = 0\\n if np.random.uniform() < prob:\\n self.links[tuple(pbc(site, shape) + [d])] = proposed_link\\n accept = 1\\n return accept\",\n \"def link_information_source(self, link_information_source):\\n\\n self._link_information_source = link_information_source\",\n \"def mutate_urls(self, mutator):\",\n \"def get_link(self, conf, link_id):\\n\\t\\tpass\",\n \"def updateFields(self, table_fullpath, fields_dict, options):\\r\\n \\r\\n rows = arcpy.UpdateCursor(table_fullpath, options.get('where_clause',''), options.get('spatial_reference',''),options.get('fields',''), options.get('sort_fields',''))\\r\\n try: \\r\\n for row in rows:\\r\\n for field_name in fields_dict:\\r\\n print \\\"updating field...\\\", str(field_name), fields_dict[field_name]\\r\\n row.setValue(str(field_name), fields_dict[field_name])\\r\\n rows.updateRow(row)\\r\\n finally:\\r\\n del rows\",\n \"def update_flow_metadata(self, update_with):\\n if update_with:\\n source, clone = self._fetch_flowdetail(clone=True)\\n clone.meta.update(update_with)\\n self._with_connection(self._save_flow_detail, source, clone)\",\n \"def test_link_serializer_update_validation(self):\\n link = Link(title=\\\"old\\\", clicks=1)\\n link.save()\\n data = {\\n \\\"title\\\": \\\"super duper long title that is more than the character length\\\",\\n \\\"clicks\\\": 123,\\n }\\n serializer = LinkSerializer(link, data)\\n self.assertFalse(serializer.is_valid())\\n self.assertEqual(\\n serializer.errors,\\n {\\n \\\"title\\\": [\\n ErrorDetail(\\n string=\\\"Ensure this field has no more than 36 characters.\\\",\\n code=\\\"max_length\\\",\\n )\\n ]\\n },\\n )\\n old_link = Link.objects.get(id=link.id)\\n self.assertEqual(1, len(Link.objects.all()))\\n self.assertEqual(link, old_link)\",\n \"def price_link(self, price_link):\\n\\n self._price_link = price_link\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.68344724","0.66124517","0.660164","0.65914994","0.6363283","0.63509566","0.63125825","0.6273736","0.61451024","0.61311626","0.61165154","0.6072572","0.60497147","0.60104465","0.60076165","0.5906549","0.5847444","0.5844992","0.5826938","0.58229995","0.58023095","0.5791657","0.57741654","0.57741654","0.57741654","0.57741654","0.57741654","0.57741654","0.57741654","0.57069665","0.5660983","0.5634986","0.5632283","0.5611247","0.5600757","0.5590959","0.5585478","0.55717766","0.5558968","0.5509395","0.55045307","0.5503172","0.54981583","0.54945666","0.548418","0.5466409","0.5464455","0.54626924","0.54542476","0.5436394","0.54337376","0.54294574","0.5422016","0.541449","0.5398396","0.53870916","0.537984","0.53769535","0.53743523","0.53669834","0.5366768","0.5365539","0.53628224","0.5362396","0.53608334","0.53505343","0.53434575","0.5339021","0.5333004","0.5303674","0.5302696","0.52981496","0.52943563","0.52943563","0.52943563","0.5290767","0.52783686","0.5272251","0.52652353","0.526076","0.5247671","0.52403694","0.5221375","0.52175933","0.5211083","0.5209084","0.5193655","0.5187111","0.5169665","0.5166337","0.5166337","0.51640594","0.51602495","0.51572806","0.5153494","0.5153181","0.51528466","0.5151031","0.51374036","0.5135994"],"string":"[\n \"0.68344724\",\n \"0.66124517\",\n \"0.660164\",\n \"0.65914994\",\n \"0.6363283\",\n \"0.63509566\",\n \"0.63125825\",\n \"0.6273736\",\n \"0.61451024\",\n \"0.61311626\",\n \"0.61165154\",\n \"0.6072572\",\n \"0.60497147\",\n \"0.60104465\",\n \"0.60076165\",\n \"0.5906549\",\n \"0.5847444\",\n \"0.5844992\",\n \"0.5826938\",\n \"0.58229995\",\n \"0.58023095\",\n \"0.5791657\",\n \"0.57741654\",\n \"0.57741654\",\n \"0.57741654\",\n \"0.57741654\",\n \"0.57741654\",\n \"0.57741654\",\n \"0.57741654\",\n \"0.57069665\",\n \"0.5660983\",\n \"0.5634986\",\n \"0.5632283\",\n \"0.5611247\",\n \"0.5600757\",\n \"0.5590959\",\n \"0.5585478\",\n \"0.55717766\",\n \"0.5558968\",\n \"0.5509395\",\n \"0.55045307\",\n \"0.5503172\",\n \"0.54981583\",\n \"0.54945666\",\n \"0.548418\",\n \"0.5466409\",\n \"0.5464455\",\n \"0.54626924\",\n \"0.54542476\",\n \"0.5436394\",\n \"0.54337376\",\n \"0.54294574\",\n \"0.5422016\",\n \"0.541449\",\n \"0.5398396\",\n \"0.53870916\",\n \"0.537984\",\n \"0.53769535\",\n \"0.53743523\",\n \"0.53669834\",\n \"0.5366768\",\n \"0.5365539\",\n \"0.53628224\",\n \"0.5362396\",\n \"0.53608334\",\n \"0.53505343\",\n \"0.53434575\",\n \"0.5339021\",\n \"0.5333004\",\n \"0.5303674\",\n \"0.5302696\",\n \"0.52981496\",\n \"0.52943563\",\n \"0.52943563\",\n \"0.52943563\",\n \"0.5290767\",\n \"0.52783686\",\n \"0.5272251\",\n \"0.52652353\",\n \"0.526076\",\n \"0.5247671\",\n \"0.52403694\",\n \"0.5221375\",\n \"0.52175933\",\n \"0.5211083\",\n \"0.5209084\",\n \"0.5193655\",\n \"0.5187111\",\n \"0.5169665\",\n \"0.5166337\",\n \"0.5166337\",\n \"0.51640594\",\n \"0.51602495\",\n \"0.51572806\",\n \"0.5153494\",\n \"0.5153181\",\n \"0.51528466\",\n \"0.5151031\",\n \"0.51374036\",\n \"0.5135994\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.68995327"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":83491,"cells":{"query":{"kind":"string","value":"Query database for link related to current record. Return link if found, otherwise return None"},"document":{"kind":"string","value":"def lookupLink(cls, session, link, model, recordID):\n checkURL = Link.httpRegexSub(link.get('url', None))\n return session.query(cls)\\\n .join(model.__tablename__)\\\n .filter(model.id == recordID)\\\n .filter(cls.url == checkURL)\\\n .one_or_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 _link_for_query(self, query):\r\n results = list(query)\r\n return results[0] if results else None","def link(self) -> Optional[str]:\n return pulumi.get(self, \"link\")","def link(self) -> Optional[str]:\n return pulumi.get(self, \"link\")","def _get_self_record(self, record: dict) -> Link:\n rel = \"self\"\n href = os.path.join(self.api_endpoint, record[\"id\"])\n return Link(href=href, rel=rel)","def link(self):\n return self._link","def link(self):\n return self._link","def link(self):\n return self._link","def Link(self, default=None):\n return self.data.get('links', {}).get('self', default)","def getLink(self):\n return self.link","def self_link(self):\n return self._json['coredata'].get('link', [])[0].get('@href')","def getLink(self):","def link(self):\n\n return self._get_field(\"link\")","def search_link(self):\n return self._json['coredata'].get('link', [])[2].get('@href')","def link(self):\n return self.container['link']","def fetch_url_record(short_url = None):\r\n\r\n if short_url:\r\n url_record = db_collection.find_one({'name': short_url, 'deleted': False})\r\n\r\n if url_record:\r\n return url_record\r\n\r\n return None","def get_object(self, url_id, user_id):\n try:\n return Link.objects.get(id=url_id, user=user_id)\n except Link.DoesNotExist:\n return None","def get_link(self, conf, link_id):\n\t\tpass","def self_link_with_id(self) -> str:\n return pulumi.get(self, \"self_link_with_id\")","def self_link_with_id(self) -> str:\n return pulumi.get(self, \"self_link_with_id\")","def self_link(self) -> str:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> str:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> str:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> str:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> str:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> str:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> str:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> str:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> str:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"self_link\")","def next_link(self) -> Optional[str]:\n return pulumi.get(self, \"next_link\")","def find_url(self, url: Url) -> Optional[sqlite3.Row]:\n\n sql = \"\"\"SELECT rowid, url as 'url [url]', title,\n added as 'added [local_datetime]',\n updated as 'updated [local_datetime]',\n deleted as 'deleted [local_datetime]',\n tags, comments\n FROM bookmarks\n WHERE domain=? AND url=?\"\"\"\n return self._selectOne(sql, (url.domain, url.address))","def linkno(self):\n if hasattr(self, \"_linkno\"):\n return self._linkno\n else:\n return None","def updateOrInsert(cls, session, link, model, recordID):\n outLink = Link.lookupLink(session, link, model, recordID)\n if outLink is None: outLink = Link(**link)\n else: outLink.update(link)\n \n return outLink","def _get_link(li):\n try:\n a = li.find(\"a\")\n link = a[\"href\"]\n except Exception:\n return None\n return link","def get_link_data(self, hashed_link):\n\n try:\n data = self.link_db[hashed_link]\n return data\n except:\n return None","async def get_external_link(segmentnr: str):\n query_result = {\"link\": \"\"}\n filename = segmentnr.split(':')[0]\n database = get_db()\n query_displayname = database.AQLQuery(\n query=main_queries.QUERY_LINK,\n bindVars={\n \"filename\": filename\n },\n rawResults=True\n )\n query_result = {\"link\": query_displayname.result[0]}\n return query_result","def self_link(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"self_link\")","def self_link(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"self_link\")","def get_data_link(self, ctx, params):\n # ctx is the context object\n # return variables are: link\n #BEGIN get_data_link\n id_ = _get_id_from_object(params, 'linkid', required=True)\n _check_admin(\n self._user_lookup, ctx[_CTX_TOKEN], _AdminPermission.READ,\n # pretty annoying to test ctx.log_info is working, do it manually\n 'get_data_link', ctx.log_info)\n dl = self._samples.get_data_link_admin(id_)\n link = _links_to_dicts([dl])[0]\n #END get_data_link\n\n # At some point might do deeper type checking...\n if not isinstance(link, dict):\n raise ValueError('Method get_data_link return value ' +\n 'link is not type dict as required.')\n # return the results\n return [link]","def find_id(self, uid: int) -> Optional[sqlite3.Row]:\n\n sql = \"\"\"SELECT rowid, url as 'url [url]', title,\n added as 'added [local_datetime]',\n updated as 'updated [local_datetime]',\n deleted as 'deleted [local_datetime]',\n tags, comments\n FROM bookmarks\n WHERE rowid=?\"\"\"\n return self._selectOne(sql, (uid,))","def external_link_already_exists(external_link):\r\n sql_query = \"SELECT link_id, link_anchor FROM external_links WHERE link_url = %(external_link)s\"\r\n db = connect()\r\n cursor = db.cursor()\r\n try:\r\n cursor.execute(sql_query, {\"external_link\" : external_link})\r\n tmp = cursor.fetchall()\r\n except:\r\n cursor.close()\r\n raise RuntimeError(\"An Exception happened with the Database, make sure you are connected\")\r\n cursor.close()\r\n db.close()\r\n return tmp","def get_or_404(self, id):\n return self.__model__.query.get_or_404(id)","def url(self):\n\n if not hasattr(self, \"_url\"):\n query = db.Query(\"query_term u\", \"u.value\")\n query.join(\"query_term t\", \"t.doc_id = u.doc_id\")\n query.where(f\"u.path = '{self.URL_PATH}'\")\n query.where(f\"t.path = '{self.TERM_PATH}'\")\n query.where(query.Condition(\"t.int_val\", self.id))\n rows = query.execute(self.loader.cdr_cursor).fetchall()\n self._url = rows[0].value if rows else \"\"\n return self._url","def link_url(self):\n # planet_assoc = self.planet_assocs.join(PlanetAssociation.planet.of_type(LinkPlanet)).first()\n\n for planet_assoc in self.planet_assocs:\n if planet_assoc.planet.kind == \"link\":\n return planet_assoc.planet.url\n return None","def findLink(self, query):\n\t\ttry:\n\t\t\tassert(type(query)) == str or Pattern\n\t\t\treturn self.driver.find_element_by_partial_link_text(query)\n\t\texcept Exception as e:\n\t\t\tprint(\"[*] Unable to find link by searching {}\\n{}\".format(query, e))\n\t\t\treturn -1","def link(self, link):\r\n return links.Link(self, link)","def find_publish_link(self):\n return self.find_url(PUBLISH_LINK_REL)","def get_item_with_href(self, href):\n for item in self.get_items():\n if item.get_name() == href:\n return item\n\n return None","def theLinky(self):\n theLink = self.absolute_url()\n return theLink","def link(self, id):\r\n return links.RepoLink(self, id)","def getItem(self, imgId, userId, admin):\n\n imgLinks = []\n result = self.queryStore([imgId], imgLinks, userId, admin)\n\n if (result):\n return imgLinks[0]\n else:\n return None","def lookup_entry(self, linked_resource):\n request = datacatalog.LookupEntryRequest()\n request.linked_resource = linked_resource\n return self.__datacatalog.lookup_entry(request=request)","def make_absolute_query_link(db,**params):\n pass","def find(self, node):\n saveCursor = self.cursor\n if self.first() and self.cursor.nodeId == node.nodeId:\n return self.cursor\n while self.next():\n if self.cursor.nodeId == node.nodeId:\n return self.cursor\n self.cursor = saveCursor\n return None","def get_url(connection: DBConnection, did: int):\n return connection.execute(\"SELECT url FROM docs WHERE did=:did\", (did,)).fetchone()[0]","def get_link(self, link_id):\n return self._search_link(key=\"link_id\", value=link_id)","def getIdLink(self):\n return self.urlLink()","def selflinking(self):\n return self._selflinking","def link(self):\n \n self.__enter__()\n return self.stable_path","def match(self, brain, getlink):\n link = getlink(brain.getId,\n getlink(normalize(brain.Title), None))\n if link:\n return True","def _resolve_context(r, tablename, context):\n\n record_id = r.id\n if not record_id:\n return None\n\n if not context:\n query = None\n\n elif type(context) is tuple:\n context, field = context\n query = (FS(context) == r.record[field])\n\n elif context == \"location\":\n # Show records linked to this Location & all it's Child Locations\n s = \"(location)$path\"\n # This version doesn't serialize_url\n #m = (\"%(id)s/*,*/%(id)s/*\" % dict(id=id)).split(\",\")\n #filter = (FS(s).like(m)) | (FS(s) == id)\n m = (\"%(id)s,%(id)s/*,*/%(id)s/*,*/%(id)s\" % dict(id=record_id)).split(\",\")\n m = [f.replace(\"*\", \"%\") for f in m]\n query = (FS(s).like(m))\n # @ToDo:\n #elif context == \"organisation\":\n # # Show records linked to this Organisation and all it's Branches\n # s = \"(%s)\" % context\n # query = (FS(s) == id)\n else:\n # Normal: show just records linked directly to this master resource\n s = \"(%s)\" % context\n query = (FS(s) == record_id)\n\n # Define target resource\n resource = current.s3db.resource(tablename, filter=query)\n r.customise_resource(tablename)\n return resource, query","def paired_link(self):\n for link in self.cross_project_links():\n if link.is_ode_noad_link() and link.lexid is not None:\n return link\n return None","def db_for_read(self, model, **hints):\n if model._meta.app_label in self.route_app_labels:\n return self.db_entry\n return None","def get_link(self, name):\n return self._link_reg[name]","def get_reference(self, refobj):\n c = cmds.listConnections(\"%s.referencenode\" % refobj, d=False)\n return c[0] if c else None","def get_selfLink(self):\n if 'selfLink' in self.target_pool_config:\n return self.target_pool_config['selfLink']","def check_exists_onProgress_pages(db,link):\r\n cursor = db.cursor()\r\n sql_query = \"SELECT page_id FROM on_progress_pages WHERE page_url= %(ln)s\"\r\n try:\r\n cursor.execute(sql_query, {'ln':link})\r\n result = cursor.fetchone()\r\n except:\r\n cursor.close()\r\n raise RuntimeError(\"An Exception happened with the Database, make sure you are connected\")\r\n cursor.close()\r\n return result is not None","def next(self):\n cur_item = None\n while cur_item == None:\n try:\n cur_item = self.iterator.next()\n except StopIteration:\n if self.current_page < self.total_pages:\n self.__next_page()\n else: raise\n\n element = cur_item.find(self.GLOBAL_NP + 'link')\n\n return element.attrib['href']","def get_link(prefix: str, identifier: str, use_bioregistry_io: bool = True) -> Optional[str]:\n providers = get_providers(prefix, identifier)\n for key in LINK_PRIORITY:\n if not use_bioregistry_io and key == \"bioregistry\":\n continue\n if key not in providers:\n continue\n rv = providers[key]\n if rv is not None:\n return rv\n return None","def get_message_link(self,message):\n \n data = {'chat_id': message.get('sender',{}).get('chat_id',None),\n 'message_id': message.get('id',None)\n }\n result = self._send_data('getMessageLink',data)\n if result.update:\n return result.update.get('link','')","def _get_self_href(response):\n data = jsonutils.loads(response.body)\n for link in data['versions'][0]['links']:\n if link['rel'] == 'self':\n return link['href']\n return ''","def get_broker_affiliate_link(broker, what):\n return_data = ''\n affiliate_link = ''\n baseurl = ''\n connection = pymysql.connect(host=DB_SRV,\n user=DB_USR,\n password=DB_PWD,\n db=DB_NAME,\n charset='utf8mb4',\n cursorclass=pymysql.cursors.DictCursor)\n cursor = connection.cursor(pymysql.cursors.SSCursor)\n sql = \"SELECT affiliate_link, burl FROM brokers WHERE broker_id ='\"+ str(broker) +\"'\"\n cursor.execute(sql)\n res = cursor.fetchall()\n for row in res:\n affiliate_link = row[0]\n baseurl = row[1]\n cursor.close()\n connection.close()\n\n if what == 'affiliate':\n return_data = affiliate_link\n else:\n return_data = baseurl\n return return_data","def get_record(self, id: uplink.Path):\n pass","def link(self):\n return Link(connection=self)","def next_link(self) -> str:\n return pulumi.get(self, \"next_link\")","def detail_link(db_obj, text=None):\n\n def build_link(obj):\n name = str(obj) if text is None else text\n return _make_link(obj.detail_url(), name)\n\n return mark_safe(', '.join(map(build_link, as_list(db_obj))))","def next_absolute_url(self, value):\n\t\tif self.next(): #checking if there is a next in the first place\n\t\t\treturn self.next().get_absolute_url\n\t\telse:\n\t\t\treturn None","def has_at_index(self, index):\n count = 0\n start = self.head\n while start:\n if count==index:\n return start\n start = start.getLink()\n count+=1\n return None","def related_url(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['RelatedUrlArgs']]]]:\n return pulumi.get(self, \"related_url\")","def entry_exist_bool(dbfile, link):\n\n conn = sqlite3.connect(dbfile)\n c = conn.cursor()\n query = \"\"\"\n SELECT link FROM bringatrailer WHERE link='{}'\n \"\"\".format(link)\n c.execute(query)\n result = c.fetchall()\n if not result:\n return False\n else:\n return True","def get_link(self) -> (str, int):\n raise NotImplemented","def _get_parent_record(self) -> Link:\n rel = \"parent\"\n href = self.api_endpoint\n return Link(href=href, rel=rel)","def click_related_item_link(self, heading, title):\n self.load_related_list(heading)\n locator = lex_locators[\"record\"][\"related\"][\"link\"].format(heading, title)\n try:\n self._jsclick(locator)\n except Exception as e:\n self.builtin.log(f\"Exception: {e}\", \"DEBUG\")\n raise Exception(\n f\"Unable to find related link under heading '{heading}' with the text '{title}'\"\n )\n self.wait_until_loading_is_complete()","def search_db(self, key, item):\n db = self.check_db()\n data = [record for record in db if record[key] == item]\n if data:\n return data[0]\n else:\n return False","def link(self, rel, default=None):\n return self.links.rel(rel, default)","def _links_get(self, cr, uid, context=None):\n obj = self.pool.get('res.request.link')\n ids = obj.search(cr, uid, [])\n res = obj.read(cr, uid, ids, ['object', 'name'], context)\n return [(r['object'], r['name']) for r in res]","def is_linked(self): \n return self.ichair_id is not None","def get_url(self):\n return self.metadata['thisRecordUrl']","def get_link(model_url):\n\n response = requests.get(model_url)\n\n return response.content","def fetch_pyvideo_pk(self):\n url = 'http://pyvideo.org/search?models=videos.video&q={0}'.format(self.full_name.replace(\" \", \"+\"))\n soup = BeautifulSoup(requests.get(url).content).findAll(\"a\")\n if soup:\n for link in soup:\n if link.string == self.full_name:\n self.pyvideo_pk = link.get('href').split('/')[2]\n self.save()\n return self.pyvideo_pk\n self.pyvideo_pk = None\n self.save()\n return None","def find_in_db(self, *args, **kwargs):\n return self.relation.find_in_db(*args, **kwargs)","def check_link_tag(self):\r\n node = self.article.raw_doc\r\n meta = self.parser.getElementsByTag(node, tag='link', attr='rel', value='image_src')\r\n for item in meta:\r\n src = self.parser.getAttribute(item, attr='href')\r\n if src:\r\n return self.get_image(item, src, extraction_type='linktag')\r\n return None"],"string":"[\n \"def _link_for_query(self, query):\\r\\n results = list(query)\\r\\n return results[0] if results else None\",\n \"def link(self) -> Optional[str]:\\n return pulumi.get(self, \\\"link\\\")\",\n \"def link(self) -> Optional[str]:\\n return pulumi.get(self, \\\"link\\\")\",\n \"def _get_self_record(self, record: dict) -> Link:\\n rel = \\\"self\\\"\\n href = os.path.join(self.api_endpoint, record[\\\"id\\\"])\\n return Link(href=href, rel=rel)\",\n \"def link(self):\\n return self._link\",\n \"def link(self):\\n return self._link\",\n \"def link(self):\\n return self._link\",\n \"def Link(self, default=None):\\n return self.data.get('links', {}).get('self', default)\",\n \"def getLink(self):\\n return self.link\",\n \"def self_link(self):\\n return self._json['coredata'].get('link', [])[0].get('@href')\",\n \"def getLink(self):\",\n \"def link(self):\\n\\n return self._get_field(\\\"link\\\")\",\n \"def search_link(self):\\n return self._json['coredata'].get('link', [])[2].get('@href')\",\n \"def link(self):\\n return self.container['link']\",\n \"def fetch_url_record(short_url = None):\\r\\n\\r\\n if short_url:\\r\\n url_record = db_collection.find_one({'name': short_url, 'deleted': False})\\r\\n\\r\\n if url_record:\\r\\n return url_record\\r\\n\\r\\n return None\",\n \"def get_object(self, url_id, user_id):\\n try:\\n return Link.objects.get(id=url_id, user=user_id)\\n except Link.DoesNotExist:\\n return None\",\n \"def get_link(self, conf, link_id):\\n\\t\\tpass\",\n \"def self_link_with_id(self) -> str:\\n return pulumi.get(self, \\\"self_link_with_id\\\")\",\n \"def self_link_with_id(self) -> str:\\n return pulumi.get(self, \\\"self_link_with_id\\\")\",\n \"def self_link(self) -> str:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> str:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> str:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> str:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> str:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> str:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> str:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> str:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> str:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def next_link(self) -> Optional[str]:\\n return pulumi.get(self, \\\"next_link\\\")\",\n \"def find_url(self, url: Url) -> Optional[sqlite3.Row]:\\n\\n sql = \\\"\\\"\\\"SELECT rowid, url as 'url [url]', title,\\n added as 'added [local_datetime]',\\n updated as 'updated [local_datetime]',\\n deleted as 'deleted [local_datetime]',\\n tags, comments\\n FROM bookmarks\\n WHERE domain=? AND url=?\\\"\\\"\\\"\\n return self._selectOne(sql, (url.domain, url.address))\",\n \"def linkno(self):\\n if hasattr(self, \\\"_linkno\\\"):\\n return self._linkno\\n else:\\n return None\",\n \"def updateOrInsert(cls, session, link, model, recordID):\\n outLink = Link.lookupLink(session, link, model, recordID)\\n if outLink is None: outLink = Link(**link)\\n else: outLink.update(link)\\n \\n return outLink\",\n \"def _get_link(li):\\n try:\\n a = li.find(\\\"a\\\")\\n link = a[\\\"href\\\"]\\n except Exception:\\n return None\\n return link\",\n \"def get_link_data(self, hashed_link):\\n\\n try:\\n data = self.link_db[hashed_link]\\n return data\\n except:\\n return None\",\n \"async def get_external_link(segmentnr: str):\\n query_result = {\\\"link\\\": \\\"\\\"}\\n filename = segmentnr.split(':')[0]\\n database = get_db()\\n query_displayname = database.AQLQuery(\\n query=main_queries.QUERY_LINK,\\n bindVars={\\n \\\"filename\\\": filename\\n },\\n rawResults=True\\n )\\n query_result = {\\\"link\\\": query_displayname.result[0]}\\n return query_result\",\n \"def self_link(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def self_link(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"self_link\\\")\",\n \"def get_data_link(self, ctx, params):\\n # ctx is the context object\\n # return variables are: link\\n #BEGIN get_data_link\\n id_ = _get_id_from_object(params, 'linkid', required=True)\\n _check_admin(\\n self._user_lookup, ctx[_CTX_TOKEN], _AdminPermission.READ,\\n # pretty annoying to test ctx.log_info is working, do it manually\\n 'get_data_link', ctx.log_info)\\n dl = self._samples.get_data_link_admin(id_)\\n link = _links_to_dicts([dl])[0]\\n #END get_data_link\\n\\n # At some point might do deeper type checking...\\n if not isinstance(link, dict):\\n raise ValueError('Method get_data_link return value ' +\\n 'link is not type dict as required.')\\n # return the results\\n return [link]\",\n \"def find_id(self, uid: int) -> Optional[sqlite3.Row]:\\n\\n sql = \\\"\\\"\\\"SELECT rowid, url as 'url [url]', title,\\n added as 'added [local_datetime]',\\n updated as 'updated [local_datetime]',\\n deleted as 'deleted [local_datetime]',\\n tags, comments\\n FROM bookmarks\\n WHERE rowid=?\\\"\\\"\\\"\\n return self._selectOne(sql, (uid,))\",\n \"def external_link_already_exists(external_link):\\r\\n sql_query = \\\"SELECT link_id, link_anchor FROM external_links WHERE link_url = %(external_link)s\\\"\\r\\n db = connect()\\r\\n cursor = db.cursor()\\r\\n try:\\r\\n cursor.execute(sql_query, {\\\"external_link\\\" : external_link})\\r\\n tmp = cursor.fetchall()\\r\\n except:\\r\\n cursor.close()\\r\\n raise RuntimeError(\\\"An Exception happened with the Database, make sure you are connected\\\")\\r\\n cursor.close()\\r\\n db.close()\\r\\n return tmp\",\n \"def get_or_404(self, id):\\n return self.__model__.query.get_or_404(id)\",\n \"def url(self):\\n\\n if not hasattr(self, \\\"_url\\\"):\\n query = db.Query(\\\"query_term u\\\", \\\"u.value\\\")\\n query.join(\\\"query_term t\\\", \\\"t.doc_id = u.doc_id\\\")\\n query.where(f\\\"u.path = '{self.URL_PATH}'\\\")\\n query.where(f\\\"t.path = '{self.TERM_PATH}'\\\")\\n query.where(query.Condition(\\\"t.int_val\\\", self.id))\\n rows = query.execute(self.loader.cdr_cursor).fetchall()\\n self._url = rows[0].value if rows else \\\"\\\"\\n return self._url\",\n \"def link_url(self):\\n # planet_assoc = self.planet_assocs.join(PlanetAssociation.planet.of_type(LinkPlanet)).first()\\n\\n for planet_assoc in self.planet_assocs:\\n if planet_assoc.planet.kind == \\\"link\\\":\\n return planet_assoc.planet.url\\n return None\",\n \"def findLink(self, query):\\n\\t\\ttry:\\n\\t\\t\\tassert(type(query)) == str or Pattern\\n\\t\\t\\treturn self.driver.find_element_by_partial_link_text(query)\\n\\t\\texcept Exception as e:\\n\\t\\t\\tprint(\\\"[*] Unable to find link by searching {}\\\\n{}\\\".format(query, e))\\n\\t\\t\\treturn -1\",\n \"def link(self, link):\\r\\n return links.Link(self, link)\",\n \"def find_publish_link(self):\\n return self.find_url(PUBLISH_LINK_REL)\",\n \"def get_item_with_href(self, href):\\n for item in self.get_items():\\n if item.get_name() == href:\\n return item\\n\\n return None\",\n \"def theLinky(self):\\n theLink = self.absolute_url()\\n return theLink\",\n \"def link(self, id):\\r\\n return links.RepoLink(self, id)\",\n \"def getItem(self, imgId, userId, admin):\\n\\n imgLinks = []\\n result = self.queryStore([imgId], imgLinks, userId, admin)\\n\\n if (result):\\n return imgLinks[0]\\n else:\\n return None\",\n \"def lookup_entry(self, linked_resource):\\n request = datacatalog.LookupEntryRequest()\\n request.linked_resource = linked_resource\\n return self.__datacatalog.lookup_entry(request=request)\",\n \"def make_absolute_query_link(db,**params):\\n pass\",\n \"def find(self, node):\\n saveCursor = self.cursor\\n if self.first() and self.cursor.nodeId == node.nodeId:\\n return self.cursor\\n while self.next():\\n if self.cursor.nodeId == node.nodeId:\\n return self.cursor\\n self.cursor = saveCursor\\n return None\",\n \"def get_url(connection: DBConnection, did: int):\\n return connection.execute(\\\"SELECT url FROM docs WHERE did=:did\\\", (did,)).fetchone()[0]\",\n \"def get_link(self, link_id):\\n return self._search_link(key=\\\"link_id\\\", value=link_id)\",\n \"def getIdLink(self):\\n return self.urlLink()\",\n \"def selflinking(self):\\n return self._selflinking\",\n \"def link(self):\\n \\n self.__enter__()\\n return self.stable_path\",\n \"def match(self, brain, getlink):\\n link = getlink(brain.getId,\\n getlink(normalize(brain.Title), None))\\n if link:\\n return True\",\n \"def _resolve_context(r, tablename, context):\\n\\n record_id = r.id\\n if not record_id:\\n return None\\n\\n if not context:\\n query = None\\n\\n elif type(context) is tuple:\\n context, field = context\\n query = (FS(context) == r.record[field])\\n\\n elif context == \\\"location\\\":\\n # Show records linked to this Location & all it's Child Locations\\n s = \\\"(location)$path\\\"\\n # This version doesn't serialize_url\\n #m = (\\\"%(id)s/*,*/%(id)s/*\\\" % dict(id=id)).split(\\\",\\\")\\n #filter = (FS(s).like(m)) | (FS(s) == id)\\n m = (\\\"%(id)s,%(id)s/*,*/%(id)s/*,*/%(id)s\\\" % dict(id=record_id)).split(\\\",\\\")\\n m = [f.replace(\\\"*\\\", \\\"%\\\") for f in m]\\n query = (FS(s).like(m))\\n # @ToDo:\\n #elif context == \\\"organisation\\\":\\n # # Show records linked to this Organisation and all it's Branches\\n # s = \\\"(%s)\\\" % context\\n # query = (FS(s) == id)\\n else:\\n # Normal: show just records linked directly to this master resource\\n s = \\\"(%s)\\\" % context\\n query = (FS(s) == record_id)\\n\\n # Define target resource\\n resource = current.s3db.resource(tablename, filter=query)\\n r.customise_resource(tablename)\\n return resource, query\",\n \"def paired_link(self):\\n for link in self.cross_project_links():\\n if link.is_ode_noad_link() and link.lexid is not None:\\n return link\\n return None\",\n \"def db_for_read(self, model, **hints):\\n if model._meta.app_label in self.route_app_labels:\\n return self.db_entry\\n return None\",\n \"def get_link(self, name):\\n return self._link_reg[name]\",\n \"def get_reference(self, refobj):\\n c = cmds.listConnections(\\\"%s.referencenode\\\" % refobj, d=False)\\n return c[0] if c else None\",\n \"def get_selfLink(self):\\n if 'selfLink' in self.target_pool_config:\\n return self.target_pool_config['selfLink']\",\n \"def check_exists_onProgress_pages(db,link):\\r\\n cursor = db.cursor()\\r\\n sql_query = \\\"SELECT page_id FROM on_progress_pages WHERE page_url= %(ln)s\\\"\\r\\n try:\\r\\n cursor.execute(sql_query, {'ln':link})\\r\\n result = cursor.fetchone()\\r\\n except:\\r\\n cursor.close()\\r\\n raise RuntimeError(\\\"An Exception happened with the Database, make sure you are connected\\\")\\r\\n cursor.close()\\r\\n return result is not None\",\n \"def next(self):\\n cur_item = None\\n while cur_item == None:\\n try:\\n cur_item = self.iterator.next()\\n except StopIteration:\\n if self.current_page < self.total_pages:\\n self.__next_page()\\n else: raise\\n\\n element = cur_item.find(self.GLOBAL_NP + 'link')\\n\\n return element.attrib['href']\",\n \"def get_link(prefix: str, identifier: str, use_bioregistry_io: bool = True) -> Optional[str]:\\n providers = get_providers(prefix, identifier)\\n for key in LINK_PRIORITY:\\n if not use_bioregistry_io and key == \\\"bioregistry\\\":\\n continue\\n if key not in providers:\\n continue\\n rv = providers[key]\\n if rv is not None:\\n return rv\\n return None\",\n \"def get_message_link(self,message):\\n \\n data = {'chat_id': message.get('sender',{}).get('chat_id',None),\\n 'message_id': message.get('id',None)\\n }\\n result = self._send_data('getMessageLink',data)\\n if result.update:\\n return result.update.get('link','')\",\n \"def _get_self_href(response):\\n data = jsonutils.loads(response.body)\\n for link in data['versions'][0]['links']:\\n if link['rel'] == 'self':\\n return link['href']\\n return ''\",\n \"def get_broker_affiliate_link(broker, what):\\n return_data = ''\\n affiliate_link = ''\\n baseurl = ''\\n connection = pymysql.connect(host=DB_SRV,\\n user=DB_USR,\\n password=DB_PWD,\\n db=DB_NAME,\\n charset='utf8mb4',\\n cursorclass=pymysql.cursors.DictCursor)\\n cursor = connection.cursor(pymysql.cursors.SSCursor)\\n sql = \\\"SELECT affiliate_link, burl FROM brokers WHERE broker_id ='\\\"+ str(broker) +\\\"'\\\"\\n cursor.execute(sql)\\n res = cursor.fetchall()\\n for row in res:\\n affiliate_link = row[0]\\n baseurl = row[1]\\n cursor.close()\\n connection.close()\\n\\n if what == 'affiliate':\\n return_data = affiliate_link\\n else:\\n return_data = baseurl\\n return return_data\",\n \"def get_record(self, id: uplink.Path):\\n pass\",\n \"def link(self):\\n return Link(connection=self)\",\n \"def next_link(self) -> str:\\n return pulumi.get(self, \\\"next_link\\\")\",\n \"def detail_link(db_obj, text=None):\\n\\n def build_link(obj):\\n name = str(obj) if text is None else text\\n return _make_link(obj.detail_url(), name)\\n\\n return mark_safe(', '.join(map(build_link, as_list(db_obj))))\",\n \"def next_absolute_url(self, value):\\n\\t\\tif self.next(): #checking if there is a next in the first place\\n\\t\\t\\treturn self.next().get_absolute_url\\n\\t\\telse:\\n\\t\\t\\treturn None\",\n \"def has_at_index(self, index):\\n count = 0\\n start = self.head\\n while start:\\n if count==index:\\n return start\\n start = start.getLink()\\n count+=1\\n return None\",\n \"def related_url(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['RelatedUrlArgs']]]]:\\n return pulumi.get(self, \\\"related_url\\\")\",\n \"def entry_exist_bool(dbfile, link):\\n\\n conn = sqlite3.connect(dbfile)\\n c = conn.cursor()\\n query = \\\"\\\"\\\"\\n SELECT link FROM bringatrailer WHERE link='{}'\\n \\\"\\\"\\\".format(link)\\n c.execute(query)\\n result = c.fetchall()\\n if not result:\\n return False\\n else:\\n return True\",\n \"def get_link(self) -> (str, int):\\n raise NotImplemented\",\n \"def _get_parent_record(self) -> Link:\\n rel = \\\"parent\\\"\\n href = self.api_endpoint\\n return Link(href=href, rel=rel)\",\n \"def click_related_item_link(self, heading, title):\\n self.load_related_list(heading)\\n locator = lex_locators[\\\"record\\\"][\\\"related\\\"][\\\"link\\\"].format(heading, title)\\n try:\\n self._jsclick(locator)\\n except Exception as e:\\n self.builtin.log(f\\\"Exception: {e}\\\", \\\"DEBUG\\\")\\n raise Exception(\\n f\\\"Unable to find related link under heading '{heading}' with the text '{title}'\\\"\\n )\\n self.wait_until_loading_is_complete()\",\n \"def search_db(self, key, item):\\n db = self.check_db()\\n data = [record for record in db if record[key] == item]\\n if data:\\n return data[0]\\n else:\\n return False\",\n \"def link(self, rel, default=None):\\n return self.links.rel(rel, default)\",\n \"def _links_get(self, cr, uid, context=None):\\n obj = self.pool.get('res.request.link')\\n ids = obj.search(cr, uid, [])\\n res = obj.read(cr, uid, ids, ['object', 'name'], context)\\n return [(r['object'], r['name']) for r in res]\",\n \"def is_linked(self): \\n return self.ichair_id is not None\",\n \"def get_url(self):\\n return self.metadata['thisRecordUrl']\",\n \"def get_link(model_url):\\n\\n response = requests.get(model_url)\\n\\n return response.content\",\n \"def fetch_pyvideo_pk(self):\\n url = 'http://pyvideo.org/search?models=videos.video&q={0}'.format(self.full_name.replace(\\\" \\\", \\\"+\\\"))\\n soup = BeautifulSoup(requests.get(url).content).findAll(\\\"a\\\")\\n if soup:\\n for link in soup:\\n if link.string == self.full_name:\\n self.pyvideo_pk = link.get('href').split('/')[2]\\n self.save()\\n return self.pyvideo_pk\\n self.pyvideo_pk = None\\n self.save()\\n return None\",\n \"def find_in_db(self, *args, **kwargs):\\n return self.relation.find_in_db(*args, **kwargs)\",\n \"def check_link_tag(self):\\r\\n node = self.article.raw_doc\\r\\n meta = self.parser.getElementsByTag(node, tag='link', attr='rel', value='image_src')\\r\\n for item in meta:\\r\\n src = self.parser.getAttribute(item, attr='href')\\r\\n if src:\\r\\n return self.get_image(item, src, extraction_type='linktag')\\r\\n return None\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6749376","0.6332646","0.6332646","0.62515604","0.61730146","0.61730146","0.61730146","0.6066266","0.60131997","0.5963378","0.5962121","0.5958353","0.59456277","0.589322","0.5848187","0.58002985","0.5758175","0.5740583","0.5740583","0.5739168","0.5739168","0.5739168","0.5739168","0.5739168","0.5739168","0.5739168","0.5739168","0.5739168","0.5698533","0.5698533","0.5698533","0.5698533","0.5698533","0.5654602","0.5606542","0.5590217","0.5572818","0.5561538","0.55582076","0.55310076","0.54646665","0.54646665","0.54646665","0.54646665","0.54646665","0.54646665","0.5399189","0.53813624","0.5361318","0.5332636","0.53309864","0.5327658","0.5323014","0.53202885","0.5308533","0.53072983","0.529832","0.52779734","0.52678335","0.52655596","0.52514046","0.52406144","0.523936","0.52326286","0.5220655","0.5218851","0.52107054","0.5206085","0.5176319","0.5175641","0.5165431","0.51621395","0.51566994","0.51560616","0.51418245","0.5129689","0.51207626","0.5116178","0.51154864","0.5114215","0.51073176","0.51068294","0.510341","0.50916314","0.5083627","0.50815463","0.50512576","0.5048562","0.5041136","0.50334656","0.5031891","0.50285804","0.50261027","0.50198144","0.5014253","0.49950773","0.49876925","0.4986737","0.4985535","0.4981448"],"string":"[\n \"0.6749376\",\n \"0.6332646\",\n \"0.6332646\",\n \"0.62515604\",\n \"0.61730146\",\n \"0.61730146\",\n \"0.61730146\",\n \"0.6066266\",\n \"0.60131997\",\n \"0.5963378\",\n \"0.5962121\",\n \"0.5958353\",\n \"0.59456277\",\n \"0.589322\",\n \"0.5848187\",\n \"0.58002985\",\n \"0.5758175\",\n \"0.5740583\",\n \"0.5740583\",\n \"0.5739168\",\n \"0.5739168\",\n \"0.5739168\",\n \"0.5739168\",\n \"0.5739168\",\n \"0.5739168\",\n \"0.5739168\",\n \"0.5739168\",\n \"0.5739168\",\n \"0.5698533\",\n \"0.5698533\",\n \"0.5698533\",\n \"0.5698533\",\n \"0.5698533\",\n \"0.5654602\",\n \"0.5606542\",\n \"0.5590217\",\n \"0.5572818\",\n \"0.5561538\",\n \"0.55582076\",\n \"0.55310076\",\n \"0.54646665\",\n \"0.54646665\",\n \"0.54646665\",\n \"0.54646665\",\n \"0.54646665\",\n \"0.54646665\",\n \"0.5399189\",\n \"0.53813624\",\n \"0.5361318\",\n \"0.5332636\",\n \"0.53309864\",\n \"0.5327658\",\n \"0.5323014\",\n \"0.53202885\",\n \"0.5308533\",\n \"0.53072983\",\n \"0.529832\",\n \"0.52779734\",\n \"0.52678335\",\n \"0.52655596\",\n \"0.52514046\",\n \"0.52406144\",\n \"0.523936\",\n \"0.52326286\",\n \"0.5220655\",\n \"0.5218851\",\n \"0.52107054\",\n \"0.5206085\",\n \"0.5176319\",\n \"0.5175641\",\n \"0.5165431\",\n \"0.51621395\",\n \"0.51566994\",\n \"0.51560616\",\n \"0.51418245\",\n \"0.5129689\",\n \"0.51207626\",\n \"0.5116178\",\n \"0.51154864\",\n \"0.5114215\",\n \"0.51073176\",\n \"0.51068294\",\n \"0.510341\",\n \"0.50916314\",\n \"0.5083627\",\n \"0.50815463\",\n \"0.50512576\",\n \"0.5048562\",\n \"0.5041136\",\n \"0.50334656\",\n \"0.5031891\",\n \"0.50285804\",\n \"0.50261027\",\n \"0.50198144\",\n \"0.5014253\",\n \"0.49950773\",\n \"0.49876925\",\n \"0.4986737\",\n \"0.4985535\",\n \"0.4981448\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.71646607"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":83492,"cells":{"query":{"kind":"string","value":"Create a new cell from a Cell protobuf."},"document":{"kind":"string","value":"def from_pb(cls, cell_pb):\n timestamp = _datetime_from_microseconds(cell_pb.timestamp_micros)\n if cell_pb.labels:\n return cls(cell_pb.value, timestamp, labels=cell_pb.labels)\n else:\n return cls(cell_pb.value, timestamp)"},"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 create_cell(self, cid):\n self.cells[cid] = Cell()","def reproduce(self, id, position, partner):\n return Cell(id, position, self, partner)","def _create_cell(self,row_number,cell_number):\n cell = Cell(self)\n cell.x = cell_number * self.cell_width\n cell.y = row_number * self.cell_width\n cell.rect.x = cell.x\n cell.rect.y = cell.y\n return cell","def deserialize(self, str):\n try:\n if self.base is None:\n self.base = rwrc12_msgs.msg.CellBase()\n end = 0\n _x = self\n start = end\n end += 12\n (_x.base.header.seq, _x.base.header.stamp.secs, _x.base.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])\n start = end\n end += 4\n (length,) = _struct_I.unpack(str[start:end])\n start = end\n end += length\n if python3:\n self.base.header.frame_id = str[start:end].decode('utf-8')\n else:\n self.base.header.frame_id = str[start:end]\n _x = self\n start = end\n end += 20\n (_x.base.cell_width, _x.base.cell_height, _x.base.position.x, _x.base.position.y, _x.base.position.z,) = _struct_5f.unpack(str[start:end])\n start = end\n end += 4\n (length,) = _struct_I.unpack(str[start:end])\n self.base.points = []\n for i in range(0, length):\n val1 = geometry_msgs.msg.Point32()\n _x = val1\n start = end\n end += 12\n (_x.x, _x.y, _x.z,) = _struct_3f.unpack(str[start:end])\n self.base.points.append(val1)\n start = end\n end += 4\n (length,) = _struct_I.unpack(str[start:end])\n pattern = '<%sf'%length\n start = end\n end += struct.calcsize(pattern)\n self.base.intensity = struct.unpack(pattern, str[start:end])\n start = end\n end += 1\n (self.base.cost,) = _struct_b.unpack(str[start:end])\n start = end\n end += 4\n (length,) = _struct_I.unpack(str[start:end])\n start = end\n end += length\n if python3:\n self.base.label = str[start:end].decode('utf-8')\n else:\n self.base.label = str[start:end]\n _x = self\n start = end\n end += 8\n (_x.mean_height, _x.mean_intensity,) = _struct_2f.unpack(str[start:end])\n return self\n except struct.error as e:\n raise genpy.DeserializationError(e) #most likely buffer underfill","def cell(self, cell_id):\r\n return Cell(self, cell_id)","def createCell(self, space):\n\t\tself.createCellEntity(space)\n\t\tDEBUG_MSG(\"Avatar::createCell\")","def from_protobuf(cls, msg):\n if not isinstance(msg, cls._protobuf_cls):\n raise TypeError(\"Expected message of type \"\n \"%r\" % cls._protobuf_cls.__name__)\n kwargs = {k: getattr(msg, k) for k in cls._get_params()}\n return cls(**kwargs)","def from_json(self, _json: Dict) -> \"Cell\":\n\n cell = Cell(content=_json[\"content\"], data=_json[\"data\"])\n cell.id = _json[\"id\"]\n return cell","def from_proto_dict(proto_dict: Dict) -> 'GridQubit':\n # TODO: Deprecate v1 proto method.\n if 'row' not in proto_dict or 'col' not in proto_dict:\n raise ValueError(\n 'Proto dict does not contain row or col: {}'.format(proto_dict))\n return GridQubit(row=proto_dict['row'], col=proto_dict['col'])","def constructCell():\n\t\tself.weightGenerate()","def SimpleDeepCell():\n cell = Cell()\n node = cell._get_hcell2()\n node[\"celltype\"] = \"mixed\"\n node[\"hash_pattern\"] = {\"*\": \"#\"}\n return cell","def copy(self) -> 'Cell':\n new = Cell(self.letter)\n new.player = self.player\n return new","def _make_cell(self, cell, editable, position, model):\n _cellrenderers = {\n 'pixbuf': gtk.CellRendererPixbuf(),\n 'text': gtk.CellRendererText()\n }\n\n _cell = _cellrenderers[cell]\n\n if not editable:\n _cell.set_property('cell-background', 'light gray')\n else:\n _cell.connect('edited', self._do_edit_cell, position, model)\n\n if cell == 'text':\n _cell.set_property('editable', editable)\n _cell.set_property('wrap-width', 250)\n _cell.set_property('wrap-mode', pango.WRAP_WORD_CHAR)\n _cell.set_property('yalign', 0.1)\n\n return _cell","def FromProto(cls, proto_obj):\n source = GameSource()\n source.type = proto_obj.type\n if proto_obj.update_time_utc_str:\n source.update_date_time = datetime.strptime(\n proto_obj.update_time_utc_str, tweets.DATE_PARSE_FMT_STR)\n else:\n source.update_date_time = datetime.now()\n if proto_obj.twitter_account:\n source.account_id = long(proto_obj.twitter_account.id_str)\n source.tweet_text = proto_obj.tweet_text\n if proto_obj.score_reporter_url:\n source.score_reporter_url = proto_obj.score_reporter_url\n if not (source.account_id or source.score_reporter_url):\n raise GameModelError('Converting GameSource from malformed proto')\n return source","def from_bytes(buf: bytes) -> 'ProposalInfo':\n proposal_info_in_dict: dict = json_loads(buf.decode())\n proposal_info_in_dict[\"id\"] = bytes.fromhex(proposal_info_in_dict[\"id\"])\n proposal_info_in_dict[\"proposer\"] = Address.from_string(proposal_info_in_dict[\"proposer\"])\n return ProposalInfo(**proposal_info_in_dict)","def deserialize_numpy(self, str, numpy):\n try:\n if self.base is None:\n self.base = rwrc12_msgs.msg.CellBase()\n end = 0\n _x = self\n start = end\n end += 12\n (_x.base.header.seq, _x.base.header.stamp.secs, _x.base.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])\n start = end\n end += 4\n (length,) = _struct_I.unpack(str[start:end])\n start = end\n end += length\n if python3:\n self.base.header.frame_id = str[start:end].decode('utf-8')\n else:\n self.base.header.frame_id = str[start:end]\n _x = self\n start = end\n end += 20\n (_x.base.cell_width, _x.base.cell_height, _x.base.position.x, _x.base.position.y, _x.base.position.z,) = _struct_5f.unpack(str[start:end])\n start = end\n end += 4\n (length,) = _struct_I.unpack(str[start:end])\n self.base.points = []\n for i in range(0, length):\n val1 = geometry_msgs.msg.Point32()\n _x = val1\n start = end\n end += 12\n (_x.x, _x.y, _x.z,) = _struct_3f.unpack(str[start:end])\n self.base.points.append(val1)\n start = end\n end += 4\n (length,) = _struct_I.unpack(str[start:end])\n pattern = '<%sf'%length\n start = end\n end += struct.calcsize(pattern)\n self.base.intensity = numpy.frombuffer(str[start:end], dtype=numpy.float32, count=length)\n start = end\n end += 1\n (self.base.cost,) = _struct_b.unpack(str[start:end])\n start = end\n end += 4\n (length,) = _struct_I.unpack(str[start:end])\n start = end\n end += length\n if python3:\n self.base.label = str[start:end].decode('utf-8')\n else:\n self.base.label = str[start:end]\n _x = self\n start = end\n end += 8\n (_x.mean_height, _x.mean_intensity,) = _struct_2f.unpack(str[start:end])\n return self\n except struct.error as e:\n raise genpy.DeserializationError(e) #most likely buffer underfill","def new_cell(self, name, overwrite_duplicate=False, update_references=True):\n cell = Cell(name)\n self.add(cell, False, overwrite_duplicate, update_references)\n return cell","def __init__(self, x, y, type, id):\n Cell.__init__(self, x, y, type, id, \"S\")","def _proto2object(\n proto: CreateGroupMessage_PB,\n ) -> \"CreateGroupMessage\":\n\n return CreateGroupMessage(\n msg_id=_deserialize(blob=proto.msg_id),\n address=_deserialize(blob=proto.address),\n content=json.loads(proto.content),\n reply_to=_deserialize(blob=proto.reply_to),\n )","def get_new_cell(path: tuple(str, ...)) -> dict[str, Any]:\n return {\n \"path\": path,\n \"type\": \"cell\",\n # \"celltype\": \"structured\", # or \"text\" for help cells\n \"datatype\": \"mixed\",\n \"hash_pattern\": None,\n \"UNTRANSLATED\": True,\n }","def createCell(self, xPos, yPos):\n self.cells.append(Cell(self.screen, xPos, yPos))","def upgrade_cell(cell):\n cell.setdefault(\"metadata\", NotebookNode())\n cell.id = random_cell_id()\n if cell.cell_type == \"code\":\n cell.pop(\"language\", \"\")\n if \"collapsed\" in cell:\n cell.metadata[\"collapsed\"] = cell.pop(\"collapsed\")\n cell.source = cell.pop(\"input\", \"\")\n cell.execution_count = cell.pop(\"prompt_number\", None)\n cell.outputs = upgrade_outputs(cell.outputs)\n elif cell.cell_type == \"heading\":\n cell.cell_type = \"markdown\"\n level = cell.pop(\"level\", 1)\n cell.source = \"{hashes} {single_line}\".format(\n hashes=\"#\" * level,\n single_line=\" \".join(cell.get(\"source\", \"\").splitlines()),\n )\n elif cell.cell_type == \"html\":\n # Technically, this exists. It will never happen in practice.\n cell.cell_type = \"markdown\"\n return cell","def from_raw(cls, buffer: bytes):\n assert len(buffer) == 304\n block_hash = to_str(buffer[:32])\n height = to_int(buffer[32:36])\n nonce = to_int(buffer[36:40])\n time = to_int(buffer[40:48])\n prevBlock = to_str(buffer[48:80])\n treeRoot = to_str(buffer[80:112])\n extraNonce = to_str(buffer[112:136])\n reservedRoot = to_str(buffer[136:168])\n witnessRoot = to_str(buffer[168:200])\n merkleRoot = to_str(buffer[200:232])\n version = to_int(buffer[232:236])\n bits = to_int(buffer[236:240])\n mask = to_str(buffer[240:272])\n chainwork = to_str(buffer[272:304])\n return ChainEntry(\n block_hash,\n height,\n nonce,\n time,\n prevBlock,\n treeRoot,\n extraNonce,\n reservedRoot,\n witnessRoot,\n merkleRoot,\n version,\n bits,\n mask,\n chainwork,\n )","def _from_protobuf(cls, aux_data):\n data = AuxData.serializer.decode(\n BytesIO(aux_data.data), aux_data.type_name\n )\n return cls(data=data, type_name=aux_data.type_name)","def __init__(self, cell, input_keep_prob=1.0, output_keep_prob=1.0,\n is_training=True, seed=None):\n if not isinstance(cell, tf.nn.rnn_cell.RNNCell):\n raise TypeError(\"The parameter cell is not a RNNCell.\")\n if (isinstance(input_keep_prob, float) and\n not (input_keep_prob >= 0.0 and input_keep_prob <= 1.0)):\n raise ValueError(\"Parameter input_keep_prob must be between 0 and 1: %d\"\n % input_keep_prob)\n if (isinstance(output_keep_prob, float) and\n not (output_keep_prob >= 0.0 and output_keep_prob <= 1.0)):\n raise ValueError(\"Parameter output_keep_prob must be between 0 and 1: %d\"\n % output_keep_prob)\n self._cell = cell\n self._input_keep_prob = input_keep_prob\n self._output_keep_prob = output_keep_prob\n self._seed = seed\n self._is_training = is_training","def __init__(self, celltype, model=None, build_mode='lazy'):\n # Generate the NineLine class from the nineml file and initialise a\n # single cell from it\n if (isinstance(celltype, BiophysNineml) or isinstance(celltype, str)):\n self.celltype = CellMetaClass(celltype, build_mode=build_mode)\n else:\n self.celltype = celltype\n self.default_seg = self.celltype(model=model).source_section.name\n self._model = model\n self.genome_keys = []\n self.log_scales = []","def process_cell(self, neighbourhood: List[Cell], old_cell: Cell) -> Cell:","def FromPb(pb):\n if isinstance(pb, str):\n real_pb = entity_pb.EntityProto()\n real_pb.ParseFromString(pb)\n pb = real_pb\n\n return Entity._FromPb(pb, require_valid_key=False)","def __init__(self, cell, attn_inputs, \n attn_size, attn_vec_size,\n output_size=None, input_size=None, \n state_is_tuple=True, attn_masks=None,\n merge_output_attn='linear',\n reuse=None):\n if not isinstance(cell, rnn.RNNCell):\n raise TypeError(\"The parameter cell is not RNNCell.\")\n if nest.is_sequence(cell.state_size) and not state_is_tuple:\n raise ValueError(\"Cell returns tuple of states, but the flag \"\n \"state_is_tuple is not set. State size is: %s\"\n % str(cell.state_size))\n if not state_is_tuple:\n logging.warn(\n \"%s: Using a concatenated state is slower and will soon be \"\n \"deprecated. Use state_is_tuple=True.\", self)\n\n self._state_is_tuple = state_is_tuple\n\n if not state_is_tuple:\n raise NotImplementedError\n\n self._cell = cell\n self._input_size = input_size\n self._output_size = output_size\n if output_size is None:\n self._output_size = cell.output_size\n self._attn_size = attn_size\n self._reuse = reuse\n self._attn_inputs = attn_inputs\n self._attn_vec_size = attn_vec_size\n self.attn_masks = attn_masks\n self.merge_output_attn = merge_output_attn","def __init__(self, cell, shape):\n self.cell = cell\n self.shape = shape\n self.dimension = cell.dimension\n self.Nsites = np.prod(shape) * self.cell.Nsites\n self.sites = np.zeros(self.shape+[self.cell.Nsites],dtype='object')\n self.bonds = []\n self.build_sites()\n self.build_bonds()","def FromBytes(cls, value: bytes):\n precondition.AssertType(value, bytes)\n return _GetFactory(cls).FromBytes(value)","def __init__(self, cell, mem_size, embed_size, max_n_valid_indices):\n self._cell = cell\n self._mem_size = mem_size\n self._embed_size = embed_size\n self._max_n_valid_indices = max_n_valid_indices","def from_bytes(byteseq, width, height=None):\n if not width:\n return Glyph()\n if height is not None:\n bytewidth = len(byteseq) // height\n else:\n bytewidth = ceildiv(width, 8)\n byteseq = list(byteseq)\n rows = [byteseq[_offs:_offs+bytewidth] for _offs in range(0, len(byteseq), bytewidth)]\n return Glyph(tuple(bytes_to_bits(_row, width) for _row in rows))","def from_bytes(self, ???):","def cell_create(game_set, screen, covids, cells):\n cell_create_flag = True\n cell = Cell(game_set, screen)\n for old_cell in cells.sprites():\n if old_cell.rect.y < game_set.cell_number_adjust:\n cell_create_flag = False\n break\n if (not pygame.sprite.spritecollide(cell, cells, 0) and\n not pygame.sprite.spritecollide(cell, covids, 0) and\n cell_create_flag):\n cells.add(cell)","def __init__(self,\n shape,\n kernel,\n depth,\n use_peepholes=False,\n cell_clip=None,\n initializer=None,\n forget_bias=1.0,\n activation=None,\n normalize=None,\n dropout=None,\n reuse=None):\n super(ConvLSTMCell, self).__init__(_reuse=reuse)\n\n tf_shape = tf.TensorShape(shape + [depth])\n self._output_size = tf_shape\n self._state_size = tf.nn.rnn_cell.LSTMStateTuple(tf_shape, tf_shape)\n\n self._kernel = kernel\n self._depth = depth\n self._use_peepholes = use_peepholes\n self._cell_clip = cell_clip\n self._initializer = initializer\n self._forget_bias = forget_bias\n self._activation = activation or tf.nn.tanh\n self._normalize = normalize\n self._dropout = dropout\n\n self._w_conv = None\n if self._use_peepholes:\n self._w_f_diag = None\n self._w_i_diag = None\n self._w_o_diag = None","def newCell(self,spaceGroupInt,a,b,c,alpha, beta, gamma, magNa, magNb, magNc, cutNa, cutNb, cutNc):\n spaceGroup = SpaceGroups.GetSpaceGroup(spaceGroupInt)\n unitcell = Cell(spaceGroup, 0,0,0, a, b, c, alpha, gamma, beta)\n self.MagCell = MagneticCell(unitcell, cutNa, cutNb, cutNc, spaceGroup)\n \n #Regenerate Bonds as well\n #self.changeBonds(self.bondTable.data, notifyGUI)","def from_pb(cls, instance_pb, client):\n match = _INSTANCE_NAME_RE.match(instance_pb.name)\n if match is None:\n raise ValueError('Instance protobuf name was not in the '\n 'expected format.', instance_pb.name)\n if match.group('project') != client.project:\n raise ValueError('Project ID on instance does not match the '\n 'project ID on the client')\n instance_id = match.group('instance_id')\n\n result = cls(instance_id, client, _EXISTING_INSTANCE_LOCATION_ID)\n result._update_from_pb(instance_pb)\n return result","def __init__(self, *args, **kwds):\n if args or kwds:\n super(MultiDataCell, self).__init__(*args, **kwds)\n #message fields cannot be None, assign default values for those that are\n if self.base is None:\n self.base = rwrc12_msgs.msg.CellBase()\n if self.mean_height is None:\n self.mean_height = 0.\n if self.mean_intensity is None:\n self.mean_intensity = 0.\n else:\n self.base = rwrc12_msgs.msg.CellBase()\n self.mean_height = 0.\n self.mean_intensity = 0.","def create_cells(self):\n raise NotImplementedError(\n \"create_cells function not reimplemented from base class\")","def __init__(self, cell_contents: Tuple[CellContent, ...] = cn.DEFAULT_CELL_CONTENTS, *args, **kwargs):\n super().__init__(*args, **kwargs)\n\n self.cell_contents = cell_contents\n for cell in self.cell_contents:\n cell.signal_ids = tuple(self.add_new_signal(cell.row, cell.col) for _ in range(cell.count))\n\n for i in range(cell.count):\n self.set_signal_color(cell.signal_ids[i], cn.COLORS.DEFAULT_SIGNAL_COLORS[i])","def createEctoCell(module, cell_type, name, params=list()):\n\tmod = __import__(module, globals(), locals(), [cell_type], 0)\n\tcell_builder = getattr(\n\t mod,\n\t cell_type\n\t)\n\tinit_params = dict()\n\tfor param in params:\n\t\tif len(param[\"values\"])>0:\n\t\t\t# If value is a str and start with the module name, interpret it\n\t\t\t# as a global value\n\t\t\tfor i in range(len(param[\"values\"])):\n\t\t\t\tif isinstance(param[\"values\"][i], basestring)\\\n\t\t\t\t and param[\"values\"][i].startswith(module+'.'):\n\t\t\t\t\tattrs = param[\"values\"][i][len(module)+1:].split('.')\n\t\t\t\t\tparam_val = mod\n\t\t\t\t\twhile len(attrs)>0:\n\t\t\t\t\t\tparam_val = getattr(param_val, attrs.pop(0))\n\t\t\t\t\tparam[\"values\"][i] = param_val\n\t\t\tv = param[\"values\"][0]\n\t\t\tif isinstance(v, unicode):\n\t\t\t\tv = str(v)\n\t\t\tinit_params[str(param[\"param_name\"])] = v\n\treturn cell_builder(str(name),**init_params)","def __init__(self,cell1,site1,cell2,site2,color=None,label=None,linewidth=None,linetype=None):\n self.cell1 = np.array(cell1)\n self.site1 = site1\n self.cell2 = np.array(cell2)\n self.site2 = site2\n coordinate1 = None\n coordinate2 = None\n self.color = color\n self.label = label\n self.linewidth = linewidth\n self.linetype = linetype","def from_binary(cls, data):\n if isinstance(data, basestring):\n data = ctypes.c_buffer(data)\n return ctypes.cast(data, cls)","def __init__(self, id, position, parent_a=None, parent_b=None):\n \"\"\" int: For uniquely identifying cells \"\"\"\n self._id = 0\n \"\"\" int: Possibly used for data or life-span related functions \"\"\"\n self._age = 0;\n \"\"\" int: To measure the success of a gene \"\"\"\n self._score = p.params['initial_score']\n \"\"\" Gene: The decision making entity of the cell.\"\"\"\n self._gene = None\n \"\"\" dict(Cell,Memory): To hold the memory of past interactions with other cells\"\"\"\n self._memory = {}\n \"\"\" Position: The location of the Cell within the toroidal world. \"\"\"\n self._position = None\n\n if parent_a is not None and parent_b is not None:\n self._gene = Gene.Gene(parent_a.get_gene(), parent_b.get_gene())\n else:\n self._gene = Gene.Gene()\n self._position = position\n self._id = id","def make_cell(self, column_title: str, field_value: Any) -> Cell:\n column = self.get_column(column_title)\n if column is None:\n raise ValueError(\n \"A column with the title %s does not exist in this sheet\", column_title\n )\n if column.type == ColumnType.MULTI_PICKLIST:\n if not column.id:\n raise ValueError(f\"Column {column!r} does not have ID\")\n cell = Cell.create_multi_picklist(column_id=column.id, values=field_value)\n else:\n cell = Cell(column_id=column.id, value=field_value)\n return cell","def __init__(\n self,\n arg=None,\n align=None,\n alignsrc=None,\n fill=None,\n font=None,\n format=None,\n formatsrc=None,\n height=None,\n line=None,\n prefix=None,\n prefixsrc=None,\n suffix=None,\n suffixsrc=None,\n values=None,\n valuessrc=None,\n **kwargs\n ):\n super(Cells, self).__init__(\"cells\")\n\n # Validate arg\n # ------------\n if arg is None:\n arg = {}\n elif isinstance(arg, self.__class__):\n arg = arg.to_plotly_json()\n elif isinstance(arg, dict):\n arg = _copy.copy(arg)\n else:\n raise ValueError(\n \"\"\"\\\nThe first argument to the plotly.graph_objs.table.Cells \nconstructor must be a dict or \nan instance of :class:`plotly.graph_objs.table.Cells`\"\"\"\n )\n\n # Handle skip_invalid\n # -------------------\n self._skip_invalid = kwargs.pop(\"skip_invalid\", False)\n\n # Import validators\n # -----------------\n from plotly.validators.table import cells as v_cells\n\n # Initialize validators\n # ---------------------\n self._validators[\"align\"] = v_cells.AlignValidator()\n self._validators[\"alignsrc\"] = v_cells.AlignsrcValidator()\n self._validators[\"fill\"] = v_cells.FillValidator()\n self._validators[\"font\"] = v_cells.FontValidator()\n self._validators[\"format\"] = v_cells.FormatValidator()\n self._validators[\"formatsrc\"] = v_cells.FormatsrcValidator()\n self._validators[\"height\"] = v_cells.HeightValidator()\n self._validators[\"line\"] = v_cells.LineValidator()\n self._validators[\"prefix\"] = v_cells.PrefixValidator()\n self._validators[\"prefixsrc\"] = v_cells.PrefixsrcValidator()\n self._validators[\"suffix\"] = v_cells.SuffixValidator()\n self._validators[\"suffixsrc\"] = v_cells.SuffixsrcValidator()\n self._validators[\"values\"] = v_cells.ValuesValidator()\n self._validators[\"valuessrc\"] = v_cells.ValuessrcValidator()\n\n # Populate data dict with properties\n # ----------------------------------\n _v = arg.pop(\"align\", None)\n self[\"align\"] = align if align is not None else _v\n _v = arg.pop(\"alignsrc\", None)\n self[\"alignsrc\"] = alignsrc if alignsrc is not None else _v\n _v = arg.pop(\"fill\", None)\n self[\"fill\"] = fill if fill is not None else _v\n _v = arg.pop(\"font\", None)\n self[\"font\"] = font if font is not None else _v\n _v = arg.pop(\"format\", None)\n self[\"format\"] = format if format is not None else _v\n _v = arg.pop(\"formatsrc\", None)\n self[\"formatsrc\"] = formatsrc if formatsrc is not None else _v\n _v = arg.pop(\"height\", None)\n self[\"height\"] = height if height is not None else _v\n _v = arg.pop(\"line\", None)\n self[\"line\"] = line if line is not None else _v\n _v = arg.pop(\"prefix\", None)\n self[\"prefix\"] = prefix if prefix is not None else _v\n _v = arg.pop(\"prefixsrc\", None)\n self[\"prefixsrc\"] = prefixsrc if prefixsrc is not None else _v\n _v = arg.pop(\"suffix\", None)\n self[\"suffix\"] = suffix if suffix is not None else _v\n _v = arg.pop(\"suffixsrc\", None)\n self[\"suffixsrc\"] = suffixsrc if suffixsrc is not None else _v\n _v = arg.pop(\"values\", None)\n self[\"values\"] = values if values is not None else _v\n _v = arg.pop(\"valuessrc\", None)\n self[\"valuessrc\"] = valuessrc if valuessrc is not None else _v\n\n # Process unknown kwargs\n # ----------------------\n self._process_kwargs(**dict(arg, **kwargs))\n\n # Reset skip_invalid\n # ------------------\n self._skip_invalid = False","def fromBytes(cls, inBytes):\n return cls.fromJson(inBytes.decode())","def fromBytes(cls, inBytes):\n return cls.fromJson(inBytes.decode())","def fromBytes(cls, inBytes):\n return cls.fromJson(inBytes.decode())","def from_wire(cls, header, payload_bytes, *, sender_address=None,\n validate=False):\n return cls.from_components(header, b'', payload_bytes,\n sender_address=sender_address,\n validate=validate)","def make_cell(self, unit_type, num_units, forget_bias, dropout,\n mode, residual_connection=False):\n\n # dropout (= 1 - keep_prob) is set to 0 during eval and infer\n dropout = dropout if mode == tf.contrib.learn.ModeKeys.TRAIN else 0.0\n\n # Cell Type\n if unit_type == \"lstm\":\n cell = tf.contrib.rnn.BasicLSTMCell(\n num_units,\n forget_bias=forget_bias)\n elif unit_type == \"gru\":\n cell = tf.contrib.rnn.GRUCell(num_units)\n elif unit_type == \"layer_norm_lstm\":\n cell = tf.contrib.rnn.LayerNormBasicLSTMCell(\n num_units,\n forget_bias=forget_bias,\n layer_norm=True)\n else:\n raise ValueError(\"Unknown unit type %s!\" % unit_type)\n\n # Dropout (= 1 - keep_prob)\n if dropout > 0.0:\n cell = tf.contrib.rnn.DropoutWrapper(\n cell=cell, input_keep_prob=(1.0 - dropout))\n\n # Residual\n if residual_connection:\n cell = tf.contrib.rnn.ResidualWrapper(cell)\n\n return cell","def __init__(cell, value):\n\t\tcell.value = value\n\t\tcell.parent = None\n\t\tcell.visited = False","def from_layer(cls, layer, cell_classifier, **kwargs):\n return cls.__class__(layer.data, cell_classifier, **kwargs)","def from_bin(cls, bin):\n raw = msgpack.unpackb(bin, raw=False)\n event_msg = EventMessage.from_text(raw[\"event_message\"])\n msg = cls(\n uri_name=raw[\"uri_name\"],\n event_message=event_msg,\n publisher_connection_id=raw[\"publisher_connection_id\"]\n )\n msg.publisher_node_id = raw[\"publisher_node_id\"]\n return msg","def add_cell(self, cell):\n\n if cell.uuid is None:\n cell.uuid = self._generate_uuid()\n\n if cell.uuid in self._cells:\n error_str = \"Trying to add an already existing cell with uuid: \"\\\n + str(cell.uuid)\n raise KeyError(error_str)\n\n self._cells[cell.uuid] = Cell.from_cell(cell)\n\n return cell.uuid","def from_wire(cls, header, payload_bytes, *, sender_address=None,\n validate=False):\n\n return cls.from_components(header, b'', payload_bytes,\n sender_address=sender_address,\n validate=validate)","def _proto2object(\n proto: UpdateGroupMessage_PB,\n ) -> \"UpdateGroupMessage\":\n\n return UpdateGroupMessage(\n msg_id=_deserialize(blob=proto.msg_id),\n address=_deserialize(blob=proto.address),\n content=json.loads(proto.content),\n reply_to=_deserialize(blob=proto.reply_to),\n )","def object_from_protobuf(pb, model_type=None):\n key = None\n if isinstance(pb, entity_pb2.Entity):\n pb = pb._pb\n\n if pb.HasField(\"key\"): # Message field (Key)\n key = CustomIterator.key_from_protobuf(pb.key)\n key._type = SubclassMap.get()[key.kind]\n\n entity_props = {}\n\n for prop_name, value_pb in pb.properties.items():\n value = CustomIterator._get_value_from_value_pb(value_pb)\n entity_props[prop_name] = value\n\n obj = model_type._dotted_dict_to_object(entity_props, key)\n return obj","def from_message(cls, template_message):\n new_equivalent_message = cls(\n template_message.env,\n template_message.source,\n template_message.destination,\n template_message.size_bytes,\n template_message.message_type,\n template_message.data)\n return new_equivalent_message","def add_cell_field(self,name,data,on_exists='fail'):\n # will need to get fancier to discern vector dtypes\n # assert data.ndim==1 - maybe no need to be smart?\n if name in np.dtype(self.cell_dtype).names:\n if on_exists == 'fail':\n raise GridException(\"Node field %s already exists\"%name)\n elif on_exists == 'pass':\n return\n elif on_exists == 'overwrite':\n self.cells[name] = data\n else:\n self.cells=recarray_add_fields(self.cells,\n [(name,data)])\n self.cell_dtype=self.cells.dtype","def from_bytes(self, bytearr):\n if len(bytearr) >= SensorMessage.BYTE_LENGTH:\n if len(bytearr) > SensorMessage.BYTE_LENGTH:\n bytearr = bytearr[:SensorMessage.BYTE_LENGTH+1]\n if bytearr[0] == \"\\xca\" and bytearr[1] == \"\\x55\":\n # Checksum checking is taken care of at RF module.\n #if self.calc_checksum(bytearr[:-1]) == ord(bytearr[-1]):\n self.address = bytearr[2:7]\n try:\n (self.errorflags,\n self.temperature,\n self.humidity,\n self.supply_v,\n self.link_quality,\n self.message_id) = struct.unpack(\">BHHHBH\", bytearr[7:17])\n except:\n print \"Failed to unpack message: \" + format_hex(bytearr[7:])\n #else:\n # raise ValueError(\"Incorrect checksum: Given: \" + repr(ord(bytearr[-1])) + \", calc.: \" + repr(self.calc_checksum(bytearr[:-1])))\n else:\n raise ValueError(\"Incorrect message header!\")","def __init__(self, cell_type, explicit_values,\n derived_values=None, non_column_labels=None, align='',\n sort_values=True):\n self.type = cell_type\n self.align = align\n self.col_index = 0 # Is set afterward\n self.values = []\n if non_column_labels:\n self.non_column_labels = [\n template_helpers.EZTItem(value=v, is_derived=ezt.boolean(d))\n for v, d in non_column_labels]\n else:\n self.non_column_labels = []\n\n for v in (sorted(explicit_values) if sort_values else explicit_values):\n self.values.append(CellItem(v))\n\n if derived_values:\n for v in (sorted(derived_values) if sort_values else derived_values):\n self.values.append(CellItem(v, is_derived=True))","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def from_bytes(self, *args, **kwargs): # real signature unknown\n pass","def new(cls, edge_str):\n return Tile(TileEdges(*edge_str))","def initialize_cells(self):\n for loc in np.ndindex(*self.shape): # TODO: see if nested for loop is faster than this\n c = Cell(loc, self)\n self.cells.append(c)","def from_serialized_proto(cls, proto_string: bytes) -> 'TableInfo':\n proto = schema_pb2.TableInfo.FromString(proto_string)\n if proto.HasField('signature'):\n signature = nested_structure_coder.decode_proto(proto.signature)\n else:\n signature = None\n return cls(\n name=proto.name,\n sampler_options=proto.sampler_options,\n remover_options=proto.remover_options,\n max_size=proto.max_size,\n max_times_sampled=proto.max_times_sampled,\n rate_limiter_info=proto.rate_limiter_info,\n signature=signature,\n current_size=proto.current_size,\n num_episodes=proto.num_episodes,\n num_deleted_episodes=proto.num_deleted_episodes,\n num_unique_samples=proto.num_unique_samples,\n table_worker_time=proto.table_worker_time,\n )","def _proto2object(proto: Metadata_PB) -> \"Metadata\":\n\n return Metadata(\n id=validate_type(_deserialize(blob=proto.id), UID, optional=True),\n name=proto.name,\n node=validate_type(_deserialize(blob=proto.node), Location),\n )","def from_buffer(cls, data, codec):\n new = cls()\n new.codec = codec\n new.data = codec.parse(data)\n return new","def __init__(self, board = np.random.randint(2, size=(5, 5), dtype = np.uint8)): \n # Check for valid filetype for board\n if not isinstance(board, np.ndarray):\n raise NotImplementedError(\"Board must be an numpy.array.\")\n # Check for valid board size.\n if any(x < 2 for x in board.shape):\n raise NotImplementedError(\"Board state invalid! Must be at least 2x2.\")\n # Check for valid board cell entries.\n if not np.all(np.isin(board, [0,1])):\n raise NotImplementedError(\"Board state invalid! Must be filled with 0s and 1s.\")\n\n # Define lookup table for cell evaluation\n self.lookup = np.asarray([[0,0,0,1,0,0,0,0,0],[0,0,1,1,0,0,0,0,0]])\n\n # Define expanded board for easier border cell calculations\n expanded_shape = tuple(d+2 for d in board.shape)\n board_slice = (slice(1, -1),) * 2\n self.expanded_board = np.zeros(expanded_shape,dtype = np.uint8)\n self.expanded_board[board_slice] = board\n self.board = self.expanded_board[board_slice]","def gen_CASTEP_supercell(CASTEP_cell,na,nb,nc):\n nruter=dict()\n nruter[\"na\"]=na\n nruter[\"nb\"]=nb\n nruter[\"nc\"]=nc\n nruter[\"lattvec\"]=np.array(CASTEP_cell[\"lattvec\"])\n nruter[\"lattvec\"][:,0]*=na\n nruter[\"lattvec\"][:,1]*=nb\n nruter[\"lattvec\"][:,2]*=nc\n nruter[\"elements\"]=copy.copy(CASTEP_cell[\"elements\"])\n nruter[\"numbers\"]=na*nb*nc*CASTEP_cell[\"numbers\"]\n nruter[\"positions\"]=np.empty((3,CASTEP_cell[\"positions\"].shape[1]*na*nb*nc))\n pos=0\n for pos,(k,j,i,iat) in enumerate(itertools.product(xrange(nc),\n xrange(nb),\n xrange(na),\n xrange(\n CASTEP_cell[\"positions\"].shape[1]))):\n nruter[\"positions\"][:,pos]=(CASTEP_cell[\"positions\"][:,iat]+[i,j,k])/[\n na,nb,nc]\n nruter[\"types\"]=[]\n for i in xrange(na*nb*nc):\n nruter[\"types\"].extend(CASTEP_cell[\"types\"])\n # print \"supercell\", nruter\n return nruter","def from_msg(cls, msg):\n if cls._debug:\n log.debug('msg=%s', msg)\n key, seq_s, uuid, prop_s, body = msg\n key = key if key else None\n seq = struct.unpack('!q', seq_s)[0]\n body = body if body else None\n if body:\n body = pipeline.load(body)\n #body = json.loads(body_s)\n #prop = json.loads(prop_s)\n prop = pipeline.load(prop_s)\n return cls(seq, uuid=uuid, key=key, properties=prop, body=body)","def new_cell_in_time(self, cell_type, mcs=None):\n cell = self.new_cell(cell_type)\n if mcs is None:\n if self.mcs < 0:\n mcs = 0\n else:\n mcs = self.mcs\n\n cell.dict[CoronavirusLib.new_cell_mcs_key] = mcs\n return cell","def add_cell(self,**kwargs):\n i=None\n if '_index' in kwargs:\n i=kwargs.pop('_index')\n if i==len(self.cells): # had been self.edges, seems wrong\n # this is the index we'd get anyway.\n i=None\n else:\n assert len(self.cells)>i\n assert self.cells[i]['deleted']\n\n if i is None:\n c=np.zeros( (),dtype=self.cell_dtype)\n self.cells=array_append(self.cells,c)\n i=len(self.cells)-1\n else:\n pass\n\n # default values for native fields\n self.cells['_center'][i]=np.nan\n self.cells['_area'][i]=np.nan\n self.cells['edges'][i]=self.UNKNOWN \n\n for k,v in six.iteritems(kwargs):\n if k in ['edges','nodes']: # may have to make this more generic..\n self.cells[k][i][:len(v)] = v\n self.cells[k][i][len(v):] = self.UNDEFINED # -1\n else:\n self.cells[k][i]=v\n\n # Avoids issue with bogus value of 'deleted' coming in with kwargs\n self.cells['deleted'][i]=False\n\n if self._node_to_cells is not None:\n for n in self.cell_to_nodes(i):\n self._node_to_cells[n].append(i)\n\n if self._cell_center_index is not None:\n if self.cell_center_index_point=='circumcenter':\n cc=self.cells_center()[i]\n else: # centroid\n cc=self.cells_centroid([i])[0]\n self._cell_center_index.insert(i,cc[self.xxyy])\n\n # updated 2016-08-25 - not positive here.\n # This whole chunk needs testing.\n # maybe some confusion over when edges has to be set\n edges=self.cell_to_edges(i)\n \n if 'edges' not in kwargs:\n # wait - is this circular??\n self.cells['edges'][i,:len(edges)]=edges\n self.cells['edges'][i,len(edges):]=self.UNDEFINED\n\n nodes=self.cell_to_nodes(i)\n \n for side in range(len(edges)):\n j=edges[side]\n n1=nodes[side]\n n2=nodes[ (side+1)%len(nodes) ]\n \n if ( (n1==self.edges['nodes'][j,0]) and\n (n2==self.edges['nodes'][j,1]) ):\n # this cell is on the 'left' side of the edge\n assert self.edges['cells'][j,0]<0\n # TODO: probably this ought to be using modify_edge\n self.edges['cells'][j,0]=i\n elif ( (n1==self.edges['nodes'][j,1]) and\n (n2==self.edges['nodes'][j,0]) ):\n # this cell is on the 'right' side of the edge\n assert self.edges['cells'][j,1]<0\n # TODO: probably this ought to be using modify_edge\n self.edges['cells'][j,1]=i\n else:\n assert False\n \n self.push_op(self.unadd_cell,i)\n\n return i","def create_from_buffer(cls, buffer: str) -> \"TensorImage\":\n image_data = image_utils.decode_image_from_buffer(buffer, len(buffer))\n return cls(image_data, is_from_numpy_array=False)","def create_from_proto(cls, aux_pow_proto: protos.BitcoinAuxPow) -> 'BitcoinAuxPow':\n return cls(\n header_head=aux_pow_proto.header_head,\n coinbase_head=aux_pow_proto.coinbase_head,\n coinbase_tail=aux_pow_proto.coinbase_tail,\n merkle_path=list(aux_pow_proto.merkle_path),\n header_tail=aux_pow_proto.header_tail,\n )","def parse_and_decode(cls, data: bytes) -> \"Message\":\n if len(data) < cls.calc_size() + 1:\n raise NotEnoughData()\n if data[0] != cls.type:\n raise InvalidType()\n\n return cls(*unpack('<' + cls.fmt, data[1:cls.calc_size() + 1]))","def initial_cell_state_from_embedding(cell, z, batch_size, name=None):\n flat_state_sizes = tf_nest.flatten(cell.state_size)\n return tf_nest.pack_sequence_as(\n cell.zero_state(batch_size=batch_size, dtype=tf.float32),\n tf.split(\n tf.layers.dense(\n z,\n sum(flat_state_sizes),\n activation=tf.tanh,\n kernel_initializer=tf.random_normal_initializer(stddev=0.001),\n name=name),\n flat_state_sizes,\n axis=1))","def cell(self, value):\n if value is not None:\n value.get_shape().assert_is_compatible_with(self._output_shape)\n self._cell = value","def __init__(self, cells):\n self.cells = cells\n # Used by MakeTableData for layout.\n self.idx = None\n self.group = None\n self.rows_in_group = None\n self.starred = None","def from_wire(cls, header, payload_bytes, *, sender_address=None,\n validate=False):\n if not cls.HAS_PAYLOAD:\n return cls.from_components(header)\n payload = from_buffer(header.data_type, header.data_count,\n payload_bytes)\n return cls.from_components(header, *payload,\n sender_address=sender_address,\n validate=validate)","def _new_record():\n nonlocal key\n nonlocal value_list\n nonlocal record\n nonlocal origin\n nonlocal field_offset_map\n key = None\n value_list = None\n if source is not None:\n origin = Origin(source, None, None)\n field_offset_map = {}\n record = RFC822Record(data_cls(), origin, data_cls(), field_offset_map)","def from_dict(cls, dikt: dict) -> 'NeighborAddress':\n return util.deserialize_model(dikt, cls)","def create_model():\n\n class Net(nn.Cell):\n def construct(self, x, y):\n return x\n\n net = Net()\n model_simple = Model(net)\n\n return model_simple","def from_simple_data(self,points=[],edges=[],cells=[]):\n\n if isinstance(points,int):\n self.nodes = np.zeros( points, self.node_dtype)\n else:\n self.nodes = np.zeros( len(points), self.node_dtype)\n if len(points):\n points = np.asarray(points)\n self.nodes['x'] = points[:,:2] # discard any z's that come in\n\n if isinstance(cells,int):\n self.cells = np.zeros(cells,self.cell_dtype)\n else:\n self.cells = np.zeros( len(cells), self.cell_dtype)\n if len(cells):\n cells = np.asarray(cells)\n self.cells['nodes'][...] = -1\n # allow for initializing the grid with a cell\n # array with fewer than maxsides\n Nnode_in = cells.shape[1]\n self.cells['nodes'][:,:Nnode_in] = cells\n self.cells['_center'] = np.nan # signal stale\n self.cells['_area'] = np.nan # signal stale\n self.cells['edges'] = self.UNKNOWN # and no data here\n\n if isinstance(edges,int):\n self.edges = np.zeros(edges,self.edge_dtype)\n else:\n self.edges = np.zeros(len(edges),self.edge_dtype)\n if len(edges):\n edges = np.asarray(edges)\n # incoming edges may just have connectivity\n if edges.shape[1] == 2:\n self.edges['nodes'] = edges\n\n self.edges['mark'] = self.UNKNOWN\n self.edges['cells'][:,0] = self.UNKNOWN\n self.edges['cells'][:,1] = self.UNKNOWN\n elif edges.shape[1] == 5:\n self.edges['nodes'] = edges[:,:2]\n self.edges['mark'] = edges[:,2]\n self.edges['cells'] = edges[:,3:5]\n else:\n raise GridException(\"Edges should have 2 or 5 entries per edge\")\n \n self.refresh_metadata()"],"string":"[\n \"def create_cell(self, cid):\\n self.cells[cid] = Cell()\",\n \"def reproduce(self, id, position, partner):\\n return Cell(id, position, self, partner)\",\n \"def _create_cell(self,row_number,cell_number):\\n cell = Cell(self)\\n cell.x = cell_number * self.cell_width\\n cell.y = row_number * self.cell_width\\n cell.rect.x = cell.x\\n cell.rect.y = cell.y\\n return cell\",\n \"def deserialize(self, str):\\n try:\\n if self.base is None:\\n self.base = rwrc12_msgs.msg.CellBase()\\n end = 0\\n _x = self\\n start = end\\n end += 12\\n (_x.base.header.seq, _x.base.header.stamp.secs, _x.base.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])\\n start = end\\n end += 4\\n (length,) = _struct_I.unpack(str[start:end])\\n start = end\\n end += length\\n if python3:\\n self.base.header.frame_id = str[start:end].decode('utf-8')\\n else:\\n self.base.header.frame_id = str[start:end]\\n _x = self\\n start = end\\n end += 20\\n (_x.base.cell_width, _x.base.cell_height, _x.base.position.x, _x.base.position.y, _x.base.position.z,) = _struct_5f.unpack(str[start:end])\\n start = end\\n end += 4\\n (length,) = _struct_I.unpack(str[start:end])\\n self.base.points = []\\n for i in range(0, length):\\n val1 = geometry_msgs.msg.Point32()\\n _x = val1\\n start = end\\n end += 12\\n (_x.x, _x.y, _x.z,) = _struct_3f.unpack(str[start:end])\\n self.base.points.append(val1)\\n start = end\\n end += 4\\n (length,) = _struct_I.unpack(str[start:end])\\n pattern = '<%sf'%length\\n start = end\\n end += struct.calcsize(pattern)\\n self.base.intensity = struct.unpack(pattern, str[start:end])\\n start = end\\n end += 1\\n (self.base.cost,) = _struct_b.unpack(str[start:end])\\n start = end\\n end += 4\\n (length,) = _struct_I.unpack(str[start:end])\\n start = end\\n end += length\\n if python3:\\n self.base.label = str[start:end].decode('utf-8')\\n else:\\n self.base.label = str[start:end]\\n _x = self\\n start = end\\n end += 8\\n (_x.mean_height, _x.mean_intensity,) = _struct_2f.unpack(str[start:end])\\n return self\\n except struct.error as e:\\n raise genpy.DeserializationError(e) #most likely buffer underfill\",\n \"def cell(self, cell_id):\\r\\n return Cell(self, cell_id)\",\n \"def createCell(self, space):\\n\\t\\tself.createCellEntity(space)\\n\\t\\tDEBUG_MSG(\\\"Avatar::createCell\\\")\",\n \"def from_protobuf(cls, msg):\\n if not isinstance(msg, cls._protobuf_cls):\\n raise TypeError(\\\"Expected message of type \\\"\\n \\\"%r\\\" % cls._protobuf_cls.__name__)\\n kwargs = {k: getattr(msg, k) for k in cls._get_params()}\\n return cls(**kwargs)\",\n \"def from_json(self, _json: Dict) -> \\\"Cell\\\":\\n\\n cell = Cell(content=_json[\\\"content\\\"], data=_json[\\\"data\\\"])\\n cell.id = _json[\\\"id\\\"]\\n return cell\",\n \"def from_proto_dict(proto_dict: Dict) -> 'GridQubit':\\n # TODO: Deprecate v1 proto method.\\n if 'row' not in proto_dict or 'col' not in proto_dict:\\n raise ValueError(\\n 'Proto dict does not contain row or col: {}'.format(proto_dict))\\n return GridQubit(row=proto_dict['row'], col=proto_dict['col'])\",\n \"def constructCell():\\n\\t\\tself.weightGenerate()\",\n \"def SimpleDeepCell():\\n cell = Cell()\\n node = cell._get_hcell2()\\n node[\\\"celltype\\\"] = \\\"mixed\\\"\\n node[\\\"hash_pattern\\\"] = {\\\"*\\\": \\\"#\\\"}\\n return cell\",\n \"def copy(self) -> 'Cell':\\n new = Cell(self.letter)\\n new.player = self.player\\n return new\",\n \"def _make_cell(self, cell, editable, position, model):\\n _cellrenderers = {\\n 'pixbuf': gtk.CellRendererPixbuf(),\\n 'text': gtk.CellRendererText()\\n }\\n\\n _cell = _cellrenderers[cell]\\n\\n if not editable:\\n _cell.set_property('cell-background', 'light gray')\\n else:\\n _cell.connect('edited', self._do_edit_cell, position, model)\\n\\n if cell == 'text':\\n _cell.set_property('editable', editable)\\n _cell.set_property('wrap-width', 250)\\n _cell.set_property('wrap-mode', pango.WRAP_WORD_CHAR)\\n _cell.set_property('yalign', 0.1)\\n\\n return _cell\",\n \"def FromProto(cls, proto_obj):\\n source = GameSource()\\n source.type = proto_obj.type\\n if proto_obj.update_time_utc_str:\\n source.update_date_time = datetime.strptime(\\n proto_obj.update_time_utc_str, tweets.DATE_PARSE_FMT_STR)\\n else:\\n source.update_date_time = datetime.now()\\n if proto_obj.twitter_account:\\n source.account_id = long(proto_obj.twitter_account.id_str)\\n source.tweet_text = proto_obj.tweet_text\\n if proto_obj.score_reporter_url:\\n source.score_reporter_url = proto_obj.score_reporter_url\\n if not (source.account_id or source.score_reporter_url):\\n raise GameModelError('Converting GameSource from malformed proto')\\n return source\",\n \"def from_bytes(buf: bytes) -> 'ProposalInfo':\\n proposal_info_in_dict: dict = json_loads(buf.decode())\\n proposal_info_in_dict[\\\"id\\\"] = bytes.fromhex(proposal_info_in_dict[\\\"id\\\"])\\n proposal_info_in_dict[\\\"proposer\\\"] = Address.from_string(proposal_info_in_dict[\\\"proposer\\\"])\\n return ProposalInfo(**proposal_info_in_dict)\",\n \"def deserialize_numpy(self, str, numpy):\\n try:\\n if self.base is None:\\n self.base = rwrc12_msgs.msg.CellBase()\\n end = 0\\n _x = self\\n start = end\\n end += 12\\n (_x.base.header.seq, _x.base.header.stamp.secs, _x.base.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])\\n start = end\\n end += 4\\n (length,) = _struct_I.unpack(str[start:end])\\n start = end\\n end += length\\n if python3:\\n self.base.header.frame_id = str[start:end].decode('utf-8')\\n else:\\n self.base.header.frame_id = str[start:end]\\n _x = self\\n start = end\\n end += 20\\n (_x.base.cell_width, _x.base.cell_height, _x.base.position.x, _x.base.position.y, _x.base.position.z,) = _struct_5f.unpack(str[start:end])\\n start = end\\n end += 4\\n (length,) = _struct_I.unpack(str[start:end])\\n self.base.points = []\\n for i in range(0, length):\\n val1 = geometry_msgs.msg.Point32()\\n _x = val1\\n start = end\\n end += 12\\n (_x.x, _x.y, _x.z,) = _struct_3f.unpack(str[start:end])\\n self.base.points.append(val1)\\n start = end\\n end += 4\\n (length,) = _struct_I.unpack(str[start:end])\\n pattern = '<%sf'%length\\n start = end\\n end += struct.calcsize(pattern)\\n self.base.intensity = numpy.frombuffer(str[start:end], dtype=numpy.float32, count=length)\\n start = end\\n end += 1\\n (self.base.cost,) = _struct_b.unpack(str[start:end])\\n start = end\\n end += 4\\n (length,) = _struct_I.unpack(str[start:end])\\n start = end\\n end += length\\n if python3:\\n self.base.label = str[start:end].decode('utf-8')\\n else:\\n self.base.label = str[start:end]\\n _x = self\\n start = end\\n end += 8\\n (_x.mean_height, _x.mean_intensity,) = _struct_2f.unpack(str[start:end])\\n return self\\n except struct.error as e:\\n raise genpy.DeserializationError(e) #most likely buffer underfill\",\n \"def new_cell(self, name, overwrite_duplicate=False, update_references=True):\\n cell = Cell(name)\\n self.add(cell, False, overwrite_duplicate, update_references)\\n return cell\",\n \"def __init__(self, x, y, type, id):\\n Cell.__init__(self, x, y, type, id, \\\"S\\\")\",\n \"def _proto2object(\\n proto: CreateGroupMessage_PB,\\n ) -> \\\"CreateGroupMessage\\\":\\n\\n return CreateGroupMessage(\\n msg_id=_deserialize(blob=proto.msg_id),\\n address=_deserialize(blob=proto.address),\\n content=json.loads(proto.content),\\n reply_to=_deserialize(blob=proto.reply_to),\\n )\",\n \"def get_new_cell(path: tuple(str, ...)) -> dict[str, Any]:\\n return {\\n \\\"path\\\": path,\\n \\\"type\\\": \\\"cell\\\",\\n # \\\"celltype\\\": \\\"structured\\\", # or \\\"text\\\" for help cells\\n \\\"datatype\\\": \\\"mixed\\\",\\n \\\"hash_pattern\\\": None,\\n \\\"UNTRANSLATED\\\": True,\\n }\",\n \"def createCell(self, xPos, yPos):\\n self.cells.append(Cell(self.screen, xPos, yPos))\",\n \"def upgrade_cell(cell):\\n cell.setdefault(\\\"metadata\\\", NotebookNode())\\n cell.id = random_cell_id()\\n if cell.cell_type == \\\"code\\\":\\n cell.pop(\\\"language\\\", \\\"\\\")\\n if \\\"collapsed\\\" in cell:\\n cell.metadata[\\\"collapsed\\\"] = cell.pop(\\\"collapsed\\\")\\n cell.source = cell.pop(\\\"input\\\", \\\"\\\")\\n cell.execution_count = cell.pop(\\\"prompt_number\\\", None)\\n cell.outputs = upgrade_outputs(cell.outputs)\\n elif cell.cell_type == \\\"heading\\\":\\n cell.cell_type = \\\"markdown\\\"\\n level = cell.pop(\\\"level\\\", 1)\\n cell.source = \\\"{hashes} {single_line}\\\".format(\\n hashes=\\\"#\\\" * level,\\n single_line=\\\" \\\".join(cell.get(\\\"source\\\", \\\"\\\").splitlines()),\\n )\\n elif cell.cell_type == \\\"html\\\":\\n # Technically, this exists. It will never happen in practice.\\n cell.cell_type = \\\"markdown\\\"\\n return cell\",\n \"def from_raw(cls, buffer: bytes):\\n assert len(buffer) == 304\\n block_hash = to_str(buffer[:32])\\n height = to_int(buffer[32:36])\\n nonce = to_int(buffer[36:40])\\n time = to_int(buffer[40:48])\\n prevBlock = to_str(buffer[48:80])\\n treeRoot = to_str(buffer[80:112])\\n extraNonce = to_str(buffer[112:136])\\n reservedRoot = to_str(buffer[136:168])\\n witnessRoot = to_str(buffer[168:200])\\n merkleRoot = to_str(buffer[200:232])\\n version = to_int(buffer[232:236])\\n bits = to_int(buffer[236:240])\\n mask = to_str(buffer[240:272])\\n chainwork = to_str(buffer[272:304])\\n return ChainEntry(\\n block_hash,\\n height,\\n nonce,\\n time,\\n prevBlock,\\n treeRoot,\\n extraNonce,\\n reservedRoot,\\n witnessRoot,\\n merkleRoot,\\n version,\\n bits,\\n mask,\\n chainwork,\\n )\",\n \"def _from_protobuf(cls, aux_data):\\n data = AuxData.serializer.decode(\\n BytesIO(aux_data.data), aux_data.type_name\\n )\\n return cls(data=data, type_name=aux_data.type_name)\",\n \"def __init__(self, cell, input_keep_prob=1.0, output_keep_prob=1.0,\\n is_training=True, seed=None):\\n if not isinstance(cell, tf.nn.rnn_cell.RNNCell):\\n raise TypeError(\\\"The parameter cell is not a RNNCell.\\\")\\n if (isinstance(input_keep_prob, float) and\\n not (input_keep_prob >= 0.0 and input_keep_prob <= 1.0)):\\n raise ValueError(\\\"Parameter input_keep_prob must be between 0 and 1: %d\\\"\\n % input_keep_prob)\\n if (isinstance(output_keep_prob, float) and\\n not (output_keep_prob >= 0.0 and output_keep_prob <= 1.0)):\\n raise ValueError(\\\"Parameter output_keep_prob must be between 0 and 1: %d\\\"\\n % output_keep_prob)\\n self._cell = cell\\n self._input_keep_prob = input_keep_prob\\n self._output_keep_prob = output_keep_prob\\n self._seed = seed\\n self._is_training = is_training\",\n \"def __init__(self, celltype, model=None, build_mode='lazy'):\\n # Generate the NineLine class from the nineml file and initialise a\\n # single cell from it\\n if (isinstance(celltype, BiophysNineml) or isinstance(celltype, str)):\\n self.celltype = CellMetaClass(celltype, build_mode=build_mode)\\n else:\\n self.celltype = celltype\\n self.default_seg = self.celltype(model=model).source_section.name\\n self._model = model\\n self.genome_keys = []\\n self.log_scales = []\",\n \"def process_cell(self, neighbourhood: List[Cell], old_cell: Cell) -> Cell:\",\n \"def FromPb(pb):\\n if isinstance(pb, str):\\n real_pb = entity_pb.EntityProto()\\n real_pb.ParseFromString(pb)\\n pb = real_pb\\n\\n return Entity._FromPb(pb, require_valid_key=False)\",\n \"def __init__(self, cell, attn_inputs, \\n attn_size, attn_vec_size,\\n output_size=None, input_size=None, \\n state_is_tuple=True, attn_masks=None,\\n merge_output_attn='linear',\\n reuse=None):\\n if not isinstance(cell, rnn.RNNCell):\\n raise TypeError(\\\"The parameter cell is not RNNCell.\\\")\\n if nest.is_sequence(cell.state_size) and not state_is_tuple:\\n raise ValueError(\\\"Cell returns tuple of states, but the flag \\\"\\n \\\"state_is_tuple is not set. State size is: %s\\\"\\n % str(cell.state_size))\\n if not state_is_tuple:\\n logging.warn(\\n \\\"%s: Using a concatenated state is slower and will soon be \\\"\\n \\\"deprecated. Use state_is_tuple=True.\\\", self)\\n\\n self._state_is_tuple = state_is_tuple\\n\\n if not state_is_tuple:\\n raise NotImplementedError\\n\\n self._cell = cell\\n self._input_size = input_size\\n self._output_size = output_size\\n if output_size is None:\\n self._output_size = cell.output_size\\n self._attn_size = attn_size\\n self._reuse = reuse\\n self._attn_inputs = attn_inputs\\n self._attn_vec_size = attn_vec_size\\n self.attn_masks = attn_masks\\n self.merge_output_attn = merge_output_attn\",\n \"def __init__(self, cell, shape):\\n self.cell = cell\\n self.shape = shape\\n self.dimension = cell.dimension\\n self.Nsites = np.prod(shape) * self.cell.Nsites\\n self.sites = np.zeros(self.shape+[self.cell.Nsites],dtype='object')\\n self.bonds = []\\n self.build_sites()\\n self.build_bonds()\",\n \"def FromBytes(cls, value: bytes):\\n precondition.AssertType(value, bytes)\\n return _GetFactory(cls).FromBytes(value)\",\n \"def __init__(self, cell, mem_size, embed_size, max_n_valid_indices):\\n self._cell = cell\\n self._mem_size = mem_size\\n self._embed_size = embed_size\\n self._max_n_valid_indices = max_n_valid_indices\",\n \"def from_bytes(byteseq, width, height=None):\\n if not width:\\n return Glyph()\\n if height is not None:\\n bytewidth = len(byteseq) // height\\n else:\\n bytewidth = ceildiv(width, 8)\\n byteseq = list(byteseq)\\n rows = [byteseq[_offs:_offs+bytewidth] for _offs in range(0, len(byteseq), bytewidth)]\\n return Glyph(tuple(bytes_to_bits(_row, width) for _row in rows))\",\n \"def from_bytes(self, ???):\",\n \"def cell_create(game_set, screen, covids, cells):\\n cell_create_flag = True\\n cell = Cell(game_set, screen)\\n for old_cell in cells.sprites():\\n if old_cell.rect.y < game_set.cell_number_adjust:\\n cell_create_flag = False\\n break\\n if (not pygame.sprite.spritecollide(cell, cells, 0) and\\n not pygame.sprite.spritecollide(cell, covids, 0) and\\n cell_create_flag):\\n cells.add(cell)\",\n \"def __init__(self,\\n shape,\\n kernel,\\n depth,\\n use_peepholes=False,\\n cell_clip=None,\\n initializer=None,\\n forget_bias=1.0,\\n activation=None,\\n normalize=None,\\n dropout=None,\\n reuse=None):\\n super(ConvLSTMCell, self).__init__(_reuse=reuse)\\n\\n tf_shape = tf.TensorShape(shape + [depth])\\n self._output_size = tf_shape\\n self._state_size = tf.nn.rnn_cell.LSTMStateTuple(tf_shape, tf_shape)\\n\\n self._kernel = kernel\\n self._depth = depth\\n self._use_peepholes = use_peepholes\\n self._cell_clip = cell_clip\\n self._initializer = initializer\\n self._forget_bias = forget_bias\\n self._activation = activation or tf.nn.tanh\\n self._normalize = normalize\\n self._dropout = dropout\\n\\n self._w_conv = None\\n if self._use_peepholes:\\n self._w_f_diag = None\\n self._w_i_diag = None\\n self._w_o_diag = None\",\n \"def newCell(self,spaceGroupInt,a,b,c,alpha, beta, gamma, magNa, magNb, magNc, cutNa, cutNb, cutNc):\\n spaceGroup = SpaceGroups.GetSpaceGroup(spaceGroupInt)\\n unitcell = Cell(spaceGroup, 0,0,0, a, b, c, alpha, gamma, beta)\\n self.MagCell = MagneticCell(unitcell, cutNa, cutNb, cutNc, spaceGroup)\\n \\n #Regenerate Bonds as well\\n #self.changeBonds(self.bondTable.data, notifyGUI)\",\n \"def from_pb(cls, instance_pb, client):\\n match = _INSTANCE_NAME_RE.match(instance_pb.name)\\n if match is None:\\n raise ValueError('Instance protobuf name was not in the '\\n 'expected format.', instance_pb.name)\\n if match.group('project') != client.project:\\n raise ValueError('Project ID on instance does not match the '\\n 'project ID on the client')\\n instance_id = match.group('instance_id')\\n\\n result = cls(instance_id, client, _EXISTING_INSTANCE_LOCATION_ID)\\n result._update_from_pb(instance_pb)\\n return result\",\n \"def __init__(self, *args, **kwds):\\n if args or kwds:\\n super(MultiDataCell, self).__init__(*args, **kwds)\\n #message fields cannot be None, assign default values for those that are\\n if self.base is None:\\n self.base = rwrc12_msgs.msg.CellBase()\\n if self.mean_height is None:\\n self.mean_height = 0.\\n if self.mean_intensity is None:\\n self.mean_intensity = 0.\\n else:\\n self.base = rwrc12_msgs.msg.CellBase()\\n self.mean_height = 0.\\n self.mean_intensity = 0.\",\n \"def create_cells(self):\\n raise NotImplementedError(\\n \\\"create_cells function not reimplemented from base class\\\")\",\n \"def __init__(self, cell_contents: Tuple[CellContent, ...] = cn.DEFAULT_CELL_CONTENTS, *args, **kwargs):\\n super().__init__(*args, **kwargs)\\n\\n self.cell_contents = cell_contents\\n for cell in self.cell_contents:\\n cell.signal_ids = tuple(self.add_new_signal(cell.row, cell.col) for _ in range(cell.count))\\n\\n for i in range(cell.count):\\n self.set_signal_color(cell.signal_ids[i], cn.COLORS.DEFAULT_SIGNAL_COLORS[i])\",\n \"def createEctoCell(module, cell_type, name, params=list()):\\n\\tmod = __import__(module, globals(), locals(), [cell_type], 0)\\n\\tcell_builder = getattr(\\n\\t mod,\\n\\t cell_type\\n\\t)\\n\\tinit_params = dict()\\n\\tfor param in params:\\n\\t\\tif len(param[\\\"values\\\"])>0:\\n\\t\\t\\t# If value is a str and start with the module name, interpret it\\n\\t\\t\\t# as a global value\\n\\t\\t\\tfor i in range(len(param[\\\"values\\\"])):\\n\\t\\t\\t\\tif isinstance(param[\\\"values\\\"][i], basestring)\\\\\\n\\t\\t\\t\\t and param[\\\"values\\\"][i].startswith(module+'.'):\\n\\t\\t\\t\\t\\tattrs = param[\\\"values\\\"][i][len(module)+1:].split('.')\\n\\t\\t\\t\\t\\tparam_val = mod\\n\\t\\t\\t\\t\\twhile len(attrs)>0:\\n\\t\\t\\t\\t\\t\\tparam_val = getattr(param_val, attrs.pop(0))\\n\\t\\t\\t\\t\\tparam[\\\"values\\\"][i] = param_val\\n\\t\\t\\tv = param[\\\"values\\\"][0]\\n\\t\\t\\tif isinstance(v, unicode):\\n\\t\\t\\t\\tv = str(v)\\n\\t\\t\\tinit_params[str(param[\\\"param_name\\\"])] = v\\n\\treturn cell_builder(str(name),**init_params)\",\n \"def __init__(self,cell1,site1,cell2,site2,color=None,label=None,linewidth=None,linetype=None):\\n self.cell1 = np.array(cell1)\\n self.site1 = site1\\n self.cell2 = np.array(cell2)\\n self.site2 = site2\\n coordinate1 = None\\n coordinate2 = None\\n self.color = color\\n self.label = label\\n self.linewidth = linewidth\\n self.linetype = linetype\",\n \"def from_binary(cls, data):\\n if isinstance(data, basestring):\\n data = ctypes.c_buffer(data)\\n return ctypes.cast(data, cls)\",\n \"def __init__(self, id, position, parent_a=None, parent_b=None):\\n \\\"\\\"\\\" int: For uniquely identifying cells \\\"\\\"\\\"\\n self._id = 0\\n \\\"\\\"\\\" int: Possibly used for data or life-span related functions \\\"\\\"\\\"\\n self._age = 0;\\n \\\"\\\"\\\" int: To measure the success of a gene \\\"\\\"\\\"\\n self._score = p.params['initial_score']\\n \\\"\\\"\\\" Gene: The decision making entity of the cell.\\\"\\\"\\\"\\n self._gene = None\\n \\\"\\\"\\\" dict(Cell,Memory): To hold the memory of past interactions with other cells\\\"\\\"\\\"\\n self._memory = {}\\n \\\"\\\"\\\" Position: The location of the Cell within the toroidal world. \\\"\\\"\\\"\\n self._position = None\\n\\n if parent_a is not None and parent_b is not None:\\n self._gene = Gene.Gene(parent_a.get_gene(), parent_b.get_gene())\\n else:\\n self._gene = Gene.Gene()\\n self._position = position\\n self._id = id\",\n \"def make_cell(self, column_title: str, field_value: Any) -> Cell:\\n column = self.get_column(column_title)\\n if column is None:\\n raise ValueError(\\n \\\"A column with the title %s does not exist in this sheet\\\", column_title\\n )\\n if column.type == ColumnType.MULTI_PICKLIST:\\n if not column.id:\\n raise ValueError(f\\\"Column {column!r} does not have ID\\\")\\n cell = Cell.create_multi_picklist(column_id=column.id, values=field_value)\\n else:\\n cell = Cell(column_id=column.id, value=field_value)\\n return cell\",\n \"def __init__(\\n self,\\n arg=None,\\n align=None,\\n alignsrc=None,\\n fill=None,\\n font=None,\\n format=None,\\n formatsrc=None,\\n height=None,\\n line=None,\\n prefix=None,\\n prefixsrc=None,\\n suffix=None,\\n suffixsrc=None,\\n values=None,\\n valuessrc=None,\\n **kwargs\\n ):\\n super(Cells, self).__init__(\\\"cells\\\")\\n\\n # Validate arg\\n # ------------\\n if arg is None:\\n arg = {}\\n elif isinstance(arg, self.__class__):\\n arg = arg.to_plotly_json()\\n elif isinstance(arg, dict):\\n arg = _copy.copy(arg)\\n else:\\n raise ValueError(\\n \\\"\\\"\\\"\\\\\\nThe first argument to the plotly.graph_objs.table.Cells \\nconstructor must be a dict or \\nan instance of :class:`plotly.graph_objs.table.Cells`\\\"\\\"\\\"\\n )\\n\\n # Handle skip_invalid\\n # -------------------\\n self._skip_invalid = kwargs.pop(\\\"skip_invalid\\\", False)\\n\\n # Import validators\\n # -----------------\\n from plotly.validators.table import cells as v_cells\\n\\n # Initialize validators\\n # ---------------------\\n self._validators[\\\"align\\\"] = v_cells.AlignValidator()\\n self._validators[\\\"alignsrc\\\"] = v_cells.AlignsrcValidator()\\n self._validators[\\\"fill\\\"] = v_cells.FillValidator()\\n self._validators[\\\"font\\\"] = v_cells.FontValidator()\\n self._validators[\\\"format\\\"] = v_cells.FormatValidator()\\n self._validators[\\\"formatsrc\\\"] = v_cells.FormatsrcValidator()\\n self._validators[\\\"height\\\"] = v_cells.HeightValidator()\\n self._validators[\\\"line\\\"] = v_cells.LineValidator()\\n self._validators[\\\"prefix\\\"] = v_cells.PrefixValidator()\\n self._validators[\\\"prefixsrc\\\"] = v_cells.PrefixsrcValidator()\\n self._validators[\\\"suffix\\\"] = v_cells.SuffixValidator()\\n self._validators[\\\"suffixsrc\\\"] = v_cells.SuffixsrcValidator()\\n self._validators[\\\"values\\\"] = v_cells.ValuesValidator()\\n self._validators[\\\"valuessrc\\\"] = v_cells.ValuessrcValidator()\\n\\n # Populate data dict with properties\\n # ----------------------------------\\n _v = arg.pop(\\\"align\\\", None)\\n self[\\\"align\\\"] = align if align is not None else _v\\n _v = arg.pop(\\\"alignsrc\\\", None)\\n self[\\\"alignsrc\\\"] = alignsrc if alignsrc is not None else _v\\n _v = arg.pop(\\\"fill\\\", None)\\n self[\\\"fill\\\"] = fill if fill is not None else _v\\n _v = arg.pop(\\\"font\\\", None)\\n self[\\\"font\\\"] = font if font is not None else _v\\n _v = arg.pop(\\\"format\\\", None)\\n self[\\\"format\\\"] = format if format is not None else _v\\n _v = arg.pop(\\\"formatsrc\\\", None)\\n self[\\\"formatsrc\\\"] = formatsrc if formatsrc is not None else _v\\n _v = arg.pop(\\\"height\\\", None)\\n self[\\\"height\\\"] = height if height is not None else _v\\n _v = arg.pop(\\\"line\\\", None)\\n self[\\\"line\\\"] = line if line is not None else _v\\n _v = arg.pop(\\\"prefix\\\", None)\\n self[\\\"prefix\\\"] = prefix if prefix is not None else _v\\n _v = arg.pop(\\\"prefixsrc\\\", None)\\n self[\\\"prefixsrc\\\"] = prefixsrc if prefixsrc is not None else _v\\n _v = arg.pop(\\\"suffix\\\", None)\\n self[\\\"suffix\\\"] = suffix if suffix is not None else _v\\n _v = arg.pop(\\\"suffixsrc\\\", None)\\n self[\\\"suffixsrc\\\"] = suffixsrc if suffixsrc is not None else _v\\n _v = arg.pop(\\\"values\\\", None)\\n self[\\\"values\\\"] = values if values is not None else _v\\n _v = arg.pop(\\\"valuessrc\\\", None)\\n self[\\\"valuessrc\\\"] = valuessrc if valuessrc is not None else _v\\n\\n # Process unknown kwargs\\n # ----------------------\\n self._process_kwargs(**dict(arg, **kwargs))\\n\\n # Reset skip_invalid\\n # ------------------\\n self._skip_invalid = False\",\n \"def fromBytes(cls, inBytes):\\n return cls.fromJson(inBytes.decode())\",\n \"def fromBytes(cls, inBytes):\\n return cls.fromJson(inBytes.decode())\",\n \"def fromBytes(cls, inBytes):\\n return cls.fromJson(inBytes.decode())\",\n \"def from_wire(cls, header, payload_bytes, *, sender_address=None,\\n validate=False):\\n return cls.from_components(header, b'', payload_bytes,\\n sender_address=sender_address,\\n validate=validate)\",\n \"def make_cell(self, unit_type, num_units, forget_bias, dropout,\\n mode, residual_connection=False):\\n\\n # dropout (= 1 - keep_prob) is set to 0 during eval and infer\\n dropout = dropout if mode == tf.contrib.learn.ModeKeys.TRAIN else 0.0\\n\\n # Cell Type\\n if unit_type == \\\"lstm\\\":\\n cell = tf.contrib.rnn.BasicLSTMCell(\\n num_units,\\n forget_bias=forget_bias)\\n elif unit_type == \\\"gru\\\":\\n cell = tf.contrib.rnn.GRUCell(num_units)\\n elif unit_type == \\\"layer_norm_lstm\\\":\\n cell = tf.contrib.rnn.LayerNormBasicLSTMCell(\\n num_units,\\n forget_bias=forget_bias,\\n layer_norm=True)\\n else:\\n raise ValueError(\\\"Unknown unit type %s!\\\" % unit_type)\\n\\n # Dropout (= 1 - keep_prob)\\n if dropout > 0.0:\\n cell = tf.contrib.rnn.DropoutWrapper(\\n cell=cell, input_keep_prob=(1.0 - dropout))\\n\\n # Residual\\n if residual_connection:\\n cell = tf.contrib.rnn.ResidualWrapper(cell)\\n\\n return cell\",\n \"def __init__(cell, value):\\n\\t\\tcell.value = value\\n\\t\\tcell.parent = None\\n\\t\\tcell.visited = False\",\n \"def from_layer(cls, layer, cell_classifier, **kwargs):\\n return cls.__class__(layer.data, cell_classifier, **kwargs)\",\n \"def from_bin(cls, bin):\\n raw = msgpack.unpackb(bin, raw=False)\\n event_msg = EventMessage.from_text(raw[\\\"event_message\\\"])\\n msg = cls(\\n uri_name=raw[\\\"uri_name\\\"],\\n event_message=event_msg,\\n publisher_connection_id=raw[\\\"publisher_connection_id\\\"]\\n )\\n msg.publisher_node_id = raw[\\\"publisher_node_id\\\"]\\n return msg\",\n \"def add_cell(self, cell):\\n\\n if cell.uuid is None:\\n cell.uuid = self._generate_uuid()\\n\\n if cell.uuid in self._cells:\\n error_str = \\\"Trying to add an already existing cell with uuid: \\\"\\\\\\n + str(cell.uuid)\\n raise KeyError(error_str)\\n\\n self._cells[cell.uuid] = Cell.from_cell(cell)\\n\\n return cell.uuid\",\n \"def from_wire(cls, header, payload_bytes, *, sender_address=None,\\n validate=False):\\n\\n return cls.from_components(header, b'', payload_bytes,\\n sender_address=sender_address,\\n validate=validate)\",\n \"def _proto2object(\\n proto: UpdateGroupMessage_PB,\\n ) -> \\\"UpdateGroupMessage\\\":\\n\\n return UpdateGroupMessage(\\n msg_id=_deserialize(blob=proto.msg_id),\\n address=_deserialize(blob=proto.address),\\n content=json.loads(proto.content),\\n reply_to=_deserialize(blob=proto.reply_to),\\n )\",\n \"def object_from_protobuf(pb, model_type=None):\\n key = None\\n if isinstance(pb, entity_pb2.Entity):\\n pb = pb._pb\\n\\n if pb.HasField(\\\"key\\\"): # Message field (Key)\\n key = CustomIterator.key_from_protobuf(pb.key)\\n key._type = SubclassMap.get()[key.kind]\\n\\n entity_props = {}\\n\\n for prop_name, value_pb in pb.properties.items():\\n value = CustomIterator._get_value_from_value_pb(value_pb)\\n entity_props[prop_name] = value\\n\\n obj = model_type._dotted_dict_to_object(entity_props, key)\\n return obj\",\n \"def from_message(cls, template_message):\\n new_equivalent_message = cls(\\n template_message.env,\\n template_message.source,\\n template_message.destination,\\n template_message.size_bytes,\\n template_message.message_type,\\n template_message.data)\\n return new_equivalent_message\",\n \"def add_cell_field(self,name,data,on_exists='fail'):\\n # will need to get fancier to discern vector dtypes\\n # assert data.ndim==1 - maybe no need to be smart?\\n if name in np.dtype(self.cell_dtype).names:\\n if on_exists == 'fail':\\n raise GridException(\\\"Node field %s already exists\\\"%name)\\n elif on_exists == 'pass':\\n return\\n elif on_exists == 'overwrite':\\n self.cells[name] = data\\n else:\\n self.cells=recarray_add_fields(self.cells,\\n [(name,data)])\\n self.cell_dtype=self.cells.dtype\",\n \"def from_bytes(self, bytearr):\\n if len(bytearr) >= SensorMessage.BYTE_LENGTH:\\n if len(bytearr) > SensorMessage.BYTE_LENGTH:\\n bytearr = bytearr[:SensorMessage.BYTE_LENGTH+1]\\n if bytearr[0] == \\\"\\\\xca\\\" and bytearr[1] == \\\"\\\\x55\\\":\\n # Checksum checking is taken care of at RF module.\\n #if self.calc_checksum(bytearr[:-1]) == ord(bytearr[-1]):\\n self.address = bytearr[2:7]\\n try:\\n (self.errorflags,\\n self.temperature,\\n self.humidity,\\n self.supply_v,\\n self.link_quality,\\n self.message_id) = struct.unpack(\\\">BHHHBH\\\", bytearr[7:17])\\n except:\\n print \\\"Failed to unpack message: \\\" + format_hex(bytearr[7:])\\n #else:\\n # raise ValueError(\\\"Incorrect checksum: Given: \\\" + repr(ord(bytearr[-1])) + \\\", calc.: \\\" + repr(self.calc_checksum(bytearr[:-1])))\\n else:\\n raise ValueError(\\\"Incorrect message header!\\\")\",\n \"def __init__(self, cell_type, explicit_values,\\n derived_values=None, non_column_labels=None, align='',\\n sort_values=True):\\n self.type = cell_type\\n self.align = align\\n self.col_index = 0 # Is set afterward\\n self.values = []\\n if non_column_labels:\\n self.non_column_labels = [\\n template_helpers.EZTItem(value=v, is_derived=ezt.boolean(d))\\n for v, d in non_column_labels]\\n else:\\n self.non_column_labels = []\\n\\n for v in (sorted(explicit_values) if sort_values else explicit_values):\\n self.values.append(CellItem(v))\\n\\n if derived_values:\\n for v in (sorted(derived_values) if sort_values else derived_values):\\n self.values.append(CellItem(v, is_derived=True))\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def from_bytes(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def new(cls, edge_str):\\n return Tile(TileEdges(*edge_str))\",\n \"def initialize_cells(self):\\n for loc in np.ndindex(*self.shape): # TODO: see if nested for loop is faster than this\\n c = Cell(loc, self)\\n self.cells.append(c)\",\n \"def from_serialized_proto(cls, proto_string: bytes) -> 'TableInfo':\\n proto = schema_pb2.TableInfo.FromString(proto_string)\\n if proto.HasField('signature'):\\n signature = nested_structure_coder.decode_proto(proto.signature)\\n else:\\n signature = None\\n return cls(\\n name=proto.name,\\n sampler_options=proto.sampler_options,\\n remover_options=proto.remover_options,\\n max_size=proto.max_size,\\n max_times_sampled=proto.max_times_sampled,\\n rate_limiter_info=proto.rate_limiter_info,\\n signature=signature,\\n current_size=proto.current_size,\\n num_episodes=proto.num_episodes,\\n num_deleted_episodes=proto.num_deleted_episodes,\\n num_unique_samples=proto.num_unique_samples,\\n table_worker_time=proto.table_worker_time,\\n )\",\n \"def _proto2object(proto: Metadata_PB) -> \\\"Metadata\\\":\\n\\n return Metadata(\\n id=validate_type(_deserialize(blob=proto.id), UID, optional=True),\\n name=proto.name,\\n node=validate_type(_deserialize(blob=proto.node), Location),\\n )\",\n \"def from_buffer(cls, data, codec):\\n new = cls()\\n new.codec = codec\\n new.data = codec.parse(data)\\n return new\",\n \"def __init__(self, board = np.random.randint(2, size=(5, 5), dtype = np.uint8)): \\n # Check for valid filetype for board\\n if not isinstance(board, np.ndarray):\\n raise NotImplementedError(\\\"Board must be an numpy.array.\\\")\\n # Check for valid board size.\\n if any(x < 2 for x in board.shape):\\n raise NotImplementedError(\\\"Board state invalid! Must be at least 2x2.\\\")\\n # Check for valid board cell entries.\\n if not np.all(np.isin(board, [0,1])):\\n raise NotImplementedError(\\\"Board state invalid! Must be filled with 0s and 1s.\\\")\\n\\n # Define lookup table for cell evaluation\\n self.lookup = np.asarray([[0,0,0,1,0,0,0,0,0],[0,0,1,1,0,0,0,0,0]])\\n\\n # Define expanded board for easier border cell calculations\\n expanded_shape = tuple(d+2 for d in board.shape)\\n board_slice = (slice(1, -1),) * 2\\n self.expanded_board = np.zeros(expanded_shape,dtype = np.uint8)\\n self.expanded_board[board_slice] = board\\n self.board = self.expanded_board[board_slice]\",\n \"def gen_CASTEP_supercell(CASTEP_cell,na,nb,nc):\\n nruter=dict()\\n nruter[\\\"na\\\"]=na\\n nruter[\\\"nb\\\"]=nb\\n nruter[\\\"nc\\\"]=nc\\n nruter[\\\"lattvec\\\"]=np.array(CASTEP_cell[\\\"lattvec\\\"])\\n nruter[\\\"lattvec\\\"][:,0]*=na\\n nruter[\\\"lattvec\\\"][:,1]*=nb\\n nruter[\\\"lattvec\\\"][:,2]*=nc\\n nruter[\\\"elements\\\"]=copy.copy(CASTEP_cell[\\\"elements\\\"])\\n nruter[\\\"numbers\\\"]=na*nb*nc*CASTEP_cell[\\\"numbers\\\"]\\n nruter[\\\"positions\\\"]=np.empty((3,CASTEP_cell[\\\"positions\\\"].shape[1]*na*nb*nc))\\n pos=0\\n for pos,(k,j,i,iat) in enumerate(itertools.product(xrange(nc),\\n xrange(nb),\\n xrange(na),\\n xrange(\\n CASTEP_cell[\\\"positions\\\"].shape[1]))):\\n nruter[\\\"positions\\\"][:,pos]=(CASTEP_cell[\\\"positions\\\"][:,iat]+[i,j,k])/[\\n na,nb,nc]\\n nruter[\\\"types\\\"]=[]\\n for i in xrange(na*nb*nc):\\n nruter[\\\"types\\\"].extend(CASTEP_cell[\\\"types\\\"])\\n # print \\\"supercell\\\", nruter\\n return nruter\",\n \"def from_msg(cls, msg):\\n if cls._debug:\\n log.debug('msg=%s', msg)\\n key, seq_s, uuid, prop_s, body = msg\\n key = key if key else None\\n seq = struct.unpack('!q', seq_s)[0]\\n body = body if body else None\\n if body:\\n body = pipeline.load(body)\\n #body = json.loads(body_s)\\n #prop = json.loads(prop_s)\\n prop = pipeline.load(prop_s)\\n return cls(seq, uuid=uuid, key=key, properties=prop, body=body)\",\n \"def new_cell_in_time(self, cell_type, mcs=None):\\n cell = self.new_cell(cell_type)\\n if mcs is None:\\n if self.mcs < 0:\\n mcs = 0\\n else:\\n mcs = self.mcs\\n\\n cell.dict[CoronavirusLib.new_cell_mcs_key] = mcs\\n return cell\",\n \"def add_cell(self,**kwargs):\\n i=None\\n if '_index' in kwargs:\\n i=kwargs.pop('_index')\\n if i==len(self.cells): # had been self.edges, seems wrong\\n # this is the index we'd get anyway.\\n i=None\\n else:\\n assert len(self.cells)>i\\n assert self.cells[i]['deleted']\\n\\n if i is None:\\n c=np.zeros( (),dtype=self.cell_dtype)\\n self.cells=array_append(self.cells,c)\\n i=len(self.cells)-1\\n else:\\n pass\\n\\n # default values for native fields\\n self.cells['_center'][i]=np.nan\\n self.cells['_area'][i]=np.nan\\n self.cells['edges'][i]=self.UNKNOWN \\n\\n for k,v in six.iteritems(kwargs):\\n if k in ['edges','nodes']: # may have to make this more generic..\\n self.cells[k][i][:len(v)] = v\\n self.cells[k][i][len(v):] = self.UNDEFINED # -1\\n else:\\n self.cells[k][i]=v\\n\\n # Avoids issue with bogus value of 'deleted' coming in with kwargs\\n self.cells['deleted'][i]=False\\n\\n if self._node_to_cells is not None:\\n for n in self.cell_to_nodes(i):\\n self._node_to_cells[n].append(i)\\n\\n if self._cell_center_index is not None:\\n if self.cell_center_index_point=='circumcenter':\\n cc=self.cells_center()[i]\\n else: # centroid\\n cc=self.cells_centroid([i])[0]\\n self._cell_center_index.insert(i,cc[self.xxyy])\\n\\n # updated 2016-08-25 - not positive here.\\n # This whole chunk needs testing.\\n # maybe some confusion over when edges has to be set\\n edges=self.cell_to_edges(i)\\n \\n if 'edges' not in kwargs:\\n # wait - is this circular??\\n self.cells['edges'][i,:len(edges)]=edges\\n self.cells['edges'][i,len(edges):]=self.UNDEFINED\\n\\n nodes=self.cell_to_nodes(i)\\n \\n for side in range(len(edges)):\\n j=edges[side]\\n n1=nodes[side]\\n n2=nodes[ (side+1)%len(nodes) ]\\n \\n if ( (n1==self.edges['nodes'][j,0]) and\\n (n2==self.edges['nodes'][j,1]) ):\\n # this cell is on the 'left' side of the edge\\n assert self.edges['cells'][j,0]<0\\n # TODO: probably this ought to be using modify_edge\\n self.edges['cells'][j,0]=i\\n elif ( (n1==self.edges['nodes'][j,1]) and\\n (n2==self.edges['nodes'][j,0]) ):\\n # this cell is on the 'right' side of the edge\\n assert self.edges['cells'][j,1]<0\\n # TODO: probably this ought to be using modify_edge\\n self.edges['cells'][j,1]=i\\n else:\\n assert False\\n \\n self.push_op(self.unadd_cell,i)\\n\\n return i\",\n \"def create_from_buffer(cls, buffer: str) -> \\\"TensorImage\\\":\\n image_data = image_utils.decode_image_from_buffer(buffer, len(buffer))\\n return cls(image_data, is_from_numpy_array=False)\",\n \"def create_from_proto(cls, aux_pow_proto: protos.BitcoinAuxPow) -> 'BitcoinAuxPow':\\n return cls(\\n header_head=aux_pow_proto.header_head,\\n coinbase_head=aux_pow_proto.coinbase_head,\\n coinbase_tail=aux_pow_proto.coinbase_tail,\\n merkle_path=list(aux_pow_proto.merkle_path),\\n header_tail=aux_pow_proto.header_tail,\\n )\",\n \"def parse_and_decode(cls, data: bytes) -> \\\"Message\\\":\\n if len(data) < cls.calc_size() + 1:\\n raise NotEnoughData()\\n if data[0] != cls.type:\\n raise InvalidType()\\n\\n return cls(*unpack('<' + cls.fmt, data[1:cls.calc_size() + 1]))\",\n \"def initial_cell_state_from_embedding(cell, z, batch_size, name=None):\\n flat_state_sizes = tf_nest.flatten(cell.state_size)\\n return tf_nest.pack_sequence_as(\\n cell.zero_state(batch_size=batch_size, dtype=tf.float32),\\n tf.split(\\n tf.layers.dense(\\n z,\\n sum(flat_state_sizes),\\n activation=tf.tanh,\\n kernel_initializer=tf.random_normal_initializer(stddev=0.001),\\n name=name),\\n flat_state_sizes,\\n axis=1))\",\n \"def cell(self, value):\\n if value is not None:\\n value.get_shape().assert_is_compatible_with(self._output_shape)\\n self._cell = value\",\n \"def __init__(self, cells):\\n self.cells = cells\\n # Used by MakeTableData for layout.\\n self.idx = None\\n self.group = None\\n self.rows_in_group = None\\n self.starred = None\",\n \"def from_wire(cls, header, payload_bytes, *, sender_address=None,\\n validate=False):\\n if not cls.HAS_PAYLOAD:\\n return cls.from_components(header)\\n payload = from_buffer(header.data_type, header.data_count,\\n payload_bytes)\\n return cls.from_components(header, *payload,\\n sender_address=sender_address,\\n validate=validate)\",\n \"def _new_record():\\n nonlocal key\\n nonlocal value_list\\n nonlocal record\\n nonlocal origin\\n nonlocal field_offset_map\\n key = None\\n value_list = None\\n if source is not None:\\n origin = Origin(source, None, None)\\n field_offset_map = {}\\n record = RFC822Record(data_cls(), origin, data_cls(), field_offset_map)\",\n \"def from_dict(cls, dikt: dict) -> 'NeighborAddress':\\n return util.deserialize_model(dikt, cls)\",\n \"def create_model():\\n\\n class Net(nn.Cell):\\n def construct(self, x, y):\\n return x\\n\\n net = Net()\\n model_simple = Model(net)\\n\\n return model_simple\",\n \"def from_simple_data(self,points=[],edges=[],cells=[]):\\n\\n if isinstance(points,int):\\n self.nodes = np.zeros( points, self.node_dtype)\\n else:\\n self.nodes = np.zeros( len(points), self.node_dtype)\\n if len(points):\\n points = np.asarray(points)\\n self.nodes['x'] = points[:,:2] # discard any z's that come in\\n\\n if isinstance(cells,int):\\n self.cells = np.zeros(cells,self.cell_dtype)\\n else:\\n self.cells = np.zeros( len(cells), self.cell_dtype)\\n if len(cells):\\n cells = np.asarray(cells)\\n self.cells['nodes'][...] = -1\\n # allow for initializing the grid with a cell\\n # array with fewer than maxsides\\n Nnode_in = cells.shape[1]\\n self.cells['nodes'][:,:Nnode_in] = cells\\n self.cells['_center'] = np.nan # signal stale\\n self.cells['_area'] = np.nan # signal stale\\n self.cells['edges'] = self.UNKNOWN # and no data here\\n\\n if isinstance(edges,int):\\n self.edges = np.zeros(edges,self.edge_dtype)\\n else:\\n self.edges = np.zeros(len(edges),self.edge_dtype)\\n if len(edges):\\n edges = np.asarray(edges)\\n # incoming edges may just have connectivity\\n if edges.shape[1] == 2:\\n self.edges['nodes'] = edges\\n\\n self.edges['mark'] = self.UNKNOWN\\n self.edges['cells'][:,0] = self.UNKNOWN\\n self.edges['cells'][:,1] = self.UNKNOWN\\n elif edges.shape[1] == 5:\\n self.edges['nodes'] = edges[:,:2]\\n self.edges['mark'] = edges[:,2]\\n self.edges['cells'] = edges[:,3:5]\\n else:\\n raise GridException(\\\"Edges should have 2 or 5 entries per edge\\\")\\n \\n self.refresh_metadata()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6069733","0.59923977","0.591453","0.5743067","0.57002413","0.5664882","0.56352407","0.56330913","0.5609407","0.5444072","0.54251987","0.5407165","0.53757244","0.53634584","0.5359123","0.53427815","0.534006","0.5338059","0.5290304","0.52515936","0.52507013","0.52430564","0.5207342","0.5180202","0.5175145","0.51378036","0.5120299","0.511448","0.51074165","0.51002747","0.50926024","0.50622463","0.5040573","0.50404674","0.50353557","0.5014632","0.5002294","0.50001043","0.49961415","0.4977032","0.49601808","0.4959983","0.49395838","0.48971352","0.48959547","0.48953244","0.48902795","0.4881485","0.4881485","0.4881485","0.48733342","0.48520705","0.48430064","0.48308808","0.48303282","0.4829634","0.48216122","0.48195845","0.4817078","0.4816","0.4802349","0.47970554","0.47951952","0.4786505","0.4786505","0.4786505","0.4786505","0.4786505","0.4786505","0.4786505","0.4786505","0.4786505","0.4786505","0.4786505","0.4786505","0.4786505","0.4786505","0.4786505","0.4786505","0.47856373","0.47809774","0.47649047","0.4760937","0.47543433","0.4741104","0.4727902","0.47248572","0.47247094","0.47159684","0.47126165","0.47089598","0.47077912","0.4705125","0.47038713","0.47013637","0.47002223","0.4698925","0.46952835","0.4690838","0.46892962"],"string":"[\n \"0.6069733\",\n \"0.59923977\",\n \"0.591453\",\n \"0.5743067\",\n \"0.57002413\",\n \"0.5664882\",\n \"0.56352407\",\n \"0.56330913\",\n \"0.5609407\",\n \"0.5444072\",\n \"0.54251987\",\n \"0.5407165\",\n \"0.53757244\",\n \"0.53634584\",\n \"0.5359123\",\n \"0.53427815\",\n \"0.534006\",\n \"0.5338059\",\n \"0.5290304\",\n \"0.52515936\",\n \"0.52507013\",\n \"0.52430564\",\n \"0.5207342\",\n \"0.5180202\",\n \"0.5175145\",\n \"0.51378036\",\n \"0.5120299\",\n \"0.511448\",\n \"0.51074165\",\n \"0.51002747\",\n \"0.50926024\",\n \"0.50622463\",\n \"0.5040573\",\n \"0.50404674\",\n \"0.50353557\",\n \"0.5014632\",\n \"0.5002294\",\n \"0.50001043\",\n \"0.49961415\",\n \"0.4977032\",\n \"0.49601808\",\n \"0.4959983\",\n \"0.49395838\",\n \"0.48971352\",\n \"0.48959547\",\n \"0.48953244\",\n \"0.48902795\",\n \"0.4881485\",\n \"0.4881485\",\n \"0.4881485\",\n \"0.48733342\",\n \"0.48520705\",\n \"0.48430064\",\n \"0.48308808\",\n \"0.48303282\",\n \"0.4829634\",\n \"0.48216122\",\n \"0.48195845\",\n \"0.4817078\",\n \"0.4816\",\n \"0.4802349\",\n \"0.47970554\",\n \"0.47951952\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.4786505\",\n \"0.47856373\",\n \"0.47809774\",\n \"0.47649047\",\n \"0.4760937\",\n \"0.47543433\",\n \"0.4741104\",\n \"0.4727902\",\n \"0.47248572\",\n \"0.47247094\",\n \"0.47159684\",\n \"0.47126165\",\n \"0.47089598\",\n \"0.47077912\",\n \"0.4705125\",\n \"0.47038713\",\n \"0.47013637\",\n \"0.47002223\",\n \"0.4698925\",\n \"0.46952835\",\n \"0.4690838\",\n \"0.46892962\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7500258"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":83493,"cells":{"query":{"kind":"string","value":"Append bytes from a new chunk to value."},"document":{"kind":"string","value":"def append_value(self, value):\n self.value += value"},"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 append_bytes(self, data):\n\n if self.index != 7:\n self.buf.append(self.byte)\n self.byte = 0\n self.index = 7\n\n self.buf.extend(data)","def add_chunk(self, chunk):\n self.chunkbuffer.appendleft(chunk)","def add_byte(self, newbyte):\n self._data.append(newbyte)","def push(self, value):\n # Add value, then increment pointer (and size if necessary)\n self.buf[self.ptr] = np.array(value)\n self.ptr = (self.ptr + 1) % self.length\n if self._size < self.length:\n self._size += 1","def append(self, data):\n self.buf = b''.join([self.buf, data])","def add_slice(self, value):\n if isinstance(value, str):\n self._add_slice_length(len(value))\n self._data += value.encode(\"utf-8\")\n elif isinstance(value, (bytes, bytearray)):\n self._add_slice_length(len(value))\n self._data += value\n else:\n length = 0\n for _ in value:\n length += 1\n self._add_slice_length(length)\n self.add_array(value)","def append(self, s):\n self.offset += len(s)\n self.data += s","def append(self, value):\n value = np.asarray(value)\n\n if self.__buffer is None:\n newsize = (ArrayBuffer.initial_size,) + value.shape # tuples\n self.__buffer = np.zeros(newsize, value.dtype)\n\n assert(value.ndim == self.__buffer.ndim - 1)\n assert(value.shape == self.__buffer.shape[1:])\n\n self.__count += 1\n\n if self.__count >= self.__buffer.shape[0]:\n growth_factor = 2.0\n newsize = list(self.__buffer.shape)\n newsize[0] = int(np.floor(growth_factor * newsize[0] + 2.0))\n self.__buffer = np.resize(self.__buffer, newsize)\n\n self.__buffer[self.__count - 1] = value\n self.__value = self.__buffer[:self.__count]","def add_byte(self, value):\n if isinstance(value, int):\n self.add_int8(int(value))\n else:\n if isinstance(value, str):\n value = value.encode(\"utf-8\")\n elif not isinstance(value, (bytes, bytearray)):\n raise Exception(\"value of type {} cannot be added as a single byte\".format(type(value)))\n if len(value) != 1:\n raise j.exceptions.Value(\n \"a single byte has to be accepted, amount of bytes given: {}\".format(len(value))\n )\n self._data += value","def append(self, value: object) -> None:\n self.data.append(value)","def append(self, value):\n if len(self.data) >= n:\n self.data.pop(0)\n self.data.append(value)","def append(self, value):\n self.data.append(None)\n self.data[len(self.data)-1] = value","def add_bytes(self, data, **kwargs):\n\t\tbody, headers = multipart.stream_bytes(data, self.chunk_size)\n\t\treturn self._client.request('/add', decoder='json',\n\t\t data=body, headers=headers, **kwargs)","def extend_data(self, data):\r\n\r\n self._data_l += len(data)\r\n if not self.store: return\r\n self._data_b.write(data)","def pack(self,buffer):\n buffer.append(self.data)","def write_binary(self,value):\n self.write_uint32(len(value))\n self.data.extend(value)","def append(self, data):\n\n if data is None:\n return\n\n odata = data\n if not isinstance(data, (six.binary_type, six.text_type, bytearray)):\n if hasattr(data, \"getvalue\"):\n data = data.getvalue()\n elif (hasattr(data, \"read\") and\n hasattr(data, \"seek\") and\n hasattr(data, \"tell\")):\n with Excursion(data):\n data = data.read()\n\n if isinstance(data, six.text_type):\n data = data.encode(\"utf-8\")\n elif isinstance(data, bytearray):\n data = six.binary_type(data)\n\n if not isinstance(data, six.binary_type):\n raise TypeError(\"expected a string or filelike, not %r\"\n % odata)\n\n with Excursion(self._buf):\n self._buf.seek(0, 2)\n self._buf.write(data)\n self._len = self._buf.tell()","def append(self, value):\n self[self._end] = value\n self._end = (self._end + 1) % self._capacity\n\n if self.full:\n self._begin = (self._begin + 1) % self._capacity\n\n else:\n self._size += 1","def add(self, value):\n self._resolve_copies()\n self.data.append(value)","def add_to_buffer(self, values):\n self._buffer.extend(values)","def push(self, value: object) -> None:\n self._data.append(value)","def push(self, value: object) -> None:\n self._data.append(value)","def append(self, value):\r\n # Assign\r\n self._data[self.curr_pos] = value\r\n # Go to the next position\r\n self.curr_pos = (self.curr_pos + 1) % self.rows\r\n # Increment filled_rows if necessary\r\n if self.filled_rows < self.rows: \r\n self.filled_rows+=1","def _add_cached_chunk(self, offset, data):\n if (\n self._cached_chunk_position + len(self._cached_chunk) == offset\n and len(self._cached_chunk) + len(data) < _MAX_CACHED_CHUNK_SIZE\n ):\n # add to existing cache\n self._cached_chunk += data\n else:\n self._cached_chunk = data\n self._cached_chunk_position = offset","def append(self, data):\n self.ensure_initialized()\n Buffer(stream=self.name,\n data=data).save(write_concern=dict(w=0, j=False))","def append(self, v):\n self.data.append(v)","def add( self, chunk ):\n self.chunkSeq.append( chunk )\n chunk.web= weakref.ref(self)","def process(self, chunk):\n self._buf += chunk\n\n # Streams are `\\r\\n`-separated JSON messages.\n raw_lines = self._buf.split(b\"\\r\\n\")\n\n # If only one element in the split, then there wasn't a CRLF.\n if len(raw_lines) > 1:\n\n # The last element may be a b'', which is perfectly fine.\n self._buf = raw_lines[-1]\n\n # Blank lines are keep-alive messages.\n self._mailbox.extend(l for l in raw_lines[:-1] if l.strip())","def append(self, value):\n self.values.append(value)\n return value","def append(self, x):\n if self.buffer[self.end]:\n if self.start <= self.end:\n self.buffer = (self.buffer[self.start:self.end]\n + [x]\n + [None]*(self.size - 1))\n else:\n self.buffer = ([(item for item\n in (self.buffer[self.start:]\n + self.buffer[:self.end])\n if item is not None)]\n + [x]\n + [None]*(self.size - 1))\n self.start = 0\n self.end = len(self.buffer) - self.size + 1\n else:\n self.buffer[self.end] = x\n self.end = (self.end + 1) % len(self.buffer)","def append_to(self, key, value):\n self.get_data()[key].append(value.get_data())","def write( chunk, callback=None ):","def addition(self, first_value, second_value):\n return bytes(first_value + second_value)","def push_word(self, value):\n self.push_byte((value & 0xFF00) >> 8)\n return self.push_byte(value & 0xFF)","def enqueue(self, value: object) -> None:\n self._data.append(value)","def enqueue(self, value: object) -> None:\n self._data.append(value)","def add_data(self, data):\n self._data += data","def push_byte(self, value):\n reg_s = self.get_register('S')\n self.set_memory(reg_s + self.stack_base, value)\n self.set_register('S', reg_s - 1)\n return reg_s + self.stack_base - 1","def push(self, value):\n raise NotImplementedError","def append(self, line):\n self.buffer.append(line)","def add(self, data):\n self.databuffer.append(data)\n if len(self.databuffer) > self.buffersize:\n self._flush()","def write(self, data):\n self.buffer.append(data)\n while self.push():\n pass","def append(self, line):\n if self.__maxsize > 0 and len(self.__contents) > self.__maxsize:\n self.__contents = self.__contents[1:]\n # Remove trailing newline/end of line characters\n self.__contents.append(line.rstrip(\"\\r\\n\"))","def append(self, val):\n self._values.push(val)","def write(self, data):\n self.buffer.write(data)\n self.offset += len(data)","def chunk_written(self):\n pass","def put(self, item): \n if len(self.contents) < self.max_size:\n self.contents.append(item)\n elif len(self.contents) >= self.max_size:\n print \"Backpack Full.\"","def add(self, item):\r\n if len(self.buff)==self.size: self.buff.pop(0)\r\n self.buff.append(item)","def add_data(self, data):\n self.data = self.data + data","def _writeBytes(self, b):\n self.stream.write(b)\n self.stream.flush()","def append(self, value) -> None:\n key = getattr(value, self.keyattr)\n if callable(key):\n key = key()\n if key not in self.data:\n self.data[key] = []\n self.data[key].append(value)\n self.size += 1","def push(self, value):\n self.append(value)\n return len(self) - 1","def append(self, val):\n self.val.append(val)","def write(self, address: int, value: bytearray):\n for i, val in enumerate(value):\n self.mem[address+i] = value","def add(self, value):\n\n # if the value implements the RivineBinaryObjectEncoderBase class,\n # we ignore the underlying type and use the custom-defined logic\n # as provided by the RivineBinaryObjectEncoder.\n if isinstance(value, RivineBinaryObjectEncoderBase):\n value.rivine_binary_encode(encoder=self)\n return\n\n # try to rivbin-encode the value based on its python type\n if isinstance(value, bool):\n if value:\n self._data += bytearray([1])\n else:\n self._data += bytearray([0])\n elif isinstance(value, int):\n self.add_int64(value)\n else:\n # try to rivbin-encode the value as a slice\n try:\n self.add_slice(value)\n return\n except TypeError:\n pass\n raise Exception(\"cannot rivbin-encode value with unsupported type {}\".format(type(value)))","def write(self, chunk):\n return self.tornado_request.write(chunk)","def append(self, state):\n self._buffer[:-1] = self._buffer[1:]\n self._buffer[-1] = state","def insert(self, val):\n self.data.insert(0,val)\n self.size = self.size + 1","def insert(self, value):\n current_timestamp = time.time()\n self.timestamps.append(current_timestamp)\n self.dataBuffer.append(value)\n if (self.timestamps[0] < (current_timestamp - self.seconds_back)):\n self.dataBuffer.pop(0)\n self.timestamps.pop(0)","def update_bytes_array(self):\n self.bytes = data_manipulation.convert_from_binary_array(self.binary_array)","def writeChunk(chunk):","def write(self, data):\n\n # TODO - Check bytes vs unicode\n data = _as_bytes(data)\n # block_size = 2**16 = 65536\n data_len = len(data)\n if len(self._buffer) + data_len < 65536:\n # print(\"Cached %r\" % data)\n self._buffer += data\n return\n else:\n # print(\"Got %r, writing out some data...\" % data)\n self._buffer += data\n while len(self._buffer) >= 65536:\n self._write_block(self._buffer[:65536])\n self._buffer = self._buffer[65536:]","def add_value(self, val: float):\n self._mtx.acquire()\n self._buffer.append(val)\n self._sum += val\n\n if self._cur_elem_count < self._frame_size:\n self._cur_elem_count += 1\n else:\n self._sum -= self._buffer[0]\n self._buffer.pop(0)\n self._mtx.release()","def Write(buf: IO[bytes], chunk: bytes) -> None:\n buf.write(_UINT64.pack(len(chunk)))\n buf.write(chunk)","def enQueue(self, value):\n if self.isFull():\n return False\n self.__buffer[(self.__start+self.__size) % len(self.__buffer)] = value\n self.__size += 1\n return True","def extendMessage(self, message: bytearray) -> bytearray:\n initLength: int = len(message)\n appendLength: int = 16 - initLength % 16\n message = message + \\\n bytearray([appendLength for _ in range(appendLength)])\n return message","def push(self, value):\n self.last = self.current\n self.current = np.array(value)","def write(self, b):\n if isinstance(b, six.string_types):\n b = bytearray(b, encoding='utf-8')\n\n logger.debug(\"writing %r bytes to %r\", len(b), self._buf)\n\n self._buf.write(b)\n\n if self._buf.tell() >= self._upload_chunk_size:\n self._upload_next_part()\n\n return len(b)","def __bytes__(self):\n return bytes([self.type * 2, len(self.value)]) + bytes(self.value, 'utf-8')","def __bytes__(self):\n return bytes([self.type * 2, len(self.value)]) + bytes(self.value, 'utf-8')","def __bytes__(self):\n return bytes([self.type * 2, len(self.value)]) + bytes(self.value, 'utf-8')","def add_int64(self, value):\n self._check_int_type(value, _INT_8BYTE_UPPERLIMIT)\n self._data += value.to_bytes(8, byteorder=\"little\")","def append_chunk(cls, uuid, sequence_number, raw_data, compressed=False):\n if compressed:\n f = BytesIO()\n z = zipfile.ZipFile(f, \"w\", zipfile.ZIP_DEFLATED)\n z.writestr(\"data\", raw_data)\n z.close()\n data = f.getvalue()\n f.close()\n else:\n data = raw_data\n data_object = cls(\n uuid=uuid, sequence_number=sequence_number, blob=data,\n compressed=compressed\n )\n data_object.save()\n return data_object","def append(self, val):\n self.new_dll.append(val)","def write(self, b):\n return self._write_at(b, self._offset)","def push(self, value):\n self.items.append(value)","def write_value(self, value, length, error=True, move_start=True):\n if not error and length > self.maxsize:\n length = self.maxsize\n\n idxs = self.get_indexes(self._end, length, self.maxsize)\n self.move_end(length, error, move_start)\n self._data[idxs] = value","def rawAppend(self, data):\n self.message = self.message + data","def update_binary_bytes(self):\n self.binary_array = data_manipulation.convert_byte_array(self.bytes, self.binary_size)","def append_buffer(self, buffer):\n\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\n\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\n d1 = [b[0] for b in buffer.memory] # actions\n d2 = [b[1][0] for b in buffer.memory] # speeds\n d3 = [b[1][1] for b in buffer.memory] # lidar\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes (terminated or truncated)\n d5 = [b[2] for b in buffer.memory] # rewards\n d6 = [b[5] for b in buffer.memory] # infos\n d7 = [b[3] for b in buffer.memory] # terminated\n d8 = [b[4] for b in buffer.memory] # truncated\n\n if self.__len__() > 0:\n self.data[0] += d0\n self.data[1] += d1\n self.data[2] += d2\n self.data[3] += d3\n self.data[4] += d4\n self.data[5] += d5\n self.data[6] += d6\n self.data[7] += d7\n self.data[8] += d8\n else:\n self.data.append(d0)\n self.data.append(d1)\n self.data.append(d2)\n self.data.append(d3)\n self.data.append(d4)\n self.data.append(d5)\n self.data.append(d6)\n self.data.append(d7)\n self.data.append(d8)\n\n to_trim = self.__len__() - self.memory_size\n if to_trim > 0:\n self.data[0] = self.data[0][to_trim:]\n self.data[1] = self.data[1][to_trim:]\n self.data[2] = self.data[2][to_trim:]\n self.data[3] = self.data[3][to_trim:]\n self.data[4] = self.data[4][to_trim:]\n self.data[5] = self.data[5][to_trim:]\n self.data[6] = self.data[6][to_trim:]\n self.data[7] = self.data[7][to_trim:]\n self.data[8] = self.data[8][to_trim:]\n\n return self","def add_int8(self, value):\n self._check_int_type(value, _INT_1BYTE_UPPERLIMIT)\n self._data += value.to_bytes(1, byteorder=\"little\")","def _got_remote(self, data):\n self._recv_buffer += data","def append_buffer(self, buffer):\n\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\n\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\n d1 = [b[0] for b in buffer.memory] # actions\n d2 = [b[1][0] for b in buffer.memory] # speeds\n d3 = [b[1][2] for b in buffer.memory] # lidar\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\n d5 = [b[2] for b in buffer.memory] # rewards\n d6 = [b[5] for b in buffer.memory] # infos\n d7 = [b[1][1] for b in buffer.memory] # progress\n d8 = [b[3] for b in buffer.memory] # terminated\n d9 = [b[4] for b in buffer.memory] # truncated\n\n if self.__len__() > 0:\n self.data[0] += d0\n self.data[1] += d1\n self.data[2] += d2\n self.data[3] += d3\n self.data[4] += d4\n self.data[5] += d5\n self.data[6] += d6\n self.data[7] += d7\n self.data[8] += d8\n self.data[9] += d9\n else:\n self.data.append(d0)\n self.data.append(d1)\n self.data.append(d2)\n self.data.append(d3)\n self.data.append(d4)\n self.data.append(d5)\n self.data.append(d6)\n self.data.append(d7)\n self.data.append(d8)\n self.data.append(d9)\n\n to_trim = self.__len__() - self.memory_size\n if to_trim > 0:\n self.data[0] = self.data[0][to_trim:]\n self.data[1] = self.data[1][to_trim:]\n self.data[2] = self.data[2][to_trim:]\n self.data[3] = self.data[3][to_trim:]\n self.data[4] = self.data[4][to_trim:]\n self.data[5] = self.data[5][to_trim:]\n self.data[6] = self.data[6][to_trim:]\n self.data[7] = self.data[7][to_trim:]\n self.data[8] = self.data[8][to_trim:]\n self.data[9] = self.data[9][to_trim:]\n\n return self","def insertLast(self, value):\n if not self.isFull():\n self._data.append(value)\n return True\n else:\n return False","def _append_value(self, stream, value):\n if FLAGS.timestamp:\n x_val = float(time.time())\n stream['x'].append(x_val)\n\n y_val = float(value)\n stream['y'].append(y_val)","def add(self, value):\n ind = self._ind % self.shape[0]\n self._values[ind] = value\n self._ind += 1\n self._cached = False","def readinto(self, b):\n read_resp = self._read_range(self._offset, self._offset + len(b))\n bytes_read = len(read_resp)\n b[:bytes_read] = read_resp\n return bytes_read","def _add_to_buffer(self, data):\n for byte in data:\n self.next_fn(byte) \n self._parse_cmds()","def put_byte(self, *args) -> \"int\":\n return _ida_fpro.qfile_t_put_byte(self, *args)","def appendleft(self, val):\n self.new_dll.push(val)","def upload_add_progress(self, nbytes):\n\n self.send_cur_nbytes += nbytes\n if self.send_goal_nbytes != 0:\n self.republish_output()","def insert_bytes(self, bytes_to_write, location=None, overwrite=False):\n num_bytes = len(bytes_to_write)\n\n off = self._offset\n if location is not None:\n off = location\n if overwrite:\n self._tiff[off:off + num_bytes] = bytes_to_write\n else:\n self._tiff = np.insert(self._tiff, off, bytes_to_write)\n if location is None:\n self._offset += num_bytes\n\n return num_bytes","def data(self, data):\n try:\n self.put_nowait(data)\n except Full:\n pass","def append_end(self, data):\r\n with open(self.file_name, 'a', encoding='utf-8') as self.file:\r\n self.file.write(data)","def setByteArray(self, name: unicode, value: List[int]) -> None:\n ...","def push(self, value):\n self.h.append(value)\n self.d[value] = len(self.h) - 1\n self.float_up(len(self.h) - 1)","def push(self, value):\n self.h.append(value)\n self.d[value] = len(self.h) - 1\n self.float_up(len(self.h) - 1)","def push(self, value):\n self.container.append(value)","def write(self, buf: bytes, /) -> int:","def write(self, buf: bytes, /) -> int:"],"string":"[\n \"def append_bytes(self, data):\\n\\n if self.index != 7:\\n self.buf.append(self.byte)\\n self.byte = 0\\n self.index = 7\\n\\n self.buf.extend(data)\",\n \"def add_chunk(self, chunk):\\n self.chunkbuffer.appendleft(chunk)\",\n \"def add_byte(self, newbyte):\\n self._data.append(newbyte)\",\n \"def push(self, value):\\n # Add value, then increment pointer (and size if necessary)\\n self.buf[self.ptr] = np.array(value)\\n self.ptr = (self.ptr + 1) % self.length\\n if self._size < self.length:\\n self._size += 1\",\n \"def append(self, data):\\n self.buf = b''.join([self.buf, data])\",\n \"def add_slice(self, value):\\n if isinstance(value, str):\\n self._add_slice_length(len(value))\\n self._data += value.encode(\\\"utf-8\\\")\\n elif isinstance(value, (bytes, bytearray)):\\n self._add_slice_length(len(value))\\n self._data += value\\n else:\\n length = 0\\n for _ in value:\\n length += 1\\n self._add_slice_length(length)\\n self.add_array(value)\",\n \"def append(self, s):\\n self.offset += len(s)\\n self.data += s\",\n \"def append(self, value):\\n value = np.asarray(value)\\n\\n if self.__buffer is None:\\n newsize = (ArrayBuffer.initial_size,) + value.shape # tuples\\n self.__buffer = np.zeros(newsize, value.dtype)\\n\\n assert(value.ndim == self.__buffer.ndim - 1)\\n assert(value.shape == self.__buffer.shape[1:])\\n\\n self.__count += 1\\n\\n if self.__count >= self.__buffer.shape[0]:\\n growth_factor = 2.0\\n newsize = list(self.__buffer.shape)\\n newsize[0] = int(np.floor(growth_factor * newsize[0] + 2.0))\\n self.__buffer = np.resize(self.__buffer, newsize)\\n\\n self.__buffer[self.__count - 1] = value\\n self.__value = self.__buffer[:self.__count]\",\n \"def add_byte(self, value):\\n if isinstance(value, int):\\n self.add_int8(int(value))\\n else:\\n if isinstance(value, str):\\n value = value.encode(\\\"utf-8\\\")\\n elif not isinstance(value, (bytes, bytearray)):\\n raise Exception(\\\"value of type {} cannot be added as a single byte\\\".format(type(value)))\\n if len(value) != 1:\\n raise j.exceptions.Value(\\n \\\"a single byte has to be accepted, amount of bytes given: {}\\\".format(len(value))\\n )\\n self._data += value\",\n \"def append(self, value: object) -> None:\\n self.data.append(value)\",\n \"def append(self, value):\\n if len(self.data) >= n:\\n self.data.pop(0)\\n self.data.append(value)\",\n \"def append(self, value):\\n self.data.append(None)\\n self.data[len(self.data)-1] = value\",\n \"def add_bytes(self, data, **kwargs):\\n\\t\\tbody, headers = multipart.stream_bytes(data, self.chunk_size)\\n\\t\\treturn self._client.request('/add', decoder='json',\\n\\t\\t data=body, headers=headers, **kwargs)\",\n \"def extend_data(self, data):\\r\\n\\r\\n self._data_l += len(data)\\r\\n if not self.store: return\\r\\n self._data_b.write(data)\",\n \"def pack(self,buffer):\\n buffer.append(self.data)\",\n \"def write_binary(self,value):\\n self.write_uint32(len(value))\\n self.data.extend(value)\",\n \"def append(self, data):\\n\\n if data is None:\\n return\\n\\n odata = data\\n if not isinstance(data, (six.binary_type, six.text_type, bytearray)):\\n if hasattr(data, \\\"getvalue\\\"):\\n data = data.getvalue()\\n elif (hasattr(data, \\\"read\\\") and\\n hasattr(data, \\\"seek\\\") and\\n hasattr(data, \\\"tell\\\")):\\n with Excursion(data):\\n data = data.read()\\n\\n if isinstance(data, six.text_type):\\n data = data.encode(\\\"utf-8\\\")\\n elif isinstance(data, bytearray):\\n data = six.binary_type(data)\\n\\n if not isinstance(data, six.binary_type):\\n raise TypeError(\\\"expected a string or filelike, not %r\\\"\\n % odata)\\n\\n with Excursion(self._buf):\\n self._buf.seek(0, 2)\\n self._buf.write(data)\\n self._len = self._buf.tell()\",\n \"def append(self, value):\\n self[self._end] = value\\n self._end = (self._end + 1) % self._capacity\\n\\n if self.full:\\n self._begin = (self._begin + 1) % self._capacity\\n\\n else:\\n self._size += 1\",\n \"def add(self, value):\\n self._resolve_copies()\\n self.data.append(value)\",\n \"def add_to_buffer(self, values):\\n self._buffer.extend(values)\",\n \"def push(self, value: object) -> None:\\n self._data.append(value)\",\n \"def push(self, value: object) -> None:\\n self._data.append(value)\",\n \"def append(self, value):\\r\\n # Assign\\r\\n self._data[self.curr_pos] = value\\r\\n # Go to the next position\\r\\n self.curr_pos = (self.curr_pos + 1) % self.rows\\r\\n # Increment filled_rows if necessary\\r\\n if self.filled_rows < self.rows: \\r\\n self.filled_rows+=1\",\n \"def _add_cached_chunk(self, offset, data):\\n if (\\n self._cached_chunk_position + len(self._cached_chunk) == offset\\n and len(self._cached_chunk) + len(data) < _MAX_CACHED_CHUNK_SIZE\\n ):\\n # add to existing cache\\n self._cached_chunk += data\\n else:\\n self._cached_chunk = data\\n self._cached_chunk_position = offset\",\n \"def append(self, data):\\n self.ensure_initialized()\\n Buffer(stream=self.name,\\n data=data).save(write_concern=dict(w=0, j=False))\",\n \"def append(self, v):\\n self.data.append(v)\",\n \"def add( self, chunk ):\\n self.chunkSeq.append( chunk )\\n chunk.web= weakref.ref(self)\",\n \"def process(self, chunk):\\n self._buf += chunk\\n\\n # Streams are `\\\\r\\\\n`-separated JSON messages.\\n raw_lines = self._buf.split(b\\\"\\\\r\\\\n\\\")\\n\\n # If only one element in the split, then there wasn't a CRLF.\\n if len(raw_lines) > 1:\\n\\n # The last element may be a b'', which is perfectly fine.\\n self._buf = raw_lines[-1]\\n\\n # Blank lines are keep-alive messages.\\n self._mailbox.extend(l for l in raw_lines[:-1] if l.strip())\",\n \"def append(self, value):\\n self.values.append(value)\\n return value\",\n \"def append(self, x):\\n if self.buffer[self.end]:\\n if self.start <= self.end:\\n self.buffer = (self.buffer[self.start:self.end]\\n + [x]\\n + [None]*(self.size - 1))\\n else:\\n self.buffer = ([(item for item\\n in (self.buffer[self.start:]\\n + self.buffer[:self.end])\\n if item is not None)]\\n + [x]\\n + [None]*(self.size - 1))\\n self.start = 0\\n self.end = len(self.buffer) - self.size + 1\\n else:\\n self.buffer[self.end] = x\\n self.end = (self.end + 1) % len(self.buffer)\",\n \"def append_to(self, key, value):\\n self.get_data()[key].append(value.get_data())\",\n \"def write( chunk, callback=None ):\",\n \"def addition(self, first_value, second_value):\\n return bytes(first_value + second_value)\",\n \"def push_word(self, value):\\n self.push_byte((value & 0xFF00) >> 8)\\n return self.push_byte(value & 0xFF)\",\n \"def enqueue(self, value: object) -> None:\\n self._data.append(value)\",\n \"def enqueue(self, value: object) -> None:\\n self._data.append(value)\",\n \"def add_data(self, data):\\n self._data += data\",\n \"def push_byte(self, value):\\n reg_s = self.get_register('S')\\n self.set_memory(reg_s + self.stack_base, value)\\n self.set_register('S', reg_s - 1)\\n return reg_s + self.stack_base - 1\",\n \"def push(self, value):\\n raise NotImplementedError\",\n \"def append(self, line):\\n self.buffer.append(line)\",\n \"def add(self, data):\\n self.databuffer.append(data)\\n if len(self.databuffer) > self.buffersize:\\n self._flush()\",\n \"def write(self, data):\\n self.buffer.append(data)\\n while self.push():\\n pass\",\n \"def append(self, line):\\n if self.__maxsize > 0 and len(self.__contents) > self.__maxsize:\\n self.__contents = self.__contents[1:]\\n # Remove trailing newline/end of line characters\\n self.__contents.append(line.rstrip(\\\"\\\\r\\\\n\\\"))\",\n \"def append(self, val):\\n self._values.push(val)\",\n \"def write(self, data):\\n self.buffer.write(data)\\n self.offset += len(data)\",\n \"def chunk_written(self):\\n pass\",\n \"def put(self, item): \\n if len(self.contents) < self.max_size:\\n self.contents.append(item)\\n elif len(self.contents) >= self.max_size:\\n print \\\"Backpack Full.\\\"\",\n \"def add(self, item):\\r\\n if len(self.buff)==self.size: self.buff.pop(0)\\r\\n self.buff.append(item)\",\n \"def add_data(self, data):\\n self.data = self.data + data\",\n \"def _writeBytes(self, b):\\n self.stream.write(b)\\n self.stream.flush()\",\n \"def append(self, value) -> None:\\n key = getattr(value, self.keyattr)\\n if callable(key):\\n key = key()\\n if key not in self.data:\\n self.data[key] = []\\n self.data[key].append(value)\\n self.size += 1\",\n \"def push(self, value):\\n self.append(value)\\n return len(self) - 1\",\n \"def append(self, val):\\n self.val.append(val)\",\n \"def write(self, address: int, value: bytearray):\\n for i, val in enumerate(value):\\n self.mem[address+i] = value\",\n \"def add(self, value):\\n\\n # if the value implements the RivineBinaryObjectEncoderBase class,\\n # we ignore the underlying type and use the custom-defined logic\\n # as provided by the RivineBinaryObjectEncoder.\\n if isinstance(value, RivineBinaryObjectEncoderBase):\\n value.rivine_binary_encode(encoder=self)\\n return\\n\\n # try to rivbin-encode the value based on its python type\\n if isinstance(value, bool):\\n if value:\\n self._data += bytearray([1])\\n else:\\n self._data += bytearray([0])\\n elif isinstance(value, int):\\n self.add_int64(value)\\n else:\\n # try to rivbin-encode the value as a slice\\n try:\\n self.add_slice(value)\\n return\\n except TypeError:\\n pass\\n raise Exception(\\\"cannot rivbin-encode value with unsupported type {}\\\".format(type(value)))\",\n \"def write(self, chunk):\\n return self.tornado_request.write(chunk)\",\n \"def append(self, state):\\n self._buffer[:-1] = self._buffer[1:]\\n self._buffer[-1] = state\",\n \"def insert(self, val):\\n self.data.insert(0,val)\\n self.size = self.size + 1\",\n \"def insert(self, value):\\n current_timestamp = time.time()\\n self.timestamps.append(current_timestamp)\\n self.dataBuffer.append(value)\\n if (self.timestamps[0] < (current_timestamp - self.seconds_back)):\\n self.dataBuffer.pop(0)\\n self.timestamps.pop(0)\",\n \"def update_bytes_array(self):\\n self.bytes = data_manipulation.convert_from_binary_array(self.binary_array)\",\n \"def writeChunk(chunk):\",\n \"def write(self, data):\\n\\n # TODO - Check bytes vs unicode\\n data = _as_bytes(data)\\n # block_size = 2**16 = 65536\\n data_len = len(data)\\n if len(self._buffer) + data_len < 65536:\\n # print(\\\"Cached %r\\\" % data)\\n self._buffer += data\\n return\\n else:\\n # print(\\\"Got %r, writing out some data...\\\" % data)\\n self._buffer += data\\n while len(self._buffer) >= 65536:\\n self._write_block(self._buffer[:65536])\\n self._buffer = self._buffer[65536:]\",\n \"def add_value(self, val: float):\\n self._mtx.acquire()\\n self._buffer.append(val)\\n self._sum += val\\n\\n if self._cur_elem_count < self._frame_size:\\n self._cur_elem_count += 1\\n else:\\n self._sum -= self._buffer[0]\\n self._buffer.pop(0)\\n self._mtx.release()\",\n \"def Write(buf: IO[bytes], chunk: bytes) -> None:\\n buf.write(_UINT64.pack(len(chunk)))\\n buf.write(chunk)\",\n \"def enQueue(self, value):\\n if self.isFull():\\n return False\\n self.__buffer[(self.__start+self.__size) % len(self.__buffer)] = value\\n self.__size += 1\\n return True\",\n \"def extendMessage(self, message: bytearray) -> bytearray:\\n initLength: int = len(message)\\n appendLength: int = 16 - initLength % 16\\n message = message + \\\\\\n bytearray([appendLength for _ in range(appendLength)])\\n return message\",\n \"def push(self, value):\\n self.last = self.current\\n self.current = np.array(value)\",\n \"def write(self, b):\\n if isinstance(b, six.string_types):\\n b = bytearray(b, encoding='utf-8')\\n\\n logger.debug(\\\"writing %r bytes to %r\\\", len(b), self._buf)\\n\\n self._buf.write(b)\\n\\n if self._buf.tell() >= self._upload_chunk_size:\\n self._upload_next_part()\\n\\n return len(b)\",\n \"def __bytes__(self):\\n return bytes([self.type * 2, len(self.value)]) + bytes(self.value, 'utf-8')\",\n \"def __bytes__(self):\\n return bytes([self.type * 2, len(self.value)]) + bytes(self.value, 'utf-8')\",\n \"def __bytes__(self):\\n return bytes([self.type * 2, len(self.value)]) + bytes(self.value, 'utf-8')\",\n \"def add_int64(self, value):\\n self._check_int_type(value, _INT_8BYTE_UPPERLIMIT)\\n self._data += value.to_bytes(8, byteorder=\\\"little\\\")\",\n \"def append_chunk(cls, uuid, sequence_number, raw_data, compressed=False):\\n if compressed:\\n f = BytesIO()\\n z = zipfile.ZipFile(f, \\\"w\\\", zipfile.ZIP_DEFLATED)\\n z.writestr(\\\"data\\\", raw_data)\\n z.close()\\n data = f.getvalue()\\n f.close()\\n else:\\n data = raw_data\\n data_object = cls(\\n uuid=uuid, sequence_number=sequence_number, blob=data,\\n compressed=compressed\\n )\\n data_object.save()\\n return data_object\",\n \"def append(self, val):\\n self.new_dll.append(val)\",\n \"def write(self, b):\\n return self._write_at(b, self._offset)\",\n \"def push(self, value):\\n self.items.append(value)\",\n \"def write_value(self, value, length, error=True, move_start=True):\\n if not error and length > self.maxsize:\\n length = self.maxsize\\n\\n idxs = self.get_indexes(self._end, length, self.maxsize)\\n self.move_end(length, error, move_start)\\n self._data[idxs] = value\",\n \"def rawAppend(self, data):\\n self.message = self.message + data\",\n \"def update_binary_bytes(self):\\n self.binary_array = data_manipulation.convert_byte_array(self.bytes, self.binary_size)\",\n \"def append_buffer(self, buffer):\\n\\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\\n\\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\\n d1 = [b[0] for b in buffer.memory] # actions\\n d2 = [b[1][0] for b in buffer.memory] # speeds\\n d3 = [b[1][1] for b in buffer.memory] # lidar\\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes (terminated or truncated)\\n d5 = [b[2] for b in buffer.memory] # rewards\\n d6 = [b[5] for b in buffer.memory] # infos\\n d7 = [b[3] for b in buffer.memory] # terminated\\n d8 = [b[4] for b in buffer.memory] # truncated\\n\\n if self.__len__() > 0:\\n self.data[0] += d0\\n self.data[1] += d1\\n self.data[2] += d2\\n self.data[3] += d3\\n self.data[4] += d4\\n self.data[5] += d5\\n self.data[6] += d6\\n self.data[7] += d7\\n self.data[8] += d8\\n else:\\n self.data.append(d0)\\n self.data.append(d1)\\n self.data.append(d2)\\n self.data.append(d3)\\n self.data.append(d4)\\n self.data.append(d5)\\n self.data.append(d6)\\n self.data.append(d7)\\n self.data.append(d8)\\n\\n to_trim = self.__len__() - self.memory_size\\n if to_trim > 0:\\n self.data[0] = self.data[0][to_trim:]\\n self.data[1] = self.data[1][to_trim:]\\n self.data[2] = self.data[2][to_trim:]\\n self.data[3] = self.data[3][to_trim:]\\n self.data[4] = self.data[4][to_trim:]\\n self.data[5] = self.data[5][to_trim:]\\n self.data[6] = self.data[6][to_trim:]\\n self.data[7] = self.data[7][to_trim:]\\n self.data[8] = self.data[8][to_trim:]\\n\\n return self\",\n \"def add_int8(self, value):\\n self._check_int_type(value, _INT_1BYTE_UPPERLIMIT)\\n self._data += value.to_bytes(1, byteorder=\\\"little\\\")\",\n \"def _got_remote(self, data):\\n self._recv_buffer += data\",\n \"def append_buffer(self, buffer):\\n\\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\\n\\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\\n d1 = [b[0] for b in buffer.memory] # actions\\n d2 = [b[1][0] for b in buffer.memory] # speeds\\n d3 = [b[1][2] for b in buffer.memory] # lidar\\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\\n d5 = [b[2] for b in buffer.memory] # rewards\\n d6 = [b[5] for b in buffer.memory] # infos\\n d7 = [b[1][1] for b in buffer.memory] # progress\\n d8 = [b[3] for b in buffer.memory] # terminated\\n d9 = [b[4] for b in buffer.memory] # truncated\\n\\n if self.__len__() > 0:\\n self.data[0] += d0\\n self.data[1] += d1\\n self.data[2] += d2\\n self.data[3] += d3\\n self.data[4] += d4\\n self.data[5] += d5\\n self.data[6] += d6\\n self.data[7] += d7\\n self.data[8] += d8\\n self.data[9] += d9\\n else:\\n self.data.append(d0)\\n self.data.append(d1)\\n self.data.append(d2)\\n self.data.append(d3)\\n self.data.append(d4)\\n self.data.append(d5)\\n self.data.append(d6)\\n self.data.append(d7)\\n self.data.append(d8)\\n self.data.append(d9)\\n\\n to_trim = self.__len__() - self.memory_size\\n if to_trim > 0:\\n self.data[0] = self.data[0][to_trim:]\\n self.data[1] = self.data[1][to_trim:]\\n self.data[2] = self.data[2][to_trim:]\\n self.data[3] = self.data[3][to_trim:]\\n self.data[4] = self.data[4][to_trim:]\\n self.data[5] = self.data[5][to_trim:]\\n self.data[6] = self.data[6][to_trim:]\\n self.data[7] = self.data[7][to_trim:]\\n self.data[8] = self.data[8][to_trim:]\\n self.data[9] = self.data[9][to_trim:]\\n\\n return self\",\n \"def insertLast(self, value):\\n if not self.isFull():\\n self._data.append(value)\\n return True\\n else:\\n return False\",\n \"def _append_value(self, stream, value):\\n if FLAGS.timestamp:\\n x_val = float(time.time())\\n stream['x'].append(x_val)\\n\\n y_val = float(value)\\n stream['y'].append(y_val)\",\n \"def add(self, value):\\n ind = self._ind % self.shape[0]\\n self._values[ind] = value\\n self._ind += 1\\n self._cached = False\",\n \"def readinto(self, b):\\n read_resp = self._read_range(self._offset, self._offset + len(b))\\n bytes_read = len(read_resp)\\n b[:bytes_read] = read_resp\\n return bytes_read\",\n \"def _add_to_buffer(self, data):\\n for byte in data:\\n self.next_fn(byte) \\n self._parse_cmds()\",\n \"def put_byte(self, *args) -> \\\"int\\\":\\n return _ida_fpro.qfile_t_put_byte(self, *args)\",\n \"def appendleft(self, val):\\n self.new_dll.push(val)\",\n \"def upload_add_progress(self, nbytes):\\n\\n self.send_cur_nbytes += nbytes\\n if self.send_goal_nbytes != 0:\\n self.republish_output()\",\n \"def insert_bytes(self, bytes_to_write, location=None, overwrite=False):\\n num_bytes = len(bytes_to_write)\\n\\n off = self._offset\\n if location is not None:\\n off = location\\n if overwrite:\\n self._tiff[off:off + num_bytes] = bytes_to_write\\n else:\\n self._tiff = np.insert(self._tiff, off, bytes_to_write)\\n if location is None:\\n self._offset += num_bytes\\n\\n return num_bytes\",\n \"def data(self, data):\\n try:\\n self.put_nowait(data)\\n except Full:\\n pass\",\n \"def append_end(self, data):\\r\\n with open(self.file_name, 'a', encoding='utf-8') as self.file:\\r\\n self.file.write(data)\",\n \"def setByteArray(self, name: unicode, value: List[int]) -> None:\\n ...\",\n \"def push(self, value):\\n self.h.append(value)\\n self.d[value] = len(self.h) - 1\\n self.float_up(len(self.h) - 1)\",\n \"def push(self, value):\\n self.h.append(value)\\n self.d[value] = len(self.h) - 1\\n self.float_up(len(self.h) - 1)\",\n \"def push(self, value):\\n self.container.append(value)\",\n \"def write(self, buf: bytes, /) -> int:\",\n \"def write(self, buf: bytes, /) -> int:\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6965538","0.6886509","0.6466157","0.6369547","0.63468874","0.63018787","0.61934674","0.6191349","0.61861724","0.6181847","0.6159716","0.61312646","0.6124018","0.6061957","0.5985089","0.5908056","0.5903064","0.58985186","0.58978224","0.58650523","0.5863178","0.5863178","0.58599204","0.58598626","0.58490795","0.57119334","0.57000643","0.5685204","0.56743896","0.5636649","0.5625167","0.56077445","0.56010216","0.559543","0.55889773","0.55889773","0.5576904","0.55720484","0.55538756","0.5546728","0.5542534","0.5541641","0.55314356","0.55255944","0.5522979","0.54763556","0.5465038","0.5461633","0.54582703","0.5446412","0.54381144","0.543184","0.5430684","0.5429327","0.54229915","0.54206556","0.5420529","0.54154986","0.53976834","0.53794444","0.5370564","0.5364529","0.535107","0.5342262","0.53367776","0.53247416","0.53209996","0.53172934","0.5301213","0.5301213","0.5301213","0.52867943","0.5277975","0.52738184","0.52701765","0.5262697","0.5260553","0.52584594","0.52550966","0.5252595","0.5251485","0.52400744","0.5236437","0.5230579","0.5225479","0.5219692","0.5216265","0.5212698","0.52082866","0.5208264","0.520067","0.51989144","0.5190094","0.51892114","0.51815826","0.51798016","0.51798016","0.51700723","0.5167004","0.5167004"],"string":"[\n \"0.6965538\",\n \"0.6886509\",\n \"0.6466157\",\n \"0.6369547\",\n \"0.63468874\",\n \"0.63018787\",\n \"0.61934674\",\n \"0.6191349\",\n \"0.61861724\",\n \"0.6181847\",\n \"0.6159716\",\n \"0.61312646\",\n \"0.6124018\",\n \"0.6061957\",\n \"0.5985089\",\n \"0.5908056\",\n \"0.5903064\",\n \"0.58985186\",\n \"0.58978224\",\n \"0.58650523\",\n \"0.5863178\",\n \"0.5863178\",\n \"0.58599204\",\n \"0.58598626\",\n \"0.58490795\",\n \"0.57119334\",\n \"0.57000643\",\n \"0.5685204\",\n \"0.56743896\",\n \"0.5636649\",\n \"0.5625167\",\n \"0.56077445\",\n \"0.56010216\",\n \"0.559543\",\n \"0.55889773\",\n \"0.55889773\",\n \"0.5576904\",\n \"0.55720484\",\n \"0.55538756\",\n \"0.5546728\",\n \"0.5542534\",\n \"0.5541641\",\n \"0.55314356\",\n \"0.55255944\",\n \"0.5522979\",\n \"0.54763556\",\n \"0.5465038\",\n \"0.5461633\",\n \"0.54582703\",\n \"0.5446412\",\n \"0.54381144\",\n \"0.543184\",\n \"0.5430684\",\n \"0.5429327\",\n \"0.54229915\",\n \"0.54206556\",\n \"0.5420529\",\n \"0.54154986\",\n \"0.53976834\",\n \"0.53794444\",\n \"0.5370564\",\n \"0.5364529\",\n \"0.535107\",\n \"0.5342262\",\n \"0.53367776\",\n \"0.53247416\",\n \"0.53209996\",\n \"0.53172934\",\n \"0.5301213\",\n \"0.5301213\",\n \"0.5301213\",\n \"0.52867943\",\n \"0.5277975\",\n \"0.52738184\",\n \"0.52701765\",\n \"0.5262697\",\n \"0.5260553\",\n \"0.52584594\",\n \"0.52550966\",\n \"0.5252595\",\n \"0.5251485\",\n \"0.52400744\",\n \"0.5236437\",\n \"0.5230579\",\n \"0.5225479\",\n \"0.5219692\",\n \"0.5216265\",\n \"0.5212698\",\n \"0.52082866\",\n \"0.5208264\",\n \"0.520067\",\n \"0.51989144\",\n \"0.5190094\",\n \"0.51892114\",\n \"0.51815826\",\n \"0.51798016\",\n \"0.51798016\",\n \"0.51700723\",\n \"0.5167004\",\n \"0.5167004\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.63629705"},"document_rank":{"kind":"string","value":"4"}}},{"rowIdx":83494,"cells":{"query":{"kind":"string","value":"Convert the cells to a dictionary. This is intended to be used with HappyBase, so the column family and"},"document":{"kind":"string","value":"def to_dict(self):\n result = {}\n for column_family_id, columns in six.iteritems(self._cells):\n for column_qual, cells in six.iteritems(columns):\n key = (_to_bytes(column_family_id) + b':' +\n _to_bytes(column_qual))\n result[key] = cells\n return result"},"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 as_dict(self) -> Dict[str, Any]:\n return {\n column_title: cell.get_value()\n for column_title, cell in self.column_title_to_cell.items()\n }","def as_dict(self) -> Dict[str, Any]:\n return {\n column_title: cell.value\n for column_title, cell in self.column_title_to_cell.items()\n }","def _get_cell_map(row: TRowResult) -> Dict[bytes, TCell]:\n if row.sortedColumns is not None:\n return {c.columnName: c.cell for c in row.sortedColumns}\n elif row.columns is not None:\n return row.columns\n else: # pragma: no cover\n raise RuntimeError(\"Neither columns nor sortedColumns is available!\")","def as_dict(self) :\n\n return dict(zip(self.cols, self.data))","def to_python(self):\r\n mapping = {}\r\n for row in self.rows:\r\n mapping[row[0]] = _format_python_value(row[1])\r\n return mapping","def make_dict(row):\n return dict((key[0], value) for key, value in zip(colnames, row))","def excel_to_dict_from_xlsx(fn):\r\n data = pd.read_excel(fn, index_col=0)\r\n\r\n output_dict = dict()\r\n for ids, row in data.iterrows():\r\n output_dict[ids] = row.tolist()\r\n\r\n return output_dict","def dictionary(self):\n data = {}\n for i, col in enumerate(self.columns):\n key = col.get_display_tag(sort_attributes=True)\n if key and (not key in data) and (i < len(self.values)):\n data[key] = self.values[i]\n return data","def parse_worksheet_into_dictionary(self, ws, headers):\n self.is_not_used()\n result = {}\n\n try:\n for x in range(2, ws.max_row + 1): # enumerate rows\n data = {}\n pkey = ws.cell(row=x, column=1).value\n for key, value in headers.items():\n buffer = self.get_cell_details(ws, pkey, key)\n if buffer['cell_found']:\n value = {'value': buffer['value'], 'row': buffer['row'], 'col': buffer['col']}\n data[key] = value\n result[pkey] = data\n\n except Exception as e:\n self.error(str(e))\n\n return result","def get_column_dict(self) -> HeaderToWells:\n return self._grid.columns","def table_to_dict(self, tab):\n dict = {}\n for colname in tab.colnames:\n dict[colname] = tab[colname].data\n return dict","def _read_cell_direct(cls):\n\n cell_data = {}\n cell_columns = cls._get_columns(CELL_MANIFEST)\n cell_psvs = cls._get_component_psvs(CELL_MANIFEST)\n\n for cell_psv in cell_psvs:\n for row in gzip.GzipFile(fileobj=io.BytesIO(cls._read_s3_url(cell_psv))):\n row_dict = dict(zip(cell_columns, row.strip().split(b'|')))\n cell_data[row_dict[\"cellkey\"].decode()] = {k: v.decode() for\n k, v in row_dict.items()}\n total_umis = cell_data[row_dict[\"cellkey\"].decode()][\"total_umis\"]\n cell_data[row_dict[\"cellkey\"].decode()][\"total_umis\"] = (total_umis if total_umis == \"nan\"\n else str(float(total_umis)))\n\n return cell_data","def sv_to_dict(sv_data, cell_delimiter=\"\\t\"):\n result = {}\n rows = [row.split(cell_delimiter) for row in sv_data.splitlines()]\n\n if rows:\n header = rows.pop(0)\n header_len = len(header)\n\n for idx, header_col in enumerate(header):\n result[header_col] = []\n\n for row in rows:\n # Makes sure all rows size equals header's size\n if len(row) < header_len:\n [row.append(\"\") for x in range(0, (header_len - len(row)))]\n\n row_val = int(row[idx]) if row[idx].isdigit() else row[idx]\n result[header_col].append(row_val)\n\n return result","def convert_to_dict(df):\n df = df[['ISO3166A2',\n 'ISOen_ro_name',\n 'minlongitude',\n 'maxlongitude',\n 'minlatitude',\n 'maxlatitude',\n 'land_total',\n ]]\n df.ISOen_ro_name = df.ISOen_ro_name.str.strip()\n df.set_index('ISOen_ro_name', inplace=True)\n df.columns = ['country_tag',\n 'min_lon',\n 'max_lon',\n 'min_lat',\n 'max_lat',\n 'area',\n ]\n df.loc[:, \"country_tag\"] = df.loc[:, \"country_tag\"].str.lower()\n return {i[0]: i[1].to_dict() for i in df.iterrows()}","def to_dict(self):\n columns = self.__mapper__.column_attrs.keys()\n result = {}\n for column in columns:\n result[column] = getattr(self, column)\n return result","def to_dict(self):\n columns = self.__mapper__.column_attrs.keys()\n result = {}\n for column in columns:\n result[column] = getattr(self, column)\n return result","def to_dict(self):\n columns = self.__mapper__.column_attrs.keys()\n result = {}\n for column in columns:\n result[column] = getattr(self, column)\n return result","def to_dict(self):\n columns = self.__mapper__.column_attrs.keys()\n result = {}\n for column in columns:\n result[column] = getattr(self, column)\n return result","def to_dict(self):\n columns = self.__mapper__.column_attrs.keys()\n result = {}\n for column in columns:\n result[column] = getattr(self, column)\n return result","def gen_dict():\n lines = [line for line in csv.reader(open(__ppath__ + \"/data/occupations.csv\"))] # uses a csv.reader to parse the file, converts the generic iterable to a list\n lines = [(line[0],float(line[1])) for line in lines[1:-2]]# removes the column names and \"Total\" row, re-expresses as a list of tuples to enable dictionary conversion\n lines.append((\"Unemployed\",0.2)) # accounts for missing 0.2% of jobs\n return dict(lines) # converts to dictionary","def tsvRowToDict(row):\n return {col: getattr(row, col) for col in row._columns_}","def as_dict(self):\r\n values = {}\r\n for name, col in self._columns.items():\r\n values[name] = col.to_database(getattr(self, name, None))\r\n return values","def df_to_dict(df, key_column, val_column):\n xkey = df[key_column].tolist()\n xval = df[val_column].tolist()\n return dict(zip(xkey,xval))","def as_dict(self):\n return {c.name: getattr(self, c.name) for c in self.__table__.columns}","def as_dict(self):\n return {c.name: getattr(self, c.name) for c in self.__table__.columns}","def as_dict(self):\n return {c.name: getattr(self, c.name) for c in self.__table__.columns}","def as_dict(self):\n return {c.name: getattr(self, c.name) for c in self.__table__.columns}","def value(self):\n if not hasattr(self, \"table\"):\n return {}\n return {\n \"rowlabels\": self.row_labels,\n \"collabels\": self.col_labels,\n \"rows\": self.rows,\n \"cols\": self.cols,\n \"rowname\": self.rowname,\n \"colname\": self.colname,\n \"naxis\": self.naxis,\n \"table\": self.table\n }","def grid_values(self, grid):\n chars = [col for col in grid if col in self.digits or col in '0.']\n assert len(chars) == 81\n return dict(zip(self.squares, chars))","def _df_to_cellchat_format(self, df_to_convert) -> dict:\n interactions_dataframes = {}\n\n for _, row in df_to_convert.iterrows():\n df = pd.DataFrame(index=self.cell_types, columns=self.cell_types)\n\n for cell_type_i in self.cell_types:\n for cell_type_j in self.cell_types:\n interaction_name = f\"{cell_type_i}|{cell_type_j}\"\n df.loc[cell_type_i, cell_type_j] = row[interaction_name]\n\n interactions_dataframes[row.interacting_pair] = df\n\n return interactions_dataframes","def chunk_to_dict(chunk):\n csv_cols = chunk.keys()\n return [dict(zip(csv_cols, v)) for v in chunk.values]","def as_dict(self):\n\n return {c.name: getattr(self, c.name) for c in self.__table__.columns}","def _get_columns_mapping_dict():\n\n columns_mapping_dict = {}\n for original_header in COLUMN_HEADERS_MAPPER:\n new_header = COLUMN_HEADERS_MAPPER[original_header]\n columns_mapping_dict[new_header] = [original_header]\n return columns_mapping_dict","def to_dict(self) -> 'collections.OrderedDict[str, tuple]':\n\n columns = [(column.typed_column, column.values)\n for column in self.plaincolumns]\n\n return collections.OrderedDict(columns)","def df2dict(df):\n attr_list = list(df.columns)\n res_dict = {}\n for attr in attr_list:\n res_dict[attr.lower()] = list(df[attr])\n\n return res_dict","def row_to_byte_dict(row: bigtable.row.Row, f_id: str = None, idx: int = None\n ) -> Dict[int, Dict]:\n row_dict = {}\n\n for fam_id in row.cells.keys():\n row_dict[fam_id] = {}\n\n for row_k in row.cells[fam_id].keys():\n if idx is None:\n row_dict[fam_id][deserialize_key(row_k)] = \\\n [c.value for c in row.cells[fam_id][row_k]]\n else:\n row_dict[fam_id][deserialize_key(row_k)] = \\\n row.cells[fam_id][row_k][idx].value\n\n if f_id is not None and f_id in row_dict:\n return row_dict[f_id]\n elif f_id is None:\n return row_dict\n else:\n raise Exception(\"Family id not found\")","def rows_coldict(self) -> List[Dict]:\n return self._rows_coldict","def as_dict(self):\n return {\n column.name: getattr(self, column.name)\n for column in self.__table__.columns\n }","def table_row_to_dict(row, make_quantity=True):\n data = {}\n for name, col in row.columns.items():\n val = row[name]\n\n if make_quantity and col.unit:\n val = Quantity(val, unit=col.unit)\n data[name] = val\n return data","def dict_factory(self, cursor, row):\n results = {}\n for index, col_name in enumerate(cursor.description):\n results[col_name[0]] = row[index]\n\n return results","def get_row_dict(self) -> HeaderToWells:\n return self._grid.rows","def _convert_table_to_dict(self, data_table):\n column_names = ['star_name', 'distance', 'brightness', 'luminosity']\n stars = {}\n for line in data_table:\n stars[line[0]] = {column_names[i] : line[i] for i in range(1, len(column_names))}\n return stars","def to_backgrid_dict(self):\n # shorten global import times by importing django here\n import numpy as np\n from mpcontribs.io.core.utils import get_composition_from_string\n from pandas import MultiIndex\n import pymatgen.util as pmg_util\n from pymatgen.core.composition import CompositionError\n\n table = dict()\n nrows_max = 260\n nrows = self.shape[0]\n df = Table(self.head(n=nrows_max)) if nrows > nrows_max else self\n numeric_columns = df.select_dtypes(include=[np.number]).columns.tolist()\n\n if isinstance(df.index, MultiIndex):\n df.reset_index(inplace=True)\n\n table['columns'] = []\n table['rows'] = super(Table, df).to_dict(orient='records')\n\n for col_index, col in enumerate(list(df.columns)):\n cell_type = 'number'\n\n # avoid looping rows to minimize use of `df.iat` (time-consuming in 3d)\n if not col.startswith('level_') and col not in numeric_columns:\n is_url_column, prev_unit, old_col = True, None, col\n\n for row_index in range(df.shape[0]):\n cell = str(df.iat[row_index, col_index])\n cell_split = cell.split(' ', 1)\n\n if not cell or len(cell_split) == 1: # empty cell or no space\n is_url_column = bool(is_url_column and (not cell or mp_id_pattern.match(cell)))\n if is_url_column:\n if cell:\n value = 'https://materialsproject.org/materials/{}'.format(cell)\n table['rows'][row_index][col] = value\n elif cell:\n try:\n composition = get_composition_from_string(cell)\n composition = pmg_util.string.unicodeify(composition)\n table['rows'][row_index][col] = composition\n except (CompositionError, ValueError, OverflowError):\n try:\n # https://stackoverflow.com/a/38020041\n result = urlparse(cell)\n if not all([result.scheme, result.netloc, result.path]):\n break\n is_url_column = True\n except:\n break\n\n else:\n value, unit = cell_split # TODO convert cell_split[0] to float?\n is_url_column = False\n try:\n float(value) # unit is only a unit if value is number\n except ValueError:\n continue\n table['rows'][row_index].pop(old_col)\n if prev_unit is None:\n prev_unit = unit\n col = '{} [{}]'.format(col, unit)\n table['rows'][row_index][col] = cell if prev_unit != unit else value\n\n cell_type = 'uri' if is_url_column else 'string'\n\n col_split = col.split('##')\n nesting = [col_split[0]] if len(col_split) > 1 else []\n table['columns'].append({\n 'name': col, 'cell': cell_type, 'nesting': nesting, 'editable': 0\n })\n if len(col_split) > 1:\n table['columns'][-1].update({'label': '##'.join(col_split[1:])})\n if len(table['columns']) > 12:\n table['columns'][-1]['renderable'] = 0\n\n header = RecursiveDict()\n for idx, col in enumerate(table['columns']):\n if 'label' in col:\n k, sk = col['name'].split('##')\n sk_split = sk.split()\n if len(sk_split) == 2:\n d = {'name': sk_split[0], 'unit': sk_split[1], 'idx': idx}\n if k not in header:\n header[k] = [d]\n else:\n header[k].append(d)\n elif k in header:\n header.pop(k)\n\n for k, skl in header.items():\n units = [sk['unit'] for sk in skl]\n if units.count(units[0]) == len(units):\n for sk in skl:\n table['columns'][sk['idx']]['label'] = sk['name']\n table['columns'][sk['idx']]['nesting'][0] = '{} {}'.format(k, sk['unit'])\n\n return table","def _dictify(cols, vals):\n assert (len(cols) == len(vals)), 'Columns and values must be the same length to map to dictionary'\n return {col: vals[i] for i, col in enumerate(cols)}","def to_dict(self):\r\n return {\r\n \"Row_ID\": self.row_id,\r\n \"Question\": self.question,\r\n \"answer1\": self.answer1,\r\n \"answer2\": self.answer2,\r\n \"answer3\": self.answer3,\r\n \"answer4\": self.answer4,\r\n \"answer5\": self.answer5,\r\n \"Right Answers\": self.right_answers,\r\n \"Hitpoints\": self.firsts\r\n }","def toDict(self):\n\n aDict = {}\n\n # Required Keys\n try:\n aDict[self.E0_KEY] = self.e0.toDict()\n aDict[self.E1_KEY] = self.e1.toDict()\n aDict[self.E2_KEY] = self.e2.toDict()\n aDict[self.MAXIMUM_HORIZONTAL_KEY] = self.maximumHorizontalProjection\n aDict[self.MAXIMUM_VERTICAL_KEY] = self.maximumVerticalProjection\n aDict[self.EQUIVALENT_HORIZONTAL_KEY] = self.equivalentHorizontalRadius\n\n except (NameError, AttributeError) as e:\n print(\"Missing required data error: %s\" % e)\n\n return aDict","def parse(self):\n mp = {}\n cells = self.row.find_all(\"td\")\n\n for cell in cells:\n if \"visible-mobile\" in cell.attrs[\"class\"]:\n continue\n title = self._get_cell_title(cell)\n content = cell.find(\"span\", class_=\"table-responsive__inner\")\n\n if title == \"name\":\n mp.update(self._parse_name(cell, content))\n elif title == \"fraktion\":\n fraktion, klub = self._parse_abbreviation(content)\n mp[\"political_affiliation\"] = klub + \" (\" + fraktion + \")\"\n elif title == \"wahlkreis\":\n mp[\"wahlkreis\"] = content.text.strip()\n elif title == \"bundesland\":\n mp[\"state\"] = self._parse_abbreviation(content)[1]\n\n return mp","def as_dict(self):\n return {c.key: getattr(self, c.key)\n for c in inspect(self).mapper.column_attrs}","def dict_factory(cursor, row):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row[idx]\n return d","def parseSheet(self):\n self.log.info(\"Parsing {0} rows and {1} columns.\".format(self.rowns,self.colns))\n \n self.column_dimensions = {}\n self.property_dimensions = {}\n self.row_dimensions = {}\n self.rowhierarchy = {}\n\n # Get dictionary of annotations\n self.annotations = self.r_sheet.cell_note_map\n \n for i in range(0,self.rowns):\n self.rowhierarchy[i] = {}\n \n for j in range(0, self.colns):\n # Parse cell data\n self.source_cell = self.r_sheet.cell(i,j)\n self.source_cell_name = cellname(i,j)\n self.style = self.styles[self.source_cell].name\n self.cellType = self.getType(self.style)\n self.source_cell_qname = self.getQName(self.source_cell_name)\n \n self.log.debug(\"({},{}) {}/{}: \\\"{}\\\"\". format(i,j,self.cellType, self.source_cell_name, self.source_cell.value))\n\n # Try to parse ints to avoid ugly _0 URIs\n try:\n if int(self.source_cell.value) == self.source_cell.value:\n self.source_cell.value = int(self.source_cell.value)\n except ValueError:\n self.log.debug(\"(%s.%s) No parseable int\" % (i,j))\n\n \n # Parse annotation (if any)\n if self.config.get('annotations', 'enabled') == \"1\":\n if (i,j) in self.annotations:\n self.parseAnnotation(i, j)\n\n # Parse cell even if empty\n if self.cellType == 'Data':\n self.parseData(i, j)\n elif (self.cellType == 'HRowHeader') :\n self.updateRowHierarchy(i, j)\n elif self.cellType == 'ColHeader' :\n self.parseColHeader(i, j)\n elif self.cellType == 'RowProperty' :\n self.parseRowProperty(i, j)\n \n # If cell not empty, check for more types\n if not self.isEmpty(i,j) :\n #self.graph.add((self.namespaces['scope'][self.source_cell_qname],RDF.type,self.namespaces['tablink'][self.cellType]))\n #self.graph.add((self.namespaces['scope'][self.source_cell_qname],self.namespaces['tablink']['cell'],Literal(self.source_cell_name)))\n #self.graph.add((self.namespaces['scope'][self.source_cell_qname],self.namespaces['tablink']['col'],Literal(colname(j))))\n #self.graph.add((self.namespaces['scope'][self.source_cell_qname],self.namespaces['tablink']['row'],Literal(i+1)))\n #self.graph.add((self.namespaces['scope'][self.source_cell_qname] isrow row\n if self.cellType == 'Title' :\n self.parseTitle(i, j)\n \n elif self.cellType == 'RowHeader' :\n self.parseRowHeader(i, j)\n \n elif self.cellType == 'HRowHeader' :\n self.parseHierarchicalRowHeader(i, j)\n \n elif self.cellType == 'RowLabel' :\n self.parseRowLabel(i, j)\n \n # Add additional information about the hierarchy of column headers\n for value in self.column_dimensions.values():\n for index in range(1, len(value)):\n uri_sub = self.getColHeaderValueURI(value[:index+1])\n uri_top = self.getColHeaderValueURI(value[:index])\n self.graph.add((uri_sub, self.namespaces['tablink']['subColHeaderOf'], uri_top))\n self.graph.add((uri_sub, self.namespaces['tablink']['depth'], Literal(index)))\n self.graph.add((uri_top, self.namespaces['tablink']['depth'], Literal(index-1)))\n \n self.log.info(\"Done parsing...\")","def dict_factory(cursor, row):\n rowdict = {}\n for idx, col in enumerate(cursor.description):\n rowdict[col[0]] = row[idx]\n return rowdict","def map_row_to_dict(cursor: sqlite3.Cursor, row_data):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row_data[idx]\n return d","def PostgresTableToDict(sqldef, conn):\n df = pd.read_sql(sqldef, con=conn)\n return dict(zip(df.iloc[:, 0], df.iloc[:, 1]))","def get_dict(\n self,\n col = '',\n row = '',\n entry = '',\n ):\n \n if row and not col:\n try:\n return self._cache[row,entry]\n except:\n pass\n\n if row not in self.rows:\n print(\"[!] The row you selected is not available!\")\n else:\n data = self._dict[row]\n if not entry:\n entries = data\n else:\n entries = {}\n idx = self._header[entry]\n\n for key,value in data.items():\n entries[key] = [self[i][idx] for i in value]\n \n self._cache[row,entry] = entries\n return entries\n\n if col and not row:\n try:\n return self._cache[col,entry]\n except:\n pass\n\n if col not in self.cols:\n print(\"[!] The column you selected is not available!\")\n else:\n data = {}\n for i,j in [(self[i][self._rowIdx],i) for \n i in self._array[:,self.cols.index(col)] if i != 0]:\n try:\n data[i] += [j]\n except:\n data[i] = [j]\n\n if not entry:\n entries = data\n else:\n entries = {}\n idx = self._header[entry]\n\n for key,value in data.items():\n entries[key] = [self[i][idx] for i in value]\n \n self._cache[col,entry] = entries\n \n return entries\n \n elif row and col:\n print(\"[!] You should specify only a value for row or for col!\")\n else:\n print(\"[!] Neither rows nor columns are selected!\")","def to_obj(self, entity):\n return {k: conv(getattr(entity, k, None)) for k, conv in self.cols_to_obj.items()}","def _as_dict(self):\r\n values = self._dynamic_columns or {}\r\n for name, col in self._columns.items():\r\n values[name] = col.to_database(getattr(self, name, None))\r\n return values","def make_to_dict(item, include_timestamp):\n return {\n '%s:%s' % (cell.family, cell.qualifier): (cell.value, cell.timestamp) if include_timestamp else cell.value\n for cell in item\n }","def to_dictionary(self):\n dict_contents = [\"id\", \"size\", \"x\", \"y\"]\n new_dict = {}\n for key in dict_contents:\n new_dict[key] = getattr(self, key)\n return new_dict","def DataFrame_to_dict(df):\n return df.to_dict(orient='records')","def dictify(df):\n return {str(k): v for k, v in df.items()}","def getInterventions():\n intFrame = xl.load_workbook(param.initial_interventions_filename, data_only=True).active\n\n interventionDict = dict()\n\n for row in intFrame['A{}:G{}'.format(intFrame.min_row + 1, intFrame.max_row)]:\n intervention = row[0].value\n data_list = list()\n\n data = row[1:len(row)]\n\n for cell in data:\n data_list.append(cell.value)\n\n interventionDict[intervention] = data_list\n\n return interventionDict","def make_dicts(cursor, row):\n return dict((cursor.description[idx][0], value)\n for idx, value in enumerate(row))","def make_dicts(cursor, row):\n return dict((cursor.description[idx][0], value)\n for idx, value in enumerate(row))","def to_dict(self) -> dict:","def csv_to_dict(self):\n log = logger.configure(\"default\")\n try: \n df = pd.read_csv(self.__csv_path)\n except IOError as e:\n # file not found\n log.error('Could not import {}. Got error {}'.format(self.__csv_path, e))\n raise \n else:\n cols = list(df.columns)\n metafield_cols = [col for col in cols if 'metafields' in col]\n if metafield_cols == [] or 'Handle' not in cols:\n # relevant columns don't exist\n log.error('{} does not contain `Handle` or `metafields` named columns'.format(self.__csv_path))\n raise\n else:\n new_cols = ['Handle'] + metafield_cols\n df = df[new_cols].set_index('Handle')\n df = df[~df.index.duplicated(keep='first')]\n return df.to_dict('index')","def df_to_dict(df):\n return df.to_dict('index')","def compile_as_dict(self, data):\r\n fut = {}\r\n index = self.primary_key.index\r\n for i in data:\r\n popped = i.pop(index)\r\n head = self.table_headers.copy()\r\n head.pop(index)\r\n s = {}\r\n for j in range(len(head)):\r\n s[j] = i[j]\r\n fut[popped] = s\r\n return fut","def to_dictionary(self):\n dic = {}\n ls = ['id', 'size', 'x', 'y']\n for i in ls:\n dic[i] = getattr(self, i)\n return dic","def to_dict(self) -> Dict[str, Any]:\n fields = [\n k\n for row in self.field_values\n for k, _ in row.statuses.items()\n if k != DUMMY_ENTITY_ID\n ]\n features_dict: Dict[str, List[Any]] = {k: list() for k in fields}\n\n for row in self.field_values:\n for feature in features_dict.keys():\n native_type_value = feast_value_type_to_python_type(row.fields[feature])\n features_dict[feature].append(native_type_value)\n\n return features_dict","def _row_to_dict(row, fields):\n dict_row = {}\n for i, value in enumerate(row):\n key = fields[i]\n if value and str(value).lower() == 'nan':\n value = None\n dict_row[key] = value\n return dict_row","def to_proto_dict(self, v2_proto=False) -> Dict:\n # TODO: Deprecate v1 proto method.\n return {\n 'row': self.row,\n 'col': self.col,\n }","def dict_factory(cursor, row):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row[idx]\n return d","def dict_factory(cursor, row):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row[idx]\n return d","def dict_factory(cursor, row):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row[idx]\n return d","def __get_column_mapping(self):\n\n s1 = list(Sample(\"FL\", \"M1.0@265_Primary_ar115_s2010-08-06T06_36_00_e2010-08-06T18_24_00.csv\").get_data().columns)[:25]\n column_mapping = {}\n for i in range(len(s1)):\n column_mapping[i] = s1[i]\n\n return column_mapping","def dict(self) -> Dict[str, List[NumericType]]:\n return {r.name: r.floats() for r in self._records}","def to_entries(col):\n sheet = col.sheet\n rows = sheet.rows\n\n new_idx = sheet.columns.index(col) + 1\n new_col = SettableColumn(col.name)\n sheet.addColumn(new_col, index=new_idx)\n isNull = _isNullFunc()\n for r in rows:\n val = col.getValue(r)\n if isNull(val):\n continue\n if not isinstance(val, dict):\n sheet.columns.pop(new_idx)\n vd.fail('Column \"{}\" is not a dict'.format(col.name))\n new_col.setValue(r, [{\"Key\": k, \"Value\": v} for k, v in val.items()])\n col.hide()\n return new_col","def to_dict(df):\n\t# Extract the names\n\tnames = list(df.columns.values)\n\t# Create sequence\n\tdf_list = []\n\t#Iterate over rows of data frame\n\tfor index, row in df.iterrows():\n\t\t# Create temporary object\n\t\ttemp_dict = {}\n\t\t#Iterate over key names and add values\n\t\tfor name in names:\n\t\t\ttemp_dict[name] = row[name]\n\t\t# Append object to dictionary\n\t\tdf_list.append(temp_dict.copy())\n\t\n\treturn df_list","def columnar(row_table: list[dict[str, str]]) -> dict[str, list[str]]:\n result: dict[str, list[str]] = {}\n \n first_row: dict[str, str] = row_table[0]\n for column in first_row:\n result[column] = column_values(row_table, column)\n \n return result","def _deduct_types(cls, row: Row) -> ColumnTypes:\n return {\n key: get_value_type(cls.whole_number_to_int(value))\n for key, value in row.items()\n }","def to_dict(self):","def to_dict(self):\n dictionary = {}\n for column in self.__table__.columns:\n attribute_field_name = self.__mapper__.get_property_by_column(column).key\n attribute = getattr(self, attribute_field_name)\n dictionary[attribute_field_name] = self._make_serializable(attribute)\n\n return dictionary","def object_as_dict(cls, obj):\n return {c.key: getattr(obj, c.key) for c in inspect(obj).mapper.column_attrs}","def to_dict(self):\n\n out = dict()\n out['imsi'] = self.imsi\n out['tmsi'] = self.tmsi\n out['rnti'] = self.rnti\n out['cell'] = self.cell\n out['plmnid'] = self.plmnid\n out['status'] = USER_STATUS[self.status]\n out['ue_measurements'] = self.ue_measurements\n return out","def _dict(content):\n response = _data_frame(content).to_dict(orient='records')\n return response","def dict_factory(cursor, row):\r\n\td = {}\r\n\tfor idx, col in enumerate(cursor.description):\r\n\t\td[col[0]] = row[idx]\r\n\treturn d","def as_dict(self):\n if self._feat_matrix is not None:\n feature_matrix = self._feat_matrix.tolist()\n else:\n feature_matrix = self._feat_matrix\n if self.regression_data is not None:\n reg_data = jsanitize(asdict(self.regression_data))\n else:\n reg_data = None\n\n ce_d = {\n \"@module\": self.__class__.__module__,\n \"@class\": self.__class__.__name__,\n \"cluster_subspace\": self.cluster_subspace.as_dict(),\n \"coefs\": self.coefs.tolist(),\n \"regression_data\": reg_data,\n \"feature_matrix\": feature_matrix,\n }\n return ce_d","def to_dict(self, *columns_to_ignore):\n dict_ = {}\n for key in self.__mapper__.c.keys():\n if key in columns_to_ignore:\n continue\n dict_[key] = getattr(self, key)\n return dict_","def cell_map_from_database(self) -> None:\n for row in self.session.query(DatamapItem).all():\n self.cell_map.append(\n Cell(\n datamap_id=row.id,\n cell_key=row.key,\n cell_value=None,\n template_sheet=row.bicc_sheet,\n bg_colour=None,\n fg_colour=None,\n number_format=None,\n verification_list=None,\n cell_reference=row.bicc_cellref))","def vc_to_dict(column):\n vc = column.value_counts()\n vc.index = vc.index.astype(str)\n return vc.to_dict()","def to_dict(self):\n d = {}\n i = 0\n for entry in self.entries:\n d[i] = {}\n attributes = self.get_attribute_list()\n print (attributes)\n for data in attributes:\n d[i][data] = entry.__getattribute__(data)\n i = i + 1\n return d","def dict_factory(cursor, row):\n dic = {}\n for idx, col in enumerate(cursor.description):\n if isinstance(row[idx], unicode):\n dic[col[0]] = u.unicode_to_string(row[idx])\n else:\n dic[col[0]] = row[idx]\n return dic","def row_to_dict(keys):\n return lambda row: dict(izip(keys, row))","def convert_data(df):\n print(\"Converting history...\")\n return [ dict(row) for i, row in df.iterrows() ]","def dict_factory(cursor, row):\n fields = [column[0] for column in cursor.description]\n return {key: value for key, value in zip(fields, row)}","def get_new_cell(path: tuple(str, ...)) -> dict[str, Any]:\n return {\n \"path\": path,\n \"type\": \"cell\",\n # \"celltype\": \"structured\", # or \"text\" for help cells\n \"datatype\": \"mixed\",\n \"hash_pattern\": None,\n \"UNTRANSLATED\": True,\n }","def to_dict_index(df):\r\n return df.to_dict('index')","def to_dict(self):\r\n return {\r\n \"Row_ID\": self.row_id,\r\n \"Question\": self.question,\r\n \"Right Answer Seq\": self.right_answers,\r\n \"User Answer Seq\": self.user_answers,\r\n \"Score\": self.score,\r\n \"Time Needed\": self.time_track,\r\n \"Hitpoints\": self.firsts\r\n }","def createDictBase(self):\n #allFiles = glob.glob(self.path + \"/*\"+ self.filetype)\n #data = pd.read_excel(allFiles[0])\n#================================================================================================================== \n# self.list_files = self.Files_to_import()\n# data=pd.read_excel(self.path +'/'+self.list_files[0]) # importing the first excel sheet from the first/zero time point\n self.list_files = self.Files_to_import()\n try:\n tim = pd.read_excel(self.path +'/timePoints' + self.filetype) # importin the time points from a shhet called time_points\n time = np.array(tim['time']) # assigning variable time conataing an array with the timepoints\n self.nr_files = len(time)\n except:\n time = np.array(list(range(self.nr_files))) \n \n data=pd.read_excel(self.path +'/'+self.list_files[0])\n \n data=np.array(data) # converts it to array, so we can manipualte the data easier\n #python wants for some reason first to create the dictionary with at least on value before we can run it in a loop. THat is why we have litle redundancy, since the next part is allmost the same.\n for i in range(len(data)): # the numbers of rows. Goes through the rows\n for ii in range(len(data[i])): # the numbers of columns. For every row goes through the columns\n cell_id=str(i)+str(ii) # we create a variable that has a value cell_id= rowNUm colNUm, for example x= '34' means row 3 column 4\n dat=[] # a list that will contain the first value of the cell. It will be cleaned every time the loop runs the newxt value\n dat.append(data[i][ii]) # we put the value of the well to the list\n self.dbase[cell_id]=dat # the list is put to the table. For example dabse['cell_id']= some OD value \n \n # then we go through the rest of the excell time points and collect them\n for i in range(1,len(time)): \n if self.list_files[i] != 0:\n \n #data = pd.read_excel(allFiles[i])\n data=pd.read_excel(self.path +'/'+ self.list_files[i]) \n data=np.array(data)\n for i in range(len(data)): # the numbers of rows. Goes through the rows\n for ii in range(len(data[i])): # the numbers of columns. For every row goes through the columns\n cell_id=str(i)+str(ii) # we create a variable that has a value cell_id= rowNUm colNUm, for example x= '34' means row 3 column 4\n \n tempVar=self.dbase[cell_id] # here we use a method of exchanging variables to be able to uppdate the cloumn corresponding to the cell_id\n tempVar.append(data[i][ii]) # add the new data to the copy\n self.dbase[cell_id] = tempVar # uppdate the original dictionary\n else:\n pass\n self.dbase['time'] = time # at theend we add a column that takes care of the time_points \n return self.dbase","def _to_dict(self) -> dict:\n pass"],"string":"[\n \"def as_dict(self) -> Dict[str, Any]:\\n return {\\n column_title: cell.get_value()\\n for column_title, cell in self.column_title_to_cell.items()\\n }\",\n \"def as_dict(self) -> Dict[str, Any]:\\n return {\\n column_title: cell.value\\n for column_title, cell in self.column_title_to_cell.items()\\n }\",\n \"def _get_cell_map(row: TRowResult) -> Dict[bytes, TCell]:\\n if row.sortedColumns is not None:\\n return {c.columnName: c.cell for c in row.sortedColumns}\\n elif row.columns is not None:\\n return row.columns\\n else: # pragma: no cover\\n raise RuntimeError(\\\"Neither columns nor sortedColumns is available!\\\")\",\n \"def as_dict(self) :\\n\\n return dict(zip(self.cols, self.data))\",\n \"def to_python(self):\\r\\n mapping = {}\\r\\n for row in self.rows:\\r\\n mapping[row[0]] = _format_python_value(row[1])\\r\\n return mapping\",\n \"def make_dict(row):\\n return dict((key[0], value) for key, value in zip(colnames, row))\",\n \"def excel_to_dict_from_xlsx(fn):\\r\\n data = pd.read_excel(fn, index_col=0)\\r\\n\\r\\n output_dict = dict()\\r\\n for ids, row in data.iterrows():\\r\\n output_dict[ids] = row.tolist()\\r\\n\\r\\n return output_dict\",\n \"def dictionary(self):\\n data = {}\\n for i, col in enumerate(self.columns):\\n key = col.get_display_tag(sort_attributes=True)\\n if key and (not key in data) and (i < len(self.values)):\\n data[key] = self.values[i]\\n return data\",\n \"def parse_worksheet_into_dictionary(self, ws, headers):\\n self.is_not_used()\\n result = {}\\n\\n try:\\n for x in range(2, ws.max_row + 1): # enumerate rows\\n data = {}\\n pkey = ws.cell(row=x, column=1).value\\n for key, value in headers.items():\\n buffer = self.get_cell_details(ws, pkey, key)\\n if buffer['cell_found']:\\n value = {'value': buffer['value'], 'row': buffer['row'], 'col': buffer['col']}\\n data[key] = value\\n result[pkey] = data\\n\\n except Exception as e:\\n self.error(str(e))\\n\\n return result\",\n \"def get_column_dict(self) -> HeaderToWells:\\n return self._grid.columns\",\n \"def table_to_dict(self, tab):\\n dict = {}\\n for colname in tab.colnames:\\n dict[colname] = tab[colname].data\\n return dict\",\n \"def _read_cell_direct(cls):\\n\\n cell_data = {}\\n cell_columns = cls._get_columns(CELL_MANIFEST)\\n cell_psvs = cls._get_component_psvs(CELL_MANIFEST)\\n\\n for cell_psv in cell_psvs:\\n for row in gzip.GzipFile(fileobj=io.BytesIO(cls._read_s3_url(cell_psv))):\\n row_dict = dict(zip(cell_columns, row.strip().split(b'|')))\\n cell_data[row_dict[\\\"cellkey\\\"].decode()] = {k: v.decode() for\\n k, v in row_dict.items()}\\n total_umis = cell_data[row_dict[\\\"cellkey\\\"].decode()][\\\"total_umis\\\"]\\n cell_data[row_dict[\\\"cellkey\\\"].decode()][\\\"total_umis\\\"] = (total_umis if total_umis == \\\"nan\\\"\\n else str(float(total_umis)))\\n\\n return cell_data\",\n \"def sv_to_dict(sv_data, cell_delimiter=\\\"\\\\t\\\"):\\n result = {}\\n rows = [row.split(cell_delimiter) for row in sv_data.splitlines()]\\n\\n if rows:\\n header = rows.pop(0)\\n header_len = len(header)\\n\\n for idx, header_col in enumerate(header):\\n result[header_col] = []\\n\\n for row in rows:\\n # Makes sure all rows size equals header's size\\n if len(row) < header_len:\\n [row.append(\\\"\\\") for x in range(0, (header_len - len(row)))]\\n\\n row_val = int(row[idx]) if row[idx].isdigit() else row[idx]\\n result[header_col].append(row_val)\\n\\n return result\",\n \"def convert_to_dict(df):\\n df = df[['ISO3166A2',\\n 'ISOen_ro_name',\\n 'minlongitude',\\n 'maxlongitude',\\n 'minlatitude',\\n 'maxlatitude',\\n 'land_total',\\n ]]\\n df.ISOen_ro_name = df.ISOen_ro_name.str.strip()\\n df.set_index('ISOen_ro_name', inplace=True)\\n df.columns = ['country_tag',\\n 'min_lon',\\n 'max_lon',\\n 'min_lat',\\n 'max_lat',\\n 'area',\\n ]\\n df.loc[:, \\\"country_tag\\\"] = df.loc[:, \\\"country_tag\\\"].str.lower()\\n return {i[0]: i[1].to_dict() for i in df.iterrows()}\",\n \"def to_dict(self):\\n columns = self.__mapper__.column_attrs.keys()\\n result = {}\\n for column in columns:\\n result[column] = getattr(self, column)\\n return result\",\n \"def to_dict(self):\\n columns = self.__mapper__.column_attrs.keys()\\n result = {}\\n for column in columns:\\n result[column] = getattr(self, column)\\n return result\",\n \"def to_dict(self):\\n columns = self.__mapper__.column_attrs.keys()\\n result = {}\\n for column in columns:\\n result[column] = getattr(self, column)\\n return result\",\n \"def to_dict(self):\\n columns = self.__mapper__.column_attrs.keys()\\n result = {}\\n for column in columns:\\n result[column] = getattr(self, column)\\n return result\",\n \"def to_dict(self):\\n columns = self.__mapper__.column_attrs.keys()\\n result = {}\\n for column in columns:\\n result[column] = getattr(self, column)\\n return result\",\n \"def gen_dict():\\n lines = [line for line in csv.reader(open(__ppath__ + \\\"/data/occupations.csv\\\"))] # uses a csv.reader to parse the file, converts the generic iterable to a list\\n lines = [(line[0],float(line[1])) for line in lines[1:-2]]# removes the column names and \\\"Total\\\" row, re-expresses as a list of tuples to enable dictionary conversion\\n lines.append((\\\"Unemployed\\\",0.2)) # accounts for missing 0.2% of jobs\\n return dict(lines) # converts to dictionary\",\n \"def tsvRowToDict(row):\\n return {col: getattr(row, col) for col in row._columns_}\",\n \"def as_dict(self):\\r\\n values = {}\\r\\n for name, col in self._columns.items():\\r\\n values[name] = col.to_database(getattr(self, name, None))\\r\\n return values\",\n \"def df_to_dict(df, key_column, val_column):\\n xkey = df[key_column].tolist()\\n xval = df[val_column].tolist()\\n return dict(zip(xkey,xval))\",\n \"def as_dict(self):\\n return {c.name: getattr(self, c.name) for c in self.__table__.columns}\",\n \"def as_dict(self):\\n return {c.name: getattr(self, c.name) for c in self.__table__.columns}\",\n \"def as_dict(self):\\n return {c.name: getattr(self, c.name) for c in self.__table__.columns}\",\n \"def as_dict(self):\\n return {c.name: getattr(self, c.name) for c in self.__table__.columns}\",\n \"def value(self):\\n if not hasattr(self, \\\"table\\\"):\\n return {}\\n return {\\n \\\"rowlabels\\\": self.row_labels,\\n \\\"collabels\\\": self.col_labels,\\n \\\"rows\\\": self.rows,\\n \\\"cols\\\": self.cols,\\n \\\"rowname\\\": self.rowname,\\n \\\"colname\\\": self.colname,\\n \\\"naxis\\\": self.naxis,\\n \\\"table\\\": self.table\\n }\",\n \"def grid_values(self, grid):\\n chars = [col for col in grid if col in self.digits or col in '0.']\\n assert len(chars) == 81\\n return dict(zip(self.squares, chars))\",\n \"def _df_to_cellchat_format(self, df_to_convert) -> dict:\\n interactions_dataframes = {}\\n\\n for _, row in df_to_convert.iterrows():\\n df = pd.DataFrame(index=self.cell_types, columns=self.cell_types)\\n\\n for cell_type_i in self.cell_types:\\n for cell_type_j in self.cell_types:\\n interaction_name = f\\\"{cell_type_i}|{cell_type_j}\\\"\\n df.loc[cell_type_i, cell_type_j] = row[interaction_name]\\n\\n interactions_dataframes[row.interacting_pair] = df\\n\\n return interactions_dataframes\",\n \"def chunk_to_dict(chunk):\\n csv_cols = chunk.keys()\\n return [dict(zip(csv_cols, v)) for v in chunk.values]\",\n \"def as_dict(self):\\n\\n return {c.name: getattr(self, c.name) for c in self.__table__.columns}\",\n \"def _get_columns_mapping_dict():\\n\\n columns_mapping_dict = {}\\n for original_header in COLUMN_HEADERS_MAPPER:\\n new_header = COLUMN_HEADERS_MAPPER[original_header]\\n columns_mapping_dict[new_header] = [original_header]\\n return columns_mapping_dict\",\n \"def to_dict(self) -> 'collections.OrderedDict[str, tuple]':\\n\\n columns = [(column.typed_column, column.values)\\n for column in self.plaincolumns]\\n\\n return collections.OrderedDict(columns)\",\n \"def df2dict(df):\\n attr_list = list(df.columns)\\n res_dict = {}\\n for attr in attr_list:\\n res_dict[attr.lower()] = list(df[attr])\\n\\n return res_dict\",\n \"def row_to_byte_dict(row: bigtable.row.Row, f_id: str = None, idx: int = None\\n ) -> Dict[int, Dict]:\\n row_dict = {}\\n\\n for fam_id in row.cells.keys():\\n row_dict[fam_id] = {}\\n\\n for row_k in row.cells[fam_id].keys():\\n if idx is None:\\n row_dict[fam_id][deserialize_key(row_k)] = \\\\\\n [c.value for c in row.cells[fam_id][row_k]]\\n else:\\n row_dict[fam_id][deserialize_key(row_k)] = \\\\\\n row.cells[fam_id][row_k][idx].value\\n\\n if f_id is not None and f_id in row_dict:\\n return row_dict[f_id]\\n elif f_id is None:\\n return row_dict\\n else:\\n raise Exception(\\\"Family id not found\\\")\",\n \"def rows_coldict(self) -> List[Dict]:\\n return self._rows_coldict\",\n \"def as_dict(self):\\n return {\\n column.name: getattr(self, column.name)\\n for column in self.__table__.columns\\n }\",\n \"def table_row_to_dict(row, make_quantity=True):\\n data = {}\\n for name, col in row.columns.items():\\n val = row[name]\\n\\n if make_quantity and col.unit:\\n val = Quantity(val, unit=col.unit)\\n data[name] = val\\n return data\",\n \"def dict_factory(self, cursor, row):\\n results = {}\\n for index, col_name in enumerate(cursor.description):\\n results[col_name[0]] = row[index]\\n\\n return results\",\n \"def get_row_dict(self) -> HeaderToWells:\\n return self._grid.rows\",\n \"def _convert_table_to_dict(self, data_table):\\n column_names = ['star_name', 'distance', 'brightness', 'luminosity']\\n stars = {}\\n for line in data_table:\\n stars[line[0]] = {column_names[i] : line[i] for i in range(1, len(column_names))}\\n return stars\",\n \"def to_backgrid_dict(self):\\n # shorten global import times by importing django here\\n import numpy as np\\n from mpcontribs.io.core.utils import get_composition_from_string\\n from pandas import MultiIndex\\n import pymatgen.util as pmg_util\\n from pymatgen.core.composition import CompositionError\\n\\n table = dict()\\n nrows_max = 260\\n nrows = self.shape[0]\\n df = Table(self.head(n=nrows_max)) if nrows > nrows_max else self\\n numeric_columns = df.select_dtypes(include=[np.number]).columns.tolist()\\n\\n if isinstance(df.index, MultiIndex):\\n df.reset_index(inplace=True)\\n\\n table['columns'] = []\\n table['rows'] = super(Table, df).to_dict(orient='records')\\n\\n for col_index, col in enumerate(list(df.columns)):\\n cell_type = 'number'\\n\\n # avoid looping rows to minimize use of `df.iat` (time-consuming in 3d)\\n if not col.startswith('level_') and col not in numeric_columns:\\n is_url_column, prev_unit, old_col = True, None, col\\n\\n for row_index in range(df.shape[0]):\\n cell = str(df.iat[row_index, col_index])\\n cell_split = cell.split(' ', 1)\\n\\n if not cell or len(cell_split) == 1: # empty cell or no space\\n is_url_column = bool(is_url_column and (not cell or mp_id_pattern.match(cell)))\\n if is_url_column:\\n if cell:\\n value = 'https://materialsproject.org/materials/{}'.format(cell)\\n table['rows'][row_index][col] = value\\n elif cell:\\n try:\\n composition = get_composition_from_string(cell)\\n composition = pmg_util.string.unicodeify(composition)\\n table['rows'][row_index][col] = composition\\n except (CompositionError, ValueError, OverflowError):\\n try:\\n # https://stackoverflow.com/a/38020041\\n result = urlparse(cell)\\n if not all([result.scheme, result.netloc, result.path]):\\n break\\n is_url_column = True\\n except:\\n break\\n\\n else:\\n value, unit = cell_split # TODO convert cell_split[0] to float?\\n is_url_column = False\\n try:\\n float(value) # unit is only a unit if value is number\\n except ValueError:\\n continue\\n table['rows'][row_index].pop(old_col)\\n if prev_unit is None:\\n prev_unit = unit\\n col = '{} [{}]'.format(col, unit)\\n table['rows'][row_index][col] = cell if prev_unit != unit else value\\n\\n cell_type = 'uri' if is_url_column else 'string'\\n\\n col_split = col.split('##')\\n nesting = [col_split[0]] if len(col_split) > 1 else []\\n table['columns'].append({\\n 'name': col, 'cell': cell_type, 'nesting': nesting, 'editable': 0\\n })\\n if len(col_split) > 1:\\n table['columns'][-1].update({'label': '##'.join(col_split[1:])})\\n if len(table['columns']) > 12:\\n table['columns'][-1]['renderable'] = 0\\n\\n header = RecursiveDict()\\n for idx, col in enumerate(table['columns']):\\n if 'label' in col:\\n k, sk = col['name'].split('##')\\n sk_split = sk.split()\\n if len(sk_split) == 2:\\n d = {'name': sk_split[0], 'unit': sk_split[1], 'idx': idx}\\n if k not in header:\\n header[k] = [d]\\n else:\\n header[k].append(d)\\n elif k in header:\\n header.pop(k)\\n\\n for k, skl in header.items():\\n units = [sk['unit'] for sk in skl]\\n if units.count(units[0]) == len(units):\\n for sk in skl:\\n table['columns'][sk['idx']]['label'] = sk['name']\\n table['columns'][sk['idx']]['nesting'][0] = '{} {}'.format(k, sk['unit'])\\n\\n return table\",\n \"def _dictify(cols, vals):\\n assert (len(cols) == len(vals)), 'Columns and values must be the same length to map to dictionary'\\n return {col: vals[i] for i, col in enumerate(cols)}\",\n \"def to_dict(self):\\r\\n return {\\r\\n \\\"Row_ID\\\": self.row_id,\\r\\n \\\"Question\\\": self.question,\\r\\n \\\"answer1\\\": self.answer1,\\r\\n \\\"answer2\\\": self.answer2,\\r\\n \\\"answer3\\\": self.answer3,\\r\\n \\\"answer4\\\": self.answer4,\\r\\n \\\"answer5\\\": self.answer5,\\r\\n \\\"Right Answers\\\": self.right_answers,\\r\\n \\\"Hitpoints\\\": self.firsts\\r\\n }\",\n \"def toDict(self):\\n\\n aDict = {}\\n\\n # Required Keys\\n try:\\n aDict[self.E0_KEY] = self.e0.toDict()\\n aDict[self.E1_KEY] = self.e1.toDict()\\n aDict[self.E2_KEY] = self.e2.toDict()\\n aDict[self.MAXIMUM_HORIZONTAL_KEY] = self.maximumHorizontalProjection\\n aDict[self.MAXIMUM_VERTICAL_KEY] = self.maximumVerticalProjection\\n aDict[self.EQUIVALENT_HORIZONTAL_KEY] = self.equivalentHorizontalRadius\\n\\n except (NameError, AttributeError) as e:\\n print(\\\"Missing required data error: %s\\\" % e)\\n\\n return aDict\",\n \"def parse(self):\\n mp = {}\\n cells = self.row.find_all(\\\"td\\\")\\n\\n for cell in cells:\\n if \\\"visible-mobile\\\" in cell.attrs[\\\"class\\\"]:\\n continue\\n title = self._get_cell_title(cell)\\n content = cell.find(\\\"span\\\", class_=\\\"table-responsive__inner\\\")\\n\\n if title == \\\"name\\\":\\n mp.update(self._parse_name(cell, content))\\n elif title == \\\"fraktion\\\":\\n fraktion, klub = self._parse_abbreviation(content)\\n mp[\\\"political_affiliation\\\"] = klub + \\\" (\\\" + fraktion + \\\")\\\"\\n elif title == \\\"wahlkreis\\\":\\n mp[\\\"wahlkreis\\\"] = content.text.strip()\\n elif title == \\\"bundesland\\\":\\n mp[\\\"state\\\"] = self._parse_abbreviation(content)[1]\\n\\n return mp\",\n \"def as_dict(self):\\n return {c.key: getattr(self, c.key)\\n for c in inspect(self).mapper.column_attrs}\",\n \"def dict_factory(cursor, row):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row[idx]\\n return d\",\n \"def parseSheet(self):\\n self.log.info(\\\"Parsing {0} rows and {1} columns.\\\".format(self.rowns,self.colns))\\n \\n self.column_dimensions = {}\\n self.property_dimensions = {}\\n self.row_dimensions = {}\\n self.rowhierarchy = {}\\n\\n # Get dictionary of annotations\\n self.annotations = self.r_sheet.cell_note_map\\n \\n for i in range(0,self.rowns):\\n self.rowhierarchy[i] = {}\\n \\n for j in range(0, self.colns):\\n # Parse cell data\\n self.source_cell = self.r_sheet.cell(i,j)\\n self.source_cell_name = cellname(i,j)\\n self.style = self.styles[self.source_cell].name\\n self.cellType = self.getType(self.style)\\n self.source_cell_qname = self.getQName(self.source_cell_name)\\n \\n self.log.debug(\\\"({},{}) {}/{}: \\\\\\\"{}\\\\\\\"\\\". format(i,j,self.cellType, self.source_cell_name, self.source_cell.value))\\n\\n # Try to parse ints to avoid ugly _0 URIs\\n try:\\n if int(self.source_cell.value) == self.source_cell.value:\\n self.source_cell.value = int(self.source_cell.value)\\n except ValueError:\\n self.log.debug(\\\"(%s.%s) No parseable int\\\" % (i,j))\\n\\n \\n # Parse annotation (if any)\\n if self.config.get('annotations', 'enabled') == \\\"1\\\":\\n if (i,j) in self.annotations:\\n self.parseAnnotation(i, j)\\n\\n # Parse cell even if empty\\n if self.cellType == 'Data':\\n self.parseData(i, j)\\n elif (self.cellType == 'HRowHeader') :\\n self.updateRowHierarchy(i, j)\\n elif self.cellType == 'ColHeader' :\\n self.parseColHeader(i, j)\\n elif self.cellType == 'RowProperty' :\\n self.parseRowProperty(i, j)\\n \\n # If cell not empty, check for more types\\n if not self.isEmpty(i,j) :\\n #self.graph.add((self.namespaces['scope'][self.source_cell_qname],RDF.type,self.namespaces['tablink'][self.cellType]))\\n #self.graph.add((self.namespaces['scope'][self.source_cell_qname],self.namespaces['tablink']['cell'],Literal(self.source_cell_name)))\\n #self.graph.add((self.namespaces['scope'][self.source_cell_qname],self.namespaces['tablink']['col'],Literal(colname(j))))\\n #self.graph.add((self.namespaces['scope'][self.source_cell_qname],self.namespaces['tablink']['row'],Literal(i+1)))\\n #self.graph.add((self.namespaces['scope'][self.source_cell_qname] isrow row\\n if self.cellType == 'Title' :\\n self.parseTitle(i, j)\\n \\n elif self.cellType == 'RowHeader' :\\n self.parseRowHeader(i, j)\\n \\n elif self.cellType == 'HRowHeader' :\\n self.parseHierarchicalRowHeader(i, j)\\n \\n elif self.cellType == 'RowLabel' :\\n self.parseRowLabel(i, j)\\n \\n # Add additional information about the hierarchy of column headers\\n for value in self.column_dimensions.values():\\n for index in range(1, len(value)):\\n uri_sub = self.getColHeaderValueURI(value[:index+1])\\n uri_top = self.getColHeaderValueURI(value[:index])\\n self.graph.add((uri_sub, self.namespaces['tablink']['subColHeaderOf'], uri_top))\\n self.graph.add((uri_sub, self.namespaces['tablink']['depth'], Literal(index)))\\n self.graph.add((uri_top, self.namespaces['tablink']['depth'], Literal(index-1)))\\n \\n self.log.info(\\\"Done parsing...\\\")\",\n \"def dict_factory(cursor, row):\\n rowdict = {}\\n for idx, col in enumerate(cursor.description):\\n rowdict[col[0]] = row[idx]\\n return rowdict\",\n \"def map_row_to_dict(cursor: sqlite3.Cursor, row_data):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row_data[idx]\\n return d\",\n \"def PostgresTableToDict(sqldef, conn):\\n df = pd.read_sql(sqldef, con=conn)\\n return dict(zip(df.iloc[:, 0], df.iloc[:, 1]))\",\n \"def get_dict(\\n self,\\n col = '',\\n row = '',\\n entry = '',\\n ):\\n \\n if row and not col:\\n try:\\n return self._cache[row,entry]\\n except:\\n pass\\n\\n if row not in self.rows:\\n print(\\\"[!] The row you selected is not available!\\\")\\n else:\\n data = self._dict[row]\\n if not entry:\\n entries = data\\n else:\\n entries = {}\\n idx = self._header[entry]\\n\\n for key,value in data.items():\\n entries[key] = [self[i][idx] for i in value]\\n \\n self._cache[row,entry] = entries\\n return entries\\n\\n if col and not row:\\n try:\\n return self._cache[col,entry]\\n except:\\n pass\\n\\n if col not in self.cols:\\n print(\\\"[!] The column you selected is not available!\\\")\\n else:\\n data = {}\\n for i,j in [(self[i][self._rowIdx],i) for \\n i in self._array[:,self.cols.index(col)] if i != 0]:\\n try:\\n data[i] += [j]\\n except:\\n data[i] = [j]\\n\\n if not entry:\\n entries = data\\n else:\\n entries = {}\\n idx = self._header[entry]\\n\\n for key,value in data.items():\\n entries[key] = [self[i][idx] for i in value]\\n \\n self._cache[col,entry] = entries\\n \\n return entries\\n \\n elif row and col:\\n print(\\\"[!] You should specify only a value for row or for col!\\\")\\n else:\\n print(\\\"[!] Neither rows nor columns are selected!\\\")\",\n \"def to_obj(self, entity):\\n return {k: conv(getattr(entity, k, None)) for k, conv in self.cols_to_obj.items()}\",\n \"def _as_dict(self):\\r\\n values = self._dynamic_columns or {}\\r\\n for name, col in self._columns.items():\\r\\n values[name] = col.to_database(getattr(self, name, None))\\r\\n return values\",\n \"def make_to_dict(item, include_timestamp):\\n return {\\n '%s:%s' % (cell.family, cell.qualifier): (cell.value, cell.timestamp) if include_timestamp else cell.value\\n for cell in item\\n }\",\n \"def to_dictionary(self):\\n dict_contents = [\\\"id\\\", \\\"size\\\", \\\"x\\\", \\\"y\\\"]\\n new_dict = {}\\n for key in dict_contents:\\n new_dict[key] = getattr(self, key)\\n return new_dict\",\n \"def DataFrame_to_dict(df):\\n return df.to_dict(orient='records')\",\n \"def dictify(df):\\n return {str(k): v for k, v in df.items()}\",\n \"def getInterventions():\\n intFrame = xl.load_workbook(param.initial_interventions_filename, data_only=True).active\\n\\n interventionDict = dict()\\n\\n for row in intFrame['A{}:G{}'.format(intFrame.min_row + 1, intFrame.max_row)]:\\n intervention = row[0].value\\n data_list = list()\\n\\n data = row[1:len(row)]\\n\\n for cell in data:\\n data_list.append(cell.value)\\n\\n interventionDict[intervention] = data_list\\n\\n return interventionDict\",\n \"def make_dicts(cursor, row):\\n return dict((cursor.description[idx][0], value)\\n for idx, value in enumerate(row))\",\n \"def make_dicts(cursor, row):\\n return dict((cursor.description[idx][0], value)\\n for idx, value in enumerate(row))\",\n \"def to_dict(self) -> dict:\",\n \"def csv_to_dict(self):\\n log = logger.configure(\\\"default\\\")\\n try: \\n df = pd.read_csv(self.__csv_path)\\n except IOError as e:\\n # file not found\\n log.error('Could not import {}. Got error {}'.format(self.__csv_path, e))\\n raise \\n else:\\n cols = list(df.columns)\\n metafield_cols = [col for col in cols if 'metafields' in col]\\n if metafield_cols == [] or 'Handle' not in cols:\\n # relevant columns don't exist\\n log.error('{} does not contain `Handle` or `metafields` named columns'.format(self.__csv_path))\\n raise\\n else:\\n new_cols = ['Handle'] + metafield_cols\\n df = df[new_cols].set_index('Handle')\\n df = df[~df.index.duplicated(keep='first')]\\n return df.to_dict('index')\",\n \"def df_to_dict(df):\\n return df.to_dict('index')\",\n \"def compile_as_dict(self, data):\\r\\n fut = {}\\r\\n index = self.primary_key.index\\r\\n for i in data:\\r\\n popped = i.pop(index)\\r\\n head = self.table_headers.copy()\\r\\n head.pop(index)\\r\\n s = {}\\r\\n for j in range(len(head)):\\r\\n s[j] = i[j]\\r\\n fut[popped] = s\\r\\n return fut\",\n \"def to_dictionary(self):\\n dic = {}\\n ls = ['id', 'size', 'x', 'y']\\n for i in ls:\\n dic[i] = getattr(self, i)\\n return dic\",\n \"def to_dict(self) -> Dict[str, Any]:\\n fields = [\\n k\\n for row in self.field_values\\n for k, _ in row.statuses.items()\\n if k != DUMMY_ENTITY_ID\\n ]\\n features_dict: Dict[str, List[Any]] = {k: list() for k in fields}\\n\\n for row in self.field_values:\\n for feature in features_dict.keys():\\n native_type_value = feast_value_type_to_python_type(row.fields[feature])\\n features_dict[feature].append(native_type_value)\\n\\n return features_dict\",\n \"def _row_to_dict(row, fields):\\n dict_row = {}\\n for i, value in enumerate(row):\\n key = fields[i]\\n if value and str(value).lower() == 'nan':\\n value = None\\n dict_row[key] = value\\n return dict_row\",\n \"def to_proto_dict(self, v2_proto=False) -> Dict:\\n # TODO: Deprecate v1 proto method.\\n return {\\n 'row': self.row,\\n 'col': self.col,\\n }\",\n \"def dict_factory(cursor, row):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row[idx]\\n return d\",\n \"def dict_factory(cursor, row):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row[idx]\\n return d\",\n \"def dict_factory(cursor, row):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row[idx]\\n return d\",\n \"def __get_column_mapping(self):\\n\\n s1 = list(Sample(\\\"FL\\\", \\\"M1.0@265_Primary_ar115_s2010-08-06T06_36_00_e2010-08-06T18_24_00.csv\\\").get_data().columns)[:25]\\n column_mapping = {}\\n for i in range(len(s1)):\\n column_mapping[i] = s1[i]\\n\\n return column_mapping\",\n \"def dict(self) -> Dict[str, List[NumericType]]:\\n return {r.name: r.floats() for r in self._records}\",\n \"def to_entries(col):\\n sheet = col.sheet\\n rows = sheet.rows\\n\\n new_idx = sheet.columns.index(col) + 1\\n new_col = SettableColumn(col.name)\\n sheet.addColumn(new_col, index=new_idx)\\n isNull = _isNullFunc()\\n for r in rows:\\n val = col.getValue(r)\\n if isNull(val):\\n continue\\n if not isinstance(val, dict):\\n sheet.columns.pop(new_idx)\\n vd.fail('Column \\\"{}\\\" is not a dict'.format(col.name))\\n new_col.setValue(r, [{\\\"Key\\\": k, \\\"Value\\\": v} for k, v in val.items()])\\n col.hide()\\n return new_col\",\n \"def to_dict(df):\\n\\t# Extract the names\\n\\tnames = list(df.columns.values)\\n\\t# Create sequence\\n\\tdf_list = []\\n\\t#Iterate over rows of data frame\\n\\tfor index, row in df.iterrows():\\n\\t\\t# Create temporary object\\n\\t\\ttemp_dict = {}\\n\\t\\t#Iterate over key names and add values\\n\\t\\tfor name in names:\\n\\t\\t\\ttemp_dict[name] = row[name]\\n\\t\\t# Append object to dictionary\\n\\t\\tdf_list.append(temp_dict.copy())\\n\\t\\n\\treturn df_list\",\n \"def columnar(row_table: list[dict[str, str]]) -> dict[str, list[str]]:\\n result: dict[str, list[str]] = {}\\n \\n first_row: dict[str, str] = row_table[0]\\n for column in first_row:\\n result[column] = column_values(row_table, column)\\n \\n return result\",\n \"def _deduct_types(cls, row: Row) -> ColumnTypes:\\n return {\\n key: get_value_type(cls.whole_number_to_int(value))\\n for key, value in row.items()\\n }\",\n \"def to_dict(self):\",\n \"def to_dict(self):\\n dictionary = {}\\n for column in self.__table__.columns:\\n attribute_field_name = self.__mapper__.get_property_by_column(column).key\\n attribute = getattr(self, attribute_field_name)\\n dictionary[attribute_field_name] = self._make_serializable(attribute)\\n\\n return dictionary\",\n \"def object_as_dict(cls, obj):\\n return {c.key: getattr(obj, c.key) for c in inspect(obj).mapper.column_attrs}\",\n \"def to_dict(self):\\n\\n out = dict()\\n out['imsi'] = self.imsi\\n out['tmsi'] = self.tmsi\\n out['rnti'] = self.rnti\\n out['cell'] = self.cell\\n out['plmnid'] = self.plmnid\\n out['status'] = USER_STATUS[self.status]\\n out['ue_measurements'] = self.ue_measurements\\n return out\",\n \"def _dict(content):\\n response = _data_frame(content).to_dict(orient='records')\\n return response\",\n \"def dict_factory(cursor, row):\\r\\n\\td = {}\\r\\n\\tfor idx, col in enumerate(cursor.description):\\r\\n\\t\\td[col[0]] = row[idx]\\r\\n\\treturn d\",\n \"def as_dict(self):\\n if self._feat_matrix is not None:\\n feature_matrix = self._feat_matrix.tolist()\\n else:\\n feature_matrix = self._feat_matrix\\n if self.regression_data is not None:\\n reg_data = jsanitize(asdict(self.regression_data))\\n else:\\n reg_data = None\\n\\n ce_d = {\\n \\\"@module\\\": self.__class__.__module__,\\n \\\"@class\\\": self.__class__.__name__,\\n \\\"cluster_subspace\\\": self.cluster_subspace.as_dict(),\\n \\\"coefs\\\": self.coefs.tolist(),\\n \\\"regression_data\\\": reg_data,\\n \\\"feature_matrix\\\": feature_matrix,\\n }\\n return ce_d\",\n \"def to_dict(self, *columns_to_ignore):\\n dict_ = {}\\n for key in self.__mapper__.c.keys():\\n if key in columns_to_ignore:\\n continue\\n dict_[key] = getattr(self, key)\\n return dict_\",\n \"def cell_map_from_database(self) -> None:\\n for row in self.session.query(DatamapItem).all():\\n self.cell_map.append(\\n Cell(\\n datamap_id=row.id,\\n cell_key=row.key,\\n cell_value=None,\\n template_sheet=row.bicc_sheet,\\n bg_colour=None,\\n fg_colour=None,\\n number_format=None,\\n verification_list=None,\\n cell_reference=row.bicc_cellref))\",\n \"def vc_to_dict(column):\\n vc = column.value_counts()\\n vc.index = vc.index.astype(str)\\n return vc.to_dict()\",\n \"def to_dict(self):\\n d = {}\\n i = 0\\n for entry in self.entries:\\n d[i] = {}\\n attributes = self.get_attribute_list()\\n print (attributes)\\n for data in attributes:\\n d[i][data] = entry.__getattribute__(data)\\n i = i + 1\\n return d\",\n \"def dict_factory(cursor, row):\\n dic = {}\\n for idx, col in enumerate(cursor.description):\\n if isinstance(row[idx], unicode):\\n dic[col[0]] = u.unicode_to_string(row[idx])\\n else:\\n dic[col[0]] = row[idx]\\n return dic\",\n \"def row_to_dict(keys):\\n return lambda row: dict(izip(keys, row))\",\n \"def convert_data(df):\\n print(\\\"Converting history...\\\")\\n return [ dict(row) for i, row in df.iterrows() ]\",\n \"def dict_factory(cursor, row):\\n fields = [column[0] for column in cursor.description]\\n return {key: value for key, value in zip(fields, row)}\",\n \"def get_new_cell(path: tuple(str, ...)) -> dict[str, Any]:\\n return {\\n \\\"path\\\": path,\\n \\\"type\\\": \\\"cell\\\",\\n # \\\"celltype\\\": \\\"structured\\\", # or \\\"text\\\" for help cells\\n \\\"datatype\\\": \\\"mixed\\\",\\n \\\"hash_pattern\\\": None,\\n \\\"UNTRANSLATED\\\": True,\\n }\",\n \"def to_dict_index(df):\\r\\n return df.to_dict('index')\",\n \"def to_dict(self):\\r\\n return {\\r\\n \\\"Row_ID\\\": self.row_id,\\r\\n \\\"Question\\\": self.question,\\r\\n \\\"Right Answer Seq\\\": self.right_answers,\\r\\n \\\"User Answer Seq\\\": self.user_answers,\\r\\n \\\"Score\\\": self.score,\\r\\n \\\"Time Needed\\\": self.time_track,\\r\\n \\\"Hitpoints\\\": self.firsts\\r\\n }\",\n \"def createDictBase(self):\\n #allFiles = glob.glob(self.path + \\\"/*\\\"+ self.filetype)\\n #data = pd.read_excel(allFiles[0])\\n#================================================================================================================== \\n# self.list_files = self.Files_to_import()\\n# data=pd.read_excel(self.path +'/'+self.list_files[0]) # importing the first excel sheet from the first/zero time point\\n self.list_files = self.Files_to_import()\\n try:\\n tim = pd.read_excel(self.path +'/timePoints' + self.filetype) # importin the time points from a shhet called time_points\\n time = np.array(tim['time']) # assigning variable time conataing an array with the timepoints\\n self.nr_files = len(time)\\n except:\\n time = np.array(list(range(self.nr_files))) \\n \\n data=pd.read_excel(self.path +'/'+self.list_files[0])\\n \\n data=np.array(data) # converts it to array, so we can manipualte the data easier\\n #python wants for some reason first to create the dictionary with at least on value before we can run it in a loop. THat is why we have litle redundancy, since the next part is allmost the same.\\n for i in range(len(data)): # the numbers of rows. Goes through the rows\\n for ii in range(len(data[i])): # the numbers of columns. For every row goes through the columns\\n cell_id=str(i)+str(ii) # we create a variable that has a value cell_id= rowNUm colNUm, for example x= '34' means row 3 column 4\\n dat=[] # a list that will contain the first value of the cell. It will be cleaned every time the loop runs the newxt value\\n dat.append(data[i][ii]) # we put the value of the well to the list\\n self.dbase[cell_id]=dat # the list is put to the table. For example dabse['cell_id']= some OD value \\n \\n # then we go through the rest of the excell time points and collect them\\n for i in range(1,len(time)): \\n if self.list_files[i] != 0:\\n \\n #data = pd.read_excel(allFiles[i])\\n data=pd.read_excel(self.path +'/'+ self.list_files[i]) \\n data=np.array(data)\\n for i in range(len(data)): # the numbers of rows. Goes through the rows\\n for ii in range(len(data[i])): # the numbers of columns. For every row goes through the columns\\n cell_id=str(i)+str(ii) # we create a variable that has a value cell_id= rowNUm colNUm, for example x= '34' means row 3 column 4\\n \\n tempVar=self.dbase[cell_id] # here we use a method of exchanging variables to be able to uppdate the cloumn corresponding to the cell_id\\n tempVar.append(data[i][ii]) # add the new data to the copy\\n self.dbase[cell_id] = tempVar # uppdate the original dictionary\\n else:\\n pass\\n self.dbase['time'] = time # at theend we add a column that takes care of the time_points \\n return self.dbase\",\n \"def _to_dict(self) -> dict:\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.76013017","0.75878423","0.71978664","0.69413537","0.66823757","0.6574558","0.643032","0.64155895","0.6379977","0.6318955","0.6313105","0.6252503","0.6244445","0.62411374","0.61758727","0.61758727","0.61758727","0.61758727","0.61758727","0.61635846","0.61515564","0.6130489","0.61183155","0.6109212","0.6109212","0.6109212","0.6109212","0.6087283","0.60694987","0.6062373","0.60274076","0.6022243","0.6018103","0.600234","0.5999033","0.5983247","0.5978787","0.5963552","0.5956755","0.59483135","0.59390515","0.59158385","0.5895728","0.5885902","0.5871937","0.5869136","0.58680326","0.58639777","0.5857102","0.58540016","0.58430374","0.5839774","0.58350104","0.58001596","0.5797854","0.579386","0.578842","0.57755756","0.5760371","0.57504356","0.5740239","0.5739041","0.5739041","0.5729007","0.57161385","0.57108223","0.57103926","0.5709836","0.5703616","0.56978756","0.5689357","0.56859136","0.56859136","0.56859136","0.5684943","0.5682347","0.5680348","0.5664558","0.56498724","0.5644958","0.56403935","0.5631108","0.56291467","0.56290174","0.5625051","0.5618853","0.5607328","0.56067693","0.5604645","0.55990285","0.5595281","0.5595242","0.55862254","0.5577897","0.55770713","0.55738026","0.5573718","0.5568322","0.5565499","0.5549074"],"string":"[\n \"0.76013017\",\n \"0.75878423\",\n \"0.71978664\",\n \"0.69413537\",\n \"0.66823757\",\n \"0.6574558\",\n \"0.643032\",\n \"0.64155895\",\n \"0.6379977\",\n \"0.6318955\",\n \"0.6313105\",\n \"0.6252503\",\n \"0.6244445\",\n \"0.62411374\",\n \"0.61758727\",\n \"0.61758727\",\n \"0.61758727\",\n \"0.61758727\",\n \"0.61758727\",\n \"0.61635846\",\n \"0.61515564\",\n \"0.6130489\",\n \"0.61183155\",\n \"0.6109212\",\n \"0.6109212\",\n \"0.6109212\",\n \"0.6109212\",\n \"0.6087283\",\n \"0.60694987\",\n \"0.6062373\",\n \"0.60274076\",\n \"0.6022243\",\n \"0.6018103\",\n \"0.600234\",\n \"0.5999033\",\n \"0.5983247\",\n \"0.5978787\",\n \"0.5963552\",\n \"0.5956755\",\n \"0.59483135\",\n \"0.59390515\",\n \"0.59158385\",\n \"0.5895728\",\n \"0.5885902\",\n \"0.5871937\",\n \"0.5869136\",\n \"0.58680326\",\n \"0.58639777\",\n \"0.5857102\",\n \"0.58540016\",\n \"0.58430374\",\n \"0.5839774\",\n \"0.58350104\",\n \"0.58001596\",\n \"0.5797854\",\n \"0.579386\",\n \"0.578842\",\n \"0.57755756\",\n \"0.5760371\",\n \"0.57504356\",\n \"0.5740239\",\n \"0.5739041\",\n \"0.5739041\",\n \"0.5729007\",\n \"0.57161385\",\n \"0.57108223\",\n \"0.57103926\",\n \"0.5709836\",\n \"0.5703616\",\n \"0.56978756\",\n \"0.5689357\",\n \"0.56859136\",\n \"0.56859136\",\n \"0.56859136\",\n \"0.5684943\",\n \"0.5682347\",\n \"0.5680348\",\n \"0.5664558\",\n \"0.56498724\",\n \"0.5644958\",\n \"0.56403935\",\n \"0.5631108\",\n \"0.56291467\",\n \"0.56290174\",\n \"0.5625051\",\n \"0.5618853\",\n \"0.5607328\",\n \"0.56067693\",\n \"0.5604645\",\n \"0.55990285\",\n \"0.5595281\",\n \"0.5595242\",\n \"0.55862254\",\n \"0.5577897\",\n \"0.55770713\",\n \"0.55738026\",\n \"0.5573718\",\n \"0.5568322\",\n \"0.5565499\",\n \"0.5549074\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.79329205"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":83495,"cells":{"query":{"kind":"string","value":"Property returning all the cells accumulated on this partial row."},"document":{"kind":"string","value":"def cells(self):\n return copy.deepcopy(self._cells)"},"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 cells_total(self):\n return self._inv.get(\"cells\", len(self))","def get_total_cells(self):\n return self._get(\"cells\")","def cells(self):\n return self.container['cells']","def cells(self):\n return chain.from_iterable(self.cols)","def cells(self):\r\n return Cells(self)","def get_cells(self):\n raise NotImplementedError","def rows(self):\n return self.Rows(self)","def cells(self) -> List[Tuple[int, int]]:\n return self._cells","def merged_cells(self):\n return self.container['merged_cells']","def rows(self):\n return self.row","def cells(self) -> Iterable[\"RenderableType\"]:\n yield from self._cells","def rows(self):\r\n raise NotImplementedError","def iter_cells(self):\n\t\treturn iter(self._cells)","def rows(self):\r\n raise NotImplementedError()","def get_cells(self):\n return [\n cell for column in self.children for cell in column.get_cells()]","def get_rows(self) -> WellsByDimension:\n return self._rows","def get_all(self):\r\n if self.filled_rows < self.rows:\r\n return np.roll(self._data, -(self.curr_pos + self.rows - self.filled_rows),\r\n axis=0)[:self.filled_rows,:]\r\n else:\r\n # The buffer has fewer lines in this case\r\n return np.roll(self._data, -self.curr_pos,\r\n axis=0)","def get_rows(self):\n raise NotImplementedError('Subclass this to make the rows')","def rows(self):\r\n return Rows(self)","def rows(self):\n # NOTE: To avoid duplicating large objects, this is just the\n # mutable private data.\n return self._rows","def row_total(self):\n return self._row_total","def rows(self) -> List[List]:\n return self._rows","def cells(self):\n return ((row, col) for row in self.rows for col in self.cols)","def rows(self):\n return self._row_list","def GetCells(self):\n if not self.VTKObject.GetCells():\n return None\n return vtkDataArrayToVTKArray(\n self.VTKObject.GetCells().GetData(), self)","def get_cells_revealed(self):\n return self.cells_revealed","def rows(self):\n return list(self)","def sum_across_rows(grid):\n pass","def _reduce_cells(self):\n\n def reduce_cell(result, cell):\n # We assume only _sum aggergation\n # All measures should be prepared so we can to this\n for aggregate in self.aggregate_names:\n result[aggregate] = result.get(aggregate, 0) + \\\n cell.get(aggregate, 0)\n return result\n\n # 1. Map cells to reduced time path\n #\n reduced_map = defaultdict(list)\n reduced_len = len(self.time_levels)\n\n for key, cell in self.time_cells.items():\n time_path = key[0]\n reduced_path = time_path[0:reduced_len]\n\n reduced_key = (reduced_path, key[1])\n\n # self.logger.debug(\"reducing %s -> %s\" % (key, reduced_key))\n reduced_map[reduced_key].append(cell)\n\n self.browser.logger.debug(\"response cell count: %s reduced to: %s\" %\n (len(self.time_cells), len(reduced_map)))\n\n # 2. Reduce the cells\n #\n # See the function reduce_cell() above for aggregation:\n #\n reduced_cells = {}\n for key, cells in reduced_map.items():\n # self.browser.logger.debug(\"Reducing: %s -> %s\" % (key, cells))\n cell = reduce(reduce_cell, cells, {})\n\n reduced_cells[key] = cell\n\n self.time_cells = reduced_cells","def get_rows(self):\n return utils.copy_matrix(self.board)","def cells(self):\n \"\"\"\n Note that we use the convention that the first cell is (1,1)\n \"\"\"\n part = Partition(list(self))\n coordinates = part.cells()\n coordinates = [(x+1, y+1) for x, y in coordinates]\n return coordinates","def rowsums (self):\n return self.values.sum (axis=0)","def cell(self):\n return self._cell","def all_cells(self):\n \"\"\"\n Note that we use the convention that the first cell is (1,1)\n \"\"\"\n spart_star = self.circle_star()\n part = Partition(list(spart_star))\n coordinates = part.cells()\n coordinates = [(x+1, y+1) for x, y in coordinates]\n return coordinates","def area(self, by_spec=False):\n if by_spec:\n cell_area = {}\n for element in self.elements:\n element_area = element.area(True)\n for ll in element_area.keys():\n if ll in cell_area:\n cell_area[ll] += element_area[ll]\n else:\n cell_area[ll] = element_area[ll]\n else:\n cell_area = 0\n for element in self.elements:\n cell_area += element.area()\n return cell_area","def get_cells(self):\r\n return \\\r\n (self.nx-1 if self.nx>1 else 1)* \\\r\n (self.ny-1 if self.ny>1 else 1)* \\\r\n (self.nz-1 if self.nz>1 else 1)","def Ncells(self):\n return len(self.cells)","def rows_body(self) -> List[List]:\n return self.rows[1:]","def base_row_total(self):\n return self._base_row_total","def merge_cells(self):\n\n for rownum, row in enumerate(self.cells):\n for colnum, cell in enumerate(row):\n if not isinstance(cell, Cell):\n continue\n cols_to_merge = 0\n for i in range(colnum+1, len(row)):\n if isinstance(self.cells[rownum][i], Cell) and self.cells[rownum][i].event == cell.event:\n cols_to_merge += 1\n if cols_to_merge > 0:\n cell.colspan = cols_to_merge + 1\n for i in range(1, cols_to_merge + 1):\n self.cells[rownum][colnum + i] = SpanCell(rownum, colnum + i)","def cells(self):\n \"\"\"\n Note that we use the convention that the first cell is (1,1)\n \"\"\"\n spart_star = self.star()\n part = Partition(list(spart_star))\n coordinates = part.cells()\n coordinates = [(x+1, y+1) for x, y in coordinates]\n return coordinates","def get_board_rows(self):\n\n return self._board_rows","def cells(self):\n c = HBINCell(self._buf, self._offset + 0x20, self)\n\n while c.offset() < self._offset_next_hbin:\n yield c\n if c.offset() + c.size() == self._offset_next_hbin:\n break\n c = c.next()","def list(self):\n return self.cell.objects+self.cell.tempObjects","def get_rnn_cells(self):\n return [self.rnn]","def num_cells_for_rows(self, rows):\r\n return (rows * rows + rows) // 2","def empty_cells(self) -> List[Cell]:\n return list(ob.pos[0] for ob in self.new_obs())","def _cells(self):\n\n # Matrix size\n size = self.specification['DIMENSION']\n # Edge weight format\n edge_format = self.specification['EDGE_WEIGHT_FORMAT'].split('_')\n # Matrix type: FULL, UPPER, LOWER\n matrix = edge_format[0]\n\n # Data direction: ROW, COL; diagonal offset\n offset = 0\n if matrix != 'FULL':\n if edge_format[1] in ['ROW', 'COL']:\n direction = edge_format[1]\n # No diagonal entries, matrix needs to be offseted by 1\n offset = 1\n else:\n direction = edge_format[2]\n\n # Initial position in the matrix\n row = col = -1\n\n # Increments `b`. If `b` is larger than `bound` increments `a` and\n # sets `b` to `ret`.\n def calc(a, b, bound, ret):\n a = max(a, 0)\n b += 1\n if b > bound:\n a += 1\n b = ret\n return a, max(b, ret)\n\n # Generate the coordinates\n while True:\n if matrix == 'FULL':\n row, col = calc(row, col, size - 1, 0)\n elif matrix == 'UPPER' and direction == 'ROW':\n row, col = calc(row, col, size - 1, row + 1 + offset)\n elif matrix == 'LOWER' and direction == 'COL':\n col, row = calc(col, row, size - 1, col + 1 + offset)\n elif matrix == 'LOWER' and direction == 'ROW':\n row, col = calc(\n row, col, row - offset if offset else max(row, 0), 0)\n elif matrix == 'UPPER' and direction == 'COL':\n col, row = calc(\n col, row, col - offset if offset else max(col, 0), 0)\n\n # End when all coordinates are generated\n if row >= size or col >= size:\n break\n\n yield row, col","def _get_rows(self) -> List[htmler.Tr]:\n r = []\n\n widgets_per_row = len(self._get_widgets())\n for row_num in range(0, len(self.value), widgets_per_row):\n row_widgets = self._get_widgets()\n for col_num in range(len(row_widgets)):\n row_widgets[col_num].value = self.value[row_num + col_num]\n r.append(self._get_row(row_widgets, row_num))\n\n return r","def full(self):\n return [cell for cell in self.compact if cell.peg]","def get_cells(self):\n cell_list = []\n for cell_row in self.board:\n for current_cell in cell_row:\n if current_cell is not None:\n cell_list.append(current_cell)\n return cell_list","def rows(self) -> java.util.Collection:\n ...","def get_rnn_cells(self) -> List[mx.rnn.BaseRNNCell]:\n return self.forward_rnn.get_rnn_cells() + self.reverse_rnn.get_rnn_cells()","def rows(self):\n return self.settings['field_rows']","def get_visible_rows(self):\r\n start, end, _, _ = self.get_visible_cells()\r\n return start, end","def get_cells(self, row, col):\r\n surrounding_cells = self.get_surrounding_cells(row, col)\r\n closed_cells = self.filter_cells(surrounding_cells, '?')\r\n mine_cells = self.filter_cells(surrounding_cells, 'x')\r\n numbered_cells = list(set(surrounding_cells).difference(closed_cells))\r\n numbered_cells = list(set(numbered_cells).difference(mine_cells))\r\n return surrounding_cells, closed_cells, mine_cells, numbered_cells","def grand_total(self):\n return sum(self.grid[pos][1] for pos in assignable_positions if self.grid[pos][0]) + self.grid[\"nb\"][1]","def ncells(self):\n return self.izone.size","def GetNumberOfCells(self):\n return self.GetNumberOfElements(ArrayAssociation.CELL)","def __iter__(self):\n return iter(self.__rows)","def iter_related(self, inclusive=False, **kwargs):\n ret = self.sudoku.row(self.row, **kwargs) + \\\n self.sudoku.col(self.col, **kwargs) + \\\n self.sudoku.box(self.box, **kwargs)\n if not inclusive:\n ret -= self\n return ret","def cell_edges(self):\n return self._cell_edges","def get_row_dict(self) -> HeaderToWells:\n return self._grid.rows","def __len__(self):\n return len(self.rows)","def __iter__(self):\n return iter(self.rows)","def get(self):\n return np.hstack((self.data[:, self.cur:], self.data[:, :self.cur])) #Concatena los datos en horizontal","def addrCellsProperty(self):\n return FdtPropertyWords(\"#address-cells\", self.addr_cells)","def rows (self):\n for row in self._m:\n yield Vector(row)","def row(self):\n\t\treturn self.__row","def get_claimable_cells(self) -> list[tuple[int, int]]:\n pass","def get_grid(self):\n self.fullws = []\n for row in self.word_search_grid:\n rowdata = []\n for column in row:\n rowdata += [column.entry.get()]\n self.fullws += [rowdata]\n self.logic.set_grid(self.fullws)","def __ret_cell(self, cell):\n # try:\n # assert cell < self.length\n # except AssertionError:\n # print(\"ERROR: Cell value '%d' is larger than total size '%d'.\" % (cell, self.length-1))\n # sys.exit()\n # Next value is every self.row * N. Work backwards with int division.\n # a = cell // self.row % self.row\n # a = cell // self.row\n a = cell // self.col % self.row\n # Values are consequtive and wrap at self.col.\n b = cell % self.col\n return [a, b]","def getObjects(self):\n return Cell_Objects(self)","def getNonEmptyCells(self):\n nonemptys = []\n for ri in range(self.nRow):\n for ci in range(self.nCol):\n val = self.vals[ri][ci]\n if not self.isEmpty(val):\n row = ri+1\n col = ci+1\n nonemptys.append(CellDesc(row=row, col=col, val=val))\n return nonemptys","def get_all_numbered_cells(self):\r\n num_rows = len(self.mine_field)\r\n num_cols = len(self.mine_field[0])\r\n numbered_cells = [(row, col)\r\n for row in range(num_rows)\r\n for col in range(num_cols)\r\n if self.mine_field[row][col] != '?' and \\\r\n self.mine_field[row][col] != 'x']\r\n return numbered_cells","def sum_grid(self, grid):\n new_grid = []\n for i in range(self.grid_size):\n new_grid.append(self.sum_row(grid[i]))\n return new_grid","def rows(self):\n if self._cached_rows is None:\n self._cached_rows = tuple(self.iterrows())\n return self._cached_rows","def row_count(self):\n return self.well_count // self.col_count","def colsums (self):\n return self.values.sum (axis=1)","def cells_list(self):\n xx, yy = np.meshgrid(self.x_spacings, self.y_spacings)\n return np.vstack([yy.ravel(), xx.ravel()]).transpose()","def render(self):\n rval = N.zeros((self.rows, self.cols, 3))\n\n for component in self.components:\n rval = component.render( prev_layer = rval, parent = self )\n assert rval is not None\n\n return rval","def grid(self):\n return self.__grid","def cols(self):\n\n return []","def occupied_cells(self):\n\n for lm in self.landmarks:\n if self.cell_size < 1:\n # expand the range the landmark exists\n lm_x_range = np.arange(lm[0]-self.R, lm[0]+self.R, self.cell_size)\n lm_y_range = np.arange(lm[1]-self.R, lm[1]+self.R, self.cell_size)\n\n # loop through expanded ranges and compute grid positions\n for lm_x in lm_x_range:\n for lm_y in lm_y_range:\n\n row, col = self.cell_index([lm_x, lm_y])\n\n # apply cost of occupied cell\n try:\n self.world[row][col] = 1000\n except IndexError:\n pass\n\n else:\n # apply cost of occupied cell\n row, col = self.cell_index(lm)\n try:\n self.world[row][col] = 1000\n except IndexError:\n pass","def calc_total_rows(self):\n #total_rows = len(self.file_list) - 1 # Minus header\n print('Total number of rows: ' + str(self.tot_rows))\n results.append('Total number of rows: ' + str(self.tot_rows))","def get_cellcount(self):\n self.cellcount += 1\n return self.cellcount - 1","def rows(self) -> int:\n return self.__squares.__len__()","def values(self):\n self._values = [[cell for cell in row]\n for row in self.sheet._op.values]\n # self._values = [cell for row in self.sheet._op.values for cell in row]\n return self._values","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def generate_cells(self,n_c):\n self.n_c = n_c\n self.cells = [Cell() for i in range(n_c)]\n return self.cells","def num_rows(self):\n return len(self[0])","def iterrows(self):\n return (self.Row(*row_vals) for row_vals in izip(*self.columns))","def empty(self):\n return [cell for cell in self.compact if not cell.peg]","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)"],"string":"[\n \"def cells_total(self):\\n return self._inv.get(\\\"cells\\\", len(self))\",\n \"def get_total_cells(self):\\n return self._get(\\\"cells\\\")\",\n \"def cells(self):\\n return self.container['cells']\",\n \"def cells(self):\\n return chain.from_iterable(self.cols)\",\n \"def cells(self):\\r\\n return Cells(self)\",\n \"def get_cells(self):\\n raise NotImplementedError\",\n \"def rows(self):\\n return self.Rows(self)\",\n \"def cells(self) -> List[Tuple[int, int]]:\\n return self._cells\",\n \"def merged_cells(self):\\n return self.container['merged_cells']\",\n \"def rows(self):\\n return self.row\",\n \"def cells(self) -> Iterable[\\\"RenderableType\\\"]:\\n yield from self._cells\",\n \"def rows(self):\\r\\n raise NotImplementedError\",\n \"def iter_cells(self):\\n\\t\\treturn iter(self._cells)\",\n \"def rows(self):\\r\\n raise NotImplementedError()\",\n \"def get_cells(self):\\n return [\\n cell for column in self.children for cell in column.get_cells()]\",\n \"def get_rows(self) -> WellsByDimension:\\n return self._rows\",\n \"def get_all(self):\\r\\n if self.filled_rows < self.rows:\\r\\n return np.roll(self._data, -(self.curr_pos + self.rows - self.filled_rows),\\r\\n axis=0)[:self.filled_rows,:]\\r\\n else:\\r\\n # The buffer has fewer lines in this case\\r\\n return np.roll(self._data, -self.curr_pos,\\r\\n axis=0)\",\n \"def get_rows(self):\\n raise NotImplementedError('Subclass this to make the rows')\",\n \"def rows(self):\\r\\n return Rows(self)\",\n \"def rows(self):\\n # NOTE: To avoid duplicating large objects, this is just the\\n # mutable private data.\\n return self._rows\",\n \"def row_total(self):\\n return self._row_total\",\n \"def rows(self) -> List[List]:\\n return self._rows\",\n \"def cells(self):\\n return ((row, col) for row in self.rows for col in self.cols)\",\n \"def rows(self):\\n return self._row_list\",\n \"def GetCells(self):\\n if not self.VTKObject.GetCells():\\n return None\\n return vtkDataArrayToVTKArray(\\n self.VTKObject.GetCells().GetData(), self)\",\n \"def get_cells_revealed(self):\\n return self.cells_revealed\",\n \"def rows(self):\\n return list(self)\",\n \"def sum_across_rows(grid):\\n pass\",\n \"def _reduce_cells(self):\\n\\n def reduce_cell(result, cell):\\n # We assume only _sum aggergation\\n # All measures should be prepared so we can to this\\n for aggregate in self.aggregate_names:\\n result[aggregate] = result.get(aggregate, 0) + \\\\\\n cell.get(aggregate, 0)\\n return result\\n\\n # 1. Map cells to reduced time path\\n #\\n reduced_map = defaultdict(list)\\n reduced_len = len(self.time_levels)\\n\\n for key, cell in self.time_cells.items():\\n time_path = key[0]\\n reduced_path = time_path[0:reduced_len]\\n\\n reduced_key = (reduced_path, key[1])\\n\\n # self.logger.debug(\\\"reducing %s -> %s\\\" % (key, reduced_key))\\n reduced_map[reduced_key].append(cell)\\n\\n self.browser.logger.debug(\\\"response cell count: %s reduced to: %s\\\" %\\n (len(self.time_cells), len(reduced_map)))\\n\\n # 2. Reduce the cells\\n #\\n # See the function reduce_cell() above for aggregation:\\n #\\n reduced_cells = {}\\n for key, cells in reduced_map.items():\\n # self.browser.logger.debug(\\\"Reducing: %s -> %s\\\" % (key, cells))\\n cell = reduce(reduce_cell, cells, {})\\n\\n reduced_cells[key] = cell\\n\\n self.time_cells = reduced_cells\",\n \"def get_rows(self):\\n return utils.copy_matrix(self.board)\",\n \"def cells(self):\\n \\\"\\\"\\\"\\n Note that we use the convention that the first cell is (1,1)\\n \\\"\\\"\\\"\\n part = Partition(list(self))\\n coordinates = part.cells()\\n coordinates = [(x+1, y+1) for x, y in coordinates]\\n return coordinates\",\n \"def rowsums (self):\\n return self.values.sum (axis=0)\",\n \"def cell(self):\\n return self._cell\",\n \"def all_cells(self):\\n \\\"\\\"\\\"\\n Note that we use the convention that the first cell is (1,1)\\n \\\"\\\"\\\"\\n spart_star = self.circle_star()\\n part = Partition(list(spart_star))\\n coordinates = part.cells()\\n coordinates = [(x+1, y+1) for x, y in coordinates]\\n return coordinates\",\n \"def area(self, by_spec=False):\\n if by_spec:\\n cell_area = {}\\n for element in self.elements:\\n element_area = element.area(True)\\n for ll in element_area.keys():\\n if ll in cell_area:\\n cell_area[ll] += element_area[ll]\\n else:\\n cell_area[ll] = element_area[ll]\\n else:\\n cell_area = 0\\n for element in self.elements:\\n cell_area += element.area()\\n return cell_area\",\n \"def get_cells(self):\\r\\n return \\\\\\r\\n (self.nx-1 if self.nx>1 else 1)* \\\\\\r\\n (self.ny-1 if self.ny>1 else 1)* \\\\\\r\\n (self.nz-1 if self.nz>1 else 1)\",\n \"def Ncells(self):\\n return len(self.cells)\",\n \"def rows_body(self) -> List[List]:\\n return self.rows[1:]\",\n \"def base_row_total(self):\\n return self._base_row_total\",\n \"def merge_cells(self):\\n\\n for rownum, row in enumerate(self.cells):\\n for colnum, cell in enumerate(row):\\n if not isinstance(cell, Cell):\\n continue\\n cols_to_merge = 0\\n for i in range(colnum+1, len(row)):\\n if isinstance(self.cells[rownum][i], Cell) and self.cells[rownum][i].event == cell.event:\\n cols_to_merge += 1\\n if cols_to_merge > 0:\\n cell.colspan = cols_to_merge + 1\\n for i in range(1, cols_to_merge + 1):\\n self.cells[rownum][colnum + i] = SpanCell(rownum, colnum + i)\",\n \"def cells(self):\\n \\\"\\\"\\\"\\n Note that we use the convention that the first cell is (1,1)\\n \\\"\\\"\\\"\\n spart_star = self.star()\\n part = Partition(list(spart_star))\\n coordinates = part.cells()\\n coordinates = [(x+1, y+1) for x, y in coordinates]\\n return coordinates\",\n \"def get_board_rows(self):\\n\\n return self._board_rows\",\n \"def cells(self):\\n c = HBINCell(self._buf, self._offset + 0x20, self)\\n\\n while c.offset() < self._offset_next_hbin:\\n yield c\\n if c.offset() + c.size() == self._offset_next_hbin:\\n break\\n c = c.next()\",\n \"def list(self):\\n return self.cell.objects+self.cell.tempObjects\",\n \"def get_rnn_cells(self):\\n return [self.rnn]\",\n \"def num_cells_for_rows(self, rows):\\r\\n return (rows * rows + rows) // 2\",\n \"def empty_cells(self) -> List[Cell]:\\n return list(ob.pos[0] for ob in self.new_obs())\",\n \"def _cells(self):\\n\\n # Matrix size\\n size = self.specification['DIMENSION']\\n # Edge weight format\\n edge_format = self.specification['EDGE_WEIGHT_FORMAT'].split('_')\\n # Matrix type: FULL, UPPER, LOWER\\n matrix = edge_format[0]\\n\\n # Data direction: ROW, COL; diagonal offset\\n offset = 0\\n if matrix != 'FULL':\\n if edge_format[1] in ['ROW', 'COL']:\\n direction = edge_format[1]\\n # No diagonal entries, matrix needs to be offseted by 1\\n offset = 1\\n else:\\n direction = edge_format[2]\\n\\n # Initial position in the matrix\\n row = col = -1\\n\\n # Increments `b`. If `b` is larger than `bound` increments `a` and\\n # sets `b` to `ret`.\\n def calc(a, b, bound, ret):\\n a = max(a, 0)\\n b += 1\\n if b > bound:\\n a += 1\\n b = ret\\n return a, max(b, ret)\\n\\n # Generate the coordinates\\n while True:\\n if matrix == 'FULL':\\n row, col = calc(row, col, size - 1, 0)\\n elif matrix == 'UPPER' and direction == 'ROW':\\n row, col = calc(row, col, size - 1, row + 1 + offset)\\n elif matrix == 'LOWER' and direction == 'COL':\\n col, row = calc(col, row, size - 1, col + 1 + offset)\\n elif matrix == 'LOWER' and direction == 'ROW':\\n row, col = calc(\\n row, col, row - offset if offset else max(row, 0), 0)\\n elif matrix == 'UPPER' and direction == 'COL':\\n col, row = calc(\\n col, row, col - offset if offset else max(col, 0), 0)\\n\\n # End when all coordinates are generated\\n if row >= size or col >= size:\\n break\\n\\n yield row, col\",\n \"def _get_rows(self) -> List[htmler.Tr]:\\n r = []\\n\\n widgets_per_row = len(self._get_widgets())\\n for row_num in range(0, len(self.value), widgets_per_row):\\n row_widgets = self._get_widgets()\\n for col_num in range(len(row_widgets)):\\n row_widgets[col_num].value = self.value[row_num + col_num]\\n r.append(self._get_row(row_widgets, row_num))\\n\\n return r\",\n \"def full(self):\\n return [cell for cell in self.compact if cell.peg]\",\n \"def get_cells(self):\\n cell_list = []\\n for cell_row in self.board:\\n for current_cell in cell_row:\\n if current_cell is not None:\\n cell_list.append(current_cell)\\n return cell_list\",\n \"def rows(self) -> java.util.Collection:\\n ...\",\n \"def get_rnn_cells(self) -> List[mx.rnn.BaseRNNCell]:\\n return self.forward_rnn.get_rnn_cells() + self.reverse_rnn.get_rnn_cells()\",\n \"def rows(self):\\n return self.settings['field_rows']\",\n \"def get_visible_rows(self):\\r\\n start, end, _, _ = self.get_visible_cells()\\r\\n return start, end\",\n \"def get_cells(self, row, col):\\r\\n surrounding_cells = self.get_surrounding_cells(row, col)\\r\\n closed_cells = self.filter_cells(surrounding_cells, '?')\\r\\n mine_cells = self.filter_cells(surrounding_cells, 'x')\\r\\n numbered_cells = list(set(surrounding_cells).difference(closed_cells))\\r\\n numbered_cells = list(set(numbered_cells).difference(mine_cells))\\r\\n return surrounding_cells, closed_cells, mine_cells, numbered_cells\",\n \"def grand_total(self):\\n return sum(self.grid[pos][1] for pos in assignable_positions if self.grid[pos][0]) + self.grid[\\\"nb\\\"][1]\",\n \"def ncells(self):\\n return self.izone.size\",\n \"def GetNumberOfCells(self):\\n return self.GetNumberOfElements(ArrayAssociation.CELL)\",\n \"def __iter__(self):\\n return iter(self.__rows)\",\n \"def iter_related(self, inclusive=False, **kwargs):\\n ret = self.sudoku.row(self.row, **kwargs) + \\\\\\n self.sudoku.col(self.col, **kwargs) + \\\\\\n self.sudoku.box(self.box, **kwargs)\\n if not inclusive:\\n ret -= self\\n return ret\",\n \"def cell_edges(self):\\n return self._cell_edges\",\n \"def get_row_dict(self) -> HeaderToWells:\\n return self._grid.rows\",\n \"def __len__(self):\\n return len(self.rows)\",\n \"def __iter__(self):\\n return iter(self.rows)\",\n \"def get(self):\\n return np.hstack((self.data[:, self.cur:], self.data[:, :self.cur])) #Concatena los datos en horizontal\",\n \"def addrCellsProperty(self):\\n return FdtPropertyWords(\\\"#address-cells\\\", self.addr_cells)\",\n \"def rows (self):\\n for row in self._m:\\n yield Vector(row)\",\n \"def row(self):\\n\\t\\treturn self.__row\",\n \"def get_claimable_cells(self) -> list[tuple[int, int]]:\\n pass\",\n \"def get_grid(self):\\n self.fullws = []\\n for row in self.word_search_grid:\\n rowdata = []\\n for column in row:\\n rowdata += [column.entry.get()]\\n self.fullws += [rowdata]\\n self.logic.set_grid(self.fullws)\",\n \"def __ret_cell(self, cell):\\n # try:\\n # assert cell < self.length\\n # except AssertionError:\\n # print(\\\"ERROR: Cell value '%d' is larger than total size '%d'.\\\" % (cell, self.length-1))\\n # sys.exit()\\n # Next value is every self.row * N. Work backwards with int division.\\n # a = cell // self.row % self.row\\n # a = cell // self.row\\n a = cell // self.col % self.row\\n # Values are consequtive and wrap at self.col.\\n b = cell % self.col\\n return [a, b]\",\n \"def getObjects(self):\\n return Cell_Objects(self)\",\n \"def getNonEmptyCells(self):\\n nonemptys = []\\n for ri in range(self.nRow):\\n for ci in range(self.nCol):\\n val = self.vals[ri][ci]\\n if not self.isEmpty(val):\\n row = ri+1\\n col = ci+1\\n nonemptys.append(CellDesc(row=row, col=col, val=val))\\n return nonemptys\",\n \"def get_all_numbered_cells(self):\\r\\n num_rows = len(self.mine_field)\\r\\n num_cols = len(self.mine_field[0])\\r\\n numbered_cells = [(row, col)\\r\\n for row in range(num_rows)\\r\\n for col in range(num_cols)\\r\\n if self.mine_field[row][col] != '?' and \\\\\\r\\n self.mine_field[row][col] != 'x']\\r\\n return numbered_cells\",\n \"def sum_grid(self, grid):\\n new_grid = []\\n for i in range(self.grid_size):\\n new_grid.append(self.sum_row(grid[i]))\\n return new_grid\",\n \"def rows(self):\\n if self._cached_rows is None:\\n self._cached_rows = tuple(self.iterrows())\\n return self._cached_rows\",\n \"def row_count(self):\\n return self.well_count // self.col_count\",\n \"def colsums (self):\\n return self.values.sum (axis=1)\",\n \"def cells_list(self):\\n xx, yy = np.meshgrid(self.x_spacings, self.y_spacings)\\n return np.vstack([yy.ravel(), xx.ravel()]).transpose()\",\n \"def render(self):\\n rval = N.zeros((self.rows, self.cols, 3))\\n\\n for component in self.components:\\n rval = component.render( prev_layer = rval, parent = self )\\n assert rval is not None\\n\\n return rval\",\n \"def grid(self):\\n return self.__grid\",\n \"def cols(self):\\n\\n return []\",\n \"def occupied_cells(self):\\n\\n for lm in self.landmarks:\\n if self.cell_size < 1:\\n # expand the range the landmark exists\\n lm_x_range = np.arange(lm[0]-self.R, lm[0]+self.R, self.cell_size)\\n lm_y_range = np.arange(lm[1]-self.R, lm[1]+self.R, self.cell_size)\\n\\n # loop through expanded ranges and compute grid positions\\n for lm_x in lm_x_range:\\n for lm_y in lm_y_range:\\n\\n row, col = self.cell_index([lm_x, lm_y])\\n\\n # apply cost of occupied cell\\n try:\\n self.world[row][col] = 1000\\n except IndexError:\\n pass\\n\\n else:\\n # apply cost of occupied cell\\n row, col = self.cell_index(lm)\\n try:\\n self.world[row][col] = 1000\\n except IndexError:\\n pass\",\n \"def calc_total_rows(self):\\n #total_rows = len(self.file_list) - 1 # Minus header\\n print('Total number of rows: ' + str(self.tot_rows))\\n results.append('Total number of rows: ' + str(self.tot_rows))\",\n \"def get_cellcount(self):\\n self.cellcount += 1\\n return self.cellcount - 1\",\n \"def rows(self) -> int:\\n return self.__squares.__len__()\",\n \"def values(self):\\n self._values = [[cell for cell in row]\\n for row in self.sheet._op.values]\\n # self._values = [cell for row in self.sheet._op.values for cell in row]\\n return self._values\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def generate_cells(self,n_c):\\n self.n_c = n_c\\n self.cells = [Cell() for i in range(n_c)]\\n return self.cells\",\n \"def num_rows(self):\\n return len(self[0])\",\n \"def iterrows(self):\\n return (self.Row(*row_vals) for row_vals in izip(*self.columns))\",\n \"def empty(self):\\n return [cell for cell in self.compact if not cell.peg]\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7329604","0.72963184","0.7285541","0.71675426","0.70034677","0.6740002","0.6697525","0.6685098","0.6658701","0.66584843","0.653525","0.6513235","0.6502038","0.6449473","0.6402963","0.63210136","0.62875944","0.6282429","0.6233849","0.61757165","0.6172168","0.61571896","0.61458623","0.6137921","0.61028564","0.60897136","0.60659033","0.60424393","0.60195136","0.6013085","0.60036","0.5996485","0.59779525","0.5970863","0.5967414","0.5948011","0.59463066","0.589704","0.5857024","0.58531684","0.584972","0.5825297","0.58236885","0.5793682","0.57862556","0.5752499","0.5751992","0.57333803","0.572788","0.57214504","0.57201385","0.57084626","0.5690169","0.5686238","0.5683734","0.5661972","0.56407595","0.56334364","0.56304646","0.5622456","0.561496","0.56004596","0.5562946","0.5552824","0.5549955","0.55355364","0.5529707","0.5523837","0.5515968","0.5515653","0.551273","0.5504965","0.5504236","0.5501806","0.5500607","0.54983354","0.5477465","0.5475694","0.54748803","0.5468523","0.5465192","0.546284","0.5451639","0.5431091","0.54268247","0.54249847","0.5420807","0.5418801","0.5410886","0.5410886","0.5407562","0.54063815","0.5395148","0.53881603","0.5387817","0.5387817","0.5387817","0.5387817","0.5387817","0.5387817"],"string":"[\n \"0.7329604\",\n \"0.72963184\",\n \"0.7285541\",\n \"0.71675426\",\n \"0.70034677\",\n \"0.6740002\",\n \"0.6697525\",\n \"0.6685098\",\n \"0.6658701\",\n \"0.66584843\",\n \"0.653525\",\n \"0.6513235\",\n \"0.6502038\",\n \"0.6449473\",\n \"0.6402963\",\n \"0.63210136\",\n \"0.62875944\",\n \"0.6282429\",\n \"0.6233849\",\n \"0.61757165\",\n \"0.6172168\",\n \"0.61571896\",\n \"0.61458623\",\n \"0.6137921\",\n \"0.61028564\",\n \"0.60897136\",\n \"0.60659033\",\n \"0.60424393\",\n \"0.60195136\",\n \"0.6013085\",\n \"0.60036\",\n \"0.5996485\",\n \"0.59779525\",\n \"0.5970863\",\n \"0.5967414\",\n \"0.5948011\",\n \"0.59463066\",\n \"0.589704\",\n \"0.5857024\",\n \"0.58531684\",\n \"0.584972\",\n \"0.5825297\",\n \"0.58236885\",\n \"0.5793682\",\n \"0.57862556\",\n \"0.5752499\",\n \"0.5751992\",\n \"0.57333803\",\n \"0.572788\",\n \"0.57214504\",\n \"0.57201385\",\n \"0.57084626\",\n \"0.5690169\",\n \"0.5686238\",\n \"0.5683734\",\n \"0.5661972\",\n \"0.56407595\",\n \"0.56334364\",\n \"0.56304646\",\n \"0.5622456\",\n \"0.561496\",\n \"0.56004596\",\n \"0.5562946\",\n \"0.5552824\",\n \"0.5549955\",\n \"0.55355364\",\n \"0.5529707\",\n \"0.5523837\",\n \"0.5515968\",\n \"0.5515653\",\n \"0.551273\",\n \"0.5504965\",\n \"0.5504236\",\n \"0.5501806\",\n \"0.5500607\",\n \"0.54983354\",\n \"0.5477465\",\n \"0.5475694\",\n \"0.54748803\",\n \"0.5468523\",\n \"0.5465192\",\n \"0.546284\",\n \"0.5451639\",\n \"0.5431091\",\n \"0.54268247\",\n \"0.54249847\",\n \"0.5420807\",\n \"0.5418801\",\n \"0.5410886\",\n \"0.5410886\",\n \"0.5407562\",\n \"0.54063815\",\n \"0.5395148\",\n \"0.53881603\",\n \"0.5387817\",\n \"0.5387817\",\n \"0.5387817\",\n \"0.5387817\",\n \"0.5387817\",\n \"0.5387817\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.69514596"},"document_rank":{"kind":"string","value":"5"}}},{"rowIdx":83496,"cells":{"query":{"kind":"string","value":"Getter for the current (partial) row's key."},"document":{"kind":"string","value":"def row_key(self):\n return self._row_key"},"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 __key__(self) -> Tuple[int, int]:\n return self.col, self.row","def get_key(self) -> int:\n return self.__key","def get_key(self) -> int:\n return self.key","def get_key(self):\n return self.key","def get_key(self):\n return self.key","def key(self):\n return self.__key","def key(self):\n return self.value()._key","def key(self):\n return self.key_for(self.id)","def get_key(self):\n return self._determine_key()","def key(self):\n return self._key","def key(self):\n return self._key","def key(self):\n return self._key","def key(self):\n return self._key","def get_key(self):\n\n return self._key","def getKey(self):\n\t\treturn self.key","def getKey(self):\n return self.__key","def 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self.__keys[self.__pq[1]]\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n 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pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> str:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> Optional[str]:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> Optional[str]:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> Optional[str]:\\n return pulumi.get(self, \\\"key\\\")\",\n \"def key(self) -> Optional[str]:\\n return pulumi.get(self, \\\"key\\\")\"\n]","isConversational":false},"negative_scores":{"kind":"list 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\"0.72316724\",\n \"0.72159064\",\n \"0.7207303\",\n \"0.7157399\",\n \"0.7157399\",\n \"0.71138483\",\n \"0.7061789\",\n \"0.7047705\",\n \"0.6999932\",\n \"0.6988818\",\n \"0.6988818\",\n \"0.6988818\",\n \"0.6988818\",\n \"0.6960423\",\n \"0.6876054\",\n \"0.683839\",\n \"0.68287086\",\n \"0.6781018\",\n \"0.6758112\",\n \"0.67410135\",\n \"0.6730147\",\n \"0.6718879\",\n \"0.66619945\",\n \"0.6654567\",\n \"0.6591671\",\n \"0.6585299\",\n \"0.6576176\",\n \"0.65732145\",\n \"0.65676945\",\n \"0.6537412\",\n \"0.6532713\",\n \"0.6520809\",\n \"0.6518459\",\n \"0.64861774\",\n \"0.6472876\",\n \"0.6439855\",\n \"0.6423872\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6422198\",\n \"0.6419737\",\n \"0.6419737\",\n \"0.6419737\",\n \"0.6419737\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.84983855"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":83497,"cells":{"query":{"kind":"string","value":"Property returning all rows accumulated from the stream."},"document":{"kind":"string","value":"def rows(self):\n # NOTE: To avoid duplicating large objects, this is just the\n # mutable private data.\n return self._rows"},"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":["async def fetchall(self):\n\n self._check_executed()\n\n if self._query_id == -1:\n msg = \"query didn't result in a resultset\"\n self._exception_handler(ProgrammingError, msg)\n\n result = self._rows[self.rownumber - self._offset :]\n self.rownumber = len(self._rows) + self._offset\n\n # slide the window over the resultset\n while await self.nextset():\n result += self._rows\n self.rownumber = len(self._rows) + self._offset\n print(\n \"\\nresult: \",\n self._rows,\n \"\\n\\n\",\n )\n return result","def get_all(self):\r\n if self.filled_rows < self.rows:\r\n return np.roll(self._data, -(self.curr_pos + self.rows - self.filled_rows),\r\n axis=0)[:self.filled_rows,:]\r\n else:\r\n # The buffer has fewer lines in this case\r\n return np.roll(self._data, -self.curr_pos,\r\n axis=0)","def rows(self):\n return self.Rows(self)","def rows(self):\n if self._cached_rows is None:\n self._cached_rows = tuple(self.iterrows())\n return self._cached_rows","def total_rows(self):\n self._fetch_if_needed()\n # reduce case, count number of lines\n if self._total_rows is None:\n return self.count()\n return self._total_rows","def rows(self):\n return self._row_list","def __iter__(self):\n for row in self.rows:\n yield row","def __iter__(self):\n return iter(self.__rows)","def rows(self):\n return self.row","def __iter__(self):\n return iter(self.rows)","def rows(self) -> List[List]:\n return self._rows","def rows(self):\r\n\r\n done_sending = False\r\n while not done_sending:\r\n self._note(\"C _not_empty acq?\")\r\n self.not_empty.acquire()\r\n try:\r\n self._note(\"C _not_empty wait ...\")\r\n while not self._ready_buffer and not self._closed:\r\n self.not_empty.wait()\r\n self._note(\"C _not_empty got <\")\r\n\r\n if self._ready_buffer:\r\n rows = self._ready_buffer\r\n self._ready_buffer = None\r\n self._note(\"C _not_full notify >\")\r\n self.not_full.notify()\r\n\r\n for row in rows:\r\n yield row\r\n else:\r\n self._note(\"C no buffer\")\r\n\r\n\r\n done_sending = self._closed\r\n finally:\r\n self._note(\"_not_empty rel!\")\r\n self.not_empty.release()","def get_rows(self):\n raise NotImplementedError('Subclass this to make the rows')","def rows(self):\n return list(self)","def rows(self):\n with self.input().open('r') as fobj:\n for line in fobj:\n yield line.strip('\\n').split('\\t')","def _write_rows(self):\n try:\n xf = self._writer.xf.send(True)\n except StopIteration:\n self._already_saved()\n\n with xf.element(\"sheetData\"):\n row_idx = 1\n try:\n while True:\n row = (yield)\n row = self._values_to_row(row, row_idx)\n self._writer.write_row(xf, row, row_idx)\n row_idx += 1\n except GeneratorExit:\n pass\n\n self._writer.xf.send(None)","def fetchall(self):\n self._check_closed()\n\n fetched_rows = []\n while True:\n row = self.fetchone()\n if row is None:\n break\n else:\n fetched_rows.append(row)\n return fetched_rows","def get_rows(self) -> QuerySet:\n return self.get_source_query().values(*self.COLUMNS)","def rows(self):\r\n _rows = []\r\n try:\r\n csv_file = open(self.file_path,'rbU')\r\n csv_rows = csv.DictReader(csv_file)\r\n for row in csv_rows:\r\n _rows.append(row)\r\n csv_file.close()\r\n return _rows\r\n except:\r\n return _rows","def fetch(self):\n # type: () -> List[List[Any]]\n if self._request.next_uri is None:\n self._finished = True\n return []\n response = self._request.get(self._request.next_uri)\n status = self._request.process(response)\n if status.columns:\n self._columns = status.columns\n self._stats.update(status.stats)\n if status.next_uri is None:\n self._finished = True\n return status.rows","def _batcher(self, rows):\n row_count = 0\n batch = []\n batch_count = 1\n\n total_rows_modified = 0\n throttle_count = 0\n\n i = 0\n for row in rows:\n if row_count > self.batch_size - 1:\n logger.debug(f\"row_count={row_count} batch_size={self.batch_size} and batch={len(batch)}\")\n # Yield the previous batch\n yield batch\n\n # Start the new batch\n batch = []\n batch.append(row)\n row_count = 1\n\n batch_count += 1\n # break # toggle to load one batch only\n else:\n row_count += 1\n batch.append(row)\n\n # Put in a sleep timer to throttle how hard we hit the database\n if self.throttle_time and self.throttle_size and (throttle_count > self.throttle_size - 1):\n logger.info(f\"Sleeping for {self.throttle_time} seconds... row: {i}\")\n time.sleep(int(self.throttle_time))\n throttle_count = 0\n elif self.throttle_time and self.throttle_size:\n throttle_count += 1\n i += 1\n\n yield batch","def fetchmany(self, size=None):\n\n self._check_executed()\n\n if self.rownumber >= self.rowcount:\n return []\n\n end = min(self.rownumber + (size or self.arraysize), self.rowcount)\n result = self._rows[self.rownumber - self._offset : end - self._offset]\n self.rownumber = min(end, len(self._rows) + self._offset)\n\n while (end > self.rownumber) and self.nextset():\n result += self._rows[self.rownumber - self._offset : end - self._offset]\n self.rownumber = min(end, len(self._rows) + self._offset)\n return result","def rows(self):\r\n return Rows(self)","def getAggregatedRows(self, context, obj, aggData):\n return []","def __iter__(self):\n index = len(self._logrecords)\n while index > 0:\n index -= 1\n yield self._logrecords[index]","def rows(self) -> java.util.Collection:\n ...","def rows(self):\r\n raise NotImplementedError","def get_all_rows(self):\n cur = self.cursor()\n sql = (\"SELECT * FROM snapshot_log;\")\n cur.execute(sql)\n r = cur.fetchall()\n #cur.close()\n self.close()\n return r","def __iter__(self):\n counter = 0\n while True:\n if counter < len(self.all_records):\n yield self.all_records[counter]\n else:\n yield self.next()\n counter += 1","def rows(self):\r\n raise NotImplementedError()","def iterrows(self):\n return (self.Row(*row_vals) for row_vals in izip(*self.columns))","def sum(self) -> \"Stream[float]\":\n return self.agg(np.sum).astype(\"float\")","def rows(self):\n out = []\n for row in self.a:\n new = self.new(1, len(row), fake=False)\n new.a[0] = row\n out.append(new)\n return out","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def collect(self):\n if self._completion_status is None or not self._completion_status.done:\n raise RuntimeError(\"No reading until done!\")\n self._completion_status = None\n\n yield from self._data","async def collect(self):\n result = helpers.TotalList()\n async for message in self:\n result.append(message)\n\n result.total = self.total\n return result","def rows (self):\n for row in self._m:\n yield Vector(row)","def rowsums (self):\n return self.values.sum (axis=0)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\n return (self.GetNumberRows() + numRows)","def all(self):\n self.scan()\n return self.entries","def aggregate_results(self):\n\n raise NotImplementedError","def __iter__(self):\r\n results = ResultSet.__iter__(self)\r\n while results:\r\n for obj in results:\r\n yield obj\r\n if self.is_truncated:\r\n self.is_truncated = False\r\n results = self.connection.get_all_rrsets(self.hosted_zone_id, name=self.next_record_name, type=self.next_record_type)\r\n else:\r\n results = None","def __iter__(self):\n batch = []\n for idx in self._sampler:\n batch.append(idx)\n if len(batch) == self._batch_size:\n batch = sum(batch, [])\n yield batch\n batch = []\n if len(batch) > 0:\n batch = sum(batch, [])\n yield batch","def iter_rp(self):\n\n from .rowproxy import RowProxy\n\n itr = iter(self)\n\n headers = next(itr)\n\n row_proxy = RowProxy(headers)\n\n for row in itr:\n yield row_proxy.set_row(row)","def test_iterate_over_stream():\n archive = Archive()\n archive.commit(doc=DataFrameDocument(df=DF1))\n rows = list()\n with archive.open(version=0).open() as reader:\n for row in reader:\n rows.append(row)\n assert rows == [\n (0, 0, ['Alice', 32]),\n (1, 1, ['Bob', 45]),\n (2, 2, ['Claire', 27]),\n (3, 3, ['Alice', 23])\n ]","def getRows(self, context, obj, data, aggData):\n rowNum = obj.get('rowNum', 1)\n obj['rowNum'] = rowNum + 1\n return [[rowNum] + data + [aggData]]","def consume_next(self):\n response = six.next(self._response_iterator)\n self._counter += 1\n\n if self._last_scanned_row_key is None: # first response\n if response.last_scanned_row_key:\n raise InvalidReadRowsResponse()\n\n self._last_scanned_row_key = response.last_scanned_row_key\n\n row = self._row\n cell = self._cell\n\n for chunk in response.chunks:\n\n self._validate_chunk(chunk)\n\n if chunk.reset_row:\n row = self._row = None\n cell = self._cell = self._previous_cell = None\n continue\n\n if row is None:\n row = self._row = PartialRowData(chunk.row_key)\n\n if cell is None:\n cell = self._cell = PartialCellData(\n chunk.row_key,\n chunk.family_name.value,\n chunk.qualifier.value,\n chunk.timestamp_micros,\n chunk.labels,\n chunk.value)\n self._copy_from_previous(cell)\n else:\n cell.append_value(chunk.value)\n\n if chunk.commit_row:\n self._save_current_row()\n row = cell = None\n continue\n\n if chunk.value_size == 0:\n self._save_current_cell()\n cell = None","def _aggregate(self, row):\n if not self._head:\n self._head = self._create_head(row)\n if self._args.head:\n return\n\n if 'key' not in self._state:\n self._state['key'] = self._replace_fields(self._args.key)\n\n if 'begin' not in self._state:\n self._state['begin'] = eval(self._replace_fields(self._args.begin))\n\n if 'reduce' not in self._state:\n self._state['reduce'] = self._replace_fields(self._args.reduce)\n\n if 'result_map' not in self._state:\n self._state['result_map'] = {}\n\n r = list(map(self._convert, row))\n\n key = eval(self._state['key'])\n\n if key not in self._state['result_map']:\n self._state['result_map'][key] = len(self._result)\n entry = deepcopy(self._state['begin'])\n self._result.append([key, entry])\n\n index = self._state['result_map'][key]\n\n ns = {\n '__result__': self._result[index][1],\n 'r': r\n }\n exec(self._state['reduce'], ns)\n self._result[index][1] = ns['__result__']","def readall(self):\n return self._read_range(self._offset)","def __iter__(self):\n for source in self._sources:\n for row in source.__iter__():\n yield row","def get_rows(self):\n return utils.copy_matrix(self.board)","def _read_all(self):\n return self._connector.read_all()","def next(self, num_rows=10):\n\n start = self._cursor\n stop = start + num_rows\n self._cursor += num_rows\n return self._data.iloc[start:stop]","def rows_body(self) -> List[List]:\n return self.rows[1:]","def readlines(self):\n return [line for line in self]","def getAggregatedRows(self, context, obj, aggData):\n raise NotImplementedError()","def flush(self):\n return Cursor(self.data, self.end, self.end)","def __iter__(self):\n for r in self.cursor:\n yield r","def get_rows(self) -> WellsByDimension:\n return self._rows","def rows(self, table_name):\n\n # still sticking to full caching client-side without\n # support for memory-preserving iterators. Given our\n # use case, I think this will be fine. Can always change later\n cursor = self.connection.cursor()\n cursor.execute('SELECT * FROM %s' % table_name)\n rows = [row for row in cursor]\n cursor.close()\n\n return rows","def collect(self):\n while self.proc is not None:\n self.read()\n if not len(self.datalines):\n return\n while len(self.datalines):\n # pop the first node of list\n yield self.datalines.pop(0)","def records(self) -> Generator[Record, None, None]:\n mapping = [(r, self.get_column(r).name) for r in self.query.refs]\n q = self.compose_query()\n log.info(\"Query: %s\", q)\n with self.engine.connect() as conn:\n rp = conn.execution_options(stream_results=True).execute(q)\n while True:\n rows = rp.fetchmany(size=DATA_PAGE)\n if not len(rows):\n break\n for row in rows:\n row_map = row._mapping\n data: Record = {}\n for ref, name in mapping:\n value = sanitize_text(row_map[name])\n if value is not None:\n data[ref] = value\n yield data","def next(self, num_rows=10):\n\n start = self._cursor\n stop = start + num_rows\n self._cursor += num_rows\n return self._data[start:stop]","def get_batch(self):\n result = self.buffer_.get()\n self._async_next()\n return result","def get_batch(self):\n result = self.buffer_.get()\n self._async_next()\n return result","def get_table_rows(self, conn):\n raise NotImplementedError(\"Please implement this method\")","def concat_all(self):\n return self.merge(1)","def __iter__(self):\n if not self.resolved:\n self._resolve_reader()\n\n if isinstance(self.resolved, WriterType):\n raise TypeError('Writer is not iterable')\n\n def gen():\n for row in self.resolved:\n if self.header and self.rowklass:\n row = self.rowklass(*row)\n yield row\n\n return gen()","def peek(self):\n if self._buffer:\n values = self._buffer[0]\n return Record(self.keys(), tuple(map(hydrated, values)))\n while not self._buffer and not self._consumed:\n self.connection.fetch()\n if self._buffer:\n values = self._buffer[0]\n return Record(self.keys(), tuple(map(hydrated, values)))\n raise ResultError(\"End of stream\")","def __iter__(self):\n for item in self._reader:\n yield item","def tsv_rows(self):\n return self.tsv_lines[1:]","async def get(self) -> List[RowProxy]:","def __iter__(self):\n batch = []\n for sample in self.dataset:\n batch.append(sample)\n if len(batch) == self.size:\n yield self.transform(batch)\n batch = []\n if batch:\n # the last batch may be less then batch size.\n yield self.transform(batch)","def get_all(self):\n return ReadingSet(self._set)","def rows(self):\n return self.prov[PROV_ROWS]","def calc_total_rows(self):\n #total_rows = len(self.file_list) - 1 # Minus header\n print('Total number of rows: ' + str(self.tot_rows))\n results.append('Total number of rows: ' + str(self.tot_rows))","def fetchLogRecords(self):\n return self.handler.buffer","def consume(self):\n if self.connection and not self.connection.closed:\n list(self)\n self.connection = None\n return self._summary","def readlines(self):\n return list(self.iterlines())","async def fetch_next_block(self):\n\n results = []\n for _ in range(self._page_size):\n try:\n results.append(await self.__anext__())\n except StopAsyncIteration:\n # no more results\n break\n return results","def append_rows(self, rows):\n for row in rows:\n self.append_row(row)","def getAll(self):\n return self.dataBuffer","def manual_read(self, iterable, force_distinct=True, offset=None,\n limit=None, *args, **kwargs):\n emitted = 0\n unique_rows = set()\n\n for i, row in enumerate(iterable):\n if limit is not None and emitted >= limit:\n break\n\n _row = row[:self.row_length]\n\n if force_distinct:\n _row_hash = hash(tuple(_row))\n\n if _row_hash in unique_rows:\n continue\n\n unique_rows.add(_row_hash)\n\n if offset is None or i >= offset:\n emitted += 1\n\n yield self._format_row(_row, context=kwargs)","def rows(addressed_data):\n stream = iter(addressed_data)\n while True:\n row = []\n a1, a2, data = next(stream)\n try:\n row.extend(bytearray(data))\n for i in range(len(data), 16, len(data)):\n an1, an2, data = next(stream)\n row.extend(bytearray(data))\n if a1 is not None and an1 != a1 + i: break\n if a2 is not None and an2 != a2 + i: break\n finally:\n yield a1, a2, row","def next(self):\n batches = [self._last_batch]\n for step in range(self._num_unrollings):\n batches.append(self._next_batch())\n self._last_batch = batches[-1]\n return batches","def next(self):\n batches = [self._last_batch]\n for step in range(self._num_unrollings):\n batches.append(self._next_batch())\n self._last_batch = batches[-1]\n return batches","def next(self):\n batches = [self._last_batch]\n for step in range(self._num_unrollings):\n batches.append(self._next_batch())\n self._last_batch = batches[-1]\n return batches","def rows(self):\n if self.header is None:\n raise ValueError('header cannot be None.')\n header = list(enumerate(self.header))\n return ({'count': v, **{f: k[i] for i, f in header}} for k, v in self.items())","def rows(self):\n\n return [self._meta.row_class(self, o) for o in self.paginator.page(self._meta.page).object_list]","def __iter__(self):\n return (yield from self.lines)","def as_rows(self, rows: Iterable):\n try:\n out = self.from_rows(rows, columns=self.data.columns, meta_dict=self.meta)\n except AssertionError as exc:\n columns = self.data.columns.tolist()\n firstrow = next(iter(rows))\n raise RuntimeError(\n f\"Passed {len(columns)} columns {columns!r}, but \"\n f\"{len(firstrow)} elements in first row: {firstrow}\"\n ) from exc\n return out","def _yield_rows(self, ws_name):\n for idx, row in self._get_rows(ws_name):\n if idx >= WS_ROW_OFFSETS[ws_name] and \\\n len(row[0].value):\n yield idx, row","def all(self):\n return list(self.iterator())"],"string":"[\n \"async def fetchall(self):\\n\\n self._check_executed()\\n\\n if self._query_id == -1:\\n msg = \\\"query didn't result in a resultset\\\"\\n self._exception_handler(ProgrammingError, msg)\\n\\n result = self._rows[self.rownumber - self._offset :]\\n self.rownumber = len(self._rows) + self._offset\\n\\n # slide the window over the resultset\\n while await self.nextset():\\n result += self._rows\\n self.rownumber = len(self._rows) + self._offset\\n print(\\n \\\"\\\\nresult: \\\",\\n self._rows,\\n \\\"\\\\n\\\\n\\\",\\n )\\n return result\",\n \"def get_all(self):\\r\\n if self.filled_rows < self.rows:\\r\\n return np.roll(self._data, -(self.curr_pos + self.rows - self.filled_rows),\\r\\n axis=0)[:self.filled_rows,:]\\r\\n else:\\r\\n # The buffer has fewer lines in this case\\r\\n return np.roll(self._data, -self.curr_pos,\\r\\n axis=0)\",\n \"def rows(self):\\n return self.Rows(self)\",\n \"def rows(self):\\n if self._cached_rows is None:\\n self._cached_rows = tuple(self.iterrows())\\n return self._cached_rows\",\n \"def total_rows(self):\\n self._fetch_if_needed()\\n # reduce case, count number of lines\\n if self._total_rows is None:\\n return self.count()\\n return self._total_rows\",\n \"def rows(self):\\n return self._row_list\",\n \"def __iter__(self):\\n for row in self.rows:\\n yield row\",\n \"def __iter__(self):\\n return iter(self.__rows)\",\n \"def rows(self):\\n return self.row\",\n \"def __iter__(self):\\n return iter(self.rows)\",\n \"def rows(self) -> List[List]:\\n return self._rows\",\n \"def rows(self):\\r\\n\\r\\n done_sending = False\\r\\n while not done_sending:\\r\\n self._note(\\\"C _not_empty acq?\\\")\\r\\n self.not_empty.acquire()\\r\\n try:\\r\\n self._note(\\\"C _not_empty wait ...\\\")\\r\\n while not self._ready_buffer and not self._closed:\\r\\n self.not_empty.wait()\\r\\n self._note(\\\"C _not_empty got <\\\")\\r\\n\\r\\n if self._ready_buffer:\\r\\n rows = self._ready_buffer\\r\\n self._ready_buffer = None\\r\\n self._note(\\\"C _not_full notify >\\\")\\r\\n self.not_full.notify()\\r\\n\\r\\n for row in rows:\\r\\n yield row\\r\\n else:\\r\\n self._note(\\\"C no buffer\\\")\\r\\n\\r\\n\\r\\n done_sending = self._closed\\r\\n finally:\\r\\n self._note(\\\"_not_empty rel!\\\")\\r\\n self.not_empty.release()\",\n \"def get_rows(self):\\n raise NotImplementedError('Subclass this to make the rows')\",\n \"def rows(self):\\n return list(self)\",\n \"def rows(self):\\n with self.input().open('r') as fobj:\\n for line in fobj:\\n yield line.strip('\\\\n').split('\\\\t')\",\n \"def _write_rows(self):\\n try:\\n xf = self._writer.xf.send(True)\\n except StopIteration:\\n self._already_saved()\\n\\n with xf.element(\\\"sheetData\\\"):\\n row_idx = 1\\n try:\\n while True:\\n row = (yield)\\n row = self._values_to_row(row, row_idx)\\n self._writer.write_row(xf, row, row_idx)\\n row_idx += 1\\n except GeneratorExit:\\n pass\\n\\n self._writer.xf.send(None)\",\n \"def fetchall(self):\\n self._check_closed()\\n\\n fetched_rows = []\\n while True:\\n row = self.fetchone()\\n if row is None:\\n break\\n else:\\n fetched_rows.append(row)\\n return fetched_rows\",\n \"def get_rows(self) -> QuerySet:\\n return self.get_source_query().values(*self.COLUMNS)\",\n \"def rows(self):\\r\\n _rows = []\\r\\n try:\\r\\n csv_file = open(self.file_path,'rbU')\\r\\n csv_rows = csv.DictReader(csv_file)\\r\\n for row in csv_rows:\\r\\n _rows.append(row)\\r\\n csv_file.close()\\r\\n return _rows\\r\\n except:\\r\\n return _rows\",\n \"def fetch(self):\\n # type: () -> List[List[Any]]\\n if self._request.next_uri is None:\\n self._finished = True\\n return []\\n response = self._request.get(self._request.next_uri)\\n status = self._request.process(response)\\n if status.columns:\\n self._columns = status.columns\\n self._stats.update(status.stats)\\n if status.next_uri is None:\\n self._finished = True\\n return status.rows\",\n \"def _batcher(self, rows):\\n row_count = 0\\n batch = []\\n batch_count = 1\\n\\n total_rows_modified = 0\\n throttle_count = 0\\n\\n i = 0\\n for row in rows:\\n if row_count > self.batch_size - 1:\\n logger.debug(f\\\"row_count={row_count} batch_size={self.batch_size} and batch={len(batch)}\\\")\\n # Yield the previous batch\\n yield batch\\n\\n # Start the new batch\\n batch = []\\n batch.append(row)\\n row_count = 1\\n\\n batch_count += 1\\n # break # toggle to load one batch only\\n else:\\n row_count += 1\\n batch.append(row)\\n\\n # Put in a sleep timer to throttle how hard we hit the database\\n if self.throttle_time and self.throttle_size and (throttle_count > self.throttle_size - 1):\\n logger.info(f\\\"Sleeping for {self.throttle_time} seconds... row: {i}\\\")\\n time.sleep(int(self.throttle_time))\\n throttle_count = 0\\n elif self.throttle_time and self.throttle_size:\\n throttle_count += 1\\n i += 1\\n\\n yield batch\",\n \"def fetchmany(self, size=None):\\n\\n self._check_executed()\\n\\n if self.rownumber >= self.rowcount:\\n return []\\n\\n end = min(self.rownumber + (size or self.arraysize), self.rowcount)\\n result = self._rows[self.rownumber - self._offset : end - self._offset]\\n self.rownumber = min(end, len(self._rows) + self._offset)\\n\\n while (end > self.rownumber) and self.nextset():\\n result += self._rows[self.rownumber - self._offset : end - self._offset]\\n self.rownumber = min(end, len(self._rows) + self._offset)\\n return result\",\n \"def rows(self):\\r\\n return Rows(self)\",\n \"def getAggregatedRows(self, context, obj, aggData):\\n return []\",\n \"def __iter__(self):\\n index = len(self._logrecords)\\n while index > 0:\\n index -= 1\\n yield self._logrecords[index]\",\n \"def rows(self) -> java.util.Collection:\\n ...\",\n \"def rows(self):\\r\\n raise NotImplementedError\",\n \"def get_all_rows(self):\\n cur = self.cursor()\\n sql = (\\\"SELECT * FROM snapshot_log;\\\")\\n cur.execute(sql)\\n r = cur.fetchall()\\n #cur.close()\\n self.close()\\n return r\",\n \"def __iter__(self):\\n counter = 0\\n while True:\\n if counter < len(self.all_records):\\n yield self.all_records[counter]\\n else:\\n yield self.next()\\n counter += 1\",\n \"def rows(self):\\r\\n raise NotImplementedError()\",\n \"def iterrows(self):\\n return (self.Row(*row_vals) for row_vals in izip(*self.columns))\",\n \"def sum(self) -> \\\"Stream[float]\\\":\\n return self.agg(np.sum).astype(\\\"float\\\")\",\n \"def rows(self):\\n out = []\\n for row in self.a:\\n new = self.new(1, len(row), fake=False)\\n new.a[0] = row\\n out.append(new)\\n return out\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def collect(self):\\n if self._completion_status is None or not self._completion_status.done:\\n raise RuntimeError(\\\"No reading until done!\\\")\\n self._completion_status = None\\n\\n yield from self._data\",\n \"async def collect(self):\\n result = helpers.TotalList()\\n async for message in self:\\n result.append(message)\\n\\n result.total = self.total\\n return result\",\n \"def rows (self):\\n for row in self._m:\\n yield Vector(row)\",\n \"def rowsums (self):\\n return self.values.sum (axis=0)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def AppendRows(self, numRows=1): # real signature unknown; restored from __doc__\\n return (self.GetNumberRows() + numRows)\",\n \"def all(self):\\n self.scan()\\n return self.entries\",\n \"def aggregate_results(self):\\n\\n raise NotImplementedError\",\n \"def __iter__(self):\\r\\n results = ResultSet.__iter__(self)\\r\\n while results:\\r\\n for obj in results:\\r\\n yield obj\\r\\n if self.is_truncated:\\r\\n self.is_truncated = False\\r\\n results = self.connection.get_all_rrsets(self.hosted_zone_id, name=self.next_record_name, type=self.next_record_type)\\r\\n else:\\r\\n results = None\",\n \"def __iter__(self):\\n batch = []\\n for idx in self._sampler:\\n batch.append(idx)\\n if len(batch) == self._batch_size:\\n batch = sum(batch, [])\\n yield batch\\n batch = []\\n if len(batch) > 0:\\n batch = sum(batch, [])\\n yield batch\",\n \"def iter_rp(self):\\n\\n from .rowproxy import RowProxy\\n\\n itr = iter(self)\\n\\n headers = next(itr)\\n\\n row_proxy = RowProxy(headers)\\n\\n for row in itr:\\n yield row_proxy.set_row(row)\",\n \"def test_iterate_over_stream():\\n archive = Archive()\\n archive.commit(doc=DataFrameDocument(df=DF1))\\n rows = list()\\n with archive.open(version=0).open() as reader:\\n for row in reader:\\n rows.append(row)\\n assert rows == [\\n (0, 0, ['Alice', 32]),\\n (1, 1, ['Bob', 45]),\\n (2, 2, ['Claire', 27]),\\n (3, 3, ['Alice', 23])\\n ]\",\n \"def getRows(self, context, obj, data, aggData):\\n rowNum = obj.get('rowNum', 1)\\n obj['rowNum'] = rowNum + 1\\n return [[rowNum] + data + [aggData]]\",\n \"def consume_next(self):\\n response = six.next(self._response_iterator)\\n self._counter += 1\\n\\n if self._last_scanned_row_key is None: # first response\\n if response.last_scanned_row_key:\\n raise InvalidReadRowsResponse()\\n\\n self._last_scanned_row_key = response.last_scanned_row_key\\n\\n row = self._row\\n cell = self._cell\\n\\n for chunk in response.chunks:\\n\\n self._validate_chunk(chunk)\\n\\n if chunk.reset_row:\\n row = self._row = None\\n cell = self._cell = self._previous_cell = None\\n continue\\n\\n if row is None:\\n row = self._row = PartialRowData(chunk.row_key)\\n\\n if cell is None:\\n cell = self._cell = PartialCellData(\\n chunk.row_key,\\n chunk.family_name.value,\\n chunk.qualifier.value,\\n chunk.timestamp_micros,\\n chunk.labels,\\n chunk.value)\\n self._copy_from_previous(cell)\\n else:\\n cell.append_value(chunk.value)\\n\\n if chunk.commit_row:\\n self._save_current_row()\\n row = cell = None\\n continue\\n\\n if chunk.value_size == 0:\\n self._save_current_cell()\\n cell = None\",\n \"def _aggregate(self, row):\\n if not self._head:\\n self._head = self._create_head(row)\\n if self._args.head:\\n return\\n\\n if 'key' not in self._state:\\n self._state['key'] = self._replace_fields(self._args.key)\\n\\n if 'begin' not in self._state:\\n self._state['begin'] = eval(self._replace_fields(self._args.begin))\\n\\n if 'reduce' not in self._state:\\n self._state['reduce'] = self._replace_fields(self._args.reduce)\\n\\n if 'result_map' not in self._state:\\n self._state['result_map'] = {}\\n\\n r = list(map(self._convert, row))\\n\\n key = eval(self._state['key'])\\n\\n if key not in self._state['result_map']:\\n self._state['result_map'][key] = len(self._result)\\n entry = deepcopy(self._state['begin'])\\n self._result.append([key, entry])\\n\\n index = self._state['result_map'][key]\\n\\n ns = {\\n '__result__': self._result[index][1],\\n 'r': r\\n }\\n exec(self._state['reduce'], ns)\\n self._result[index][1] = ns['__result__']\",\n \"def readall(self):\\n return self._read_range(self._offset)\",\n \"def __iter__(self):\\n for source in self._sources:\\n for row in source.__iter__():\\n yield row\",\n \"def get_rows(self):\\n return utils.copy_matrix(self.board)\",\n \"def _read_all(self):\\n return self._connector.read_all()\",\n \"def next(self, num_rows=10):\\n\\n start = self._cursor\\n stop = start + num_rows\\n self._cursor += num_rows\\n return self._data.iloc[start:stop]\",\n \"def rows_body(self) -> List[List]:\\n return self.rows[1:]\",\n \"def readlines(self):\\n return [line for line in self]\",\n \"def getAggregatedRows(self, context, obj, aggData):\\n raise NotImplementedError()\",\n \"def flush(self):\\n return Cursor(self.data, self.end, self.end)\",\n \"def __iter__(self):\\n for r in self.cursor:\\n yield r\",\n \"def get_rows(self) -> WellsByDimension:\\n return self._rows\",\n \"def rows(self, table_name):\\n\\n # still sticking to full caching client-side without\\n # support for memory-preserving iterators. Given our\\n # use case, I think this will be fine. Can always change later\\n cursor = self.connection.cursor()\\n cursor.execute('SELECT * FROM %s' % table_name)\\n rows = [row for row in cursor]\\n cursor.close()\\n\\n return rows\",\n \"def collect(self):\\n while self.proc is not None:\\n self.read()\\n if not len(self.datalines):\\n return\\n while len(self.datalines):\\n # pop the first node of list\\n yield self.datalines.pop(0)\",\n \"def records(self) -> Generator[Record, None, None]:\\n mapping = [(r, self.get_column(r).name) for r in self.query.refs]\\n q = self.compose_query()\\n log.info(\\\"Query: %s\\\", q)\\n with self.engine.connect() as conn:\\n rp = conn.execution_options(stream_results=True).execute(q)\\n while True:\\n rows = rp.fetchmany(size=DATA_PAGE)\\n if not len(rows):\\n break\\n for row in rows:\\n row_map = row._mapping\\n data: Record = {}\\n for ref, name in mapping:\\n value = sanitize_text(row_map[name])\\n if value is not None:\\n data[ref] = value\\n yield data\",\n \"def next(self, num_rows=10):\\n\\n start = self._cursor\\n stop = start + num_rows\\n self._cursor += num_rows\\n return self._data[start:stop]\",\n \"def get_batch(self):\\n result = self.buffer_.get()\\n self._async_next()\\n return result\",\n \"def get_batch(self):\\n result = self.buffer_.get()\\n self._async_next()\\n return result\",\n \"def get_table_rows(self, conn):\\n raise NotImplementedError(\\\"Please implement this method\\\")\",\n \"def concat_all(self):\\n return self.merge(1)\",\n \"def __iter__(self):\\n if not self.resolved:\\n self._resolve_reader()\\n\\n if isinstance(self.resolved, WriterType):\\n raise TypeError('Writer is not iterable')\\n\\n def gen():\\n for row in self.resolved:\\n if self.header and self.rowklass:\\n row = self.rowklass(*row)\\n yield row\\n\\n return gen()\",\n \"def peek(self):\\n if self._buffer:\\n values = self._buffer[0]\\n return Record(self.keys(), tuple(map(hydrated, values)))\\n while not self._buffer and not self._consumed:\\n self.connection.fetch()\\n if self._buffer:\\n values = self._buffer[0]\\n return Record(self.keys(), tuple(map(hydrated, values)))\\n raise ResultError(\\\"End of stream\\\")\",\n \"def __iter__(self):\\n for item in self._reader:\\n yield item\",\n \"def tsv_rows(self):\\n return self.tsv_lines[1:]\",\n \"async def get(self) -> List[RowProxy]:\",\n \"def __iter__(self):\\n batch = []\\n for sample in self.dataset:\\n batch.append(sample)\\n if len(batch) == self.size:\\n yield self.transform(batch)\\n batch = []\\n if batch:\\n # the last batch may be less then batch size.\\n yield self.transform(batch)\",\n \"def get_all(self):\\n return ReadingSet(self._set)\",\n \"def rows(self):\\n return self.prov[PROV_ROWS]\",\n \"def calc_total_rows(self):\\n #total_rows = len(self.file_list) - 1 # Minus header\\n print('Total number of rows: ' + str(self.tot_rows))\\n results.append('Total number of rows: ' + str(self.tot_rows))\",\n \"def fetchLogRecords(self):\\n return self.handler.buffer\",\n \"def consume(self):\\n if self.connection and not self.connection.closed:\\n list(self)\\n self.connection = None\\n return self._summary\",\n \"def readlines(self):\\n return list(self.iterlines())\",\n \"async def fetch_next_block(self):\\n\\n results = []\\n for _ in range(self._page_size):\\n try:\\n results.append(await self.__anext__())\\n except StopAsyncIteration:\\n # no more results\\n break\\n return results\",\n \"def append_rows(self, rows):\\n for row in rows:\\n self.append_row(row)\",\n \"def getAll(self):\\n return self.dataBuffer\",\n \"def manual_read(self, iterable, force_distinct=True, offset=None,\\n limit=None, *args, **kwargs):\\n emitted = 0\\n unique_rows = set()\\n\\n for i, row in enumerate(iterable):\\n if limit is not None and emitted >= limit:\\n break\\n\\n _row = row[:self.row_length]\\n\\n if force_distinct:\\n _row_hash = hash(tuple(_row))\\n\\n if _row_hash in unique_rows:\\n continue\\n\\n unique_rows.add(_row_hash)\\n\\n if offset is None or i >= offset:\\n emitted += 1\\n\\n yield self._format_row(_row, context=kwargs)\",\n \"def rows(addressed_data):\\n stream = iter(addressed_data)\\n while True:\\n row = []\\n a1, a2, data = next(stream)\\n try:\\n row.extend(bytearray(data))\\n for i in range(len(data), 16, len(data)):\\n an1, an2, data = next(stream)\\n row.extend(bytearray(data))\\n if a1 is not None and an1 != a1 + i: break\\n if a2 is not None and an2 != a2 + i: break\\n finally:\\n yield a1, a2, row\",\n \"def next(self):\\n batches = [self._last_batch]\\n for step in range(self._num_unrollings):\\n batches.append(self._next_batch())\\n self._last_batch = batches[-1]\\n return batches\",\n \"def next(self):\\n batches = [self._last_batch]\\n for step in range(self._num_unrollings):\\n batches.append(self._next_batch())\\n self._last_batch = batches[-1]\\n return batches\",\n \"def next(self):\\n batches = [self._last_batch]\\n for step in range(self._num_unrollings):\\n batches.append(self._next_batch())\\n self._last_batch = batches[-1]\\n return batches\",\n \"def rows(self):\\n if self.header is None:\\n raise ValueError('header cannot be None.')\\n header = list(enumerate(self.header))\\n return ({'count': v, **{f: k[i] for i, f in header}} for k, v in self.items())\",\n \"def rows(self):\\n\\n return [self._meta.row_class(self, o) for o in self.paginator.page(self._meta.page).object_list]\",\n \"def __iter__(self):\\n return (yield from self.lines)\",\n \"def as_rows(self, rows: Iterable):\\n try:\\n out = self.from_rows(rows, columns=self.data.columns, meta_dict=self.meta)\\n except AssertionError as exc:\\n columns = self.data.columns.tolist()\\n firstrow = next(iter(rows))\\n raise RuntimeError(\\n f\\\"Passed {len(columns)} columns {columns!r}, but \\\"\\n f\\\"{len(firstrow)} elements in first row: {firstrow}\\\"\\n ) from exc\\n return out\",\n \"def _yield_rows(self, ws_name):\\n for idx, row in self._get_rows(ws_name):\\n if idx >= WS_ROW_OFFSETS[ws_name] and \\\\\\n len(row[0].value):\\n yield idx, row\",\n \"def all(self):\\n return list(self.iterator())\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6823442","0.64770746","0.63634026","0.62843436","0.6277957","0.62755823","0.6224927","0.6217208","0.61437726","0.61001796","0.6064008","0.60063374","0.5994555","0.5987653","0.59443873","0.5943947","0.59357786","0.5925868","0.5912474","0.58995414","0.58987916","0.5876134","0.58672154","0.58572114","0.5848336","0.58467054","0.5837792","0.5836687","0.58012855","0.57897997","0.5785563","0.5773531","0.5734113","0.5731565","0.5731565","0.5710278","0.57064825","0.5705274","0.5700963","0.56879175","0.56879175","0.56879175","0.56879175","0.56879175","0.56879175","0.56879175","0.56413233","0.5639951","0.56315833","0.56300503","0.5598481","0.5594402","0.5587412","0.55853856","0.5580807","0.5578964","0.5525954","0.55074614","0.5500395","0.54967976","0.5491583","0.5483386","0.54794717","0.54736245","0.5470093","0.54685473","0.54637474","0.5452399","0.5451588","0.5447971","0.5430902","0.5430902","0.5421423","0.54203176","0.5413632","0.54117906","0.5408773","0.54038954","0.5397978","0.539415","0.5388738","0.5387775","0.53771317","0.53693414","0.53650796","0.5364764","0.5336646","0.53346914","0.5332825","0.5328605","0.5324315","0.5317197","0.5317197","0.5317197","0.531313","0.5307871","0.5302985","0.53010905","0.52953565","0.52941895"],"string":"[\n \"0.6823442\",\n \"0.64770746\",\n \"0.63634026\",\n \"0.62843436\",\n \"0.6277957\",\n \"0.62755823\",\n \"0.6224927\",\n \"0.6217208\",\n \"0.61437726\",\n \"0.61001796\",\n \"0.6064008\",\n \"0.60063374\",\n \"0.5994555\",\n \"0.5987653\",\n \"0.59443873\",\n \"0.5943947\",\n \"0.59357786\",\n \"0.5925868\",\n \"0.5912474\",\n \"0.58995414\",\n \"0.58987916\",\n \"0.5876134\",\n \"0.58672154\",\n \"0.58572114\",\n \"0.5848336\",\n \"0.58467054\",\n \"0.5837792\",\n \"0.5836687\",\n \"0.58012855\",\n \"0.57897997\",\n \"0.5785563\",\n \"0.5773531\",\n \"0.5734113\",\n \"0.5731565\",\n \"0.5731565\",\n \"0.5710278\",\n \"0.57064825\",\n \"0.5705274\",\n \"0.5700963\",\n \"0.56879175\",\n \"0.56879175\",\n \"0.56879175\",\n \"0.56879175\",\n \"0.56879175\",\n \"0.56879175\",\n \"0.56879175\",\n \"0.56413233\",\n \"0.5639951\",\n \"0.56315833\",\n \"0.56300503\",\n \"0.5598481\",\n \"0.5594402\",\n \"0.5587412\",\n \"0.55853856\",\n \"0.5580807\",\n \"0.5578964\",\n \"0.5525954\",\n \"0.55074614\",\n \"0.5500395\",\n \"0.54967976\",\n \"0.5491583\",\n \"0.5483386\",\n \"0.54794717\",\n \"0.54736245\",\n \"0.5470093\",\n \"0.54685473\",\n \"0.54637474\",\n \"0.5452399\",\n \"0.5451588\",\n \"0.5447971\",\n \"0.5430902\",\n \"0.5430902\",\n \"0.5421423\",\n \"0.54203176\",\n \"0.5413632\",\n \"0.54117906\",\n \"0.5408773\",\n \"0.54038954\",\n \"0.5397978\",\n \"0.539415\",\n \"0.5388738\",\n \"0.5387775\",\n \"0.53771317\",\n \"0.53693414\",\n \"0.53650796\",\n \"0.5364764\",\n \"0.5336646\",\n \"0.53346914\",\n \"0.5332825\",\n \"0.5328605\",\n \"0.5324315\",\n \"0.5317197\",\n \"0.5317197\",\n \"0.5317197\",\n \"0.531313\",\n \"0.5307871\",\n \"0.5302985\",\n \"0.53010905\",\n \"0.52953565\",\n \"0.52941895\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6456861"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":83498,"cells":{"query":{"kind":"string","value":"Cancels the iterator, closing the stream."},"document":{"kind":"string","value":"def cancel(self):\n self._response_iterator.cancel()"},"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 close(self):\n if callable(getattr(self._file, 'close', None)):\n self._iterator.close()\n self._iterator = None\n self._unconsumed = None\n self.closed = True","def close(self):\n if self.closed:\n return\n self._stream.close()\n self._stream = None","def close(self):\n self._stream.close()\n self._stream = None","def cancel(self):\n self.filename = None\n self.close()","def cancel(self):\n\n self.end()\n super().cancel()","def cancel(self):\n if self.outFile:\n self.outFile.close()\n if os.path.exists(self.outpath):\n os.remove(self.outpath)","def close(istream):\n # e.g. close files or disconnect apis\n istream.close()","def _close_stream(self):\n if self.stream:\n try:\n if not self.stream.closed:\n self.stream.flush()\n self.stream.close()\n finally:\n self.stream = None","def close(self):\n self._raw_stream.close()","def close(self):\n logging.debug(\"Closing stream\")\n # pyserial cancel_read doesn't seem to work, therefore we ask the reader thread to close things for us\n self._wantExit = True\n if self._rxThread != threading.current_thread():\n self._rxThread.join() # wait for it to exit","def stop_stream(self):\n pass","def close(self) -> None:\n self._stream.close()","def cancel(self):\n self.__canceled = True","def close(self):\n try:\n self.throw(GeneratorExit)\n except (GeneratorExit, StopIteration):\n pass\n else:\n raise RuntimeError(\"generator ignored GeneratorExit\")","def cancel(self):\n self.cancelled = True","def cancel(self):\n self.cancelled = True","def close(self):\n self._state = Computation.STATE_COMPLETED\n if self._stream:\n self._stream.close()\n self._stream = None","def cancel(self):\n pass","def close(self):\n try:\n self._close_stream()\n self._close_stream_lock()\n finally:\n self.stream = None\n self.stream_lock = None","def close(self):\n self._normal_close = True\n\n self.cancel()","def close(self):\n self.p.close(self.inStream)","def close(self):\r\n if self._session:\r\n self._session.close()\r\n self._session = None\r\n try:\r\n self._writer.remove_file()\r\n self._reader.remove_file()\r\n except Oct2PyError:\r\n pass","def close_stream(self):\n sel.socket.close()","def stop(self) -> None:\n self._stream.stop()","def _cancel(self, d):\n if self._finished:\n return\n try:\n raise CancelledError()\n except:\n self._caught_failure = failure.Failure()\n self._iterate()","def cancelChanges(self):\n self.close()","def close(self):\n self.stream.stop_stream()\n self.stream.close()\n self.p.terminate()","def cancel():","def stop_rec(self):\r\n if self._csv_file is not None:\r\n if not self._csv_file.closed:\r\n self._csv_file.close()","def cancel(self):\n self.cancelled.set()","def stream_closed(self,stream):\n pass","def close(self):\n self.closed = True\n for stream in self.streams:\n stream.close()","def check_for_cancellation(self) -> Iterator:\n yield","def stop(self) -> None:\n self._stream.stop()","def cancel(self):","def cancel(self):","def cancel(self):","def stop(self):\n\t\tself.stream.stop_stream()","def close(self):\n self._run_process_pending_rows = False","def close(self):\n self.closed = True\n for cursor in self.cursors:\n try:\n cursor.close()\n except exceptions.Error:\n pass # already closed","def rollback(self):\n self.stream.seek(0)","def _cancel(self):\n now = LOOP_TIME()\n next_ = self.last + USER_CHUNK_TIMEOUT\n if next_ > now:\n self.timer = KOKORO.call_at(next_, type(self)._cancel, self)\n else:\n self.timer = None\n self.waiter.set_result_if_pending(False)","def __del__(self):\n if self.reader is not None:\n self.reader.close()","def remove(self):\n self.iterator.remove()","def _onCancel(self):\n\n self.close()","def close(self):\n self.read1_batch = None\n self.read2_batch = None\n self.writer.close()","def close(self):\n self.file.close()\n self.file = None","def stream_reset(self, stream_id):\n if stream_id in self.flow_control_futures:\n future = self.flow_control_futures.pop(stream_id)\n future.cancel()","def close(self):\n try:\n self._stream.close()\n except AttributeError:\n raise _plotly_utils.exceptions.PlotlyError(\n \"Stream has not been opened yet.\"\n )","def do_cancel(self):\r\n self.write({'cancelled': True})","def cancel(self):\n self.stop()\n self.make_callback('canceled')","def endTasks():\n __terminalState.bufferedReaderTask.cancel()","def stop(self):\n\t\tself.running = False\n\t\tself.data_source.close()\n\t\tfor protocol in self.protocols:\n\t\t\tprotocol.close()\n\t\tprint('%s IO closed' % self.name)","def cancel(self):\n # type: () -> None\n if self.query_id is None or self.is_finished():\n return\n\n self._cancelled = True\n url = self._request.get_url(\"/v1/query/{}\".format(self.query_id))\n logger.debug(\"cancelling query: %s\", self.query_id)\n response = self._request.delete(url)\n logger.info(response)\n if response.status_code == requests.codes.no_content:\n logger.debug(\"query cancelled: %s\", self.query_id)\n return\n self._request.raise_response_error(response)","def cancel(self):\n self._task.cancel()","def close(self) -> None:\n if self.writer:\n try:\n self.writer.close()\n except Exception: # pylint: disable=W0703\n pass\n self.writer = None","def close( self ):\n self.__del__()","def cancel(self):\n raise NotImplementedError(\n u\"%s: Method not implemented\", self.__class__.__name__)","def cancel(self):\n self.succeeded = False\n self.reject()","def cancel(self):\n self.succeeded = False\n self.reject()","def cancel(self):\n self.succeeded = False\n self.reject()","def cancel(self):\n self.succeeded = False\n self.reject()","def _close_stream(p, stream):\n stream.stop_stream()\n stream.close()\n p.terminate()","def _close(self):\n self.fh.close()","def close(self):\n file = self.file\n self.file = None\n self.filename = None\n self.current_line = None\n file.close()","def close(self, reason=''):\n self.clear()","def cancel(self):\n path = 'auditlogEntryReport'\n return self._session.delete(path)","def close_stream(self, id, reason):\r\n self.c.close_stream(id, reason)","def close(self):\n self._closed = True\n self._writer.close()","def cancel(self) -> asyncio.Future:\n pass # pragma: no cover","def close(self):\n if self.current_file_number is not None:\n self.fh_raw.close()\n self.current_file_number = None","def close(self):\n\n self.r.close()","def close(self):\n if self._open:\n self._open = False","def destroy_input_stream(self):\n\n # Destroy the stream\n del self.inp\n\n # Garbage collect\n gc.collect()","def stop(self):\n self.stream.stop()\n self.running = False","def __del__(self):\n self._writer.close()","def close(self):\n self.flush()\n self.file.close()\n self.file = None","def canceled(self):\n self.reject()","def close(self):\n self._s.close()","def cancel(self, id):\n def _cancel(pipe):\n if self.redis.zrank(self.feed_claimed, id) is None:\n return # raise exception?\n pipe.multi()\n pipe.hincrby(self.feed_cancelled, id, 1)\n pipe.lpush(self.feed_ids, id)\n pipe.zrem(self.feed_claimed, id)\n \n self.redis.transaction(_cancel, self.feed_claimed)","def close(self):\n self.file_out.close()","def stop(self):\n \n for watched_file in self._watched_files:\n watched_file.close()","def Close(self):\n super(CPIOArchiveFile, self).Close()\n self._file_entries = None","def stop(self):\n # Get the current future instance\n future = self.future\n\n # Cancel the job\n if future:\n future.cancel()","def cancel(self):\n LOG.debug('cancelling %s', self)\n self._cancelled = True\n self.clear_callbacks() # not strictly necessary, but may release references\n while True:\n try:\n self._waitables.get_nowait().put_nowait(self.sentinel)\n except queue.Empty:\n break","def cancel(self):\n self.waiter.set_result_if_pending(True)\n \n timer = self.timer\n if (timer is not None):\n self.timer = None\n timer.cancel()","def __del__(self):\n if not getattr(self, \"closed\", True):\n self.close()","def close(self) -> None:\n self._close_impl(invalidate=False)","def close(self):\n if self._key is not None:\n logger.debug('StObjectDelete(key)')\n self._lib.StObjectDelete(self._key)\n self._key = None\n\n for filepath in self._tmpstandards:\n os.remove(filepath)\n logger.debug('Remove temporary standard: %s', filepath)\n\n self.reset()","def close(self, reason):\n self.clear()","def close(self, reason):\n self.clear()","def cancel(self):\r\n self.require_item()\r\n\r\n url = '{0}/cancel'.format(self.get_url())\r\n request = http.Request('PUT', url)\r\n request.use_xml = False\r\n\r\n return request, parsers.parse_empty","def cancel_retry(self):\n if self._cancel_retry is not None:\n self._cancel_retry.cancel()\n self._cancel_retry = None","def cancel_retry(self):\n if self._cancel_retry is not None:\n self._cancel_retry.cancel()\n self._cancel_retry = None","def close(self):\n self.out_file.close()","def close(self):\r\n if not self.closed:\r\n for result in self._decrefAsync():\r\n pass","def close(self) -> None:\n os.remove(self.FILE_NAME)","async def close(self):\n await self.flush()\n await self.abort()","def close(self):\n self._isOpen = False","async def close(self):\n self.writer.close()\n await self.writer.wait_closed()\n self.reader = None\n self.writer = None\n self.ref = Ref()"],"string":"[\n \"def close(self):\\n if callable(getattr(self._file, 'close', None)):\\n self._iterator.close()\\n self._iterator = None\\n self._unconsumed = None\\n self.closed = True\",\n \"def close(self):\\n if self.closed:\\n return\\n self._stream.close()\\n self._stream = None\",\n \"def close(self):\\n self._stream.close()\\n self._stream = None\",\n \"def cancel(self):\\n self.filename = None\\n self.close()\",\n \"def cancel(self):\\n\\n self.end()\\n super().cancel()\",\n \"def cancel(self):\\n if self.outFile:\\n self.outFile.close()\\n if os.path.exists(self.outpath):\\n os.remove(self.outpath)\",\n \"def close(istream):\\n # e.g. close files or disconnect apis\\n istream.close()\",\n \"def _close_stream(self):\\n if self.stream:\\n try:\\n if not self.stream.closed:\\n self.stream.flush()\\n self.stream.close()\\n finally:\\n self.stream = None\",\n \"def close(self):\\n self._raw_stream.close()\",\n \"def close(self):\\n logging.debug(\\\"Closing stream\\\")\\n # pyserial cancel_read doesn't seem to work, therefore we ask the reader thread to close things for us\\n self._wantExit = True\\n if self._rxThread != threading.current_thread():\\n self._rxThread.join() # wait for it to exit\",\n \"def stop_stream(self):\\n pass\",\n \"def close(self) -> None:\\n self._stream.close()\",\n \"def cancel(self):\\n self.__canceled = True\",\n \"def close(self):\\n try:\\n self.throw(GeneratorExit)\\n except (GeneratorExit, StopIteration):\\n pass\\n else:\\n raise RuntimeError(\\\"generator ignored GeneratorExit\\\")\",\n \"def cancel(self):\\n self.cancelled = True\",\n \"def cancel(self):\\n self.cancelled = True\",\n \"def close(self):\\n self._state = Computation.STATE_COMPLETED\\n if self._stream:\\n self._stream.close()\\n self._stream = None\",\n \"def cancel(self):\\n pass\",\n \"def close(self):\\n try:\\n self._close_stream()\\n self._close_stream_lock()\\n finally:\\n self.stream = None\\n self.stream_lock = None\",\n \"def close(self):\\n self._normal_close = True\\n\\n self.cancel()\",\n \"def close(self):\\n self.p.close(self.inStream)\",\n \"def close(self):\\r\\n if self._session:\\r\\n self._session.close()\\r\\n self._session = None\\r\\n try:\\r\\n self._writer.remove_file()\\r\\n self._reader.remove_file()\\r\\n except Oct2PyError:\\r\\n pass\",\n \"def close_stream(self):\\n sel.socket.close()\",\n \"def stop(self) -> None:\\n self._stream.stop()\",\n \"def _cancel(self, d):\\n if self._finished:\\n return\\n try:\\n raise CancelledError()\\n except:\\n self._caught_failure = failure.Failure()\\n self._iterate()\",\n \"def cancelChanges(self):\\n self.close()\",\n \"def close(self):\\n self.stream.stop_stream()\\n self.stream.close()\\n self.p.terminate()\",\n \"def cancel():\",\n \"def stop_rec(self):\\r\\n if self._csv_file is not None:\\r\\n if not self._csv_file.closed:\\r\\n self._csv_file.close()\",\n \"def cancel(self):\\n self.cancelled.set()\",\n \"def stream_closed(self,stream):\\n pass\",\n \"def close(self):\\n self.closed = True\\n for stream in self.streams:\\n stream.close()\",\n \"def check_for_cancellation(self) -> Iterator:\\n yield\",\n \"def stop(self) -> None:\\n self._stream.stop()\",\n \"def cancel(self):\",\n \"def cancel(self):\",\n \"def cancel(self):\",\n \"def stop(self):\\n\\t\\tself.stream.stop_stream()\",\n \"def close(self):\\n self._run_process_pending_rows = False\",\n \"def close(self):\\n self.closed = True\\n for cursor in self.cursors:\\n try:\\n cursor.close()\\n except exceptions.Error:\\n pass # already closed\",\n \"def rollback(self):\\n self.stream.seek(0)\",\n \"def _cancel(self):\\n now = LOOP_TIME()\\n next_ = self.last + USER_CHUNK_TIMEOUT\\n if next_ > now:\\n self.timer = KOKORO.call_at(next_, type(self)._cancel, self)\\n else:\\n self.timer = None\\n self.waiter.set_result_if_pending(False)\",\n \"def __del__(self):\\n if self.reader is not None:\\n self.reader.close()\",\n \"def remove(self):\\n self.iterator.remove()\",\n \"def _onCancel(self):\\n\\n self.close()\",\n \"def close(self):\\n self.read1_batch = None\\n self.read2_batch = None\\n self.writer.close()\",\n \"def close(self):\\n self.file.close()\\n self.file = None\",\n \"def stream_reset(self, stream_id):\\n if stream_id in self.flow_control_futures:\\n future = self.flow_control_futures.pop(stream_id)\\n future.cancel()\",\n \"def close(self):\\n try:\\n self._stream.close()\\n except AttributeError:\\n raise _plotly_utils.exceptions.PlotlyError(\\n \\\"Stream has not been opened yet.\\\"\\n )\",\n \"def do_cancel(self):\\r\\n self.write({'cancelled': True})\",\n \"def cancel(self):\\n self.stop()\\n self.make_callback('canceled')\",\n \"def endTasks():\\n __terminalState.bufferedReaderTask.cancel()\",\n \"def stop(self):\\n\\t\\tself.running = False\\n\\t\\tself.data_source.close()\\n\\t\\tfor protocol in self.protocols:\\n\\t\\t\\tprotocol.close()\\n\\t\\tprint('%s IO closed' % self.name)\",\n \"def cancel(self):\\n # type: () -> None\\n if self.query_id is None or self.is_finished():\\n return\\n\\n self._cancelled = True\\n url = self._request.get_url(\\\"/v1/query/{}\\\".format(self.query_id))\\n logger.debug(\\\"cancelling query: %s\\\", self.query_id)\\n response = self._request.delete(url)\\n logger.info(response)\\n if response.status_code == requests.codes.no_content:\\n logger.debug(\\\"query cancelled: %s\\\", self.query_id)\\n return\\n self._request.raise_response_error(response)\",\n \"def cancel(self):\\n self._task.cancel()\",\n \"def close(self) -> None:\\n if self.writer:\\n try:\\n self.writer.close()\\n except Exception: # pylint: disable=W0703\\n pass\\n self.writer = None\",\n \"def close( self ):\\n self.__del__()\",\n \"def cancel(self):\\n raise NotImplementedError(\\n u\\\"%s: Method not implemented\\\", self.__class__.__name__)\",\n \"def cancel(self):\\n self.succeeded = False\\n self.reject()\",\n \"def cancel(self):\\n self.succeeded = False\\n self.reject()\",\n \"def cancel(self):\\n self.succeeded = False\\n self.reject()\",\n \"def cancel(self):\\n self.succeeded = False\\n self.reject()\",\n \"def _close_stream(p, stream):\\n stream.stop_stream()\\n stream.close()\\n p.terminate()\",\n \"def _close(self):\\n self.fh.close()\",\n \"def close(self):\\n file = self.file\\n self.file = None\\n self.filename = None\\n self.current_line = None\\n file.close()\",\n \"def close(self, reason=''):\\n self.clear()\",\n \"def cancel(self):\\n path = 'auditlogEntryReport'\\n return self._session.delete(path)\",\n \"def close_stream(self, id, reason):\\r\\n self.c.close_stream(id, reason)\",\n \"def close(self):\\n self._closed = True\\n self._writer.close()\",\n \"def cancel(self) -> asyncio.Future:\\n pass # pragma: no cover\",\n \"def close(self):\\n if self.current_file_number is not None:\\n self.fh_raw.close()\\n self.current_file_number = None\",\n \"def close(self):\\n\\n self.r.close()\",\n \"def close(self):\\n if self._open:\\n self._open = False\",\n \"def destroy_input_stream(self):\\n\\n # Destroy the stream\\n del self.inp\\n\\n # Garbage collect\\n gc.collect()\",\n \"def stop(self):\\n self.stream.stop()\\n self.running = False\",\n \"def __del__(self):\\n self._writer.close()\",\n \"def close(self):\\n self.flush()\\n self.file.close()\\n self.file = None\",\n \"def canceled(self):\\n self.reject()\",\n \"def close(self):\\n self._s.close()\",\n \"def cancel(self, id):\\n def _cancel(pipe):\\n if self.redis.zrank(self.feed_claimed, id) is None:\\n return # raise exception?\\n pipe.multi()\\n pipe.hincrby(self.feed_cancelled, id, 1)\\n pipe.lpush(self.feed_ids, id)\\n pipe.zrem(self.feed_claimed, id)\\n \\n self.redis.transaction(_cancel, self.feed_claimed)\",\n \"def close(self):\\n self.file_out.close()\",\n \"def stop(self):\\n \\n for watched_file in self._watched_files:\\n watched_file.close()\",\n \"def Close(self):\\n super(CPIOArchiveFile, self).Close()\\n self._file_entries = None\",\n \"def stop(self):\\n # Get the current future instance\\n future = self.future\\n\\n # Cancel the job\\n if future:\\n future.cancel()\",\n \"def cancel(self):\\n LOG.debug('cancelling %s', self)\\n self._cancelled = True\\n self.clear_callbacks() # not strictly necessary, but may release references\\n while True:\\n try:\\n self._waitables.get_nowait().put_nowait(self.sentinel)\\n except queue.Empty:\\n break\",\n \"def cancel(self):\\n self.waiter.set_result_if_pending(True)\\n \\n timer = self.timer\\n if (timer is not None):\\n self.timer = None\\n timer.cancel()\",\n \"def __del__(self):\\n if not getattr(self, \\\"closed\\\", True):\\n self.close()\",\n \"def close(self) -> None:\\n self._close_impl(invalidate=False)\",\n \"def close(self):\\n if self._key is not None:\\n logger.debug('StObjectDelete(key)')\\n self._lib.StObjectDelete(self._key)\\n self._key = None\\n\\n for filepath in self._tmpstandards:\\n os.remove(filepath)\\n logger.debug('Remove temporary standard: %s', filepath)\\n\\n self.reset()\",\n \"def close(self, reason):\\n self.clear()\",\n \"def close(self, reason):\\n self.clear()\",\n \"def cancel(self):\\r\\n self.require_item()\\r\\n\\r\\n url = '{0}/cancel'.format(self.get_url())\\r\\n request = http.Request('PUT', url)\\r\\n request.use_xml = False\\r\\n\\r\\n return request, parsers.parse_empty\",\n \"def cancel_retry(self):\\n if self._cancel_retry is not None:\\n self._cancel_retry.cancel()\\n self._cancel_retry = None\",\n \"def cancel_retry(self):\\n if self._cancel_retry is not None:\\n self._cancel_retry.cancel()\\n self._cancel_retry = None\",\n \"def close(self):\\n self.out_file.close()\",\n \"def close(self):\\r\\n if not self.closed:\\r\\n for result in self._decrefAsync():\\r\\n pass\",\n \"def close(self) -> None:\\n os.remove(self.FILE_NAME)\",\n \"async def close(self):\\n await self.flush()\\n await self.abort()\",\n \"def close(self):\\n self._isOpen = False\",\n \"async def close(self):\\n self.writer.close()\\n await self.writer.wait_closed()\\n self.reader = None\\n self.writer = None\\n self.ref = Ref()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.67333686","0.63217324","0.6200361","0.6189285","0.60646605","0.5990257","0.59821737","0.5979769","0.5914633","0.58941954","0.58596677","0.58370185","0.5811813","0.5810032","0.5777921","0.5777921","0.57457614","0.57253283","0.5688793","0.56884354","0.56859386","0.5675942","0.56705","0.5660552","0.56468236","0.5637341","0.5623364","0.56187415","0.56145257","0.561205","0.56076366","0.5580126","0.557805","0.55697054","0.5558347","0.5558347","0.5558347","0.5546934","0.5535446","0.55278283","0.5519521","0.55113035","0.548584","0.5480722","0.54741853","0.54644954","0.5459575","0.5458946","0.5439385","0.54350424","0.542347","0.5387053","0.53852135","0.5383848","0.5382086","0.53785884","0.5378422","0.5357764","0.53556025","0.53556025","0.53556025","0.53556025","0.5354268","0.5340749","0.53372085","0.53159934","0.5311085","0.5303939","0.5303221","0.53026825","0.5297789","0.52963996","0.5283098","0.5266945","0.52647394","0.5264718","0.52600294","0.5236802","0.52305937","0.52295583","0.5229511","0.5229453","0.52248317","0.5221401","0.5218216","0.52160305","0.5214982","0.5206694","0.5206241","0.5201307","0.5201307","0.51967216","0.5189696","0.5189696","0.51882327","0.5185631","0.5181348","0.5180371","0.5168556","0.5168451"],"string":"[\n \"0.67333686\",\n \"0.63217324\",\n \"0.6200361\",\n \"0.6189285\",\n \"0.60646605\",\n \"0.5990257\",\n \"0.59821737\",\n \"0.5979769\",\n \"0.5914633\",\n \"0.58941954\",\n \"0.58596677\",\n \"0.58370185\",\n \"0.5811813\",\n \"0.5810032\",\n \"0.5777921\",\n \"0.5777921\",\n \"0.57457614\",\n \"0.57253283\",\n \"0.5688793\",\n \"0.56884354\",\n \"0.56859386\",\n \"0.5675942\",\n \"0.56705\",\n \"0.5660552\",\n \"0.56468236\",\n \"0.5637341\",\n \"0.5623364\",\n \"0.56187415\",\n \"0.56145257\",\n \"0.561205\",\n \"0.56076366\",\n \"0.5580126\",\n \"0.557805\",\n \"0.55697054\",\n \"0.5558347\",\n \"0.5558347\",\n \"0.5558347\",\n \"0.5546934\",\n \"0.5535446\",\n \"0.55278283\",\n \"0.5519521\",\n \"0.55113035\",\n \"0.548584\",\n \"0.5480722\",\n \"0.54741853\",\n \"0.54644954\",\n \"0.5459575\",\n \"0.5458946\",\n \"0.5439385\",\n \"0.54350424\",\n \"0.542347\",\n \"0.5387053\",\n \"0.53852135\",\n \"0.5383848\",\n \"0.5382086\",\n \"0.53785884\",\n \"0.5378422\",\n \"0.5357764\",\n \"0.53556025\",\n \"0.53556025\",\n \"0.53556025\",\n \"0.53556025\",\n \"0.5354268\",\n \"0.5340749\",\n \"0.53372085\",\n \"0.53159934\",\n \"0.5311085\",\n \"0.5303939\",\n \"0.5303221\",\n \"0.53026825\",\n \"0.5297789\",\n \"0.52963996\",\n \"0.5283098\",\n \"0.5266945\",\n \"0.52647394\",\n \"0.5264718\",\n \"0.52600294\",\n \"0.5236802\",\n \"0.52305937\",\n \"0.52295583\",\n \"0.5229511\",\n \"0.5229453\",\n \"0.52248317\",\n \"0.5221401\",\n \"0.5218216\",\n \"0.52160305\",\n \"0.5214982\",\n \"0.5206694\",\n \"0.5206241\",\n \"0.5201307\",\n \"0.5201307\",\n \"0.51967216\",\n \"0.5189696\",\n \"0.5189696\",\n \"0.51882327\",\n \"0.5185631\",\n \"0.5181348\",\n \"0.5180371\",\n \"0.5168556\",\n \"0.5168451\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.67483526"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":83499,"cells":{"query":{"kind":"string","value":"Consume the next ``ReadRowsResponse`` from the stream. Parse the response and its chunks into a new/existing row in"},"document":{"kind":"string","value":"def consume_next(self):\n response = six.next(self._response_iterator)\n self._counter += 1\n\n if self._last_scanned_row_key is None: # first response\n if response.last_scanned_row_key:\n raise InvalidReadRowsResponse()\n\n self._last_scanned_row_key = response.last_scanned_row_key\n\n row = self._row\n cell = self._cell\n\n for chunk in response.chunks:\n\n self._validate_chunk(chunk)\n\n if chunk.reset_row:\n row = self._row = None\n cell = self._cell = self._previous_cell = None\n continue\n\n if row is None:\n row = self._row = PartialRowData(chunk.row_key)\n\n if cell is None:\n cell = self._cell = PartialCellData(\n chunk.row_key,\n chunk.family_name.value,\n chunk.qualifier.value,\n chunk.timestamp_micros,\n chunk.labels,\n chunk.value)\n self._copy_from_previous(cell)\n else:\n cell.append_value(chunk.value)\n\n if chunk.commit_row:\n self._save_current_row()\n row = cell = None\n continue\n\n if chunk.value_size == 0:\n self._save_current_cell()\n cell = 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":["async def _receive_response_body(\n self, request: Request, stream_id: int\n ) -> typing.AsyncIterator[bytes]:\n while True:\n event = await self._receive_stream_event(request, stream_id)\n if isinstance(event, h2.events.DataReceived):\n amount = event.flow_controlled_length\n self._h2_state.acknowledge_received_data(amount, stream_id)\n await self._write_outgoing_data(request)\n yield event.data\n elif isinstance(event, h2.events.StreamEnded):\n break","def parse_rows(self, response):\n\n for row in csviter(\n response, self.delimiter, self.headers, quotechar=self.quotechar\n ):\n ret = iterate_spider_output(self.parse_row(response, row))\n for result_item in self.process_results(response, ret):\n yield result_item","def next(self):\r\n self.open_read()\r\n data = self.resp.read(self.BufferSize)\r\n if not data:\r\n self.close()\r\n raise StopIteration\r\n return data","def __read_response(self, nblines=-1):\n resp, code, data = (b\"\", None, None)\n cpt = 0\n while True:\n try:\n line = self.__read_line()\n except Response as inst:\n code = inst.code\n data = inst.data\n break\n except Literal as inst:\n resp += self.__read_block(inst.value)\n if not resp.endswith(CRLF):\n resp += self.__read_line() + CRLF\n continue\n if not len(line):\n continue\n resp += line + CRLF\n cpt += 1\n if nblines != -1 and cpt == nblines:\n break\n\n return (code, data, resp)","def parse_row(self, response, row):\n raise NotImplementedError","def state_readChunk(self, fileObj):\n if not self.reader.next(fileObj, self.destination):\n self.readResponse = self.state_finalStatus","async def __parse_csv(responses: SourceResponses) -> Samples:\n rows = []\n for response in responses:\n csv_text = await response.text()\n rows.extend(list(csv.DictReader(StringIO(csv_text.strip(), newline=\"\"))))\n return rows","def _unpack_body(self, buff):\n\n # Unpack <return_code> and <count> (how many records affected or selected)\n self._return_code = struct_L.unpack_from(buff, offset=0)[0]\n\n # Separate return_code and completion_code\n self._completion_status = self._return_code & 0x00ff\n self._return_code >>= 8\n\n # In case of an error unpack the body as an error message\n if self._return_code != 0:\n self._return_message = unicode(buff[4:-1], self.charset, self.errors)\n if self._completion_status == 2:\n raise TarantoolError(self._return_code, self._return_message)\n\n # Unpack <count> (how many records affected or selected)\n self._rowcount = struct_L.unpack_from(buff, offset=4)[0]\n\n # If the response doesn't contain any tuple - there is nothing to unpack\n if self._body_length == 8:\n return\n\n # Parse response tuples (<fq_tuple>)\n if self._rowcount > 0:\n offset = 8 # The first 4 bytes in the response body is the <count> we have already read\n while offset < self._body_length:\n # In resonse tuples have the form <size><tuple> (<fq_tuple> ::= <size><tuple>).\n # Attribute <size> takes into account only size of tuple's <field> payload,\n # but does not include 4-byte of <cardinality> field.\n #Therefore the actual size of the <tuple> is greater to 4 bytes.\n tuple_size = struct.unpack_from(\"<L\", buff, offset)[0] + 4\n tuple_data = struct.unpack_from(\"<%ds\" % (tuple_size), buff, offset+4)[0]\n tuple_value = self._unpack_tuple(tuple_data)\n if self.field_types:\n self.append(self._cast_tuple(tuple_value))\n else:\n self.append(tuple_value)\n\n offset = offset + tuple_size + 4 # This '4' is a size of <size> attribute","def parse_rows_with(reader, parsers):\n for row in reader:\n yield parse_row(row, parsers)","def parse_rows_with(reader, parsers):\n for row in reader:\n yield parse_row(row, parsers)","def next(self):\n self.record_offset += 2 ** self.blockettes[1000]['Data Record Length']\n self._parseHeader()","def parse_rows_with(reader, parsers):\n for row in reader:\n yield parse_row(row,parsers)","def _read_responses(self):\n try:\n while not self.shutting_down:\n try:\n raw_message = self.kernel_socket.recv()\n response_message = json_decode(utf8(raw_message))\n\n msg_id = KernelClient._get_msg_id(response_message, self.log)\n\n if msg_id not in self.response_queues:\n # this will happen when the msg_id is generated by the server\n self.response_queues[msg_id] = queue.Queue()\n\n # insert into queue\n self.log.debug(\"Inserting response for msg_id: {}, msg_type: {}\".\n format(msg_id, response_message['msg_type']))\n self.response_queues.get(msg_id).put_nowait(response_message)\n except BaseException as be1:\n if self.restarting: # If restarting, wait until restart has completed - which includes new socket\n i = 1\n while self.restarting:\n if i >= 10 and i % 2 == 0:\n self.log.debug(\"Still restarting after {} secs...\".format(i))\n time.sleep(1)\n i += 1\n continue\n raise be1\n\n except websocket.WebSocketConnectionClosedException:\n pass # websocket closure most likely due to shutdown\n\n except BaseException as be2:\n if not self.shutting_down:\n self.log.warning('Unexpected exception encountered ({})'.format(be2))\n\n self.log.debug('Response reader thread exiting...')","def receiveLines(self):\n\n\t\tif self.s is None:\n\t\t\traise ConnectionError(\"There was a connection error\")\n\n\t\tif \"\\r\\n\" not in self.buf:\n\t\t\t# Read 1024 bytes from socket try to decode it as UTF-8\n\t\t\t# and append it to buffer.\n\t\t\t# It gets appended because there might be incomplete data\n\t\t\t# from a previous read.\n\t\t\t# Try to decode as UTF-8, replace unknown characters on error\n\t\t\tself.buf = self.buf + self.s.recv(1024).decode(\"utf-8\", \"replace\")\n\t\t\tif not self.buf:\n\t\t\t\tsys.exit(1)\n\n\t\tlines = self.buf.split(\"\\r\\n\", 1)\n\t\tline = lines[0]\n\n\t\tif len(lines) > 1:\n\t\t\tself.buf = lines[1]\n\n\t\tyield line","def _incoming_read(self, client, data, error):\n\n if error is not None:\n client.close()\n del self._incoming[client]\n return\n\n incoming = self._incoming[client]\n incoming.unpacker.feed(data)\n for req_id, message in incoming.unpacker:\n self._call_handler(\n partial(self._queue_response,\n client, req_id),\n self._call_interface.queue_call,\n message,\n )","def get_next_record(self):\n return_dict = {}\n flex_fields = []\n line = self._get_line()\n\n row = next(\n csv.reader([line], dialect='excel', delimiter=self.delimiter))\n if len(row) != self.column_count:\n raise ResponseException(\n \"Wrong number of fields in this row\", StatusCode.CLIENT_ERROR,\n ValueError, ValidationError.readError)\n for idx, cell in enumerate(row):\n if idx >= self.column_count:\n raise ResponseException(\n \"Record contains too many fields\", StatusCode.CLIENT_ERROR,\n ValueError, ValidationError.readError)\n # Use None instead of empty strings for sqlalchemy\n if cell == \"\":\n cell = None\n # self.expected_headers uses the short, machine-readable column\n # names\n if self.expected_headers[idx] is None and self.flex_headers[idx] is not None:\n flex_fields.append(FlexField(header=self.flex_headers[idx], cell=cell))\n # We skip headers which aren't expected and aren't flex\n elif self.expected_headers[idx] is not None:\n return_dict[self.expected_headers[idx]] = cell\n return return_dict, flex_fields","def readResponse(self, numElements=1):\n while 1:\n resp = self.serial.readline().decode()\n if len(resp) > 5 and resp[0:5] == \"ERROR\":\n self._waiting_response = 0\n raise Exception(resp)\n _LOGGER.debug(\"Response %s\" % resp)\n if resp.find('#') > -1:\n self._waiting_response = 0\n break\n if resp == '':\n # nothing coming, have read too many lines\n return None\n respitems = resp.split(\"#\",maxsplit=1)[1].split()\n if numElements == 1:\n return respitems[-1]\n else:\n return respitems[-numElements:]","def next(self, num_rows=10):\n\n start = self._cursor\n stop = start + num_rows\n self._cursor += num_rows\n return self._data[start:stop]","def process(self):\n\n try:\n self._read_buffer += self._socket.recv(4096)\n except socket.error as exc:\n if exc.errno not in [errno.EAGAIN,\n errno.EWOULDBLOCK,\n errno.WSAEWOULDBLOCK]:\n raise\n response, self._read_buffer = Message.decode(self._read_buffer)\n # Check if terminating RESPONSE_VALUE with body 00 01 00 00\n if (response.type == Message.SERVERDATA_RESPONSE_VALUE and\n response.body.encode(\"ascii\") == \"\\x00\\x01\\x00\\x00\"):\n response = Message(self._response[0].id,\n self._response[0].type,\n \"\".join([r.body for r in self._response]))\n self._active_requests[response.id].response = response\n self._response = []\n self._active_requests[response.id]\n elif response.type == Message.SERVERDATA_RESPONSE_VALUE:\n self._response.append(response)\n elif response.type == Message.SERVERDATA_AUTH_RESPONSE:\n self._active_requests[self._response[0].id].response = response\n # Clear empty SERVERDATA_RESPONSE_VALUE sent before\n # SERVERDATA_AUTH_RESPONSE\n self._response = []\n self._active_requests[response.id]","def parse(self, response):\n\n rows = json.loads(response.body.decode('utf-8'))['values']\n rows = [row for row in rows if (len(row) == 12)]\n now = self.start_date.replace(tzinfo=timezone(self.timezone))\n\n for row in rows:\n # Strip leading or trailing whitespace from all values\n for i in range(len(row)):\n row[i] = row[i].strip()\n\n # The JSON omits values for trailing columns with no values. By padding\n # the rows out, the rest of the code can assume there will always be 14\n # columns.\n missing_values = 13 - len(row)\n row.extend([''] * missing_values)\n data = self._parse_row(row)\n yield data\n\n # Only work with the next month's worth of meetings\n # to avoid overloading database\n delta = self._parse_start_datetime(row).replace(tzinfo=timezone(self.timezone)) - now\n if delta.days > 30 or delta.days < 0:\n yield None\n else:\n yield data","def _fetch(self):\n if self.closed():\n raise self.Error(\"Failed to read from closed connection {!r}\".format(self.server.address))\n if self.defunct():\n raise self.Error(\"Failed to read from defunct connection {!r}\".format(self.server.address))\n if not self.responses:\n return 0, 0\n\n self._receive()\n\n details, summary_signature, summary_metadata = self._unpack()\n\n if details:\n log_debug(\"S: RECORD * %d\", len(details)) # TODO\n self.responses[0].on_records(details)\n\n if summary_signature is None:\n return len(details), 0\n\n response = self.responses.popleft()\n response.complete = True\n if summary_signature == SUCCESS:\n log_debug(\"S: SUCCESS (%r)\", summary_metadata)\n response.on_success(summary_metadata or {})\n elif summary_signature == IGNORED:\n self._last_run_statement = None\n log_debug(\"S: IGNORED (%r)\", summary_metadata)\n response.on_ignored(summary_metadata or {})\n elif summary_signature == FAILURE:\n self._last_run_statement = None\n log_debug(\"S: FAILURE (%r)\", summary_metadata)\n response.on_failure(summary_metadata or {})\n else:\n self._last_run_statement = None\n raise ProtocolError(\"Unexpected response message with signature %02X\" % summary_signature)\n\n return len(details), 1","async def async_readchunks(self, size: int):\n while True:\n data = await self.read(size)\n if data:\n await yield_(data)\n else:\n return","def _read_chunk_body(self, data):\n resp = self.current_response\n\n if resp._decompressor:\n resp.body += resp._decompressor.decompress(data[:-2])\n else:\n resp.body += data[:-2]\n\n self._stream.on_read = self._read_chunk_head\n self._stream.read_delimiter = CRLF","def iter_lines(response: requests.Response):\n buffer = b''\n while buffer[-2:] != b'\\r\\n':\n buffer += iter_content(response, 1)\n return buffer[:-2]","def parse_response(self, response: requests.Response) -> Iterable[dict]:\n resp_json = response.json()\n if isinstance(resp_json, list):\n results = resp_json\n else:\n results = resp_json.get(\"items\")\n for row in results:\n yield row","def __iter__(self):\n\n # TODO: handle chunked encoding delimited by marker instead\n # of content-length.\n\n while True:\n length = None\n #if line == (self._boundary+\"\\r\\n\").encode('ascii'):\n while True:\n l = self.response.fp.readline()\n # print(\"Chunk start\")\n # l = self.response.fp.readline()\n # l = self.response.fp.readline()\n # print(l)\n\n if l.startswith(b\"Content-Length:\"):\n length = int(l.split(b\" \")[1])\n # print(\"found length\", length)\n\n if length is not None and l== b\"\\r\\n\":\n break\n\n yield self.response.fp.read(length)\n \n # Look for an empty line, signifying the end of the headers.","def _handle_client_read_data(self, first_value, line_name):\n stream_data = self.server.stream_data\n self._append_value(stream_data[line_name], first_value)\n while True:\n data = self.rfile.readline().strip()\n # TODO: add verbose logging\n #print \"value\", data\n if data == \"\":\n break\n\n # TODO: add verbose logging options\n #print \"[%s-%s] %s: %s\" % (thread_name, self.client_address[0],\n # timestamp(), float(data))\n self._append_value(stream_data[line_name], data)","def __read_line(self):\n ret = b\"\"\n while True:\n try:\n pos = self.__read_buffer.index(CRLF)\n ret = self.__read_buffer[:pos]\n self.__read_buffer = self.__read_buffer[pos + len(CRLF):]\n break\n except ValueError:\n pass\n try:\n nval = self.sock.recv(self.read_size)\n self.__dprint(nval)\n if not len(nval):\n break\n self.__read_buffer += nval\n except (socket.timeout, ssl.SSLError):\n raise Error(\"Failed to read data from the server\")\n\n if len(ret):\n m = self.__size_expr.match(ret)\n if m:\n raise Literal(int(m.group(1)))\n\n m = self.__respcode_expr.match(ret)\n if m:\n if m.group(1) == b\"BYE\":\n raise Error(\"Connection closed by server\")\n if m.group(1) == b\"NO\":\n self.__parse_error(m.group(2))\n raise Response(m.group(1), m.group(2))\n return ret","async def fetch_next_part(self) -> Union[MultipartReader, BodyPartReader]:\n ...","def handle(self):\n line = b\"\"\n try:\n while True:\n raw = self.request.recv(1024)\n if not raw:\n return\n raw = bytearray(raw)\n while True:\n splitter = raw.find(b\"\\r\")\n if splitter > -1:\n line = raw[1:splitter]\n raw = raw[splitter + 1 :]\n else:\n break\n\n self.handle_line(line.decode())\n except Exception as exc:\n _LOGGER.error(\n \"TCP: Handle: last line %s gave error: %s\", line.decode(), str(exc)\n )\n return","def read_chunks(self):\n buf = []\n chunks = []\n delays = []\n if not self.chunked:\n chunks.append(self.read())\n delays.append(0)\n else:\n start = TIMER()\n try:\n while True:\n line = self.fp.readline()\n chunk_size = self._read_chunk_size(line)\n if chunk_size is None:\n raise httplib.IncompleteRead(''.join(chunks))\n if chunk_size == 0:\n break\n delays.append(TIMER() - start)\n chunks.append(self._safe_read(chunk_size))\n self._safe_read(2) # skip the CRLF at the end of the chunk\n start = TIMER()\n\n # Ignore any trailers.\n while True:\n line = self.fp.readline()\n if not line or line == '\\r\\n':\n break\n finally:\n self.close()\n return chunks, delays","def run(self) -> None:\n\n # Track the last timestamp we see. When we fetch_stream() again on the\n # next iteration, we'll start from that timestamp onwards to avoid\n # fetching every single page again. The last event or two will be\n # still be in the response, but our de-duping will ignore those.\n last_timestamp = None\n\n # Keep track of what log entries we've consumed so that we suppress\n # duplicates. Duplicates will arise in our stream due to the way we\n # watch for new entries.\n consumed = set() # type: MutableSet\n\n # How many successful vs failed fetch_stream calls. If we consistently see\n # failures but we never see a successful attempt, we should raise an exception\n # and stop.\n success_count = 0\n failure_count = 0\n\n while not self.stopped.wait(0.2):\n try:\n for entry in fetch_stream(self.stream, start_time = last_timestamp):\n if entry[\"eventId\"] not in consumed:\n consumed.add(entry[\"eventId\"])\n\n last_timestamp = entry[\"timestamp\"]\n\n self.consumer(entry)\n except (ClientError, BotocoreConnectionError):\n failure_count += 1\n if failure_count > MAX_FAILURES and not success_count:\n raise\n else:\n success_count += 1","def _line_iter(self, stream):\n buf = b''\n while True:\n if len(buf) < self.blocksize:\n buf += stream.read(self.blocksize - len(buf))\n if not buf:\n break\n i = buf.find(b'\\n')\n if i < 0:\n yield buf\n buf = b''\n else:\n yield buf[:i + 1]\n buf = buf[i + 1:]","def _receive(self, transport, response_schema, timeout=10):\n in_data = \"\"\n start_time = time.time()\n duration = 0\n while duration < timeout:\n in_data = in_data + transport.receive().decode(self.ENCODING)\n try:\n response = response_schema.load(in_data)\n logger.debug(f\"Received SOS Access Data: {in_data}\")\n return response\n except XMLParseError:\n duration = time.time() - start_time\n continue\n\n raise SOSAccessClientException(\"Reading response within timeout failed\")","async def read_stream(self, stream_read_request_body: StreamReadRequestBody = Body(None, description=\"\")) -> StreamRead:\n adapter = self._create_low_code_adapter(manifest=stream_read_request_body.manifest)\n schema_inferrer = SchemaInferrer()\n\n if stream_read_request_body.record_limit is None:\n record_limit = self.max_record_limit\n else:\n record_limit = min(stream_read_request_body.record_limit, self.max_record_limit)\n\n slices = []\n log_messages = []\n try:\n for message_group in self._get_message_groups(\n adapter.read_stream(stream_read_request_body.stream, stream_read_request_body.config),\n schema_inferrer,\n record_limit,\n ):\n if isinstance(message_group, AirbyteLogMessage):\n log_messages.append({\"message\": message_group.message})\n else:\n slices.append(message_group)\n except Exception as error:\n # TODO: We're temporarily using FastAPI's default exception model. Ideally we should use exceptions defined in the OpenAPI spec\n self.logger.error(f\"Could not perform read with with error: {error.args[0]} - {self._get_stacktrace_as_string(error)}\")\n raise HTTPException(\n status_code=400,\n detail=f\"Could not perform read with with error: {error.args[0]}\",\n )\n\n return StreamRead(\n logs=log_messages,\n slices=slices,\n test_read_limit_reached=self._has_reached_limit(slices),\n inferred_schema=schema_inferrer.get_stream_schema(stream_read_request_body.stream)\n )","async def fetch_next_block(self):\n try:\n return await self._execution_context.fetch_next_block()\n except CosmosHttpResponseError as e:\n if _is_partitioned_execution_info(e): #cross partition query not servable\n query_to_use = self._query if self._query is not None else \"Select * from root r\"\n query_execution_info = _PartitionedQueryExecutionInfo(await self._client._GetQueryPlanThroughGateway\n (query_to_use, self._resource_link))\n self._execution_context = await self._create_pipelined_execution_context(query_execution_info)\n else:\n raise e\n\n return await self._execution_context.fetch_next_block()","async def readchunk(self) -> Tuple[bytes, bool]:\n ...","def process(self):\n self.reader += 1","def GetNextLine(self):\n\t\tline = self._fin.readline()\n\n\t\tif len(line) == 0:\n\t\t\twx.MessageBox(\"All records processed\", \"DONE!\", wx.ICON_INFORMATION | wx.OK)\n\t\t\tself.EndRun()\n\t\t\t\n\t\telse:\n\t\t\tline = line[:-1]\n\t\t\tobj = json.loads(line)\n\t\t\tself._textControl.SetValue(obj[\"description\"])\n\t\t\tself._existingClass = obj[\"class\"]\n\t\t\tself._existingClassLabel.SetLabel(obj[\"class\"])","async def _stream_next_event(stream):\n while True:\n last_new_line = False\n data = b\"\"\n\n while True:\n dat = await stream.read(1)\n if dat == b\"\\n\" and last_new_line:\n break\n data += dat\n last_new_line = dat == b\"\\n\"\n\n conv = data.decode(\"utf-8\").strip()[6:]\n\n if conv != \"ping\":\n break\n return json.loads(conv)","def _handle_reading(self, soc):\n chunk = soc.recv(_RECV_CHUNK_SIZE)\n if not chunk:\n self._handle_error(soc) # unexpected EOF\n return\n if soc not in self._reading:\n self._reading[soc] = \"\"\n self._reading[soc] += chunk.decode(\"utf-8\")\n\n if self._reading[soc].endswith(\"\\r\\n\\r\\n\"):\n # Finished reading request headers, don't expect request body.\n self._log(\"read %r\" % self._reading[soc])\n headers = self._reading[soc]\n self._reading[soc] = \"\"\n\n if not headers.startswith(\"GET \"):\n raise Exception(\"Only GET requests are supported.\")\n self._writing[soc], hook = self._responses[headers.split()[1]]\n\n # Move the socket to list of things waiting to write.\n self._read_list.remove(soc)\n self._write_list.append(soc)\n\n hook(self, soc)","async def __parse_csv(responses: SourceResponses) -> list[dict[str, str]]:\n rows = []\n for response in responses:\n csv_text = (await response.text()).strip()\n rows.extend(list(csv.DictReader(StringIO(csv_text, newline=\"\"))))\n return rows","def _read_data(self):\n while True:\n try:\n data = yield from asyncio.wait_for(self._socket.recv(), 1)\n except asyncio.TimeoutError:\n continue\n except asyncio.CancelledError:\n break\n except ConnectionClosed:\n break\n\n self._push_packet(data)\n\n self._loop.call_soon(self.close)","def next(self, num_rows=10):\n\n start = self._cursor\n stop = start + num_rows\n self._cursor += num_rows\n return self._data.iloc[start:stop]","def process_records(self, shard_iterator: str, shard_id: str):\n response = self.client.get_records(\n ShardIterator=shard_iterator\n )\n\n logger.debug('Getting data from shard: {shard_id}', extra=response)\n records = response['Records']\n\n if len(records) == 0:\n logger.info(f'Nothing to process for shard: \"{shard_id}\"')\n self._empty_shards.append(shard_id)\n else:\n for item in records:\n if self.item_callback:\n data = json.loads(item.get('Data'))\n order = data.get('order')\n contents = data.get('contents')\n self.item_callback(order, contents)\n self._sequences[shard_id] = item['SequenceNumber']\n\n next_shard_iterator = response['NextShardIterator']\n date = response.get('ResponseMetadata').get('HTTPHeaders').get('date')\n self._iterators[shard_id] = next_shard_iterator, date","def enter_read_loop(self):\n\n try:\n while True:\n try:\n request = DAPBaseMessage.recv(self._current_client)\n except Exception as e:\n # TODO send error\n traceback.print_exc()\n continue\n\n if request is None:\n # client terminated without termination request\n return\n try:\n self.resolve_message(request)\n except Exception as e:\n # TODO send error\n traceback.print_exc()\n self.next_seq += 1\n DAPErrorResponse.create(self.next_seq, rq.seq, False, message=\"Error\").send(self._current_client)\n continue\n\n if self._current_client is None:\n self._ready_for_events = False\n return # terminated\n\n except BaseException as e:\n # failure while communicating\n traceback.print_exc()\n pass\n finally:\n # final handler, clear active client\n self._current_client = None\n self._ready_for_events = False\n\n debugger.reset()","def stream(self, batch):\n response = self.post(batch)\n try:\n for i, result_data in grouped(response):\n result = JobResult.hydrate(assembled(result_data), batch)\n log.info(\"< %s\", result)\n yield result\n finally:\n response.close()","def parse(handle):\n while True:\n record = __read(handle)\n if not record:\n break\n yield record","async def _load_next_chunk(self):\n raise NotImplementedError","def read_response(self, read_lines=True):\n response = None\n if read_lines:\n response = self.stdout_stream.readlines()\n else:\n response = self.stdout_stream.read()\n return response","def fetch(self):\n # type: () -> List[List[Any]]\n if self._request.next_uri is None:\n self._finished = True\n return []\n response = self._request.get(self._request.next_uri)\n status = self._request.process(response)\n if status.columns:\n self._columns = status.columns\n self._stats.update(status.stats)\n if status.next_uri is None:\n self._finished = True\n return status.rows","async def get_records(self):\n\n callback_coro = self.consumer._get_checkpoint_callback()\n while True:\n try:\n if self._stop:\n return\n records = await self._get_records()\n if len(records) > 0:\n self.last_sequence_number = records[-1]['SequenceNumber']\n yield records\n\n # FIXME: Could there be empty records in the list? If yes, should we filter them out?\n self.record_count += len(records)\n if self.record_count > self.checkpoint_interval:\n\n if callback_coro:\n if not await callback_coro(self.shard_id, records[-1]['SequenceNumber']):\n raise ShardClosedException('Shard closed by application request')\n if self.dynamodb:\n await self.dynamodb.checkpoint(seq=records[-1]['SequenceNumber'])\n self.record_count = 0\n self.retries = 0\n except RetryGetRecordsException as e:\n sleep_time = min((\n 30,\n (self.retries or 1) * self.sleep_time\n ))\n if self.retries > 5:\n log.debug(\"Retrying get_records (#%d %ds): %s\", self.retries + 1, sleep_time, e)\n if not await self.interruptable_sleep(sleep_time):\n return\n self.retries += 1\n except ReaderExitException:\n self.is_running = False\n self.consumer.reader_exited(self.shard_id)\n except Exception as e:\n self.is_running = False\n # Reporting exit on exceptions\n log.debug(\"Shard %s got exception: %s\", self.shard_id, e)\n self.consumer.reader_exited(self.shard_id)\n raise e","def _yield_rows(self, ws_name):\n for idx, row in self._get_rows(ws_name):\n if idx >= WS_ROW_OFFSETS[ws_name] and \\\n len(row[0].value):\n yield idx, row","def _load_reading_row(self):\n\n raise NotImplementedError()","def _get_data(self):\n while not (self.closed or self.ended):\n block = self.stream.read(8192)\n with self.lock:\n if len(block) == 0:\n self.ended = True\n else:\n self.data.append(block)\n self.available.set()","def read_records(\n self, stream_state: Mapping[str, Any] = None, stream_slice: Mapping[str, Any] = None, **kwargs\n ) -> Iterable[Mapping[str, Any]]:\n self.current_slice = stream_slice\n records = super().read_records(stream_slice=stream_slice, stream_state=stream_state, **kwargs)\n if stream_state:\n for record in records:\n if record[self.cursor_field] > stream_state.get(self.cursor_field):\n yield record\n else:\n yield from records","def parse_response(self, response: requests.Response, **kwargs) -> Iterable[Mapping]:\n json_response = response.json().get(self.response_root_name)\n for resp in json_response:\n if self.response_item_name not in resp:\n error_text = f\"JSON field named '{self.response_item_name}' is absent in the response for {self.name} stream\"\n self.logger.error(error_text)\n raise SnapchatMarketingException(error_text)\n yield resp.get(self.response_item_name)","def extract_chunk_records(buf, offset):\n try:\n chunk = Evtx.Evtx.ChunkHeader(buf, offset)\n except:\n raise ParseError('failed to parse chunk header')\n\n cache = {}\n for record in chunk.records():\n try:\n record_xml = Evtx.Views.evtx_record_xml_view(record, cache=cache)\n eid = evtxtract.utils.get_eid(record_xml)\n yield RecoveredRecord(record.offset(), eid, record_xml)\n\n except UnicodeEncodeError:\n logger.info(\"Unicode encoding issue processing record at 0x%X\", record.offset())\n continue\n\n except UnicodeDecodeError:\n logger.info(\"Unicode decoding issue processing record at 0x%X\", record.offset())\n continue\n\n except Evtx.Evtx.InvalidRecordException:\n logger.info(\"EVTX parsing issue processing record at 0x%X\", record.offset())\n continue\n\n except Exception as e:\n logger.info(\"Unknown exception processing record at 0x%X\", record.offset(), exc_info=True)\n continue","async def _receive_response(\n self, request: Request, stream_id: int\n ) -> typing.Tuple[int, typing.List[typing.Tuple[bytes, bytes]]]:\n while True:\n event = await self._receive_stream_event(request, stream_id)\n if isinstance(event, h2.events.ResponseReceived):\n break\n\n status_code = 200\n headers = []\n for k, v in event.headers:\n if k == b\":status\":\n status_code = int(v.decode(\"ascii\", errors=\"ignore\"))\n elif not k.startswith(b\":\"):\n headers.append((k, v))\n\n return (status_code, headers)","def process_response(self, response: Dict) -> Iterator[dict]:","def next_chunk(self):\n if self._unconsumed:\n data = self._unconsumed.pop()\n else:\n data = self._iterator.next() # Might raise StopIteration\n self._pos += len(data)\n return data","def _process_stream(self):\n input_df = self._read_stream()\n\n clean_df = input_df \\\n .select(from_json(input_df.value.cast('string'),\n self.schema).alias('value'))\n explode_df = clean_df.select('value.*')\n\n enrich_df = explode_df \\\n .withColumn('event_time', explode_df.event_time.cast(TimestampType())) \\\n .withColumn('process_time', current_timestamp())\n\n return enrich_df","async def next(self) -> Optional[Union[MultipartReader, BodyPartReader]]:\n ...","async def next(self) -> Optional[Union[MultipartReader, BodyPartReader]]:\n ...","def iter_records(self):\n\n decomp_type = 'gzip'\n block_size = 16384\n\n self.reader = DecompressingBufferedReader(self.fh,\n block_size=block_size)\n self.offset = self.fh.tell()\n\n next_line = None\n\n while True:\n try:\n record = self._next_record(next_line)\n yield record\n except EOFError:\n break\n\n self.read_to_end(record)\n\n # for non-compressed, consume blank lines here\n if not self.reader.decompressor:\n next_line = self._consume_blanklines()\n if next_line is None:\n # at end of file\n break\n\n # reset reader for next member\n else:\n self.reader.read_next_member()","def get_response_content_iterator(self):\n return self.__response.iter_lines()","def on_readable(self):\n data = self.read(2048)\n if len(data) == 0:\n self.mark_down()\n if self.response is None:\n return\n else:\n self.response.on_connection_down(self)\n return\n elif self.response is None:\n self.receive_bytes = b''.join([self.receive_bytes, data])\n terminal_idx = self.receive_bytes.find(b'\\r\\n\\r\\n')\n if terminal_idx < 0:\n return\n\n header_bytes = self.receive_bytes[:terminal_idx]\n remain_bytes = self.receive_head_bytes[terminal_idx + 4:]\n self.response = self.on_process_request_header(header_bytes, remain_bytes)\n else:\n self.response.on_body_received(self, data)","def read(self, batch_size=1):\n cur_q_size = len(self._queue)\n while cur_q_size < batch_size:\n if self._thread.get_exception() is not None:\n break\n time.sleep(0.1)\n cur_q_size = len(self._queue)\n\n exception = self._thread.get_exception()\n if isinstance(exception, EndOfVideoError):\n if cur_q_size == 0:\n raise EndOfVideoError()\n elif cur_q_size <= batch_size:\n data = self._read_all()\n else:\n data = self._read(batch_size)\n elif isinstance(exception, ConnectionBrokenError):\n raise ConnectionBrokenError()\n else:\n # XXX: In this case we are assuming that everything is fine,\n # and current queue size should greater than the batch\n # size.\n data = self._read(batch_size)\n return data","def recv_stream_resp(self):\n return_mess = b''\n while True:\n return_mess += self.recv_resp_simple(1)\n if return_mess[-2:] == self.end_mess_bytes:\n start_idx = return_mess.rfind(b'RUP') # Find start of response\n if start_idx < 0:\n continue\n cut_mess = return_mess[start_idx:]\n split_mess = cut_mess.split()\n return_code = int(split_mess[1])\n\n # Sometimes we have overflow of data when attempting to stop stream - probably extra scan data we\n # haven't picked up yet. So we try to decode it all, but if we hit an error we just decode the last\n # few bytes which contain the message we are interested in\n # try:\n # mess_ascii = return_mess.decode(self.encoding)\n # except UnicodeDecodeError as e:\n # # print('Error decoding message: {}'.format(e))\n # mess_ascii = return_mess[-7:].decode(self.encoding)\n # return_code = int(mess_ascii[-3])\n if self.gui_message is not None:\n if return_code == 0:\n self.gui_message.message('[LSP] Response all good!')\n else:\n self.gui_message.message('[LSP] Error code: %i' % return_code)\n else:\n if return_code == 0:\n print('[LSP] Response all good!')\n else:\n print('[LSP] Error code: %i' % return_code)\n return return_code","def _process_response(self, response, marker_elems=None):\r\n body = response.read()\r\n #print body\r\n if '<Errors>' not in body:\r\n rs = ResultSet(marker_elems)\r\n h = handler.XmlHandler(rs, self)\r\n xml.sax.parseString(body, h)\r\n return rs\r\n else:\r\n raise MTurkRequestError(response.status, response.reason, body)","def read_until_eof(self):\n with self.reading:\n try:\n while True:\n self.read_buffer.enqueue((yield self.base.read(self.bufsize)))\n except BrokenPipeError:\n pass\n do_return(self.read_buffer.dequeue())","def handle(self):\n req_lines = self._read_lines()\n if not req_lines:\n self.cleanup()\n for req in req_lines:\n log.debug('%s => %s', self.client, req)\n req = req.split()\n cmd = req.pop(0)\n try:\n self.get_command(cmd)(req)\n result = [OK]\n except Exception as error:\n result = [ERROR, error.message]\n self.send_line(' '.join(result))\n self.flush()","def load_next_response(self):\n if self.response_info['next']:\n self.response = requests.get(self.response_info['next'])\n self.response_info = self.response.json()","def process(self, chunk):\n self._buf += chunk\n\n # Streams are `\\r\\n`-separated JSON messages.\n raw_lines = self._buf.split(b\"\\r\\n\")\n\n # If only one element in the split, then there wasn't a CRLF.\n if len(raw_lines) > 1:\n\n # The last element may be a b'', which is perfectly fine.\n self._buf = raw_lines[-1]\n\n # Blank lines are keep-alive messages.\n self._mailbox.extend(l for l in raw_lines[:-1] if l.strip())","def handle_read(self):\n data, ancdata, _, _ = recvmsg(self.socket, 65536, 4096)\n\n if not data:\n return self.handle_close()\n\n fds, cred = parse_ancdata(ancdata)\n\n if self.header_buffer is not None:\n self.header_buffer += data.decode()\n\n linefeed = self.header_buffer.find('\\n')\n if linefeed == -1:\n return\n\n header = json.loads(self.header_buffer[:linefeed])\n data = self.header_buffer[linefeed + 1:]\n self.header_buffer = None\n\n self.handle_header(fds, header)\n\n if not data:\n return\n\n meta = Metadata(time=datetime.now(), pid=cred.pid,\n comm=(comm_for_pid(cred.pid) or \"unknown\"),\n unit=(unit_for_pid(cred.pid) or self.unit))\n\n if meta.unit is not None:\n log = self.log_manager.get(meta.unit, \"stdio\")\n log.write(data, meta)","def _read (self, sock, max_buffer, read_size=64*1024, proxied=False):\n\t\t# yield request, content\n\t\t# request is the text that form the request header\n\t\t# content any text which is related to the current request after the headers\n\n\t\tyield ''\n\n\t\tr_buffer = ''\n\t\tnb_to_send = 0\n\t\tseek = 0\n\t\tmasquerade = None\n\n\t\t# mode can be one of : request, chunk, extension, relay\n\t\t# request : we are reading the request (read all you can until a separator)\n\t\t# extra-headers : we are reading data until a separator\n\t\t# chunked : we are reading chunk-encoded darta\n\t\t# transfer : we are reading as much as requested in remaining\n\t\t# passthrough : read as much as can to be relayed\n\n\t\tmode = 'proxy' if proxied else 'http'\n\t\thttp_request = ''\n\t\tdata = ''\n\n\t\twhile True:\n\t\t\ttry:\n\t\t\t\twhile True:\n\t\t\t\t\tif mode != 'new-request' and (mode != 'transfer' or r_buffer == ''):\n\t\t\t\t\t\tnew_data = sock.recv(read_size)\n\t\t\t\t\t\tif not new_data:\n\t\t\t\t\t\t\tbreak # read failed so we abort\n\n\t\t\t\t\t\tr_buffer += new_data\n\n\t\t\t\t\telif mode == 'new-request':\n\t\t\t\t\t\tmode = 'http'\n\n\t\t\t\t\tif mode == 'proxy':\n\t\t\t\t\t\tmasquerade, r_buffer, mode = self.processProxyHeader(r_buffer, mode)\n\t\t\t\t\t\tif masquerade is None:\n\t\t\t\t\t\t\tbreak\n\n\t\t\t\t\t\telif not masquerade:\n\t\t\t\t\t\t\tcontinue\n\n\t\t\t\t\t\tself.setPeer(masquerade)\n\n\t\t\t\t\t# check for a new http header\n\t\t\t\t\tif mode == 'http':\n\t\t\t\t\t\tr_buffer = r_buffer.lstrip('\\r\\n')\n\n\t\t\t\t\t\thttp_request, r_buffer, seek = self.checkRequest(r_buffer, max_buffer, seek)\n\t\t\t\t\t\tif http_request is None:\n\t\t\t\t\t\t\tbreak\n\n\t\t\t\t\t# all modes that are not directly related to reading a new request\n\t\t\t\t\tif mode != 'http':\n\t\t\t\t\t\tdata, r_buffer, mode, nb_to_send, seek = self.process(r_buffer, mode, nb_to_send, max_buffer, seek)\n\t\t\t\t\t\tif data is None:\n\t\t\t\t\t\t\tbreak\n\n\t\t\t\t\tif mode == 'http' and http_request:\n\t\t\t\t\t\thttp_response, http_request = [http_request], ''\n\t\t\t\t\t\tseek = 0\n\n\t\t\t\t\t\tmode, nb_to_send = yield http_response, ['']\n\n\t\t\t\t\telif data:\n\t\t\t\t\t\tdata_response, data = [data], ''\n\t\t\t\t\t\tyield [''], data_response\n\n\t\t\t\t\telse:\n\t\t\t\t\t\tyield [''], ['']\n\n\n\t\t\t\t# break out of the outer loop as soon as we leave the inner loop\n\t\t\t\t# through normal execution\n\t\t\t\tbreak\n\n\t\t\texcept socket.error, e:\n\t\t\t\tif e.args[0] in errno_block:\n\t\t\t\t\tyield [''], ['']\n\t\t\t\telse:\n\t\t\t\t\tbreak\n\n\t\tyield [None], [None]","def _get_next_record(self):\n # Read next record from xlsx file\n row = self.ds_reader.next()\n if len(row) == 0:\n raise StopIteration\n \n # build record\n record = {'__row':row[0].row}\n for cell in row:\n record[str(cell.column)] = cell.internal_value\n #if cell.internal_value != None:\n # self.ds_processedBytes += len(cell.internal_value)\n \n # finished\n return record","def parse(stream, idx):\n\n # Skip comment lines\n stream = filter(lambda x: not x.startswith('#'), stream)\n\n # Ignore empty lines.\n stream = filter(lambda x: x.strip(), stream)\n\n # Format the stream.\n stream = csv.reader(stream, delimiter=delimiter)\n\n # Generate empty values on missing columns.\n for row in stream:\n try:\n yield (row[idx], None)\n except IndexError as exc:\n yield ('', None)","def next(self, rows: List[Row]) -> List[Row]:\n if not rows:\n return []\n input_row_index = self._get_row_index(rows[0])\n if input_row_index < len(self.table_data) - 1 and input_row_index != -1:\n return [self.table_data[input_row_index + 1]]\n return []","async def fetch_next_block(self):\n\n results = []\n for _ in range(self._page_size):\n try:\n results.append(await self.__anext__())\n except StopAsyncIteration:\n # no more results\n break\n return results","def _read_chunked(self):\r\n buf = \"\"\r\n size = 1\r\n while size:\r\n size = int(self._read_line(), 16)\r\n buf += self._read_num_bytes(size)\r\n self._read_num_bytes(2) # CRLF\r\n return buf","def _read_range(self, start=0, end=None):\n max_read_size = self.channel.connection.negotiate_response.max_read_size\n offset = start\n response_buffers = []\n while end is None or offset < end:\n if end is not None:\n max_read_size = min(end - offset, max_read_size)\n available = min(\n self.channel.connection.credits * smb2.BYTES_PER_CREDIT,\n max_read_size,\n )\n try:\n read_resp = self.channel.read(self, available, offset)\n response_buffers.append(read_resp)\n offset += len(read_resp)\n except ResponseError as re:\n if re.response.status == ntstatus.STATUS_END_OF_FILE:\n break\n raise\n read_buffer = b\"\".join(rb.tobytes() for rb in response_buffers)\n if read_buffer:\n self._offset = start + len(read_buffer)\n # update the EOF marker if we read past it\n self._end_of_file = max(self.end_of_file, self._offset)\n return read_buffer","def fetch_message_batch(self, callback=None):\n\n # on response from server return with messages\n def _on_response(*args):\n if callback:\n self.offset += len(args[0])\n callback(*args)\n\n self.inbox.search(self.search_string, full=True,\n limit=self.per_page, offset=self.offset, callback=_on_response)","def next(self):\n return self.read_message()","def feed_records(self):\n if not self.stats_file:\n return\n\n with open(self.stats_file) as fh:\n reader = reverse_file(fh)\n for line in reader:\n if line is None:\n return\n if not line:\n continue\n\n try:\n js = json.loads(line)\n except Exception as e:\n continue\n\n yield js","def next(self, payload):\n\n session = ZuoraApiSession(self.org_uid)\n\n # There are 2 different endpoints for querying.\n # One which takes the initial query string and one which takes a cursor if there is another page of data.\n if self.sync_data.cursor:\n response = session.post(\n QUERY_MORE_URI,\n json={'queryLocator': self.sync_data.cursor}\n )\n else:\n response = session.post(\n QUERY_URI,\n json={'queryString': self._get_query()}\n )\n\n endpoint = ENDPOINTS[self.sync_data.endpoint_index]\n\n items = response.get('records', [])\n new_payload = {}\n has_more_items = False\n max_updated_at = None\n\n if items:\n # Parse datetime strings\n updated_dates = [parser.parse(item['UpdatedDate']) for item in items]\n\n # Retrieve the max UpdatedDate to use in the query for the next changeset\n max_updated_at = items[updated_dates.index(max(updated_dates))]['UpdatedDate']\n\n item_objects = []\n\n for item in items:\n item_objects.extend(\n sync_utils.create_items(\n self.org_uid,\n self.org.provider,\n self.org.changeset,\n endpoint,\n item['Id'],\n item\n )\n )\n\n sync_utils.save_items(item_objects)\n\n # If there are more pages to fetch, store the cursor\n if 'queryLocator' in response:\n logging.info(\"There is another page of {}\".format(endpoint))\n self.sync_data.cursor = response['queryLocator']\n new_payload['max_updated_at'] = max_updated_at\n\n else:\n logging.info(\"no more data expected for endpoint {}\".format(endpoint))\n marker = max_updated_at or payload.get('max_updated_at')\n\n if marker:\n logging.info(\"setting updated_at marker for {} to {}\".format(endpoint, marker))\n self.sync_data.markers[self.sync_data.endpoint_index] = marker\n\n self.sync_data.endpoint_index += 1\n self.sync_data.cursor = None\n\n complete = self.sync_data.endpoint_index == len(ENDPOINTS)\n\n if complete:\n self.sync_data.endpoint_index = 0\n\n self.sync_data.put()\n complete = complete and not has_more_items\n\n return complete, new_payload","def processData(self):\n _lastLine = True\n _firstRead = True\n n = 0\n while self.console.working:\n remotelog = ''\n response = ''\n remote_log_data = ''\n remotelogsize = 0\n\n # specify range depending on if the last line\n # is in the remote log chunk or not\n if _lastLine:\n b = 'bytes=-10000'\n else:\n b = 'bytes=-100000'\n\n headers = {\n 'User-Agent' : user_agent,\n 'Range' : b,\n 'Accept-encoding' : 'gzip'\n }\n\n request = urllib2.Request(self._url, None, headers)\n\n # get remote log url response and headers\n try:\n response = urllib2.urlopen(request)\n headers = response.info()\n\n # buffer/download remote log\n if response != '':\n remote_log_data = response.read()\n remotelogsize = round((len(remote_log_data) / float(1024)), 2)\n # self.verbose('Downloaded: %s KB total' % remotelogsize)\n\n try:\n # close remote file\n response.close()\n except AttributeError, e:\n self.error('ERROR: %s' % e)\n\n except (urllib2.HTTPError, urllib2.URLError), e:\n self.error('HTTP ERROR: %s' % e)\n except socket.timeout:\n self.error('TIMEOUT ERROR: socket timed out!')\n\n # start keeping the time\n start = time.time()\n\n # decompress remote log and return for use\n # First, make sure that there is domething worth decompressing\n # In case the server has just done a restart\n if len(remote_log_data) > 0:\n try:\n #self.debug('Content-Encoding: %s' % headers.get('Content-Encoding'))\n if headers.get('Content-Encoding') == 'gzip':\n compressedstream = StringIO.StringIO(remote_log_data)\n gzipper = gzip.GzipFile(fileobj=compressedstream)\n remotelog = gzipper.read()\n else:\n remotelog = remote_log_data\n except IOError, e:\n remotelog = ''\n self.error('IOERROR: %s' % e)\n\n if os.path.exists(self.locallog) and os.path.getsize(self.locallog) > 0 and not _firstRead:\n\n # check if last line is in the remote log chunk\n if remotelog.find(self.lastlines) != -1:\n _lastLine = True\n n = 0\n\n # we'll get the new lines i.e what is available after the last line\n # of our local log file\n try:\n checklog = remotelog.rpartition(self.lastlines)\n newlog = checklog[2]\n # remove any broken last line\n i = newlog.rfind ('\\r\\n')\n newlog = newlog[:i + 2]\n # remove any blank lines\n while newlog[-4:-2] == '\\r\\n':\n newlog = newlog[:-2]\n except ValueError, error:\n self.error ('ValueError: %s' % error)\n newlog = ''\n\n # remove any blank lines from end\n # append the additions to our log if there is something and update lazy cursor\n if len(newlog) > 0:\n output = open(self.locallog,'ab')\n output.write(newlog)\n output.close()\n self.lastlines = remotelog[-1000:] \n self.debug('downloaded %s KB and added %s char(s) to log' % (remotelogsize, len(newlog)))\n\n else:\n _lastLine = False\n self.debug('can\\'t find last line in the log chunk: checking again...')\n n += 1\n\n # check once in a larger chunk and if we are still unable to find last line\n # in the remote chunk, restart the process\n if n == 2:\n self.debug('Logs rotated or unable to find last line in remote log, restarting process...')\n self.writeCompletelog(self.locallog, remotelog)\n _lastLine = True\n n = 0\n\n else:\n self.debug('writing first log read')\n self.writeCompletelog(self.locallog, remotelog)\n _firstRead = False\n\n # calculate how long it took to process\n timespent = time.time() - start\n\n # calculate time to wait until next request.\n timeout = float(self.timeout)\n\n # self.verbose('Given timeout value is %s seconds' % timeout)\n # self.verbose('Total time spent to process the downloaded file is %s seconds' % timespent)\n\n # Calculate sleep time for next request. Adding 0.1 secs to prevent HTTP Error 403 errors\n wait = float((timeout - timespent) + 0.1)\n\n if wait <= 0:\n wait = 1\n\n # make the plugin thread fast-killable\n i = 0\n w = int(wait)\n while i < w and self.console.working:\n time.sleep(1)\n i += 1\n time.sleep(wait - w)\n\n self.verbose('B3 is down: stopping Cod7Http plugin')","def recv_read_response(self, recv_payload): \n\t#Only unpack the headers because we want to store the file data as binary\n\tunpacked_payload = struct.unpack('!H3IQ', recv_payload[:22])\n\tstatus = unpacked_payload[0:1][0]\n\tepoch_no = unpacked_payload[1:2][0]\n\thandle_no = unpacked_payload[2:3][0]\t\n\t\n\t#Check that file handle is the same, to make sure it is the same file request.\n\tif (self.epoch_no == epoch_no and self.handle_no == handle_no):\n\t start_position = unpacked_payload[3:4][0]\n\t num_bytes_been_read = unpacked_payload[4:5][0] \n\t # If we receive less bytes than the number we requested to read, this means that\n\t # end of file has been reached\n\t if (num_bytes_been_read < self.NUM_BYTES_TO_READ):\n\t\tself.eof = True\n\t data_to_write = recv_payload[22:]\t \n\t #If status field says that response contains real data: Append to file. Otherwise react \n\t #depending on error code received.\n\t #Status 00 = OK\n\t #Status 01 = Epoch no. of file handle doesnt match epoch no. of current invocation\n\t #Status 10 = No context found for file-handle and no data has been read\n\t #Status 11 = Context could be found but start position out of range\n\t if (status == 0b00):\n\t\tself.file_append.seek(start_position)\n\t\tself.file_append.write(data_to_write)\n\t elif (status == 0b01):\n\t\tprint(\"Error: Epoch no. of file handle doesnt match epoch no. of current invocation\")\n\t\tsys.exit()\n\t elif (status == 0b10):\n\t\tprint(\"Error: No context found for file-handle and no data has been read\")\n\t\tsys.exit()\n\t elif(status == 0b11):\n\t\tprint(\"Error: Context could be found but start position out of range\")\n\t\tsys.exit()\n\telse:\n\t print(\"Error: File handle does not match file handle stored in client. Wrong file received.\")\n\t sys.exit() \t \n\t#Then return control to read_service_loop() method so that next iteration of send_read_request \n\t#from new start position is called.\n return","def ReadFlowRequestsReadyForProcessing(self,\n client_id,\n flow_id,\n next_needed_request=None):\n request_dict = self.flow_requests.get((client_id, flow_id), {})\n response_dict = self.flow_responses.get((client_id, flow_id), {})\n\n # Do a pass for completed requests.\n res = {}\n for request_id in sorted(request_dict):\n # Ignore outdated requests.\n if request_id < next_needed_request:\n continue\n # The request we are currently looking for is not in yet, we are done.\n if request_id != next_needed_request:\n break\n request = request_dict[request_id]\n\n if not request.needs_processing:\n break\n\n responses = sorted(\n response_dict.get(request_id, {}).values(),\n key=lambda response: response.response_id)\n # Serialize/deserialize responses to better simulate the\n # real DB behavior (where serialization/deserialization is almost\n # guaranteed to be done).\n # TODO(user): change mem-db implementation to do\n # serialization/deserialization everywhere in a generic way.\n responses = [\n r.__class__.FromSerializedBytes(r.SerializeToBytes())\n for r in responses\n ]\n res[request_id] = (request, responses)\n next_needed_request += 1\n\n # Do a pass for incremental requests.\n for request_id in request_dict:\n # Ignore outdated and processed requests.\n if request_id < next_needed_request:\n continue\n\n request = request_dict[request_id]\n if not request.callback_state:\n continue\n\n responses = response_dict.get(request_id, {}).values()\n responses = [\n r for r in responses if r.response_id >= request.next_response_id\n ]\n responses = sorted(responses, key=lambda response: response.response_id)\n\n # Serialize/deserialize responses to better simulate the\n # real DB behavior (where serialization/deserialization is almost\n # guaranteed to be done).\n # TODO(user): change mem-db implementation to do\n # serialization/deserialization everywhere in a generic way.\n responses = [\n r.__class__.FromSerializedBytes(r.SerializeToBytes())\n for r in responses\n ]\n res[request_id] = (request, responses)\n\n return res","def parse(self, response: scrapy.http.Response):\n for job in self.parse_jobs(response):\n yield job\n\n if self.has_next_page(response):\n yield scrapy.Request(self.next_url,\n meta={'cookiejar': response.meta['cookiejar'],\n 'queries': response.meta['queries']},\n dont_filter=True)","async def read(self) -> Union[dictwrapper, str]:\n while True:\n await self.connect()\n try:\n rx_timeout = self.alive_opts.get('rx_timeout', None)\n reader = self.reader.readuntil(separator=b'\\n')\n self.bresponse = await asyncio.wait_for(reader,\n rx_timeout)\n self.response = polystr(self.bresponse)\n if self.response.startswith(\n \"{\") and self.response.endswith(\"}\\r\\n\"):\n self.unpack(self.response)\n self._oldstyle_shim()\n self.valid |= PACKET_SET\n return self.data\n return self.response\n except asyncio.CancelledError:\n self.close()\n raise\n except Exception as exc: # pylint: disable=W0703\n error = 'timeout' if isinstance(\n exc, asyncio.TimeoutError) else exc\n self.logger.warning(\n f'Failed to get message from GPSD: {error}')\n self.close()\n if self.reconnect:\n # Try again later\n await asyncio.sleep(self.reconnect)\n else:\n raise","async def client_read(reader, connection):\n while connection.state[\"connected\"]:\n inp = await reader.readline()\n\n if not inp: # This is an EOF. Hard disconnect.\n connection.state[\"connected\"] = False\n return\n\n payload = {\n \"uuid\": connection.uuid,\n \"addr\": connection.addr,\n \"port\": connection.port,\n \"msg\": inp.strip(),\n }\n msg = {\n \"event\": \"player/input\",\n \"secret\": WS_SECRET,\n \"payload\": payload,\n }\n\n asyncio.create_task(messages_to_game.put(Message(\"IO\", message=json.dumps(msg, sort_keys=True, indent=4))))","def seek_record_read(self, offset, count):\n self.seek(offset)\n return self.record_read(count)","def read(self):\n while True:\n size_bytes = self.connection.read(Frame.SIZE_WIDTH)\n # Read will return zero bytes when the other side of the connection\n # closes.\n if not size_bytes:\n break\n\n message_length = read_number_string(size_bytes, Frame.SIZE_WIDTH)\n\n chunk = self.connection.read(message_length - Frame.SIZE_WIDTH)\n if not chunk:\n raise ProtocolException(\n 'Expected %d bytes available, got none' % message_length\n )\n\n if len(chunk) != message_length - Frame.SIZE_WIDTH:\n raise ProtocolException(\n 'Expected %d bytes, got %d' %\n (len(chunk), message_length - Frame.SIZE_WIDTH)\n )\n\n yield Frame.decode(BytesIO(chunk), message_length)","def peek(self):\n if self._buffer:\n values = self._buffer[0]\n return Record(self.keys(), tuple(map(hydrated, values)))\n while not self._buffer and not self._consumed:\n self.connection.fetch()\n if self._buffer:\n values = self._buffer[0]\n return Record(self.keys(), tuple(map(hydrated, values)))\n raise ResultError(\"End of stream\")","def _record_iterator(self):\n\n # Alias these values so the code won't need to keep performing\n # attribute lookups on `self` (small optimization)\n stream = self.stream\n sync_marker = self._sync_marker\n writer_schema = self.writer_schema\n reader_schema = self.reader_schema\n\n # Get the block decoder\n if self.codec == 'deflate':\n read_block = deflate_read_block\n elif self.codec == 'snappy':\n read_block = snappy_read_block\n else:\n read_block = null_read_block\n\n block_buf = BytesIO()\n\n try:\n while True:\n block_count = read_long(stream)\n read_block(stream, block_buf)\n\n for i in xrange(block_count):\n yield read_data(block_buf, writer_schema, reader_schema)\n\n skip_sync(stream, sync_marker)\n\n except EOFError:\n pass\n finally:\n block_buf.close()","def _batcher(self, rows):\n row_count = 0\n batch = []\n batch_count = 1\n\n total_rows_modified = 0\n throttle_count = 0\n\n i = 0\n for row in rows:\n if row_count > self.batch_size - 1:\n logger.debug(f\"row_count={row_count} batch_size={self.batch_size} and batch={len(batch)}\")\n # Yield the previous batch\n yield batch\n\n # Start the new batch\n batch = []\n batch.append(row)\n row_count = 1\n\n batch_count += 1\n # break # toggle to load one batch only\n else:\n row_count += 1\n batch.append(row)\n\n # Put in a sleep timer to throttle how hard we hit the database\n if self.throttle_time and self.throttle_size and (throttle_count > self.throttle_size - 1):\n logger.info(f\"Sleeping for {self.throttle_time} seconds... row: {i}\")\n time.sleep(int(self.throttle_time))\n throttle_count = 0\n elif self.throttle_time and self.throttle_size:\n throttle_count += 1\n i += 1\n\n yield batch","def _read_thread(self):\r\n\r\n while self._reading and self._serial_object:\r\n if self._serial_object.in_waiting:\r\n try:\r\n (raw_data, parsed_data) = self._ubxreader.read()\r\n # if raw_data:\r\n # print(raw_data)\r\n if parsed_data:\r\n print(parsed_data)\r\n except (\r\n ube.UBXStreamError,\r\n ube.UBXMessageError,\r\n ube.UBXTypeError,\r\n ube.UBXParseError,\r\n ) as err:\r\n print(f\"Something went wrong {err}\")\r\n continue","def handle_read(self):\n while True:\n try:\n content = self.recv(1024)\n if content:\n self.rbuf.write(content.decode('utf-8'))\n if len(content) < 1024:\n break\n except Exception as e:\n print(e)\n self.handle_rpc()","def rows(self):\r\n\r\n done_sending = False\r\n while not done_sending:\r\n self._note(\"C _not_empty acq?\")\r\n self.not_empty.acquire()\r\n try:\r\n self._note(\"C _not_empty wait ...\")\r\n while not self._ready_buffer and not self._closed:\r\n self.not_empty.wait()\r\n self._note(\"C _not_empty got <\")\r\n\r\n if self._ready_buffer:\r\n rows = self._ready_buffer\r\n self._ready_buffer = None\r\n self._note(\"C _not_full notify >\")\r\n self.not_full.notify()\r\n\r\n for row in rows:\r\n yield row\r\n else:\r\n self._note(\"C no buffer\")\r\n\r\n\r\n done_sending = self._closed\r\n finally:\r\n self._note(\"_not_empty rel!\")\r\n self.not_empty.release()"],"string":"[\n \"async def _receive_response_body(\\n self, request: Request, stream_id: int\\n ) -> typing.AsyncIterator[bytes]:\\n while True:\\n event = await self._receive_stream_event(request, stream_id)\\n if isinstance(event, h2.events.DataReceived):\\n amount = event.flow_controlled_length\\n self._h2_state.acknowledge_received_data(amount, stream_id)\\n await self._write_outgoing_data(request)\\n yield event.data\\n elif isinstance(event, h2.events.StreamEnded):\\n break\",\n \"def parse_rows(self, response):\\n\\n for row in csviter(\\n response, self.delimiter, self.headers, quotechar=self.quotechar\\n ):\\n ret = iterate_spider_output(self.parse_row(response, row))\\n for result_item in self.process_results(response, ret):\\n yield result_item\",\n \"def next(self):\\r\\n self.open_read()\\r\\n data = self.resp.read(self.BufferSize)\\r\\n if not data:\\r\\n self.close()\\r\\n raise StopIteration\\r\\n return data\",\n \"def __read_response(self, nblines=-1):\\n resp, code, data = (b\\\"\\\", None, None)\\n cpt = 0\\n while True:\\n try:\\n line = self.__read_line()\\n except Response as inst:\\n code = inst.code\\n data = inst.data\\n break\\n except Literal as inst:\\n resp += self.__read_block(inst.value)\\n if not resp.endswith(CRLF):\\n resp += self.__read_line() + CRLF\\n continue\\n if not len(line):\\n continue\\n resp += line + CRLF\\n cpt += 1\\n if nblines != -1 and cpt == nblines:\\n break\\n\\n return (code, data, resp)\",\n \"def parse_row(self, response, row):\\n raise NotImplementedError\",\n \"def state_readChunk(self, fileObj):\\n if not self.reader.next(fileObj, self.destination):\\n self.readResponse = self.state_finalStatus\",\n \"async def __parse_csv(responses: SourceResponses) -> Samples:\\n rows = []\\n for response in responses:\\n csv_text = await response.text()\\n rows.extend(list(csv.DictReader(StringIO(csv_text.strip(), newline=\\\"\\\"))))\\n return rows\",\n \"def _unpack_body(self, buff):\\n\\n # Unpack <return_code> and <count> (how many records affected or selected)\\n self._return_code = struct_L.unpack_from(buff, offset=0)[0]\\n\\n # Separate return_code and completion_code\\n self._completion_status = self._return_code & 0x00ff\\n self._return_code >>= 8\\n\\n # In case of an error unpack the body as an error message\\n if self._return_code != 0:\\n self._return_message = unicode(buff[4:-1], self.charset, self.errors)\\n if self._completion_status == 2:\\n raise TarantoolError(self._return_code, self._return_message)\\n\\n # Unpack <count> (how many records affected or selected)\\n self._rowcount = struct_L.unpack_from(buff, offset=4)[0]\\n\\n # If the response doesn't contain any tuple - there is nothing to unpack\\n if self._body_length == 8:\\n return\\n\\n # Parse response tuples (<fq_tuple>)\\n if self._rowcount > 0:\\n offset = 8 # The first 4 bytes in the response body is the <count> we have already read\\n while offset < self._body_length:\\n # In resonse tuples have the form <size><tuple> (<fq_tuple> ::= <size><tuple>).\\n # Attribute <size> takes into account only size of tuple's <field> payload,\\n # but does not include 4-byte of <cardinality> field.\\n #Therefore the actual size of the <tuple> is greater to 4 bytes.\\n tuple_size = struct.unpack_from(\\\"<L\\\", buff, offset)[0] + 4\\n tuple_data = struct.unpack_from(\\\"<%ds\\\" % (tuple_size), buff, offset+4)[0]\\n tuple_value = self._unpack_tuple(tuple_data)\\n if self.field_types:\\n self.append(self._cast_tuple(tuple_value))\\n else:\\n self.append(tuple_value)\\n\\n offset = offset + tuple_size + 4 # This '4' is a size of <size> attribute\",\n \"def parse_rows_with(reader, parsers):\\n for row in reader:\\n yield parse_row(row, parsers)\",\n \"def parse_rows_with(reader, parsers):\\n for row in reader:\\n yield parse_row(row, parsers)\",\n \"def next(self):\\n self.record_offset += 2 ** self.blockettes[1000]['Data Record Length']\\n self._parseHeader()\",\n \"def parse_rows_with(reader, parsers):\\n for row in reader:\\n yield parse_row(row,parsers)\",\n \"def _read_responses(self):\\n try:\\n while not self.shutting_down:\\n try:\\n raw_message = self.kernel_socket.recv()\\n response_message = json_decode(utf8(raw_message))\\n\\n msg_id = KernelClient._get_msg_id(response_message, self.log)\\n\\n if msg_id not in self.response_queues:\\n # this will happen when the msg_id is generated by the server\\n self.response_queues[msg_id] = queue.Queue()\\n\\n # insert into queue\\n self.log.debug(\\\"Inserting response for msg_id: {}, msg_type: {}\\\".\\n format(msg_id, response_message['msg_type']))\\n self.response_queues.get(msg_id).put_nowait(response_message)\\n except BaseException as be1:\\n if self.restarting: # If restarting, wait until restart has completed - which includes new socket\\n i = 1\\n while self.restarting:\\n if i >= 10 and i % 2 == 0:\\n self.log.debug(\\\"Still restarting after {} secs...\\\".format(i))\\n time.sleep(1)\\n i += 1\\n continue\\n raise be1\\n\\n except websocket.WebSocketConnectionClosedException:\\n pass # websocket closure most likely due to shutdown\\n\\n except BaseException as be2:\\n if not self.shutting_down:\\n self.log.warning('Unexpected exception encountered ({})'.format(be2))\\n\\n self.log.debug('Response reader thread exiting...')\",\n \"def receiveLines(self):\\n\\n\\t\\tif self.s is None:\\n\\t\\t\\traise ConnectionError(\\\"There was a connection error\\\")\\n\\n\\t\\tif \\\"\\\\r\\\\n\\\" not in self.buf:\\n\\t\\t\\t# Read 1024 bytes from socket try to decode it as UTF-8\\n\\t\\t\\t# and append it to buffer.\\n\\t\\t\\t# It gets appended because there might be incomplete data\\n\\t\\t\\t# from a previous read.\\n\\t\\t\\t# Try to decode as UTF-8, replace unknown characters on error\\n\\t\\t\\tself.buf = self.buf + self.s.recv(1024).decode(\\\"utf-8\\\", \\\"replace\\\")\\n\\t\\t\\tif not self.buf:\\n\\t\\t\\t\\tsys.exit(1)\\n\\n\\t\\tlines = self.buf.split(\\\"\\\\r\\\\n\\\", 1)\\n\\t\\tline = lines[0]\\n\\n\\t\\tif len(lines) > 1:\\n\\t\\t\\tself.buf = lines[1]\\n\\n\\t\\tyield line\",\n \"def _incoming_read(self, client, data, error):\\n\\n if error is not None:\\n client.close()\\n del self._incoming[client]\\n return\\n\\n incoming = self._incoming[client]\\n incoming.unpacker.feed(data)\\n for req_id, message in incoming.unpacker:\\n self._call_handler(\\n partial(self._queue_response,\\n client, req_id),\\n self._call_interface.queue_call,\\n message,\\n )\",\n \"def get_next_record(self):\\n return_dict = {}\\n flex_fields = []\\n line = self._get_line()\\n\\n row = next(\\n csv.reader([line], dialect='excel', delimiter=self.delimiter))\\n if len(row) != self.column_count:\\n raise ResponseException(\\n \\\"Wrong number of fields in this row\\\", StatusCode.CLIENT_ERROR,\\n ValueError, ValidationError.readError)\\n for idx, cell in enumerate(row):\\n if idx >= self.column_count:\\n raise ResponseException(\\n \\\"Record contains too many fields\\\", StatusCode.CLIENT_ERROR,\\n ValueError, ValidationError.readError)\\n # Use None instead of empty strings for sqlalchemy\\n if cell == \\\"\\\":\\n cell = None\\n # self.expected_headers uses the short, machine-readable column\\n # names\\n if self.expected_headers[idx] is None and self.flex_headers[idx] is not None:\\n flex_fields.append(FlexField(header=self.flex_headers[idx], cell=cell))\\n # We skip headers which aren't expected and aren't flex\\n elif self.expected_headers[idx] is not None:\\n return_dict[self.expected_headers[idx]] = cell\\n return return_dict, flex_fields\",\n \"def readResponse(self, numElements=1):\\n while 1:\\n resp = self.serial.readline().decode()\\n if len(resp) > 5 and resp[0:5] == \\\"ERROR\\\":\\n self._waiting_response = 0\\n raise Exception(resp)\\n _LOGGER.debug(\\\"Response %s\\\" % resp)\\n if resp.find('#') > -1:\\n self._waiting_response = 0\\n break\\n if resp == '':\\n # nothing coming, have read too many lines\\n return None\\n respitems = resp.split(\\\"#\\\",maxsplit=1)[1].split()\\n if numElements == 1:\\n return respitems[-1]\\n else:\\n return respitems[-numElements:]\",\n \"def next(self, num_rows=10):\\n\\n start = self._cursor\\n stop = start + num_rows\\n self._cursor += num_rows\\n return self._data[start:stop]\",\n \"def process(self):\\n\\n try:\\n self._read_buffer += self._socket.recv(4096)\\n except socket.error as exc:\\n if exc.errno not in [errno.EAGAIN,\\n errno.EWOULDBLOCK,\\n errno.WSAEWOULDBLOCK]:\\n raise\\n response, self._read_buffer = Message.decode(self._read_buffer)\\n # Check if terminating RESPONSE_VALUE with body 00 01 00 00\\n if (response.type == Message.SERVERDATA_RESPONSE_VALUE and\\n response.body.encode(\\\"ascii\\\") == \\\"\\\\x00\\\\x01\\\\x00\\\\x00\\\"):\\n response = Message(self._response[0].id,\\n self._response[0].type,\\n \\\"\\\".join([r.body for r in self._response]))\\n self._active_requests[response.id].response = response\\n self._response = []\\n self._active_requests[response.id]\\n elif response.type == Message.SERVERDATA_RESPONSE_VALUE:\\n self._response.append(response)\\n elif response.type == Message.SERVERDATA_AUTH_RESPONSE:\\n self._active_requests[self._response[0].id].response = response\\n # Clear empty SERVERDATA_RESPONSE_VALUE sent before\\n # SERVERDATA_AUTH_RESPONSE\\n self._response = []\\n self._active_requests[response.id]\",\n \"def parse(self, response):\\n\\n rows = json.loads(response.body.decode('utf-8'))['values']\\n rows = [row for row in rows if (len(row) == 12)]\\n now = self.start_date.replace(tzinfo=timezone(self.timezone))\\n\\n for row in rows:\\n # Strip leading or trailing whitespace from all values\\n for i in range(len(row)):\\n row[i] = row[i].strip()\\n\\n # The JSON omits values for trailing columns with no values. By padding\\n # the rows out, the rest of the code can assume there will always be 14\\n # columns.\\n missing_values = 13 - len(row)\\n row.extend([''] * missing_values)\\n data = self._parse_row(row)\\n yield data\\n\\n # Only work with the next month's worth of meetings\\n # to avoid overloading database\\n delta = self._parse_start_datetime(row).replace(tzinfo=timezone(self.timezone)) - now\\n if delta.days > 30 or delta.days < 0:\\n yield None\\n else:\\n yield data\",\n \"def _fetch(self):\\n if self.closed():\\n raise self.Error(\\\"Failed to read from closed connection {!r}\\\".format(self.server.address))\\n if self.defunct():\\n raise self.Error(\\\"Failed to read from defunct connection {!r}\\\".format(self.server.address))\\n if not self.responses:\\n return 0, 0\\n\\n self._receive()\\n\\n details, summary_signature, summary_metadata = self._unpack()\\n\\n if details:\\n log_debug(\\\"S: RECORD * %d\\\", len(details)) # TODO\\n self.responses[0].on_records(details)\\n\\n if summary_signature is None:\\n return len(details), 0\\n\\n response = self.responses.popleft()\\n response.complete = True\\n if summary_signature == SUCCESS:\\n log_debug(\\\"S: SUCCESS (%r)\\\", summary_metadata)\\n response.on_success(summary_metadata or {})\\n elif summary_signature == IGNORED:\\n self._last_run_statement = None\\n log_debug(\\\"S: IGNORED (%r)\\\", summary_metadata)\\n response.on_ignored(summary_metadata or {})\\n elif summary_signature == FAILURE:\\n self._last_run_statement = None\\n log_debug(\\\"S: FAILURE (%r)\\\", summary_metadata)\\n response.on_failure(summary_metadata or {})\\n else:\\n self._last_run_statement = None\\n raise ProtocolError(\\\"Unexpected response message with signature %02X\\\" % summary_signature)\\n\\n return len(details), 1\",\n \"async def async_readchunks(self, size: int):\\n while True:\\n data = await self.read(size)\\n if data:\\n await yield_(data)\\n else:\\n return\",\n \"def _read_chunk_body(self, data):\\n resp = self.current_response\\n\\n if resp._decompressor:\\n resp.body += resp._decompressor.decompress(data[:-2])\\n else:\\n resp.body += data[:-2]\\n\\n self._stream.on_read = self._read_chunk_head\\n self._stream.read_delimiter = CRLF\",\n \"def iter_lines(response: requests.Response):\\n buffer = b''\\n while buffer[-2:] != b'\\\\r\\\\n':\\n buffer += iter_content(response, 1)\\n return buffer[:-2]\",\n \"def parse_response(self, response: requests.Response) -> Iterable[dict]:\\n resp_json = response.json()\\n if isinstance(resp_json, list):\\n results = resp_json\\n else:\\n results = resp_json.get(\\\"items\\\")\\n for row in results:\\n yield row\",\n \"def __iter__(self):\\n\\n # TODO: handle chunked encoding delimited by marker instead\\n # of content-length.\\n\\n while True:\\n length = None\\n #if line == (self._boundary+\\\"\\\\r\\\\n\\\").encode('ascii'):\\n while True:\\n l = self.response.fp.readline()\\n # print(\\\"Chunk start\\\")\\n # l = self.response.fp.readline()\\n # l = self.response.fp.readline()\\n # print(l)\\n\\n if l.startswith(b\\\"Content-Length:\\\"):\\n length = int(l.split(b\\\" \\\")[1])\\n # print(\\\"found length\\\", length)\\n\\n if length is not None and l== b\\\"\\\\r\\\\n\\\":\\n break\\n\\n yield self.response.fp.read(length)\\n \\n # Look for an empty line, signifying the end of the headers.\",\n \"def _handle_client_read_data(self, first_value, line_name):\\n stream_data = self.server.stream_data\\n self._append_value(stream_data[line_name], first_value)\\n while True:\\n data = self.rfile.readline().strip()\\n # TODO: add verbose logging\\n #print \\\"value\\\", data\\n if data == \\\"\\\":\\n break\\n\\n # TODO: add verbose logging options\\n #print \\\"[%s-%s] %s: %s\\\" % (thread_name, self.client_address[0],\\n # timestamp(), float(data))\\n self._append_value(stream_data[line_name], data)\",\n \"def __read_line(self):\\n ret = b\\\"\\\"\\n while True:\\n try:\\n pos = self.__read_buffer.index(CRLF)\\n ret = self.__read_buffer[:pos]\\n self.__read_buffer = self.__read_buffer[pos + len(CRLF):]\\n break\\n except ValueError:\\n pass\\n try:\\n nval = self.sock.recv(self.read_size)\\n self.__dprint(nval)\\n if not len(nval):\\n break\\n self.__read_buffer += nval\\n except (socket.timeout, ssl.SSLError):\\n raise Error(\\\"Failed to read data from the server\\\")\\n\\n if len(ret):\\n m = self.__size_expr.match(ret)\\n if m:\\n raise Literal(int(m.group(1)))\\n\\n m = self.__respcode_expr.match(ret)\\n if m:\\n if m.group(1) == b\\\"BYE\\\":\\n raise Error(\\\"Connection closed by server\\\")\\n if m.group(1) == b\\\"NO\\\":\\n self.__parse_error(m.group(2))\\n raise Response(m.group(1), m.group(2))\\n return ret\",\n \"async def fetch_next_part(self) -> Union[MultipartReader, BodyPartReader]:\\n ...\",\n \"def handle(self):\\n line = b\\\"\\\"\\n try:\\n while True:\\n raw = self.request.recv(1024)\\n if not raw:\\n return\\n raw = bytearray(raw)\\n while True:\\n splitter = raw.find(b\\\"\\\\r\\\")\\n if splitter > -1:\\n line = raw[1:splitter]\\n raw = raw[splitter + 1 :]\\n else:\\n break\\n\\n self.handle_line(line.decode())\\n except Exception as exc:\\n _LOGGER.error(\\n \\\"TCP: Handle: last line %s gave error: %s\\\", line.decode(), str(exc)\\n )\\n return\",\n \"def read_chunks(self):\\n buf = []\\n chunks = []\\n delays = []\\n if not self.chunked:\\n chunks.append(self.read())\\n delays.append(0)\\n else:\\n start = TIMER()\\n try:\\n while True:\\n line = self.fp.readline()\\n chunk_size = self._read_chunk_size(line)\\n if chunk_size is None:\\n raise httplib.IncompleteRead(''.join(chunks))\\n if chunk_size == 0:\\n break\\n delays.append(TIMER() - start)\\n chunks.append(self._safe_read(chunk_size))\\n self._safe_read(2) # skip the CRLF at the end of the chunk\\n start = TIMER()\\n\\n # Ignore any trailers.\\n while True:\\n line = self.fp.readline()\\n if not line or line == '\\\\r\\\\n':\\n break\\n finally:\\n self.close()\\n return chunks, delays\",\n \"def run(self) -> None:\\n\\n # Track the last timestamp we see. When we fetch_stream() again on the\\n # next iteration, we'll start from that timestamp onwards to avoid\\n # fetching every single page again. The last event or two will be\\n # still be in the response, but our de-duping will ignore those.\\n last_timestamp = None\\n\\n # Keep track of what log entries we've consumed so that we suppress\\n # duplicates. Duplicates will arise in our stream due to the way we\\n # watch for new entries.\\n consumed = set() # type: MutableSet\\n\\n # How many successful vs failed fetch_stream calls. If we consistently see\\n # failures but we never see a successful attempt, we should raise an exception\\n # and stop.\\n success_count = 0\\n failure_count = 0\\n\\n while not self.stopped.wait(0.2):\\n try:\\n for entry in fetch_stream(self.stream, start_time = last_timestamp):\\n if entry[\\\"eventId\\\"] not in consumed:\\n consumed.add(entry[\\\"eventId\\\"])\\n\\n last_timestamp = entry[\\\"timestamp\\\"]\\n\\n self.consumer(entry)\\n except (ClientError, BotocoreConnectionError):\\n failure_count += 1\\n if failure_count > MAX_FAILURES and not success_count:\\n raise\\n else:\\n success_count += 1\",\n \"def _line_iter(self, stream):\\n buf = b''\\n while True:\\n if len(buf) < self.blocksize:\\n buf += stream.read(self.blocksize - len(buf))\\n if not buf:\\n break\\n i = buf.find(b'\\\\n')\\n if i < 0:\\n yield buf\\n buf = b''\\n else:\\n yield buf[:i + 1]\\n buf = buf[i + 1:]\",\n \"def _receive(self, transport, response_schema, timeout=10):\\n in_data = \\\"\\\"\\n start_time = time.time()\\n duration = 0\\n while duration < timeout:\\n in_data = in_data + transport.receive().decode(self.ENCODING)\\n try:\\n response = response_schema.load(in_data)\\n logger.debug(f\\\"Received SOS Access Data: {in_data}\\\")\\n return response\\n except XMLParseError:\\n duration = time.time() - start_time\\n continue\\n\\n raise SOSAccessClientException(\\\"Reading response within timeout failed\\\")\",\n \"async def read_stream(self, stream_read_request_body: StreamReadRequestBody = Body(None, description=\\\"\\\")) -> StreamRead:\\n adapter = self._create_low_code_adapter(manifest=stream_read_request_body.manifest)\\n schema_inferrer = SchemaInferrer()\\n\\n if stream_read_request_body.record_limit is None:\\n record_limit = self.max_record_limit\\n else:\\n record_limit = min(stream_read_request_body.record_limit, self.max_record_limit)\\n\\n slices = []\\n log_messages = []\\n try:\\n for message_group in self._get_message_groups(\\n adapter.read_stream(stream_read_request_body.stream, stream_read_request_body.config),\\n schema_inferrer,\\n record_limit,\\n ):\\n if isinstance(message_group, AirbyteLogMessage):\\n log_messages.append({\\\"message\\\": message_group.message})\\n else:\\n slices.append(message_group)\\n except Exception as error:\\n # TODO: We're temporarily using FastAPI's default exception model. Ideally we should use exceptions defined in the OpenAPI spec\\n self.logger.error(f\\\"Could not perform read with with error: {error.args[0]} - {self._get_stacktrace_as_string(error)}\\\")\\n raise HTTPException(\\n status_code=400,\\n detail=f\\\"Could not perform read with with error: {error.args[0]}\\\",\\n )\\n\\n return StreamRead(\\n logs=log_messages,\\n slices=slices,\\n test_read_limit_reached=self._has_reached_limit(slices),\\n inferred_schema=schema_inferrer.get_stream_schema(stream_read_request_body.stream)\\n )\",\n \"async def fetch_next_block(self):\\n try:\\n return await self._execution_context.fetch_next_block()\\n except CosmosHttpResponseError as e:\\n if _is_partitioned_execution_info(e): #cross partition query not servable\\n query_to_use = self._query if self._query is not None else \\\"Select * from root r\\\"\\n query_execution_info = _PartitionedQueryExecutionInfo(await self._client._GetQueryPlanThroughGateway\\n (query_to_use, self._resource_link))\\n self._execution_context = await self._create_pipelined_execution_context(query_execution_info)\\n else:\\n raise e\\n\\n return await self._execution_context.fetch_next_block()\",\n \"async def readchunk(self) -> Tuple[bytes, bool]:\\n ...\",\n \"def process(self):\\n self.reader += 1\",\n \"def GetNextLine(self):\\n\\t\\tline = self._fin.readline()\\n\\n\\t\\tif len(line) == 0:\\n\\t\\t\\twx.MessageBox(\\\"All records processed\\\", \\\"DONE!\\\", wx.ICON_INFORMATION | wx.OK)\\n\\t\\t\\tself.EndRun()\\n\\t\\t\\t\\n\\t\\telse:\\n\\t\\t\\tline = line[:-1]\\n\\t\\t\\tobj = json.loads(line)\\n\\t\\t\\tself._textControl.SetValue(obj[\\\"description\\\"])\\n\\t\\t\\tself._existingClass = obj[\\\"class\\\"]\\n\\t\\t\\tself._existingClassLabel.SetLabel(obj[\\\"class\\\"])\",\n \"async def _stream_next_event(stream):\\n while True:\\n last_new_line = False\\n data = b\\\"\\\"\\n\\n while True:\\n dat = await stream.read(1)\\n if dat == b\\\"\\\\n\\\" and last_new_line:\\n break\\n data += dat\\n last_new_line = dat == b\\\"\\\\n\\\"\\n\\n conv = data.decode(\\\"utf-8\\\").strip()[6:]\\n\\n if conv != \\\"ping\\\":\\n break\\n return json.loads(conv)\",\n \"def _handle_reading(self, soc):\\n chunk = soc.recv(_RECV_CHUNK_SIZE)\\n if not chunk:\\n self._handle_error(soc) # unexpected EOF\\n return\\n if soc not in self._reading:\\n self._reading[soc] = \\\"\\\"\\n self._reading[soc] += chunk.decode(\\\"utf-8\\\")\\n\\n if self._reading[soc].endswith(\\\"\\\\r\\\\n\\\\r\\\\n\\\"):\\n # Finished reading request headers, don't expect request body.\\n self._log(\\\"read %r\\\" % self._reading[soc])\\n headers = self._reading[soc]\\n self._reading[soc] = \\\"\\\"\\n\\n if not headers.startswith(\\\"GET \\\"):\\n raise Exception(\\\"Only GET requests are supported.\\\")\\n self._writing[soc], hook = self._responses[headers.split()[1]]\\n\\n # Move the socket to list of things waiting to write.\\n self._read_list.remove(soc)\\n self._write_list.append(soc)\\n\\n hook(self, soc)\",\n \"async def __parse_csv(responses: SourceResponses) -> list[dict[str, str]]:\\n rows = []\\n for response in responses:\\n csv_text = (await response.text()).strip()\\n rows.extend(list(csv.DictReader(StringIO(csv_text, newline=\\\"\\\"))))\\n return rows\",\n \"def _read_data(self):\\n while True:\\n try:\\n data = yield from asyncio.wait_for(self._socket.recv(), 1)\\n except asyncio.TimeoutError:\\n continue\\n except asyncio.CancelledError:\\n break\\n except ConnectionClosed:\\n break\\n\\n self._push_packet(data)\\n\\n self._loop.call_soon(self.close)\",\n \"def next(self, num_rows=10):\\n\\n start = self._cursor\\n stop = start + num_rows\\n self._cursor += num_rows\\n return self._data.iloc[start:stop]\",\n \"def process_records(self, shard_iterator: str, shard_id: str):\\n response = self.client.get_records(\\n ShardIterator=shard_iterator\\n )\\n\\n logger.debug('Getting data from shard: {shard_id}', extra=response)\\n records = response['Records']\\n\\n if len(records) == 0:\\n logger.info(f'Nothing to process for shard: \\\"{shard_id}\\\"')\\n self._empty_shards.append(shard_id)\\n else:\\n for item in records:\\n if self.item_callback:\\n data = json.loads(item.get('Data'))\\n order = data.get('order')\\n contents = data.get('contents')\\n self.item_callback(order, contents)\\n self._sequences[shard_id] = item['SequenceNumber']\\n\\n next_shard_iterator = response['NextShardIterator']\\n date = response.get('ResponseMetadata').get('HTTPHeaders').get('date')\\n self._iterators[shard_id] = next_shard_iterator, date\",\n \"def enter_read_loop(self):\\n\\n try:\\n while True:\\n try:\\n request = DAPBaseMessage.recv(self._current_client)\\n except Exception as e:\\n # TODO send error\\n traceback.print_exc()\\n continue\\n\\n if request is None:\\n # client terminated without termination request\\n return\\n try:\\n self.resolve_message(request)\\n except Exception as e:\\n # TODO send error\\n traceback.print_exc()\\n self.next_seq += 1\\n DAPErrorResponse.create(self.next_seq, rq.seq, False, message=\\\"Error\\\").send(self._current_client)\\n continue\\n\\n if self._current_client is None:\\n self._ready_for_events = False\\n return # terminated\\n\\n except BaseException as e:\\n # failure while communicating\\n traceback.print_exc()\\n pass\\n finally:\\n # final handler, clear active client\\n self._current_client = None\\n self._ready_for_events = False\\n\\n debugger.reset()\",\n \"def stream(self, batch):\\n response = self.post(batch)\\n try:\\n for i, result_data in grouped(response):\\n result = JobResult.hydrate(assembled(result_data), batch)\\n log.info(\\\"< %s\\\", result)\\n yield result\\n finally:\\n response.close()\",\n \"def parse(handle):\\n while True:\\n record = __read(handle)\\n if not record:\\n break\\n yield record\",\n \"async def _load_next_chunk(self):\\n raise NotImplementedError\",\n \"def read_response(self, read_lines=True):\\n response = None\\n if read_lines:\\n response = self.stdout_stream.readlines()\\n else:\\n response = self.stdout_stream.read()\\n return response\",\n \"def fetch(self):\\n # type: () -> List[List[Any]]\\n if self._request.next_uri is None:\\n self._finished = True\\n return []\\n response = self._request.get(self._request.next_uri)\\n status = self._request.process(response)\\n if status.columns:\\n self._columns = status.columns\\n self._stats.update(status.stats)\\n if status.next_uri is None:\\n self._finished = True\\n return status.rows\",\n \"async def get_records(self):\\n\\n callback_coro = self.consumer._get_checkpoint_callback()\\n while True:\\n try:\\n if self._stop:\\n return\\n records = await self._get_records()\\n if len(records) > 0:\\n self.last_sequence_number = records[-1]['SequenceNumber']\\n yield records\\n\\n # FIXME: Could there be empty records in the list? If yes, should we filter them out?\\n self.record_count += len(records)\\n if self.record_count > self.checkpoint_interval:\\n\\n if callback_coro:\\n if not await callback_coro(self.shard_id, records[-1]['SequenceNumber']):\\n raise ShardClosedException('Shard closed by application request')\\n if self.dynamodb:\\n await self.dynamodb.checkpoint(seq=records[-1]['SequenceNumber'])\\n self.record_count = 0\\n self.retries = 0\\n except RetryGetRecordsException as e:\\n sleep_time = min((\\n 30,\\n (self.retries or 1) * self.sleep_time\\n ))\\n if self.retries > 5:\\n log.debug(\\\"Retrying get_records (#%d %ds): %s\\\", self.retries + 1, sleep_time, e)\\n if not await self.interruptable_sleep(sleep_time):\\n return\\n self.retries += 1\\n except ReaderExitException:\\n self.is_running = False\\n self.consumer.reader_exited(self.shard_id)\\n except Exception as e:\\n self.is_running = False\\n # Reporting exit on exceptions\\n log.debug(\\\"Shard %s got exception: %s\\\", self.shard_id, e)\\n self.consumer.reader_exited(self.shard_id)\\n raise e\",\n \"def _yield_rows(self, ws_name):\\n for idx, row in self._get_rows(ws_name):\\n if idx >= WS_ROW_OFFSETS[ws_name] and \\\\\\n len(row[0].value):\\n yield idx, row\",\n \"def _load_reading_row(self):\\n\\n raise NotImplementedError()\",\n \"def _get_data(self):\\n while not (self.closed or self.ended):\\n block = self.stream.read(8192)\\n with self.lock:\\n if len(block) == 0:\\n self.ended = True\\n else:\\n self.data.append(block)\\n self.available.set()\",\n \"def read_records(\\n self, stream_state: Mapping[str, Any] = None, stream_slice: Mapping[str, Any] = None, **kwargs\\n ) -> Iterable[Mapping[str, Any]]:\\n self.current_slice = stream_slice\\n records = super().read_records(stream_slice=stream_slice, stream_state=stream_state, **kwargs)\\n if stream_state:\\n for record in records:\\n if record[self.cursor_field] > stream_state.get(self.cursor_field):\\n yield record\\n else:\\n yield from records\",\n \"def parse_response(self, response: requests.Response, **kwargs) -> Iterable[Mapping]:\\n json_response = response.json().get(self.response_root_name)\\n for resp in json_response:\\n if self.response_item_name not in resp:\\n error_text = f\\\"JSON field named '{self.response_item_name}' is absent in the response for {self.name} stream\\\"\\n self.logger.error(error_text)\\n raise SnapchatMarketingException(error_text)\\n yield resp.get(self.response_item_name)\",\n \"def extract_chunk_records(buf, offset):\\n try:\\n chunk = Evtx.Evtx.ChunkHeader(buf, offset)\\n except:\\n raise ParseError('failed to parse chunk header')\\n\\n cache = {}\\n for record in chunk.records():\\n try:\\n record_xml = Evtx.Views.evtx_record_xml_view(record, cache=cache)\\n eid = evtxtract.utils.get_eid(record_xml)\\n yield RecoveredRecord(record.offset(), eid, record_xml)\\n\\n except UnicodeEncodeError:\\n logger.info(\\\"Unicode encoding issue processing record at 0x%X\\\", record.offset())\\n continue\\n\\n except UnicodeDecodeError:\\n logger.info(\\\"Unicode decoding issue processing record at 0x%X\\\", record.offset())\\n continue\\n\\n except Evtx.Evtx.InvalidRecordException:\\n logger.info(\\\"EVTX parsing issue processing record at 0x%X\\\", record.offset())\\n continue\\n\\n except Exception as e:\\n logger.info(\\\"Unknown exception processing record at 0x%X\\\", record.offset(), exc_info=True)\\n continue\",\n \"async def _receive_response(\\n self, request: Request, stream_id: int\\n ) -> typing.Tuple[int, typing.List[typing.Tuple[bytes, bytes]]]:\\n while True:\\n event = await self._receive_stream_event(request, stream_id)\\n if isinstance(event, h2.events.ResponseReceived):\\n break\\n\\n status_code = 200\\n headers = []\\n for k, v in event.headers:\\n if k == b\\\":status\\\":\\n status_code = int(v.decode(\\\"ascii\\\", errors=\\\"ignore\\\"))\\n elif not k.startswith(b\\\":\\\"):\\n headers.append((k, v))\\n\\n return (status_code, headers)\",\n \"def process_response(self, response: Dict) -> Iterator[dict]:\",\n \"def next_chunk(self):\\n if self._unconsumed:\\n data = self._unconsumed.pop()\\n else:\\n data = self._iterator.next() # Might raise StopIteration\\n self._pos += len(data)\\n return data\",\n \"def _process_stream(self):\\n input_df = self._read_stream()\\n\\n clean_df = input_df \\\\\\n .select(from_json(input_df.value.cast('string'),\\n self.schema).alias('value'))\\n explode_df = clean_df.select('value.*')\\n\\n enrich_df = explode_df \\\\\\n .withColumn('event_time', explode_df.event_time.cast(TimestampType())) \\\\\\n .withColumn('process_time', current_timestamp())\\n\\n return enrich_df\",\n \"async def next(self) -> Optional[Union[MultipartReader, BodyPartReader]]:\\n ...\",\n \"async def next(self) -> Optional[Union[MultipartReader, BodyPartReader]]:\\n ...\",\n \"def iter_records(self):\\n\\n decomp_type = 'gzip'\\n block_size = 16384\\n\\n self.reader = DecompressingBufferedReader(self.fh,\\n block_size=block_size)\\n self.offset = self.fh.tell()\\n\\n next_line = None\\n\\n while True:\\n try:\\n record = self._next_record(next_line)\\n yield record\\n except EOFError:\\n break\\n\\n self.read_to_end(record)\\n\\n # for non-compressed, consume blank lines here\\n if not self.reader.decompressor:\\n next_line = self._consume_blanklines()\\n if next_line is None:\\n # at end of file\\n break\\n\\n # reset reader for next member\\n else:\\n self.reader.read_next_member()\",\n \"def get_response_content_iterator(self):\\n return self.__response.iter_lines()\",\n \"def on_readable(self):\\n data = self.read(2048)\\n if len(data) == 0:\\n self.mark_down()\\n if self.response is None:\\n return\\n else:\\n self.response.on_connection_down(self)\\n return\\n elif self.response is None:\\n self.receive_bytes = b''.join([self.receive_bytes, data])\\n terminal_idx = self.receive_bytes.find(b'\\\\r\\\\n\\\\r\\\\n')\\n if terminal_idx < 0:\\n return\\n\\n header_bytes = self.receive_bytes[:terminal_idx]\\n remain_bytes = self.receive_head_bytes[terminal_idx + 4:]\\n self.response = self.on_process_request_header(header_bytes, remain_bytes)\\n else:\\n self.response.on_body_received(self, data)\",\n \"def read(self, batch_size=1):\\n cur_q_size = len(self._queue)\\n while cur_q_size < batch_size:\\n if self._thread.get_exception() is not None:\\n break\\n time.sleep(0.1)\\n cur_q_size = len(self._queue)\\n\\n exception = self._thread.get_exception()\\n if isinstance(exception, EndOfVideoError):\\n if cur_q_size == 0:\\n raise EndOfVideoError()\\n elif cur_q_size <= batch_size:\\n data = self._read_all()\\n else:\\n data = self._read(batch_size)\\n elif isinstance(exception, ConnectionBrokenError):\\n raise ConnectionBrokenError()\\n else:\\n # XXX: In this case we are assuming that everything is fine,\\n # and current queue size should greater than the batch\\n # size.\\n data = self._read(batch_size)\\n return data\",\n \"def recv_stream_resp(self):\\n return_mess = b''\\n while True:\\n return_mess += self.recv_resp_simple(1)\\n if return_mess[-2:] == self.end_mess_bytes:\\n start_idx = return_mess.rfind(b'RUP') # Find start of response\\n if start_idx < 0:\\n continue\\n cut_mess = return_mess[start_idx:]\\n split_mess = cut_mess.split()\\n return_code = int(split_mess[1])\\n\\n # Sometimes we have overflow of data when attempting to stop stream - probably extra scan data we\\n # haven't picked up yet. So we try to decode it all, but if we hit an error we just decode the last\\n # few bytes which contain the message we are interested in\\n # try:\\n # mess_ascii = return_mess.decode(self.encoding)\\n # except UnicodeDecodeError as e:\\n # # print('Error decoding message: {}'.format(e))\\n # mess_ascii = return_mess[-7:].decode(self.encoding)\\n # return_code = int(mess_ascii[-3])\\n if self.gui_message is not None:\\n if return_code == 0:\\n self.gui_message.message('[LSP] Response all good!')\\n else:\\n self.gui_message.message('[LSP] Error code: %i' % return_code)\\n else:\\n if return_code == 0:\\n print('[LSP] Response all good!')\\n else:\\n print('[LSP] Error code: %i' % return_code)\\n return return_code\",\n \"def _process_response(self, response, marker_elems=None):\\r\\n body = response.read()\\r\\n #print body\\r\\n if '<Errors>' not in body:\\r\\n rs = ResultSet(marker_elems)\\r\\n h = handler.XmlHandler(rs, self)\\r\\n xml.sax.parseString(body, h)\\r\\n return rs\\r\\n else:\\r\\n raise MTurkRequestError(response.status, response.reason, body)\",\n \"def read_until_eof(self):\\n with self.reading:\\n try:\\n while True:\\n self.read_buffer.enqueue((yield self.base.read(self.bufsize)))\\n except BrokenPipeError:\\n pass\\n do_return(self.read_buffer.dequeue())\",\n \"def handle(self):\\n req_lines = self._read_lines()\\n if not req_lines:\\n self.cleanup()\\n for req in req_lines:\\n log.debug('%s => %s', self.client, req)\\n req = req.split()\\n cmd = req.pop(0)\\n try:\\n self.get_command(cmd)(req)\\n result = [OK]\\n except Exception as error:\\n result = [ERROR, error.message]\\n self.send_line(' '.join(result))\\n self.flush()\",\n \"def load_next_response(self):\\n if self.response_info['next']:\\n self.response = requests.get(self.response_info['next'])\\n self.response_info = self.response.json()\",\n \"def process(self, chunk):\\n self._buf += chunk\\n\\n # Streams are `\\\\r\\\\n`-separated JSON messages.\\n raw_lines = self._buf.split(b\\\"\\\\r\\\\n\\\")\\n\\n # If only one element in the split, then there wasn't a CRLF.\\n if len(raw_lines) > 1:\\n\\n # The last element may be a b'', which is perfectly fine.\\n self._buf = raw_lines[-1]\\n\\n # Blank lines are keep-alive messages.\\n self._mailbox.extend(l for l in raw_lines[:-1] if l.strip())\",\n \"def handle_read(self):\\n data, ancdata, _, _ = recvmsg(self.socket, 65536, 4096)\\n\\n if not data:\\n return self.handle_close()\\n\\n fds, cred = parse_ancdata(ancdata)\\n\\n if self.header_buffer is not None:\\n self.header_buffer += data.decode()\\n\\n linefeed = self.header_buffer.find('\\\\n')\\n if linefeed == -1:\\n return\\n\\n header = json.loads(self.header_buffer[:linefeed])\\n data = self.header_buffer[linefeed + 1:]\\n self.header_buffer = None\\n\\n self.handle_header(fds, header)\\n\\n if not data:\\n return\\n\\n meta = Metadata(time=datetime.now(), pid=cred.pid,\\n comm=(comm_for_pid(cred.pid) or \\\"unknown\\\"),\\n unit=(unit_for_pid(cred.pid) or self.unit))\\n\\n if meta.unit is not None:\\n log = self.log_manager.get(meta.unit, \\\"stdio\\\")\\n log.write(data, meta)\",\n \"def _read (self, sock, max_buffer, read_size=64*1024, proxied=False):\\n\\t\\t# yield request, content\\n\\t\\t# request is the text that form the request header\\n\\t\\t# content any text which is related to the current request after the headers\\n\\n\\t\\tyield ''\\n\\n\\t\\tr_buffer = ''\\n\\t\\tnb_to_send = 0\\n\\t\\tseek = 0\\n\\t\\tmasquerade = None\\n\\n\\t\\t# mode can be one of : request, chunk, extension, relay\\n\\t\\t# request : we are reading the request (read all you can until a separator)\\n\\t\\t# extra-headers : we are reading data until a separator\\n\\t\\t# chunked : we are reading chunk-encoded darta\\n\\t\\t# transfer : we are reading as much as requested in remaining\\n\\t\\t# passthrough : read as much as can to be relayed\\n\\n\\t\\tmode = 'proxy' if proxied else 'http'\\n\\t\\thttp_request = ''\\n\\t\\tdata = ''\\n\\n\\t\\twhile True:\\n\\t\\t\\ttry:\\n\\t\\t\\t\\twhile True:\\n\\t\\t\\t\\t\\tif mode != 'new-request' and (mode != 'transfer' or r_buffer == ''):\\n\\t\\t\\t\\t\\t\\tnew_data = sock.recv(read_size)\\n\\t\\t\\t\\t\\t\\tif not new_data:\\n\\t\\t\\t\\t\\t\\t\\tbreak # read failed so we abort\\n\\n\\t\\t\\t\\t\\t\\tr_buffer += new_data\\n\\n\\t\\t\\t\\t\\telif mode == 'new-request':\\n\\t\\t\\t\\t\\t\\tmode = 'http'\\n\\n\\t\\t\\t\\t\\tif mode == 'proxy':\\n\\t\\t\\t\\t\\t\\tmasquerade, r_buffer, mode = self.processProxyHeader(r_buffer, mode)\\n\\t\\t\\t\\t\\t\\tif masquerade is None:\\n\\t\\t\\t\\t\\t\\t\\tbreak\\n\\n\\t\\t\\t\\t\\t\\telif not masquerade:\\n\\t\\t\\t\\t\\t\\t\\tcontinue\\n\\n\\t\\t\\t\\t\\t\\tself.setPeer(masquerade)\\n\\n\\t\\t\\t\\t\\t# check for a new http header\\n\\t\\t\\t\\t\\tif mode == 'http':\\n\\t\\t\\t\\t\\t\\tr_buffer = r_buffer.lstrip('\\\\r\\\\n')\\n\\n\\t\\t\\t\\t\\t\\thttp_request, r_buffer, seek = self.checkRequest(r_buffer, max_buffer, seek)\\n\\t\\t\\t\\t\\t\\tif http_request is None:\\n\\t\\t\\t\\t\\t\\t\\tbreak\\n\\n\\t\\t\\t\\t\\t# all modes that are not directly related to reading a new request\\n\\t\\t\\t\\t\\tif mode != 'http':\\n\\t\\t\\t\\t\\t\\tdata, r_buffer, mode, nb_to_send, seek = self.process(r_buffer, mode, nb_to_send, max_buffer, seek)\\n\\t\\t\\t\\t\\t\\tif data is None:\\n\\t\\t\\t\\t\\t\\t\\tbreak\\n\\n\\t\\t\\t\\t\\tif mode == 'http' and http_request:\\n\\t\\t\\t\\t\\t\\thttp_response, http_request = [http_request], ''\\n\\t\\t\\t\\t\\t\\tseek = 0\\n\\n\\t\\t\\t\\t\\t\\tmode, nb_to_send = yield http_response, ['']\\n\\n\\t\\t\\t\\t\\telif data:\\n\\t\\t\\t\\t\\t\\tdata_response, data = [data], ''\\n\\t\\t\\t\\t\\t\\tyield [''], data_response\\n\\n\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\tyield [''], ['']\\n\\n\\n\\t\\t\\t\\t# break out of the outer loop as soon as we leave the inner loop\\n\\t\\t\\t\\t# through normal execution\\n\\t\\t\\t\\tbreak\\n\\n\\t\\t\\texcept socket.error, e:\\n\\t\\t\\t\\tif e.args[0] in errno_block:\\n\\t\\t\\t\\t\\tyield [''], ['']\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tbreak\\n\\n\\t\\tyield [None], [None]\",\n \"def _get_next_record(self):\\n # Read next record from xlsx file\\n row = self.ds_reader.next()\\n if len(row) == 0:\\n raise StopIteration\\n \\n # build record\\n record = {'__row':row[0].row}\\n for cell in row:\\n record[str(cell.column)] = cell.internal_value\\n #if cell.internal_value != None:\\n # self.ds_processedBytes += len(cell.internal_value)\\n \\n # finished\\n return record\",\n \"def parse(stream, idx):\\n\\n # Skip comment lines\\n stream = filter(lambda x: not x.startswith('#'), stream)\\n\\n # Ignore empty lines.\\n stream = filter(lambda x: x.strip(), stream)\\n\\n # Format the stream.\\n stream = csv.reader(stream, delimiter=delimiter)\\n\\n # Generate empty values on missing columns.\\n for row in stream:\\n try:\\n yield (row[idx], None)\\n except IndexError as exc:\\n yield ('', None)\",\n \"def next(self, rows: List[Row]) -> List[Row]:\\n if not rows:\\n return []\\n input_row_index = self._get_row_index(rows[0])\\n if input_row_index < len(self.table_data) - 1 and input_row_index != -1:\\n return [self.table_data[input_row_index + 1]]\\n return []\",\n \"async def fetch_next_block(self):\\n\\n results = []\\n for _ in range(self._page_size):\\n try:\\n results.append(await self.__anext__())\\n except StopAsyncIteration:\\n # no more results\\n break\\n return results\",\n \"def _read_chunked(self):\\r\\n buf = \\\"\\\"\\r\\n size = 1\\r\\n while size:\\r\\n size = int(self._read_line(), 16)\\r\\n buf += self._read_num_bytes(size)\\r\\n self._read_num_bytes(2) # CRLF\\r\\n return buf\",\n \"def _read_range(self, start=0, end=None):\\n max_read_size = self.channel.connection.negotiate_response.max_read_size\\n offset = start\\n response_buffers = []\\n while end is None or offset < end:\\n if end is not None:\\n max_read_size = min(end - offset, max_read_size)\\n available = min(\\n self.channel.connection.credits * smb2.BYTES_PER_CREDIT,\\n max_read_size,\\n )\\n try:\\n read_resp = self.channel.read(self, available, offset)\\n response_buffers.append(read_resp)\\n offset += len(read_resp)\\n except ResponseError as re:\\n if re.response.status == ntstatus.STATUS_END_OF_FILE:\\n break\\n raise\\n read_buffer = b\\\"\\\".join(rb.tobytes() for rb in response_buffers)\\n if read_buffer:\\n self._offset = start + len(read_buffer)\\n # update the EOF marker if we read past it\\n self._end_of_file = max(self.end_of_file, self._offset)\\n return read_buffer\",\n \"def fetch_message_batch(self, callback=None):\\n\\n # on response from server return with messages\\n def _on_response(*args):\\n if callback:\\n self.offset += len(args[0])\\n callback(*args)\\n\\n self.inbox.search(self.search_string, full=True,\\n limit=self.per_page, offset=self.offset, callback=_on_response)\",\n \"def next(self):\\n return self.read_message()\",\n \"def feed_records(self):\\n if not self.stats_file:\\n return\\n\\n with open(self.stats_file) as fh:\\n reader = reverse_file(fh)\\n for line in reader:\\n if line is None:\\n return\\n if not line:\\n continue\\n\\n try:\\n js = json.loads(line)\\n except Exception as e:\\n continue\\n\\n yield js\",\n \"def next(self, payload):\\n\\n session = ZuoraApiSession(self.org_uid)\\n\\n # There are 2 different endpoints for querying.\\n # One which takes the initial query string and one which takes a cursor if there is another page of data.\\n if self.sync_data.cursor:\\n response = session.post(\\n QUERY_MORE_URI,\\n json={'queryLocator': self.sync_data.cursor}\\n )\\n else:\\n response = session.post(\\n QUERY_URI,\\n json={'queryString': self._get_query()}\\n )\\n\\n endpoint = ENDPOINTS[self.sync_data.endpoint_index]\\n\\n items = response.get('records', [])\\n new_payload = {}\\n has_more_items = False\\n max_updated_at = None\\n\\n if items:\\n # Parse datetime strings\\n updated_dates = [parser.parse(item['UpdatedDate']) for item in items]\\n\\n # Retrieve the max UpdatedDate to use in the query for the next changeset\\n max_updated_at = items[updated_dates.index(max(updated_dates))]['UpdatedDate']\\n\\n item_objects = []\\n\\n for item in items:\\n item_objects.extend(\\n sync_utils.create_items(\\n self.org_uid,\\n self.org.provider,\\n self.org.changeset,\\n endpoint,\\n item['Id'],\\n item\\n )\\n )\\n\\n sync_utils.save_items(item_objects)\\n\\n # If there are more pages to fetch, store the cursor\\n if 'queryLocator' in response:\\n logging.info(\\\"There is another page of {}\\\".format(endpoint))\\n self.sync_data.cursor = response['queryLocator']\\n new_payload['max_updated_at'] = max_updated_at\\n\\n else:\\n logging.info(\\\"no more data expected for endpoint {}\\\".format(endpoint))\\n marker = max_updated_at or payload.get('max_updated_at')\\n\\n if marker:\\n logging.info(\\\"setting updated_at marker for {} to {}\\\".format(endpoint, marker))\\n self.sync_data.markers[self.sync_data.endpoint_index] = marker\\n\\n self.sync_data.endpoint_index += 1\\n self.sync_data.cursor = None\\n\\n complete = self.sync_data.endpoint_index == len(ENDPOINTS)\\n\\n if complete:\\n self.sync_data.endpoint_index = 0\\n\\n self.sync_data.put()\\n complete = complete and not has_more_items\\n\\n return complete, new_payload\",\n \"def processData(self):\\n _lastLine = True\\n _firstRead = True\\n n = 0\\n while self.console.working:\\n remotelog = ''\\n response = ''\\n remote_log_data = ''\\n remotelogsize = 0\\n\\n # specify range depending on if the last line\\n # is in the remote log chunk or not\\n if _lastLine:\\n b = 'bytes=-10000'\\n else:\\n b = 'bytes=-100000'\\n\\n headers = {\\n 'User-Agent' : user_agent,\\n 'Range' : b,\\n 'Accept-encoding' : 'gzip'\\n }\\n\\n request = urllib2.Request(self._url, None, headers)\\n\\n # get remote log url response and headers\\n try:\\n response = urllib2.urlopen(request)\\n headers = response.info()\\n\\n # buffer/download remote log\\n if response != '':\\n remote_log_data = response.read()\\n remotelogsize = round((len(remote_log_data) / float(1024)), 2)\\n # self.verbose('Downloaded: %s KB total' % remotelogsize)\\n\\n try:\\n # close remote file\\n response.close()\\n except AttributeError, e:\\n self.error('ERROR: %s' % e)\\n\\n except (urllib2.HTTPError, urllib2.URLError), e:\\n self.error('HTTP ERROR: %s' % e)\\n except socket.timeout:\\n self.error('TIMEOUT ERROR: socket timed out!')\\n\\n # start keeping the time\\n start = time.time()\\n\\n # decompress remote log and return for use\\n # First, make sure that there is domething worth decompressing\\n # In case the server has just done a restart\\n if len(remote_log_data) > 0:\\n try:\\n #self.debug('Content-Encoding: %s' % headers.get('Content-Encoding'))\\n if headers.get('Content-Encoding') == 'gzip':\\n compressedstream = StringIO.StringIO(remote_log_data)\\n gzipper = gzip.GzipFile(fileobj=compressedstream)\\n remotelog = gzipper.read()\\n else:\\n remotelog = remote_log_data\\n except IOError, e:\\n remotelog = ''\\n self.error('IOERROR: %s' % e)\\n\\n if os.path.exists(self.locallog) and os.path.getsize(self.locallog) > 0 and not _firstRead:\\n\\n # check if last line is in the remote log chunk\\n if remotelog.find(self.lastlines) != -1:\\n _lastLine = True\\n n = 0\\n\\n # we'll get the new lines i.e what is available after the last line\\n # of our local log file\\n try:\\n checklog = remotelog.rpartition(self.lastlines)\\n newlog = checklog[2]\\n # remove any broken last line\\n i = newlog.rfind ('\\\\r\\\\n')\\n newlog = newlog[:i + 2]\\n # remove any blank lines\\n while newlog[-4:-2] == '\\\\r\\\\n':\\n newlog = newlog[:-2]\\n except ValueError, error:\\n self.error ('ValueError: %s' % error)\\n newlog = ''\\n\\n # remove any blank lines from end\\n # append the additions to our log if there is something and update lazy cursor\\n if len(newlog) > 0:\\n output = open(self.locallog,'ab')\\n output.write(newlog)\\n output.close()\\n self.lastlines = remotelog[-1000:] \\n self.debug('downloaded %s KB and added %s char(s) to log' % (remotelogsize, len(newlog)))\\n\\n else:\\n _lastLine = False\\n self.debug('can\\\\'t find last line in the log chunk: checking again...')\\n n += 1\\n\\n # check once in a larger chunk and if we are still unable to find last line\\n # in the remote chunk, restart the process\\n if n == 2:\\n self.debug('Logs rotated or unable to find last line in remote log, restarting process...')\\n self.writeCompletelog(self.locallog, remotelog)\\n _lastLine = True\\n n = 0\\n\\n else:\\n self.debug('writing first log read')\\n self.writeCompletelog(self.locallog, remotelog)\\n _firstRead = False\\n\\n # calculate how long it took to process\\n timespent = time.time() - start\\n\\n # calculate time to wait until next request.\\n timeout = float(self.timeout)\\n\\n # self.verbose('Given timeout value is %s seconds' % timeout)\\n # self.verbose('Total time spent to process the downloaded file is %s seconds' % timespent)\\n\\n # Calculate sleep time for next request. Adding 0.1 secs to prevent HTTP Error 403 errors\\n wait = float((timeout - timespent) + 0.1)\\n\\n if wait <= 0:\\n wait = 1\\n\\n # make the plugin thread fast-killable\\n i = 0\\n w = int(wait)\\n while i < w and self.console.working:\\n time.sleep(1)\\n i += 1\\n time.sleep(wait - w)\\n\\n self.verbose('B3 is down: stopping Cod7Http plugin')\",\n \"def recv_read_response(self, recv_payload): \\n\\t#Only unpack the headers because we want to store the file data as binary\\n\\tunpacked_payload = struct.unpack('!H3IQ', recv_payload[:22])\\n\\tstatus = unpacked_payload[0:1][0]\\n\\tepoch_no = unpacked_payload[1:2][0]\\n\\thandle_no = unpacked_payload[2:3][0]\\t\\n\\t\\n\\t#Check that file handle is the same, to make sure it is the same file request.\\n\\tif (self.epoch_no == epoch_no and self.handle_no == handle_no):\\n\\t start_position = unpacked_payload[3:4][0]\\n\\t num_bytes_been_read = unpacked_payload[4:5][0] \\n\\t # If we receive less bytes than the number we requested to read, this means that\\n\\t # end of file has been reached\\n\\t if (num_bytes_been_read < self.NUM_BYTES_TO_READ):\\n\\t\\tself.eof = True\\n\\t data_to_write = recv_payload[22:]\\t \\n\\t #If status field says that response contains real data: Append to file. Otherwise react \\n\\t #depending on error code received.\\n\\t #Status 00 = OK\\n\\t #Status 01 = Epoch no. of file handle doesnt match epoch no. of current invocation\\n\\t #Status 10 = No context found for file-handle and no data has been read\\n\\t #Status 11 = Context could be found but start position out of range\\n\\t if (status == 0b00):\\n\\t\\tself.file_append.seek(start_position)\\n\\t\\tself.file_append.write(data_to_write)\\n\\t elif (status == 0b01):\\n\\t\\tprint(\\\"Error: Epoch no. of file handle doesnt match epoch no. of current invocation\\\")\\n\\t\\tsys.exit()\\n\\t elif (status == 0b10):\\n\\t\\tprint(\\\"Error: No context found for file-handle and no data has been read\\\")\\n\\t\\tsys.exit()\\n\\t elif(status == 0b11):\\n\\t\\tprint(\\\"Error: Context could be found but start position out of range\\\")\\n\\t\\tsys.exit()\\n\\telse:\\n\\t print(\\\"Error: File handle does not match file handle stored in client. Wrong file received.\\\")\\n\\t sys.exit() \\t \\n\\t#Then return control to read_service_loop() method so that next iteration of send_read_request \\n\\t#from new start position is called.\\n return\",\n \"def ReadFlowRequestsReadyForProcessing(self,\\n client_id,\\n flow_id,\\n next_needed_request=None):\\n request_dict = self.flow_requests.get((client_id, flow_id), {})\\n response_dict = self.flow_responses.get((client_id, flow_id), {})\\n\\n # Do a pass for completed requests.\\n res = {}\\n for request_id in sorted(request_dict):\\n # Ignore outdated requests.\\n if request_id < next_needed_request:\\n continue\\n # The request we are currently looking for is not in yet, we are done.\\n if request_id != next_needed_request:\\n break\\n request = request_dict[request_id]\\n\\n if not request.needs_processing:\\n break\\n\\n responses = sorted(\\n response_dict.get(request_id, {}).values(),\\n key=lambda response: response.response_id)\\n # Serialize/deserialize responses to better simulate the\\n # real DB behavior (where serialization/deserialization is almost\\n # guaranteed to be done).\\n # TODO(user): change mem-db implementation to do\\n # serialization/deserialization everywhere in a generic way.\\n responses = [\\n r.__class__.FromSerializedBytes(r.SerializeToBytes())\\n for r in responses\\n ]\\n res[request_id] = (request, responses)\\n next_needed_request += 1\\n\\n # Do a pass for incremental requests.\\n for request_id in request_dict:\\n # Ignore outdated and processed requests.\\n if request_id < next_needed_request:\\n continue\\n\\n request = request_dict[request_id]\\n if not request.callback_state:\\n continue\\n\\n responses = response_dict.get(request_id, {}).values()\\n responses = [\\n r for r in responses if r.response_id >= request.next_response_id\\n ]\\n responses = sorted(responses, key=lambda response: response.response_id)\\n\\n # Serialize/deserialize responses to better simulate the\\n # real DB behavior (where serialization/deserialization is almost\\n # guaranteed to be done).\\n # TODO(user): change mem-db implementation to do\\n # serialization/deserialization everywhere in a generic way.\\n responses = [\\n r.__class__.FromSerializedBytes(r.SerializeToBytes())\\n for r in responses\\n ]\\n res[request_id] = (request, responses)\\n\\n return res\",\n \"def parse(self, response: scrapy.http.Response):\\n for job in self.parse_jobs(response):\\n yield job\\n\\n if self.has_next_page(response):\\n yield scrapy.Request(self.next_url,\\n meta={'cookiejar': response.meta['cookiejar'],\\n 'queries': response.meta['queries']},\\n dont_filter=True)\",\n \"async def read(self) -> Union[dictwrapper, str]:\\n while True:\\n await self.connect()\\n try:\\n rx_timeout = self.alive_opts.get('rx_timeout', None)\\n reader = self.reader.readuntil(separator=b'\\\\n')\\n self.bresponse = await asyncio.wait_for(reader,\\n rx_timeout)\\n self.response = polystr(self.bresponse)\\n if self.response.startswith(\\n \\\"{\\\") and self.response.endswith(\\\"}\\\\r\\\\n\\\"):\\n self.unpack(self.response)\\n self._oldstyle_shim()\\n self.valid |= PACKET_SET\\n return self.data\\n return self.response\\n except asyncio.CancelledError:\\n self.close()\\n raise\\n except Exception as exc: # pylint: disable=W0703\\n error = 'timeout' if isinstance(\\n exc, asyncio.TimeoutError) else exc\\n self.logger.warning(\\n f'Failed to get message from GPSD: {error}')\\n self.close()\\n if self.reconnect:\\n # Try again later\\n await asyncio.sleep(self.reconnect)\\n else:\\n raise\",\n \"async def client_read(reader, connection):\\n while connection.state[\\\"connected\\\"]:\\n inp = await reader.readline()\\n\\n if not inp: # This is an EOF. Hard disconnect.\\n connection.state[\\\"connected\\\"] = False\\n return\\n\\n payload = {\\n \\\"uuid\\\": connection.uuid,\\n \\\"addr\\\": connection.addr,\\n \\\"port\\\": connection.port,\\n \\\"msg\\\": inp.strip(),\\n }\\n msg = {\\n \\\"event\\\": \\\"player/input\\\",\\n \\\"secret\\\": WS_SECRET,\\n \\\"payload\\\": payload,\\n }\\n\\n asyncio.create_task(messages_to_game.put(Message(\\\"IO\\\", message=json.dumps(msg, sort_keys=True, indent=4))))\",\n \"def seek_record_read(self, offset, count):\\n self.seek(offset)\\n return self.record_read(count)\",\n \"def read(self):\\n while True:\\n size_bytes = self.connection.read(Frame.SIZE_WIDTH)\\n # Read will return zero bytes when the other side of the connection\\n # closes.\\n if not size_bytes:\\n break\\n\\n message_length = read_number_string(size_bytes, Frame.SIZE_WIDTH)\\n\\n chunk = self.connection.read(message_length - Frame.SIZE_WIDTH)\\n if not chunk:\\n raise ProtocolException(\\n 'Expected %d bytes available, got none' % message_length\\n )\\n\\n if len(chunk) != message_length - Frame.SIZE_WIDTH:\\n raise ProtocolException(\\n 'Expected %d bytes, got %d' %\\n (len(chunk), message_length - Frame.SIZE_WIDTH)\\n )\\n\\n yield Frame.decode(BytesIO(chunk), message_length)\",\n \"def peek(self):\\n if self._buffer:\\n values = self._buffer[0]\\n return Record(self.keys(), tuple(map(hydrated, values)))\\n while not self._buffer and not self._consumed:\\n self.connection.fetch()\\n if self._buffer:\\n values = self._buffer[0]\\n return Record(self.keys(), tuple(map(hydrated, values)))\\n raise ResultError(\\\"End of stream\\\")\",\n \"def _record_iterator(self):\\n\\n # Alias these values so the code won't need to keep performing\\n # attribute lookups on `self` (small optimization)\\n stream = self.stream\\n sync_marker = self._sync_marker\\n writer_schema = self.writer_schema\\n reader_schema = self.reader_schema\\n\\n # Get the block decoder\\n if self.codec == 'deflate':\\n read_block = deflate_read_block\\n elif self.codec == 'snappy':\\n read_block = snappy_read_block\\n else:\\n read_block = null_read_block\\n\\n block_buf = BytesIO()\\n\\n try:\\n while True:\\n block_count = read_long(stream)\\n read_block(stream, block_buf)\\n\\n for i in xrange(block_count):\\n yield read_data(block_buf, writer_schema, reader_schema)\\n\\n skip_sync(stream, sync_marker)\\n\\n except EOFError:\\n pass\\n finally:\\n block_buf.close()\",\n \"def _batcher(self, rows):\\n row_count = 0\\n batch = []\\n batch_count = 1\\n\\n total_rows_modified = 0\\n throttle_count = 0\\n\\n i = 0\\n for row in rows:\\n if row_count > self.batch_size - 1:\\n logger.debug(f\\\"row_count={row_count} batch_size={self.batch_size} and batch={len(batch)}\\\")\\n # Yield the previous batch\\n yield batch\\n\\n # Start the new batch\\n batch = []\\n batch.append(row)\\n row_count = 1\\n\\n batch_count += 1\\n # break # toggle to load one batch only\\n else:\\n row_count += 1\\n batch.append(row)\\n\\n # Put in a sleep timer to throttle how hard we hit the database\\n if self.throttle_time and self.throttle_size and (throttle_count > self.throttle_size - 1):\\n logger.info(f\\\"Sleeping for {self.throttle_time} seconds... row: {i}\\\")\\n time.sleep(int(self.throttle_time))\\n throttle_count = 0\\n elif self.throttle_time and self.throttle_size:\\n throttle_count += 1\\n i += 1\\n\\n yield batch\",\n \"def _read_thread(self):\\r\\n\\r\\n while self._reading and self._serial_object:\\r\\n if self._serial_object.in_waiting:\\r\\n try:\\r\\n (raw_data, parsed_data) = self._ubxreader.read()\\r\\n # if raw_data:\\r\\n # print(raw_data)\\r\\n if parsed_data:\\r\\n print(parsed_data)\\r\\n except (\\r\\n ube.UBXStreamError,\\r\\n ube.UBXMessageError,\\r\\n ube.UBXTypeError,\\r\\n ube.UBXParseError,\\r\\n ) as err:\\r\\n print(f\\\"Something went wrong {err}\\\")\\r\\n continue\",\n \"def handle_read(self):\\n while True:\\n try:\\n content = self.recv(1024)\\n if content:\\n self.rbuf.write(content.decode('utf-8'))\\n if len(content) < 1024:\\n break\\n except Exception as e:\\n print(e)\\n self.handle_rpc()\",\n \"def rows(self):\\r\\n\\r\\n done_sending = False\\r\\n while not done_sending:\\r\\n self._note(\\\"C _not_empty acq?\\\")\\r\\n self.not_empty.acquire()\\r\\n try:\\r\\n self._note(\\\"C _not_empty wait ...\\\")\\r\\n while not self._ready_buffer and not self._closed:\\r\\n self.not_empty.wait()\\r\\n self._note(\\\"C _not_empty got <\\\")\\r\\n\\r\\n if self._ready_buffer:\\r\\n rows = self._ready_buffer\\r\\n self._ready_buffer = None\\r\\n self._note(\\\"C _not_full notify >\\\")\\r\\n self.not_full.notify()\\r\\n\\r\\n for row in rows:\\r\\n yield row\\r\\n else:\\r\\n self._note(\\\"C no buffer\\\")\\r\\n\\r\\n\\r\\n done_sending = self._closed\\r\\n finally:\\r\\n self._note(\\\"_not_empty rel!\\\")\\r\\n self.not_empty.release()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.61128515","0.6106053","0.5749937","0.5664724","0.562037","0.5559969","0.55483514","0.55231017","0.551602","0.551602","0.5493233","0.54856974","0.5481049","0.54711795","0.5399032","0.53882605","0.5361007","0.53610015","0.53456414","0.5320742","0.52846736","0.52784264","0.52624923","0.523893","0.52313817","0.522091","0.52122986","0.5209372","0.5202935","0.51942813","0.5161445","0.5158969","0.5147515","0.51300526","0.512047","0.5114514","0.5108604","0.50955415","0.509395","0.50890446","0.50866634","0.50835186","0.50797105","0.5057359","0.5054093","0.5053784","0.5045445","0.50399315","0.50367343","0.50232273","0.50133246","0.5007321","0.5006931","0.50026333","0.49892813","0.49891055","0.49871665","0.49800912","0.4979904","0.49732113","0.49585092","0.49544442","0.4953597","0.4953597","0.49467152","0.49401277","0.49311298","0.4927195","0.49260834","0.49220905","0.49186027","0.49159348","0.4915852","0.49155968","0.49136773","0.48942482","0.48942104","0.48802304","0.4879903","0.48751438","0.48732927","0.48716807","0.4867147","0.48599708","0.485641","0.4846167","0.48369542","0.4836923","0.48328483","0.48313326","0.48249444","0.482337","0.48179695","0.48133212","0.4810924","0.48056084","0.48049232","0.48047802","0.4802677","0.48019403"],"string":"[\n \"0.61128515\",\n \"0.6106053\",\n \"0.5749937\",\n \"0.5664724\",\n \"0.562037\",\n \"0.5559969\",\n \"0.55483514\",\n \"0.55231017\",\n \"0.551602\",\n \"0.551602\",\n \"0.5493233\",\n \"0.54856974\",\n \"0.5481049\",\n \"0.54711795\",\n \"0.5399032\",\n \"0.53882605\",\n \"0.5361007\",\n \"0.53610015\",\n \"0.53456414\",\n \"0.5320742\",\n \"0.52846736\",\n \"0.52784264\",\n \"0.52624923\",\n \"0.523893\",\n \"0.52313817\",\n \"0.522091\",\n \"0.52122986\",\n \"0.5209372\",\n \"0.5202935\",\n \"0.51942813\",\n \"0.5161445\",\n \"0.5158969\",\n \"0.5147515\",\n \"0.51300526\",\n \"0.512047\",\n \"0.5114514\",\n \"0.5108604\",\n \"0.50955415\",\n \"0.509395\",\n \"0.50890446\",\n \"0.50866634\",\n \"0.50835186\",\n \"0.50797105\",\n \"0.5057359\",\n \"0.5054093\",\n \"0.5053784\",\n \"0.5045445\",\n \"0.50399315\",\n \"0.50367343\",\n \"0.50232273\",\n \"0.50133246\",\n \"0.5007321\",\n \"0.5006931\",\n \"0.50026333\",\n \"0.49892813\",\n \"0.49891055\",\n \"0.49871665\",\n \"0.49800912\",\n \"0.4979904\",\n \"0.49732113\",\n \"0.49585092\",\n \"0.49544442\",\n \"0.4953597\",\n \"0.4953597\",\n \"0.49467152\",\n \"0.49401277\",\n \"0.49311298\",\n \"0.4927195\",\n \"0.49260834\",\n \"0.49220905\",\n \"0.49186027\",\n \"0.49159348\",\n \"0.4915852\",\n \"0.49155968\",\n \"0.49136773\",\n \"0.48942482\",\n \"0.48942104\",\n \"0.48802304\",\n \"0.4879903\",\n \"0.48751438\",\n \"0.48732927\",\n \"0.48716807\",\n \"0.4867147\",\n \"0.48599708\",\n \"0.485641\",\n \"0.4846167\",\n \"0.48369542\",\n \"0.4836923\",\n \"0.48328483\",\n \"0.48313326\",\n \"0.48249444\",\n \"0.482337\",\n \"0.48179695\",\n \"0.48133212\",\n \"0.4810924\",\n \"0.48056084\",\n \"0.48049232\",\n \"0.48047802\",\n \"0.4802677\",\n \"0.48019403\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.80644053"},"document_rank":{"kind":"string","value":"0"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":834,"numItemsPerPage":100,"numTotalItems":95772,"offset":83400,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6IjVHZDBvd0g5MTM2eDZjc1FvbE1zcktNWUZoRVFoUm5PVVVybEpjOUhaUEEifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc4NjA2MDc5MywianRpIjoiMzg1NTUxOWQtZjlmMi00ZTQ4LTgzMDItY2FjZmZiNDBkY2VkIiwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3ODYwNjQzOTMsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.DI7NwsB9WfEA7-itT6WzcptbMcqSwCbY64VuXTZgqCYg7jz1A-14ryhBvFS9cDSABKW9OYJ7PloOPZyoas00DQ","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 |
|---|---|---|---|---|---|---|
If the password is correct, displays lstatistic page. Otherwise, displays appropriate error message. | def login(self, password):
if (password == "loveluay"):
self.lStatisticStackedWidget.setCurrentIndex(1)
else:
moreInfo = "\"" + password + "\" is incorrect. please try again or contact chilleo@gmail.com"
self.message("Incorrect Password", "The password you entered is ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def authenticate():\n return \"Please log in... Log in page\"",
"def evaluate_password_health(users, print_password=False):\n hasUpperCase = \"[A-Z]\"\n hasLowerCase = \"[a-z]\"\n hasNumbers = \"\\d\"\n hasNonalphas = \"\\W\"\n results = []\n for username, password in users.items():\n ... | [
"0.5747581",
"0.5714671",
"0.56969535",
"0.5679485",
"0.5674646",
"0.56705225",
"0.5624725",
"0.5614046",
"0.56011856",
"0.55548626",
"0.5546437",
"0.5505691",
"0.54869825",
"0.54830533",
"0.54677933",
"0.5462135",
"0.54592884",
"0.5451447",
"0.5445026",
"0.5444386",
"0.54097... | 0.66152185 | 0 |
Allows user to use enter/return key to submit password on password page. | def keyPressEvent(self, e):
super(PhyloVisApp, self).keyPressEvent(e)
if e.key() in [QtCore.Qt.Key_Enter, QtCore.Qt.Key_Return]:
if (self.stackedWidget.currentIndex() == 5):
if (self.lStatisticStackedWidget.currentIndex() == 0):
self.login(self.lStatPasswo... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def enter_password(self):",
"def enter_password(self):\n self.password.clear()\n self.password.click()\n self.password.send_keys(TestData.PASSWORD)\n sleep(TestData.DELAY)\n return self.password",
"def ChangePassword():\n if self.ChangePassword():\n ... | [
"0.7701184",
"0.7270404",
"0.65003645",
"0.642928",
"0.6395058",
"0.63937986",
"0.6267385",
"0.6249939",
"0.62455666",
"0.6233503",
"0.61884034",
"0.61816454",
"0.61720026",
"0.61567837",
"0.61168325",
"0.608349",
"0.60649306",
"0.6063698",
"0.6044538",
"0.6042732",
"0.603957... | 0.57734126 | 38 |
returns true if all tests pass otherwise false | def raxmlInputErrorHandling(self):
try:
# input alignment for raxml
self.raxmlOperations.inputFilename = self.checkEntryPopulated(self.inputFileEntry, errorTitle='Missing Alignment', errorMessage='Please select an alignment.')
self.raxmlOperations.windowSize = self.checkEntry... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run_all_tests():\n successes = 0\n testsrun = 0\n testsdir = tests_dirpath()\n for test in os.listdir(testsdir):\n path = os.path.join(testsdir, test)\n if os.path.isdir(path):\n testsrun += 1\n if run_test(path):\n successes += 1\n print(\"--- ... | [
"0.7418144",
"0.7351616",
"0.7259784",
"0.7037549",
"0.703326",
"0.68182933",
"0.6786439",
"0.6739737",
"0.6676236",
"0.6638024",
"0.6632423",
"0.6610456",
"0.66022855",
"0.6591967",
"0.6577456",
"0.6565592",
"0.6536287",
"0.6530585",
"0.64995426",
"0.6455215",
"0.64511365",
... | 0.0 | -1 |
creates and displays and window displaying the message | def message(self, title, description, extraInfo, type='Err'):
# create object
errMessage = QtGui.QMessageBox()
# set text
errMessage.setText(title)
errMessage.setInformativeText(description)
errMessage.setDetailedText(extraInfo)
# default pixmap for error
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def display_message(window, msg):\n v = create_output_panel(window, '')\n _append(v, msg)",
"def display_message():",
"def showMessage(self):",
"def modeMsgBox(self, messageText):\n self.createMessage(messageText)",
"def createMessageFrame (self,message):\n \n label = Tk.Label(self.f... | [
"0.7777422",
"0.73143095",
"0.7175642",
"0.6992637",
"0.6992474",
"0.69156057",
"0.68353176",
"0.6790964",
"0.678096",
"0.6774758",
"0.6747331",
"0.6733183",
"0.6716109",
"0.67137617",
"0.6659027",
"0.66531986",
"0.664738",
"0.66387904",
"0.66269374",
"0.66074616",
"0.6600948... | 0.0 | -1 |
creates and displays and window displaying the message | def question(self, title, description, type='Question'):
# create object
qMessage = QtGui.QMessageBox()
# set text
qMessage.setText(title)
qMessage.setInformativeText(description)
# default pixmap for error
pixmap = QtGui.QPixmap('imgs/warning.png')
# se... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def display_message(window, msg):\n v = create_output_panel(window, '')\n _append(v, msg)",
"def display_message():",
"def showMessage(self):",
"def modeMsgBox(self, messageText):\n self.createMessage(messageText)",
"def createMessageFrame (self,message):\n \n label = Tk.Label(self.f... | [
"0.7777422",
"0.73143095",
"0.7175642",
"0.6992637",
"0.6992474",
"0.69156057",
"0.68353176",
"0.6790964",
"0.678096",
"0.6774758",
"0.6747331",
"0.6733183",
"0.6716109",
"0.67137617",
"0.6659027",
"0.66531986",
"0.664738",
"0.66387904",
"0.66269374",
"0.66074616",
"0.6600948... | 0.0 | -1 |
checks if given entry is empty or not. (i) if entry is populated returns text (ii) otherwise raises value error | def checkEntryPopulated(self, entry, errorTitle='Field Not Populated', errorMessage='Please populate field.', errorDescription=None):
# if user does not provide an error description generate one automatically
if not errorDescription:
errorDescription = 'relevant entry name: ' + str(entry.ob... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _entry_field_values_are_not_empty(entry: _LexiconEntry) -> None:\n empty_fields = [f for f in _REQUIRED_FIELDS if not entry[f]]\n\n if empty_fields:\n field_str = \", \".join(sorted(empty_fields))\n raise InvalidLexiconEntryError(\n f\"Entry fields have empty values: '{field_str}'\")",
"def ge... | [
"0.6981402",
"0.6756794",
"0.6678831",
"0.66734993",
"0.6366761",
"0.6356786",
"0.63151586",
"0.631306",
"0.62579745",
"0.6219134",
"0.6212304",
"0.6151103",
"0.61417395",
"0.61398095",
"0.6114239",
"0.6044269",
"0.60362357",
"0.6025646",
"0.602314",
"0.60065186",
"0.59784955... | 0.7203207 | 0 |
checks if value of given entry is in range. i. if entry is in given range return it ii. otherwise raises value error | def checkEntryInRange(self, entry, min=(-1.0 * float('inf')), max=float('inf'), inclusive=True, errorTitle='Entry Out Of Range', errorMessage='', errorDescription=None):
# if user does not provide an error description generate one automatically
if not errorDescription:
errorDescription = 'r... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_range(num):\n for i in ranges.keys():\n if num in ranges[i]:\n return i",
"def isInRange(self,section,option,testval):\n \"\"\" us to test if 15 is in range defined as e.g. \"1-10,12,16-19\" \"\"\"\n value=ConfigParser.SafeConfigParser.get(self,section,option)\n ... | [
"0.7152191",
"0.7056733",
"0.6937104",
"0.6925974",
"0.686642",
"0.6862959",
"0.6817519",
"0.66738325",
"0.66446173",
"0.66358376",
"0.6624139",
"0.66183287",
"0.65863585",
"0.65854746",
"0.65593094",
"0.6500753",
"0.6478799",
"0.6467218",
"0.644324",
"0.64166504",
"0.6406122... | 0.7250366 | 0 |
returns the number of checkboxes that are checked | def getNumberChecked(self):
return (self.checkboxScatterPlot.checkState() + self.checkboxDonutPlot.checkState() + self.checkboxAllTrees.checkState()) / 2 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_num_of_choices(self) -> int:\n return len(self._choices)",
"def GetCheckBoxSize(*args, **kwargs):\n return _gdi_.RendererNative_GetCheckBoxSize(*args, **kwargs)",
"def get_count_of_controls(self, recurse: bool) -> int:\n return len(list(self.get_all_controls(recurse)))",
"def cou... | [
"0.63210493",
"0.6222181",
"0.6178917",
"0.61608493",
"0.61397576",
"0.6122742",
"0.6122495",
"0.6058574",
"0.6047955",
"0.59916806",
"0.59904414",
"0.59828997",
"0.594535",
"0.59252757",
"0.59179276",
"0.59048724",
"0.59024745",
"0.5901195",
"0.5893027",
"0.5889103",
"0.5889... | 0.726542 | 0 |
toggles whether or not guiElement is enabled | def toggleEnabled(self, guiElement):
enabled = guiElement.isEnabled()
guiElement.setEnabled(not enabled) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _enable_disable_gui(self, state):\r\n self.mainWidget.standbyPushButton.setDisabled(state)\r\n self.mainWidget.eventComboBox.setDisabled(state)\r\n self.mainWidget.roomComboBox.setDisabled(state)\r\n self.mainWidget.dateComboBox.setDisabled(state)\r\n self.mainWidget.talkComb... | [
"0.69816",
"0.69582343",
"0.6883505",
"0.68738556",
"0.68276453",
"0.6776707",
"0.67430043",
"0.67430043",
"0.6729134",
"0.6666026",
"0.6665531",
"0.6665531",
"0.662512",
"0.6596297",
"0.6528794",
"0.65138054",
"0.65128595",
"0.64982307",
"0.64661014",
"0.6447577",
"0.6399733... | 0.8579611 | 0 |
i. open a dialog to get in which user enters a file name to save ii. sets the text of given text entry to match file user selected | def saveFileAs(self, textEntry):
textEntry.setText(QtGui.QFileDialog.getSaveFileName(self, 'Export')) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getFileName(self, textEntry):\n textEntry.setText(QtGui.QFileDialog.getOpenFileName())\n textEntry.emit(QtCore.SIGNAL('FILE_SELECTED'))",
"def browse( self ):\n Tk.Tk().withdraw()\n filename = askopenfilename( initialdir = self.initialdir,\n ... | [
"0.7600504",
"0.7478386",
"0.73535603",
"0.7231459",
"0.71452034",
"0.7135394",
"0.7072531",
"0.6995552",
"0.6995552",
"0.6938619",
"0.6937704",
"0.6916023",
"0.68937707",
"0.68868494",
"0.688312",
"0.68801373",
"0.6855539",
"0.6847503",
"0.68176925",
"0.6816151",
"0.68119866... | 0.7488586 | 1 |
i. open a dialog to get in which user selects a file ii. sets the text of given text entry to match file user selected | def getFileName(self, textEntry):
textEntry.setText(QtGui.QFileDialog.getOpenFileName())
textEntry.emit(QtCore.SIGNAL('FILE_SELECTED')) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def browse_files_in(self,*args):\n path_to_data = tkFileDialog.askopenfilename()\n #show chosen value in textframe\n self.docstring.delete(0,tk.END)\n self.docstring.insert(0,path_to_data)\n #use chosen value as self.data_file\n self.data_file.set(path_to_data)",
"def br... | [
"0.75972843",
"0.7592121",
"0.74247646",
"0.73100656",
"0.72838455",
"0.7278615",
"0.72531843",
"0.72531843",
"0.7165265",
"0.71190333",
"0.71152383",
"0.7110643",
"0.70934874",
"0.7059284",
"0.7045121",
"0.68826526",
"0.6851092",
"0.6845944",
"0.6842857",
"0.6825622",
"0.681... | 0.7607524 | 0 |
i. open a dialog in which user selects a directory ii. sets the text of given text entry to match the directory the user selected | def openDirectory(self, textEntry):
textEntry.setText(QtGui.QFileDialog.getExistingDirectory())
textEntry.emit(QtCore.SIGNAL("DIRECTORY_SELECTED")) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def askForDir(self):\n self.dir = tkFileDialog.askdirectory(**self.dir_opt)\n self.textView.insert('end', 'Open %s\\n' % (self.dir))",
"def browse( self ):\n Tk.Tk().withdraw()\n dirname = askdirectory()\n\n self.set_text( dirname )\n #rint( f\"get_text = {self.get_tex... | [
"0.79557335",
"0.7627418",
"0.7475416",
"0.7445645",
"0.73689944",
"0.7321648",
"0.72456354",
"0.7223277",
"0.7100498",
"0.7093033",
"0.70770675",
"0.70672625",
"0.70645624",
"0.70553327",
"0.7037435",
"0.69944274",
"0.69918424",
"0.69603044",
"0.68496865",
"0.6845472",
"0.68... | 0.82809854 | 0 |
Number pattern '5' using Python for loop | def for_five():
for row in range(7):
for col in range(5):
if col==0 and row<6 and row!=4 or col>0 and col<3 and row%3==0 or col==3 and (row==0 or row>3) and row<6:
print('*', end = ' ')
else:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def numbers():\n for number in range(1, 76):\n yield number",
"def main():\n number = int(input())\n count = 0\n for i in range(1, number+1):\n if i%3 == 0 or i%5 == 0:\n count += i\n print(count)",
"def compute_pattern(n):\n for x in range(1,n):\n for y in ran... | [
"0.65481997",
"0.6515888",
"0.65046096",
"0.6434914",
"0.62507683",
"0.622045",
"0.61105067",
"0.61098456",
"0.60892016",
"0.6046951",
"0.6010077",
"0.5994545",
"0.5919658",
"0.5891623",
"0.58706415",
"0.58510786",
"0.58489823",
"0.58398044",
"0.5836585",
"0.58269024",
"0.582... | 0.58841646 | 14 |
Number pattern '5' using Python while loop | def while_five():
row = 0
while row<7:
col = 0
while col<7:
if col==0 and row<6 and row!=4 or col>0 and col<3 and row%3==0 or col==3 and (row==0 or row>3) and row<6:
print('*', end = ' ')
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def main():\n number = int(input())\n count = 0\n for i in range(1, number+1):\n if i%3 == 0 or i%5 == 0:\n count += i\n print(count)",
"def count_to10():\n numberx = 0\n while numberx < 10:\n numberx += 1\n print(numberx)",
"def renumber():\n\n counter = it... | [
"0.655466",
"0.6519697",
"0.6449413",
"0.63978386",
"0.6332752",
"0.62820756",
"0.62544936",
"0.6229543",
"0.6160936",
"0.6065578",
"0.60082173",
"0.5853708",
"0.58360726",
"0.5816996",
"0.57952696",
"0.5790483",
"0.57858884",
"0.57809883",
"0.5776131",
"0.57704246",
"0.57674... | 0.6221141 | 8 |
r"""SqueezeNet 1.1 model from the `official SqueezeNet repo | def squeezenet1_1(pretrained=False, strides=(2, 2, 2, 2, 2), inter_features=True, progress=True, **kwargs):
return _squeezenet('1_1', pretrained, strides, inter_features, progress, **kwargs) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_model(self):\n if self.model_type=='densenet_121':\n model = self.make_densenet_121(self.weights)\n\n\n return model",
"def semnasnet_140(pretrained=False, num_classes=1000, in_chans=3, **kwargs):\n default_cfg = default_cfgs['semnasnet_140']\n model = _gen_mnasnet_a1(1.4,... | [
"0.62322503",
"0.6004179",
"0.58528733",
"0.58489287",
"0.5771156",
"0.5702672",
"0.5666888",
"0.5656912",
"0.5635127",
"0.5634268",
"0.5623376",
"0.56212634",
"0.5604558",
"0.5600158",
"0.5548424",
"0.55420846",
"0.55333906",
"0.55195224",
"0.55142236",
"0.55047935",
"0.5491... | 0.0 | -1 |
This method is used for the keystroke grading in the application. The data in retrieved from the database. This data is then used in the grading process. The user selects a key and that key then performs a task. There is a queue which loads the key selections which is used to add the marks and comments to the students ... | def startGrading(event):
window.unbind("<s>", bind_id)
cur.execute(
"SELECT comment1, comment2, comment3, comment4, comment5 FROM cannedComments WHERE user_id =%s and moduleCode = %s and assignmentNo = %s",
(userID, assignmentModuleCode, assignmentNo))
fetchedComments = c... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def submitAssignment(self, _event=None):\n assignmentFilePath = AccessingFiles.getFilepath()\n cur.execute(\n \"SELECT * FROM assignments WHERE user_id =%s and student_id = %s and filename = %s and moduleCode = %s and assignmentNo = %s\",\n (userID, selection, it... | [
"0.61789244",
"0.5682106",
"0.55871874",
"0.5540368",
"0.5355401",
"0.5321885",
"0.5302319",
"0.51488197",
"0.51355994",
"0.51158065",
"0.5112609",
"0.5047955",
"0.50102323",
"0.49364117",
"0.4906312",
"0.48952746",
"0.4892012",
"0.4890522",
"0.48756707",
"0.48665848",
"0.484... | 0.6797914 | 0 |
This method is used to highlight text in the student assignment. Firstly, the PDF is saved which does not include the highlighted text. The pdf is then opened and the text from the HighlightedText.txt file is copied and the the fitz module in python locates the text in the pdf and then adds a yellow background to the t... | def highlightingTextInFile():
savingFilePDF = re.sub('\t', '', item_text[0] + ".pdf")
doc = fitz.open(gradedFilesFolder + "\\" + savingFilePDF)
page = doc[0]
with open(newTextFile, "r") as file2:
time.sleep(0.5)
text1 = file2.read()
# Search for the text... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def highlight(self):\n\n if self.selected_text_file is None:\n return\n if self.selected_text_file[FULLTEXT] is None:\n return\n format_ = QtGui.QTextCharFormat()\n cursor = self.ui.textBrowser.textCursor()\n for item in self.case_text:\n try:\n ... | [
"0.65989536",
"0.6505804",
"0.6054621",
"0.60322046",
"0.60036427",
"0.5864477",
"0.57321054",
"0.5600204",
"0.55730855",
"0.54676825",
"0.54027605",
"0.53352803",
"0.5305688",
"0.528708",
"0.51586694",
"0.51586694",
"0.51586694",
"0.5149887",
"0.5149887",
"0.51426286",
"0.51... | 0.83719736 | 0 |
If there us a mouse click on the text box or a new line is entered in the text box it will load the line numbers. | def _on_change(self, event):
self.codeLineNumbers.redraw() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def line_counter(self, event=None):\n try:\n text_area = self.get_current()\n self.canvas.delete('all')\n i = text_area.index(\"@0,0\")\n while True:\n dline = text_area.dlineinfo(i)\n if dline is None: break\n y = dlin... | [
"0.68388116",
"0.6638847",
"0.63189745",
"0.62623847",
"0.622727",
"0.613175",
"0.5789219",
"0.5706336",
"0.5689253",
"0.56639355",
"0.5612356",
"0.56078994",
"0.55938995",
"0.55646855",
"0.55344325",
"0.5507554",
"0.5504534",
"0.5494389",
"0.5490965",
"0.54685616",
"0.546091... | 0.6135949 | 5 |
This method copies the code in the assignment grading text box and creates a pdf file which will be used in order to highlight text | def savePDFFile(self):
s = self.text.get("1.0", tk.END)
f = open(file, "w", encoding='utf-8')
f.write(s)
f.close()
# Create a file for each student with their graded files
pdf = FPDF()
pdf.add_page()
pdf.set_font("Arial", s... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def highlightingTextInFile():\n savingFilePDF = re.sub('\\t', '', item_text[0] + \".pdf\")\n doc = fitz.open(gradedFilesFolder + \"\\\\\" + savingFilePDF)\n page = doc[0]\n\n with open(newTextFile, \"r\") as file2:\n time.sleep(0.5)\n text1 = file2.read()\n\n ... | [
"0.6238947",
"0.58214",
"0.5817242",
"0.5786519",
"0.57760084",
"0.57760084",
"0.57760084",
"0.57224184",
"0.56881684",
"0.56578857",
"0.56418467",
"0.5640361",
"0.5613223",
"0.56121486",
"0.5571742",
"0.5571385",
"0.555584",
"0.5549019",
"0.553231",
"0.55292517",
"0.54780155... | 0.70820236 | 0 |
This method is used to submit the students assignment grade to the database. If a grade for the student already exists in the database and the user selects that assignment for grading, they will be prompted with an message box asking if they want to regrade the assignment. If they select yes then they can regrade the a... | def submitAssignment(self, _event=None):
assignmentFilePath = AccessingFiles.getFilepath()
cur.execute(
"SELECT * FROM assignments WHERE user_id =%s and student_id = %s and filename = %s and moduleCode = %s and assignmentNo = %s",
(userID, selection, item_text[0],... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _save_grade(self):\r\n student = self._student('POST', key='grader_id')\r\n if student is None:\r\n self._error_response()\r\n\r\n else:\r\n # Update the number of essays the student has graded\r\n student.grade_peer_essay()\r\n return self._succ... | [
"0.6543872",
"0.63892865",
"0.633533",
"0.6332422",
"0.63317186",
"0.63130635",
"0.62545836",
"0.6071485",
"0.6068624",
"0.6017599",
"0.59676605",
"0.59659773",
"0.59341687",
"0.5874737",
"0.57972556",
"0.5783686",
"0.5766519",
"0.5579791",
"0.55714285",
"0.556687",
"0.555967... | 0.8227006 | 0 |
Adds the highlighted text in the assignment grading window to the HighlightedText.txt file | def highlightCode(self, _event=None):
count = 0
if self.text.tag_ranges('sel'):
self.text.tag_add('color' + str(count), tk.SEL_FIRST, tk.SEL_LAST)
self.text.tag_configure('color' + str(count), foreground='black', background='yellow')
count += 1
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def highlightingTextInFile():\n savingFilePDF = re.sub('\\t', '', item_text[0] + \".pdf\")\n doc = fitz.open(gradedFilesFolder + \"\\\\\" + savingFilePDF)\n page = doc[0]\n\n with open(newTextFile, \"r\") as file2:\n time.sleep(0.5)\n text1 = file2.read()\n\n ... | [
"0.7374293",
"0.6817336",
"0.64692134",
"0.6182169",
"0.6022382",
"0.59503573",
"0.58533984",
"0.5805103",
"0.5790315",
"0.57207805",
"0.56802523",
"0.5655003",
"0.5655003",
"0.56214184",
"0.5620613",
"0.55651665",
"0.5480074",
"0.547468",
"0.5472067",
"0.5469422",
"0.5457528... | 0.6832632 | 1 |
This method adds the marks and comments generated from the keystrokes into the students assignment | def addAssignmentComments(self, _event=None):
self.text.insert(tk.END, "\n")
self.text.insert(tk.INSERT, assignmentCommentsBox.get("1.0", "end-1c")) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def startGrading(event):\n window.unbind(\"<s>\", bind_id)\n cur.execute(\n \"SELECT comment1, comment2, comment3, comment4, comment5 FROM cannedComments WHERE user_id =%s and moduleCode = %s and assignmentNo = %s\",\n (userID, assignmentModuleCode, assignmentNo))\n fetch... | [
"0.55127954",
"0.55074334",
"0.53589535",
"0.53228885",
"0.5216916",
"0.52080244",
"0.5189307",
"0.5166053",
"0.5159105",
"0.515391",
"0.51526713",
"0.50940263",
"0.5013002",
"0.5001225",
"0.49976295",
"0.49926817",
"0.4991195",
"0.4941163",
"0.49386635",
"0.49113652",
"0.490... | 0.60720026 | 0 |
If window is closed mid grading a message box display | def on_closingWindow(self):
if messagebox.askokcancel("Quit",
"Do you want to quit grading the assignment?\n File will be saved",
parent=window):
self.submitAssignment() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __window_close(self):\n pass",
"def message_box(self):\n root = tk.Toplevel(self.top)\n root.attributes('-topmost', True)\n root.geometry(\"+650+100\")\n root.withdraw()\n messagebox.showinfo('Oh oh', 'Wrong message. Try again!')\n try:\n root.destr... | [
"0.73147106",
"0.7060031",
"0.69775015",
"0.6929832",
"0.6904085",
"0.687413",
"0.68636405",
"0.68604046",
"0.6857272",
"0.6853422",
"0.6843845",
"0.68172044",
"0.6751769",
"0.6727031",
"0.6711077",
"0.669814",
"0.669641",
"0.66409177",
"0.6637147",
"0.66262764",
"0.6613843",... | 0.74814725 | 0 |
If window is closed mid grading a message box display | def back(self, _event=None):
self.on_closingWindow() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def on_closingWindow(self):\n if messagebox.askokcancel(\"Quit\",\n \"Do you want to quit grading the assignment?\\n File will be saved\",\n parent=window):\n self.submitAssignment()",
"def __window_close(self):\n... | [
"0.7481806",
"0.73158485",
"0.705738",
"0.6976617",
"0.69277674",
"0.6903606",
"0.68744737",
"0.6865453",
"0.68603915",
"0.6857267",
"0.6853163",
"0.6844235",
"0.68156856",
"0.6752026",
"0.672771",
"0.67103666",
"0.66975254",
"0.6696275",
"0.6640213",
"0.66379935",
"0.6627065... | 0.0 | -1 |
write_ROMS_grid(grd, filename) Write ROMS_CGrid class on a NetCDF file. | def write_ROMS_grid(grd, visc_factor, diff_factor, filename='roms_grd.nc'):
Mm, Lm = grd.hgrid.x_rho.shape
# Write ROMS grid to file
nc = netCDF.Dataset(filename, 'w', format='NETCDF4')
nc.Description = 'ROMS grid'
nc.Author = 'Trond Kristiansen'
nc.Created = datetime.now().isoformat()
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def to_cdo_grid(self, outfile):",
"def save_mrc(grid_object, path):\n\n return MRC_Grid_Write(grid_object, path)",
"def write_shapefile(self, filename='grid.shp', epsg=None, prj=None):\n from ..export.shapefile_utils import write_grid_shapefile2\n if epsg is None and prj is None:\n ... | [
"0.65927523",
"0.64591205",
"0.64300597",
"0.63076574",
"0.62848854",
"0.62485576",
"0.6131454",
"0.6101492",
"0.605749",
"0.6021716",
"0.5946283",
"0.5857305",
"0.576592",
"0.57481474",
"0.5727841",
"0.572196",
"0.57188284",
"0.56795627",
"0.56728095",
"0.56445134",
"0.56236... | 0.7655568 | 0 |
Test Numeric array to VTK array conversion and viceversa. | def test_array2vtk(self):
# Put all the test arrays here.
t_z = []
# Test the different types of arrays.
t_z.append(numpy.array([-128, 0, 127], numpy.int8))
# FIXME: character arrays are a problem since there is no
# unique mapping to a VTK data type and back.
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_arr2cell_array(self):\n # Test list of lists.\n a = [[0], [1, 2], [3, 4, 5], [6, 7, 8, 9]]\n cells = array_handler.array2vtkCellArray(a)\n z = numpy.array([1, 0, 2, 1,2, 3, 3,4,5, 4, 6,7,8,9])\n arr = array_handler.vtk2array(cells.GetData())\n self.assertEqual(num... | [
"0.694688",
"0.663548",
"0.64812386",
"0.6476549",
"0.635363",
"0.631881",
"0.617769",
"0.6159509",
"0.614058",
"0.60678095",
"0.6061788",
"0.5929297",
"0.5926725",
"0.59005785",
"0.5837574",
"0.5725261",
"0.57149047",
"0.5694535",
"0.56775194",
"0.5614327",
"0.5610911",
"0... | 0.799915 | 0 |
Test Numeric array to vtkCellArray conversion. | def test_arr2cell_array(self):
# Test list of lists.
a = [[0], [1, 2], [3, 4, 5], [6, 7, 8, 9]]
cells = array_handler.array2vtkCellArray(a)
z = numpy.array([1, 0, 2, 1,2, 3, 3,4,5, 4, 6,7,8,9])
arr = array_handler.vtk2array(cells.GetData())
self.assertEqual(numpy.sum(arr ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_array2vtk(self):\n # Put all the test arrays here.\n t_z = [] \n\n # Test the different types of arrays.\n t_z.append(numpy.array([-128, 0, 127], numpy.int8))\n\n # FIXME: character arrays are a problem since there is no\n # unique mapping to a VTK data typ... | [
"0.62945616",
"0.5984892",
"0.59832245",
"0.5936498",
"0.5862382",
"0.583198",
"0.5802998",
"0.5767916",
"0.5704477",
"0.5664202",
"0.56276673",
"0.55963475",
"0.5492892",
"0.54758745",
"0.54539454",
"0.54508984",
"0.54035276",
"0.53702885",
"0.53439134",
"0.53292114",
"0.531... | 0.7681079 | 0 |
Test Numeric array to vtkPoints conversion. | def test_arr2vtkPoints(self):
a = [[0.0, 0.0, 0.0], [1.0, 1.0, 1.0]]
p = array_handler.array2vtkPoints(a)
self.assertEqual(p.GetPoint(0), (0.0, 0.0, 0.0))
self.assertEqual(p.GetPoint(1), (1.0, 1.0, 1.0))
p = vtk.vtkPoints()
ident = id(p)
p = array_handler.array2vt... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_array2vtk(self):\n # Put all the test arrays here.\n t_z = [] \n\n # Test the different types of arrays.\n t_z.append(numpy.array([-128, 0, 127], numpy.int8))\n\n # FIXME: character arrays are a problem since there is no\n # unique mapping to a VTK data typ... | [
"0.6521495",
"0.64818186",
"0.5970698",
"0.595983",
"0.5753924",
"0.5726312",
"0.5666946",
"0.5626826",
"0.5600705",
"0.55829287",
"0.55201954",
"0.550375",
"0.5496389",
"0.5471823",
"0.54700726",
"0.54335093",
"0.53982234",
"0.53903526",
"0.53780526",
"0.5361564",
"0.5358959... | 0.7969096 | 0 |
Test array to vtkIdList conversion. | def test_arr2vtkIdList(self):
a = [1, 2, 3, 4, 5]
p = array_handler.array2vtkIdList(a)
for i, j in enumerate(a):
self.assertEqual(p.GetId(i), j)
p = vtk.vtkIdList()
ident = id(p)
p = array_handler.array2vtkIdList(numpy.array(a), p)
for i, j... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_id_array(self):\n arr = vtk.vtkIdTypeArray()\n arr.SetNumberOfTuples(10)\n for i in range(10):\n arr.SetValue(i, i)\n\n np = array_handler.vtk2array(arr)\n self.assertEqual(numpy.all(np == range(10)), True)",
"def mkVtkIdList(self, it):\n vil = vtk.vt... | [
"0.7677187",
"0.647352",
"0.59208304",
"0.5762081",
"0.57502407",
"0.5743467",
"0.5742972",
"0.57179093",
"0.56799865",
"0.56706077",
"0.5654017",
"0.5637075",
"0.5625911",
"0.55883914",
"0.55837685",
"0.55628437",
"0.5555486",
"0.55226254",
"0.5453243",
"0.54327404",
"0.5366... | 0.8411601 | 0 |
Test multiple signature cases that have array arguments. | def test_get_correct_sig(self):
obj = tvtk_base.TVTKBase(vtk.vtkIdTypeArray)
sigs = [ None,
[['vtkDataArray']],
[['int', 'vtkIdList']],
[['int', 'vtkPoints'], ['int', 'int']],
[['int', 'vtkPoints'], ['int']],
[['int'], ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_handler_array(self):\n\n @intent_handler\n def decorated_test(arr: List[str]):\n return arr\n\n r = create_request(\n \"TEST_CONTEXT\",\n arr=[\n \"31-12-2001\",\n \"31-12-1001\",\n ],\n )\n result... | [
"0.6318285",
"0.6172812",
"0.6162404",
"0.610861",
"0.6058716",
"0.605753",
"0.6045802",
"0.60229707",
"0.59978545",
"0.59901863",
"0.5983605",
"0.59537596",
"0.59348905",
"0.5915856",
"0.5899093",
"0.5764791",
"0.57222784",
"0.57166",
"0.568288",
"0.56676954",
"0.5647761",
... | 0.65782744 | 0 |
Test if dereferencing array args works correctly. | def test_deref_array(self):
sigs = [[['vtkDataArray']],
[['vtkFloatArray']],
[['vtkCellArray']],
[['vtkPoints']],
[['int', 'vtkIdList']],
[['int', ('float', 'float'), 'vtkDataArray']],
[['Prop', 'int', 'vtkDataArray'... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_ptr_or_array(*args):\n return _ida_hexrays.is_ptr_or_array(*args)",
"def lookup_array(self, *args, **kwargs): # real signature unknown\n pass",
"def lookup_array(self, *args, **kwargs): # real signature unknown\n pass",
"def _check_args(self, args_):\n\n pass",
"def test_vargs(... | [
"0.6318977",
"0.60770243",
"0.60770243",
"0.59743184",
"0.5915152",
"0.5903806",
"0.58661574",
"0.5851228",
"0.58363134",
"0.57874745",
"0.57700723",
"0.55881095",
"0.5572754",
"0.5562253",
"0.55080026",
"0.5481902",
"0.54778504",
"0.5451302",
"0.54414076",
"0.5424659",
"0.54... | 0.6638242 | 0 |
Does to_array return an existing array instead of a new copy. | def test_reference_to_array(self):
arr = numpy.arange(0.0, 10.0, 0.1)
arr = numpy.reshape(arr, (25, 4))
vtk_arr = array_handler.array2vtk(arr)
arr1 = array_handler.vtk2array(vtk_arr)
# Now make sure these are using the same memory.
arr[0][0] = 100.0
self.assertEq... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def to_array(self) -> np.ndarray:\n return self.A",
"def to_numpy(self) -> np.ndarray:\n return np.stack([x.to_numpy() for x in self])",
"def asarray(self):\n from numpy import asarray\n return asarray(self)",
"def to_numpy(self) -> np.ndarray:\n log_advice(\n \"... | [
"0.7306779",
"0.72532874",
"0.7197511",
"0.7167543",
"0.7166795",
"0.7116745",
"0.7113778",
"0.70606464",
"0.6982097",
"0.68873906",
"0.68387365",
"0.67512727",
"0.6690724",
"0.669039",
"0.6492112",
"0.64499694",
"0.63818926",
"0.63742393",
"0.6354882",
"0.6346695",
"0.632135... | 0.0 | -1 |
Test the ArrayCache class. | def test_array_cache(self):
cache = array_handler.ArrayCache()
# Test if len works.
self.assertEqual(len(cache), 0)
arr = numpy.zeros(100, float)
varr = vtk.vtkFloatArray()
# test contains
self.assertEqual(varr not in cache, True)
cache.add(varr, arr)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_untimed(self):\n cache = TimedCache()\n for i in range(500):\n cache[i] = i\n for i in range(500):\n assert i in cache\n assert cache[i] == i",
"def test__cache(self):\n # Access to a protected member _cache of a client class\n # pylint... | [
"0.68710124",
"0.67767155",
"0.6772086",
"0.65992814",
"0.65391827",
"0.6536076",
"0.6400671",
"0.6391623",
"0.63568",
"0.6338708",
"0.62691534",
"0.62381554",
"0.6217318",
"0.61316127",
"0.60631394",
"0.6057452",
"0.6055985",
"0.6038328",
"0.60332614",
"0.5990136",
"0.598484... | 0.8419209 | 0 |
Test if a vtkIdTypeArray is converted correctly. | def test_id_array(self):
arr = vtk.vtkIdTypeArray()
arr.SetNumberOfTuples(10)
for i in range(10):
arr.SetValue(i, i)
np = array_handler.vtk2array(arr)
self.assertEqual(numpy.all(np == range(10)), True) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_arr2vtkIdList(self):\n a = [1, 2, 3, 4, 5]\n p = array_handler.array2vtkIdList(a)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n p = vtk.vtkIdList()\n ident = id(p)\n p = array_handler.array2vtkIdList(numpy.array(a), p)\n ... | [
"0.7641578",
"0.6041027",
"0.59939146",
"0.5906016",
"0.57242924",
"0.5714401",
"0.57085663",
"0.56843495",
"0.55889595",
"0.5541299",
"0.5535113",
"0.55233514",
"0.5509437",
"0.5506507",
"0.5470009",
"0.5457422",
"0.5454575",
"0.54334915",
"0.5413795",
"0.54070187",
"0.54061... | 0.8161448 | 0 |
Translates litteral expression to float. | def letters_to_float(let):
expr = str(let[1] # integer part
+ '.' + let[2:] # decimals
+ 'e' + _exponents[let[0].lower()] # exponent
)
try:
return (1 - 2*let[0].isupper())*float(expr)
except ValueError: return 0 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def value(self):\n float_str = first_token(self._node).spelling\n\n # Remove any C-specific suffix (f, F, l, L) so we can use Python's\n # float constructor to parse the string.\n float_str = re.sub(r'^(.*)[fFlL]$', r'\\1', float_str)\n\n return float(float_str)",
"def str2floa... | [
"0.67611974",
"0.67190254",
"0.6670269",
"0.6612682",
"0.65358835",
"0.64978874",
"0.64675283",
"0.64648813",
"0.6441169",
"0.6389028",
"0.63695776",
"0.63611645",
"0.6360769",
"0.6319111",
"0.63145465",
"0.63025874",
"0.6297094",
"0.6258761",
"0.62507975",
"0.6248428",
"0.62... | 0.64909846 | 6 |
Translates float to litteral expression. | def float_to_letters(flo):
try:
expo_int = int(floor(log10(abs(flo)))) # integer exponent
expo_let = list(_exponents.keys())[list(_exponents.values()).index(
'%i' % expo_int # corresponding letter exponent
)]
except TypeError: return '' # return empty string if input type is not recognisable... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def float(x) -> float:\n pass",
"def _parse_float(\n value_expr: str, target_expr: str, ref_parts: List[str],\n a_type: mapry.Float, auto_id: mapry.py.generate.AutoID) -> str:\n uid = auto_id.next_identifier()\n\n return _PARSE_FLOAT_TPL.render(\n uid=uid,\n value_expr=value_ex... | [
"0.6342761",
"0.6320651",
"0.6213092",
"0.6203347",
"0.6141952",
"0.6121117",
"0.61017215",
"0.6098951",
"0.6050367",
"0.6024089",
"0.59904677",
"0.5978502",
"0.59352803",
"0.592038",
"0.59183156",
"0.5900775",
"0.58872736",
"0.586948",
"0.58320737",
"0.58320016",
"0.58029497... | 0.0 | -1 |
Set data, get the highest/lowest value and calculate the total and steps | def __set_temperatures(self):
while True:
temp = self.__get_correct_input()
if temp != self.__QUIT_COMMAND:
self.__total += temp
self.__steps += 1
if temp > self.__highest:
self.__highest = temp
if temp < self.__lowest:
self.__lowest = temp
if temp < self.__LOW_TEMPERATURE_ALARM:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def apply(self, data):\n\t\t#######################################################################\n\t\t# ** START OF YOUR CODE **\n\t\t#######################################################################\n\t\treturn (data-self.data_min)/(self.data_max-self.data_min)\n\t\t################... | [
"0.63865316",
"0.6036022",
"0.59460676",
"0.5855021",
"0.58470994",
"0.58068866",
"0.57772464",
"0.5775998",
"0.56909174",
"0.5690023",
"0.56552947",
"0.56500727",
"0.5647984",
"0.5621928",
"0.56047326",
"0.5590412",
"0.55899316",
"0.55533165",
"0.55443025",
"0.55302304",
"0.... | 0.53003895 | 52 |
Reset all record and get ready for another calculation | def __reset(self):
self.__highest = -float('inf')
self.__lowest = float('inf')
self.__total = 0
self.__steps = 0
self.__cold_days = 0 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def reset(self):\n self.calc1.reset()\n self.calc2.reset()\n self.calc3.reset()\n self.calc4.reset()\n self.calc5.reset()\n self.calc6.reset()\n self.calc7.reset()\n self.calc8.reset()\n self.calc9.reset()\n self.calc10.reset()",
"def reset(se... | [
"0.77041435",
"0.74155897",
"0.7388335",
"0.73420775",
"0.73420775",
"0.73397404",
"0.719545",
"0.71558064",
"0.71446407",
"0.7093807",
"0.7093807",
"0.7093807",
"0.70556104",
"0.7054783",
"0.7039421",
"0.70392364",
"0.70332664",
"0.7028386",
"0.70257473",
"0.7018025",
"0.701... | 0.0 | -1 |
To make sure the input is a number | def __get_correct_input(self):
while True:
temp = input(f'Next Temperature: (or {self.__QUIT_COMMAND} to quit)? ')
try:
return int(temp)
except ValueError:
print('The input is not valid') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def CheckNumber(userInput):\n try:\n float(userInput)\n return True\n except(ValueError):\n return False",
"def is_number(n):\n return isinstance(n, (int, float))",
"def is_number(value):\n try:\n int(value)\n return True\n except (ValueError, TypeError):\n ... | [
"0.7778431",
"0.765497",
"0.75661147",
"0.75186193",
"0.75132155",
"0.74904877",
"0.7482881",
"0.7475753",
"0.7475029",
"0.74599016",
"0.74503165",
"0.7442724",
"0.74308676",
"0.7423358",
"0.74220467",
"0.737716",
"0.7367973",
"0.73571527",
"0.73452747",
"0.73430526",
"0.7327... | 0.0 | -1 |
Builds a `ModelResults` object from training and testing data. | def from_data(cls, model_params, y_train, train_preds,
y_test, test_preds, trace, target_col):
train_preds, test_preds = utils.cap_train_and_test_predictions(
train_preds, test_preds)
start = len(train_preds)
end = start + len(test_preds)
results_dict = util... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def train(self): \n start_time = time()\n\n # reset previous results\n self.best_result = pd.DataFrame()\n self.result = pd.DataFrame()\n\n # Generate dictionaries of all posible parameter permutations\n keys, values = zip(*self.params.items())\n self.permuta... | [
"0.646548",
"0.6221923",
"0.62212306",
"0.61293733",
"0.6127586",
"0.6083793",
"0.60787904",
"0.6065964",
"0.60605586",
"0.60277426",
"0.6002492",
"0.5993392",
"0.5984186",
"0.5919606",
"0.59128535",
"0.591156",
"0.58957183",
"0.58578795",
"0.58560926",
"0.5815098",
"0.581071... | 0.0 | -1 |
Builds null model results. A null model results object is a `ModelResults` object in which all values are null. Returns ModelResults A null `ModelResults` object. | def build_null_model_results(cls):
results_dict = {results_col: np.nan
for results_col in specs.RESULTS_COLS}
harvest_stats_dict = {
buffer_pct: HarvestStats.build_null_harvest_stats()
for buffer_pct in specs.BUFFER_PCTS}
return cls({}, results_dic... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __unwrapResults(self):\n if self.__cachedResults is None:\n if self.__rawInfo.results is not None:\n resultList = json.loads(self.__rawInfo.results)\n assert len(resultList) == 2, \\\n \"Expected 2 elements, but got %s (%s).\" % (\n len(resultList), resultList... | [
"0.6237484",
"0.5802736",
"0.5723429",
"0.5420379",
"0.539289",
"0.5236211",
"0.5229382",
"0.51973647",
"0.51388884",
"0.51044345",
"0.50627637",
"0.5057253",
"0.49960345",
"0.49328384",
"0.49274898",
"0.49107206",
"0.48796177",
"0.4867561",
"0.48638237",
"0.48547965",
"0.485... | 0.78038603 | 0 |
Gets the model results columns. These are the names of the variables of the `ModelResults` object, appearing in the same order as the list representation of the model results. Returns list A list of strings representing the names of the columns of the `ModelResults` object. | def get_model_results_cols(self):
harvest_cols = HarvestStats.get_harvest_columns_for_buffers()
return ["params"] + specs.RESULTS_COLS + harvest_cols | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_columns(self):\n columns = []\n for column in self.columns:\n columns.append(column.data.name)\n return columns",
"def columns(self):\n result = self.execute(self.commands.table_columns(self.name))\n return [x[0] for x in result]",
"def columns(self, model=... | [
"0.68451345",
"0.6789725",
"0.6645704",
"0.65304536",
"0.65295225",
"0.6463279",
"0.64613503",
"0.6439484",
"0.6391215",
"0.6350888",
"0.63452",
"0.6339204",
"0.63063014",
"0.63024807",
"0.6265027",
"0.626092",
"0.6218528",
"0.62119365",
"0.6211512",
"0.6210677",
"0.6204148",... | 0.7914969 | 0 |
The model parameters associated with the results. Returns tuple A tuple specifying the model parameters associated with the results. | def get_model_params(self):
return self._model_params | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def parameters(self):\n return self.model.parameters()",
"def get_model_params(self):\n\n results = self._model.fit()\n model_params = np.expand_dims(results.params.as_matrix(), 1)\n return model_params",
"def get_model_params(self):\n w1 = self.w1\n b1 = self.b1\n ... | [
"0.75586253",
"0.7419984",
"0.726825",
"0.7237327",
"0.7097789",
"0.7016339",
"0.70153385",
"0.6999316",
"0.69914156",
"0.6953252",
"0.6940094",
"0.6927716",
"0.69131255",
"0.69131255",
"0.69131255",
"0.6862749",
"0.6862749",
"0.68351525",
"0.68345207",
"0.68340087",
"0.68340... | 0.72877127 | 2 |
Retrieves the model results. Returns dict A dictionary containing the model results. | def get_model_results(self):
return self._results_dict | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def results(self):\n return extract_results(self.model)",
"def get_results(self):\n return self.results",
"def get_results(self):\n return self.results",
"def GetResults(self):\n return self._results",
"def get_results(self):\n return self.result",
"def get_results(self):\n... | [
"0.76512617",
"0.7250927",
"0.7250927",
"0.7165058",
"0.71104646",
"0.7065672",
"0.6948484",
"0.6898489",
"0.67698526",
"0.6763811",
"0.6760713",
"0.6705164",
"0.66972226",
"0.66972226",
"0.66551745",
"0.6650503",
"0.6627542",
"0.6627542",
"0.6627542",
"0.66273904",
"0.659701... | 0.82414335 | 0 |
Converts the model results to a list. Returns list A 9element list consisting of the model parameters and 8 floats representing the model results. | def to_list(self):
model_lst = [self._model_params]
for result in specs.RESULTS_COLS:
model_lst.append(self._results_dict[result])
for buffer_pct in specs.BUFFER_PCTS:
model_lst.extend(self._harvest_stats_dict[buffer_pct].to_list())
return model_lst | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_list_of_results(self):\n return self.__result_list",
"def __to_list(__results):\n rows = []\n for row in __results:\n rows.append(row)\n \n __results.close()\n\n return rows",
"def results(self) -> list:\n return self._... | [
"0.68007237",
"0.67216784",
"0.66928416",
"0.6679285",
"0.6616853",
"0.66016215",
"0.6484065",
"0.6437642",
"0.6435629",
"0.6417909",
"0.6390932",
"0.63305646",
"0.6188584",
"0.6112668",
"0.6065527",
"0.60347897",
"0.60145533",
"0.6003021",
"0.6002833",
"0.59735084",
"0.59684... | 0.7711234 | 0 |
Checks if the model results are better than `other_model_results`. The current model results are better than `other_model_results` if the `HarvestStats` at the lowest buffer percentage are better than the `HarvestStats` at the same buffer percentage in `other_model_results`. | def is_better(self, other_model_results):
buffer_pct = specs.TUNING_BUFFER_PCT
return self._harvest_stats_dict[buffer_pct].is_better(
other_model_results._harvest_stats_dict[buffer_pct]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def compare_thresholded_data_with_models(self):\n pass",
"def report_result(\n self,\n result: Mapping[str, Any],\n model: nn.Module,\n epoch: int,\n ) -> bool:\n metric = get_from_nested_dict(result, key=self.key, default=None)\n if metric is None:\n ... | [
"0.6502473",
"0.62888247",
"0.62768865",
"0.6213037",
"0.6123758",
"0.6072899",
"0.6068795",
"0.5921778",
"0.58675754",
"0.58598775",
"0.5847968",
"0.5845987",
"0.581194",
"0.57880193",
"0.5772249",
"0.5712979",
"0.5709731",
"0.5681822",
"0.5666867",
"0.5664734",
"0.56527406"... | 0.83155894 | 0 |
Converts array whose rows represent diagonal entries of a matrix into the matrix itself. See scipy.linalg.solve_banded | def diag_to_matrix(l_and_u, diag):
l, u = l_and_u
dim = diag.shape[1]
matrix = np.zeros((dim, dim))
for i in range(l+u+1):
np.fill_diagonal(
matrix[max(0,i-u):,max(0,u-i):],
diag[i,max(0,u-i):]
)
return matrix | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def inv_banded(banded_matrix):\n banded_matrix = banded_matrix.toarray()\n nrows = banded_matrix.shape[0]\n nbands = np.min([np.count_nonzero(row) for row in banded_matrix])\n ab = np.zeros((nbands, nrows))\n for i in np.arange(1, nbands):\n ab[i, :] = np.concatenate(\n (\n ... | [
"0.69575876",
"0.64048153",
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"0.5790228",
"0.57842326",
"0.57267654",
"0.5726118",
"0.5716055",
"0.5690097... | 0.5298268 | 86 |
Given an array of points which define a bezier curve, and two numbres 0<=a<b<=1, return an array of the same size, which describes the portion of the original bezier curve on the interval [a, b]. This algorithm is pretty nifty, and pretty dense. | def partial_bezier_points(points, a, b):
a_to_1 = np.array([
bezier(points[i:])(a)
for i in range(len(points))
])
return np.array([
bezier(a_to_1[:i+1])(b)
for i in range(len(points))
]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def qbezier_bounds((x0, y0), (x1, y1), (x2, y2)):\n\n\t# cubic Bezier reprsented in polynomial base\n\t# f(t) = A*t^2 + B*t + C\n\tAx = x0 - 2*x1 + x2\n\tBx = -2*x0 + 2*x1\n\tCx = x0\n\n\tAy = y0 - 2*y1 + y2\n\tBy = -2*y0 + 2*y1\n\tCy = y0\n\n\t# find extremas:\n\t#\t1) x(0) = x0\n\t#\t2) x(1) = x2\n\t... | [
"0.6650105",
"0.6489684",
"0.64395845",
"0.63854486",
"0.6252875",
"0.62005275",
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"0.58710194",
"0.58644146",
"0.5855325",
"0.58526003",
"0.5766097",
"0.576... | 0.788962 | 0 |
Used instead of list(set(l)) to maintain order | def remove_list_redundancies(l):
return sorted(list(set(l)), lambda a, b : l.index(a) - l.index(b)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def dedup_list(l):\n return list(set(l))",
"def sort_4(l):\n l = list(set(l))\n l.sort()",
"def list_remove_duplicates(l):\n seen = set()\n seen_add = seen.add\n return [x for x in l if not (x in seen or seen_add(x))]",
"def _unique(li):\n return list(set(li))",
"def remove_duplicates(... | [
"0.76383084",
"0.7485584",
"0.73525107",
"0.72422785",
"0.71003187",
"0.7076367",
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"0.66209424",
"0.6594591",
"0.6577758",
"0.6537239",
"0.6518429",
"0.651641... | 0.74946845 | 1 |
Used instead of list(set(l1).update(l2)) to maintain order, making sure duplicates are removed from l1, not l2. | def list_update(l1, l2):
return filter(lambda e : e not in l2, l1) + list(l2) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _merge_lists(cls, li1, li2):\n if not li1:\n return li2[:]\n elif not li2:\n return li1[:]\n else:\n li = li1[:]\n for el in li2:\n if el not in li:\n li.append(el)\n return li",
"def remove_repeated... | [
"0.7263704",
"0.7154067",
"0.68808377",
"0.6878345",
"0.6875592",
"0.68290365",
"0.6800653",
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"0.6333746",
"0.6276453",
"0.6201921",
"0.6175894",
"0.61337626",
"0.6115901",
"0.6112074",
"0.6100564... | 0.73580694 | 0 |
Useful so that classes or instance of those classes can be included in configuration, which can prevent defaults from getting created during compilation/importing | def instantiate(obj):
return obj() if isinstance(obj, type) else obj | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _config_classes(self):\n pass",
"def get_default_config(cls) -> Dict[str, Any]:\n\n def get_class_type(name: str, classes: dict):\n _cls = classes.get(name)\n if _cls is None:\n raise ValueError(f\"must be one of {list(classes)}: {name}\")\n retur... | [
"0.7530671",
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"0.5724937",
"0.5696248",
"0.5683502",
"0.5683502",
"0.56623834",
"0.5659636"... | 0.0 | -1 |
Sets init args and CONFIG values as local variables The purpose of this function is to ensure that all configuration of any object is inheritable, able to be easily passed into instantiation, and is attached as an attribute of the object. | def digest_config(obj, kwargs, local_args = {}):
### Assemble list of CONFIGs from all super classes
classes_in_heirarchy = [obj.__class__]
configs = []
while len(classes_in_heirarchy) > 0:
Class = classes_in_heirarchy.pop()
classes_in_heirarchy += Class.__bases__
if hasattr(Clas... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, *args, **kwargs):\r\n super().__init__()\r\n self._cfg = ConfigDict() # current configuration\r\n self._default_config = ConfigDict() # default configuration\r\n self._temp_config = OrderedDict() # temporary configuration\r\n self._path = Path() # current c... | [
"0.6853178",
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"0.6305136",
"0.6272914",
"0.6256017",
"0.625568",
"0.62324893",
"0.6221033"... | 0.0 | -1 |
Returns true of p0 is on the line between p1 and p2 | def is_on_line(p0, p1, p2, threshold = 0.01):
p0, p1, p2 = map(lambda tup : np.array(tup[:2]), [p0, p1, p2])
p1 -= p0
p2 -= p0
return abs((p1[0] / p1[1]) - (p2[0] / p2[1])) < threshold | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_line_on_line(feature_1: Sequence, feature_2: Sequence) -> bool:\n\n line_on_line = False\n\n for coords in feature_1:\n\n line_on_line = boolean_point_on_line(coords, feature_2)\n if not line_on_line:\n break\n\n return line_on_line",
"def isPointOnLine(node1, node2, poin... | [
"0.7579855",
"0.7464677",
"0.7417148",
"0.7244791",
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"0.7003025",
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"0.66139954",
"0.6600058",
"0.65791726",
"0.65495944",
"0.6538196... | 0.8123824 | 0 |
A "line" should come in the form [(x0, y0), (x1, y1)] for two points it runs through | def intersection(line1, line2):
p0, p1, p2, p3 = map(
lambda tup : np.array(tup[:2]),
[line1[0], line1[1], line2[0], line2[1]]
)
p1, p2, p3 = map(lambda x : x - p0, [p1, p2, p3])
transform = np.zeros((2, 2))
transform[:,0], transform[:,1] = p1, p2
if np.linalg.det(transform) == 0... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def line(x1, y1, x2, y2):\r\n\r\n x1 = normalize(x1)\r\n y1 = normalize(y1)\r\n x2 = normalize(x2)\r\n y2 = normalize(y2)\r\n\r\n xdiff = max(x1, x2) - min(x1, x2)\r\n ydiff = max(y1, y2) - min(y1, y2)\r\n xdir = 1 if x1 <= x2 else -1\r\n ydir = 1 if y1 <= y2 else -1\r\n\r\n r = max(xdif... | [
"0.8037015",
"0.747192",
"0.73408955",
"0.7293409",
"0.72838026",
"0.7218734",
"0.7174965",
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"0.6946191",
"0.69096845",
"0.6909664",
"0.68535465",
"0.6849273",
"0.6845207",
"0.68186456... | 0.0 | -1 |
func_list should contain elements of the form (f, args) | def composition(func_list):
return reduce(
lambda (f1, args1), (f2, args2) : (lambda x : f1(f2(x, *args2), *args1)),
func_list,
lambda x : x
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def eval_func_tuple(f_args):\n return f_args[0](*f_args[1:])",
"def eval_f(f, xs):\n l = []\n for x in xs:\n l.append(f(x))\n return l",
"def _parse_functions(self, locals: dict):\n functions_dict = dict(filter(self._isfunction, locals.items()))\n functions = []\n if not... | [
"0.66027486",
"0.6527124",
"0.6456615",
"0.6453033",
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"0.6453033",
"0.6453033",
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"0.64247805",
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"0.6316425",
"0.63073343",
"0.630301",
"0.63011795",
"0.62940806",
"0.62505835... | 0.60185134 | 33 |
Rotation in R^3 about a specified axess of rotation. | def rotation_matrix(angle, axis):
about_z = rotation_about_z(angle)
z_to_axis = z_to_vector(axis)
axis_to_z = np.linalg.inv(z_to_axis)
return reduce(np.dot, [z_to_axis, about_z, axis_to_z]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rotate3(x, angle_x=0, angle_y=0, angle_z=0, origin=(0, 0, 0)):\n origin = np.asarray(origin)\n x = np.asarray(x) - origin\n r = rotation_matrix3(angle_x, angle_y, angle_z)\n return x.dot(r.T) + origin",
"def rotation(self, p1, p2, p3):\n return (p2[0] - p1[0]) * (p3[1] - p1[1]) - (p2[1] - ... | [
"0.74250835",
"0.72524756",
"0.67635214",
"0.67440736",
"0.669359",
"0.66566396",
"0.6622887",
"0.65798664",
"0.65373707",
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"0.64486176",
"0.64481574",
"0.64349747",
"0.6420502",
"0.64017946",
"0.6375933",
"0.63... | 0.0 | -1 |
Returns some matrix in SO(3) which takes the zaxis to the (normalized) vector provided as an argument | def z_to_vector(vector):
norm = np.linalg.norm(vector)
if norm == 0:
return np.identity(3)
v = np.array(vector) / norm
phi = np.arccos(v[2])
if any(v[:2]):
#projection of vector to unit circle
axis_proj = v[:2] / np.linalg.norm(v[:2])
theta = np.arccos(axis_proj[0])
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def vec(x, y=0.0, z=0.0):\n return np.matrix((x, y, z)).T",
"def vector3(x, y, z):\n return np.array([x, y, z], dtype=float)",
"def vector3(x, y, z):\n return np.array([x, y, z], dtype=np.float)",
"def transl(x, y, z):\n displace_vector = [[x],\n [y],\n ... | [
"0.6809458",
"0.65553045",
"0.6546179",
"0.6475817",
"0.6406058",
"0.63439775",
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"0.6097854",
"0.60896564",
"0.6088202",
"0.60877305",
"0.60507977",
"0.604126... | 0.63574386 | 5 |
Returns polar coordinate theta when vector is project on xy plane | def angle_of_vector(vector):
z = complex(*vector[:2])
if z == 0:
return 0
return np.angle(complex(*vector[:2])) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def vector_polar(v):\n return vector_mag(v), vector_angle(v)",
"def xy_rotation(vector,theta):\r\n R = np.array([[np.cos(theta), -np.sin(theta),0],\r\n [np.sin(theta), np.cos(theta),0],\r\n [0,0,1]\r\n ])\r\n return np.dot(R,vector)",
"def get_phi_the... | [
"0.76956666",
"0.7633337",
"0.7338335",
"0.6962628",
"0.6891784",
"0.68915886",
"0.6874387",
"0.6853124",
"0.6806457",
"0.67847264",
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"0.6538311",
"0.6537484",
"0.6536811",
"0.6521249",
"0.65063834",
"0.6497525",
"0.6476558",... | 0.62594527 | 41 |
Create input dictionary for the calculation | def _init_calculation(self):
# count number of previous calculations
self.ctx.running_calc += 1
# set the structure
self.ctx.inputs.structure = self.inputs.structure
# # deal with oxidation states
# if self.ctx.running_calc > 1 and self.ctx.try_oxi:
# self.r... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_intermediate_dict(self) -> Dict[str, float]:\n intermediate = {}\n now = datetime.now()\n current_time = now.replace(hour=0, minute=0, second=0, microsecond=0)\n\n delta = timedelta(minutes=15)\n\n for i in range(0, 96):\n intermediate[self.date_to_intermedia... | [
"0.63354945",
"0.630033",
"0.6294846",
"0.6259771",
"0.62242556",
"0.6103733",
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"0.6063543",
"0.6020394",
"0.6008215",
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"0.59737456",
"0.5971995",
"0.59629464",
"0.5956414",
"0.59546196",
"0.59536123",
"0.59359044... | 0.0 | -1 |
Check if calculation is runnable, either as the original or as the restart | def runnable(self):
if "calculations" not in self.ctx:
return True # if no calculations have run
return self.ctx.running_calc < 2 and self.can_restart() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_runnable(self):\n return self.state == self.STATE_INIT and not self.require",
"def running(self) -> bool:",
"def check_results(self):\n if not self.ctx.is_restart and self.can_restart():\n self.ctx.is_restart = True\n self.report('Calculation is not converged and rest... | [
"0.64345175",
"0.64055866",
"0.62883925",
"0.6022785",
"0.583515",
"0.5817639",
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"0.5721791",
"0.57163495",
"0.5706602",
"0.5685521",
"0.5668268",
"0.5666... | 0.7984654 | 0 |
Run a calculation from self.ctx.inputs | def run_calculation(self):
process = CalculationFactory(self.ctx.calculation)
running = self.submit(process, **self.ctx.inputs)
return self.to_context(calculations=append_(running)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run(self, inputs):\n for layer in self._layers:\n inputs = layer.calc(inputs)\n return inputs",
"def calculate(self, inputs):\r\n output = inputs\r\n for layer in self.layers:\r\n output = layer.calculate(output)\r\n return output",
"async def comput... | [
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"0.6835724",
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"0.6677566",
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"0.6313585",
"0.6303633",
"0.62906355",
"0.62707853",
"0.62667006",
"0.626... | 0.66676795 | 4 |
Check the calculation results, amend calculation inputs and make it restart if needed | def check_results(self):
if not self.ctx.is_restart and self.can_restart():
self.ctx.is_restart = True
self.report('Calculation is not converged and restart parameters are given: calc scheduled for restart') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def main():\n welcome_message()\n continue_program = True\n num_calculations = 0\n # all the calculation options in the program\n calculation_options = [\"addition\", \"subtraction\", \"division\",\n \"multiplication\", \"exponents\", \"circle area\",\n ... | [
"0.62992084",
"0.62845427",
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"0.625051",
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"0.6044138",
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"0.59184784",
"0.588707",
"0.5873105",
"0.5863846",
"0.5855877",
"0.5837538",
... | 0.7682695 | 0 |
Process calculation results; adapted from aiida_vasp | def retrieve_results(self):
# return the results of the last calculation
last_calc = self.ctx.calculations[-1]
# check exit status of a last calc
if last_calc.exit_status not in (None, 0):
self.report(f'The calculations failed with exit message: {last_calc.exit_message}')
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _calc_result(self, results, calc):\r\n lg = logging.getLogger(\"%s.%s\" % (self.ln, inspect.stack()[0][3]))\r\n lg.setLevel(self.log_level)\r\n # if the calculation is empty exit\r\n if calc is None:\r\n return results\r\n lg.debug(\"calc %s\", calc)\r\n # p... | [
"0.67349535",
"0.66774166",
"0.6657482",
"0.65898657",
"0.64503765",
"0.64330107",
"0.6363478",
"0.63621926",
"0.63179433",
"0.6301655",
"0.6234125",
"0.62197614",
"0.62122",
"0.620175",
"0.6156571",
"0.61563945",
"0.6110802",
"0.6085085",
"0.60796386",
"0.607358",
"0.6043771... | 0.0 | -1 |
Finalize calculation, clean remote directory if needed (adapted from aiidavasp) | def finalize(self):
if not self.inputs.clean_workdir:
return
cleaned_calcs = []
for calculation in self.ctx.calculations:
try:
# noinspection PyProtectedMember
calculation.outputs.remote_folder._clean()
cleaned_calcs.append(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def on_terminated(self):\n super(PwBandsWorkChain, self).on_terminated()\n\n if self.inputs.clean_workdir.value is False:\n self.report('remote folders will not be cleaned')\n return\n\n cleaned_calcs = []\n\n for called_descendant in self.calc.called_descendants:\... | [
"0.6397654",
"0.6368182",
"0.61231685",
"0.61225873",
"0.6119665",
"0.60274994",
"0.6024973",
"0.59868515",
"0.593518",
"0.5925773",
"0.5923112",
"0.591191",
"0.5894966",
"0.5868265",
"0.5841424",
"0.5815715",
"0.580706",
"0.5800703",
"0.57971424",
"0.57971424",
"0.57971424",... | 0.75777876 | 0 |
Create input dictionary for the calculation, deal with restart (later?) | def init_calculation(self):
self.ctx.inputs = AttributeDict()
# set the code
self.ctx.inputs.code = self.inputs.code
# set the wavefunction
self.ctx.inputs.wavefunction = self.inputs.wavefunction
# set parameters, giving the defaults
self.ctx.inputs.parameters ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_intermediate_dict(self) -> Dict[str, float]:\n intermediate = {}\n now = datetime.now()\n current_time = now.replace(hour=0, minute=0, second=0, microsecond=0)\n\n delta = timedelta(minutes=15)\n\n for i in range(0, 96):\n intermediate[self.date_to_intermedia... | [
"0.6584127",
"0.6164442",
"0.6076059",
"0.6046547",
"0.60108364",
"0.6010455",
"0.60099846",
"0.5975037",
"0.59471935",
"0.59418076",
"0.5911587",
"0.5910082",
"0.5894325",
"0.5836499",
"0.5753927",
"0.575177",
"0.57376254",
"0.5719721",
"0.57039464",
"0.56982744",
"0.5694113... | 0.57079095 | 18 |
Set defaults to calculation parameters | def _set_default_parameters(self, parameters):
parameters_dict = parameters.get_dict()
from aiida_crystal_dft.io.f9 import Fort9
with self.inputs.wavefunction.open(mode='rb') as f:
file_name = f.name
wf = Fort9(file_name)
if 'band' in parameters_dict:
# a... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _default_parameters(cls) -> Options:\n params = super()._default_parameters()\n params.main_axes = None\n params.i_means = None\n params.q_means = None\n params.scales = None\n\n return params",
"def set_default_parameters(self):\n super().set_default_paramete... | [
"0.6943066",
"0.6919235",
"0.6629486",
"0.6605372",
"0.65865785",
"0.65397674",
"0.6539674",
"0.6494178",
"0.64272714",
"0.63984066",
"0.63891405",
"0.63767976",
"0.6373579",
"0.6346972",
"0.63348526",
"0.63092655",
"0.6272867",
"0.6268823",
"0.62534904",
"0.62277675",
"0.622... | 0.5884307 | 57 |
Run a calculation from self.ctx.inputs | def run_calculation(self):
process = CalculationFactory(self._calculation)
running = self.submit(process, **self.ctx.inputs)
return self.to_context(calculations=append_(running)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run(self, inputs):\n for layer in self._layers:\n inputs = layer.calc(inputs)\n return inputs",
"def calculate(self, inputs):\r\n output = inputs\r\n for layer in self.layers:\r\n output = layer.calculate(output)\r\n return output",
"async def comput... | [
"0.73888916",
"0.68371904",
"0.6684268",
"0.6678672",
"0.66685766",
"0.65434",
"0.6542864",
"0.6502158",
"0.63943106",
"0.639336",
"0.6384044",
"0.63404804",
"0.632782",
"0.63258415",
"0.6315129",
"0.63148564",
"0.63052267",
"0.6290937",
"0.6270991",
"0.6267059",
"0.62588346"... | 0.64950955 | 8 |
Process calculation results; adapted from aiida_vasp | def retrieve_results(self):
# return the results of the last calculation
last_calc = self.ctx.calculations[-1]
for name, port in self.spec().outputs.items():
if port.required and name not in last_calc.outputs:
self.report('the spec specifies the output {} as required ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _calc_result(self, results, calc):\r\n lg = logging.getLogger(\"%s.%s\" % (self.ln, inspect.stack()[0][3]))\r\n lg.setLevel(self.log_level)\r\n # if the calculation is empty exit\r\n if calc is None:\r\n return results\r\n lg.debug(\"calc %s\", calc)\r\n # p... | [
"0.6734962",
"0.6677146",
"0.6657827",
"0.65906954",
"0.6450266",
"0.6432466",
"0.636254",
"0.63616407",
"0.6317594",
"0.63020205",
"0.62345845",
"0.6220271",
"0.62130886",
"0.6202688",
"0.6157641",
"0.6157569",
"0.6111835",
"0.60845757",
"0.60801816",
"0.607423",
"0.6044211"... | 0.0 | -1 |
Bryukh's solution >>> solution() 5482660 | def solution():
pentagonals = []
n = 1
while True:
newp = (n*(3*n-1))/2
for p in pentagonals:
diff = abs(newp-p)
if ispentagonal(diff) and ispentagonal(newp+p):
return diff
pentagonals.append(newp)
n += 1 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def solution(s):",
"def solution(self):\n return [(\"the\", 1579644)] * 100",
"def solve(self):",
"def exercise_b2_52():\r\n pass",
"def solution(self) -> State:",
"def exercise_b2_53():\r\n pass",
"def exercise_b2_113():\r\n pass",
"def exercise_b2_82():\r\n pass",
"def solution(sel... | [
"0.7280032",
"0.69121206",
"0.66888416",
"0.6620982",
"0.6602587",
"0.6577295",
"0.6460368",
"0.6443591",
"0.64340264",
"0.6396119",
"0.6313636",
"0.6311839",
"0.62898034",
"0.62776446",
"0.62592465",
"0.6256724",
"0.6208561",
"0.62069046",
"0.61867815",
"0.6186715",
"0.61863... | 0.0 | -1 |
Will save the state so it can be restored later | def save(self):
self.pushes.append((self.token, self.stream, self.line, self.column)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save_state(self):\n pass",
"def saveState(self) -> None:\n # TODO: Saves State\n pass",
"def savestate(self, state):\n pass",
"def save_state(self) -> None:\n raise NotImplementedError(\"Save state is is not implemented.\")",
"def save(self, *args, **kwargs):\n ... | [
"0.9262114",
"0.88588667",
"0.8651228",
"0.8636893",
"0.8285493",
"0.7981114",
"0.7923887",
"0.76744914",
"0.7601485",
"0.75755954",
"0.7566344",
"0.75488573",
"0.7545564",
"0.75297433",
"0.743897",
"0.74088436",
"0.7294165",
"0.7291157",
"0.72792566",
"0.7241757",
"0.7219886... | 0.0 | -1 |
Will restore the state to the saved state | def restore(self):
token, stream, line, col = self.pushes.pop()
self.token = token
self.stream = stream
self.line = line
self.column = col | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def restore_state(self, state):\n state_ref = self.ale.decodeState(state)\n self.ale.restoreState(state_ref)\n self.ale.deleteState(state_ref)",
"def restore(self):\n raise NotImplementedError",
"def restore_state(self, state: ale_py.ALEState):\n self.ale.restoreState(state)"... | [
"0.81704223",
"0.81169754",
"0.80634177",
"0.79704624",
"0.7892635",
"0.78692335",
"0.7859833",
"0.7734005",
"0.7663427",
"0.7634011",
"0.7608364",
"0.75698084",
"0.75514317",
"0.74182177",
"0.73968023",
"0.73769253",
"0.73577315",
"0.7354427",
"0.73164636",
"0.7300497",
"0.7... | 0.0 | -1 |
Discard the last saved state | def discard(self):
self.pushes.pop() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def restore_last_undo_point(self):\n self.unload()",
"def revert_state(self):\n if self.previous_states > 0: # checks for empty\n self.update_status(self.previous_states.pop())",
"def reset(self):\n self.history_states.clear()",
"def reset_state(self):\n return dict(sel... | [
"0.70523554",
"0.69862825",
"0.6965245",
"0.68354887",
"0.67271405",
"0.6689352",
"0.66892314",
"0.6631443",
"0.6619713",
"0.6613089",
"0.6596752",
"0.6594047",
"0.659116",
"0.6574138",
"0.65437245",
"0.65336823",
"0.65235734",
"0.6473415",
"0.64700496",
"0.6468176",
"0.64681... | 0.0 | -1 |
Initialize parameters and build model. Params ====== | def __init__(self, state_size, action_size, seed, fc_units=[128,128]):
super(Actor, self).__init__()
self.seed = torch.manual_seed(seed)
self.fc = []
self.fc.append(nn.Linear(state_size, fc_units[0]))
self.fc.append(nn.ReLU())
for i in range(1,len(fc_units)):
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, **kwargs):\n super(Model, self).__init__(**kwargs)\n self._params = self.find_params()",
"def build_model():",
"def build_model(self):\n pass",
"def build_model(self):\n pass",
"def __init__(self, param_dictionary):\n\n BaseModel.__init__(self)\n\n ... | [
"0.79983556",
"0.77646637",
"0.73733515",
"0.73733515",
"0.72585744",
"0.7250074",
"0.7170411",
"0.71661454",
"0.7156735",
"0.70888656",
"0.70778716",
"0.70772207",
"0.7069133",
"0.70286226",
"0.70094854",
"0.697547",
"0.69357735",
"0.6890618",
"0.6884159",
"0.6858014",
"0.68... | 0.0 | -1 |
Build an actor (policy) network that maps states > actions. | def forward(self, state):
x = self.fc(state)
return x | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _make_actor_network(states, num_controls, params, scope_name):\n scope_key = scope_name + '/'\n with tf.variable_scope(scope_name):\n hidden_1 = tf.layers.dense(states,\n units=params.actor_hidden_units[0],\n activation=None,\n ... | [
"0.69361234",
"0.6364334",
"0.6270192",
"0.6208838",
"0.62005234",
"0.6187673",
"0.6147678",
"0.61465186",
"0.61283225",
"0.6019157",
"0.60020804",
"0.5976981",
"0.59597296",
"0.59523076",
"0.59488183",
"0.5928019",
"0.5916519",
"0.58979034",
"0.58936965",
"0.5891595",
"0.588... | 0.0 | -1 |
Initialize parameters and build model. Params ====== | def __init__(self, state_size, action_size, seed, fc_units=[128, 128, 128]):
super(Critic, self).__init__()
self.seed = torch.manual_seed(seed)
self.fc1 = nn.Sequential(nn.Linear(state_size, fc_units[0]),
nn.ReLU())
self.fc2 = []
for i in range(1,... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, **kwargs):\n super(Model, self).__init__(**kwargs)\n self._params = self.find_params()",
"def build_model():",
"def build_model(self):\n pass",
"def build_model(self):\n pass",
"def __init__(self, param_dictionary):\n\n BaseModel.__init__(self)\n\n ... | [
"0.79974955",
"0.77619344",
"0.7370926",
"0.7370926",
"0.72581285",
"0.7249673",
"0.71711296",
"0.71638674",
"0.71567893",
"0.7086708",
"0.70749104",
"0.70745933",
"0.7067782",
"0.7028256",
"0.7006761",
"0.6972652",
"0.69358397",
"0.68917364",
"0.68821913",
"0.68578583",
"0.6... | 0.0 | -1 |
Build a critic (value) network that maps (state, action) pairs > Qvalues. | def forward(self, state, action):
xs = self.fc1(state)
x = torch.cat((xs, action), dim=1)
return self.fc2(x) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, mdp, discount=0.9, iterations=100):\n self.mdp = mdp\n self.discount = discount\n self.iterations = iterations\n self.values = util.Counter() # A Counter is a dict with default 0\n self.actions = {}\n\n # iterating over all states and over all possible ... | [
"0.6131123",
"0.5916274",
"0.5914222",
"0.58920246",
"0.5792611",
"0.5785752",
"0.5772253",
"0.5719415",
"0.5712879",
"0.5707243",
"0.5700962",
"0.5635917",
"0.5635139",
"0.55866385",
"0.55533576",
"0.5539992",
"0.5538776",
"0.553673",
"0.5503467",
"0.5502352",
"0.54854625",
... | 0.0 | -1 |
Initialize an Agent object. Params ====== | def __init__(self, state_size, action_size, random_seed):
self.state_size = state_size
self.action_size = action_size
self.seed = random.seed(random_seed)
# Actor Network (w/ Target Network)
self.actor_local = Actor(state_size, action_size, random_seed).to(device)
self.a... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def init(self, parameters, agent_parameters):\n pass",
"def agent_init(self):\n pass",
"def __init__(self, agent: AEA) -> None:\n self._agent = agent\n super().__init__()",
"def __init__(self, agent):\n self.agent = agent",
"def __init__(self, env, agent, agent_config, re... | [
"0.79144794",
"0.7907644",
"0.78940237",
"0.7858127",
"0.7576287",
"0.75161403",
"0.73331255",
"0.7310851",
"0.7076011",
"0.7008415",
"0.6965792",
"0.6952463",
"0.69338655",
"0.69262373",
"0.6922748",
"0.6908661",
"0.6906984",
"0.6862683",
"0.6776692",
"0.6774649",
"0.6766101... | 0.0 | -1 |
Save experience in replay memory, and use random sample from buffer to learn. | def step(self, state, action, reward, next_state, done):
# Save experience / reward
self.memory.add(state, action, reward, next_state, done)
# Learn, if enough samples are available in memory
if len(self.memory) > BATCH_SIZE:
experiences = self.memory.sample()
se... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def experience_replay(self):\n s,a,r,sp,done = self.memory.sample(self.batch_size)\n # TODO: 5 lines missing.\n raise NotImplementedError(\"\")\n self.Q.fit(s, target=target)",
"def learn(self, observation, action, reward, next_observation):\n\n # log transition in replay buffe... | [
"0.74321526",
"0.7182348",
"0.6886112",
"0.67871237",
"0.67315227",
"0.6636601",
"0.66350985",
"0.6614109",
"0.654479",
"0.64978814",
"0.64533705",
"0.63893026",
"0.63325363",
"0.6220898",
"0.6161728",
"0.6121152",
"0.61211336",
"0.6089247",
"0.60032904",
"0.6002333",
"0.5994... | 0.5787425 | 45 |
Returns actions for given state as per current policy. | def act(self, state, add_noise=True):
state = torch.from_numpy(state).float().to(device)
self.actor_local.eval()
with torch.no_grad():
action = self.actor_local(state).cpu().data.numpy()
self.actor_local.train()
if add_noise:
action += self.noise.sample()
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getActions(self, state): \n util.raiseNotDefined()",
"def get_available_actions(self, state):\n pass",
"def getLegalActions(self, state):\n return self.actionFn(state)",
"def getLegalActions(self,state):\n return self.actionFn(state)",
"def get_actions(self, state: TState... | [
"0.81838465",
"0.78749645",
"0.77763903",
"0.7757848",
"0.73765945",
"0.7321794",
"0.7245651",
"0.72075933",
"0.7111871",
"0.7106728",
"0.7075502",
"0.70645916",
"0.7050402",
"0.7008547",
"0.70066535",
"0.69912755",
"0.69878536",
"0.6983712",
"0.6970548",
"0.6949809",
"0.6895... | 0.0 | -1 |
Initialize an Agent object. Params ====== | def __init__(self, state_size, action_size, num_agents, random_seed):
self.state_size = state_size
self.action_size = action_size
self.seed = random.seed(random_seed)
self.num_agents = num_agents
# Actor Network (w/ Target Network)
self.actor_local = [Actor(state_size, a... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def init(self, parameters, agent_parameters):\n pass",
"def agent_init(self):\n pass",
"def __init__(self, agent: AEA) -> None:\n self._agent = agent\n super().__init__()",
"def __init__(self, agent):\n self.agent = agent",
"def __init__(self, env, agent, agent_config, re... | [
"0.79144794",
"0.7907644",
"0.78940237",
"0.7858127",
"0.7576287",
"0.75161403",
"0.73331255",
"0.7310851",
"0.7076011",
"0.7008415",
"0.6965792",
"0.6952463",
"0.69338655",
"0.69262373",
"0.6922748",
"0.6908661",
"0.6906984",
"0.6862683",
"0.6776692",
"0.6774649",
"0.6766101... | 0.0 | -1 |
Save experience in replay memory, and use random sample from buffer to learn. | def step(self, states, actions, rewards, next_states, dones):
# Save experience / reward
for state, action, reward, next_state, done in zip(states, actions, rewards, next_states, dones):
self.memory.add(state, action, reward, next_state, done)
# Learn, if enough samples are availabl... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def experience_replay(self):\n s,a,r,sp,done = self.memory.sample(self.batch_size)\n # TODO: 5 lines missing.\n raise NotImplementedError(\"\")\n self.Q.fit(s, target=target)",
"def learn(self, observation, action, reward, next_observation):\n\n # log transition in replay buffe... | [
"0.7433034",
"0.7182474",
"0.6887168",
"0.67872477",
"0.6732001",
"0.66373146",
"0.6634795",
"0.6615569",
"0.6545275",
"0.64977324",
"0.64536935",
"0.638845",
"0.63325757",
"0.62210405",
"0.6161313",
"0.6121714",
"0.6120443",
"0.6090666",
"0.6004787",
"0.6002316",
"0.5994054"... | 0.0 | -1 |
Initialize parameters and noise process. | def __init__(self, size, seed, mu=0., theta=0.15, sigma=0.2):
self.mu = mu * np.ones(size)
self.theta = theta
self.sigma = sigma
self.seed = random.seed(seed)
self.reset() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def noisePreset() :\n s.noisePreset()",
"def __init__(self, init_pos, init_stdev, num_particles, sense_noise):\n self.particles = np.random.multivariate_normal(\n init_pos, [[init_stdev**2, 0], [0, init_stdev**2]], num_particles)\n self.weights = np.array(\n [1. / num_parti... | [
"0.7101346",
"0.70631665",
"0.6602473",
"0.6492304",
"0.6487118",
"0.6473944",
"0.6457828",
"0.64518017",
"0.6436474",
"0.64171517",
"0.6410189",
"0.64020544",
"0.63967407",
"0.63947",
"0.63871187",
"0.6379632",
"0.6376569",
"0.6375367",
"0.63648623",
"0.636282",
"0.6358098",... | 0.0 | -1 |
Reset the internal state (= noise) to mean (mu). | def reset(self):
self.state = copy.copy(self.mu) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def reset(self):\n self.noise.reset()",
"def reset_mean(self,new_mean):\n self.mean = new_mean\n return",
"def reset_mean(self,new_mean):\n self.mean = new_mean\n return",
"def reset(self):\r\n self.state = copy.copy(self.mu)",
"def reset_noise(self):\n self... | [
"0.7501553",
"0.7318112",
"0.7318112",
"0.72231454",
"0.70561457",
"0.69214433",
"0.6806284",
"0.6723683",
"0.6640285",
"0.6487892",
"0.6453199",
"0.6448848",
"0.6381134",
"0.6295363",
"0.62755775",
"0.62719554",
"0.62412703",
"0.6215498",
"0.6210647",
"0.6181644",
"0.6179889... | 0.71814483 | 12 |
Update internal state and return it as a noise sample. | def sample(self):
x = self.state
dx = self.theta * (self.mu - x) + self.sigma * np.array([random.random() for i in range(len(x))])
self.state = x + dx
return self.state | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def noise(self):\r\n if self.buffer_offset + self.frames_per_buffer - 1 > self.x_max:\r\n #relleno con ceros al final si es necesario\r\n xs = np.arange(self.buffer_offset, self.x_max)\r\n tmp = np.random.random_sample(len(xs)) #ruido\r\n out = np.append(tmp, np.z... | [
"0.71401685",
"0.7024491",
"0.70208496",
"0.7018174",
"0.7010538",
"0.7009448",
"0.69488925",
"0.69327927",
"0.69189125",
"0.69058925",
"0.6794285",
"0.6789316",
"0.67037934",
"0.65971905",
"0.6578757",
"0.6578077",
"0.6543776",
"0.65035415",
"0.6503421",
"0.6483831",
"0.6477... | 0.6966576 | 8 |
Initialize a ReplayBuffer object. Params ====== | def __init__(self, action_size, buffer_size, batch_size, seed):
self.action_size = action_size
self.memory = deque(maxlen=buffer_size) # internal memory (deque)
self.batch_size = batch_size
self.experience = namedtuple("Experience", field_names=["state", "action", "reward", "next_state"... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _initialize_buffers(self) -> None:",
"def __init__(self,buffer_size,state_dim,action_dim,random_seed=123):\n print(\"Creating Replay Buffer object\")\n self.buffer_size=buffer_size\n self.state_dim=state_dim\n self.action_dim=action_dim\n self.pointer=0\n self.states... | [
"0.7181454",
"0.713491",
"0.7095326",
"0.7037811",
"0.6902241",
"0.6832732",
"0.6715989",
"0.66719276",
"0.6636482",
"0.6636482",
"0.66211057",
"0.66046816",
"0.6513312",
"0.6483003",
"0.6372656",
"0.62879187",
"0.6269024",
"0.6256504",
"0.62485546",
"0.62461096",
"0.6237805"... | 0.0 | -1 |
Add a new experience to memory. | def add(self, state, action, reward, next_state, done):
e = self.experience(state, action, reward, next_state, done)
self.memory.append(e) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_new_experience(self, state, action, reward, next_state, done):\n e = self.experience(state, action, reward, next_state, done, self.max_priority)\n self.memory.append(e)",
"def add(self, state, action, reward, next_state, done):\n experience = Experience(state, action, reward, next_st... | [
"0.79568833",
"0.79042006",
"0.78795445",
"0.7577913",
"0.7570969",
"0.74478436",
"0.7361023",
"0.72697705",
"0.721816",
"0.71451885",
"0.7106998",
"0.7101183",
"0.69837016",
"0.68905056",
"0.68842727",
"0.6755663",
"0.6712557",
"0.6677425",
"0.64961654",
"0.6488678",
"0.6486... | 0.71984994 | 15 |
Randomly sample a batch of experiences from memory. | def sample(self):
experiences = random.sample(self.memory, k=self.batch_size)
states = torch.from_numpy(np.vstack([e.state for e in experiences if e is not None])).float().to(device)
actions = torch.from_numpy(np.vstack([e.action for e in experiences if e is not None])).float().to(device)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def experience_replay(batch_size):\n memory = []\n while True:\n experience = yield rsample(memory, batch_size) if batch_size <= len(memory) else None\n memory.append(experience)",
"def sample(self):\n sample_ind = np.random.choice(len(self.memory), self.batch_size)\n # get the ... | [
"0.766466",
"0.7457429",
"0.7440625",
"0.7404941",
"0.7354707",
"0.72963357",
"0.72740436",
"0.7271187",
"0.7271187",
"0.7262163",
"0.7245689",
"0.71789676",
"0.7083509",
"0.7074134",
"0.696216",
"0.69442594",
"0.694124",
"0.6940197",
"0.68188226",
"0.6801462",
"0.67985487",
... | 0.7283416 | 6 |
Return the current size of internal memory. | def __len__(self):
return len(self.memory) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getSize(self) -> int:\n return len(self.mem)",
"def getSize(self):\n return self.bf.memory()",
"def memsize(self):\n return self.xlist(\"get-memsize\")[1][0] * 1024",
"def size(self):\n size = 0\n size += self.data.size * sys.getsizeof(self.data)\n return size / ... | [
"0.8573486",
"0.8216719",
"0.8200263",
"0.80869377",
"0.80215144",
"0.7890612",
"0.78215307",
"0.7801178",
"0.77899903",
"0.77588975",
"0.77554387",
"0.77554387",
"0.7755218",
"0.775394",
"0.773285",
"0.77322316",
"0.7719518",
"0.77139354",
"0.7708652",
"0.77072173",
"0.76973... | 0.75126064 | 55 |
Utility function systematizing file name convention | def chk_pt_file_name(i_episode,dueling,doubleq):
chk_pt_name = 'checkpoint_{0}'.format(i_episode)
if dueling:
chk_pt_name += '_dueling'
if doubleq:
chk_pt_name += '_doubleq'
chk_pt_name += '.pth'
return os.path.join('checkpoints',chk_pt_name) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_fixed_filename(filename):\n new_name = \"\"\n for i, char in enumerate(filename):\n if i + 1 != len(filename):\n previous_character = filename[i - 1]\n next_character = filename[i + 1]\n if char.islower() and next_character.isupper():\n new_name ... | [
"0.76159656",
"0.75144535",
"0.74587727",
"0.735376",
"0.73140705",
"0.7235197",
"0.72076446",
"0.7191207",
"0.71763813",
"0.7174404",
"0.7150744",
"0.71171355",
"0.71063554",
"0.71063554",
"0.71063554",
"0.71026623",
"0.70655054",
"0.7064385",
"0.7057215",
"0.7016418",
"0.69... | 0.0 | -1 |
Query the database for a link on the current record. If found, update the existing link, if not, insert new row | def updateOrInsert(cls, session, link, model, recordID):
outLink = Link.lookupLink(session, link, model, recordID)
if outLink is None: outLink = Link(**link)
else: outLink.update(link)
return outLink | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def insert_link_into_external_link(link, found_date, anchor, link_type):\r\n db = connect()\r\n cursor = db.cursor()\r\n print \"------------------------------------------------------------------------------\"\r\n print \"link:\",link\r\n print \"link:\",found_date\r\n #print \"link:\",str(anchor... | [
"0.623239",
"0.6042356",
"0.60063356",
"0.591801",
"0.5868072",
"0.58506054",
"0.5849309",
"0.5798199",
"0.5755617",
"0.5753384",
"0.573804",
"0.5720427",
"0.56632406",
"0.5543761",
"0.55327636",
"0.55120534",
"0.5490153",
"0.54851514",
"0.5463551",
"0.5451651",
"0.5436525",
... | 0.7612958 | 0 |
Update fields on existing link | def update(self, linkData):
for field, value in linkData.items():
if field == 'flags':
setattr(self, field, value)
elif(value is not None and value.strip() != ''):
setattr(self, field, value) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def relink(self, link_id):",
"def put(self):\n if jwthandler.authorize_action(self, 1) == False:\n return None\n\n userdata = jwthandler.decode_userdata(self.request.headers[\"Authorization\"])\n\n body_categories = {\"link_id\": 1, \"view_id\": 0, \"node_id_1\": 0, \"node_id_2\":... | [
"0.68344724",
"0.66124517",
"0.660164",
"0.65914994",
"0.6363283",
"0.63509566",
"0.63125825",
"0.6273736",
"0.61451024",
"0.61311626",
"0.61165154",
"0.6072572",
"0.60497147",
"0.60104465",
"0.60076165",
"0.5906549",
"0.5847444",
"0.5844992",
"0.5826938",
"0.58229995",
"0.58... | 0.68995327 | 0 |
Query database for link related to current record. Return link if found, otherwise return None | def lookupLink(cls, session, link, model, recordID):
checkURL = Link.httpRegexSub(link.get('url', None))
return session.query(cls)\
.join(model.__tablename__)\
.filter(model.id == recordID)\
.filter(cls.url == checkURL)\
.one_or_none() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _link_for_query(self, query):\r\n results = list(query)\r\n return results[0] if results else None",
"def link(self) -> Optional[str]:\n return pulumi.get(self, \"link\")",
"def link(self) -> Optional[str]:\n return pulumi.get(self, \"link\")",
"def _get_self_record(self, record: ... | [
"0.6749376",
"0.6332646",
"0.6332646",
"0.62515604",
"0.61730146",
"0.61730146",
"0.61730146",
"0.6066266",
"0.60131997",
"0.5963378",
"0.5962121",
"0.5958353",
"0.59456277",
"0.589322",
"0.5848187",
"0.58002985",
"0.5758175",
"0.5740583",
"0.5740583",
"0.5739168",
"0.5739168... | 0.71646607 | 0 |
Create a new cell from a Cell protobuf. | def from_pb(cls, cell_pb):
timestamp = _datetime_from_microseconds(cell_pb.timestamp_micros)
if cell_pb.labels:
return cls(cell_pb.value, timestamp, labels=cell_pb.labels)
else:
return cls(cell_pb.value, timestamp) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_cell(self, cid):\n self.cells[cid] = Cell()",
"def reproduce(self, id, position, partner):\n return Cell(id, position, self, partner)",
"def _create_cell(self,row_number,cell_number):\n cell = Cell(self)\n cell.x = cell_number * self.cell_width\n cell.y = row_numbe... | [
"0.6069733",
"0.59923977",
"0.591453",
"0.5743067",
"0.57002413",
"0.5664882",
"0.56352407",
"0.56330913",
"0.5609407",
"0.5444072",
"0.54251987",
"0.5407165",
"0.53757244",
"0.53634584",
"0.5359123",
"0.53427815",
"0.534006",
"0.5338059",
"0.5290304",
"0.52515936",
"0.525070... | 0.7500258 | 0 |
Append bytes from a new chunk to value. | def append_value(self, value):
self.value += value | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def append_bytes(self, data):\n\n if self.index != 7:\n self.buf.append(self.byte)\n self.byte = 0\n self.index = 7\n\n self.buf.extend(data)",
"def add_chunk(self, chunk):\n self.chunkbuffer.appendleft(chunk)",
"def add_byte(self, newbyte):\n self._... | [
"0.6965538",
"0.6886509",
"0.6466157",
"0.6369547",
"0.63468874",
"0.63018787",
"0.61934674",
"0.6191349",
"0.61861724",
"0.6181847",
"0.6159716",
"0.61312646",
"0.6124018",
"0.6061957",
"0.5985089",
"0.5908056",
"0.5903064",
"0.58985186",
"0.58978224",
"0.58650523",
"0.58631... | 0.63629705 | 4 |
Convert the cells to a dictionary. This is intended to be used with HappyBase, so the column family and | def to_dict(self):
result = {}
for column_family_id, columns in six.iteritems(self._cells):
for column_qual, cells in six.iteritems(columns):
key = (_to_bytes(column_family_id) + b':' +
_to_bytes(column_qual))
result[key] = cells
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def as_dict(self) -> Dict[str, Any]:\n return {\n column_title: cell.get_value()\n for column_title, cell in self.column_title_to_cell.items()\n }",
"def as_dict(self) -> Dict[str, Any]:\n return {\n column_title: cell.value\n for column_title, cel... | [
"0.76013017",
"0.75878423",
"0.71978664",
"0.69413537",
"0.66823757",
"0.6574558",
"0.643032",
"0.64155895",
"0.6379977",
"0.6318955",
"0.6313105",
"0.6252503",
"0.6244445",
"0.62411374",
"0.61758727",
"0.61758727",
"0.61758727",
"0.61758727",
"0.61758727",
"0.61635846",
"0.6... | 0.79329205 | 0 |
Property returning all the cells accumulated on this partial row. | def cells(self):
return copy.deepcopy(self._cells) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cells_total(self):\n return self._inv.get(\"cells\", len(self))",
"def get_total_cells(self):\n return self._get(\"cells\")",
"def cells(self):\n return self.container['cells']",
"def cells(self):\n return chain.from_iterable(self.cols)",
"def cells(self):\r\n return ... | [
"0.7329604",
"0.72963184",
"0.7285541",
"0.71675426",
"0.70034677",
"0.6740002",
"0.6697525",
"0.6685098",
"0.6658701",
"0.66584843",
"0.653525",
"0.6513235",
"0.6502038",
"0.6449473",
"0.6402963",
"0.63210136",
"0.62875944",
"0.6282429",
"0.6233849",
"0.61757165",
"0.6172168... | 0.69514596 | 5 |
Getter for the current (partial) row's key. | def row_key(self):
return self._row_key | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __key__(self) -> Tuple[int, int]:\n return self.col, self.row",
"def get_key(self) -> int:\n return self.__key",
"def get_key(self) -> int:\n return self.key",
"def get_key(self):\n return self.key",
"def get_key(self):\n return self.key",
"def key(self):\n r... | [
"0.72316724",
"0.72159064",
"0.7207303",
"0.7157399",
"0.7157399",
"0.71138483",
"0.7061789",
"0.7047705",
"0.6999932",
"0.6988818",
"0.6988818",
"0.6988818",
"0.6988818",
"0.6960423",
"0.6876054",
"0.683839",
"0.68287086",
"0.6781018",
"0.6758112",
"0.67410135",
"0.6730147",... | 0.84983855 | 0 |
Property returning all rows accumulated from the stream. | def rows(self):
# NOTE: To avoid duplicating large objects, this is just the
# mutable private data.
return self._rows | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def fetchall(self):\n\n self._check_executed()\n\n if self._query_id == -1:\n msg = \"query didn't result in a resultset\"\n self._exception_handler(ProgrammingError, msg)\n\n result = self._rows[self.rownumber - self._offset :]\n self.rownumber = len(self._r... | [
"0.6823442",
"0.64770746",
"0.63634026",
"0.62843436",
"0.6277957",
"0.62755823",
"0.6224927",
"0.6217208",
"0.61437726",
"0.61001796",
"0.6064008",
"0.60063374",
"0.5994555",
"0.5987653",
"0.59443873",
"0.5943947",
"0.59357786",
"0.5925868",
"0.5912474",
"0.58995414",
"0.589... | 0.6456861 | 2 |
Cancels the iterator, closing the stream. | def cancel(self):
self._response_iterator.cancel() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def close(self):\n if callable(getattr(self._file, 'close', None)):\n self._iterator.close()\n self._iterator = None\n self._unconsumed = None\n self.closed = True",
"def close(self):\n if self.closed:\n return\n self._stream.close()\n self._stream = None",
... | [
"0.67333686",
"0.63217324",
"0.6200361",
"0.6189285",
"0.60646605",
"0.5990257",
"0.59821737",
"0.5979769",
"0.5914633",
"0.58941954",
"0.58596677",
"0.58370185",
"0.5811813",
"0.5810032",
"0.5777921",
"0.5777921",
"0.57457614",
"0.57253283",
"0.5688793",
"0.56884354",
"0.568... | 0.67483526 | 0 |
Consume the next ``ReadRowsResponse`` from the stream. Parse the response and its chunks into a new/existing row in | def consume_next(self):
response = six.next(self._response_iterator)
self._counter += 1
if self._last_scanned_row_key is None: # first response
if response.last_scanned_row_key:
raise InvalidReadRowsResponse()
self._last_scanned_row_key = response.last_scan... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def _receive_response_body(\n self, request: Request, stream_id: int\n ) -> typing.AsyncIterator[bytes]:\n while True:\n event = await self._receive_stream_event(request, stream_id)\n if isinstance(event, h2.events.DataReceived):\n amount = event.flow_con... | [
"0.61128515",
"0.6106053",
"0.5749937",
"0.5664724",
"0.562037",
"0.5559969",
"0.55483514",
"0.55231017",
"0.551602",
"0.551602",
"0.5493233",
"0.54856974",
"0.5481049",
"0.54711795",
"0.5399032",
"0.53882605",
"0.5361007",
"0.53610015",
"0.53456414",
"0.5320742",
"0.52846736... | 0.80644053 | 0 |
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