%s</tasks>\\\" % xml\\n\\n # what are we gonna call this file?\\n seconds = str(int(time.time()))\\n filename = \\\"%s_%s.xml\\\" % (helpername.replace(\\\" \\\", \\\"\\\").replace(\\\"/\\\", \\\"\\\"), seconds)\\n with open(os.path.join(catoconfig.CONFIG[\\\"tmpdir\\\"], filename), 'w') as f_out:\\n if not f_out:\\n uiCommon.log(\\\"ERROR: unable to write task export file.\\\")\\n f_out.write(xml)\\n\\n return json.dumps({\\\"export_file\\\": filename})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2547af7bc61856c63e02ec6670921396\",\n \"score\": \"0.50806886\",\n \"text\": \"def write_samples_tsv(cls, samp_ids: list) -> None:\\n samp_tab = \\\"view_samples_ena\\\"\\n samples = Samples.fetch_entries(samp_tab, sample_ids=samp_ids)\\n EnaTsvSamples.write(samples)\\n with ZipFile(cls.get_tempfile(), \\\"w\\\") as zipObj:\\n zipObj.write(EnaTsvSamples.get_tempfile(), EnaTsvSamples.filename)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ba824ed06d89054b1374786c534e9624\",\n \"score\": \"0.5073121\",\n \"text\": \"def export(user: str, start: date, end: date, output_dir: Path) -> None:\\n filename = f\\\"{start}-{end}_usage.csv\\\"\\n\\n df = fetch(user, start, end)\\n df.to_csv(output_dir/filename, sep=DELIMITER, index=False)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"826a35bc2f4690dc75b563cd5b619a80\",\n \"score\": \"0.5064271\",\n \"text\": \"def contact_export_batch(session, model_name, backend_id, domain=None, fields=None, delay=False, **kwargs):\\n connector_env = get_environment(session, model_name, backend_id)\\n\\n # Get the exporter connector unit\\n batch_exporter = connector_env.get_connector_unit(ContactBatchExporter)\\n\\n # Start the batch export\\n batch_exporter.batch_run(domain=domain, fields=fields, delay=delay, **kwargs)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f37f742fc31f4ab7a6b8fbb92993bebb\",\n \"score\": \"0.5061552\",\n \"text\": \"def export(gen, filepath):\\n meta = {} # to be exported as JSON at the end\\n meta['descriptors'] = defaultdict(list) # map stream_name to descriptors\\n files = {} # map descriptor uid to file handle of CSV file\\n desc_counters = defaultdict(itertools.count)\\n try:\\n for name, doc in gen:\\n if name == 'start':\\n if 'start' in meta:\\n raise RuntimeError(\\\"This exporter expects documents from \\\"\\n \\\"one run only.\\\")\\n meta['start'] = doc\\n elif name == 'stop':\\n meta['stop'] = doc\\n elif name == 'descriptor':\\n stream_name = doc.get('name')\\n meta['descriptors'][stream_name].append(doc)\\n filepath_ = f\\\"{filepath}_{stream_name}_{next(desc_counters[doc['uid']])}.csv\\\"\\n files[doc['uid']] = open(filepath_, 'w+')\\n elif name == 'event':\\n row = ', '.join(map(str, (doc['time'], *doc['data'].values())))\\n f = files[doc['descriptor']]\\n f.write(f'{row}\\\\n')\\n finally:\\n for f in files.values():\\n f.close()\\n with open(f\\\"{filepath}_meta.json\\\", 'w') as f:\\n json.dump(meta, f)\\n return (f.name,) + tuple(f.name for f in files.values())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e9714862822c02586cb532e44a4c27ea\",\n \"score\": \"0.5058238\",\n \"text\": \"def _export_model_csv(self, inference_writer, gpu_metrics_writer,\\n column_separator):\\n\\n gpu_table = self._result_tables[self.model_gpu_table_key]\\n non_gpu_table = self._result_tables[self.model_inference_table_key]\\n\\n self._write_result(table=gpu_table,\\n writer=gpu_metrics_writer,\\n column_separator=column_separator,\\n ignore_widths=True,\\n include_title=False)\\n\\n self._write_result(table=non_gpu_table,\\n writer=inference_writer,\\n column_separator=column_separator,\\n ignore_widths=True,\\n include_title=False)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f5f2a57d88d321fd5d903a363fd0f454\",\n \"score\": \"0.5056593\",\n \"text\": \"def test_generate_telemetry(run_generate, summary_store: SummaryStore):\\n run_generate(\\\"ls8_satellite_telemetry_data\\\")\\n\\n _expect_values(\\n summary_store.get(\\\"ls8_satellite_telemetry_data\\\"),\\n dataset_count=1199,\\n footprint_count=1199,\\n time_range=Range(\\n begin=datetime(2016, 1, 1, 0, 0, tzinfo=DEFAULT_TZ),\\n end=datetime(2018, 1, 1, 0, 0, tzinfo=DEFAULT_TZ),\\n ),\\n region_dataset_counts={\\n \\\"91\\\": 56,\\n \\\"92\\\": 56,\\n \\\"93\\\": 56,\\n \\\"90\\\": 51,\\n \\\"95\\\": 47,\\n \\\"94\\\": 45,\\n \\\"96\\\": 44,\\n \\\"101\\\": 43,\\n \\\"98\\\": 43,\\n \\\"100\\\": 42,\\n \\\"105\\\": 42,\\n \\\"111\\\": 42,\\n \\\"99\\\": 42,\\n \\\"104\\\": 41,\\n \\\"110\\\": 41,\\n \\\"112\\\": 41,\\n \\\"103\\\": 40,\\n \\\"107\\\": 40,\\n \\\"108\\\": 40,\\n \\\"109\\\": 40,\\n \\\"89\\\": 40,\\n \\\"97\\\": 40,\\n \\\"113\\\": 39,\\n \\\"102\\\": 37,\\n \\\"106\\\": 36,\\n \\\"114\\\": 32,\\n \\\"116\\\": 29,\\n \\\"115\\\": 27,\\n \\\"88\\\": 27,\\n },\\n newest_creation_time=datetime(2017, 12, 31, 3, 38, 43, tzinfo=tzutc()),\\n timeline_period=\\\"month\\\",\\n timeline_count=24,\\n crses={\\\"EPSG:4326\\\"},\\n size_bytes=10333203380934,\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ca57c3ab98fd6ad5c4005f8cbb549a59\",\n \"score\": \"0.50532097\",\n \"text\": \"def export_dataset(self, filename=None):\\n\\n file_ac = FileAccess(storage=\\\"export\\\", resource_id=self.id, cloud_parms=self._cloud_parms)\\n if not filename:\\n filename = self.id + \\\".dset\\\"\\n\\n self.load_all_images()\\n\\n export_data = {\\n \\\"export_version\\\": \\\"2\\\",\\n \\\"export_date\\\": datetime.datetime.now(),\\n \\\"dataset\\\": self.dataset_name,\\n \\\"dataset_id\\\": self.id,\\n \\\"num_examples\\\": len(self.examples),\\n \\\"images_list\\\": list(self.images.keys())\\n }\\n\\n # Dataset.export_to_file(filename)\\n Dataset.export_to_hdf5(export_data, self.parms, self.examples, self.images, filename, self.id)\\n if self._cloud_parms is not None:\\n file_ac.sync_files(\\n file_list=[filename],\\n origin=\\\"local\\\"\\n )\\n log.info(f\\\"Dataset exported to file {len(self.examples)} examples\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b4c21123e7ba99f5cd5e538e0170b34a\",\n \"score\": \"0.50523907\",\n \"text\": \"def write_experiments_tsv(cls, samp_ids: list) -> None:\\n samp_tab = \\\"view_samples_ena_experiment\\\"\\n run_samples = Samples.fetch_entries(samp_tab, sample_ids=samp_ids)\\n EnaTsvExperiment.write(run_samples)\\n with ZipFile(cls.get_tempfile(), \\\"a\\\") as zipObj:\\n zipObj.write(EnaTsvExperiment.get_tempfile(),\\n EnaTsvExperiment.filename)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"83655634622707ae18a48be2116daeac\",\n \"score\": \"0.5049891\",\n \"text\": \"def dump_data(filename, values, cols=None):\\n if filename:\\n outfile = open(filename, 'w')\\n else:\\n outfile = sys.stdout\\n\\n res_writer = csv.writer(outfile)\\n if cols:\\n for r in values:\\n row = [r[i] for i in cols]\\n res_writer.writerow(row)\\n else:\\n res_writer.writerows(values)\\n outfile.write('\\\\n')\\n\\n if filename:\\n outfile.close()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"713a421f4a20066fcba44a17b0c8e236\",\n \"score\": \"0.50357884\",\n \"text\": \"def output_csv_data(self, top = False, summary = False):\\n output_dfs, output_names = self.get_csv_data(top, summary)\\n for index, df in enumerate(output_dfs):\\n name = output_names[index]\\n df.to_csv(name+\\\".csv\\\")\\n\\n print \\\"Wrote: \\\"+name+\\\".csv\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"01ffe913ce229269a67a7874a5c35a85\",\n \"score\": \"0.50271004\",\n \"text\": \"def write_batch_arrow(self):\\n data = list(self.chunk())\\n data = zip(*data)\\n arrays = []\\n for i, column in enumerate(data):\\n arrays.append(pa.array(column, self.pa_schema[i].type))\\n\\n batch = pa.RecordBatch.from_arrays(arrays, names=self.pa_schema.names)\\n return batch\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e9fe9033dcda5406736acd335960a780\",\n \"score\": \"0.5026336\",\n \"text\": \"def default_export_aggregated_timers(aggregated_report):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"79b9358dc9f6e7f59d7085b035c51971\",\n \"score\": \"0.5025023\",\n \"text\": \"def export(self, spans: typing.Sequence[ReadableSpan]) -> SpanExportResult:\\n if self._stopped:\\n return SpanExportResult.FAILURE\\n with self._lock:\\n self._finished_spans.extend(spans)\\n return SpanExportResult.SUCCESS\",\n \"title\": \"\"\n },\n {\n \"docid\": \"447e4692e1e6b5fe1fd2eec524dd2e49\",\n \"score\": \"0.5025004\",\n \"text\": \"def export_tables():\\n with DatabaseAPI() as db_obj:\\n for table in Base.metadata.tables.keys():\\n export_table(db_obj, to_class(table))\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":379,"cells":{"query_id":{"kind":"string","value":"dcd5cfeec1176c6ac0717df07bad0e9a"},"query":{"kind":"string","value":"Sends the help message"},"positive_passages":{"kind":"list like","value":[{"docid":"6a6dad1f3b2ffea5792f1b3258f003ef","score":"0.0","text":"async def help(self, ctx):\n\n await ctx.send('Type `>run` and python script to run python')","title":""}],"string":"[\n {\n \"docid\": \"6a6dad1f3b2ffea5792f1b3258f003ef\",\n \"score\": \"0.0\",\n \"text\": \"async def help(self, ctx):\\n\\n await ctx.send('Type `>run` and python script to run python')\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"dc0ada3b234879429e494800a76a63e9","score":"0.8490778","text":"def do_help(self, *args):\n self.stdout.write(HELP_MESSAGE)","title":""},{"docid":"d47fb2e6b3684f66a3ede28374e5bee6","score":"0.81821424","text":"def do_help(self):\n self.send_bot_msg('*Commands:* https://github.com/TinyChat/Tinychat-Bot/wiki/', self.user.nick)","title":""},{"docid":"c802229b407fbf9827caf8e8703c7bd1","score":"0.806487","text":"def _help(bot, update):\n help_txt = \"Hey! This is a help text.\"\n bot.send_message(chat_id=update.message.chat_id, text=help_txt)","title":""},{"docid":"f283d24055d60b06f784efd9f9c903cb","score":"0.8044507","text":"async def help(self, args, mobj):\n output = \"Hey there! Thank you for using the help functionality.\\n\\n\"\n output += \"##############################################################################\\n\"\n output += \"# Don't forget to run the more server related commands in the actual server! #\\n\"\n output += \"##############################################################################\\n\\n\"\n output += \"Here are the available commands:\\n\\n\"\n\n for c in [f\"{k}\" for k in self.ACTIONS.keys()]:\n output += f\" {c}\\n\"\n\n output += \"\\n For more info on each command, use '!command help'\"\n return await self.message(mobj.author, self.pre_text(output))","title":""},{"docid":"35b94caca6a502f03b7f70978f2a6d77","score":"0.80123097","text":"def help_command(update, context):\n update.message.reply_text('Help!')","title":""},{"docid":"cddc4f86384bdf22dc68059aead373cd","score":"0.79230416","text":"def help(update, context):\n update.message.reply_text(_(\"Help\"))","title":""},{"docid":"78c687a3a60b7933d78533fd979fd53c","score":"0.7887985","text":"def cmd_help(self, params):\n self.help()","title":""},{"docid":"726c5202c0620f1176ef4f949ff8cf7a","score":"0.7876978","text":"def do_help(self, inputs):\n cmd.Cmd.do_help(self, inputs)","title":""},{"docid":"7788117b224f2fae21fb4f9fa3c97782","score":"0.7855003","text":"async def help_command(message: types.Message):\n await message.reply(msg.help_message)","title":""},{"docid":"cf93a3c658b3ee40f14e35925ff53214","score":"0.7831273","text":"def help_help(self):\n\n self.stdout.write(self.help_help.__doc__ + \"\\n\")","title":""},{"docid":"9b269d5944fcb5cc7ce44c53bebf0ede","score":"0.78282434","text":"def help_command(self):\n text = _(\"User commands:\\n\") + \\\n _(\"r N - run the simulation for N cycles\\n\") + \\\n _(\"c N - continue the simulation for N cycles\\n\") + \\\n _(\"s X N - set switch X to N (0 or 1)\\n\") + \\\n _(\"m X - set a monitor on signal X\\n\") + \\\n _(\"z X - zap the monitor on signal X\\n\") + \\\n _(\"h - help (this command)\\n\") + \\\n _(\"q - quit the program\")\n wx.MessageBox(text, _(\"Help on Commands\"), wx.ICON_INFORMATION | wx.OK)","title":""},{"docid":"6d7c7054688225af9261c5a56cb0adb6","score":"0.77996266","text":"def help(update, context):\n update.message.reply_text('Help!')\n #TODO","title":""},{"docid":"378551e33972ddd9c26d985dc80898fc","score":"0.77729344","text":"def do_help(self, args):\n cmd.Cmd.do_help(self, args)","title":""},{"docid":"031d47ae0b747df41a784ede6fd540c4","score":"0.77707136","text":"def help_command(update: Update, context: CallbackContext) -> None:\n update.message.reply_text('Help!')","title":""},{"docid":"4f89969c8b3e5a12c9fb2c214dc46893","score":"0.776831","text":"def help_command(update: Update, context: CallbackContext) -> None:\n update.message.reply_text('Helping you helping you.')","title":""},{"docid":"4df6f586861ada3181afe2abe004b452","score":"0.772737","text":"def help(bot, update):\r\n update.message.reply_text('Help!')","title":""},{"docid":"1286ae6941bf742ad078db7b7c4f271a","score":"0.7699966","text":"def helpMsg(actor):\n\tprint(\"Avaiable options: get|help|exit|list_neighbors|list_files\")","title":""},{"docid":"cc13d91d57e8fd854c402fa2c3c699ac","score":"0.76746005","text":"def help(update: Update, context: CallbackContext) -> None:\n s = \"\"\n for i in myCommands:\n s += '/'+myCommands[i]+\" - \"+i+\"\\n\"\n update.message.reply_text('Help!\\n' + s)","title":""},{"docid":"87a22a579e53fd6f6fa10f12c2a4c121","score":"0.7650296","text":"def help(server, data):\r\n\r\n # Construct the help message's header\r\n message = \"Here are the available commands:\\r\\n\"\r\n\r\n # Construct the content\r\n for command in server.commands.keys():\r\n message = message + \" - \" + command + \"\\r\\n\"\r\n\r\n # Add further help info\r\n message = message + \"To learn more about each command, type <command> help. \" + \"\\r\\n\"\r\n message = message + \"To add arguments to a command, type <command> <argument1> <argument2> (...)\" + \"\\r\\n\"\r\n\r\n # Send the prepared message to the client\r\n server.send(message)","title":""},{"docid":"c31100003ecf78d47fc1db90674a7b8d","score":"0.7593971","text":"def do_help():\r\n\r\n global STATE\r\n STATE = STATE_START\r\n attributes = {\"state\":globals()['STATE']}\r\n return response(attributes, response_plain_text(HELP_MESSAGE, False))","title":""},{"docid":"d541374ce4a00a7473d2ca5f1d010a6f","score":"0.7584389","text":"def help(self, message, args):\n raise NotImplementedError('This method must be implemented')","title":""},{"docid":"b8b99ac44eacf797ffb7ea375b8a1b38","score":"0.75822437","text":"def do_help(self, args):\n ## The only reason to define this method is for the help text in the doc string\n cmd.Cmd.do_help(self, args)","title":""},{"docid":"c654bc6719ec6389c5bc3b0f6dc88156","score":"0.757944","text":"def do_help(self, line):\n enterHelp(self.client)","title":""},{"docid":"3a507cc7db8915be98355fe38230588b","score":"0.75738716","text":"def help():","title":""},{"docid":"b2a73f5351231ae885d74ce59bdb957e","score":"0.7564036","text":"def show_help(bot, update):\n bot.send_message(chat_id=update.message.chat_id,\n text=MESSAGES['HELP'],\n parse_mode=ParseMode.HTML)","title":""},{"docid":"723ff42dfdc99e815b145a9edc2ae69e","score":"0.7558429","text":"def help(bot, update):\n bot.sendMessage(update.message.chat_id, text='Help!')","title":""},{"docid":"40b22538455f87cefa1a8d4f66c4fd04","score":"0.7539667","text":"def do_help(self, args):\n # The only reason to define this method is for the help text in the doc\n # string\n cmd.Cmd.do_help(self, args)","title":""},{"docid":"e9a787cf9112c25e6fe3f453db0199fb","score":"0.7531621","text":"async def help(ctx):\n await server_bot.help(ctx)","title":""},{"docid":"99c2783978243e651e4251be3fd10edc","score":"0.75235754","text":"def do_main_help(self, data):\n msg = \"Hi, I'm a bot! I have {0} commands loaded: {1}. You can get help for any command with '!help <command>'.\"\n cmnds = sorted([cmnd.name for cmnd in self.bot.commands])\n msg = msg.format(len(cmnds), ', '.join(cmnds))\n self.reply(data, msg)","title":""},{"docid":"3ef15081b0229e960c2546bddebf77a3","score":"0.75202906","text":"def do_help(self, args):\n # The only reason to define this method\n # is for the help text in the doc string\n cmd.Cmd.do_help(self, args)","title":""},{"docid":"6088e28731da3f68f6c5691834839f69","score":"0.7514919","text":"def help():\n return help_text","title":""},{"docid":"7c12107736c0a8bef614f88f99e04e2d","score":"0.7506989","text":"def help(update, context):\n update.message.reply_text('Help!')\n time.sleep(3)\n update.message.reply_text('Just kidding! HAHAHAHAHAHA')\n update.message.reply_text('''Add triggers by doing: /add <trigger>:<respons>\nRemove triggers by doing: /delete <trigger>\nGet all triggers by doing: /triggers\\\n ''')","title":""},{"docid":"ad16aa42b7001533c46c00b6e26f0045","score":"0.7504356","text":"def msg_help(self, text):\n if type(self).help_more:\n usemore = True\n\n if self.session.protocol_key in (\"websocket\", \"ajax/comet\"):\n try:\n options = self.player.db._saved_webclient_options\n if options and options[\"helppopup\"]:\n usemore = False\n except KeyError:\n pass\n\n if usemore:\n evmore.msg(self.caller, text)\n return\n\n self.msg((text, {\"type\": \"help\"}))","title":""},{"docid":"e84239e0b10fdbc1c4506ffa1d6314a0","score":"0.7500062","text":"def do_help():\n\n global STATE\n STATE = STATE_START\n # attributes = {\"state\":globals()['STATE']}\n return response_plain_text_ga(HELP_MESSAGE, True)","title":""},{"docid":"e69aa82c0cfab47788efab973ac20334","score":"0.74996126","text":"async def help_handler(msg: types.Message) -> None:\n help_text = \"This is a help text for testing\"\n await msg.answer(help_text)\n await msg.reply(\"Son of a bitch, hay que decirlo mas\")","title":""},{"docid":"073e149b82a1d815b030a9d347a1b0d3","score":"0.7447619","text":"async def send_command_help(self, command: commands.Command):\n if command.name == 'help':\n desc = Help.help\n else:\n desc = command.help\n desc = desc.replace('{{pre}}', self.context.prefix)\n title = self.get_command_signature(command)\n e = discord.Embed(title=title, color=colours.HELP, description=desc)\n await self.get_destination().send(embed=e)","title":""},{"docid":"d9549a001d995a662f5092ac35c6fc3c","score":"0.74306446","text":"def send_help_message(self, channel):\n\n self.logger.debug('Sending help message.')\n\n message = \"\"\"There are a few things I can do:\n\nIf you say `slack`, or `master`, I will speak using everything I have\nlearned from slack. This is my default behaviour.\n\nIf you say `#channel`, I will speak using everything I have learned\nfrom that channel.\n\nIf you say `@user`, I will speak using everything I have learned from\nthat user.\n\nIf you say `$external source`, I will speak using everything I have\nlearned from that source.\n\nHint: You can combine multiple commands.\n \"\"\"\n\n self.send_message(channel, message)","title":""},{"docid":"59da4d65da34e130bbdff150345ef626","score":"0.7430576","text":"def help(bot, update):\r\n update.message.reply_text('Hi, I am here to help you!')\r\n update.message.reply_text('To start, you should call'\r\n ' start command with two args:')\r\n update.message.reply_text('Url to wiki and depth of search')\r\n update.message.reply_text('Bot only works with English wiki for now!')","title":""},{"docid":"5bbee8c7e69151b99a54617ff528b80f","score":"0.7422377","text":"def help(self):\n self.help_message.place(x=self.absx + 10, y=self.absy + 10)","title":""},{"docid":"9d4a9d1510d808b88b8f46fd2347fc36","score":"0.7418295","text":"def handle_help(self, event: Event) -> None:\n content = scripts.get_help()\n\n return self.reply_line(event, content)","title":""},{"docid":"6d049507aebd874542210f03c46e4531","score":"0.74178636","text":"async def help(self, context, user : discord.Member=None):\n f = open(helptxt, 'r')\n general=f.read()\n await context.channel.send(general)\n f.close()","title":""},{"docid":"4f7fcbf9fc063295766fd318348c7605","score":"0.7397008","text":"async def help(ctx):\n\n print(f\"{ctx.message.author}: {ctx.message.content}\")\n await ctx.message.delete()\n await cdef.print_help_message(ctx)","title":""},{"docid":"a17f2a88519fd1914f6a09d564bd8dbe","score":"0.73854035","text":"async def help(ctx):\n embed = discord.Embed(title=\"Battle Ships Bot\",\n description=\"a bot the lets you play the Battle \"\n \"Ships game in a DM channel in Discord\",\n color=0xeee657)\n\n embed.add_field(name=\"^start_game\", value=\"bot creates a dm channel and \"\n \"starts a battle ship game\",\n inline=False)\n embed.add_field(name=\"^shoot X Y\", value=\"Bot shoots the given \"\n \"coordinates\", inline=False)\n embed.add_field(name=\"^stats\", value=\"Gives stats about current game, \"\n \"number of turns, hits and misses\",\n inline=False)\n embed.add_field(name=\"^surrender\", value=\"surrenders and stops a current \"\n \"game session\", inline=False)\n embed.add_field(name=\"^info\", value=\"Gives a little info about the bot\",\n inline=False)\n embed.add_field(name=\"^help\", value=\"Gives this message\", inline=False)\n\n await ctx.send(embed=embed)","title":""},{"docid":"8062de968f18b2702982e6c61f67913c","score":"0.7379159","text":"def help(update, context):\n user = update.message.from_user\n \n context.bot.send_message(text=constants.HELP_MESSAGE,\n chat_id=user.id,\n parse_mode=ParseMode.HTML)","title":""},{"docid":"d1ce256bda0e0fab11dcc029e12232fb","score":"0.7372104","text":"def chat_help(update: Update, context: CallbackContext):\n update.message.reply_text(HELP_MESSAGE)","title":""},{"docid":"6ad19320a90921d80d9cb2b012106b64","score":"0.73642117","text":"def cb_help(self, obj):\n display_help(webpage = WIKI_HELP_PAGE, section = WIKI_HELP_SEC)","title":""},{"docid":"902ba76d51efa1fcc49c9a33cb8112c2","score":"0.73545146","text":"def help(self):\n pass","title":""},{"docid":"3a3ae010c4c1282c6e2f29ec82de1d75","score":"0.73493034","text":"def callhelp(self):\n self.parser.print_help()","title":""},{"docid":"6b9486437f15f6e10599769045369610","score":"0.7306459","text":"def help(update, context):\n #update.message.reply_text(\"Доступные команды: \\n\\n/id\")\n update.message.reply_text(\"Прости, лично я пока ничем не готов помочь...\")","title":""},{"docid":"486000c1422f79eacf699430b9c0db7b","score":"0.73041505","text":"def help(update, context):\n update.message.reply_text('cazzo vuoi io non ti aiuto')","title":""},{"docid":"4448dad758c1e8cb9a2f4416dee83436","score":"0.7293747","text":"def OnHelp( self, evt ):\n wx.MessageBox( \"Documentation available at\\nhttp://ctrax.sourceforge.net\", \"Help\" )","title":""},{"docid":"304570b1bcf0b535b63d47da99066933","score":"0.7291669","text":"async def write(self, ctx):\n await self.bot.send_cmd_help(ctx)","title":""},{"docid":"55decaecaf2b4b4b70a23f29ab08ecc6","score":"0.72851753","text":"def help_(self):\n pass","title":""},{"docid":"abf8e0ce9c88791fb70fe0cca953d363","score":"0.7280757","text":"def help(self, **kwds):","title":""},{"docid":"260db9140088250b6bd7a365288b2221","score":"0.7271429","text":"def help_command(chat_id, text):\n logger.info('COMMAND {}: chat_id={}'.format(text, chat_id))\n get_bot().send_message(chat_id=chat_id, text='\\n'.join(tr('help', chat_id)))","title":""},{"docid":"53956d664d4c78758c5be0fbfad23ae9","score":"0.72584754","text":"async def help(client, message, **kwargs):\n commandName = kwargs.get('command')\n if commandName:\n command = cmds.find(commandName)\n if command:\n context_cache = {'db_server': db.get_server(message.server) if message.server else None}\n context_cache = cmds.get_context_cache_update(context_cache, message)\n validated, exc = await command.validate_context(client, message, [], context_cache)\n if validated or isinstance(exc, MissingParameters):\n await client.send_message(message.channel, command.pretty_print())\n else:\n commandsStr = []\n async for c in AuthorizedCommandsWrapper(client, message):\n commandsStr.append(c)\n await client.send_message(message.channel, T_HelpGlobal.format('\\n '.join(commandsStr)))","title":""},{"docid":"100455fbcb2a0247ffce4b72acd63cbb","score":"0.7258179","text":"def cmd_help( self, command, params, event, received=\"channel\" ):\n\n if len( params ) < 1:\n self.send_message( event.source, \"List of commands:\" )\n for cmd in self.commands:\n self.send_message( event.source, format.color( \"## \", format.LIME_GREEN ) + '{:<20} {}'.format( *self.commands[ cmd ][1].__doc__.format( format.bold( format_command( cmd, received ) ) ).splitlines()[0].strip().split( \"!X!\", 1 ) ) ) # split and justify\n return\n if params[0].lower() in self.commands:\n self.send_message( event.source, \"Usage info for command {0}:\".format( format.bold( params[0] ) ) )\n for line in self.commands[ params[0].lower() ][1].__doc__.format( *[ format.bold( format_command( c, received ) ) for c in params ] ).splitlines():\n self.send_message( event.source, format.color( \"## \", format.LIME_GREEN ) + '{:<35} {}'.format( *line.strip().split( \"!X!\", 1 ) ) ) # split and justify\n else:\n self.send_message( event.source, \"Unkown Command {0}.\".format( format.bold( params[0] ) ) )","title":""},{"docid":"92d848a72bae335023b22138a3d35af6","score":"0.7244817","text":"def show_help(update: Update, context: CallbackContext):\n update.message.reply_text(\"Help!\")\n log_context(context)","title":""},{"docid":"78f55633db05c3e85f0e175abef98f1d","score":"0.72430915","text":"def help(self, *args: Any, **kwargs: Any) -> None:\n print(self._help(*args))","title":""},{"docid":"9e3e1c48a28115d5364744716318e318","score":"0.7238084","text":"async def help(self, /, timeout: Optional[Union[float, Default]] = _default) -> str:\n await self._ehlo_or_helo_if_needed()\n\n response = await self.execute_command(b\"HELP\", timeout=timeout)\n if response.code not in (\n SMTPStatus.system_status_ok,\n SMTPStatus.help_message,\n SMTPStatus.completed,\n ):\n raise SMTPResponseException(response.code, response.message)\n\n return response.message","title":""},{"docid":"fbfdcd77467d42901dc8a10c54e53bdf","score":"0.7234989","text":"def help(update, context):\n update.message.reply_text('Bischd du dumm?')","title":""},{"docid":"16189a160af4e224d10999630669b8a5","score":"0.7222698","text":"async def handle_command_help(self, target, nick):\n help_msg = (\"Pump19 is run by Twisted Pear. \"\n \"Check {url} for a list of supported commands.\").format(\n url=COMMAND_URL)\n await self.client.privmsg(target, help_msg)","title":""},{"docid":"22eeab3319c36a80d8f876b16ce3c83e","score":"0.72175574","text":"def handle_help(self):\n print(\"Help not implemented yet for PyXtal!\")","title":""},{"docid":"0cf9372768ac0d709c5b908d49961589","score":"0.7214833","text":"def help_help(self):\n print \"List commands or print details about a command\"","title":""},{"docid":"243842f7f070518fbd1d39b11d879731","score":"0.7213134","text":"def help(update, context):\n help_text = get_help_text(is_telegram=True)\n update.message.reply_text(help_text)\n return","title":""},{"docid":"2904501c85c9a6f7a17c12c5515404b4","score":"0.7211631","text":"def __help_msg(self):\n return \"\"\"\\\nHelp:\n - /IGNORE \"\"\" + self.connection.get_nickname() + \"\"\" - Lets you stop reading the bot.\n\n You can send these commands in private message (PM) to \"\"\" + self.connection.get_nickname() + \"\"\":\n - !help - Show this help message.\n - !stats - Show some statistics.\n - !list - Show all feeds.\n - !last - Show last news published in all feeds.\n - !lastfeed <feedid> - Show last news published in a specific feed.\n\"\"\"","title":""},{"docid":"5beca3b23d6b0196b384730dd3f10ad7","score":"0.720753","text":"def help(self, mess, args):\n if not args:\n if self.__doc__:\n description = self.__doc__.strip()\n else:\n description = _('Available commands:')\n\n usage = sorted(['%s:\\t%s' % (name, (command.__doc__ or \\\n '(undocumented)').strip().split('\\n', 1)[0])\n for (name, command) in self.commands.iteritems() \\\n if name != 'help' \\\n and not command._jabberbot_command_hidden\n ])\n #usage = '\\n\\n' + '\\n\\n'.join(filter(None, [usage, self.MSG_HELP_TAIL]))\n usage = usage + [self.MSG_HELP_TAIL]\n else:\n description = ''\n if args in self.commands:\n usage = (self.commands[args].__doc__ or \\\n 'undocumented').strip()\n else:\n usage = [self.MSG_HELP_UNDEFINED_COMMAND]\n\n if isinstance(usage, str):\n usage = [usage]\n if isinstance(description, str):\n description = [description]\n\n # return [description] + usage\n self.send_simple_reply(mess, description + usage, True)","title":""},{"docid":"ffdc9fc8c453bbc9a6ba0f4a3171c076","score":"0.71776325","text":"def send_help(message):\n bot.send_message(message.chat.id, 'Hei, ' + message.from_user.first_name +\n '! Рад тебя видеть! Чем могу помочь?',\n reply_markup=config.keyboard(content.main_menu))","title":""},{"docid":"4453c93839d26b0d99a84a6569d6c56b","score":"0.7177051","text":"async def faq(self, ctx):\n await ctx.send_help(ctx.command)","title":""},{"docid":"260b0efcf7bfe425dabb95754ccf95c7","score":"0.717615","text":"def help(self, args):\n print('Various commands for couchpotato')\n print('run with --help for more information')","title":""},{"docid":"ab56972c5a82c239bd5d55933485240b","score":"0.71744657","text":"def do_command_help(self, data):\n target = data.args[0]\n\n for command in self.bot.commands:\n if command.name == target or target in command.commands:\n if command.__doc__:\n doc = command.__doc__.replace(\"\\n\", \"\")\n doc = re.sub(r\"\\s\\s+\", \" \", doc)\n msg = 'Help for command \\x0303{0}\\x0F: \"{1}\"'\n self.reply(data, msg.format(target, doc))\n return\n\n msg = \"Sorry, no help for \\x0303{0}\\x0F.\".format(target)\n self.reply(data, msg)","title":""},{"docid":"10ef278124e799cc68a952e9a6630415","score":"0.716986","text":"def help(cls, task):\n executor = task.executor\n\n if cls.__doc__:\n out = fmt.FormatList(executor)\n out.add(fmt.Header(f\"Help: {cls.name}\"))\n out.add(fmt.Line(cls.__doc__))\n out.add(fmt.Footer())\n executor.send(out)\n else:\n executor.msg(text=\"Help is not implemented for this command.\")","title":""},{"docid":"d64c3ba2e1dde5452d1b373791760272","score":"0.7154695","text":"async def show_bot_help(self):\n\n self.embed.title = 'Using the **C02* bot'\n self.embed.description = 'Hello! Welcome to the help page.'\n self.embed.clear_fields()\n\n entries = (\n ('<argument>', 'This means the argument is __**required**__.'),\n ('[argument]', 'This means the argument is __**optional**__.'),\n ('[A|B]', 'This means the it can be __**either A or B**__.'),\n ('[argument...]', 'This means you can have multiple arguments.\\n__**You do not type in the brackets!**__')\n )\n\n for name, value in entries:\n self.embed.add_field(name=name, value=value, inline=False)\n\n self.embed.set_footer(text=f'We were on page {self.current_page} before this message.')\n await self.message.edit(embed=self.embed)\n\n async def go_back_to_current_page():\n await asyncio.sleep(30.0)\n await self.show_current_page()\n\n self.bot.loop.create_task(go_back_to_current_page())","title":""},{"docid":"c33808163f19aa079d9ffe299507dc38","score":"0.7152405","text":"def do_help(self, arg):\n if arg:\n helper = [n[5:] for n in self.get_names()\n if n.startswith('help_' + arg)]\n if len(helper) == 0:\n self.stdout.write('*** Unknown command: %s\\n' % arg)\n return\n elif len(helper) > 1:\n self.stdout.write((\n \"*** {} is a shorcut to several commands\\n\"\n \" Please give more characters for disambiguation\"\n ).format(cmd))\n return\n else:\n arg = helper[0]\n cmd.Cmd.do_help(self, arg)","title":""},{"docid":"3876464481a92f00979051f50995d2b6","score":"0.7133162","text":"def help(bot, update):\n update.message.reply_text('These are our commands:\\n/start: to roll with us'\n '\\n/help: to get to this selection'\n '\\n/add_event: to add an event you want to visit'\n '\\n/del_event: to remove an event you dont want to visit any more, or youve visited it already'\n '\\n/list: to get the list of your events you want to visit'\n '\\n/get_all_events: to see the list of all events')","title":""},{"docid":"f04a783e501c825a7080cc5f0020e103","score":"0.71281564","text":"def Help(self, verb):\n return ''","title":""},{"docid":"8ee726458ec392f40b97bd97cca8ad7b","score":"0.7125904","text":"def help(self, event):\n self.master.help()","title":""},{"docid":"eda42e163a13c9179754de96fc6bf45a","score":"0.71244067","text":"def help(self, event):\n\n try:\n path = staticPath(__file__, \"res/help_msg.txt\")\n with open(path, \"r\", encoding=\"utf-8\") as f_in:\n help_msg = f_in.read().strip()\n self.log(help_msg, \"info\")\n except:\n self.log(\"Help Message couldn't be loaded due to some error!\", \"error\")","title":""},{"docid":"0cdf46121ff8744c1b86bcb1e6a5263f","score":"0.71209794","text":"def help_command(bot, update):\n\n help_message = \"La lista di comandi:\\n\\n\" \\\n \"/help - Stampa questo messaggio\\n\" \\\n \"/news - Leggi le ultime 10 news\\n\" \\\n \"/news num - Leggi le ultime <num> news\\n\" \\\n \"/newson - Abilita le notifiche per ogni nuova news (default)\\n\" \\\n \"/newsoff - Disabilita le notifiche per ogni nuova news\\n\" \\\n \"/prof - Stampa la lista dei professori\\n\" \\\n \"/prof cognome - Info su un docente\\n\" \\\n \"/segreteria - Info sulla segreteria studenti\\n\" \\\n \"/mensa - Info sugli orari della mensa\\n\" \\\n \"/adsu - Info sull'adsu\" \\\n \"\\n\\nQuesto bot è orgogliosamente open source, sviluppato da Giacomo Cerquone\" \\\n \" e Diego Mariani.\"\n\n bot.sendMessage(update.message.chat_id, text=help_message)","title":""},{"docid":"6bd05572c036a6669b47c975b3081c0b","score":"0.71194637","text":"def print_help(self):\n if self.help:\n print(_HELP)\n sys.exit(0)","title":""},{"docid":"cea8894a8508d96491d47442026b452e","score":"0.71085113","text":"def do_help(self, argv):\n\n if len(argv) == 0:\n commands = [x for x in dir(self) if x.startswith(\"do_\")]\n else:\n commands = [x for x in dir(self) if x.startswith(\"do_\") and x[3:] in argv]\n\n for c in commands:\n help_msg = getattr(self, c).__doc__\n print(f\"{c[3:]:15s}{help_msg}\")","title":""},{"docid":"3fe455e64a7b2dfc2f6aaf7d11159978","score":"0.7099045","text":"def cmd_help(message):\n lines = []\n\n targets = message.parsed_args['<object>'] or (list(command_dispatcher.commands.keys()) + list(plugin_pages.keys()))\n\n for command_name in targets:\n if command_name in command_dispatcher.commands:\n command_handler = command_dispatcher.commands[command_name]\n if hasattr(command_handler, '__m5_permissions__'):\n if not permissions.check(message.source.identity, command_handler.__m5_permissions__):\n continue\n lines.append('Help for command {} (aliases: {}):'.format(\n command_name,\n ', '.join(command_handler.__m5_aliases__))\n )\n if command_handler.__doc__:\n lines.append(_remove_indent(command_handler.__doc__))\n else:\n lines.append(' No help message :(\\n')\n elif command_name in plugin_pages:\n lines.append('Help for plugin {}:'.format(command_name))\n lines.append(_remove_indent(plugin_pages[command_name]))\n else:\n lines.append('Unknown command or plugin: {}!'.format(command_name))\n\n reply('\\n'.join(lines), message)","title":""},{"docid":"8dfd354ac9d0e6a843182fcae2635640","score":"0.70909584","text":"def menu_help():\n\thelp_msg= '''\nSTART <level file> - Starts the game with a provided file.\nQUIT - Quits the game\nHELP - Shows this message\n'''\n\tprint(help_msg)","title":""},{"docid":"63e40fdca9cb5d9892351c1c102c842e","score":"0.70897526","text":"def help():\r\n print(\"\\nType the name of your next task (e.g. \\\"grading Algebra 1 HW\\\")\",\r\n \"\\nto get started. Or type one of the following commands:\\n\",\r\n \"\\n\\texit\\t\\texit TaskTimer\",\r\n \"\\n\\thistory\\t\\tdisplay previously recorded tasks\",\r\n \"\\n\\ttesting\\t\\tuse a test file for task history\",\r\n \"\\n\\tnormal\\t\\tuse the normal file for task history\",\r\n \"\\n\\thelp\\t\\tdisplay this help menu\",\r\n \"\\n\\topen\\t\\topen task history file\",\r\n \"\\n\\tclear\\t\\tclear the screen\")","title":""},{"docid":"211d236d7ff232e48716395812b26e72","score":"0.70661205","text":"def do_help(self, line):\n print('Below commands are supported')\n help_content = \"\"\"\n add: Add data to status logger\n view: View entered data\n update: Update entered data\n commit: Write data to status log file\n sync: Sync status file to google drive \n exit: Exit from log file\n \"\"\"\n print(help_content)","title":""},{"docid":"fa36f572f35173ebf1ad118aa98172b1","score":"0.706077","text":"def HelpTopic(self) -> str:","title":""},{"docid":"95f4cd1165d60516ac4181fd60ea5f0d","score":"0.7056012","text":"def help(bot, update) -> None:\n update.message.reply_text('/hilfe /temperatur /luftfeuchtigkeit /wassermelder')","title":""},{"docid":"b61a59661f958ee96e7ebe1cd0977f29","score":"0.7034612","text":"def on_help_clicked(self, obj):\n display_help(webpage=WIKI_HELP_PAGE, section=WIKI_HELP_SEC)","title":""},{"docid":"6c294b55c665a470d5d5edc4d7d7d639","score":"0.7034602","text":"def invoke(self, ctx: click.Context) -> None:\n\n click.echo(self.help, color=ctx.color)\n ctx.exit(1)","title":""},{"docid":"1687a44b9f94095576b6a6db49843f75","score":"0.70306456","text":"def help(bot, update):\n formatted_string = ('I can manage and perform stock analysis and broker related tasks.\\n\\n'\n 'Here are some basic commands to get started:\\n\\n'\n '/price (ticker) - find current stock price\\n'\n '/news (ticker) - latest news on company (top 5)\\n\\n'\n '<b>Portfolio Settings</b>\\n'\n '/portfolios - view all portfolios you\\'ve created'\n '/create (name) - creates a portfolio')\n update.message.reply_text(formatted_string, quote=False, parse_mode=ParseMode.HTML)","title":""},{"docid":"ba53e27d4eb77fe79010e3b7a91c1585","score":"0.6998821","text":"async def lichess(self, ctx: Context) -> None:\n await ctx.send_help(ctx.command)","title":""},{"docid":"fc4e44ba011c4638b29bfb05e6239eb9","score":"0.69964015","text":"def DoHelp(options, args):\n if len(args) == 1 and args[0] in COMMAND_USAGE_TEXT:\n print >>options.stdout, COMMAND_USAGE_TEXT[args[0]]\n else:\n raise Error(\"unknown subcommand '%s'; see 'gclient help'\" % args[0])","title":""},{"docid":"d2c875171cdc29f2cdd6ca1fcb2e7395","score":"0.6978998","text":"def help_handler(self, update, context):\n update.message.reply_text(\"Benutze /open, /sub oder /unsub um Aktionen durchzuführen\")","title":""},{"docid":"84cb4bccf2bf42124d4933d4fa8ec066","score":"0.6978929","text":"def do_help(self, argv):\r\n if argv[1:]:\r\n for arg in argv[1:]:\r\n if self._do_one_help(arg):\r\n break\r\n else:\r\n # If bare 'help' is called, print this class's doc\r\n # string (if it has one).\r\n doc = self._doc_to_help(self.__class__)\r\n if doc:\r\n sys.stdout.write(doc + '\\n')\r\n sys.stdout.flush()","title":""},{"docid":"0fe54cf26564c37b8e858fafa207fdc1","score":"0.6975974","text":"def help(self, print_output=True):\n help_text = self._rpc('help')\n if print_output:\n print(help_text)\n else:\n return help_text","title":""},{"docid":"0574573d2ee6b59c8a8e7d1b3a236d5d","score":"0.6974609","text":"def _help(self, *args: Any) -> str:\n return self.dispatch(*self.encode_args(args)).__doc__","title":""},{"docid":"c029ba5a5a73d2c31bb482ff8faf010c","score":"0.69740677","text":"async def send_bot_help(self, cogs: typing.Dict[\n commands.Cog, typing.Iterable[\n commands.Command\n ]]):\n e = discord.Embed(title='Help', color=colours.HELP)\n for cog in cogs:\n if not cog:\n continue\n lines = []\n for command in cogs[cog]:\n if command.hidden:\n continue\n line = '**{cmd}** *{brief}*'.format(\n cmd=self.get_command_signature(command),\n brief=command.brief or Help.brief\n )\n if line not in lines: # known bug where commands with\n lines.append(line) # aliases are duplicated\n text = '\\n'.join(lines)\n e.add_field(name=cog.qualified_name, value=text, inline=False)\n await self.get_destination().send(embed=e)","title":""},{"docid":"fe99a6458991e5f15968dedfee02e281","score":"0.6968065","text":"def help(self, dummy):\r\n help = self.doc\r\n if help.find(\"%s\") > 0:\r\n help = help.replace(\"%s\", self.progname)\r\n print help,\r\n self.exit(0)","title":""},{"docid":"667a8551ae9ca4590c37b4749bd8984b","score":"0.69650424","text":"def help(update, context):\r\n\thelp_mes = '''Comands list:\r\n\tfinish\r\n\tstart\r\n\taddlist\r\n\tadd\r\n\tload\r\n\tlogin\r\n\tresetanswer\r\n\tresetgame\r\n\tstats'''\r\n\tupdate.message.reply_text(help_mes)","title":""},{"docid":"f56444348466292df90a45e14e00e322","score":"0.69612944","text":"async def send_cog_help(self, cog: commands.Cog):\n await self.send_bot_help({cog: cog.walk_commands()})","title":""},{"docid":"e2efdfd2125c1ce7a32d54c971a8e6be","score":"0.69586253","text":"def help(self):\r\n top = Tk()\r\n top.title('Help on epicsLogger')\r\n text = Pmw.ScrolledText(top, text_font=self.fonts['help'], \r\n text_width=80, text_height=40)\r\n text.pack(fill=BOTH, expand=YES)\r\n text.insert(END, self.__doc__)\r\n text.insert(END, self.__init__.__doc__)","title":""}],"string":"[\n {\n \"docid\": \"dc0ada3b234879429e494800a76a63e9\",\n \"score\": \"0.8490778\",\n \"text\": \"def do_help(self, *args):\\n self.stdout.write(HELP_MESSAGE)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d47fb2e6b3684f66a3ede28374e5bee6\",\n \"score\": \"0.81821424\",\n \"text\": \"def do_help(self):\\n self.send_bot_msg('*Commands:* https://github.com/TinyChat/Tinychat-Bot/wiki/', self.user.nick)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c802229b407fbf9827caf8e8703c7bd1\",\n \"score\": \"0.806487\",\n \"text\": \"def _help(bot, update):\\n help_txt = \\\"Hey! This is a help text.\\\"\\n bot.send_message(chat_id=update.message.chat_id, text=help_txt)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f283d24055d60b06f784efd9f9c903cb\",\n \"score\": \"0.8044507\",\n \"text\": \"async def help(self, args, mobj):\\n output = \\\"Hey there! Thank you for using the help functionality.\\\\n\\\\n\\\"\\n output += \\\"##############################################################################\\\\n\\\"\\n output += \\\"# Don't forget to run the more server related commands in the actual server! #\\\\n\\\"\\n output += \\\"##############################################################################\\\\n\\\\n\\\"\\n output += \\\"Here are the available commands:\\\\n\\\\n\\\"\\n\\n for c in [f\\\"{k}\\\" for k in self.ACTIONS.keys()]:\\n output += f\\\" {c}\\\\n\\\"\\n\\n output += \\\"\\\\n For more info on each command, use '!command help'\\\"\\n return await self.message(mobj.author, self.pre_text(output))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"35b94caca6a502f03b7f70978f2a6d77\",\n \"score\": \"0.80123097\",\n \"text\": \"def help_command(update, context):\\n update.message.reply_text('Help!')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cddc4f86384bdf22dc68059aead373cd\",\n \"score\": \"0.79230416\",\n \"text\": \"def help(update, context):\\n update.message.reply_text(_(\\\"Help\\\"))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"78c687a3a60b7933d78533fd979fd53c\",\n \"score\": \"0.7887985\",\n \"text\": \"def cmd_help(self, params):\\n self.help()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"726c5202c0620f1176ef4f949ff8cf7a\",\n \"score\": \"0.7876978\",\n \"text\": \"def do_help(self, inputs):\\n cmd.Cmd.do_help(self, inputs)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7788117b224f2fae21fb4f9fa3c97782\",\n \"score\": \"0.7855003\",\n \"text\": \"async def help_command(message: types.Message):\\n await message.reply(msg.help_message)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cf93a3c658b3ee40f14e35925ff53214\",\n \"score\": \"0.7831273\",\n \"text\": \"def help_help(self):\\n\\n self.stdout.write(self.help_help.__doc__ + \\\"\\\\n\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9b269d5944fcb5cc7ce44c53bebf0ede\",\n \"score\": \"0.78282434\",\n \"text\": \"def help_command(self):\\n text = _(\\\"User commands:\\\\n\\\") + \\\\\\n _(\\\"r N - run the simulation for N cycles\\\\n\\\") + \\\\\\n _(\\\"c N - continue the simulation for N cycles\\\\n\\\") + \\\\\\n _(\\\"s X N - set switch X to N (0 or 1)\\\\n\\\") + \\\\\\n _(\\\"m X - set a monitor on signal X\\\\n\\\") + \\\\\\n _(\\\"z X - zap the monitor on signal X\\\\n\\\") + \\\\\\n _(\\\"h - help (this command)\\\\n\\\") + \\\\\\n _(\\\"q - quit the program\\\")\\n wx.MessageBox(text, _(\\\"Help on Commands\\\"), wx.ICON_INFORMATION | wx.OK)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6d7c7054688225af9261c5a56cb0adb6\",\n \"score\": \"0.77996266\",\n \"text\": \"def help(update, context):\\n update.message.reply_text('Help!')\\n #TODO\",\n \"title\": \"\"\n },\n {\n \"docid\": \"378551e33972ddd9c26d985dc80898fc\",\n \"score\": \"0.77729344\",\n \"text\": \"def do_help(self, args):\\n cmd.Cmd.do_help(self, args)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"031d47ae0b747df41a784ede6fd540c4\",\n \"score\": \"0.77707136\",\n \"text\": \"def help_command(update: Update, context: CallbackContext) -> None:\\n update.message.reply_text('Help!')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4f89969c8b3e5a12c9fb2c214dc46893\",\n \"score\": \"0.776831\",\n \"text\": \"def help_command(update: Update, context: CallbackContext) -> None:\\n update.message.reply_text('Helping you helping you.')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4df6f586861ada3181afe2abe004b452\",\n \"score\": \"0.772737\",\n \"text\": \"def help(bot, update):\\r\\n update.message.reply_text('Help!')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1286ae6941bf742ad078db7b7c4f271a\",\n \"score\": \"0.7699966\",\n \"text\": \"def helpMsg(actor):\\n\\tprint(\\\"Avaiable options: get|help|exit|list_neighbors|list_files\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cc13d91d57e8fd854c402fa2c3c699ac\",\n \"score\": \"0.76746005\",\n \"text\": \"def help(update: Update, context: CallbackContext) -> None:\\n s = \\\"\\\"\\n for i in myCommands:\\n s += '/'+myCommands[i]+\\\" - \\\"+i+\\\"\\\\n\\\"\\n update.message.reply_text('Help!\\\\n' + s)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"87a22a579e53fd6f6fa10f12c2a4c121\",\n \"score\": \"0.7650296\",\n \"text\": \"def help(server, data):\\r\\n\\r\\n # Construct the help message's header\\r\\n message = \\\"Here are the available commands:\\\\r\\\\n\\\"\\r\\n\\r\\n # Construct the content\\r\\n for command in server.commands.keys():\\r\\n message = message + \\\" - \\\" + command + \\\"\\\\r\\\\n\\\"\\r\\n\\r\\n # Add further help info\\r\\n message = message + \\\"To learn more about each command, type <command> help. \\\" + \\\"\\\\r\\\\n\\\"\\r\\n message = message + \\\"To add arguments to a command, type <command> <argument1> <argument2> (...)\\\" + \\\"\\\\r\\\\n\\\"\\r\\n\\r\\n # Send the prepared message to the client\\r\\n server.send(message)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c31100003ecf78d47fc1db90674a7b8d\",\n \"score\": \"0.7593971\",\n \"text\": \"def do_help():\\r\\n\\r\\n global STATE\\r\\n STATE = STATE_START\\r\\n attributes = {\\\"state\\\":globals()['STATE']}\\r\\n return response(attributes, response_plain_text(HELP_MESSAGE, False))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d541374ce4a00a7473d2ca5f1d010a6f\",\n \"score\": \"0.7584389\",\n \"text\": \"def help(self, message, args):\\n raise NotImplementedError('This method must be implemented')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b8b99ac44eacf797ffb7ea375b8a1b38\",\n \"score\": \"0.75822437\",\n \"text\": \"def do_help(self, args):\\n ## The only reason to define this method is for the help text in the doc string\\n cmd.Cmd.do_help(self, args)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c654bc6719ec6389c5bc3b0f6dc88156\",\n \"score\": \"0.757944\",\n \"text\": \"def do_help(self, line):\\n enterHelp(self.client)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3a507cc7db8915be98355fe38230588b\",\n \"score\": \"0.75738716\",\n \"text\": \"def help():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b2a73f5351231ae885d74ce59bdb957e\",\n \"score\": \"0.7564036\",\n \"text\": \"def show_help(bot, update):\\n bot.send_message(chat_id=update.message.chat_id,\\n text=MESSAGES['HELP'],\\n parse_mode=ParseMode.HTML)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"723ff42dfdc99e815b145a9edc2ae69e\",\n \"score\": \"0.7558429\",\n \"text\": \"def help(bot, update):\\n bot.sendMessage(update.message.chat_id, text='Help!')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"40b22538455f87cefa1a8d4f66c4fd04\",\n \"score\": \"0.7539667\",\n \"text\": \"def do_help(self, args):\\n # The only reason to define this method is for the help text in the doc\\n # string\\n cmd.Cmd.do_help(self, args)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e9a787cf9112c25e6fe3f453db0199fb\",\n \"score\": \"0.7531621\",\n \"text\": \"async def help(ctx):\\n await server_bot.help(ctx)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"99c2783978243e651e4251be3fd10edc\",\n \"score\": \"0.75235754\",\n \"text\": \"def do_main_help(self, data):\\n msg = \\\"Hi, I'm a bot! I have {0} commands loaded: {1}. You can get help for any command with '!help <command>'.\\\"\\n cmnds = sorted([cmnd.name for cmnd in self.bot.commands])\\n msg = msg.format(len(cmnds), ', '.join(cmnds))\\n self.reply(data, msg)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3ef15081b0229e960c2546bddebf77a3\",\n \"score\": \"0.75202906\",\n \"text\": \"def do_help(self, args):\\n # The only reason to define this method\\n # is for the help text in the doc string\\n cmd.Cmd.do_help(self, args)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6088e28731da3f68f6c5691834839f69\",\n \"score\": \"0.7514919\",\n \"text\": \"def help():\\n return help_text\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7c12107736c0a8bef614f88f99e04e2d\",\n \"score\": \"0.7506989\",\n \"text\": \"def help(update, context):\\n update.message.reply_text('Help!')\\n time.sleep(3)\\n update.message.reply_text('Just kidding! HAHAHAHAHAHA')\\n update.message.reply_text('''Add triggers by doing: /add <trigger>:<respons>\\nRemove triggers by doing: /delete <trigger>\\nGet all triggers by doing: /triggers\\\\\\n ''')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ad16aa42b7001533c46c00b6e26f0045\",\n \"score\": \"0.7504356\",\n \"text\": \"def msg_help(self, text):\\n if type(self).help_more:\\n usemore = True\\n\\n if self.session.protocol_key in (\\\"websocket\\\", \\\"ajax/comet\\\"):\\n try:\\n options = self.player.db._saved_webclient_options\\n if options and options[\\\"helppopup\\\"]:\\n usemore = False\\n except KeyError:\\n pass\\n\\n if usemore:\\n evmore.msg(self.caller, text)\\n return\\n\\n self.msg((text, {\\\"type\\\": \\\"help\\\"}))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e84239e0b10fdbc1c4506ffa1d6314a0\",\n \"score\": \"0.7500062\",\n \"text\": \"def do_help():\\n\\n global STATE\\n STATE = STATE_START\\n # attributes = {\\\"state\\\":globals()['STATE']}\\n return response_plain_text_ga(HELP_MESSAGE, True)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e69aa82c0cfab47788efab973ac20334\",\n \"score\": \"0.74996126\",\n \"text\": \"async def help_handler(msg: types.Message) -> None:\\n help_text = \\\"This is a help text for testing\\\"\\n await msg.answer(help_text)\\n await msg.reply(\\\"Son of a bitch, hay que decirlo mas\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"073e149b82a1d815b030a9d347a1b0d3\",\n \"score\": \"0.7447619\",\n \"text\": \"async def send_command_help(self, command: commands.Command):\\n if command.name == 'help':\\n desc = Help.help\\n else:\\n desc = command.help\\n desc = desc.replace('{{pre}}', self.context.prefix)\\n title = self.get_command_signature(command)\\n e = discord.Embed(title=title, color=colours.HELP, description=desc)\\n await self.get_destination().send(embed=e)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d9549a001d995a662f5092ac35c6fc3c\",\n \"score\": \"0.74306446\",\n \"text\": \"def send_help_message(self, channel):\\n\\n self.logger.debug('Sending help message.')\\n\\n message = \\\"\\\"\\\"There are a few things I can do:\\n\\nIf you say `slack`, or `master`, I will speak using everything I have\\nlearned from slack. This is my default behaviour.\\n\\nIf you say `#channel`, I will speak using everything I have learned\\nfrom that channel.\\n\\nIf you say `@user`, I will speak using everything I have learned from\\nthat user.\\n\\nIf you say `$external source`, I will speak using everything I have\\nlearned from that source.\\n\\nHint: You can combine multiple commands.\\n \\\"\\\"\\\"\\n\\n self.send_message(channel, message)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"59da4d65da34e130bbdff150345ef626\",\n \"score\": \"0.7430576\",\n \"text\": \"def help(bot, update):\\r\\n update.message.reply_text('Hi, I am here to help you!')\\r\\n update.message.reply_text('To start, you should call'\\r\\n ' start command with two args:')\\r\\n update.message.reply_text('Url to wiki and depth of search')\\r\\n update.message.reply_text('Bot only works with English wiki for now!')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5bbee8c7e69151b99a54617ff528b80f\",\n \"score\": \"0.7422377\",\n \"text\": \"def help(self):\\n self.help_message.place(x=self.absx + 10, y=self.absy + 10)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9d4a9d1510d808b88b8f46fd2347fc36\",\n \"score\": \"0.7418295\",\n \"text\": \"def handle_help(self, event: Event) -> None:\\n content = scripts.get_help()\\n\\n return self.reply_line(event, content)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6d049507aebd874542210f03c46e4531\",\n \"score\": \"0.74178636\",\n \"text\": \"async def help(self, context, user : discord.Member=None):\\n f = open(helptxt, 'r')\\n general=f.read()\\n await context.channel.send(general)\\n f.close()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4f7fcbf9fc063295766fd318348c7605\",\n \"score\": \"0.7397008\",\n \"text\": \"async def help(ctx):\\n\\n print(f\\\"{ctx.message.author}: {ctx.message.content}\\\")\\n await ctx.message.delete()\\n await cdef.print_help_message(ctx)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a17f2a88519fd1914f6a09d564bd8dbe\",\n \"score\": \"0.73854035\",\n \"text\": \"async def help(ctx):\\n embed = discord.Embed(title=\\\"Battle Ships Bot\\\",\\n description=\\\"a bot the lets you play the Battle \\\"\\n \\\"Ships game in a DM channel in Discord\\\",\\n color=0xeee657)\\n\\n embed.add_field(name=\\\"^start_game\\\", value=\\\"bot creates a dm channel and \\\"\\n \\\"starts a battle ship game\\\",\\n inline=False)\\n embed.add_field(name=\\\"^shoot X Y\\\", value=\\\"Bot shoots the given \\\"\\n \\\"coordinates\\\", inline=False)\\n embed.add_field(name=\\\"^stats\\\", value=\\\"Gives stats about current game, \\\"\\n \\\"number of turns, hits and misses\\\",\\n inline=False)\\n embed.add_field(name=\\\"^surrender\\\", value=\\\"surrenders and stops a current \\\"\\n \\\"game session\\\", inline=False)\\n embed.add_field(name=\\\"^info\\\", value=\\\"Gives a little info about the bot\\\",\\n inline=False)\\n embed.add_field(name=\\\"^help\\\", value=\\\"Gives this message\\\", inline=False)\\n\\n await ctx.send(embed=embed)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8062de968f18b2702982e6c61f67913c\",\n \"score\": \"0.7379159\",\n \"text\": \"def help(update, context):\\n user = update.message.from_user\\n \\n context.bot.send_message(text=constants.HELP_MESSAGE,\\n chat_id=user.id,\\n parse_mode=ParseMode.HTML)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d1ce256bda0e0fab11dcc029e12232fb\",\n \"score\": \"0.7372104\",\n \"text\": \"def chat_help(update: Update, context: CallbackContext):\\n update.message.reply_text(HELP_MESSAGE)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6ad19320a90921d80d9cb2b012106b64\",\n \"score\": \"0.73642117\",\n \"text\": \"def cb_help(self, obj):\\n display_help(webpage = WIKI_HELP_PAGE, section = WIKI_HELP_SEC)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"902ba76d51efa1fcc49c9a33cb8112c2\",\n \"score\": \"0.73545146\",\n \"text\": \"def help(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3a3ae010c4c1282c6e2f29ec82de1d75\",\n \"score\": \"0.73493034\",\n \"text\": \"def callhelp(self):\\n self.parser.print_help()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6b9486437f15f6e10599769045369610\",\n \"score\": \"0.7306459\",\n \"text\": \"def help(update, context):\\n #update.message.reply_text(\\\"Доступные команды: \\\\n\\\\n/id\\\")\\n update.message.reply_text(\\\"Прости, лично я пока ничем не готов помочь...\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"486000c1422f79eacf699430b9c0db7b\",\n \"score\": \"0.73041505\",\n \"text\": \"def help(update, context):\\n update.message.reply_text('cazzo vuoi io non ti aiuto')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4448dad758c1e8cb9a2f4416dee83436\",\n \"score\": \"0.7293747\",\n \"text\": \"def OnHelp( self, evt ):\\n wx.MessageBox( \\\"Documentation available at\\\\nhttp://ctrax.sourceforge.net\\\", \\\"Help\\\" )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"304570b1bcf0b535b63d47da99066933\",\n \"score\": \"0.7291669\",\n \"text\": \"async def write(self, ctx):\\n await self.bot.send_cmd_help(ctx)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"55decaecaf2b4b4b70a23f29ab08ecc6\",\n \"score\": \"0.72851753\",\n \"text\": \"def help_(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"abf8e0ce9c88791fb70fe0cca953d363\",\n \"score\": \"0.7280757\",\n \"text\": \"def help(self, **kwds):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"260db9140088250b6bd7a365288b2221\",\n \"score\": \"0.7271429\",\n \"text\": \"def help_command(chat_id, text):\\n logger.info('COMMAND {}: chat_id={}'.format(text, chat_id))\\n get_bot().send_message(chat_id=chat_id, text='\\\\n'.join(tr('help', chat_id)))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"53956d664d4c78758c5be0fbfad23ae9\",\n \"score\": \"0.72584754\",\n \"text\": \"async def help(client, message, **kwargs):\\n commandName = kwargs.get('command')\\n if commandName:\\n command = cmds.find(commandName)\\n if command:\\n context_cache = {'db_server': db.get_server(message.server) if message.server else None}\\n context_cache = cmds.get_context_cache_update(context_cache, message)\\n validated, exc = await command.validate_context(client, message, [], context_cache)\\n if validated or isinstance(exc, MissingParameters):\\n await client.send_message(message.channel, command.pretty_print())\\n else:\\n commandsStr = []\\n async for c in AuthorizedCommandsWrapper(client, message):\\n commandsStr.append(c)\\n await client.send_message(message.channel, T_HelpGlobal.format('\\\\n '.join(commandsStr)))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"100455fbcb2a0247ffce4b72acd63cbb\",\n \"score\": \"0.7258179\",\n \"text\": \"def cmd_help( self, command, params, event, received=\\\"channel\\\" ):\\n\\n if len( params ) < 1:\\n self.send_message( event.source, \\\"List of commands:\\\" )\\n for cmd in self.commands:\\n self.send_message( event.source, format.color( \\\"## \\\", format.LIME_GREEN ) + '{:<20} {}'.format( *self.commands[ cmd ][1].__doc__.format( format.bold( format_command( cmd, received ) ) ).splitlines()[0].strip().split( \\\"!X!\\\", 1 ) ) ) # split and justify\\n return\\n if params[0].lower() in self.commands:\\n self.send_message( event.source, \\\"Usage info for command {0}:\\\".format( format.bold( params[0] ) ) )\\n for line in self.commands[ params[0].lower() ][1].__doc__.format( *[ format.bold( format_command( c, received ) ) for c in params ] ).splitlines():\\n self.send_message( event.source, format.color( \\\"## \\\", format.LIME_GREEN ) + '{:<35} {}'.format( *line.strip().split( \\\"!X!\\\", 1 ) ) ) # split and justify\\n else:\\n self.send_message( event.source, \\\"Unkown Command {0}.\\\".format( format.bold( params[0] ) ) )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"92d848a72bae335023b22138a3d35af6\",\n \"score\": \"0.7244817\",\n \"text\": \"def show_help(update: Update, context: CallbackContext):\\n update.message.reply_text(\\\"Help!\\\")\\n log_context(context)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"78f55633db05c3e85f0e175abef98f1d\",\n \"score\": \"0.72430915\",\n \"text\": \"def help(self, *args: Any, **kwargs: Any) -> None:\\n print(self._help(*args))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9e3e1c48a28115d5364744716318e318\",\n \"score\": \"0.7238084\",\n \"text\": \"async def help(self, /, timeout: Optional[Union[float, Default]] = _default) -> str:\\n await self._ehlo_or_helo_if_needed()\\n\\n response = await self.execute_command(b\\\"HELP\\\", timeout=timeout)\\n if response.code not in (\\n SMTPStatus.system_status_ok,\\n SMTPStatus.help_message,\\n SMTPStatus.completed,\\n ):\\n raise SMTPResponseException(response.code, response.message)\\n\\n return response.message\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fbfdcd77467d42901dc8a10c54e53bdf\",\n \"score\": \"0.7234989\",\n \"text\": \"def help(update, context):\\n update.message.reply_text('Bischd du dumm?')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"16189a160af4e224d10999630669b8a5\",\n \"score\": \"0.7222698\",\n \"text\": \"async def handle_command_help(self, target, nick):\\n help_msg = (\\\"Pump19 is run by Twisted Pear. \\\"\\n \\\"Check {url} for a list of supported commands.\\\").format(\\n url=COMMAND_URL)\\n await self.client.privmsg(target, help_msg)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"22eeab3319c36a80d8f876b16ce3c83e\",\n \"score\": \"0.72175574\",\n \"text\": \"def handle_help(self):\\n print(\\\"Help not implemented yet for PyXtal!\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0cf9372768ac0d709c5b908d49961589\",\n \"score\": \"0.7214833\",\n \"text\": \"def help_help(self):\\n print \\\"List commands or print details about a command\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"243842f7f070518fbd1d39b11d879731\",\n \"score\": \"0.7213134\",\n \"text\": \"def help(update, context):\\n help_text = get_help_text(is_telegram=True)\\n update.message.reply_text(help_text)\\n return\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2904501c85c9a6f7a17c12c5515404b4\",\n \"score\": \"0.7211631\",\n \"text\": \"def __help_msg(self):\\n return \\\"\\\"\\\"\\\\\\nHelp:\\n - /IGNORE \\\"\\\"\\\" + self.connection.get_nickname() + \\\"\\\"\\\" - Lets you stop reading the bot.\\n\\n You can send these commands in private message (PM) to \\\"\\\"\\\" + self.connection.get_nickname() + \\\"\\\"\\\":\\n - !help - Show this help message.\\n - !stats - Show some statistics.\\n - !list - Show all feeds.\\n - !last - Show last news published in all feeds.\\n - !lastfeed <feedid> - Show last news published in a specific feed.\\n\\\"\\\"\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5beca3b23d6b0196b384730dd3f10ad7\",\n \"score\": \"0.720753\",\n \"text\": \"def help(self, mess, args):\\n if not args:\\n if self.__doc__:\\n description = self.__doc__.strip()\\n else:\\n description = _('Available commands:')\\n\\n usage = sorted(['%s:\\\\t%s' % (name, (command.__doc__ or \\\\\\n '(undocumented)').strip().split('\\\\n', 1)[0])\\n for (name, command) in self.commands.iteritems() \\\\\\n if name != 'help' \\\\\\n and not command._jabberbot_command_hidden\\n ])\\n #usage = '\\\\n\\\\n' + '\\\\n\\\\n'.join(filter(None, [usage, self.MSG_HELP_TAIL]))\\n usage = usage + [self.MSG_HELP_TAIL]\\n else:\\n description = ''\\n if args in self.commands:\\n usage = (self.commands[args].__doc__ or \\\\\\n 'undocumented').strip()\\n else:\\n usage = [self.MSG_HELP_UNDEFINED_COMMAND]\\n\\n if isinstance(usage, str):\\n usage = [usage]\\n if isinstance(description, str):\\n description = [description]\\n\\n # return [description] + usage\\n self.send_simple_reply(mess, description + usage, True)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ffdc9fc8c453bbc9a6ba0f4a3171c076\",\n \"score\": \"0.71776325\",\n \"text\": \"def send_help(message):\\n bot.send_message(message.chat.id, 'Hei, ' + message.from_user.first_name +\\n '! Рад тебя видеть! Чем могу помочь?',\\n reply_markup=config.keyboard(content.main_menu))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4453c93839d26b0d99a84a6569d6c56b\",\n \"score\": \"0.7177051\",\n \"text\": \"async def faq(self, ctx):\\n await ctx.send_help(ctx.command)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"260b0efcf7bfe425dabb95754ccf95c7\",\n \"score\": \"0.717615\",\n \"text\": \"def help(self, args):\\n print('Various commands for couchpotato')\\n print('run with --help for more information')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ab56972c5a82c239bd5d55933485240b\",\n \"score\": \"0.71744657\",\n \"text\": \"def do_command_help(self, data):\\n target = data.args[0]\\n\\n for command in self.bot.commands:\\n if command.name == target or target in command.commands:\\n if command.__doc__:\\n doc = command.__doc__.replace(\\\"\\\\n\\\", \\\"\\\")\\n doc = re.sub(r\\\"\\\\s\\\\s+\\\", \\\" \\\", doc)\\n msg = 'Help for command \\\\x0303{0}\\\\x0F: \\\"{1}\\\"'\\n self.reply(data, msg.format(target, doc))\\n return\\n\\n msg = \\\"Sorry, no help for \\\\x0303{0}\\\\x0F.\\\".format(target)\\n self.reply(data, msg)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"10ef278124e799cc68a952e9a6630415\",\n \"score\": \"0.716986\",\n \"text\": \"def help(cls, task):\\n executor = task.executor\\n\\n if cls.__doc__:\\n out = fmt.FormatList(executor)\\n out.add(fmt.Header(f\\\"Help: {cls.name}\\\"))\\n out.add(fmt.Line(cls.__doc__))\\n out.add(fmt.Footer())\\n executor.send(out)\\n else:\\n executor.msg(text=\\\"Help is not implemented for this command.\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d64c3ba2e1dde5452d1b373791760272\",\n \"score\": \"0.7154695\",\n \"text\": \"async def show_bot_help(self):\\n\\n self.embed.title = 'Using the **C02* bot'\\n self.embed.description = 'Hello! Welcome to the help page.'\\n self.embed.clear_fields()\\n\\n entries = (\\n ('<argument>', 'This means the argument is __**required**__.'),\\n ('[argument]', 'This means the argument is __**optional**__.'),\\n ('[A|B]', 'This means the it can be __**either A or B**__.'),\\n ('[argument...]', 'This means you can have multiple arguments.\\\\n__**You do not type in the brackets!**__')\\n )\\n\\n for name, value in entries:\\n self.embed.add_field(name=name, value=value, inline=False)\\n\\n self.embed.set_footer(text=f'We were on page {self.current_page} before this message.')\\n await self.message.edit(embed=self.embed)\\n\\n async def go_back_to_current_page():\\n await asyncio.sleep(30.0)\\n await self.show_current_page()\\n\\n self.bot.loop.create_task(go_back_to_current_page())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c33808163f19aa079d9ffe299507dc38\",\n \"score\": \"0.7152405\",\n \"text\": \"def do_help(self, arg):\\n if arg:\\n helper = [n[5:] for n in self.get_names()\\n if n.startswith('help_' + arg)]\\n if len(helper) == 0:\\n self.stdout.write('*** Unknown command: %s\\\\n' % arg)\\n return\\n elif len(helper) > 1:\\n self.stdout.write((\\n \\\"*** {} is a shorcut to several commands\\\\n\\\"\\n \\\" Please give more characters for disambiguation\\\"\\n ).format(cmd))\\n return\\n else:\\n arg = helper[0]\\n cmd.Cmd.do_help(self, arg)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3876464481a92f00979051f50995d2b6\",\n \"score\": \"0.7133162\",\n \"text\": \"def help(bot, update):\\n update.message.reply_text('These are our commands:\\\\n/start: to roll with us'\\n '\\\\n/help: to get to this selection'\\n '\\\\n/add_event: to add an event you want to visit'\\n '\\\\n/del_event: to remove an event you dont want to visit any more, or youve visited it already'\\n '\\\\n/list: to get the list of your events you want to visit'\\n '\\\\n/get_all_events: to see the list of all events')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f04a783e501c825a7080cc5f0020e103\",\n \"score\": \"0.71281564\",\n \"text\": \"def Help(self, verb):\\n return ''\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8ee726458ec392f40b97bd97cca8ad7b\",\n \"score\": \"0.7125904\",\n \"text\": \"def help(self, event):\\n self.master.help()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"eda42e163a13c9179754de96fc6bf45a\",\n \"score\": \"0.71244067\",\n \"text\": \"def help(self, event):\\n\\n try:\\n path = staticPath(__file__, \\\"res/help_msg.txt\\\")\\n with open(path, \\\"r\\\", encoding=\\\"utf-8\\\") as f_in:\\n help_msg = f_in.read().strip()\\n self.log(help_msg, \\\"info\\\")\\n except:\\n self.log(\\\"Help Message couldn't be loaded due to some error!\\\", \\\"error\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0cdf46121ff8744c1b86bcb1e6a5263f\",\n \"score\": \"0.71209794\",\n \"text\": \"def help_command(bot, update):\\n\\n help_message = \\\"La lista di comandi:\\\\n\\\\n\\\" \\\\\\n \\\"/help - Stampa questo messaggio\\\\n\\\" \\\\\\n \\\"/news - Leggi le ultime 10 news\\\\n\\\" \\\\\\n \\\"/news num - Leggi le ultime <num> news\\\\n\\\" \\\\\\n \\\"/newson - Abilita le notifiche per ogni nuova news (default)\\\\n\\\" \\\\\\n \\\"/newsoff - Disabilita le notifiche per ogni nuova news\\\\n\\\" \\\\\\n \\\"/prof - Stampa la lista dei professori\\\\n\\\" \\\\\\n \\\"/prof cognome - Info su un docente\\\\n\\\" \\\\\\n \\\"/segreteria - Info sulla segreteria studenti\\\\n\\\" \\\\\\n \\\"/mensa - Info sugli orari della mensa\\\\n\\\" \\\\\\n \\\"/adsu - Info sull'adsu\\\" \\\\\\n \\\"\\\\n\\\\nQuesto bot è orgogliosamente open source, sviluppato da Giacomo Cerquone\\\" \\\\\\n \\\" e Diego Mariani.\\\"\\n\\n bot.sendMessage(update.message.chat_id, text=help_message)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6bd05572c036a6669b47c975b3081c0b\",\n \"score\": \"0.71194637\",\n \"text\": \"def print_help(self):\\n if self.help:\\n print(_HELP)\\n sys.exit(0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cea8894a8508d96491d47442026b452e\",\n \"score\": \"0.71085113\",\n \"text\": \"def do_help(self, argv):\\n\\n if len(argv) == 0:\\n commands = [x for x in dir(self) if x.startswith(\\\"do_\\\")]\\n else:\\n commands = [x for x in dir(self) if x.startswith(\\\"do_\\\") and x[3:] in argv]\\n\\n for c in commands:\\n help_msg = getattr(self, c).__doc__\\n print(f\\\"{c[3:]:15s}{help_msg}\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3fe455e64a7b2dfc2f6aaf7d11159978\",\n \"score\": \"0.7099045\",\n \"text\": \"def cmd_help(message):\\n lines = []\\n\\n targets = message.parsed_args['<object>'] or (list(command_dispatcher.commands.keys()) + list(plugin_pages.keys()))\\n\\n for command_name in targets:\\n if command_name in command_dispatcher.commands:\\n command_handler = command_dispatcher.commands[command_name]\\n if hasattr(command_handler, '__m5_permissions__'):\\n if not permissions.check(message.source.identity, command_handler.__m5_permissions__):\\n continue\\n lines.append('Help for command {} (aliases: {}):'.format(\\n command_name,\\n ', '.join(command_handler.__m5_aliases__))\\n )\\n if command_handler.__doc__:\\n lines.append(_remove_indent(command_handler.__doc__))\\n else:\\n lines.append(' No help message :(\\\\n')\\n elif command_name in plugin_pages:\\n lines.append('Help for plugin {}:'.format(command_name))\\n lines.append(_remove_indent(plugin_pages[command_name]))\\n else:\\n lines.append('Unknown command or plugin: {}!'.format(command_name))\\n\\n reply('\\\\n'.join(lines), message)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8dfd354ac9d0e6a843182fcae2635640\",\n \"score\": \"0.70909584\",\n \"text\": \"def menu_help():\\n\\thelp_msg= '''\\nSTART <level file> - Starts the game with a provided file.\\nQUIT - Quits the game\\nHELP - Shows this message\\n'''\\n\\tprint(help_msg)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"63e40fdca9cb5d9892351c1c102c842e\",\n \"score\": \"0.70897526\",\n \"text\": \"def help():\\r\\n print(\\\"\\\\nType the name of your next task (e.g. \\\\\\\"grading Algebra 1 HW\\\\\\\")\\\",\\r\\n \\\"\\\\nto get started. Or type one of the following commands:\\\\n\\\",\\r\\n \\\"\\\\n\\\\texit\\\\t\\\\texit TaskTimer\\\",\\r\\n \\\"\\\\n\\\\thistory\\\\t\\\\tdisplay previously recorded tasks\\\",\\r\\n \\\"\\\\n\\\\ttesting\\\\t\\\\tuse a test file for task history\\\",\\r\\n \\\"\\\\n\\\\tnormal\\\\t\\\\tuse the normal file for task history\\\",\\r\\n \\\"\\\\n\\\\thelp\\\\t\\\\tdisplay this help menu\\\",\\r\\n \\\"\\\\n\\\\topen\\\\t\\\\topen task history file\\\",\\r\\n \\\"\\\\n\\\\tclear\\\\t\\\\tclear the screen\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"211d236d7ff232e48716395812b26e72\",\n \"score\": \"0.70661205\",\n \"text\": \"def do_help(self, line):\\n print('Below commands are supported')\\n help_content = \\\"\\\"\\\"\\n add: Add data to status logger\\n view: View entered data\\n update: Update entered data\\n commit: Write data to status log file\\n sync: Sync status file to google drive \\n exit: Exit from log file\\n \\\"\\\"\\\"\\n print(help_content)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fa36f572f35173ebf1ad118aa98172b1\",\n \"score\": \"0.706077\",\n \"text\": \"def HelpTopic(self) -> str:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"95f4cd1165d60516ac4181fd60ea5f0d\",\n \"score\": \"0.7056012\",\n \"text\": \"def help(bot, update) -> None:\\n update.message.reply_text('/hilfe /temperatur /luftfeuchtigkeit /wassermelder')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b61a59661f958ee96e7ebe1cd0977f29\",\n \"score\": \"0.7034612\",\n \"text\": \"def on_help_clicked(self, obj):\\n display_help(webpage=WIKI_HELP_PAGE, section=WIKI_HELP_SEC)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6c294b55c665a470d5d5edc4d7d7d639\",\n \"score\": \"0.7034602\",\n \"text\": \"def invoke(self, ctx: click.Context) -> None:\\n\\n click.echo(self.help, color=ctx.color)\\n ctx.exit(1)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1687a44b9f94095576b6a6db49843f75\",\n \"score\": \"0.70306456\",\n \"text\": \"def help(bot, update):\\n formatted_string = ('I can manage and perform stock analysis and broker related tasks.\\\\n\\\\n'\\n 'Here are some basic commands to get started:\\\\n\\\\n'\\n '/price (ticker) - find current stock price\\\\n'\\n '/news (ticker) - latest news on company (top 5)\\\\n\\\\n'\\n '<b>Portfolio Settings</b>\\\\n'\\n '/portfolios - view all portfolios you\\\\'ve created'\\n '/create (name) - creates a portfolio')\\n update.message.reply_text(formatted_string, quote=False, parse_mode=ParseMode.HTML)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ba53e27d4eb77fe79010e3b7a91c1585\",\n \"score\": \"0.6998821\",\n \"text\": \"async def lichess(self, ctx: Context) -> None:\\n await ctx.send_help(ctx.command)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fc4e44ba011c4638b29bfb05e6239eb9\",\n \"score\": \"0.69964015\",\n \"text\": \"def DoHelp(options, args):\\n if len(args) == 1 and args[0] in COMMAND_USAGE_TEXT:\\n print >>options.stdout, COMMAND_USAGE_TEXT[args[0]]\\n else:\\n raise Error(\\\"unknown subcommand '%s'; see 'gclient help'\\\" % args[0])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d2c875171cdc29f2cdd6ca1fcb2e7395\",\n \"score\": \"0.6978998\",\n \"text\": \"def help_handler(self, update, context):\\n update.message.reply_text(\\\"Benutze /open, /sub oder /unsub um Aktionen durchzuführen\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"84cb4bccf2bf42124d4933d4fa8ec066\",\n \"score\": \"0.6978929\",\n \"text\": \"def do_help(self, argv):\\r\\n if argv[1:]:\\r\\n for arg in argv[1:]:\\r\\n if self._do_one_help(arg):\\r\\n break\\r\\n else:\\r\\n # If bare 'help' is called, print this class's doc\\r\\n # string (if it has one).\\r\\n doc = self._doc_to_help(self.__class__)\\r\\n if doc:\\r\\n sys.stdout.write(doc + '\\\\n')\\r\\n sys.stdout.flush()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0fe54cf26564c37b8e858fafa207fdc1\",\n \"score\": \"0.6975974\",\n \"text\": \"def help(self, print_output=True):\\n help_text = self._rpc('help')\\n if print_output:\\n print(help_text)\\n else:\\n return help_text\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0574573d2ee6b59c8a8e7d1b3a236d5d\",\n \"score\": \"0.6974609\",\n \"text\": \"def _help(self, *args: Any) -> str:\\n return self.dispatch(*self.encode_args(args)).__doc__\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c029ba5a5a73d2c31bb482ff8faf010c\",\n \"score\": \"0.69740677\",\n \"text\": \"async def send_bot_help(self, cogs: typing.Dict[\\n commands.Cog, typing.Iterable[\\n commands.Command\\n ]]):\\n e = discord.Embed(title='Help', color=colours.HELP)\\n for cog in cogs:\\n if not cog:\\n continue\\n lines = []\\n for command in cogs[cog]:\\n if command.hidden:\\n continue\\n line = '**{cmd}** *{brief}*'.format(\\n cmd=self.get_command_signature(command),\\n brief=command.brief or Help.brief\\n )\\n if line not in lines: # known bug where commands with\\n lines.append(line) # aliases are duplicated\\n text = '\\\\n'.join(lines)\\n e.add_field(name=cog.qualified_name, value=text, inline=False)\\n await self.get_destination().send(embed=e)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fe99a6458991e5f15968dedfee02e281\",\n \"score\": \"0.6968065\",\n \"text\": \"def help(self, dummy):\\r\\n help = self.doc\\r\\n if help.find(\\\"%s\\\") > 0:\\r\\n help = help.replace(\\\"%s\\\", self.progname)\\r\\n print help,\\r\\n self.exit(0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"667a8551ae9ca4590c37b4749bd8984b\",\n \"score\": \"0.69650424\",\n \"text\": \"def help(update, context):\\r\\n\\thelp_mes = '''Comands list:\\r\\n\\tfinish\\r\\n\\tstart\\r\\n\\taddlist\\r\\n\\tadd\\r\\n\\tload\\r\\n\\tlogin\\r\\n\\tresetanswer\\r\\n\\tresetgame\\r\\n\\tstats'''\\r\\n\\tupdate.message.reply_text(help_mes)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f56444348466292df90a45e14e00e322\",\n \"score\": \"0.69612944\",\n \"text\": \"async def send_cog_help(self, cog: commands.Cog):\\n await self.send_bot_help({cog: cog.walk_commands()})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e2efdfd2125c1ce7a32d54c971a8e6be\",\n \"score\": \"0.69586253\",\n \"text\": \"def help(self):\\r\\n top = Tk()\\r\\n top.title('Help on epicsLogger')\\r\\n text = Pmw.ScrolledText(top, text_font=self.fonts['help'], \\r\\n text_width=80, text_height=40)\\r\\n text.pack(fill=BOTH, expand=YES)\\r\\n text.insert(END, self.__doc__)\\r\\n text.insert(END, self.__init__.__doc__)\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":380,"cells":{"query_id":{"kind":"string","value":"835c11f46f8cfb87636628b33f3e0e4b"},"query":{"kind":"string","value":"Create leaderboard view for Round2"},"positive_passages":{"kind":"list like","value":[{"docid":"2fe3cc33225358d9525373963b157990","score":"0.56610113","text":"def rd2leaderboard(request):\n\n #Add views\n playing_players = Rd2SlotModel.objects.filter(player_name__isnull=False)\n\n #Add context\n context = {\n 'playing_players': playing_players,\n }\n\n return render(request, 'rd2Leaderboard.html', context=context)","title":""}],"string":"[\n {\n \"docid\": \"2fe3cc33225358d9525373963b157990\",\n \"score\": \"0.56610113\",\n \"text\": \"def rd2leaderboard(request):\\n\\n #Add views\\n playing_players = Rd2SlotModel.objects.filter(player_name__isnull=False)\\n\\n #Add context\\n context = {\\n 'playing_players': playing_players,\\n }\\n\\n return render(request, 'rd2Leaderboard.html', context=context)\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"437d7c5565d4948aa3c19c5e239cc8fe","score":"0.7503058","text":"def leaderboard(self):\n click.echo(\"\\n----Leaderboard----\")\n players = OrderedDict(\n sorted(self.players.items(), key=lambda x: getitem(x[1], \"round\"))\n )\n columns = [\"Rank\", \"Name\", \"Round\", \"Score\"]\n row_format = \"{:>15}\" * len(columns)\n click.echo(row_format.format(*columns))\n rank = 1\n for k, v in players.items():\n click.echo(row_format.format(rank, v[\"name\"], v[\"round\"], v[\"score\"]))\n rank = rank + 1","title":""},{"docid":"6375733d6284707ba6aaf4b11d8578d3","score":"0.72021484","text":"def show_leaderboard():\n leaderboard_data = get_sorted_scores()\n return render_template(\"leaderboard.html\", leaderboard_data=leaderboard_data)","title":""},{"docid":"dda1b561034c1f3cee9e7e65a12b0ebe","score":"0.6722733","text":"def buildLeaderboard(self):\n\t\toverall_standings = []\n\t\toverall_fpl_points = {}\n\t\toverall_league_points = {}\n\t\toverall_fines = {}\n\t\tgameweeks = {}\n\t\tfor i in self.league.league_gameweeks:\n\t\t\tgameweeks[i.fpl_event] = []\n\t\tfor i in self.members:\n\t\t\toverall_fpl_points[i] = 0\n\t\t\toverall_league_points[i] = 0\n\t\t\toverall_fines[i] = 0\n\t\t\trunning_league_points = 0\n\t\t\tfor j in i.league_gameweeks:\n\t\t\t\t\tif j.league_id == self.league.league_id:\n\t\t\t\t\t\toverall_fpl_points[i] += j.fpl_points\n\t\t\t\t\t\toverall_league_points[i] += j.championship_points\n\t\t\t\t\t\toverall_fines[i] += j.fines\n\t\t\t\t\t\trunning_league_points += j.championship_points\n\t\t\t\t\t\tgameweeks[j.fpl_event].append({\n\t\t\t\t\t\t\t'player': j.user,\n\t\t\t\t\t\t\t'fpl_points': j.fpl_points,\n\t\t\t\t\t\t\t'league_points': j.championship_points,\n\t\t\t\t\t\t\t'running_league_points': running_league_points,\n\t\t\t\t\t\t\t'fines': j.fines,\n\t\t\t\t\t\t\t'notes': j.notes\n\t\t\t\t\t\t\t})\n\t\tfor i in gameweeks:\n\t\t\tnewlist = sorted(gameweeks[i], key=lambda k: k['fpl_points'], reverse=True)\n\t\t\tgameweeks[i] = newlist\n\t\tfor i in overall_fpl_points:\n\t\t\toverall_standings.append({'player': i.username, 'fpl_points': overall_fpl_points[i], 'P & L': '+£69'})\n\t\tfor i in overall_league_points:\n\t\t\tfor j in overall_standings:\n\t\t\t\tif j['player'] == i.username:\n\t\t\t\t\tj['league_points'] = overall_league_points[i]\n\t\tfor i in overall_fines:\n\t\t\tfor j in overall_standings:\n\t\t\t\tif j['player'] == i.username:\n\t\t\t\t\tj['fines'] = overall_fines[i]\n\t\tsorted_overall = sorted(overall_standings, key=lambda k: k['league_points'], reverse=True)\n\t\tself.leaderboard = sorted_overall\n\t\tself.gameweeks = gameweeks","title":""},{"docid":"f494a072a544585cb57a2fab8d31f093","score":"0.6574417","text":"def make_leaderboard(self):\n leaderboard = [(player_id, rating.mu - 3*rating.sigma) for player_id, rating in self._ratings.items()]\n leaderboard = sorted(leaderboard, key=operator.itemgetter(1), reverse=True)\n return leaderboard","title":""},{"docid":"cafa310f61b85a6ec569e99cfafaa7c9","score":"0.65529096","text":"async def leaderboard(self, ctx: commands.Context):\n\n\t\treturn await ctx.send(await TrophyLeaderboard(ctx).create())","title":""},{"docid":"b74ed25514064c5e10d0a2346470cd3a","score":"0.6290081","text":"def displayLeaderboard():\n\n global leaderboard\n\n Y_OFFSET = 50\n TOP_OFFSET = 150\n\n leaderboard_title = largeFont.render(\"Leader Board\", True, BLACK)\n leaderboard_titleRect = leaderboard_title.get_rect()\n leaderboard_titleRect.center = ((WIN_WIDTH / 2), 50)\n screen.blit(leaderboard_title, leaderboard_titleRect)\n\n for idx, person in enumerate(leaderboard):\n person_entry_txt = person[0] + '.'\n person_entry_txt += (' ') + person[1]\n\n leaderboard_entry = mediumFont.render(person_entry_txt, True, BLACK)\n leaderboard_entryRect = leaderboard_entry.get_rect()\n leaderboard_entryRect.bottomleft = ((WIN_WIDTH / 4), TOP_OFFSET + Y_OFFSET * idx)\n screen.blit(leaderboard_entry, leaderboard_entryRect)\n\n score_entry_txt = person[2]\n rightAlign = mediumFont.size(person[2])[0]\n\n leaderboard_entryScore = mediumFont.render(score_entry_txt, True, BLACK)\n leaderboard_entryScoreRect = leaderboard_entryScore.get_rect()\n leaderboard_entryScoreRect.bottomleft = ((3 * WIN_WIDTH / 4) - rightAlign, TOP_OFFSET + Y_OFFSET * idx)\n screen.blit(leaderboard_entryScore, leaderboard_entryScoreRect)","title":""},{"docid":"29930feaccab07b2952f3ab60de65a3e","score":"0.6228906","text":"async def leaderboard(self, ctx):\n leaderboard = await self.bot.database.get_top_reps()\n embed = discord.Embed(colour=EMBED_ACCENT_COLOUR)\n embed.set_author(\n name=\"Reputation Leaderboard\",\n icon_url=\"https://images.emojiterra.com/mozilla/512px/1f3c6.png\",\n )\n for member_id, points in leaderboard:\n member = ctx.guild.get_member(member_id)\n if member:\n embed.add_field(\n name=str(member.nick if member.nick is not None else member.name),\n value=points,\n inline=False,\n )\n await ctx.send(embed=embed)","title":""},{"docid":"6d25344c35e84a3b8b9d248159286e44","score":"0.6203027","text":"def leaderboard(self, id):\n from .game import GameLeaderboard\n return GameLeaderboard.leaderboard(self.short_name, id)","title":""},{"docid":"b68db73095cfe00a7258b97ef6b10d3f","score":"0.61703","text":"async def leaderboard(self, ctx):\r\n guild = ctx.guild.id\r\n users = await self.bot.db.fetch(\"SELECT * FROM levels WHERE guild_id=$1 ORDER BY xp DESC\", guild)\r\n\r\n ranks = {(y := x + 1): f\"#{y}\" if y > 3 else f\"{self.leaderboard_emojis[y]}\" for x in range(10)}\r\n fields = {\"member\": [], \"level\": [], \"rank\": []}\r\n\r\n for index, value in zip(range(10), users):\r\n user = self.bot.get_user(value[\"user_id\"])\r\n if user:\r\n if (rank := index + 1) == 1:\r\n top_user = f\"Top Member: 🏆 **{str(user)}**\"\r\n fields[\"rank\"].append(ranks[rank])\r\n fields[\"member\"].append(f\"**{user.name}**\")\r\n xp = round((4 * (value['lvl'] ** 3) / 5))\r\n fields[\"level\"].append(f\"Level {value['lvl']} ({value['xp']}/{xp})\")\r\n else:\r\n for value in fields.values():\r\n value.append(\"...\")\r\n\r\n leaderboard = discord.Embed(color=ctx.me.colour, title=f\"Top 10 in {ctx.guild.name}\", description=top_user,\r\n timestamp=ctx.message.created_at)\r\n leaderboard.set_author(name=ctx.author.name, icon_url=ctx.author.avatar_url)\r\n\r\n author = await self.bot.db.fetchrow(\"SELECT * FROM levels WHERE user_id=$1 AND guild_id=$2\",\r\n ctx.author.id, guild)\r\n\r\n if author:\r\n fields[\"rank\"].append(ranks[users.index(author) + 1])\r\n fields[\"member\"].append(f\"**{ctx.author.name}**\")\r\n xp = round((4 * (author['lvl'] ** 3) / 5))\r\n fields[\"level\"].append(f\"Level {author['lvl']} ({author['xp']}/{xp})\")\r\n\r\n leaderboard.add_field(name=\"Rank\", value=\"\\n\".join(fields[\"rank\"]), inline=True)\r\n leaderboard.add_field(name=\"Member\", value=\"\\n\".join(fields[\"member\"]), inline=True)\r\n leaderboard.add_field(name=\"Level\", value=\"\\n\".join(fields[\"level\"]), inline=True)\r\n\r\n await ctx.send(embed=leaderboard)","title":""},{"docid":"8b902558ddeb9651656b204c2bbf7032","score":"0.6161494","text":"def display_points(self) -> List[dict]:\n self.log.debug('Generating scores...')\n score_df = self.get_score(in_game=True) # type: pd.DataFrame\n self.log.debug(f'Retrieved {score_df.shape[0]} players\\' scores')\n if score_df.shape[0] == 0:\n return [\n BKitB.make_block_section('No one has scored yet. Check back later!')\n ]\n score_df.loc[:, 'rank_emoji'] = [':blank:' for _ in range(score_df.shape[0])]\n if score_df['current'].sum() != 0:\n # Determine the emojis for 1st, 2nd and 3rd place\n is_zero = (score_df.current == 0)\n for r in range(1, 6):\n score_df.loc[(score_df.current_rank == r) & (~is_zero), 'rank_emoji'] = f':cah-rank-{r}:'\n # Determine if the recent winner is on a streak\n score_df['streak'] = ''\n if self.current_game is not None:\n player_id, n_streak = self.determine_streak()\n if n_streak > 0:\n # Streak!\n score_df.loc[score_df.player_id == player_id, 'streak'] = ':steak:' * n_streak\n # Set order of the columns\n score_df = score_df[['rank_chg_emoji', 'rank_emoji', 'current_rank', 'display_name',\n 'current', 'overall', 'streak']]\n score_df = score_df.sort_values('current_rank', ascending=True)\n\n scores_list = []\n for i, r in score_df.iterrows():\n dname = f\"{r['display_name'][:14].title():_<15}\"\n emos = f\"{r['rank_chg_emoji'] + r['rank_emoji']}\"\n c_rank = f\"{r['current_rank']:>2.0f}\"\n scores = f\"*`{r['current']:>4.0f}`*`({r['overall']:>4.0f})`\"\n streak = f\"{r['streak']}\"\n line = f\"{emos}*`{c_rank}`*` {dname}`:diddlecoin:{scores}{streak}\"\n scores_list.append(line)\n\n return [\n BKitB.make_context_section([BKitB.markdown_section('*Current Scores*')]),\n BKitB.make_block_divider(),\n BKitB.make_block_section(scores_list)\n ]","title":""},{"docid":"3b85cda051d1b14514e22f0914e73c40","score":"0.6047141","text":"def show_leaderboard_screen(self):\n self.leaderboard.retrieve()\n self.clear()\n self.add_button(\"Back\", self.show_main_screen)\n\n if self.leaderboard.entries is None:\n self.add_button(\"Error Loading Leaderboard\", None)\n else:\n for i in range(0, 4 if len(self.leaderboard.entries) > 6 else len(self.leaderboard.entries)):\n entry = self.leaderboard.entries[i]\n self.add_button(entry.name + \" Lvl=\" + entry.level + \" Scr=\" + str(entry.score) + \" Wve=\" + str(entry.wave), None)","title":""},{"docid":"74ac9d9e21fe3d8009430143163d4ee6","score":"0.60361916","text":"def load_leaderboard(self, name: str, show: bool = False) -> list:\n leaderboard = []\n members = self.__find_models(name, leaderboard_prefix)\n if len(members) > 0:\n for member in members:\n self.cursor.execute(\n f\"SELECT * FROM {self.schema}.{PREPROCESSORS} WHERE MODEL = '{member[0]}' \"\n f\"AND VERSION = {member[1]}\"\n )\n columns = self.cursor.fetchall()[\n 0\n ] # MODEL, VERSION, JSON, TRAIN_ACC, VALID_ACC, ALGORITHM, METRIC\n prep = self.__setup_preprocessor(columns[2])\n if \"Regressor\" in columns[5]:\n algo = self.reg_dict[columns[5]]\n if \"Classifier\" in columns[5]:\n algo = self.cls_dict[columns[5]]\n algo.model = super().load_model(member[0], member[1])\n algo.title = columns[5]\n model_board_member = ModelBoard(algo, 0, prep)\n model_board_member.valid_score = columns[4]\n model_board_member.train_score = columns[3]\n leaderboard.append(model_board_member)\n if show:\n print(\"\\033[33m{}\".format(f\"Loaded leaderboard '{name}':\\n\"))\n place = 1\n for member in leaderboard:\n print(\n \"\\033[33m {}\".format(\n str(place)\n + \". \"\n + str(member.algorithm.model)\n + f\"\\n Train {columns[6]} score: \"\n + str(member.train_score)\n + f\"\\n Holdout {columns[6]} score: \"\n + str(member.valid_score)\n )\n )\n print(\"\\033[0m {}\".format(\"\"))\n place += 1\n else:\n raise StorageError(\"Leaderboard not found!\")\n return leaderboard","title":""},{"docid":"6c44c80cea96895f9c3990277d80b4dc","score":"0.5880609","text":"def rd1leaderboard(request):\n\n #Add views\n playing_players = Rd1SlotModel.objects.filter(player_name__isnull=False)\n\n endurance_leader = Rd1SlotModel.objects.aggregate(Max('endurance_score'))\n\n #Add context\n context = {\n 'playing_players': playing_players,\n 'endurance_leader': endurance_leader,\n }\n\n return render(request, 'rd1Leaderboard.html', context=context)","title":""},{"docid":"b70190aa8df97b0bc7195b975aee1d0b","score":"0.5836765","text":"def leaderboard():\n #allows the leaderboard to be viewed without updating/adding to it\n if request.method == 'POST':\n new_leaderboard_name = request.form[\"leaderboard_name\"] #store the users input name\n #add the new highscore to the database\n new_highscore= User(username=new_leaderboard_name, score=flask_session['user_score'])\n db.session.add(new_highscore)\n db.session.commit()\n\n leaderboard = User.query.order_by(desc(User.score)).limit(10).all()\n\n return render_template('leaderboard.html', leaderboard=leaderboard)","title":""},{"docid":"f4837939975e559645382e5d71401c45","score":"0.58296454","text":"def fullleaderboard (request):\n # Define views here\n score_submit = EventEntryModel.objects.exclude(winner__isnull=True).count()\n active_players = PlayerModel.objects.all()\n\n loaded_points = list(EventEntryModel.objects.aggregate(Sum('points')).values())[0]\n awarded_points = list(EventEntryModel.objects.exclude(winner__isnull=True).aggregate(Sum('points')).values())[0]\n\n context = {\n 'score_submit': score_submit,\n 'active_players': active_players,\n 'loaded_points': loaded_points,\n 'awarded_points': awarded_points,\n 'tour_name_top_line': tour_name_top_line,\n 'tour_name_highlight': tour_name_highlight,\n }\n return render(request, 'fullLeaderboard.html', context=context)","title":""},{"docid":"7dd6028e15ece7f8f95d3f3b2a0caa2c","score":"0.5812916","text":"async def _server_leaderboard(self, ctx, top : int=10):\n server = ctx.message.server\n if top < 1:\n top = 10\n bank_sorted = sorted(self.bank.get_server_accounts(server),\n key=lambda x: x.balance, reverse=True)\n if len(bank_sorted) < top:\n top = len(bank_sorted)\n topten = bank_sorted[:top]\n highscore = \"\"\n place = 1\n for acc in topten:\n highscore += str(place).ljust(len(str(top))+1)\n highscore += (acc.name+\" \").ljust(23-len(str(acc.balance)))\n highscore += str(acc.balance) + \"\\n\"\n place += 1\n if highscore:\n if len(highscore) < 1985:\n await self.bot.say(\"```py\\n\"+highscore+\"```\")\n else:\n await self.bot.say(\"```css\\nThe leaderboard is too big to be displayed. Try with a lower <top> parameter.\\n```\")\n else:\n await self.bot.say(\"```css\\nThere are no accounts in the bank.\\n```\")","title":""},{"docid":"bbabea782c7d022c2385f13b6aa721c6","score":"0.5779456","text":"def test_get_leaderboard(self):\n pass","title":""},{"docid":"dae9a8857eb42415296cdc731bc2346e","score":"0.57685685","text":"async def leaderboard(self, ctx, *args):\r\n if ctx.channel.id == BANK_CHANNEL or ctx.channel.id in GENERAL_CHANNELS:\r\n if len(args) == 0:\r\n name = None\r\n key = 'total'\r\n elif len(args) == 1:\r\n if 'key=' in args[0]:\r\n name = None\r\n for userkey in users.DEFAULT_ACCOUNT.keys():\r\n if args[0][4:] in userkey:\r\n key = userkey\r\n break\r\n else:\r\n if args[0][4:] == 'total':\r\n key = 'total'\r\n else:\r\n await ctx.send(f'Key {args[0]} not found.')\r\n return\r\n\r\n else:\r\n name = args[0]\r\n key = 'total'\r\n else:\r\n key = args[0]\r\n if key not in users.DEFAULT_ACCOUNT.keys():\r\n if key != 'total':\r\n await ctx.send(f'Key {key} not found.')\r\n return\r\n name = ' '.join(args[1:])\r\n\r\n key_name = {\r\n users.ITEMS_KEY: 'gold',\r\n users.SLAYER_XP_KEY: 'slayer',\r\n users.COMBAT_XP_KEY: 'combat',\r\n users.GATHER_XP_KEY: 'gather',\r\n users.ARTISAN_XP_KEY: 'artisan',\r\n users.COOK_XP_KEY: 'cooking',\r\n users.QUESTS_KEY: 'quest points',\r\n 'total': 'total level'\r\n }\r\n if key not in key_name.keys():\r\n await ctx.send(f\"Can't make leaderboard with key {key}.\")\r\n return\r\n\r\n leaderboard = users.get_values_by_account(key=key)\r\n\r\n out = f':hammer_pick: __**{key.upper()} LEADERBOARD**__ :crossed_swords:\\n'\r\n if name is None:\r\n try:\r\n for i in range(10):\r\n user_id, amount = leaderboard[i]\r\n amount_formatted = '{:,}'.format(amount)\r\n member = ctx.message.guild.get_member(user_id)\r\n if member is not None:\r\n name = get_display_name(member)\r\n else:\r\n name = f'User {user_id}'\r\n out += f'**({1 + i}) {name}**: '\r\n if key == users.ITEMS_KEY:\r\n out += f'{amount_formatted} coins\\n'\r\n elif key == users.QUESTS_KEY:\r\n out += f'{amount_formatted} quests\\n'\r\n elif key == 'total':\r\n out += f'{amount_formatted} levels\\n'\r\n else:\r\n out += f'{users.xp_to_level(amount)} *({amount_formatted}xp)*\\n'\r\n except IndexError:\r\n pass\r\n await ctx.send(out)\r\n else:\r\n if name == 'bottom':\r\n try:\r\n for i in range(len(leaderboard) - 10, len(leaderboard)):\r\n user_id, amount = leaderboard[i]\r\n amount_formatted = '{:,}'.format(amount)\r\n member = ctx.message.guild.get_member(user_id)\r\n if member is not None:\r\n name = get_display_name(member)\r\n else:\r\n name = f'User {user_id}'\r\n out += f'**({1 + i}) {name}**: '\r\n if key == users.ITEMS_KEY:\r\n out += f'{amount_formatted} coins\\n'\r\n elif key == users.QUESTS_KEY:\r\n out += f'{amount_formatted} quests\\n'\r\n elif key == 'total':\r\n out += f'{amount_formatted} levels\\n'\r\n else:\r\n out += f'{users.xp_to_level(amount)} *({amount_formatted}xp)*\\n'\r\n except IndexError:\r\n pass\r\n await ctx.send(out)\r\n else:\r\n try:\r\n name_list = [x[0] for x in leaderboard]\r\n name_member = parse_name(ctx.message.guild, name)\r\n name_index = name_list.index(name_member.id)\r\n if name_index < 5:\r\n lower = 0\r\n upper = 10\r\n else:\r\n lower = name_index - 5\r\n upper = name_index + 5\r\n if name_index + 5 > len(leaderboard):\r\n upper = len(leaderboard)\r\n lower = len(leaderboard) - 10\r\n for i in range(lower, upper):\r\n user_id, amount = leaderboard[i]\r\n amount_formatted = '{:,}'.format(amount)\r\n member = ctx.message.guild.get_member(user_id)\r\n if member is not None:\r\n name = get_display_name(member)\r\n else:\r\n name = f'User {user_id}'\r\n out += f'**({1 + i}) {name}**: '\r\n if key == users.ITEMS_KEY:\r\n out += f'{amount_formatted} coins\\n'\r\n elif key == users.QUESTS_KEY:\r\n out += f'{amount_formatted} quests\\n'\r\n elif key == 'total':\r\n out += f'{amount_formatted} levels\\n'\r\n else:\r\n out += f'{users.xp_to_level(amount)} *({amount_formatted}xp)*\\n'\r\n except IndexError:\r\n pass\r\n except ValueError:\r\n await ctx.send(f'Name {name} not found in leaderboard.')\r\n await ctx.send(out)","title":""},{"docid":"6502ffba2dbced13f2f4a4f9f966cc3f","score":"0.5761324","text":"def compose(canvas):\n #Write the score for each player\n canvas.draw_text('Blue '+str(blue_score_G),[60,585],30,'Blue')\n canvas.draw_text('Brown '+str(brown_score_G),[430,585],30,'Brown')\n #Draw the grid unless there is no winner\n if get_winner()==0:\n boardDraw=Draw()\n boardDraw.draw_board(canvas)\n set_pieces(canvas,0,0)\n #Draw winner box\n #Brown is the winner\n elif get_winner()==1:\n brownWinsDraw=Draw()\n brownWinsDraw.draw_winner(canvas,'Brown') \n #Blue is the winner \n elif get_winner()==-1:\n blueWinsDraw=Draw()\n blueWinsDraw.draw_winner(canvas,'Blue')","title":""},{"docid":"798b9d5c1c3c546cf1dc37ee60c9219d","score":"0.5759699","text":"def getleaderboard(request):\n note_session_activity(request)\n\n if not using_unique_session(request.user):\n return HttpResponseForbidden()\n\n owner_filter = request.GET['owner_filter']\n body_pk = int(request.GET['legislative_body'])\n leg_body = LegislativeBody.objects.get(pk=body_pk)\n\n display = getleaderboarddisplay(leg_body, owner_filter)\n if display is None:\n return HttpResponse(\n _('No display configured'), content_type='text/plain')\n\n plans = getvalidplans(leg_body, request.user\n if owner_filter == 'mine' else None)\n\n try:\n html = display.render(plans, request)\n return HttpResponse(html, content_type='text/html; charset=utf-8')\n except Exception, ex:\n logger.warn('Leaderboard could not be fetched.')\n logger.debug('Reason: %s', ex)\n return HttpResponse(str(ex), content_type='text/plain')","title":""},{"docid":"4c5183029122dd3245874568b3b70244","score":"0.57568544","text":"def make_leaderboard(object, leaderboard_frame=None,\n sort_metric=\"AUTO\",\n extra_columns=[],\n scoring_data=\"AUTO\"):\n def _get_models(obj):\n if isinstance(obj, list):\n result = []\n for o in obj:\n res = _get_models(o)\n if isinstance(res, list):\n result.extend(res)\n else:\n result.append(res)\n return result\n elif hasattr(obj, \"leaderboard\"):\n return [row[0] for row in obj.leaderboard.as_data_frame(use_pandas=False, header=False)]\n elif hasattr(obj, \"model_ids\"):\n return obj.model_ids\n elif hasattr(obj, \"model_id\"):\n return obj.model_id\n elif is_type(obj, str):\n return obj\n else:\n raise H2OValueError(\"Unsupported model_id!\")\n\n model_ids = _get_models(object)\n assert is_type(model_ids, [str])\n\n if scoring_data.lower() not in (\"auto\", \"train\", \"valid\", \"xval\"):\n raise H2OValueError(\"Scoring data has to be set to one of \\\"AUTO\\\", \\\"train\\\", \\\"valid\\\", \\\"xval\\\".\")\n\n m_frame = H2OFrame._expr(ExprNode(\n \"makeLeaderboard\",\n model_ids,\n leaderboard_frame.key if leaderboard_frame is not None else \"\",\n sort_metric,\n extra_columns,\n scoring_data))\n return m_frame","title":""},{"docid":"752d02403c47af838429a85f865b45d0","score":"0.57278216","text":"def leaderboards(self):\n from .game import GameLeaderboard\n return GameLeaderboard.leaderboards(self.short_name)","title":""},{"docid":"7bddd05f16c5849c0de06c1619c399ae","score":"0.57092756","text":"def generate_board():\n\t# score_label.config(text=str(b.score))\n\t# score_label.after(100, generate_board)\n\tfor i in range(len(b.board)):\n\t\tfor j in range(len(b.board[0])):\n\t\t\tnum = b.board[i][j]\n\t\t\tbackground_color = color_map[num]\n\t\t\tcanvas.create_rectangle(j*100, i*100, (j+1)*100, (i+1)*100, fill=background_color)\n\t\t\tif num != 0:\n\t\t\t\tif num == 2 or num == 4:\n\t\t\t\t\tnum_color = \"#776e65\"\n\t\t\t\telse:\n\t\t\t\t\tnum_color = \"#f9f6f2\"\n\t\t\t\tcanvas.create_text(j*100 + offset_map[num], i*100 + 50, anchor=tk.W, font=(\"Arial\", size_map[num]), text=str(num), fill=num_color)","title":""},{"docid":"9674bbc8fbb9aa414e0df80fccf220de","score":"0.5705014","text":"async def _global_leaderboard(self, top : int=10):\n if top < 1:\n top = 10\n bank_sorted = sorted(self.bank.get_all_accounts(),\n key=lambda x: x.balance, reverse=True)\n unique_accounts = []\n for acc in bank_sorted:\n if not self.already_in_list(unique_accounts, acc):\n unique_accounts.append(acc)\n if len(unique_accounts) < top:\n top = len(unique_accounts)\n topten = unique_accounts[:top]\n highscore = \"\"\n place = 1\n for acc in topten:\n highscore += str(place).ljust(len(str(top))+1)\n highscore += (\"{} |{}| \".format(acc.name, acc.server.name)).ljust(23-len(str(acc.balance)))\n highscore += str(acc.balance) + \"\\n\"\n place += 1\n if highscore:\n if len(highscore) < 1985:\n await self.bot.say(\"```py\\n\"+highscore+\"```\")\n else:\n await self.bot.say(\"```css\\nThe leaderboard is too big to be displayed. Try with a lower <top> parameter.\\n```\")\n else:\n await self.bot.say(\"```css\\nThere are no accounts in the bank.\\n```\")","title":""},{"docid":"5e04c5112c4339c0075facf6aa06ceb6","score":"0.5663041","text":"def scoreboard():\r\n scores = {}\r\n for user in models.User.query.all():\r\n if user.is_admin:\r\n continue\r\n user.solved_questions = list(filter(lambda x: not x.question.hide, user.solved_questions))\r\n scores[user.get_id()] = { 'username' : user.username, 'score': user.total_score, 'last_question_date': user.solved_questions[len(user.solved_questions)-1].date if len(user.solved_questions) > 0 else datetime.datetime.min }\r\n\r\n scores = helpers.sortScoreDict(scores)\r\n \"\"\"\r\n enumerate generates indices for the orderedDict\r\n \"\"\"\r\n return render_template(\"scoreboard.html\",scores=enumerate(scores.items()))","title":""},{"docid":"beb981b58ae7a0cf2ba16781b2f09256","score":"0.5655952","text":"def playerdetail (request,name):\n\n #Basic player details\n player_image = PlayerModel.objects.get(name=name).image\n player_HC = PlayerModel.objects.get(name=name).HC\n player_highfinish = PlayerModel.objects.get(name=name).highfinish\n player_tournum = PlayerModel.objects.get(name=name).tournum\n player_totalpoints = LeaderBoardModel.objects.get(player=name).overall_total\n player_totalrank = LeaderBoardModel.objects.filter(overall_total__gt=player_totalpoints).count() + 1\n\n\n target_holes = 10 #Change to 10 in production\n\n ##START ROUND 1 CALCULATIONS -->\n #Trigger to show score only when round finished\n try:\n rd1holes_played = Rd1SlotModel.objects.get(player_name__name=name).player_holesplayed\n if rd1holes_played is None:\n rd1holes_played = 0\n else:\n rd1holes_played = Rd1SlotModel.objects.get(player_name__name=name).player_holesplayed\n except:\n rd1holes_played = 0\n\n\n\n #Rd1 Player golf score & rank\n if rd1holes_played >= target_holes:\n rd1golf_score = Rd1SlotModel.objects.get(player_name__name=name).player_score\n rd1golf_scoreRank = Rd1SlotModel.objects.filter(player_score__lt=rd1golf_score).count() + 1\n rd1golf_stbl = Rd1SlotModel.objects.get(player_name__name=name).player_stbl\n rd1golf_stblRank = Rd1SlotModel.objects.filter(player_stbl__gt=rd1golf_stbl).count() + 1\n else:\n rd1golf_score = \"-\"\n rd1golf_scoreRank= \"n/a\"\n rd1golf_stbl = \"-\"\n rd1golf_stblRank= \"n/a\"\n\n #Rd1PlayerPoints\n try:\n rd1golf_points = LeaderBoardModel.objects.get(player=name).rd1_golf\n except:\n rd1golf_points = \"-\"\n try:\n rd1golf_rank = LeaderBoardModel.objects.filter(rd1_golf__gt=rd1golf_points).count() + 1\n except:\n rd1golf_rank = \"-\"\n try:\n rd1ctpld_points = LeaderBoardModel.objects.get(player=name).rd1_ctpld\n except:\n rd1ctpld_points = \"-\"\n try:\n rd1ctpld_rank = LeaderBoardModel.objects.filter(rd1_ctpld__gt=rd1ctpld_points).count() + 1\n except:\n rd1ctpld_rank = \"-\"\n try:\n rd1bonus_points = LeaderBoardModel.objects.get(player=name).rd1_bonus\n except:\n rd1bonus_points = \"-\"\n try:\n rd1bonus_rank = LeaderBoardModel.objects.filter(rd1_bonus__gt=rd1bonus_points).count() + 1\n except:\n rd1bonus_rank = \"-\"\n try:\n rd1total_points = rd1golf_points + rd1ctpld_points + rd1bonus_points\n except:\n rd1total_points = \"-\"\n try:\n rd1total_rank = LeaderBoardModel.objects.filter(rd1_total__gt=rd1total_points).count() + 1\n except:\n rd1total_rank = \"-\"\n\n try:\n round1overall_points = list(LeaderBoardModel.objects.aggregate(Sum('rd1_total')).values())[0]\n except:\n round1overall_points = 0\n\n\n ##START ROUND 2 CALCULATIONS -->\n #Trigger to show score only when round finished\n try:\n rd2holes_played = Rd2SlotModel.objects.get(player_name__name=name).player_holesplayed\n if rd2holes_played is None:\n rd2holes_played = 0\n else:\n rd2holes_played = Rd2SlotModel.objects.get(player_name__name=name).player_holesplayed\n except:\n rd2holes_played = 0\n\n #Rd2 Player golf score & rank\n if rd2holes_played >= target_holes:\n rd2golf_score = Rd2SlotModel.objects.get(player_name__name=name).player_score\n rd2golf_scoreRank = Rd2SlotModel.objects.filter(player_score__lt=rd2golf_score).count() + 1\n rd2golf_stbl = Rd2SlotModel.objects.get(player_name__name=name).player_stbl\n rd2golf_stblRank = Rd2SlotModel.objects.filter(player_stbl__gt=rd2golf_stbl).count() + 1\n else:\n rd2golf_score = \"-\"\n rd2golf_scoreRank= \"n/a\"\n rd2golf_stbl = \"-\"\n rd2golf_stblRank= \"n/a\"\n\n #Rd2PlayerPoints\n try:\n rd2golf_points = LeaderBoardModel.objects.get(player=name).rd2_golf\n except:\n rd2golf_points = \"-\"\n try:\n rd2golf_rank = LeaderBoardModel.objects.filter(rd2_golf__gt=rd2golf_points).count() + 1\n except:\n rd2golf_rank = \"-\"\n try:\n rd2ctpld_points = LeaderBoardModel.objects.get(player=name).rd2_ctpld\n except:\n rd2ctpld_points = \"-\"\n try:\n rd2ctpld_rank = LeaderBoardModel.objects.filter(rd2_ctpld__gt=rd2ctpld_points).count() + 1\n except:\n rd2ctpld_rank = \"-\"\n try:\n rd2bonus_points = LeaderBoardModel.objects.get(player=name).rd2_bonus\n except:\n rd2bonus_points = \"-\"\n try:\n rd2bonus_rank = LeaderBoardModel.objects.filter(rd2_bonus__gt=rd2bonus_points).count() + 1\n except:\n rd2bonus_rank = \"-\"\n try:\n rd2total_points = rd2golf_points + rd2ctpld_points + rd2bonus_points\n except:\n rd2total_points = \"-\"\n try:\n rd2total_rank = LeaderBoardModel.objects.filter(rd2_total__gt=rd2total_points).count() + 1\n except:\n rd2total_rank = \"-\"\n\n try:\n round2overall_points = list(LeaderBoardModel.objects.aggregate(Sum('rd2_total')).values())[0]\n except:\n round2overall_points = 0\n\n ##START ROUND 3 CALCULATIONS -->\n #Trigger to show score only when round finished\n try:\n rd3holes_played = Rd3SlotModel.objects.get(player_name__name=name).player_holesplayed\n if rd3holes_played is None:\n rd3holes_played = 0\n else:\n rd3holes_played = Rd3SlotModel.objects.get(player_name__name=name).player_holesplayed\n except:\n rd3holes_played = 0\n\n #Rd3 Player golf score & rank\n if rd3holes_played >= target_holes:\n rd3golf_score = Rd3SlotModel.objects.get(player_name__name=name).player_score\n rd3golf_scoreRank = Rd3SlotModel.objects.filter(player_score__lt=rd2golf_score).count() + 1\n rd3golf_stbl = Rd3SlotModel.objects.get(player_name__name=name).player_stbl\n rd3golf_stblRank = Rd3SlotModel.objects.filter(player_stbl__gt=rd2golf_stbl).count() + 1\n else:\n rd3golf_score = \"-\"\n rd3golf_scoreRank= \"n/a\"\n rd3golf_stbl = \"-\"\n rd3golf_stblRank= \"n/a\"\n\n #Rd2PlayerPoints\n try:\n rd3golf_points = LeaderBoardModel.objects.get(player=name).rd3_golf\n except:\n rd3golf_points = \"-\"\n try:\n rd3golf_rank = LeaderBoardModel.objects.filter(rd3_golf__gt=rd3golf_points).count() + 1\n except:\n rd3golf_rank = \"-\"\n try:\n rd3ctpld_points = LeaderBoardModel.objects.get(player=name).rd3_ctpld\n except:\n rd3ctpld_points = \"-\"\n try:\n rd3ctpld_rank = LeaderBoardModel.objects.filter(rd3_ctpld__gt=rd3ctpld_points).count() + 1\n except:\n rd3ctpld_rank = \"-\"\n try:\n rd3bonus_points = LeaderBoardModel.objects.get(player=name).rd3_bonus\n except:\n rd3bonus_points = \"-\"\n try:\n rd3bonus_rank = LeaderBoardModel.objects.filter(rd3_bonus__gt=rd3bonus_points).count() + 1\n except:\n rd3bonus_rank = \"-\"\n try:\n rd3total_points = rd3golf_points + rd3ctpld_points + rd3bonus_points\n except:\n rd3total_points = \"-\"\n try:\n rd3total_rank = LeaderBoardModel.objects.filter(rd3_total__gt=rd3total_points).count() + 1\n except:\n rd3total_rank = \"-\"\n\n try:\n round3overall_points = list(LeaderBoardModel.objects.aggregate(Sum('rd3_total')).values())[0]\n except:\n round3overall_points = 0\n\n ##START OTHER_SCORES CALCULATIONS -->\n\n #Other Player Points\n try:\n social_points = LeaderBoardModel.objects.get(player=name).social\n except:\n social_points = \"-\"\n try:\n social_rank = LeaderBoardModel.objects.filter(social__gt=social_points).count() + 1\n except:\n social_rank = \"-\"\n try:\n bestdressed_points = LeaderBoardModel.objects.get(player=name).best_dressed\n except:\n bestdressed_points = \"-\"\n try:\n bestdressed_rank = LeaderBoardModel.objects.filter(best_dressed__gt=bestdressed_points).count() + 1\n except:\n bestdressed_rank = \"-\"\n try:\n tipping_points = LeaderBoardModel.objects.get(player=name).tipping\n except:\n tipping_points = \"-\"\n try:\n tipping_rank = LeaderBoardModel.objects.filter(tipping__gt=tipping_points).count() + 1\n except:\n tipping_rank = \"-\"\n try:\n othertotal_points = social_points + bestdressed_points + tipping_points\n except:\n othertotal_points = \"-\"\n try:\n othertotal_rank = LeaderBoardModel.objects.filter(other_total__gt=othertotal_points).count() + 1\n except:\n othertotal_rank = \"-\"\n\n try:\n otheroverall_points = list(LeaderBoardModel.objects.aggregate(Sum('other_total')).values())[0]\n except:\n otheroverall_points = 0\n\n## == END SCORING CALCS ==\n\n context ={\n 'name': name,\n 'player_image': player_image,\n 'player_HC': player_HC,\n 'player_highfinish': player_highfinish,\n 'player_tournum': player_tournum,\n 'player_totalpoints': player_totalpoints,\n 'player_totalrank': player_totalrank,\n 'rd1golf_score': rd1golf_score,\n 'rd1golf_stbl': rd1golf_stbl,\n 'rd1golf_scoreRank': rd1golf_scoreRank,\n 'rd1golf_stblRank': rd1golf_stblRank,\n 'rd1golf_points': rd1golf_points,\n 'rd1golf_rank': rd1golf_rank,\n 'rd1ctpld_points': rd1ctpld_points,\n 'rd1ctpld_rank': rd1ctpld_rank,\n 'rd1bonus_points': rd1bonus_points,\n 'rd1bonus_rank': rd1bonus_rank,\n 'rd1total_points': rd1total_points,\n 'rd1total_rank': rd1total_rank,\n 'round1overall_points': round1overall_points,\n 'rd2golf_score': rd2golf_score,\n 'rd2golf_stbl': rd2golf_stbl,\n 'rd2golf_scoreRank': rd2golf_scoreRank,\n 'rd2golf_stblRank': rd2golf_stblRank,\n 'rd2golf_points': rd2golf_points,\n 'rd2golf_rank': rd2golf_rank,\n 'rd2ctpld_points': rd2ctpld_points,\n 'rd2ctpld_rank': rd2ctpld_rank,\n 'rd2bonus_points': rd2bonus_points,\n 'rd2bonus_rank': rd2bonus_rank,\n 'rd2total_points': rd2total_points,\n 'rd2total_rank': rd2total_rank,\n 'round2overall_points': round2overall_points,\n 'rd3golf_score': rd3golf_score,\n 'rd3golf_stbl': rd3golf_stbl,\n 'rd3golf_scoreRank': rd3golf_scoreRank,\n 'rd3golf_stblRank': rd3golf_stblRank,\n 'rd3golf_points': rd3golf_points,\n 'rd3golf_rank': rd3golf_rank,\n 'rd3ctpld_points': rd3ctpld_points,\n 'rd3ctpld_rank': rd3ctpld_rank,\n 'rd3bonus_points': rd3bonus_points,\n 'rd3bonus_rank': rd3bonus_rank,\n 'rd3total_points': rd3total_points,\n 'rd3total_rank': rd3total_rank,\n 'round3overall_points': round3overall_points,\n 'social_points': social_points,\n 'social_rank': social_rank,\n 'bestdressed_points': bestdressed_points,\n 'bestdressed_rank': bestdressed_rank,\n 'tipping_points': tipping_points,\n 'tipping_rank': tipping_rank,\n 'othertotal_points': othertotal_points,\n 'othertotal_rank': othertotal_rank,\n 'otheroverall_points': otheroverall_points,\n\n }\n\n return render(request, 'playerDetail.html', context=context)","title":""},{"docid":"e75b49b24fb2501d75bc989162072b39","score":"0.56511414","text":"def high_scores(self):\n self.top = tk.Toplevel(self._master,width=80,height = 80)\n self.top.title(\"Top 3\")\n top_label = tk.Label(self.top,text=\"Hight Scores\", bg = 'medium spring green')\n top_label.config(height =1, font = ((None,20)))\n top_label.pack(side = tk.TOP,fill = tk.X)\n first_player = tk.Label(self.top, text = '{0}:{1}s'.format(self.name[0],self._seconds))\n first_player.pack(side = tk.TOP)\n sec_player = tk.Label(self.top, text = '{0}:{1}s'.format(self.name[1],self._seconds))\n sec_player.pack(side = tk.TOP)\n th_player = tk.Label(self.top, text = '{0}:{1}s'.format(self.name[2],self._seconds))\n th_player.pack(side = tk.TOP)\n\n top_button = tk.Button(self.top, text = 'Done',command = self.done)\n top_button.pack(side = tk.TOP)","title":""},{"docid":"5b003ef09a068df920591e2a1618c889","score":"0.56331533","text":"def display_score_window(self):\r\n \r\n #does the score window exist?\r\n try:\r\n if self.score_window.winfo_exists() == 1:\r\n return\r\n except AttributeError:\r\n pass\r\n \r\n self.score_window = tkinter.Toplevel(self.board_window)\r\n\r\n #Player labels and scores\r\n ex_name = tkinter.Label(self.score_window, text='Excluded',\r\n font = self.prefs['disp_font'], fg = 'red')\r\n ex_name.grid(row = 0, column = 0, columnspan = 2)\r\n ex_score = tkinter.Label(self.score_window, textvariable=self.excluded_score,\r\n font = self.prefs['disp_font'], fg = 'red')\r\n ex_score.grid(row = 1, column = 0, columnspan = 2)\r\n \r\n for i,j in enumerate(self.players):\r\n col = (i+1) * 2\r\n \r\n p_name = tkinter.Label(self.score_window, text=j['name'], font = self.prefs['disp_font'])\r\n p_name.grid(row=0, column=col)\r\n\r\n p_score = tkinter.Label(self.score_window, textvariable=self.scores[i],\r\n font = self.prefs['disp_font'])\r\n p_score.grid(row = 1, column = col, columnspan = 2)","title":""},{"docid":"82295137e8c69672c468eeb11df2a14e","score":"0.5604512","text":"def _get_highscore(self):\n self._player_list = player_list = self._highscore.get_entries(game='basic')\n \n self.high_scores=tk.Toplevel(root)\n self.high_scores.title('High Score List')\n\n self.high_score_title = tk.Label(self.high_scores, text= 'Top 10 Players\\n')\n self.high_score_title.pack()\n\n for i, player_list in enumerate(player_list): # List top scoring players from 1 to 10 format\n self.high_score_list = tk.Label(self.high_scores, text = \"[{}] ,{}\\n\".format(i+1,player_list)).pack()","title":""},{"docid":"4e9eacde1f1ec23048979852d73d99a7","score":"0.5563783","text":"async def leaderboard(self, ctx):\n if ctx.invoked_subcommand is None:\n await ctx.invoke(self._server_leaderboard)","title":""},{"docid":"c65811e0ee90fe44e7802c6af4baf24a","score":"0.5561256","text":"def test_scoreboard(self):\n run.add_to_scoreboard(\"testSuite\", 12)\n leaderboard = run.get_scoreboard()\n \n self.assertIn({\"username\":\"testSuite\", \"score\": 12}, leaderboard)","title":""},{"docid":"bb66f89263be375665c7f7303c124495","score":"0.555781","text":"def __repr__(self):\n if self._repr is None:\n # Player 0 scoring area\n if self.turn == 1:\n rows = [\" --\", \">| \", \" | \", \" | \", \" --\"]\n else:\n rows = [\" --\", \" | \", \" | \", \">| \", \" --\"]\n rows[2] += str(self.scores[0]) + \" |\"\n for r in [0,4]:\n rows[r] += \"-\"*(len(str(self.scores[0])) + 2)\n for r in [1,3]:\n rows[r] += \" \"*len(str(self.scores[0])) + \" |\"\n # houses\n for h in range(self.houses.shape[1]):\n width = len(str(self.houses[:,h].max()))\n for r in [1,3]:\n rows[r] += \" \" + str(self.houses[r//2,h])\n rows[r] += \" \"*(width - len(str(self.houses[r//2,h]))) +\" |\"\n for r in [0,2,4]:\n rows[r] += \"-\"*(width + 3)\n rows[2] = rows[2][:-1] + \"|\"\n # player 1 scoring area\n rows[2] += \" \" + str(self.scores[1]) + \" |\\n\"\n for r in [0,4]:\n rows[r] += \"-\"*(len(str(self.scores[1])) + 2) + \"\\n\"\n for r in [1,3]:\n rows[r] += \" \"*len(str(self.scores[1])) + \" |\"\n if self.turn == 1:\n rows[1] += \"<\\n\"\n rows[3] += \"\\n\"\n else:\n rows[1] += \"\\n\"\n rows[3] += \"<\\n\"\n self._repr = \"\".join(rows)\n return self._repr","title":""},{"docid":"648e2b9738edcdc22360410c3f34ba3b","score":"0.55369973","text":"def showCurrentRankings(self):\n \n font = pygame.font.Font(self.fontSrc, self.fontSize - self.fontSize//6)\n sorted_players = sorted([p for p in self.players], key=lambda x: x.rank)\n headerRankTxt = font.render(\"Here are the rankings:\", True, (0,0,0))\n widthTxt, heightTxt = font.size(\"Here are the rankings:\")\n self.screen.blit(headerRankTxt, (self.width//2 - widthTxt//2, (self.height//2 - heightTxt*2) + self.height//6))\n\n for i in range(len(self.players)):\n sufixes = {1: \"st\", 2: \"nd\", 3: \"rd\", 4: \"th\"}\n p = sorted_players[i]\n playerTxt = font.render(str(p.rank) + sufixes[p.rank] + \": \" + p.name + \" (\" + str(p.points) + \"p)\", True, (0,0,0))\n widthTxt, heightTxt = font.size(str(p.rank) + \": \" + p.name + \" (\" + str(p.points) + \"p)\")\n\n self.screen.blit(playerTxt, (self.width//2 - widthTxt//2, (self.height//2 + heightTxt*i) + self.height//6))","title":""},{"docid":"08aecdfcdb1c829a40d1edf9814ca236","score":"0.551315","text":"def submit_leaderboard(self):\n if self.leaderboard_name.text != \"\":\n self.leaderboard.add(self.game.level.name, self.leaderboard_name.text, self.game.level.get_score(), self.game.wave.number)\n self.game.load_level(self.game.level.name)\n self.show_leaderboard_screen()","title":""},{"docid":"8216a688672600362f0f51952fc4ae05","score":"0.5508417","text":"def layout_board(self):\n p = models.PieceType\n back_row = [\n p.ROOK, p.KNIGHT, p.BISHOP, p.QUEEN, p.KING, p.BISHOP, p.KNIGHT,\n p.ROOK\n ]\n for file, piece_type in enumerate(back_row):\n models.Piece.create(\n piece_type=piece_type, rank=0, file=file,\n side=models.Side.HOME, game=self.game\n )\n models.Piece.create(\n piece_type=piece_type, rank=7, file=file,\n side=models.Side.AWAY, game=self.game\n )\n for file in range(8):\n models.Piece.create(\n piece_type=p.PAWN, rank=1, file=file, side=models.Side.HOME,\n game=self.game\n )\n models.Piece.create(\n piece_type=p.PAWN, rank=6, file=file, side=models.Side.AWAY,\n game=self.game\n )","title":""},{"docid":"4ecb46d16a7f56cb2aaacb8d0ed103d3","score":"0.5501579","text":"def print_matches(self):\n\n os.system('cls' if os.name == 'nt' else 'clear')\n console = Console()\n table = Table(title=colored('MATCHES', 'magenta'), show_header=True, header_style=\"bold blue\")\n table.add_column('Round')\n table.add_column('Player 1')\n table.add_column('Score Player 1')\n table.add_column('Score Player 2')\n table.add_column('Player 2')\n for round in self.rounds:\n for match in round.matches:\n if match.player1[1] == 0.0 and match.player2[1] == 0.0:\n table.add_row(\"[orange1]\"+str(round.number),\n \"[orange1]\"+match.player1[0].surname,\n \"[orange1]\"+str(match.player1[1]),\n \"[orange1]\"+str(match.player2[1]),\n \"[orange1]\"+match.player2[0].surname,\n )\n elif round.number == 2 or round.number == 4:\n table.add_row(\"[yellow]\"+str(round.number),\n \"[yellow]\"+match.player1[0].surname,\n \"[yellow]\"+str(match.player1[1]),\n \"[yellow]\"+str(match.player2[1]),\n \"[yellow]\"+match.player2[0].surname,\n )\n else:\n table.add_row(\"[green]\"+str(round.number),\n \"[green]\"+match.player1[0].surname,\n \"[green]\"+str(match.player1[1]),\n \"[green]\"+str(match.player2[1]),\n \"[green]\"+match.player2[0].surname,\n )\n console.print(table)\n self.print_color_meanings()","title":""},{"docid":"d9f7a217ceeb2c3068b96078deb0bb06","score":"0.54946154","text":"def show_top_five_on_leaderboard():\n all_scores = []\n with open(leaderboard_file, 'r') as file:\n for line in file:\n words = line.split('=')\n leaderboard_score = int(words[1])\n player = words[0]\n all_scores.append((leaderboard_score, player))\n print('Here are the current top 5 players in the leaderboard:')\n sorted_scores = sorted(all_scores, reverse=True)[0:5]\n for score, name in sorted_scores:\n print('{} - {}'.format(name, score))","title":""},{"docid":"4164be066d3c3842f6ad5c32b3ac6ac9","score":"0.5493811","text":"def get_opponent_view(self, as_list = False):\n if as_list:\n view = [[location.opponent_view() for location in row] for row in self.grid]\n else:\n view = [BOARD_HEADING]\n row_num = 1\n for row in self.grid:\n view.append(str(row_num).rjust(2) + \" \" + \" \".join(\n [location.opponent_view() for location in row]))\n row_num += 1\n view.append(\"\")\n return view","title":""},{"docid":"f46e7b4f7e2f311aa08ccbd1270b2c6c","score":"0.548125","text":"def createGraph(self):\n\t\tdata = []\n\t\tfor i in self.members:\n\t\t\tx = \"rgba(220,220,220,1)\"\n\t\t\tv1 = str(randint(1,220))\n\t\t\tv2 = str(randint(1,220))\n\t\t\tv3 = str(randint(1,220))\n\t\t\tcolour = f\"rgba({v1},{v2},{v3},0.4)\"\n\t\t\tdata.append({'player': i.username, 'running_scores': [], 'gameweeks': [], 'colour': colour})\n\t\tfor i in self.gameweeks:\n\t\t\tdata[0]['gameweeks'].append(i)\n\t\t\tfor j in data:\n\t\t\t\tfor k in self.gameweeks[i]:\n\t\t\t\t\tif j['player'] == k['player'].username:\n\t\t\t\t\t\tj['running_scores'].append(k['running_league_points'])\n\t\tself.graph = data","title":""},{"docid":"589b52da5f44bb425ebec4201627a5b8","score":"0.54764396","text":"def enter_scores_round(self, one_tournament):\n list_rounds = one_tournament.list_rounds\n tournaments_form = TournamentForm()\n tournaments_form.enter_scores(list_rounds[-1])","title":""},{"docid":"39c82665d991c1f2e789098ec3719e7b","score":"0.5447808","text":"def draw_scores(self):\n # player1 score\n Label(\n text=str(self.player1.score),\n x=4,\n y=self.window.height - 40,\n font_name=\"helvetica\",\n font_size=36\n ).draw()\n # var to store the position the label needs to be drawn at\n # stays accurate enough till like 100000 ish\n LABEL_X_POS = self.window.width - len(list(str(self.player2.score))) * 30\n # player2 score\n Label(\n text=str(self.player2.score),\n x=LABEL_X_POS,\n y=self.window.height - 40,\n font_name=\"helvetica\",\n font_size=36\n ).draw()","title":""},{"docid":"542d019bb60548805a2a2244c2043544","score":"0.54329664","text":"def make_player_tree(self, frame):\n\n player_tree = ttk.Treeview(frame, columns=(\"name\", \"joins\", \"avgtime\", \"first\", \"second\", \"third\", \"winrate\", \"top3\", \"quits\", \"quitrate\"), height=25)\n\n #adjust column headers\n player_tree.heading(\"name\", text=\"Player Name\", command=lambda: self.sort_tree_column(player_tree, \"name\", False))\n player_tree.heading(\"joins\", text= \"Joins\", command=lambda: self.sort_tree_column_int(player_tree, \"joins\", False))\n player_tree.heading(\"avgtime\", text= \"Average Time\", command=lambda: self.sort_tree_column(player_tree, \"avgtime\", False))\n player_tree.heading(\"first\", text= \"First\", command=lambda: self.sort_tree_column_int(player_tree, \"first\", False))\n player_tree.heading(\"second\", text= \"Second\", command=lambda: self.sort_tree_column_int(player_tree, \"second\", False))\n player_tree.heading(\"third\", text= \"Third\", command=lambda: self.sort_tree_column_int(player_tree, \"third\", False))\n player_tree.heading(\"winrate\", text= \"Win Rate\", command=lambda: self.sort_tree_column_flt(player_tree, \"winrate\", False))\n player_tree.heading(\"top3\", text= \"Top3 Rate\", command=lambda: self.sort_tree_column_flt(player_tree, \"top3\", False))\n player_tree.heading(\"quits\", text= \"Quits\", command=lambda: self.sort_tree_column_int(player_tree, \"quits\", False))\n player_tree.heading(\"quitrate\", text= \"Quit Rate\", command=lambda: self.sort_tree_column_flt(player_tree, \"quitrate\", False))\n\n #adjust column widths\n player_tree.column(\"#0\", width=10)\n player_tree.column(\"name\", width=100, anchor=E)\n player_tree.column(\"joins\", width=50, anchor=E)\n player_tree.column(\"avgtime\", width=85, anchor=E)\n player_tree.column(\"first\", width=50, anchor=E)\n player_tree.column(\"second\", width=50, anchor=E)\n player_tree.column(\"third\", width=50, anchor=E)\n player_tree.column(\"winrate\", width=100, anchor=E)\n player_tree.column(\"top3\", width=100, anchor=E)\n player_tree.column(\"quits\", width=50, anchor=E)\n player_tree.column(\"quitrate\", width=100, anchor=E)\n\n scroll_bar = ttk.Scrollbar(frame, orient=VERTICAL, command=player_tree.yview)\n player_tree.configure(yscrollcommand=scroll_bar.set)\n\n return player_tree, scroll_bar","title":""},{"docid":"730c6743e6ee7ba3c380192aad56d262","score":"0.54272944","text":"def playerStandings():\n\n list = []\n conn, c = connect()\n \"\"\"get the wins number of each player\"\"\"\n winCount = \"create view winCount as(select winner as winner , count(*) as num from Matches group by winner );\"\n \"\"\"get the lose number of each player\"\"\" \n loseCount = \"create view loseCount as(select player2 as loser, count(*) as num from Matches group by player2);\"\n c.execute(winCount)\n c.execute(loseCount)\n conn.commit()\n \"\"\"join the player name and id with win number\"\"\"\n joinWin = \"create view joinWin as(select Players.id as id, Players.name as name, winCount.num as wins from Players left join winCount on Players.id = winCount.winner order by wins desc);\"\n \"\"\"join the player id and lose number\"\"\"\n joinLose = \"create view joinLose as(select Players.id as id, loseCount.num as num from Players left join loseCount on Players.id = loseCount.loser);\"\n c.execute(joinWin)\n c.execute(joinLose)\n conn.commit()\n \"\"\"put id, name, win, lose of each player together \"\"\"\n alljoin = \"select joinWin.id as id, joinWin.name as name, joinWin.wins as wins, joinLose.num as lose from joinWin left join joinLose on joinWin.id = joinLose.id order by wins;\"\n c.execute(alljoin)\n conn.commit()\n rows = c.fetchall()\n \"\"\"use the win, lose to get the matches of each player, and change None to zero\"\"\"\n count = 0\n inlist = []\n for row in rows:\n for item in row:\n if count != 3:\n if item is None:\n inlist.append(0)\n else:\n inlist.append(item)\n count = count + 1\n else:\n if item is None:\n inlist.append(inlist[2])\n else:\n inlist.append(item + inlist[2])\n list.append(inlist)\n count = 0\n inlist = []\n c.execute(\"drop view joinLose;\")\n c.execute(\"drop view joinWin;\")\n c.execute(\"drop view loseCount;\")\n c.execute(\"drop view winCount;\")\n conn.commit()\n conn.close()\n return list","title":""},{"docid":"dd808073990afeb033df476dcfe62583","score":"0.5383781","text":"def player_standings():\n refresh_views()\n query = \"\"\"\n SELECT players.id, players.name, v_player_wins.wins, v_matches.matches\n FROM players\n LEFT JOIN v_player_wins ON players.id = v_player_wins.player\n LEFT JOIN v_matches ON players.id = v_matches.player\n GROUP BY players.id, players.name, v_player_wins.wins, v_matches.matches\n ORDER BY v_player_wins.wins DESC;\n\t\"\"\"\n db, cursor = connect()\n cursor.execute(query)\n results = cursor.fetchall()\n db.close()\n return results","title":""},{"docid":"e22e90ff922cac6c9dff78bef29f864f","score":"0.53792036","text":"def __init__(self, current_player_index: int, nr_players_in_round: int):\n self.print_mode = False\n self.new_round(current_player_index, nr_players_in_round)","title":""},{"docid":"27baa46d22af61f48573c4ab1e51400a","score":"0.53698516","text":"def test_generate_rankings_after_round(self):\n matches = Match.objects.filter(date_played=datetime.now())\n players = Player.objects.filter(status=Player.ACTIVE).order_by('-ranking')\n for player in players:\n print(f'{player.first_name}, {player.last_name}, {player.ranking}')\n for match in matches:\n print(f'{match.player1}: {match.games_for_player1} vs {match.games_for_player2}: {match.player2}, {match.date_played}')\n\n print(f'Number of players: {len(players)}')\n generate_rankings_after_round(matches, datetime.now(), f'Test cases round')\n players = Player.objects.filter(status=Player.ACTIVE).order_by('ranking')\n for player in players:\n print(f'{player.first_name}, {player.last_name}, {player.ranking}')","title":""},{"docid":"4d006dcb3dd17fe8fa6dc50a0a24cf16","score":"0.53599024","text":"def leaderboard(request):\n try:\n earned_awards = Award.objects.filter(user=request.user)\n except ObjectDoesNotExist:\n earned_awards = {}\n leaders_br = Profile.objects.filter(\n category=\"beginnerrunner\").order_by('-distance')\n leaders_r = Profile.objects.filter(category=\"runner\").order_by('-distance')\n leaders_b = Profile.objects.filter(category=\"biker\").order_by('-distance')\n leaders_d = Profile.objects.filter(\n category=\"duathloner\").order_by('-distance')\n leaders_f = Profile.objects.filter(\n category=\"freestyler\").order_by('-distance')\n\n total_workouts = Workout.objects.all()\n total_kms = 0\n for workout in total_workouts:\n total_kms += workout.distance\n table_leaders_br = ProfileTable(leaders_br, prefix=\"leaders-br-\")\n table_leaders_r = ProfileTable(leaders_r, prefix=\"leaders-r-\")\n table_leaders_b = ProfileTable(leaders_b, prefix=\"leaders-b-\")\n table_leaders_d = ProfileTable(leaders_d, prefix=\"leaders-d-\")\n table_leaders_f = ProfileTable(leaders_f, prefix=\"leaders-f-\")\n RequestConfig(request, paginate={\n \"per_page\": 10\n }).configure(table_leaders_br)\n RequestConfig(request, paginate={\n \"per_page\": 10\n }).configure(table_leaders_r)\n RequestConfig(request, paginate={\n \"per_page\": 10\n }).configure(table_leaders_b)\n RequestConfig(request, paginate={\n \"per_page\": 10\n }).configure(table_leaders_d)\n RequestConfig(request, paginate={\n \"per_page\": 10\n }).configure(table_leaders_f)\n\n return render(\n request, 'ic_marathon_app/leaderboard.html', {\n 'leaders_br': table_leaders_br,\n 'leaders_br_c': len(leaders_br),\n 'leaders_r': table_leaders_r,\n 'leaders_r_c': len(leaders_r),\n 'leaders_b': table_leaders_b,\n 'leaders_b_c': len(leaders_b),\n 'leaders_d': table_leaders_d,\n 'leaders_d_c': len(leaders_d),\n 'leaders_f': table_leaders_f,\n 'leaders_f_c': len(leaders_f),\n 'earned_awards': earned_awards,\n 'total_kms': total_kms\n })","title":""},{"docid":"d267816d22ec1b67bc947c460e240144","score":"0.53473336","text":"def _compute_competition_leaderboard(session, submissions, leaderboard_type,\n event_name):\n event = session.query(Event).filter_by(name=event_name).one()\n score_type = event.get_official_score_type(session)\n score_name = event.official_score_name\n\n private_leaderboard = _compute_leaderboard(session, submissions, 'private',\n event_name, with_links=False)\n\n col_selected_private = (['team', 'submission'] +\n ['bag private ' + score_name,\n 'bag public ' + score_name] +\n ['train time [s]', 'test time [s]',\n 'submitted at (UTC)'])\n leaderboard_df = private_leaderboard[col_selected_private]\n leaderboard_df = leaderboard_df.rename(\n columns={'bag private ' + score_name: 'private ' + score_name,\n 'bag public ' + score_name: 'public ' + score_name}\n )\n\n # select best submission for each team\n best_df = (leaderboard_df.groupby('team').min()\n if score_type.is_lower_the_better\n else leaderboard_df.groupby('team').max())\n best_df = best_df[['public ' + score_name]].reset_index()\n best_df['best'] = True\n\n # merge to get a best indicator column then select best\n leaderboard_df = pd.merge(\n leaderboard_df, best_df, how='left',\n left_on=['team', 'public ' + score_name],\n right_on=['team', 'public ' + score_name]\n )\n leaderboard_df = leaderboard_df.fillna(False)\n leaderboard_df = leaderboard_df[leaderboard_df['best']]\n leaderboard_df = leaderboard_df.drop(columns='best')\n\n # dealing with ties: we need the lowest timestamp\n best_df = leaderboard_df.groupby('team').min()\n best_df = best_df[['submitted at (UTC)']].reset_index()\n best_df['best'] = True\n leaderboard_df = pd.merge(\n leaderboard_df, best_df, how='left',\n left_on=['team', 'submitted at (UTC)'],\n right_on=['team', 'submitted at (UTC)'])\n leaderboard_df = leaderboard_df.fillna(False)\n leaderboard_df = leaderboard_df[leaderboard_df['best']]\n leaderboard_df = leaderboard_df.drop(columns='best')\n\n # sort by public score then by submission timestamp, compute rank\n leaderboard_df = leaderboard_df.sort_values(\n by=['public ' + score_name, 'submitted at (UTC)'],\n ascending=[score_type.is_lower_the_better, True])\n leaderboard_df['public rank'] = np.arange(len(leaderboard_df)) + 1\n\n # sort by private score then by submission timestamp, compute rank\n leaderboard_df = leaderboard_df.sort_values(\n by=['private ' + score_name, 'submitted at (UTC)'],\n ascending=[score_type.is_lower_the_better, True])\n leaderboard_df['private rank'] = np.arange(len(leaderboard_df)) + 1\n\n leaderboard_df['move'] = \\\n leaderboard_df['public rank'] - leaderboard_df['private rank']\n leaderboard_df['move'] = [\n '{:+d}'.format(m) if m != 0 else '-' for m in leaderboard_df['move']]\n\n col_selected = [\n leaderboard_type + ' rank', 'team', 'submission',\n leaderboard_type + ' ' + score_name, 'train time [s]', 'test time [s]',\n 'submitted at (UTC)'\n ]\n if leaderboard_type == 'private':\n col_selected.insert(1, 'move')\n\n df = leaderboard_df[col_selected]\n df = df.rename(columns={\n leaderboard_type + ' ' + score_name: score_name,\n leaderboard_type + ' rank': 'rank'\n })\n df = df.sort_values(by='rank')\n return df","title":""},{"docid":"387d09e4c2da76e58f093e14096ea4c5","score":"0.5346853","text":"def _high_scores(self):\n\n #Creates a frame for highscore\n high_score_window = tk.Toplevel()\n high_score_window.title(\"High Scores\")\n\n \n #Gets values stored in the file\n data_input=self._high_score.get_entries()\n Output = \"Rank | Name | Score | Comment\\n-----------------------------------\\n\"\n i = 1\n\n \n #Load values and shows on screen\n for dictionary in data_input:\n dictionary_values = str(dictionary.values())\n name,score,comment = dictionary_values.split(sep = \",\")\n Output = Output + str(i) +\" |\"+ name[14:-1] +\" |\"+ score +\" |\"+ comment[:-2]+\"\\n\"\n i += 1\n\n #Button to returen to game \n msg = tk.Message(high_score_window, text=Output)\n msg.pack()\n \n button = tk.Button(high_score_window, text=\"Return to Game\", command=high_score_window.destroy)\n button.pack()","title":""},{"docid":"318a3b4013d7296e10710c0e42af5123","score":"0.534458","text":"def new_ranking(cls, user, wins, percent_won, avg_wrong):\n ranking = Ranking(user=user,\n wins=wins,\n percent_won=percent_won,\n avg_wrong=avg_wrong)\n ranking.put()\n return ranking","title":""},{"docid":"1caa32cc323771573d67362870e6a6b3","score":"0.5330613","text":"def get_winner_board(self):\n winner_info = self._best_individuals_select(1)\n winner_board = {\"indiv\": winner_info[0][0], \"score\": winner_info[1][0]}\n\n return winner_board","title":""},{"docid":"5c83b0469eaf668bd6f4a781959af545","score":"0.53277326","text":"def calculate_standings() -> str:\n leaderboard = defaultdict(list)\n for team, score in LEAGUE.items():\n leaderboard[score].append(team)\n for score, team in leaderboard.items():\n leaderboard[score] = sorted(leaderboard[score], key=str.lower)\n scores = sorted(leaderboard.keys(), reverse=True)\n output_lst = []\n rank = 1\n while rank <= len(LEAGUE.keys()):\n score = scores.pop(0)\n suffix = 's' if score != 1 else ''\n output = [f'{rank}. {team}, {score} pt{suffix}'\n for team in leaderboard[score]]\n\n output_lst.extend(output)\n rank += len(output)\n return '\\n'.join(output_lst)","title":""},{"docid":"6954894d95f9e458b36e65fcbf8211df","score":"0.5323443","text":"def get_leaderboard(db):\r\n user_scores = []\r\n prediction_users_ref = db.collection(\"prediction_users\")\r\n user_docs = prediction_users_ref.stream()\r\n for user_doc in user_docs:\r\n user_info = user_doc.to_dict()\r\n if user_info[\"can_display\"]:\r\n email = user_doc.id\r\n username = email.split(\"@\")[0]\r\n user_scores.append((round(user_info[\"current_score\"], 2), username))\r\n user_scores.sort(key=lambda x: (-x[0], x[1]))\r\n return user_scores[:10]","title":""},{"docid":"35cefada041b48405069925789eae52d","score":"0.53195363","text":"def get_player_view(self, as_list = False):\n if as_list:\n view = [[location.player_view() for location in row] for row in self.grid]\n else:\n view = [BOARD_HEADING]\n row_num = 1\n for row in self.grid:\n view.append(str(row_num).rjust(2) + \" \" + \" \".join(\n [location.player_view() for location in row]))\n row_num += 1\n view.append(\"\")\n return view","title":""},{"docid":"f119a8d1da96eafb5ebb3aff6fa8cc40","score":"0.5314359","text":"async def bet_board(self, ctx: commands.Context, top: int = 10):\n reverse = True\n if top == 0:\n top = 10\n elif top < 0:\n reverse = False\n top = -top\n members_sorted = sorted(\n await self._get_all_members(ctx.bot), key=lambda x: x.karma, reverse=reverse\n )\n if len(members_sorted) < top:\n top = len(members_sorted)\n topten = members_sorted[:top]\n highscore = \"\"\n place = 1\n for member in topten:\n highscore += str(place).ljust(len(str(top)) + 1)\n highscore += \"{0} | \".format(member.name).ljust(18 - len(str(member.karma)))\n highscore += str(member.karma) + \"\\n\"\n place += 1\n if highscore != \"\":\n embed = discord.Embed(color=0xf3f1f6)\n embed.title = \"Karma Returns\"\n embed.description = \"\"\"```xl\n{0}```\"\"\".format(highscore)\n await ctx.send(embed=embed)\n else:\n await ctx.send(\"No one has gained or lost any karma\")","title":""},{"docid":"5535675a0a19e5565fab7643ff6ea84b","score":"0.5310064","text":"def print_board(self):\n print(\"row: \" + str(self.col))\n print(\"col: \" + str(self.row))\n top_line = \" \"\n for c in range(self.col):\n top_line += str(c) + \" \"\n for row in range(self.row-1,-1,-1):\n # for row in range(self.row):\n line = str(row) + \" \"\n for col in range(self.col):\n if [row,col] == self.location:\n line += \"[ @]\"\n screen.blit(agentpic, ((col*rectangleWidth)+30, (row*rectangleHeight+rectangleHeight)+30)) \n pygame.display.update()\n '''pygame.draw.rect(screen, khaki, (col*rectangleWidth, row*rectangleHeight+rectangleHeight, rectangleWidth, rectangleHeight))\n \n pygame.draw.rect(screen, darkOliveGreen, (col*rectangleWidth-1, row*rectangleHeight+rectangleHeight-1, rectangleWidth-1, rectangleHeight-1))\n pygame.display.update()'''\n else:\n score = str(self.board[row][col].score())\n #if self.board[row][col].score()!=5:\n\n \n #print(\"My score\",score )\n if len(score) == 2:\n line = line + \"[\" + str(self.board[row][col].score()) + \"]\"\n else:\n line = line + \"[ \" + str(self.board[row][col].score()) + \"]\"\n print(line)\n print(top_line + '\\n');","title":""},{"docid":"b6310100da4bdc7408c643f81e28ba4d","score":"0.5301851","text":"def draw_ranks():\n for y in range(SQUARE_SPACE + Y1, Y2-1, SQUARE_SPACE):\n pygame.draw.line(screen, BLACKCOLOR, [X1, y], [X2, y], 1)","title":""},{"docid":"35d1e816f3bb215a64141a82f151423b","score":"0.5300731","text":"def rd3leaderboard(request):\n\n #Add views\n playing_players = Rd3SlotModel.objects.filter(player_name__isnull=False)\n\n #Add context\n context = {\n 'playing_players': playing_players,\n }\n\n return render(request, 'rd3Leaderboard.html', context=context)","title":""},{"docid":"77091a277a69ed4f4ef87f5eca07bf1c","score":"0.52900624","text":"def print_rounds(rounds):\n win = Color.OKGREEN\n end = Color.ENDC\n for r in rounds:\n print(f\"{Color.WARNING}{r.name}, start: {r.start}, end: {r.end}{Color.ENDC}\")\n for i, game in enumerate(r.games):\n for p in App.players:\n if game[0][0] == p.id:\n if game[0][1] == 1:\n p1 = f\"{win}id: {p.id}, {p.surname} {p.name}, rank: {p.rank}, score: {game[0][1]}{end}\"\n else:\n p1 = f\"id: {p.id}, {p.surname} {p.name}, rank: {p.rank}, score: {game[0][1]}\"\n if game[1][0] == p.id:\n if game[1][1] == 1:\n p2 = f\"{win}id: {p.id}, {p.surname} {p.name}, rank: {p.rank}, score: {game[1][1]}{end}\"\n else:\n p2 = f\"id: {p.id}, {p.surname} {p.name}, rank: {p.rank}, score: {game[1][1]}\"\n print(f\"Game {i + 1} | {p1} vs. {p2}\")\n return","title":""},{"docid":"2fc809d126acf83546c14880505bc463","score":"0.52662534","text":"def to_rankings_form(self):\n return UserRanking(\n user_name=self.name,\n games_played=self.games_played,\n total_attempts=self.total_attempts,\n total_points=self.total_points,\n points_per_attempt=self.points_per_attempt)","title":""},{"docid":"86f61654b22f949ed8424bc6bc678300","score":"0.52253443","text":"def new_round(self):\n self.reset()\n self.update_score_label() # updates score labels\n self.change_label_p_name() # players name\n self.clear_warning_label() # clear warning label","title":""},{"docid":"6dfd252042867f7bbb8a7934741a04c9","score":"0.5222292","text":"def finish():\n global change_leaderboard, leaderboard\n screen.fill(BLACK)\n screen.blit(Font_big.render('Вы уничтожили ' + str(points) + ' вирусов,', True, WHITE), (50, 50))\n screen.blit(Font_big.render('физтех выздоровел, но все равно', True, WHITE), (50, 100))\n screen.blit(Font_big.render('попал в дурку после сессии.', True, WHITE), (50, 150))\n screen.blit(Font.render('leaderboard (score, name, amount of viruses, time)', True, WHITE), (50, 250))\n input_leaders = open(\"leaderboard.txt\", \"r\")\n leaderboard = input_leaders.readlines()\n input_leaders.close()\n output_leaders = open(\"leaderboard.txt\", \"w\")\n for i in range(len(leaderboard)):\n leaderboard[i] = leaderboard[i].split()\n leaderboard[i][0] = int(leaderboard[i][0])\n leaderboard.append([points, name, number_of_targets, str(play_time)])\n leaderboard.sort(reverse=True)\n for i in range(len(leaderboard)):\n text = ''\n for j in range(len(leaderboard[i])):\n text += str(leaderboard[i][j]) + ' '\n output_leaders.write(text + '\\n')\n output_leaders.close()\n for i in range(min(len(leaderboard), 18)):\n text = ''\n for j in range(len(leaderboard[i])):\n text += str(leaderboard[i][j]) + ' '\n screen.blit(Font.render(text, True, WHITE), (50 + 400 * (i // 9), 300 + 50 * (i % 9)))\n change_leaderboard = False\n pygame.display.update()","title":""},{"docid":"6a74d524d6d2049bef83f8d11cb552d5","score":"0.52201647","text":"def draftBoard(draftWindow, xwidth, yheight, numTeams, numRounds):\r\n \r\n #clear = Rectangle(Point(0,0),Point(1300,650))\r\n #clear.draw(draftWindow)\r\n #clear.setFill('white')\r\n\r\n #place round text\r\n for rd in range(numRounds): #gives me range from 0 to round-1\r\n roundText = Text(Point( (0.0385 * xwidth),\r\n ( (0.9 * yheight) - (rd *\r\n ( (0.7954 * yheight) /\r\n (numRounds - 1))))),\r\n 'Round '+str(rd+1))\r\n roundText.setSize(13)\r\n roundText.draw(draftWindow)\r\n\r\n \"\"\"\r\n rd1 = Text(Point(50,585),'Round 1')\r\n rd1.setSize(13)\r\n rd1.draw(draftWindow)\r\n rd2 = Text(Point(50,548.072),'Round 2')\r\n rd2.setSize(13)\r\n rd2.draw(draftWindow)\r\n rd3 = Text(Point(50,511.144),'Round 3')\r\n rd3.setSize(13)\r\n rd3.draw(draftWindow)\r\n rd4 = Text(Point(50,474.216),'Round 4')\r\n rd4.setSize(13)\r\n rd4.draw(draftWindow)\r\n rd5 = Text(Point(50,437.288),'Round 5')\r\n rd5.setSize(13)\r\n rd5.draw(draftWindow)\r\n rd6 = Text(Point(50,400.36),'Round 6')\r\n rd6.setSize(13)\r\n rd6.draw(draftWindow)\r\n rd7 = Text(Point(50,363.432),'Round 7')\r\n rd7.setSize(13)\r\n rd7.draw(draftWindow)\r\n rd8 = Text(Point(50,326.504),'Round 8')\r\n rd8.setSize(13)\r\n rd8.draw(draftWindow)\r\n rd9 = Text(Point(50,289.576),'Round 9')\r\n rd9.setSize(13)\r\n rd9.draw(draftWindow)\r\n rd10 = Text(Point(50,252.648),'Round 10')\r\n rd10.setSize(13)\r\n rd10.draw(draftWindow)\r\n rd11 = Text(Point(50,215.72),'Round 11')\r\n rd11.setSize(13)\r\n rd11.draw(draftWindow)\r\n rd12 = Text(Point(50,178.792),'Round 12')\r\n rd12.setSize(13)\r\n rd12.draw(draftWindow)\r\n rd13 = Text(Point(50,141.864),'Round 13')\r\n rd13.setSize(13)\r\n rd13.draw(draftWindow)\r\n rd14 = Text(Point(50,104.936),'Round 14')\r\n rd14.setSize(13)\r\n rd14.draw(draftWindow)\r\n rd15 = Text(Point(50,68.008),'Round 15')\r\n rd15.setSize(13)\r\n rd15.draw(draftWindow)\r\n \"\"\"\r\n\r\n \"\"\"\r\n #agghh, so ineficient, but works for team window\r\n rd1 = Text(Point(50,585),'QB')\r\n rd1.setSize(13)\r\n rd1.draw(teamWindow)\r\n rd2 = Text(Point(50,548.072),'RB')\r\n rd2.setSize(13)\r\n rd2.draw(teamWindow)\r\n rd3 = Text(Point(50,511.144),'RB')\r\n rd3.setSize(13)\r\n rd3.draw(teamWindow)\r\n rd4 = Text(Point(50,474.216),'WR')\r\n rd4.setSize(13)\r\n rd4.draw(teamWindow)\r\n rd5 = Text(Point(50,437.288),'WR')\r\n rd5.setSize(13)\r\n rd5.draw(teamWindow)\r\n rd6 = Text(Point(50,400.36),'TE')\r\n rd6.setSize(13)\r\n rd6.draw(teamWindow)\r\n rd7 = Text(Point(50,363.432),'FLEX')\r\n rd7.setSize(13)\r\n rd7.draw(teamWindow)\r\n rd8 = Text(Point(50,326.504),'K')\r\n rd8.setSize(13)\r\n rd8.draw(teamWindow)\r\n rd9 = Text(Point(50,289.576),'DST')\r\n rd9.setSize(13)\r\n rd9.draw(teamWindow)\r\n rd10 = Text(Point(50,252.648),'Bench')\r\n rd10.setSize(13)\r\n rd10.draw(teamWindow)\r\n rd11 = Text(Point(50,215.72),'Bench')\r\n rd11.setSize(13)\r\n rd11.draw(teamWindow)\r\n rd12 = Text(Point(50,178.792),'Bench')\r\n rd12.setSize(13)\r\n rd12.draw(teamWindow)\r\n rd13 = Text(Point(50,141.864),'Bench')\r\n rd13.setSize(13)\r\n rd13.draw(teamWindow)\r\n rd14 = Text(Point(50,104.936),'Bench')\r\n rd14.setSize(13)\r\n rd14.draw(teamWindow)\r\n rd15 = Text(Point(50,68.008),'Bench')\r\n rd15.setSize(13)\r\n rd15.draw(teamWindow)\r\n \"\"\"\r\n\r\n #vertical lines\r\n for v in range(numTeams+1):\r\n vertLine = Line( Point( ((0.104 * xwidth) + (v * ( (0.896 * xwidth) /\r\n numTeams))),\r\n (0.071 * yheight)),\r\n Point( ((0.104 * xwidth) + (v * ( (0.896 * xwidth) /\r\n numTeams))),\r\n yheight))\r\n vertLine.draw(draftWindow)\r\n\r\n\r\n #horizontal lines\r\n for h in range(numRounds+1):\r\n horizLine = Line( Point( 0,\r\n ( (0.923 * yheight) -\r\n (h * ( (0.7954 * yheight) /\r\n (numRounds - 1))))),\r\n Point( xwidth,\r\n ( (0.923 * yheight) -\r\n (h * ( (0.7954 * yheight) /\r\n (numRounds - 1))))))\r\n horizLine.draw(draftWindow)\r\n\r\n \"\"\"\r\n for x in range(15):\r\n line = Line(Point(135+(x*80.357),46.08), Point(135+(x*80.357),650))\r\n line.draw(draftWindow)\r\n #line = Line(Point(135+(x*80.357),46.08), Point(135+(x*80.357),650))\r\n #line.draw(teamWindow)\r\n for y in range(16):\r\n h = Line(Point(0,600-(y*36.928)), Point(1259.998,600-(y*36.928)))\r\n h.draw(draftWindow)\r\n #h = Line(Point(0,600-(y*36.928)), Point(1259.998,600-(y*36.928)))\r\n #h.draw(teamWindow)\r\n #so much shitty programming\r\n \"\"\" \r\n\r\n #button to submit team name\r\n submit = Button(draftWindow, Point( (0.6154 * xwidth),\r\n (0.0385 * yheight)),\r\n (0.058 * xwidth),\r\n (0.034 * yheight),\r\n 'Submit', 'red')\r\n submit.activate()\r\n\r\n \"\"\"\r\n #button to submit team name\r\n submit = Button(draftWindow,Point(800,25),75,22,'Submit','red')\r\n submit.activate()\r\n \"\"\"\r\n\r\n teamNum = 1 #The current team being labled\r\n\r\n while teamNum < numTeams + 1:\r\n\r\n #text to prompt user to enter the team names\r\n prompt = Text( Point( (0.40385 * xwidth), (0.03846 * yheight)),\r\n 'Enter Team '+str(teamNum))\r\n prompt.setSize(14)\r\n prompt.draw(draftWindow)\r\n\r\n #input window for entering team names\r\n teamNameInput = Entry( Point( (0.51923 * xwidth),\r\n (0.03846 * yheight)), 15)\r\n teamNameInput.draw(draftWindow)\r\n\r\n #wait for submit button to be pressed\r\n c = draftWindow.getMouse()\r\n while not submit.check(c) or teamNameInput.getText() == \"\":\r\n c = draftWindow.getMouse()\r\n\r\n team = Text( Point( ((0.1346 * xwidth) +\r\n ((0.064 * xwidth) * (teamNum - 1))),\r\n (0.9615 * y height)),\r\n teamNameInput.getText())\r\n team.setSize(12)\r\n team.draw(draftWindow)\r\n\r\n prompt.undraw()\r\n teamNum += 1\r\n\r\n#good to this point -----------------------------------\r\n\r\n\r\n \"\"\"\r\n\r\n #the number of the team\r\n tNum = 1\r\n\r\n while tNum < 15:\r\n \r\n #text to prompt user to enter the team names\r\n prompt = Text(Point(525,25),'Enter Team '+str(tNum))\r\n prompt.setSize(14)\r\n prompt.draw(draftWindow)\r\n \r\n #input window for entering the names\r\n tNameInput = Entry(Point(675,25),15)\r\n tNameInput.draw(draftWindow)\r\n \r\n c = draftWindow.getMouse()\r\n while not submit.check(c):\r\n c = draftWindow.getMouse()\r\n #lol, here comes more shitty programming\r\n if tNum == 1:\r\n t1 = Text(Point(175,625),tNameInput.getText())\r\n t1.setSize(12)\r\n t1.draw(draftWindow)\r\n #t1 = Text(Point(175,625),tNameInput.getText())\r\n #t1.setSize(12)\r\n #t1.draw(teamWindow)\r\n elif tNum == 2:\r\n t2 = Text(Point(250.357,625),tNameInput.getText())\r\n t2.setSize(12)\r\n t2.draw(draftWindow)\r\n #t2 = Text(Point(250.357,625),tNameInput.getText())\r\n #t2.setSize(12)\r\n #t2.draw(teamWindow)\r\n elif tNum == 3:\r\n t3 = Text(Point(330.714,625),tNameInput.getText())\r\n t3.setSize(12)\r\n t3.draw(draftWindow)\r\n #t3 = Text(Point(330.714,625),tNameInput.getText())\r\n #t3.setSize(12)\r\n #t3.draw(teamWindow)\r\n elif tNum == 4:\r\n t4 = Text(Point(411.071,625),tNameInput.getText())\r\n t4.setSize(12)\r\n t4.draw(draftWindow)\r\n #t4 = Text(Point(411.071,625),tNameInput.getText())\r\n #t4.setSize(12)\r\n #t4.draw(teamWindow)\r\n elif tNum == 5:\r\n t5 = Text(Point(491.428,625),tNameInput.getText())\r\n t5.setSize(12)\r\n t5.draw(draftWindow)\r\n #t5 = Text(Point(491.428,625),tNameInput.getText())\r\n #t5.setSize(12)\r\n #t5.draw(teamWindow)\r\n elif tNum == 6:\r\n t6 = Text(Point(571.785,625),tNameInput.getText())\r\n t6.setSize(12)\r\n t6.draw(draftWindow)\r\n #t6 = Text(Point(571.785,625),tNameInput.getText())\r\n #t6.setSize(12)\r\n #t6.draw(teamWindow)\r\n elif tNum == 7:\r\n t7 = Text(Point(652.142,625),tNameInput.getText())\r\n t7.setSize(12)\r\n t7.draw(draftWindow)\r\n #t7 = Text(Point(652.142,625),tNameInput.getText())\r\n #t7.setSize(12)\r\n #t7.draw(teamWindow)\r\n elif tNum == 8:\r\n t8 = Text(Point(732.499,625),tNameInput.getText())\r\n t8.setSize(12)\r\n t8.draw(draftWindow)\r\n #t8 = Text(Point(732.499,625),tNameInput.getText())\r\n #t8.setSize(12)\r\n #t8.draw(teamWindow)\r\n elif tNum == 9:\r\n t8 = Text(Point(812.856,625),tNameInput.getText())\r\n t8.setSize(12)\r\n t8.draw(draftWindow)\r\n #t8 = Text(Point(812.856,625),tNameInput.getText())\r\n #t8.setSize(12)\r\n #t8.draw(teamWindow)\r\n elif tNum == 10:\r\n t8 = Text(Point(893.213,625),tNameInput.getText())\r\n t8.setSize(12)\r\n t8.draw(draftWindow)\r\n #t8 = Text(Point(893.213,625),tNameInput.getText())\r\n #t8.setSize(12)\r\n #t8.draw(teamWindow)\r\n elif tNum == 11:\r\n t8 = Text(Point(973.57,625),tNameInput.getText())\r\n t8.setSize(12)\r\n t8.draw(draftWindow)\r\n #t8 = Text(Point(973.57,625),tNameInput.getText())\r\n #t8.setSize(12)\r\n #t8.draw(teamWindow)\r\n elif tNum == 12:\r\n t8 = Text(Point(1053.927,625),tNameInput.getText())\r\n t8.setSize(12)\r\n t8.draw(draftWindow)\r\n #t8 = Text(Point(1053.927,625),tNameInput.getText())\r\n #t8.setSize(12)\r\n #t8.draw(teamWindow)\r\n elif tNum == 13:\r\n t8 = Text(Point(1134.284,625),tNameInput.getText())\r\n t8.setSize(12)\r\n t8.draw(draftWindow)\r\n #t8 = Text(Point(1134.284,625),tNameInput.getText())\r\n #t8.setSize(12)\r\n #t8.draw(teamWindow)\r\n elif tNum == 14:\r\n t8 = Text(Point(1214.641,625),tNameInput.getText())\r\n t8.setSize(12)\r\n t8.draw(draftWindow)\r\n #t8 = Text(Point(1214.641,625),tNameInput.getText())\r\n #t8.setSize(12)\r\n #t8.draw(teamWindow)\r\n \r\n \r\n prompt.undraw()\r\n tNum += 1\r\n \"\"\"\r\n \r\n\r\n prompt = Text(Point(425,25),\"Enter Player Position and Name\")\r\n prompt.setSize(13)\r\n prompt.draw(draftWindow)\r\n\r\n pick = 1\r\n roundNum = 1\r\n\r\n while roundNum < 16: #number of pick in the draft will be 210\r\n tNameInput = Entry(Point(675,25),15)\r\n tNameInput.draw(draftWindow)\r\n #for player name\r\n\r\n #for player position\r\n pInput = Entry(Point(575,25),5)\r\n pInput.draw(draftWindow)\r\n c = draftWindow.getMouse()\r\n while not submit.check(c):\r\n c = draftWindow.getMouse()\r\n pPosition = pInput.getText()\r\n pName = tNameInput.getText()\r\n if pPosition == 'QB':\r\n pcolor = 'orange'\r\n elif pPosition == 'RB':\r\n pcolor = 'lightblue'\r\n elif pPosition == 'WR':\r\n pcolor = 'lightgreen'\r\n elif pPosition == 'TE':\r\n pcolor = 'pink'\r\n elif pPosition == 'K':\r\n pcolor = 'yellow'\r\n elif pPosition == 'DEF':\r\n pcolor = 'brown'\r\n elif pPosition == 'NA':\r\n pcolor = 'black'\r\n\r\n #here is where we need some demensions and to make the picks\r\n #snake back and fourth between the rounds\r\n if roundNum%2 == 1:\r\n placePick = Button(draftWindow,Point(175.1785+((pick-1)*80.357),581.536-((roundNum-1)*36.928)),80.357,36.928,pName,pcolor)\r\n placePick.activate()\r\n else:\r\n placePick = Button(draftWindow,Point((175.1785+(13*80.357))-((pick-1)*80.357),581.536-((roundNum-1)*36.928)),80.357,36.928,pName,pcolor)\r\n placePick.activate()\r\n\r\n pick = pick+1\r\n if pick == 15:\r\n pick = 1\r\n roundNum = roundNum + 1","title":""},{"docid":"288af7fd2976d7772ff78d16ce0b9589","score":"0.5213266","text":"def get_leader_board_split(self, date):\n q = SQL.SQL(\n '''\n SELECT (((SUM(tbl.minutes) * 60) + SUM(tbl.seconds))::FLOAT / SUM(tbl.distance)) * 500 AS split, u.username\n FROM (\n SELECT user_id, minutes, seconds, distance\n FROM workout AS w\n JOIN erg AS e \n ON w.workout_id = e.workout_id\n WHERE w.time>{}\n ) AS tbl\n JOIN users AS u\n ON u.user_id = tbl.user_id\n GROUP BY u.username\n ORDER BY split\n '''\n ).format(SQL.Placeholder())\n\n result = self.safe_execute(q, (date,), fetchone=False)\n return result","title":""},{"docid":"fc90d7b48c2e96c47028b7b16b02475b","score":"0.52115124","text":"def show_add_to_leaderboard_screen(self):\n self.clear()\n self.add_button(\"Type Your Name\", None)\n self.leaderboard_name = self.add_button(\"\", None)\n self.add_button(\"Submit\", self.submit_leaderboard)","title":""},{"docid":"054d2733a75f9694c50ec659998f2540","score":"0.521088","text":"def __init__(self):\n\n self.play = True\n self.status = 'start_screen'\n\n self.winner = None\n self.winning_tiles = []\n self.win_combinations = []\n\n self.move_nr = 0\n self.player_list = []\n self.current_player_nr = 0\n self.settings = {'vs_computer': False, 'board_size': 3}\n\n self.view = GameView()","title":""},{"docid":"ff2f754fd2e9d5b35564bcad28a725c2","score":"0.5208663","text":"def tournament(self):\n\n x_axis = []\n y_axis = []\n\n for i in range(self.number_of_matches):\n score = self.single_match()\n\n self.scores[0] += score[0]\n self.scores[1] += score[1]\n\n self.percentage = self.scores[0] / (i + 1)\n\n x_axis.append(i + 1)\n y_axis.append(self.percentage)\n\n print(\"The tournament completed:\\n\" +\n str(self.player1) +\n \": \" +\n str(self.scores[0]) +\n \" points.\\n\" +\n str(self.player2) +\n \": \" +\n str(self.scores[1]) +\n \" points.\")\n\n matplotlib.pyplot.plot(x_axis, y_axis)\n matplotlib.pyplot.axis([0, self.number_of_matches, 0, 1])\n matplotlib.pyplot.grid(True)\n matplotlib.pyplot.axhline(y=0.5, linewidth=0.5, color=\"m\")\n matplotlib.pyplot.xlabel(\"Number of games\")\n matplotlib.pyplot.ylabel(\n \"Winning percentage for \" + str(self.player1) + \" Vs.\\n\" + str(self.player2))\n\n print(\"player moves for \" + str(self.player1) + \": \\t\\t\" +\n str(self.player1.get_results()[self.player1]))\n print(\"player moves for \" + str(self.player2) + \": \\t\\t\" +\n str(self.player2.get_results()[self.player2]))\n\n matplotlib.pyplot.show()","title":""},{"docid":"e61f02e56c7bbe55cfeb1df62165638b","score":"0.52037007","text":"def test_fetch_overall_leaderboard_position(self):\n first_user = User.objects.create(username='SomeGuy', email='me@abv.bg', password='123', score=123, role=self.base_role)\n second_user = User.objects.create(username='dGuy', email='d@abv.dg', password='123', score=122, role=self.base_role)\n second_user2 = User.objects.create(username='dGumasky', email='molly@abv.bg', password='123', score=122, role=self.base_role)\n second_user3 = User.objects.create(username='xdGumasky', email='xmolly@abv.bg', password='123', score=122, role=self.base_role)\n fifth_user = User.objects.create(username='dbrr', email='dd@abv.bg', password='123', score=121, role=self.base_role)\n fifth_user.save()\n\n self.assertEqual(fifth_user.fetch_overall_leaderboard_position(), 5)\n self.assertEqual(second_user.fetch_overall_leaderboard_position(), 2)\n self.assertEqual(second_user2.fetch_overall_leaderboard_position(), 2)\n self.assertEqual(second_user3.fetch_overall_leaderboard_position(), 2)\n self.assertEqual(first_user.fetch_overall_leaderboard_position(), 1)","title":""},{"docid":"ae1dfbff0883f6c0bae2341360719c0b","score":"0.5200481","text":"def showGameResultScreen(self, pla, sco, rounds_tot=None):\n # pylint: disable=unused-argument,too-many-locals,too-many-statements\n self.fadeUpDown(\"down\")\n self.emptyGroup(self.disp_group)\n\n # Score list group + background + question mark for sorting\n gs_group = Group()\n\n # Pale grey large GAME SCORES background\n bg_scale = 6\n sbg_dob1 = Label(self.font,\n text=\"GAME\",\n scale=bg_scale,\n color=GS_COL)\n sbg_dob1.x = (self.width - 4 * bg_scale * self.font_width) // 2\n sbg_dob1.y = self.height // 4\n sbg_dob2 = Label(self.font,\n text=\"SCORES\",\n scale=bg_scale,\n color=GS_COL)\n sbg_dob2.x = (self.width - 6 * bg_scale * self.font_width) // 2\n sbg_dob2.y = self.height // 4 * 3\n gs_group.append(sbg_dob1)\n gs_group.append(sbg_dob2)\n self.showGroup(gs_group)\n self.fadeUpDown(\"up\")\n\n # Calculate maximum length player name\n # and see if scores happen to already be in order\n max_len = 0\n prev_score = sco[0]\n descending = True\n for idx, (name, _) in enumerate(pla):\n max_len = max(max_len, len(name))\n if sco[idx] > prev_score:\n descending = False\n prev_score = sco[idx]\n\n fmt = \"{:\" + str(max_len) + \"s} {:2d}\"\n x_pos = (self.width - (max_len + 3) * 2 * self.font_width) // 2\n scale = 2\n spacing = 4 if len(pla) <= 6 else 0\n top_y_pos = round((self.height\n - len(pla) * scale * self.font_height\n - (len(pla) - 1) * spacing) / 2\n + scale * self.font_height / 2)\n scores_group = Group()\n gs_group.append(scores_group)\n for idx, (name, _) in enumerate(pla):\n op_dob = Label(self.font,\n text=fmt.format(name, sco[idx]),\n scale=2,\n color=(PLAYER_NAME_COL_FG if idx == 0 else OPP_NAME_COL_FG))\n op_dob.x = x_pos\n op_dob.y = top_y_pos + idx * (scale * self.font_height + spacing)\n scores_group.append(op_dob)\n time.sleep(0.2)\n\n # Sort the entries if needed\n sort_scores = list(sco) # Make an independent local copy\n if not descending:\n empty_group = Group() # minor hack to aid swaps in scores_group\n step = 3\n qm_dob = Label(self.font,\n text=\"?\",\n scale=2,\n color=QM_SORT_FG)\n qm_dob.x = round(x_pos - 1.5 * scale * self.font_width)\n gs_group.append(qm_dob)\n while True:\n swaps = 0\n for idx in range(0, len(sort_scores) -1):\n above_score = sort_scores[idx]\n above_y = scores_group[idx].y\n below_y = scores_group[idx + 1].y\n qm_dob.y = (above_y + below_y) // 2\n if above_score < sort_scores[idx + 1]:\n qm_dob.text = \"<\"\n qm_dob.color = QM_SORTING_FG\n swaps += 1\n\n # make list of steps\n range_y = below_y - above_y\n offsets = list(range(step, range_y + 1, step))\n # Ensure this goes to the exact final position\n if offsets[-1] != range_y:\n offsets.append(range_y)\n\n for offset in offsets:\n scores_group[idx].y = above_y + offset\n scores_group[idx + 1].y = below_y - offset\n time.sleep(0.050)\n\n # swap the scores around\n sort_scores[idx] = sort_scores[idx + 1]\n sort_scores[idx + 1] = above_score\n\n # swap the graphical objects around using empty_group\n # to avoid ValueError: Layer already in a group\n old_above_dob = scores_group[idx]\n old_below_dob = scores_group[idx + 1]\n scores_group[idx + 1] = empty_group\n scores_group[idx] = old_below_dob\n scores_group[idx + 1] = old_above_dob\n\n qm_dob.text = \"?\"\n qm_dob.color = QM_SORT_FG\n time.sleep(0.2)\n else:\n time.sleep(0.6)\n\n if swaps == 0:\n break # Sort complete if no values were swapped\n gs_group.remove(qm_dob)","title":""},{"docid":"72cee9051bbd5417c507c0515250e459","score":"0.5199042","text":"def new_game(self):\n\t\tself.__self_setup(len(self.grid[0]), len(self.grid), self.min_score)","title":""},{"docid":"d196f67ffbd74386e379b65d3ec335f8","score":"0.5162356","text":"def refresh_score(self):\n self._score_label = tk.Label(self._master, text=\"Score: {} - {}\".format(self._model.get_score()[0],self._model.get_score()[1]),font='Arial 15 bold')\n self._score_label.grid(row=3, column =0)","title":""},{"docid":"ee2ae19a7315996702b7de783a40bef9","score":"0.5156803","text":"def create_game_window(self):\r\n self.data_list = [int(self.entry.row.get()),\r\n int(self.entry.col.get()),\r\n str(self.entry.first.get()),\r\n str(self.entry.top_left.get()),\r\n self.entry.condition.get()]\r\n\r\n Othello_Gamewindow.GameWindow(self.master.master, self.data_list)\r\n # the game window launched, mainloop will be withdrawn\r\n\r\n print('Game started'\r\n '\\nrow number:', self.data_list[0],\r\n '\\ncol number:', self.data_list[1],\r\n '\\nfirst turn:', self.data_list[2],\r\n '\\ntop left piece:', self.data_list[3]\r\n )","title":""},{"docid":"a8c2a38b031166b121f5556d2c3f8602","score":"0.515397","text":"def get_leaderboards():\n top_scores = leaderboards.get_latest()\n logger.debug('Current leaderboards top score: %s', top_scores)\n return top_scores","title":""},{"docid":"c72b004ac9ce3bd2fe058fdb0138d747","score":"0.51447207","text":"def board():\n return render_template('board.html', data={\"active_player\": game.turn, \"passive_player\": game.next_player()})","title":""},{"docid":"82cd4f473c4622de4fa8e29d9047aa1e","score":"0.5139477","text":"def __init__(self):\n # starts with player 0's turn\n self.whose_turn = 0\n # positions on the grid are labeled as follows:\n # 0 1 2\n # 3 4 5\n # 6 7 8\n # will hold 1 or 0, indicating whether this player has occupied this position\n self.player_0_positions = [0] * 9\n self.player_1_positions = [0] * 9\n # number of games won in this session\n self.player_0_score = 0\n self.player_1_score = 0\n self.num_ties = 0","title":""},{"docid":"c5f675c37c4c8d913607dafdbfe1ce7c","score":"0.5138871","text":"def construct_board():\r\n pass","title":""},{"docid":"9c5e000af1bbf8499c0d6ed4a36c38d5","score":"0.5136407","text":"def generate_matchs_firstRound(self, tournament):\n list_players = tournament.list_players\n all_list_players = []\n for elt in list_players:\n all_list_players.append(PlayerController().get_one(elt))\n list_triee = sorted(\n all_list_players,\n key=attrgetter(\"rank\"),\n reverse=True\n )\n tournament.matches_dones += [\n f\"{list_triee[0].identifier}:{list_triee[4].identifier}\",\n f\"{list_triee[1].identifier}:{list_triee[5].identifier}\",\n f\"{list_triee[2].identifier}:{list_triee[6].identifier}\",\n f\"{list_triee[3].identifier}:{list_triee[7].identifier}\"\n ]\n tournament.list_rounds.append(Round(\"Round 1\", [\n Match(\"Match1\", list_triee[0], 0, list_triee[4], 0),\n Match(\"Match2\", list_triee[1], 0, list_triee[5], 0),\n Match(\"Match3\", list_triee[2], 0, list_triee[6], 0),\n Match(\"Match4\", list_triee[3], 0, list_triee[7], 0)\n ], \"\", \"\"))\n return tournament","title":""},{"docid":"63e011e2bc5e082ac655bb0c83e02dd2","score":"0.5134712","text":"async def show(ctx, *args):\n if len(server.user_list) < 1:\n await ctx.send(\"The server dosen't have any data….\")\n elif (len(args) < 1 or args[0] == \"--name\"):\n user_name = ctx.author.name\n if len(args) > 1 and \"--name\" == args[0]:\n for m in ctx.guild.members:\n if m.name == args[1] or m.nick == args[1]:\n user_name = args[1]\n break\n else:\n await ctx.send(\"Invalid user name\")\n return\n user = server.get(user_name)\n ret = \"Win rate(when Impostor or Crewmate): {:.2%}\\n\".format(\n user.win_num / user.data['Games Finished'])\n ret += \"Win rate(when Impostor): {:.2%}\\n\".format(\n user.impostor_win_num / user.data['Times Impostor'])\n ret += \"Win rate(when Crewmate): {:.2%}\\n\".format(\n user.crewmate_win_num / user.data['Times Crewmate'])\n ret += \"Kills per Impostor: {:.2f}\\n\".format(\n user.data['Impostor Kills'] / user.data['Times Impostor'])\n ret += \"Tasks Completed rate: {:.2%}\\n\".format(\n user.data['All Tasks Completed'] / user.data['Times Crewmate'])\n ret += \"Sabotages Fixed / Games: {:.2f}\".format(\n user.data['Sabotages Fixed'] / user.data['Games Finished'])\n await ctx.send(ret)\n elif args[0] == \"--rank\":\n show_num = 3\n if len(args) > 1 and is_num(args[1]):\n show_num = int(args[1])\n ret = \"leaderboard! (Win Rate) \\n\"\n ret += \"\\n\".join(\"rank {2} {1} : {0:.2%} win\".format(tup[0], tup[1],\n rank)\n for rank, tup in enumerate(\n server.rank_win_rate()[:show_num], start=1))\n ret += \"\\n\\nleaderboard! (Impostor Win Rate) \\n\"\n ret += \"\\n\".join(\"rank {2} {1} : {0:.2%} win\".format(tup[0], tup[1],\n rank)\n for rank, tup in enumerate(\n server.rank_win_rate_when_impostor()[:show_num],\n start=1))\n ret += \"\\n\\nleaderboard! (Crewmate Win Rate) \\n\"\n ret += \"\\n\".join(\"rank {2} {1} : {0:.2%} win\".format(tup[0], tup[1],\n rank)\n for rank, tup in enumerate(\n server.rank_win_rate_when_crewmate()[:show_num],\n start=1))\n ret += \"\\n\\nleaderboard! (Kill / Times Impostor) \\n\"\n ret += \"\\n\".join(\"rank {2} {1} : {0:.2f} killed\".format(tup[0], tup[1],\n rank)\n for rank, tup in enumerate(\n server.rank_kill()[:show_num], start=1))\n ret += \"\\n\\nleaderboard! (All Tasks Completed / Times Crewmate) \\n\"\n ret += \"\\n\".join(\"rank {2} {1} : {0:.2%} completed\".format(\n tup[0], tup[1],\n rank)\n for rank, tup in enumerate(\n server.rank_alltask()[:show_num], start=1))\n ret += \"\\n\\nleaderboard! (Sabotages Fixed / Number of Games) \\n\"\n ret += \"\\n\".join(\"rank {2} {1} : {0:.2f} fixed\".format(tup[0], tup[1],\n rank)\n for rank, tup in enumerate(\n server.rank_sabotagefix()[:show_num], start=1))\n await ctx.send(ret)\n elif args[0] == \"--diff\":\n await ctx.send(\"I'll implement it one day!\")\n elif args[0] == \"--userlist\":\n await ctx.send(\", \".join([k for k in server.user_list.keys()]))\n else:\n await ctx.send(\"invalid command ><\")","title":""},{"docid":"effeee1ac4e2fa12decb59618caa1b25","score":"0.51342463","text":"def create_board(self):\n self.add_piece(Floor(self, position=(1.5, -1, 5)))\n for i, tile in enumerate(self.board):\n if tile in [1, 2]:\n self.add_piece(BoardTile(self, position=(i % 3, 0, i // 3), rosetta=tile == 2))","title":""},{"docid":"51730b0ace2c1844e8597d3bb3a74469","score":"0.5120348","text":"def createGame(self):\n\t\tself.columnconfigure(0, pad = 5)\n\t\tself.columnconfigure(1, pad = 5)\n\t\tself.rowconfigure(0, pad = 10)\n\t\tself.rowconfigure(1, pad = 10)\n\t\tself.numPlayersField = Entry(self)\n\t\tself.numPlayersField.insert(0,\"1\")\n\t\tself.setPlayersButton = Button(self, text = \"Set number of players\", command = self.setPlayers)\n\t\tself.numPlayersField.grid(row=0, column = 0)\n\t\tself.setPlayersButton.grid(row=0, column = 1)\n\t\tself.gameCanvas = Canvas(self, bg = \"black\", height = self.canvasHeight, width = self.canvasWidth)\n\t\tself.gameCanvas.grid(row = 1, column = 0, columnspan = 2)\n\t\tself.newGameButton = Button(self, text=\"New game\", command = self.newGame)\n\t\tself.quitGameButton = Button(self, text=\"Quit\", command = self.quit)\n\t\tself.newGameButton.grid(row = 2, column = 0)\n\t\tself.quitGameButton.grid(row = 2, column = 1)\n\t\tself.pack()\n\t\tself.createRectangles()","title":""},{"docid":"e8d42cf9252943714075b50c24037924","score":"0.5118666","text":"def test_get_leaderboard(self):\n expected_positions = {\n self.fifth_user.username: 5,\n self.second_user.username: 2,\n self.second_user2.username: 2,\n self.second_user3.username: 2,\n self.first_user.username: 1\n }\n auth_token = 'Token {}'.format(self.second_user3.auth_token.key)\n\n received_leaderboard = self.client.get('/challenges/getLeaderboard', HTTP_AUTHORIZATION=auth_token).data\n\n for lead in received_leaderboard:\n user_name = lead['name']\n self.assertEqual(lead['position'], expected_positions[user_name])","title":""},{"docid":"cc9df34f6da374dc65252ceb8c3fda96","score":"0.5102245","text":"def ranking_data(request):\n # get the type of the last played round, even if there is no currently active round\n latest_round = Round.objects.order_by('-id')[0] # this is the latest created round\n print \"the latest round type was\"\n print latest_round.type\n if latest_round.type == 0:\n roundtype = 'selection'\n else:\n roundtype = 'final'\n\n ranking_entries = get_ranking_entries()\n\n return render(request, 'ranking_data.xml', {\n 'roundtype': roundtype,\n 'ranking_entries': ranking_entries,\n }, content_type=\"text/xml\")","title":""},{"docid":"864cd37be2a317b7b09ac7cf4913d726","score":"0.51003873","text":"def create_game_board(self):\n self.fill_screen()\n self.render_text(\n 'Dealer Chip Number: ' + str(self.dealer_num_chips), \n PLAYER_INFO_FONT_SIZE, \n DEALER_INFO_LOCATION, \n BLACK\n )\n self.render_text(\n 'Your Chip Number: ' + str(self.player_num_chips),\n PLAYER_INFO_FONT_SIZE,\n PLAYER_INFO_LOCATION, \n BLACK\n )\n self.render_image(DECK_IMG_PATH, DECK_IMG_LOCATION)","title":""},{"docid":"92c9084d9287f80537d7ecdf906c08b6","score":"0.5094188","text":"def create_label(self):\r\n row_num_label = tkinter.Label(self.master, text='rows :',\r\n width=10, height=1, pady=8)\r\n col_num_label = tkinter.Label(self.master, text='columns :',\r\n width=10, height=1, pady=5)\r\n first_turn_label = tkinter.Label(self.master, text='first turn :',\r\n width=10, height=1, pady=6)\r\n topleft_label = tkinter.Label(self.master, text='top left :',\r\n width=10, height=1, pady=6)\r\n\r\n row_num_label.grid(row=0, column=0)\r\n col_num_label.grid(row=1, column=0)\r\n first_turn_label.grid(row=2, column=0)\r\n topleft_label.grid(row=3, column=0)","title":""},{"docid":"f26bc1dd240605826c9cbcae40026569","score":"0.5094108","text":"def retrieve_team_leader(self, tl_pk: int):\n pass","title":""},{"docid":"f803e5acd91853816d9a434b3c435f07","score":"0.50906175","text":"def getleaderboarddisplay(leg_body, owner_filter):\n try:\n return ScoreDisplay.objects.get(name=\"%s_leader_%s\" % (leg_body.name,\n owner_filter))\n except:\n return None","title":""},{"docid":"26a338181e6564a8cbc07b220894291f","score":"0.5077305","text":"def print_scoreboard(self, gender):\n print('Scoreboard for track %s in season %s' % (gender, self.name))\n rank = 1\n scoreboard = self.get_scoreboard(gender)\n for points, stats in scoreboard:\n print('#%d. %s at %.2f points' % (rank, stats.player.name, stats.points))\n rank += 1","title":""},{"docid":"aee7922d05c5b0a7c973cde5865dc91e","score":"0.5076507","text":"def display_result(name, list_of_score):\r\n all_round = 1\r\n print(\"\\nThanks for playing {0}\".format(name))\r\n\r\n for row in list_of_score:\r\n print(\"Round {0} : {1}.\".format(all_round, row))\r\n all_round += 1","title":""},{"docid":"ca43b763c7d4490152090d439344a5f3","score":"0.504961","text":"def print_board(board, player1, player2):\n row_len = len(board[0])\n col_len = len(board)\n rows_template = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I']\n cols = []\n for col_index in range(col_len):\n cols.append(col_index + 1)\n cols_str = list(map(str, cols))\n rows = []\n for row_index in range(row_len):\n rows.append(rows_template[row_index])\n line = []\n for i in range(row_len):\n line.append(\"---\")\n \n board_total_length = (row_len * 3) + (row_len - 1) + 2\n score_names = f\"{player1['name']} : {player2['name']}\"\n score = f\"{str(player1['points']).rjust(len(player1['name']))} : {player2['points']}\"\n score_offset = int((board_total_length - len(score_names)) / 2)\n print(\" \"*score_offset + score_names)\n print(\" \"*score_offset + score)\n print(\"\")\n print(\" \", \" \".join(cols_str))\n for index in range(col_len):\n print(f\"{rows[index]} {' | '.join(board[index])}\")\n if index < row_len - 1:\n print(\" \", \"+\".join(line))\n print(\"\")","title":""},{"docid":"12814ecde4093c1958c0ea26271b9777","score":"0.5046536","text":"def get_leaderboard(self, id=None, state=None, owner=None, tag=None, min_running_time=None):\n\n leaderboard_entries = self._fetch_leaderboard(id, state, owner, tag, min_running_time)\n\n def make_row(entry):\n channels = dict((\"channel_{}\".format(ch.name), ch.trimmed_y) for ch in entry.channels)\n\n parameters = map_keys(\"parameter_{}\".format, entry.parameters)\n properties = map_keys(\"property_{}\".format, entry.properties)\n\n r = {}\n r.update(entry.system_properties)\n r.update(channels)\n r.update(parameters)\n r.update(properties)\n return r\n\n rows = ((n, make_row(e)) for (n, e) in enumerate(leaderboard_entries))\n\n df = pd.DataFrame.from_dict(data=dict(rows), orient=\"index\")\n df = df.reindex(self._sort_leaderboard_columns(df.columns), axis=\"columns\")\n return df","title":""},{"docid":"8d8f46e2559b39b119d7febd6d19afad","score":"0.5028831","text":"def view_scores(self):\n scores = { \n **self.__score['upper'],\n 'total upper': self.__score['total upper'],\n **self.__score['lower'],\n 'total lower': self.__score['total lower'],\n 'grand total': self.__score['grand total'] \n }\n for score in scores:\n s = scores[score]\n if s == None:\n s = 'blank'\n print(f'\\t{score.title()}: {s}')","title":""},{"docid":"e230d6041e2b95be5542e23c2cdc6dcb","score":"0.5024332","text":"def refresh_rankings(self):\n \n self.team_ranks_panel.pack_forget() #Get rid of the old rankings\n self.team_ranks_panel = tk.Frame(self.ranking_frame) #Make a new ranks panel\n self.team_ranks_panel.grid(row=3, column=0) #Add the panel\n \n self.team_ranks_textbox = tk.Text(self.team_ranks_panel, width=24, wrap=tk.NONE) #The textbox with the ranking and score information\n self.team_ranks_textbox.pack(side=tk.TOP) #Add the team ranks textbox\n \n r_teams = self.get_teams()[:] #The teams to show ranks for\n r_teams.sort(key=lambda t:-self.score(t)) #Sort the teams by score in descending order\n \n for i in range(0, len(r_teams)): #Add the teams to the team ranks textbox one at a time\n team = r_teams[i] #Get the team to add\n num_string = str(i+1)\n num_string = num_string + ':' + (' ' * (4-len(num_string)))\n string = num_string + str(team) #The rank and the team\n string += ' ' * (11-len(string)) + 'with ' + '%.2f' % self.score(team) #The score of the team\n if i != len(r_teams) - 1: #Add newlines after every string but the last\n string += '\\n'\n self.team_ranks_textbox.insert(tk.INSERT, chars=string) #Add the string to the team ranks textbox\n \n self.team_ranks_textbox.config(state=tk.DISABLED, height=30) #Make it so the team ranks textbox can't be edited \n \n self.parent.do_easter_eggs() #Trigger any appropriate easter eggs","title":""},{"docid":"41f7fc8950403b823955a2b0ed50510a","score":"0.50169355","text":"def __init__(self, width=5, height=5, playerA=PLAYER_TYPE_HUMAN, playerB=PLAYER_TYPE_HUMAN, depth = 3, useDecisionTree= True, dynamicDepth= False):\n self.width, self.height = width, height\n assert 2 <= self.width and 2 <= self.height,\\\n \"Game can't be played on this board's dimension.\"\n self.board = {}\n self.squares = {}\n self.player = 0\n self.players = {\n 0: Player(self, playerA, 0, depth, useDecisionTree, dynamicDepth),\n 1: Player(self, playerB, 1, depth, useDecisionTree, dynamicDepth),\n }\n\n self.board_state_size = (self.width-1) * self.height * 2\n self.board_state = np.zeros(shape = (1, (self.width-1) * self.height * 2))\n self.empty_states = set()\n\n self.move_to_state = None\n\n for i in range(self.board_state_size):\n self.empty_states.add(i)\n \n self.scores = [0,0]","title":""},{"docid":"875bfe209602e303398b296f829a5739","score":"0.5006537","text":"def create_board(self):\n\t\t\n\t\tprint(\"This will print the board ready for playing.\")","title":""},{"docid":"c74159b2631d46e409a8b4568f1d3d2e","score":"0.49985194","text":"def highlight_player(self):\n if self._model.get_turn():\n player_1=tk.Label(self._master,text=\"Player 1: X\",font='Arial 15 bold',bg=\"green\")\n player_1.grid(row=1,column=0)\n player_2=tk.Label(self._master,text=\"Player 2: O\",font='Arial 15 bold')\n player_2.grid(row=2,column=0)\n else:\n player_1=tk.Label(self._master,text=\"Player 1: X\",font='Arial 15 bold')\n player_1.grid(row=1,column=0)\n player_2=tk.Label(self._master,text=\"Player 2: O\",font='Arial 15 bold',bg=\"green\")\n player_2.grid(row=2,column=0)","title":""},{"docid":"85680912e9144fbb7a7965a4bbb6161a","score":"0.49831086","text":"def create_board(self):\r\n for i in range(ROW):\r\n temporary_list = []\r\n for j in range(COL):\r\n lable = tkinter.Label(self.frame2, image=self.photo,\r\n width=\"50\", height=\"50\", bg='#66B3FF')\r\n lable.photo = self.photo\r\n lable.grid(row=i, column =j)\r\n\r\n temporary_list.append(lable)\r\n self.cell_list.append(temporary_list)","title":""},{"docid":"3bb94d9db1b4e7ad432e09a4abbba736","score":"0.49772006","text":"def new_leader(self, number):\n old_leader = self.get_leader_name()\n self.leader_index = number\n leader = self.get_leader_name()\n print(leader, \"deposes\", old_leader, \"as the new leader of the pack\")","title":""},{"docid":"68110e28de7c91dfd5b54812844ec2ae","score":"0.49769977","text":"def __init__(self, master, model):\n self._master = master\n self._model = model\n self._title=tk.Label(self._master,text=\"Tic-tac-toe Game\",font='Arial 20 bold',fg = 'red')\n self._title.grid(row=0,column=0)\n self._score_label = tk.Label(self._master, text=\"Score: {} - {}\".format(self._model.get_score()[0],self._model.get_score()[1]),font='Arial 15 bold')\n self._score_label.grid(row=3, column =0)","title":""},{"docid":"75d99efdbe5c60d83a5b7acc199eb355","score":"0.49751136","text":"def show_winner(self, winners: [PlayerBase]):\n pass","title":""},{"docid":"b3e6bbfdb4d032ad04fb990948d68efc","score":"0.4974871","text":"def view_round(round_):\n keys = [\n 'id', 'title', 'status',\n 'registration_opens_at', 'is_registration_open',\n 'training_opens_at', 'is_training_open',\n 'min_team_size', 'max_team_size', 'min_team_ratio',\n 'allow_team_changes'\n ]\n return {key: round_[key] for key in keys}","title":""}],"string":"[\n {\n \"docid\": \"437d7c5565d4948aa3c19c5e239cc8fe\",\n \"score\": \"0.7503058\",\n \"text\": \"def leaderboard(self):\\n click.echo(\\\"\\\\n----Leaderboard----\\\")\\n players = OrderedDict(\\n sorted(self.players.items(), key=lambda x: getitem(x[1], \\\"round\\\"))\\n )\\n columns = [\\\"Rank\\\", \\\"Name\\\", \\\"Round\\\", \\\"Score\\\"]\\n row_format = \\\"{:>15}\\\" * len(columns)\\n click.echo(row_format.format(*columns))\\n rank = 1\\n for k, v in players.items():\\n click.echo(row_format.format(rank, v[\\\"name\\\"], v[\\\"round\\\"], v[\\\"score\\\"]))\\n rank = rank + 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6375733d6284707ba6aaf4b11d8578d3\",\n \"score\": \"0.72021484\",\n \"text\": \"def show_leaderboard():\\n leaderboard_data = get_sorted_scores()\\n return render_template(\\\"leaderboard.html\\\", leaderboard_data=leaderboard_data)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dda1b561034c1f3cee9e7e65a12b0ebe\",\n \"score\": \"0.6722733\",\n \"text\": \"def buildLeaderboard(self):\\n\\t\\toverall_standings = []\\n\\t\\toverall_fpl_points = {}\\n\\t\\toverall_league_points = {}\\n\\t\\toverall_fines = {}\\n\\t\\tgameweeks = {}\\n\\t\\tfor i in self.league.league_gameweeks:\\n\\t\\t\\tgameweeks[i.fpl_event] = []\\n\\t\\tfor i in self.members:\\n\\t\\t\\toverall_fpl_points[i] = 0\\n\\t\\t\\toverall_league_points[i] = 0\\n\\t\\t\\toverall_fines[i] = 0\\n\\t\\t\\trunning_league_points = 0\\n\\t\\t\\tfor j in i.league_gameweeks:\\n\\t\\t\\t\\t\\tif j.league_id == self.league.league_id:\\n\\t\\t\\t\\t\\t\\toverall_fpl_points[i] += j.fpl_points\\n\\t\\t\\t\\t\\t\\toverall_league_points[i] += j.championship_points\\n\\t\\t\\t\\t\\t\\toverall_fines[i] += j.fines\\n\\t\\t\\t\\t\\t\\trunning_league_points += j.championship_points\\n\\t\\t\\t\\t\\t\\tgameweeks[j.fpl_event].append({\\n\\t\\t\\t\\t\\t\\t\\t'player': j.user,\\n\\t\\t\\t\\t\\t\\t\\t'fpl_points': j.fpl_points,\\n\\t\\t\\t\\t\\t\\t\\t'league_points': j.championship_points,\\n\\t\\t\\t\\t\\t\\t\\t'running_league_points': running_league_points,\\n\\t\\t\\t\\t\\t\\t\\t'fines': j.fines,\\n\\t\\t\\t\\t\\t\\t\\t'notes': j.notes\\n\\t\\t\\t\\t\\t\\t\\t})\\n\\t\\tfor i in gameweeks:\\n\\t\\t\\tnewlist = sorted(gameweeks[i], key=lambda k: k['fpl_points'], reverse=True)\\n\\t\\t\\tgameweeks[i] = newlist\\n\\t\\tfor i in overall_fpl_points:\\n\\t\\t\\toverall_standings.append({'player': i.username, 'fpl_points': overall_fpl_points[i], 'P & L': '+£69'})\\n\\t\\tfor i in overall_league_points:\\n\\t\\t\\tfor j in overall_standings:\\n\\t\\t\\t\\tif j['player'] == i.username:\\n\\t\\t\\t\\t\\tj['league_points'] = overall_league_points[i]\\n\\t\\tfor i in overall_fines:\\n\\t\\t\\tfor j in overall_standings:\\n\\t\\t\\t\\tif j['player'] == i.username:\\n\\t\\t\\t\\t\\tj['fines'] = overall_fines[i]\\n\\t\\tsorted_overall = sorted(overall_standings, key=lambda k: k['league_points'], reverse=True)\\n\\t\\tself.leaderboard = sorted_overall\\n\\t\\tself.gameweeks = gameweeks\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f494a072a544585cb57a2fab8d31f093\",\n \"score\": \"0.6574417\",\n \"text\": \"def make_leaderboard(self):\\n leaderboard = [(player_id, rating.mu - 3*rating.sigma) for player_id, rating in self._ratings.items()]\\n leaderboard = sorted(leaderboard, key=operator.itemgetter(1), reverse=True)\\n return leaderboard\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cafa310f61b85a6ec569e99cfafaa7c9\",\n \"score\": \"0.65529096\",\n \"text\": \"async def leaderboard(self, ctx: commands.Context):\\n\\n\\t\\treturn await ctx.send(await TrophyLeaderboard(ctx).create())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b74ed25514064c5e10d0a2346470cd3a\",\n \"score\": \"0.6290081\",\n \"text\": \"def displayLeaderboard():\\n\\n global leaderboard\\n\\n Y_OFFSET = 50\\n TOP_OFFSET = 150\\n\\n leaderboard_title = largeFont.render(\\\"Leader Board\\\", True, BLACK)\\n leaderboard_titleRect = leaderboard_title.get_rect()\\n leaderboard_titleRect.center = ((WIN_WIDTH / 2), 50)\\n screen.blit(leaderboard_title, leaderboard_titleRect)\\n\\n for idx, person in enumerate(leaderboard):\\n person_entry_txt = person[0] + '.'\\n person_entry_txt += (' ') + person[1]\\n\\n leaderboard_entry = mediumFont.render(person_entry_txt, True, BLACK)\\n leaderboard_entryRect = leaderboard_entry.get_rect()\\n leaderboard_entryRect.bottomleft = ((WIN_WIDTH / 4), TOP_OFFSET + Y_OFFSET * idx)\\n screen.blit(leaderboard_entry, leaderboard_entryRect)\\n\\n score_entry_txt = person[2]\\n rightAlign = mediumFont.size(person[2])[0]\\n\\n leaderboard_entryScore = mediumFont.render(score_entry_txt, True, BLACK)\\n leaderboard_entryScoreRect = leaderboard_entryScore.get_rect()\\n leaderboard_entryScoreRect.bottomleft = ((3 * WIN_WIDTH / 4) - rightAlign, TOP_OFFSET + Y_OFFSET * idx)\\n screen.blit(leaderboard_entryScore, leaderboard_entryScoreRect)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"29930feaccab07b2952f3ab60de65a3e\",\n \"score\": \"0.6228906\",\n \"text\": \"async def leaderboard(self, ctx):\\n leaderboard = await self.bot.database.get_top_reps()\\n embed = discord.Embed(colour=EMBED_ACCENT_COLOUR)\\n embed.set_author(\\n name=\\\"Reputation Leaderboard\\\",\\n icon_url=\\\"https://images.emojiterra.com/mozilla/512px/1f3c6.png\\\",\\n )\\n for member_id, points in leaderboard:\\n member = ctx.guild.get_member(member_id)\\n if member:\\n embed.add_field(\\n name=str(member.nick if member.nick is not None else member.name),\\n value=points,\\n inline=False,\\n )\\n await ctx.send(embed=embed)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6d25344c35e84a3b8b9d248159286e44\",\n \"score\": \"0.6203027\",\n \"text\": \"def leaderboard(self, id):\\n from .game import GameLeaderboard\\n return GameLeaderboard.leaderboard(self.short_name, id)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b68db73095cfe00a7258b97ef6b10d3f\",\n \"score\": \"0.61703\",\n \"text\": \"async def leaderboard(self, ctx):\\r\\n guild = ctx.guild.id\\r\\n users = await self.bot.db.fetch(\\\"SELECT * FROM levels WHERE guild_id=$1 ORDER BY xp DESC\\\", guild)\\r\\n\\r\\n ranks = {(y := x + 1): f\\\"#{y}\\\" if y > 3 else f\\\"{self.leaderboard_emojis[y]}\\\" for x in range(10)}\\r\\n fields = {\\\"member\\\": [], \\\"level\\\": [], \\\"rank\\\": []}\\r\\n\\r\\n for index, value in zip(range(10), users):\\r\\n user = self.bot.get_user(value[\\\"user_id\\\"])\\r\\n if user:\\r\\n if (rank := index + 1) == 1:\\r\\n top_user = f\\\"Top Member: 🏆 **{str(user)}**\\\"\\r\\n fields[\\\"rank\\\"].append(ranks[rank])\\r\\n fields[\\\"member\\\"].append(f\\\"**{user.name}**\\\")\\r\\n xp = round((4 * (value['lvl'] ** 3) / 5))\\r\\n fields[\\\"level\\\"].append(f\\\"Level {value['lvl']} ({value['xp']}/{xp})\\\")\\r\\n else:\\r\\n for value in fields.values():\\r\\n value.append(\\\"...\\\")\\r\\n\\r\\n leaderboard = discord.Embed(color=ctx.me.colour, title=f\\\"Top 10 in {ctx.guild.name}\\\", description=top_user,\\r\\n timestamp=ctx.message.created_at)\\r\\n leaderboard.set_author(name=ctx.author.name, icon_url=ctx.author.avatar_url)\\r\\n\\r\\n author = await self.bot.db.fetchrow(\\\"SELECT * FROM levels WHERE user_id=$1 AND guild_id=$2\\\",\\r\\n ctx.author.id, guild)\\r\\n\\r\\n if author:\\r\\n fields[\\\"rank\\\"].append(ranks[users.index(author) + 1])\\r\\n fields[\\\"member\\\"].append(f\\\"**{ctx.author.name}**\\\")\\r\\n xp = round((4 * (author['lvl'] ** 3) / 5))\\r\\n fields[\\\"level\\\"].append(f\\\"Level {author['lvl']} ({author['xp']}/{xp})\\\")\\r\\n\\r\\n leaderboard.add_field(name=\\\"Rank\\\", value=\\\"\\\\n\\\".join(fields[\\\"rank\\\"]), inline=True)\\r\\n leaderboard.add_field(name=\\\"Member\\\", value=\\\"\\\\n\\\".join(fields[\\\"member\\\"]), inline=True)\\r\\n leaderboard.add_field(name=\\\"Level\\\", value=\\\"\\\\n\\\".join(fields[\\\"level\\\"]), inline=True)\\r\\n\\r\\n await ctx.send(embed=leaderboard)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8b902558ddeb9651656b204c2bbf7032\",\n \"score\": \"0.6161494\",\n \"text\": \"def display_points(self) -> List[dict]:\\n self.log.debug('Generating scores...')\\n score_df = self.get_score(in_game=True) # type: pd.DataFrame\\n self.log.debug(f'Retrieved {score_df.shape[0]} players\\\\' scores')\\n if score_df.shape[0] == 0:\\n return [\\n BKitB.make_block_section('No one has scored yet. Check back later!')\\n ]\\n score_df.loc[:, 'rank_emoji'] = [':blank:' for _ in range(score_df.shape[0])]\\n if score_df['current'].sum() != 0:\\n # Determine the emojis for 1st, 2nd and 3rd place\\n is_zero = (score_df.current == 0)\\n for r in range(1, 6):\\n score_df.loc[(score_df.current_rank == r) & (~is_zero), 'rank_emoji'] = f':cah-rank-{r}:'\\n # Determine if the recent winner is on a streak\\n score_df['streak'] = ''\\n if self.current_game is not None:\\n player_id, n_streak = self.determine_streak()\\n if n_streak > 0:\\n # Streak!\\n score_df.loc[score_df.player_id == player_id, 'streak'] = ':steak:' * n_streak\\n # Set order of the columns\\n score_df = score_df[['rank_chg_emoji', 'rank_emoji', 'current_rank', 'display_name',\\n 'current', 'overall', 'streak']]\\n score_df = score_df.sort_values('current_rank', ascending=True)\\n\\n scores_list = []\\n for i, r in score_df.iterrows():\\n dname = f\\\"{r['display_name'][:14].title():_<15}\\\"\\n emos = f\\\"{r['rank_chg_emoji'] + r['rank_emoji']}\\\"\\n c_rank = f\\\"{r['current_rank']:>2.0f}\\\"\\n scores = f\\\"*`{r['current']:>4.0f}`*`({r['overall']:>4.0f})`\\\"\\n streak = f\\\"{r['streak']}\\\"\\n line = f\\\"{emos}*`{c_rank}`*` {dname}`:diddlecoin:{scores}{streak}\\\"\\n scores_list.append(line)\\n\\n return [\\n BKitB.make_context_section([BKitB.markdown_section('*Current Scores*')]),\\n BKitB.make_block_divider(),\\n BKitB.make_block_section(scores_list)\\n ]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3b85cda051d1b14514e22f0914e73c40\",\n \"score\": \"0.6047141\",\n \"text\": \"def show_leaderboard_screen(self):\\n self.leaderboard.retrieve()\\n self.clear()\\n self.add_button(\\\"Back\\\", self.show_main_screen)\\n\\n if self.leaderboard.entries is None:\\n self.add_button(\\\"Error Loading Leaderboard\\\", None)\\n else:\\n for i in range(0, 4 if len(self.leaderboard.entries) > 6 else len(self.leaderboard.entries)):\\n entry = self.leaderboard.entries[i]\\n self.add_button(entry.name + \\\" Lvl=\\\" + entry.level + \\\" Scr=\\\" + str(entry.score) + \\\" Wve=\\\" + str(entry.wave), None)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"74ac9d9e21fe3d8009430143163d4ee6\",\n \"score\": \"0.60361916\",\n \"text\": \"def load_leaderboard(self, name: str, show: bool = False) -> list:\\n leaderboard = []\\n members = self.__find_models(name, leaderboard_prefix)\\n if len(members) > 0:\\n for member in members:\\n self.cursor.execute(\\n f\\\"SELECT * FROM {self.schema}.{PREPROCESSORS} WHERE MODEL = '{member[0]}' \\\"\\n f\\\"AND VERSION = {member[1]}\\\"\\n )\\n columns = self.cursor.fetchall()[\\n 0\\n ] # MODEL, VERSION, JSON, TRAIN_ACC, VALID_ACC, ALGORITHM, METRIC\\n prep = self.__setup_preprocessor(columns[2])\\n if \\\"Regressor\\\" in columns[5]:\\n algo = self.reg_dict[columns[5]]\\n if \\\"Classifier\\\" in columns[5]:\\n algo = self.cls_dict[columns[5]]\\n algo.model = super().load_model(member[0], member[1])\\n algo.title = columns[5]\\n model_board_member = ModelBoard(algo, 0, prep)\\n model_board_member.valid_score = columns[4]\\n model_board_member.train_score = columns[3]\\n leaderboard.append(model_board_member)\\n if show:\\n print(\\\"\\\\033[33m{}\\\".format(f\\\"Loaded leaderboard '{name}':\\\\n\\\"))\\n place = 1\\n for member in leaderboard:\\n print(\\n \\\"\\\\033[33m {}\\\".format(\\n str(place)\\n + \\\". \\\"\\n + str(member.algorithm.model)\\n + f\\\"\\\\n Train {columns[6]} score: \\\"\\n + str(member.train_score)\\n + f\\\"\\\\n Holdout {columns[6]} score: \\\"\\n + str(member.valid_score)\\n )\\n )\\n print(\\\"\\\\033[0m {}\\\".format(\\\"\\\"))\\n place += 1\\n else:\\n raise StorageError(\\\"Leaderboard not found!\\\")\\n return leaderboard\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6c44c80cea96895f9c3990277d80b4dc\",\n \"score\": \"0.5880609\",\n \"text\": \"def rd1leaderboard(request):\\n\\n #Add views\\n playing_players = Rd1SlotModel.objects.filter(player_name__isnull=False)\\n\\n endurance_leader = Rd1SlotModel.objects.aggregate(Max('endurance_score'))\\n\\n #Add context\\n context = {\\n 'playing_players': playing_players,\\n 'endurance_leader': endurance_leader,\\n }\\n\\n return render(request, 'rd1Leaderboard.html', context=context)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b70190aa8df97b0bc7195b975aee1d0b\",\n \"score\": \"0.5836765\",\n \"text\": \"def leaderboard():\\n #allows the leaderboard to be viewed without updating/adding to it\\n if request.method == 'POST':\\n new_leaderboard_name = request.form[\\\"leaderboard_name\\\"] #store the users input name\\n #add the new highscore to the database\\n new_highscore= User(username=new_leaderboard_name, score=flask_session['user_score'])\\n db.session.add(new_highscore)\\n db.session.commit()\\n\\n leaderboard = User.query.order_by(desc(User.score)).limit(10).all()\\n\\n return render_template('leaderboard.html', leaderboard=leaderboard)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f4837939975e559645382e5d71401c45\",\n \"score\": \"0.58296454\",\n \"text\": \"def fullleaderboard (request):\\n # Define views here\\n score_submit = EventEntryModel.objects.exclude(winner__isnull=True).count()\\n active_players = PlayerModel.objects.all()\\n\\n loaded_points = list(EventEntryModel.objects.aggregate(Sum('points')).values())[0]\\n awarded_points = list(EventEntryModel.objects.exclude(winner__isnull=True).aggregate(Sum('points')).values())[0]\\n\\n context = {\\n 'score_submit': score_submit,\\n 'active_players': active_players,\\n 'loaded_points': loaded_points,\\n 'awarded_points': awarded_points,\\n 'tour_name_top_line': tour_name_top_line,\\n 'tour_name_highlight': tour_name_highlight,\\n }\\n return render(request, 'fullLeaderboard.html', context=context)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7dd6028e15ece7f8f95d3f3b2a0caa2c\",\n \"score\": \"0.5812916\",\n \"text\": \"async def _server_leaderboard(self, ctx, top : int=10):\\n server = ctx.message.server\\n if top < 1:\\n top = 10\\n bank_sorted = sorted(self.bank.get_server_accounts(server),\\n key=lambda x: x.balance, reverse=True)\\n if len(bank_sorted) < top:\\n top = len(bank_sorted)\\n topten = bank_sorted[:top]\\n highscore = \\\"\\\"\\n place = 1\\n for acc in topten:\\n highscore += str(place).ljust(len(str(top))+1)\\n highscore += (acc.name+\\\" \\\").ljust(23-len(str(acc.balance)))\\n highscore += str(acc.balance) + \\\"\\\\n\\\"\\n place += 1\\n if highscore:\\n if len(highscore) < 1985:\\n await self.bot.say(\\\"```py\\\\n\\\"+highscore+\\\"```\\\")\\n else:\\n await self.bot.say(\\\"```css\\\\nThe leaderboard is too big to be displayed. Try with a lower <top> parameter.\\\\n```\\\")\\n else:\\n await self.bot.say(\\\"```css\\\\nThere are no accounts in the bank.\\\\n```\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bbabea782c7d022c2385f13b6aa721c6\",\n \"score\": \"0.5779456\",\n \"text\": \"def test_get_leaderboard(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dae9a8857eb42415296cdc731bc2346e\",\n \"score\": \"0.57685685\",\n \"text\": \"async def leaderboard(self, ctx, *args):\\r\\n if ctx.channel.id == BANK_CHANNEL or ctx.channel.id in GENERAL_CHANNELS:\\r\\n if len(args) == 0:\\r\\n name = None\\r\\n key = 'total'\\r\\n elif len(args) == 1:\\r\\n if 'key=' in args[0]:\\r\\n name = None\\r\\n for userkey in users.DEFAULT_ACCOUNT.keys():\\r\\n if args[0][4:] in userkey:\\r\\n key = userkey\\r\\n break\\r\\n else:\\r\\n if args[0][4:] == 'total':\\r\\n key = 'total'\\r\\n else:\\r\\n await ctx.send(f'Key {args[0]} not found.')\\r\\n return\\r\\n\\r\\n else:\\r\\n name = args[0]\\r\\n key = 'total'\\r\\n else:\\r\\n key = args[0]\\r\\n if key not in users.DEFAULT_ACCOUNT.keys():\\r\\n if key != 'total':\\r\\n await ctx.send(f'Key {key} not found.')\\r\\n return\\r\\n name = ' '.join(args[1:])\\r\\n\\r\\n key_name = {\\r\\n users.ITEMS_KEY: 'gold',\\r\\n users.SLAYER_XP_KEY: 'slayer',\\r\\n users.COMBAT_XP_KEY: 'combat',\\r\\n users.GATHER_XP_KEY: 'gather',\\r\\n users.ARTISAN_XP_KEY: 'artisan',\\r\\n users.COOK_XP_KEY: 'cooking',\\r\\n users.QUESTS_KEY: 'quest points',\\r\\n 'total': 'total level'\\r\\n }\\r\\n if key not in key_name.keys():\\r\\n await ctx.send(f\\\"Can't make leaderboard with key {key}.\\\")\\r\\n return\\r\\n\\r\\n leaderboard = users.get_values_by_account(key=key)\\r\\n\\r\\n out = f':hammer_pick: __**{key.upper()} LEADERBOARD**__ :crossed_swords:\\\\n'\\r\\n if name is None:\\r\\n try:\\r\\n for i in range(10):\\r\\n user_id, amount = leaderboard[i]\\r\\n amount_formatted = '{:,}'.format(amount)\\r\\n member = ctx.message.guild.get_member(user_id)\\r\\n if member is not None:\\r\\n name = get_display_name(member)\\r\\n else:\\r\\n name = f'User {user_id}'\\r\\n out += f'**({1 + i}) {name}**: '\\r\\n if key == users.ITEMS_KEY:\\r\\n out += f'{amount_formatted} coins\\\\n'\\r\\n elif key == users.QUESTS_KEY:\\r\\n out += f'{amount_formatted} quests\\\\n'\\r\\n elif key == 'total':\\r\\n out += f'{amount_formatted} levels\\\\n'\\r\\n else:\\r\\n out += f'{users.xp_to_level(amount)} *({amount_formatted}xp)*\\\\n'\\r\\n except IndexError:\\r\\n pass\\r\\n await ctx.send(out)\\r\\n else:\\r\\n if name == 'bottom':\\r\\n try:\\r\\n for i in range(len(leaderboard) - 10, len(leaderboard)):\\r\\n user_id, amount = leaderboard[i]\\r\\n amount_formatted = '{:,}'.format(amount)\\r\\n member = ctx.message.guild.get_member(user_id)\\r\\n if member is not None:\\r\\n name = get_display_name(member)\\r\\n else:\\r\\n name = f'User {user_id}'\\r\\n out += f'**({1 + i}) {name}**: '\\r\\n if key == users.ITEMS_KEY:\\r\\n out += f'{amount_formatted} coins\\\\n'\\r\\n elif key == users.QUESTS_KEY:\\r\\n out += f'{amount_formatted} quests\\\\n'\\r\\n elif key == 'total':\\r\\n out += f'{amount_formatted} levels\\\\n'\\r\\n else:\\r\\n out += f'{users.xp_to_level(amount)} *({amount_formatted}xp)*\\\\n'\\r\\n except IndexError:\\r\\n pass\\r\\n await ctx.send(out)\\r\\n else:\\r\\n try:\\r\\n name_list = [x[0] for x in leaderboard]\\r\\n name_member = parse_name(ctx.message.guild, name)\\r\\n name_index = name_list.index(name_member.id)\\r\\n if name_index < 5:\\r\\n lower = 0\\r\\n upper = 10\\r\\n else:\\r\\n lower = name_index - 5\\r\\n upper = name_index + 5\\r\\n if name_index + 5 > len(leaderboard):\\r\\n upper = len(leaderboard)\\r\\n lower = len(leaderboard) - 10\\r\\n for i in range(lower, upper):\\r\\n user_id, amount = leaderboard[i]\\r\\n amount_formatted = '{:,}'.format(amount)\\r\\n member = ctx.message.guild.get_member(user_id)\\r\\n if member is not None:\\r\\n name = get_display_name(member)\\r\\n else:\\r\\n name = f'User {user_id}'\\r\\n out += f'**({1 + i}) {name}**: '\\r\\n if key == users.ITEMS_KEY:\\r\\n out += f'{amount_formatted} coins\\\\n'\\r\\n elif key == users.QUESTS_KEY:\\r\\n out += f'{amount_formatted} quests\\\\n'\\r\\n elif key == 'total':\\r\\n out += f'{amount_formatted} levels\\\\n'\\r\\n else:\\r\\n out += f'{users.xp_to_level(amount)} *({amount_formatted}xp)*\\\\n'\\r\\n except IndexError:\\r\\n pass\\r\\n except ValueError:\\r\\n await ctx.send(f'Name {name} not found in leaderboard.')\\r\\n await ctx.send(out)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6502ffba2dbced13f2f4a4f9f966cc3f\",\n \"score\": \"0.5761324\",\n \"text\": \"def compose(canvas):\\n #Write the score for each player\\n canvas.draw_text('Blue '+str(blue_score_G),[60,585],30,'Blue')\\n canvas.draw_text('Brown '+str(brown_score_G),[430,585],30,'Brown')\\n #Draw the grid unless there is no winner\\n if get_winner()==0:\\n boardDraw=Draw()\\n boardDraw.draw_board(canvas)\\n set_pieces(canvas,0,0)\\n #Draw winner box\\n #Brown is the winner\\n elif get_winner()==1:\\n brownWinsDraw=Draw()\\n brownWinsDraw.draw_winner(canvas,'Brown') \\n #Blue is the winner \\n elif get_winner()==-1:\\n blueWinsDraw=Draw()\\n blueWinsDraw.draw_winner(canvas,'Blue')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"798b9d5c1c3c546cf1dc37ee60c9219d\",\n \"score\": \"0.5759699\",\n \"text\": \"def getleaderboard(request):\\n note_session_activity(request)\\n\\n if not using_unique_session(request.user):\\n return HttpResponseForbidden()\\n\\n owner_filter = request.GET['owner_filter']\\n body_pk = int(request.GET['legislative_body'])\\n leg_body = LegislativeBody.objects.get(pk=body_pk)\\n\\n display = getleaderboarddisplay(leg_body, owner_filter)\\n if display is None:\\n return HttpResponse(\\n _('No display configured'), content_type='text/plain')\\n\\n plans = getvalidplans(leg_body, request.user\\n if owner_filter == 'mine' else None)\\n\\n try:\\n html = display.render(plans, request)\\n return HttpResponse(html, content_type='text/html; charset=utf-8')\\n except Exception, ex:\\n logger.warn('Leaderboard could not be fetched.')\\n logger.debug('Reason: %s', ex)\\n return HttpResponse(str(ex), content_type='text/plain')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4c5183029122dd3245874568b3b70244\",\n \"score\": \"0.57568544\",\n \"text\": \"def make_leaderboard(object, leaderboard_frame=None,\\n sort_metric=\\\"AUTO\\\",\\n extra_columns=[],\\n scoring_data=\\\"AUTO\\\"):\\n def _get_models(obj):\\n if isinstance(obj, list):\\n result = []\\n for o in obj:\\n res = _get_models(o)\\n if isinstance(res, list):\\n result.extend(res)\\n else:\\n result.append(res)\\n return result\\n elif hasattr(obj, \\\"leaderboard\\\"):\\n return [row[0] for row in obj.leaderboard.as_data_frame(use_pandas=False, header=False)]\\n elif hasattr(obj, \\\"model_ids\\\"):\\n return obj.model_ids\\n elif hasattr(obj, \\\"model_id\\\"):\\n return obj.model_id\\n elif is_type(obj, str):\\n return obj\\n else:\\n raise H2OValueError(\\\"Unsupported model_id!\\\")\\n\\n model_ids = _get_models(object)\\n assert is_type(model_ids, [str])\\n\\n if scoring_data.lower() not in (\\\"auto\\\", \\\"train\\\", \\\"valid\\\", \\\"xval\\\"):\\n raise H2OValueError(\\\"Scoring data has to be set to one of \\\\\\\"AUTO\\\\\\\", \\\\\\\"train\\\\\\\", \\\\\\\"valid\\\\\\\", \\\\\\\"xval\\\\\\\".\\\")\\n\\n m_frame = H2OFrame._expr(ExprNode(\\n \\\"makeLeaderboard\\\",\\n model_ids,\\n leaderboard_frame.key if leaderboard_frame is not None else \\\"\\\",\\n sort_metric,\\n extra_columns,\\n scoring_data))\\n return m_frame\",\n \"title\": \"\"\n },\n {\n \"docid\": \"752d02403c47af838429a85f865b45d0\",\n \"score\": \"0.57278216\",\n \"text\": \"def leaderboards(self):\\n from .game import GameLeaderboard\\n return GameLeaderboard.leaderboards(self.short_name)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7bddd05f16c5849c0de06c1619c399ae\",\n \"score\": \"0.57092756\",\n \"text\": \"def generate_board():\\n\\t# score_label.config(text=str(b.score))\\n\\t# score_label.after(100, generate_board)\\n\\tfor i in range(len(b.board)):\\n\\t\\tfor j in range(len(b.board[0])):\\n\\t\\t\\tnum = b.board[i][j]\\n\\t\\t\\tbackground_color = color_map[num]\\n\\t\\t\\tcanvas.create_rectangle(j*100, i*100, (j+1)*100, (i+1)*100, fill=background_color)\\n\\t\\t\\tif num != 0:\\n\\t\\t\\t\\tif num == 2 or num == 4:\\n\\t\\t\\t\\t\\tnum_color = \\\"#776e65\\\"\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tnum_color = \\\"#f9f6f2\\\"\\n\\t\\t\\t\\tcanvas.create_text(j*100 + offset_map[num], i*100 + 50, anchor=tk.W, font=(\\\"Arial\\\", size_map[num]), text=str(num), fill=num_color)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9674bbc8fbb9aa414e0df80fccf220de\",\n \"score\": \"0.5705014\",\n \"text\": \"async def _global_leaderboard(self, top : int=10):\\n if top < 1:\\n top = 10\\n bank_sorted = sorted(self.bank.get_all_accounts(),\\n key=lambda x: x.balance, reverse=True)\\n unique_accounts = []\\n for acc in bank_sorted:\\n if not self.already_in_list(unique_accounts, acc):\\n unique_accounts.append(acc)\\n if len(unique_accounts) < top:\\n top = len(unique_accounts)\\n topten = unique_accounts[:top]\\n highscore = \\\"\\\"\\n place = 1\\n for acc in topten:\\n highscore += str(place).ljust(len(str(top))+1)\\n highscore += (\\\"{} |{}| \\\".format(acc.name, acc.server.name)).ljust(23-len(str(acc.balance)))\\n highscore += str(acc.balance) + \\\"\\\\n\\\"\\n place += 1\\n if highscore:\\n if len(highscore) < 1985:\\n await self.bot.say(\\\"```py\\\\n\\\"+highscore+\\\"```\\\")\\n else:\\n await self.bot.say(\\\"```css\\\\nThe leaderboard is too big to be displayed. Try with a lower <top> parameter.\\\\n```\\\")\\n else:\\n await self.bot.say(\\\"```css\\\\nThere are no accounts in the bank.\\\\n```\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5e04c5112c4339c0075facf6aa06ceb6\",\n \"score\": \"0.5663041\",\n \"text\": \"def scoreboard():\\r\\n scores = {}\\r\\n for user in models.User.query.all():\\r\\n if user.is_admin:\\r\\n continue\\r\\n user.solved_questions = list(filter(lambda x: not x.question.hide, user.solved_questions))\\r\\n scores[user.get_id()] = { 'username' : user.username, 'score': user.total_score, 'last_question_date': user.solved_questions[len(user.solved_questions)-1].date if len(user.solved_questions) > 0 else datetime.datetime.min }\\r\\n\\r\\n scores = helpers.sortScoreDict(scores)\\r\\n \\\"\\\"\\\"\\r\\n enumerate generates indices for the orderedDict\\r\\n \\\"\\\"\\\"\\r\\n return render_template(\\\"scoreboard.html\\\",scores=enumerate(scores.items()))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"beb981b58ae7a0cf2ba16781b2f09256\",\n \"score\": \"0.5655952\",\n \"text\": \"def playerdetail (request,name):\\n\\n #Basic player details\\n player_image = PlayerModel.objects.get(name=name).image\\n player_HC = PlayerModel.objects.get(name=name).HC\\n player_highfinish = PlayerModel.objects.get(name=name).highfinish\\n player_tournum = PlayerModel.objects.get(name=name).tournum\\n player_totalpoints = LeaderBoardModel.objects.get(player=name).overall_total\\n player_totalrank = LeaderBoardModel.objects.filter(overall_total__gt=player_totalpoints).count() + 1\\n\\n\\n target_holes = 10 #Change to 10 in production\\n\\n ##START ROUND 1 CALCULATIONS -->\\n #Trigger to show score only when round finished\\n try:\\n rd1holes_played = Rd1SlotModel.objects.get(player_name__name=name).player_holesplayed\\n if rd1holes_played is None:\\n rd1holes_played = 0\\n else:\\n rd1holes_played = Rd1SlotModel.objects.get(player_name__name=name).player_holesplayed\\n except:\\n rd1holes_played = 0\\n\\n\\n\\n #Rd1 Player golf score & rank\\n if rd1holes_played >= target_holes:\\n rd1golf_score = Rd1SlotModel.objects.get(player_name__name=name).player_score\\n rd1golf_scoreRank = Rd1SlotModel.objects.filter(player_score__lt=rd1golf_score).count() + 1\\n rd1golf_stbl = Rd1SlotModel.objects.get(player_name__name=name).player_stbl\\n rd1golf_stblRank = Rd1SlotModel.objects.filter(player_stbl__gt=rd1golf_stbl).count() + 1\\n else:\\n rd1golf_score = \\\"-\\\"\\n rd1golf_scoreRank= \\\"n/a\\\"\\n rd1golf_stbl = \\\"-\\\"\\n rd1golf_stblRank= \\\"n/a\\\"\\n\\n #Rd1PlayerPoints\\n try:\\n rd1golf_points = LeaderBoardModel.objects.get(player=name).rd1_golf\\n except:\\n rd1golf_points = \\\"-\\\"\\n try:\\n rd1golf_rank = LeaderBoardModel.objects.filter(rd1_golf__gt=rd1golf_points).count() + 1\\n except:\\n rd1golf_rank = \\\"-\\\"\\n try:\\n rd1ctpld_points = LeaderBoardModel.objects.get(player=name).rd1_ctpld\\n except:\\n rd1ctpld_points = \\\"-\\\"\\n try:\\n rd1ctpld_rank = LeaderBoardModel.objects.filter(rd1_ctpld__gt=rd1ctpld_points).count() + 1\\n except:\\n rd1ctpld_rank = \\\"-\\\"\\n try:\\n rd1bonus_points = LeaderBoardModel.objects.get(player=name).rd1_bonus\\n except:\\n rd1bonus_points = \\\"-\\\"\\n try:\\n rd1bonus_rank = LeaderBoardModel.objects.filter(rd1_bonus__gt=rd1bonus_points).count() + 1\\n except:\\n rd1bonus_rank = \\\"-\\\"\\n try:\\n rd1total_points = rd1golf_points + rd1ctpld_points + rd1bonus_points\\n except:\\n rd1total_points = \\\"-\\\"\\n try:\\n rd1total_rank = LeaderBoardModel.objects.filter(rd1_total__gt=rd1total_points).count() + 1\\n except:\\n rd1total_rank = \\\"-\\\"\\n\\n try:\\n round1overall_points = list(LeaderBoardModel.objects.aggregate(Sum('rd1_total')).values())[0]\\n except:\\n round1overall_points = 0\\n\\n\\n ##START ROUND 2 CALCULATIONS -->\\n #Trigger to show score only when round finished\\n try:\\n rd2holes_played = Rd2SlotModel.objects.get(player_name__name=name).player_holesplayed\\n if rd2holes_played is None:\\n rd2holes_played = 0\\n else:\\n rd2holes_played = Rd2SlotModel.objects.get(player_name__name=name).player_holesplayed\\n except:\\n rd2holes_played = 0\\n\\n #Rd2 Player golf score & rank\\n if rd2holes_played >= target_holes:\\n rd2golf_score = Rd2SlotModel.objects.get(player_name__name=name).player_score\\n rd2golf_scoreRank = Rd2SlotModel.objects.filter(player_score__lt=rd2golf_score).count() + 1\\n rd2golf_stbl = Rd2SlotModel.objects.get(player_name__name=name).player_stbl\\n rd2golf_stblRank = Rd2SlotModel.objects.filter(player_stbl__gt=rd2golf_stbl).count() + 1\\n else:\\n rd2golf_score = \\\"-\\\"\\n rd2golf_scoreRank= \\\"n/a\\\"\\n rd2golf_stbl = \\\"-\\\"\\n rd2golf_stblRank= \\\"n/a\\\"\\n\\n #Rd2PlayerPoints\\n try:\\n rd2golf_points = LeaderBoardModel.objects.get(player=name).rd2_golf\\n except:\\n rd2golf_points = \\\"-\\\"\\n try:\\n rd2golf_rank = LeaderBoardModel.objects.filter(rd2_golf__gt=rd2golf_points).count() + 1\\n except:\\n rd2golf_rank = \\\"-\\\"\\n try:\\n rd2ctpld_points = LeaderBoardModel.objects.get(player=name).rd2_ctpld\\n except:\\n rd2ctpld_points = \\\"-\\\"\\n try:\\n rd2ctpld_rank = LeaderBoardModel.objects.filter(rd2_ctpld__gt=rd2ctpld_points).count() + 1\\n except:\\n rd2ctpld_rank = \\\"-\\\"\\n try:\\n rd2bonus_points = LeaderBoardModel.objects.get(player=name).rd2_bonus\\n except:\\n rd2bonus_points = \\\"-\\\"\\n try:\\n rd2bonus_rank = LeaderBoardModel.objects.filter(rd2_bonus__gt=rd2bonus_points).count() + 1\\n except:\\n rd2bonus_rank = \\\"-\\\"\\n try:\\n rd2total_points = rd2golf_points + rd2ctpld_points + rd2bonus_points\\n except:\\n rd2total_points = \\\"-\\\"\\n try:\\n rd2total_rank = LeaderBoardModel.objects.filter(rd2_total__gt=rd2total_points).count() + 1\\n except:\\n rd2total_rank = \\\"-\\\"\\n\\n try:\\n round2overall_points = list(LeaderBoardModel.objects.aggregate(Sum('rd2_total')).values())[0]\\n except:\\n round2overall_points = 0\\n\\n ##START ROUND 3 CALCULATIONS -->\\n #Trigger to show score only when round finished\\n try:\\n rd3holes_played = Rd3SlotModel.objects.get(player_name__name=name).player_holesplayed\\n if rd3holes_played is None:\\n rd3holes_played = 0\\n else:\\n rd3holes_played = Rd3SlotModel.objects.get(player_name__name=name).player_holesplayed\\n except:\\n rd3holes_played = 0\\n\\n #Rd3 Player golf score & rank\\n if rd3holes_played >= target_holes:\\n rd3golf_score = Rd3SlotModel.objects.get(player_name__name=name).player_score\\n rd3golf_scoreRank = Rd3SlotModel.objects.filter(player_score__lt=rd2golf_score).count() + 1\\n rd3golf_stbl = Rd3SlotModel.objects.get(player_name__name=name).player_stbl\\n rd3golf_stblRank = Rd3SlotModel.objects.filter(player_stbl__gt=rd2golf_stbl).count() + 1\\n else:\\n rd3golf_score = \\\"-\\\"\\n rd3golf_scoreRank= \\\"n/a\\\"\\n rd3golf_stbl = \\\"-\\\"\\n rd3golf_stblRank= \\\"n/a\\\"\\n\\n #Rd2PlayerPoints\\n try:\\n rd3golf_points = LeaderBoardModel.objects.get(player=name).rd3_golf\\n except:\\n rd3golf_points = \\\"-\\\"\\n try:\\n rd3golf_rank = LeaderBoardModel.objects.filter(rd3_golf__gt=rd3golf_points).count() + 1\\n except:\\n rd3golf_rank = \\\"-\\\"\\n try:\\n rd3ctpld_points = LeaderBoardModel.objects.get(player=name).rd3_ctpld\\n except:\\n rd3ctpld_points = \\\"-\\\"\\n try:\\n rd3ctpld_rank = LeaderBoardModel.objects.filter(rd3_ctpld__gt=rd3ctpld_points).count() + 1\\n except:\\n rd3ctpld_rank = \\\"-\\\"\\n try:\\n rd3bonus_points = LeaderBoardModel.objects.get(player=name).rd3_bonus\\n except:\\n rd3bonus_points = \\\"-\\\"\\n try:\\n rd3bonus_rank = LeaderBoardModel.objects.filter(rd3_bonus__gt=rd3bonus_points).count() + 1\\n except:\\n rd3bonus_rank = \\\"-\\\"\\n try:\\n rd3total_points = rd3golf_points + rd3ctpld_points + rd3bonus_points\\n except:\\n rd3total_points = \\\"-\\\"\\n try:\\n rd3total_rank = LeaderBoardModel.objects.filter(rd3_total__gt=rd3total_points).count() + 1\\n except:\\n rd3total_rank = \\\"-\\\"\\n\\n try:\\n round3overall_points = list(LeaderBoardModel.objects.aggregate(Sum('rd3_total')).values())[0]\\n except:\\n round3overall_points = 0\\n\\n ##START OTHER_SCORES CALCULATIONS -->\\n\\n #Other Player Points\\n try:\\n social_points = LeaderBoardModel.objects.get(player=name).social\\n except:\\n social_points = \\\"-\\\"\\n try:\\n social_rank = LeaderBoardModel.objects.filter(social__gt=social_points).count() + 1\\n except:\\n social_rank = \\\"-\\\"\\n try:\\n bestdressed_points = LeaderBoardModel.objects.get(player=name).best_dressed\\n except:\\n bestdressed_points = \\\"-\\\"\\n try:\\n bestdressed_rank = LeaderBoardModel.objects.filter(best_dressed__gt=bestdressed_points).count() + 1\\n except:\\n bestdressed_rank = \\\"-\\\"\\n try:\\n tipping_points = LeaderBoardModel.objects.get(player=name).tipping\\n except:\\n tipping_points = \\\"-\\\"\\n try:\\n tipping_rank = LeaderBoardModel.objects.filter(tipping__gt=tipping_points).count() + 1\\n except:\\n tipping_rank = \\\"-\\\"\\n try:\\n othertotal_points = social_points + bestdressed_points + tipping_points\\n except:\\n othertotal_points = \\\"-\\\"\\n try:\\n othertotal_rank = LeaderBoardModel.objects.filter(other_total__gt=othertotal_points).count() + 1\\n except:\\n othertotal_rank = \\\"-\\\"\\n\\n try:\\n otheroverall_points = list(LeaderBoardModel.objects.aggregate(Sum('other_total')).values())[0]\\n except:\\n otheroverall_points = 0\\n\\n## == END SCORING CALCS ==\\n\\n context ={\\n 'name': name,\\n 'player_image': player_image,\\n 'player_HC': player_HC,\\n 'player_highfinish': player_highfinish,\\n 'player_tournum': player_tournum,\\n 'player_totalpoints': player_totalpoints,\\n 'player_totalrank': player_totalrank,\\n 'rd1golf_score': rd1golf_score,\\n 'rd1golf_stbl': rd1golf_stbl,\\n 'rd1golf_scoreRank': rd1golf_scoreRank,\\n 'rd1golf_stblRank': rd1golf_stblRank,\\n 'rd1golf_points': rd1golf_points,\\n 'rd1golf_rank': rd1golf_rank,\\n 'rd1ctpld_points': rd1ctpld_points,\\n 'rd1ctpld_rank': rd1ctpld_rank,\\n 'rd1bonus_points': rd1bonus_points,\\n 'rd1bonus_rank': rd1bonus_rank,\\n 'rd1total_points': rd1total_points,\\n 'rd1total_rank': rd1total_rank,\\n 'round1overall_points': round1overall_points,\\n 'rd2golf_score': rd2golf_score,\\n 'rd2golf_stbl': rd2golf_stbl,\\n 'rd2golf_scoreRank': rd2golf_scoreRank,\\n 'rd2golf_stblRank': rd2golf_stblRank,\\n 'rd2golf_points': rd2golf_points,\\n 'rd2golf_rank': rd2golf_rank,\\n 'rd2ctpld_points': rd2ctpld_points,\\n 'rd2ctpld_rank': rd2ctpld_rank,\\n 'rd2bonus_points': rd2bonus_points,\\n 'rd2bonus_rank': rd2bonus_rank,\\n 'rd2total_points': rd2total_points,\\n 'rd2total_rank': rd2total_rank,\\n 'round2overall_points': round2overall_points,\\n 'rd3golf_score': rd3golf_score,\\n 'rd3golf_stbl': rd3golf_stbl,\\n 'rd3golf_scoreRank': rd3golf_scoreRank,\\n 'rd3golf_stblRank': rd3golf_stblRank,\\n 'rd3golf_points': rd3golf_points,\\n 'rd3golf_rank': rd3golf_rank,\\n 'rd3ctpld_points': rd3ctpld_points,\\n 'rd3ctpld_rank': rd3ctpld_rank,\\n 'rd3bonus_points': rd3bonus_points,\\n 'rd3bonus_rank': rd3bonus_rank,\\n 'rd3total_points': rd3total_points,\\n 'rd3total_rank': rd3total_rank,\\n 'round3overall_points': round3overall_points,\\n 'social_points': social_points,\\n 'social_rank': social_rank,\\n 'bestdressed_points': bestdressed_points,\\n 'bestdressed_rank': bestdressed_rank,\\n 'tipping_points': tipping_points,\\n 'tipping_rank': tipping_rank,\\n 'othertotal_points': othertotal_points,\\n 'othertotal_rank': othertotal_rank,\\n 'otheroverall_points': otheroverall_points,\\n\\n }\\n\\n return render(request, 'playerDetail.html', context=context)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e75b49b24fb2501d75bc989162072b39\",\n \"score\": \"0.56511414\",\n \"text\": \"def high_scores(self):\\n self.top = tk.Toplevel(self._master,width=80,height = 80)\\n self.top.title(\\\"Top 3\\\")\\n top_label = tk.Label(self.top,text=\\\"Hight Scores\\\", bg = 'medium spring green')\\n top_label.config(height =1, font = ((None,20)))\\n top_label.pack(side = tk.TOP,fill = tk.X)\\n first_player = tk.Label(self.top, text = '{0}:{1}s'.format(self.name[0],self._seconds))\\n first_player.pack(side = tk.TOP)\\n sec_player = tk.Label(self.top, text = '{0}:{1}s'.format(self.name[1],self._seconds))\\n sec_player.pack(side = tk.TOP)\\n th_player = tk.Label(self.top, text = '{0}:{1}s'.format(self.name[2],self._seconds))\\n th_player.pack(side = tk.TOP)\\n\\n top_button = tk.Button(self.top, text = 'Done',command = self.done)\\n top_button.pack(side = tk.TOP)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5b003ef09a068df920591e2a1618c889\",\n \"score\": \"0.56331533\",\n \"text\": \"def display_score_window(self):\\r\\n \\r\\n #does the score window exist?\\r\\n try:\\r\\n if self.score_window.winfo_exists() == 1:\\r\\n return\\r\\n except AttributeError:\\r\\n pass\\r\\n \\r\\n self.score_window = tkinter.Toplevel(self.board_window)\\r\\n\\r\\n #Player labels and scores\\r\\n ex_name = tkinter.Label(self.score_window, text='Excluded',\\r\\n font = self.prefs['disp_font'], fg = 'red')\\r\\n ex_name.grid(row = 0, column = 0, columnspan = 2)\\r\\n ex_score = tkinter.Label(self.score_window, textvariable=self.excluded_score,\\r\\n font = self.prefs['disp_font'], fg = 'red')\\r\\n ex_score.grid(row = 1, column = 0, columnspan = 2)\\r\\n \\r\\n for i,j in enumerate(self.players):\\r\\n col = (i+1) * 2\\r\\n \\r\\n p_name = tkinter.Label(self.score_window, text=j['name'], font = self.prefs['disp_font'])\\r\\n p_name.grid(row=0, column=col)\\r\\n\\r\\n p_score = tkinter.Label(self.score_window, textvariable=self.scores[i],\\r\\n font = self.prefs['disp_font'])\\r\\n p_score.grid(row = 1, column = col, columnspan = 2)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"82295137e8c69672c468eeb11df2a14e\",\n \"score\": \"0.5604512\",\n \"text\": \"def _get_highscore(self):\\n self._player_list = player_list = self._highscore.get_entries(game='basic')\\n \\n self.high_scores=tk.Toplevel(root)\\n self.high_scores.title('High Score List')\\n\\n self.high_score_title = tk.Label(self.high_scores, text= 'Top 10 Players\\\\n')\\n self.high_score_title.pack()\\n\\n for i, player_list in enumerate(player_list): # List top scoring players from 1 to 10 format\\n self.high_score_list = tk.Label(self.high_scores, text = \\\"[{}] ,{}\\\\n\\\".format(i+1,player_list)).pack()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4e9eacde1f1ec23048979852d73d99a7\",\n \"score\": \"0.5563783\",\n \"text\": \"async def leaderboard(self, ctx):\\n if ctx.invoked_subcommand is None:\\n await ctx.invoke(self._server_leaderboard)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c65811e0ee90fe44e7802c6af4baf24a\",\n \"score\": \"0.5561256\",\n \"text\": \"def test_scoreboard(self):\\n run.add_to_scoreboard(\\\"testSuite\\\", 12)\\n leaderboard = run.get_scoreboard()\\n \\n self.assertIn({\\\"username\\\":\\\"testSuite\\\", \\\"score\\\": 12}, leaderboard)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bb66f89263be375665c7f7303c124495\",\n \"score\": \"0.555781\",\n \"text\": \"def __repr__(self):\\n if self._repr is None:\\n # Player 0 scoring area\\n if self.turn == 1:\\n rows = [\\\" --\\\", \\\">| \\\", \\\" | \\\", \\\" | \\\", \\\" --\\\"]\\n else:\\n rows = [\\\" --\\\", \\\" | \\\", \\\" | \\\", \\\">| \\\", \\\" --\\\"]\\n rows[2] += str(self.scores[0]) + \\\" |\\\"\\n for r in [0,4]:\\n rows[r] += \\\"-\\\"*(len(str(self.scores[0])) + 2)\\n for r in [1,3]:\\n rows[r] += \\\" \\\"*len(str(self.scores[0])) + \\\" |\\\"\\n # houses\\n for h in range(self.houses.shape[1]):\\n width = len(str(self.houses[:,h].max()))\\n for r in [1,3]:\\n rows[r] += \\\" \\\" + str(self.houses[r//2,h])\\n rows[r] += \\\" \\\"*(width - len(str(self.houses[r//2,h]))) +\\\" |\\\"\\n for r in [0,2,4]:\\n rows[r] += \\\"-\\\"*(width + 3)\\n rows[2] = rows[2][:-1] + \\\"|\\\"\\n # player 1 scoring area\\n rows[2] += \\\" \\\" + str(self.scores[1]) + \\\" |\\\\n\\\"\\n for r in [0,4]:\\n rows[r] += \\\"-\\\"*(len(str(self.scores[1])) + 2) + \\\"\\\\n\\\"\\n for r in [1,3]:\\n rows[r] += \\\" \\\"*len(str(self.scores[1])) + \\\" |\\\"\\n if self.turn == 1:\\n rows[1] += \\\"<\\\\n\\\"\\n rows[3] += \\\"\\\\n\\\"\\n else:\\n rows[1] += \\\"\\\\n\\\"\\n rows[3] += \\\"<\\\\n\\\"\\n self._repr = \\\"\\\".join(rows)\\n return self._repr\",\n \"title\": \"\"\n },\n {\n \"docid\": \"648e2b9738edcdc22360410c3f34ba3b\",\n \"score\": \"0.55369973\",\n \"text\": \"def showCurrentRankings(self):\\n \\n font = pygame.font.Font(self.fontSrc, self.fontSize - self.fontSize//6)\\n sorted_players = sorted([p for p in self.players], key=lambda x: x.rank)\\n headerRankTxt = font.render(\\\"Here are the rankings:\\\", True, (0,0,0))\\n widthTxt, heightTxt = font.size(\\\"Here are the rankings:\\\")\\n self.screen.blit(headerRankTxt, (self.width//2 - widthTxt//2, (self.height//2 - heightTxt*2) + self.height//6))\\n\\n for i in range(len(self.players)):\\n sufixes = {1: \\\"st\\\", 2: \\\"nd\\\", 3: \\\"rd\\\", 4: \\\"th\\\"}\\n p = sorted_players[i]\\n playerTxt = font.render(str(p.rank) + sufixes[p.rank] + \\\": \\\" + p.name + \\\" (\\\" + str(p.points) + \\\"p)\\\", True, (0,0,0))\\n widthTxt, heightTxt = font.size(str(p.rank) + \\\": \\\" + p.name + \\\" (\\\" + str(p.points) + \\\"p)\\\")\\n\\n self.screen.blit(playerTxt, (self.width//2 - widthTxt//2, (self.height//2 + heightTxt*i) + self.height//6))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aecdfcdb1c829a40d1edf9814ca236\",\n \"score\": \"0.551315\",\n \"text\": \"def submit_leaderboard(self):\\n if self.leaderboard_name.text != \\\"\\\":\\n self.leaderboard.add(self.game.level.name, self.leaderboard_name.text, self.game.level.get_score(), self.game.wave.number)\\n self.game.load_level(self.game.level.name)\\n self.show_leaderboard_screen()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8216a688672600362f0f51952fc4ae05\",\n \"score\": \"0.5508417\",\n \"text\": \"def layout_board(self):\\n p = models.PieceType\\n back_row = [\\n p.ROOK, p.KNIGHT, p.BISHOP, p.QUEEN, p.KING, p.BISHOP, p.KNIGHT,\\n p.ROOK\\n ]\\n for file, piece_type in enumerate(back_row):\\n models.Piece.create(\\n piece_type=piece_type, rank=0, file=file,\\n side=models.Side.HOME, game=self.game\\n )\\n models.Piece.create(\\n piece_type=piece_type, rank=7, file=file,\\n side=models.Side.AWAY, game=self.game\\n )\\n for file in range(8):\\n models.Piece.create(\\n piece_type=p.PAWN, rank=1, file=file, side=models.Side.HOME,\\n game=self.game\\n )\\n models.Piece.create(\\n piece_type=p.PAWN, rank=6, file=file, side=models.Side.AWAY,\\n game=self.game\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4ecb46d16a7f56cb2aaacb8d0ed103d3\",\n \"score\": \"0.5501579\",\n \"text\": \"def print_matches(self):\\n\\n os.system('cls' if os.name == 'nt' else 'clear')\\n console = Console()\\n table = Table(title=colored('MATCHES', 'magenta'), show_header=True, header_style=\\\"bold blue\\\")\\n table.add_column('Round')\\n table.add_column('Player 1')\\n table.add_column('Score Player 1')\\n table.add_column('Score Player 2')\\n table.add_column('Player 2')\\n for round in self.rounds:\\n for match in round.matches:\\n if match.player1[1] == 0.0 and match.player2[1] == 0.0:\\n table.add_row(\\\"[orange1]\\\"+str(round.number),\\n \\\"[orange1]\\\"+match.player1[0].surname,\\n \\\"[orange1]\\\"+str(match.player1[1]),\\n \\\"[orange1]\\\"+str(match.player2[1]),\\n \\\"[orange1]\\\"+match.player2[0].surname,\\n )\\n elif round.number == 2 or round.number == 4:\\n table.add_row(\\\"[yellow]\\\"+str(round.number),\\n \\\"[yellow]\\\"+match.player1[0].surname,\\n \\\"[yellow]\\\"+str(match.player1[1]),\\n \\\"[yellow]\\\"+str(match.player2[1]),\\n \\\"[yellow]\\\"+match.player2[0].surname,\\n )\\n else:\\n table.add_row(\\\"[green]\\\"+str(round.number),\\n \\\"[green]\\\"+match.player1[0].surname,\\n \\\"[green]\\\"+str(match.player1[1]),\\n \\\"[green]\\\"+str(match.player2[1]),\\n \\\"[green]\\\"+match.player2[0].surname,\\n )\\n console.print(table)\\n self.print_color_meanings()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d9f7a217ceeb2c3068b96078deb0bb06\",\n \"score\": \"0.54946154\",\n \"text\": \"def show_top_five_on_leaderboard():\\n all_scores = []\\n with open(leaderboard_file, 'r') as file:\\n for line in file:\\n words = line.split('=')\\n leaderboard_score = int(words[1])\\n player = words[0]\\n all_scores.append((leaderboard_score, player))\\n print('Here are the current top 5 players in the leaderboard:')\\n sorted_scores = sorted(all_scores, reverse=True)[0:5]\\n for score, name in sorted_scores:\\n print('{} - {}'.format(name, score))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4164be066d3c3842f6ad5c32b3ac6ac9\",\n \"score\": \"0.5493811\",\n \"text\": \"def get_opponent_view(self, as_list = False):\\n if as_list:\\n view = [[location.opponent_view() for location in row] for row in self.grid]\\n else:\\n view = [BOARD_HEADING]\\n row_num = 1\\n for row in self.grid:\\n view.append(str(row_num).rjust(2) + \\\" \\\" + \\\" \\\".join(\\n [location.opponent_view() for location in row]))\\n row_num += 1\\n view.append(\\\"\\\")\\n return view\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f46e7b4f7e2f311aa08ccbd1270b2c6c\",\n \"score\": \"0.548125\",\n \"text\": \"def createGraph(self):\\n\\t\\tdata = []\\n\\t\\tfor i in self.members:\\n\\t\\t\\tx = \\\"rgba(220,220,220,1)\\\"\\n\\t\\t\\tv1 = str(randint(1,220))\\n\\t\\t\\tv2 = str(randint(1,220))\\n\\t\\t\\tv3 = str(randint(1,220))\\n\\t\\t\\tcolour = f\\\"rgba({v1},{v2},{v3},0.4)\\\"\\n\\t\\t\\tdata.append({'player': i.username, 'running_scores': [], 'gameweeks': [], 'colour': colour})\\n\\t\\tfor i in self.gameweeks:\\n\\t\\t\\tdata[0]['gameweeks'].append(i)\\n\\t\\t\\tfor j in data:\\n\\t\\t\\t\\tfor k in self.gameweeks[i]:\\n\\t\\t\\t\\t\\tif j['player'] == k['player'].username:\\n\\t\\t\\t\\t\\t\\tj['running_scores'].append(k['running_league_points'])\\n\\t\\tself.graph = data\",\n \"title\": \"\"\n },\n {\n \"docid\": \"589b52da5f44bb425ebec4201627a5b8\",\n \"score\": \"0.54764396\",\n \"text\": \"def enter_scores_round(self, one_tournament):\\n list_rounds = one_tournament.list_rounds\\n tournaments_form = TournamentForm()\\n tournaments_form.enter_scores(list_rounds[-1])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"39c82665d991c1f2e789098ec3719e7b\",\n \"score\": \"0.5447808\",\n \"text\": \"def draw_scores(self):\\n # player1 score\\n Label(\\n text=str(self.player1.score),\\n x=4,\\n y=self.window.height - 40,\\n font_name=\\\"helvetica\\\",\\n font_size=36\\n ).draw()\\n # var to store the position the label needs to be drawn at\\n # stays accurate enough till like 100000 ish\\n LABEL_X_POS = self.window.width - len(list(str(self.player2.score))) * 30\\n # player2 score\\n Label(\\n text=str(self.player2.score),\\n x=LABEL_X_POS,\\n y=self.window.height - 40,\\n font_name=\\\"helvetica\\\",\\n font_size=36\\n ).draw()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"542d019bb60548805a2a2244c2043544\",\n \"score\": \"0.54329664\",\n \"text\": \"def make_player_tree(self, frame):\\n\\n player_tree = ttk.Treeview(frame, columns=(\\\"name\\\", \\\"joins\\\", \\\"avgtime\\\", \\\"first\\\", \\\"second\\\", \\\"third\\\", \\\"winrate\\\", \\\"top3\\\", \\\"quits\\\", \\\"quitrate\\\"), height=25)\\n\\n #adjust column headers\\n player_tree.heading(\\\"name\\\", text=\\\"Player Name\\\", command=lambda: self.sort_tree_column(player_tree, \\\"name\\\", False))\\n player_tree.heading(\\\"joins\\\", text= \\\"Joins\\\", command=lambda: self.sort_tree_column_int(player_tree, \\\"joins\\\", False))\\n player_tree.heading(\\\"avgtime\\\", text= \\\"Average Time\\\", command=lambda: self.sort_tree_column(player_tree, \\\"avgtime\\\", False))\\n player_tree.heading(\\\"first\\\", text= \\\"First\\\", command=lambda: self.sort_tree_column_int(player_tree, \\\"first\\\", False))\\n player_tree.heading(\\\"second\\\", text= \\\"Second\\\", command=lambda: self.sort_tree_column_int(player_tree, \\\"second\\\", False))\\n player_tree.heading(\\\"third\\\", text= \\\"Third\\\", command=lambda: self.sort_tree_column_int(player_tree, \\\"third\\\", False))\\n player_tree.heading(\\\"winrate\\\", text= \\\"Win Rate\\\", command=lambda: self.sort_tree_column_flt(player_tree, \\\"winrate\\\", False))\\n player_tree.heading(\\\"top3\\\", text= \\\"Top3 Rate\\\", command=lambda: self.sort_tree_column_flt(player_tree, \\\"top3\\\", False))\\n player_tree.heading(\\\"quits\\\", text= \\\"Quits\\\", command=lambda: self.sort_tree_column_int(player_tree, \\\"quits\\\", False))\\n player_tree.heading(\\\"quitrate\\\", text= \\\"Quit Rate\\\", command=lambda: self.sort_tree_column_flt(player_tree, \\\"quitrate\\\", False))\\n\\n #adjust column widths\\n player_tree.column(\\\"#0\\\", width=10)\\n player_tree.column(\\\"name\\\", width=100, anchor=E)\\n player_tree.column(\\\"joins\\\", width=50, anchor=E)\\n player_tree.column(\\\"avgtime\\\", width=85, anchor=E)\\n player_tree.column(\\\"first\\\", width=50, anchor=E)\\n player_tree.column(\\\"second\\\", width=50, anchor=E)\\n player_tree.column(\\\"third\\\", width=50, anchor=E)\\n player_tree.column(\\\"winrate\\\", width=100, anchor=E)\\n player_tree.column(\\\"top3\\\", width=100, anchor=E)\\n player_tree.column(\\\"quits\\\", width=50, anchor=E)\\n player_tree.column(\\\"quitrate\\\", width=100, anchor=E)\\n\\n scroll_bar = ttk.Scrollbar(frame, orient=VERTICAL, command=player_tree.yview)\\n player_tree.configure(yscrollcommand=scroll_bar.set)\\n\\n return player_tree, scroll_bar\",\n \"title\": \"\"\n },\n {\n \"docid\": \"730c6743e6ee7ba3c380192aad56d262\",\n \"score\": \"0.54272944\",\n \"text\": \"def playerStandings():\\n\\n list = []\\n conn, c = connect()\\n \\\"\\\"\\\"get the wins number of each player\\\"\\\"\\\"\\n winCount = \\\"create view winCount as(select winner as winner , count(*) as num from Matches group by winner );\\\"\\n \\\"\\\"\\\"get the lose number of each player\\\"\\\"\\\" \\n loseCount = \\\"create view loseCount as(select player2 as loser, count(*) as num from Matches group by player2);\\\"\\n c.execute(winCount)\\n c.execute(loseCount)\\n conn.commit()\\n \\\"\\\"\\\"join the player name and id with win number\\\"\\\"\\\"\\n joinWin = \\\"create view joinWin as(select Players.id as id, Players.name as name, winCount.num as wins from Players left join winCount on Players.id = winCount.winner order by wins desc);\\\"\\n \\\"\\\"\\\"join the player id and lose number\\\"\\\"\\\"\\n joinLose = \\\"create view joinLose as(select Players.id as id, loseCount.num as num from Players left join loseCount on Players.id = loseCount.loser);\\\"\\n c.execute(joinWin)\\n c.execute(joinLose)\\n conn.commit()\\n \\\"\\\"\\\"put id, name, win, lose of each player together \\\"\\\"\\\"\\n alljoin = \\\"select joinWin.id as id, joinWin.name as name, joinWin.wins as wins, joinLose.num as lose from joinWin left join joinLose on joinWin.id = joinLose.id order by wins;\\\"\\n c.execute(alljoin)\\n conn.commit()\\n rows = c.fetchall()\\n \\\"\\\"\\\"use the win, lose to get the matches of each player, and change None to zero\\\"\\\"\\\"\\n count = 0\\n inlist = []\\n for row in rows:\\n for item in row:\\n if count != 3:\\n if item is None:\\n inlist.append(0)\\n else:\\n inlist.append(item)\\n count = count + 1\\n else:\\n if item is None:\\n inlist.append(inlist[2])\\n else:\\n inlist.append(item + inlist[2])\\n list.append(inlist)\\n count = 0\\n inlist = []\\n c.execute(\\\"drop view joinLose;\\\")\\n c.execute(\\\"drop view joinWin;\\\")\\n c.execute(\\\"drop view loseCount;\\\")\\n c.execute(\\\"drop view winCount;\\\")\\n conn.commit()\\n conn.close()\\n return list\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dd808073990afeb033df476dcfe62583\",\n \"score\": \"0.5383781\",\n \"text\": \"def player_standings():\\n refresh_views()\\n query = \\\"\\\"\\\"\\n SELECT players.id, players.name, v_player_wins.wins, v_matches.matches\\n FROM players\\n LEFT JOIN v_player_wins ON players.id = v_player_wins.player\\n LEFT JOIN v_matches ON players.id = v_matches.player\\n GROUP BY players.id, players.name, v_player_wins.wins, v_matches.matches\\n ORDER BY v_player_wins.wins DESC;\\n\\t\\\"\\\"\\\"\\n db, cursor = connect()\\n cursor.execute(query)\\n results = cursor.fetchall()\\n db.close()\\n return results\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e22e90ff922cac6c9dff78bef29f864f\",\n \"score\": \"0.53792036\",\n \"text\": \"def __init__(self, current_player_index: int, nr_players_in_round: int):\\n self.print_mode = False\\n self.new_round(current_player_index, nr_players_in_round)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"27baa46d22af61f48573c4ab1e51400a\",\n \"score\": \"0.53698516\",\n \"text\": \"def test_generate_rankings_after_round(self):\\n matches = Match.objects.filter(date_played=datetime.now())\\n players = Player.objects.filter(status=Player.ACTIVE).order_by('-ranking')\\n for player in players:\\n print(f'{player.first_name}, {player.last_name}, {player.ranking}')\\n for match in matches:\\n print(f'{match.player1}: {match.games_for_player1} vs {match.games_for_player2}: {match.player2}, {match.date_played}')\\n\\n print(f'Number of players: {len(players)}')\\n generate_rankings_after_round(matches, datetime.now(), f'Test cases round')\\n players = Player.objects.filter(status=Player.ACTIVE).order_by('ranking')\\n for player in players:\\n print(f'{player.first_name}, {player.last_name}, {player.ranking}')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4d006dcb3dd17fe8fa6dc50a0a24cf16\",\n \"score\": \"0.53599024\",\n \"text\": \"def leaderboard(request):\\n try:\\n earned_awards = Award.objects.filter(user=request.user)\\n except ObjectDoesNotExist:\\n earned_awards = {}\\n leaders_br = Profile.objects.filter(\\n category=\\\"beginnerrunner\\\").order_by('-distance')\\n leaders_r = Profile.objects.filter(category=\\\"runner\\\").order_by('-distance')\\n leaders_b = Profile.objects.filter(category=\\\"biker\\\").order_by('-distance')\\n leaders_d = Profile.objects.filter(\\n category=\\\"duathloner\\\").order_by('-distance')\\n leaders_f = Profile.objects.filter(\\n category=\\\"freestyler\\\").order_by('-distance')\\n\\n total_workouts = Workout.objects.all()\\n total_kms = 0\\n for workout in total_workouts:\\n total_kms += workout.distance\\n table_leaders_br = ProfileTable(leaders_br, prefix=\\\"leaders-br-\\\")\\n table_leaders_r = ProfileTable(leaders_r, prefix=\\\"leaders-r-\\\")\\n table_leaders_b = ProfileTable(leaders_b, prefix=\\\"leaders-b-\\\")\\n table_leaders_d = ProfileTable(leaders_d, prefix=\\\"leaders-d-\\\")\\n table_leaders_f = ProfileTable(leaders_f, prefix=\\\"leaders-f-\\\")\\n RequestConfig(request, paginate={\\n \\\"per_page\\\": 10\\n }).configure(table_leaders_br)\\n RequestConfig(request, paginate={\\n \\\"per_page\\\": 10\\n }).configure(table_leaders_r)\\n RequestConfig(request, paginate={\\n \\\"per_page\\\": 10\\n }).configure(table_leaders_b)\\n RequestConfig(request, paginate={\\n \\\"per_page\\\": 10\\n }).configure(table_leaders_d)\\n RequestConfig(request, paginate={\\n \\\"per_page\\\": 10\\n }).configure(table_leaders_f)\\n\\n return render(\\n request, 'ic_marathon_app/leaderboard.html', {\\n 'leaders_br': table_leaders_br,\\n 'leaders_br_c': len(leaders_br),\\n 'leaders_r': table_leaders_r,\\n 'leaders_r_c': len(leaders_r),\\n 'leaders_b': table_leaders_b,\\n 'leaders_b_c': len(leaders_b),\\n 'leaders_d': table_leaders_d,\\n 'leaders_d_c': len(leaders_d),\\n 'leaders_f': table_leaders_f,\\n 'leaders_f_c': len(leaders_f),\\n 'earned_awards': earned_awards,\\n 'total_kms': total_kms\\n })\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d267816d22ec1b67bc947c460e240144\",\n \"score\": \"0.53473336\",\n \"text\": \"def _compute_competition_leaderboard(session, submissions, leaderboard_type,\\n event_name):\\n event = session.query(Event).filter_by(name=event_name).one()\\n score_type = event.get_official_score_type(session)\\n score_name = event.official_score_name\\n\\n private_leaderboard = _compute_leaderboard(session, submissions, 'private',\\n event_name, with_links=False)\\n\\n col_selected_private = (['team', 'submission'] +\\n ['bag private ' + score_name,\\n 'bag public ' + score_name] +\\n ['train time [s]', 'test time [s]',\\n 'submitted at (UTC)'])\\n leaderboard_df = private_leaderboard[col_selected_private]\\n leaderboard_df = leaderboard_df.rename(\\n columns={'bag private ' + score_name: 'private ' + score_name,\\n 'bag public ' + score_name: 'public ' + score_name}\\n )\\n\\n # select best submission for each team\\n best_df = (leaderboard_df.groupby('team').min()\\n if score_type.is_lower_the_better\\n else leaderboard_df.groupby('team').max())\\n best_df = best_df[['public ' + score_name]].reset_index()\\n best_df['best'] = True\\n\\n # merge to get a best indicator column then select best\\n leaderboard_df = pd.merge(\\n leaderboard_df, best_df, how='left',\\n left_on=['team', 'public ' + score_name],\\n right_on=['team', 'public ' + score_name]\\n )\\n leaderboard_df = leaderboard_df.fillna(False)\\n leaderboard_df = leaderboard_df[leaderboard_df['best']]\\n leaderboard_df = leaderboard_df.drop(columns='best')\\n\\n # dealing with ties: we need the lowest timestamp\\n best_df = leaderboard_df.groupby('team').min()\\n best_df = best_df[['submitted at (UTC)']].reset_index()\\n best_df['best'] = True\\n leaderboard_df = pd.merge(\\n leaderboard_df, best_df, how='left',\\n left_on=['team', 'submitted at (UTC)'],\\n right_on=['team', 'submitted at (UTC)'])\\n leaderboard_df = leaderboard_df.fillna(False)\\n leaderboard_df = leaderboard_df[leaderboard_df['best']]\\n leaderboard_df = leaderboard_df.drop(columns='best')\\n\\n # sort by public score then by submission timestamp, compute rank\\n leaderboard_df = leaderboard_df.sort_values(\\n by=['public ' + score_name, 'submitted at (UTC)'],\\n ascending=[score_type.is_lower_the_better, True])\\n leaderboard_df['public rank'] = np.arange(len(leaderboard_df)) + 1\\n\\n # sort by private score then by submission timestamp, compute rank\\n leaderboard_df = leaderboard_df.sort_values(\\n by=['private ' + score_name, 'submitted at (UTC)'],\\n ascending=[score_type.is_lower_the_better, True])\\n leaderboard_df['private rank'] = np.arange(len(leaderboard_df)) + 1\\n\\n leaderboard_df['move'] = \\\\\\n leaderboard_df['public rank'] - leaderboard_df['private rank']\\n leaderboard_df['move'] = [\\n '{:+d}'.format(m) if m != 0 else '-' for m in leaderboard_df['move']]\\n\\n col_selected = [\\n leaderboard_type + ' rank', 'team', 'submission',\\n leaderboard_type + ' ' + score_name, 'train time [s]', 'test time [s]',\\n 'submitted at (UTC)'\\n ]\\n if leaderboard_type == 'private':\\n col_selected.insert(1, 'move')\\n\\n df = leaderboard_df[col_selected]\\n df = df.rename(columns={\\n leaderboard_type + ' ' + score_name: score_name,\\n leaderboard_type + ' rank': 'rank'\\n })\\n df = df.sort_values(by='rank')\\n return df\",\n \"title\": \"\"\n },\n {\n \"docid\": \"387d09e4c2da76e58f093e14096ea4c5\",\n \"score\": \"0.5346853\",\n \"text\": \"def _high_scores(self):\\n\\n #Creates a frame for highscore\\n high_score_window = tk.Toplevel()\\n high_score_window.title(\\\"High Scores\\\")\\n\\n \\n #Gets values stored in the file\\n data_input=self._high_score.get_entries()\\n Output = \\\"Rank | Name | Score | Comment\\\\n-----------------------------------\\\\n\\\"\\n i = 1\\n\\n \\n #Load values and shows on screen\\n for dictionary in data_input:\\n dictionary_values = str(dictionary.values())\\n name,score,comment = dictionary_values.split(sep = \\\",\\\")\\n Output = Output + str(i) +\\\" |\\\"+ name[14:-1] +\\\" |\\\"+ score +\\\" |\\\"+ comment[:-2]+\\\"\\\\n\\\"\\n i += 1\\n\\n #Button to returen to game \\n msg = tk.Message(high_score_window, text=Output)\\n msg.pack()\\n \\n button = tk.Button(high_score_window, text=\\\"Return to Game\\\", command=high_score_window.destroy)\\n button.pack()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"318a3b4013d7296e10710c0e42af5123\",\n \"score\": \"0.534458\",\n \"text\": \"def new_ranking(cls, user, wins, percent_won, avg_wrong):\\n ranking = Ranking(user=user,\\n wins=wins,\\n percent_won=percent_won,\\n avg_wrong=avg_wrong)\\n ranking.put()\\n return ranking\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1caa32cc323771573d67362870e6a6b3\",\n \"score\": \"0.5330613\",\n \"text\": \"def get_winner_board(self):\\n winner_info = self._best_individuals_select(1)\\n winner_board = {\\\"indiv\\\": winner_info[0][0], \\\"score\\\": winner_info[1][0]}\\n\\n return winner_board\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5c83b0469eaf668bd6f4a781959af545\",\n \"score\": \"0.53277326\",\n \"text\": \"def calculate_standings() -> str:\\n leaderboard = defaultdict(list)\\n for team, score in LEAGUE.items():\\n leaderboard[score].append(team)\\n for score, team in leaderboard.items():\\n leaderboard[score] = sorted(leaderboard[score], key=str.lower)\\n scores = sorted(leaderboard.keys(), reverse=True)\\n output_lst = []\\n rank = 1\\n while rank <= len(LEAGUE.keys()):\\n score = scores.pop(0)\\n suffix = 's' if score != 1 else ''\\n output = [f'{rank}. {team}, {score} pt{suffix}'\\n for team in leaderboard[score]]\\n\\n output_lst.extend(output)\\n rank += len(output)\\n return '\\\\n'.join(output_lst)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6954894d95f9e458b36e65fcbf8211df\",\n \"score\": \"0.5323443\",\n \"text\": \"def get_leaderboard(db):\\r\\n user_scores = []\\r\\n prediction_users_ref = db.collection(\\\"prediction_users\\\")\\r\\n user_docs = prediction_users_ref.stream()\\r\\n for user_doc in user_docs:\\r\\n user_info = user_doc.to_dict()\\r\\n if user_info[\\\"can_display\\\"]:\\r\\n email = user_doc.id\\r\\n username = email.split(\\\"@\\\")[0]\\r\\n user_scores.append((round(user_info[\\\"current_score\\\"], 2), username))\\r\\n user_scores.sort(key=lambda x: (-x[0], x[1]))\\r\\n return user_scores[:10]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"35cefada041b48405069925789eae52d\",\n \"score\": \"0.53195363\",\n \"text\": \"def get_player_view(self, as_list = False):\\n if as_list:\\n view = [[location.player_view() for location in row] for row in self.grid]\\n else:\\n view = [BOARD_HEADING]\\n row_num = 1\\n for row in self.grid:\\n view.append(str(row_num).rjust(2) + \\\" \\\" + \\\" \\\".join(\\n [location.player_view() for location in row]))\\n row_num += 1\\n view.append(\\\"\\\")\\n return view\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f119a8d1da96eafb5ebb3aff6fa8cc40\",\n \"score\": \"0.5314359\",\n \"text\": \"async def bet_board(self, ctx: commands.Context, top: int = 10):\\n reverse = True\\n if top == 0:\\n top = 10\\n elif top < 0:\\n reverse = False\\n top = -top\\n members_sorted = sorted(\\n await self._get_all_members(ctx.bot), key=lambda x: x.karma, reverse=reverse\\n )\\n if len(members_sorted) < top:\\n top = len(members_sorted)\\n topten = members_sorted[:top]\\n highscore = \\\"\\\"\\n place = 1\\n for member in topten:\\n highscore += str(place).ljust(len(str(top)) + 1)\\n highscore += \\\"{0} | \\\".format(member.name).ljust(18 - len(str(member.karma)))\\n highscore += str(member.karma) + \\\"\\\\n\\\"\\n place += 1\\n if highscore != \\\"\\\":\\n embed = discord.Embed(color=0xf3f1f6)\\n embed.title = \\\"Karma Returns\\\"\\n embed.description = \\\"\\\"\\\"```xl\\n{0}```\\\"\\\"\\\".format(highscore)\\n await ctx.send(embed=embed)\\n else:\\n await ctx.send(\\\"No one has gained or lost any karma\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5535675a0a19e5565fab7643ff6ea84b\",\n \"score\": \"0.5310064\",\n \"text\": \"def print_board(self):\\n print(\\\"row: \\\" + str(self.col))\\n print(\\\"col: \\\" + str(self.row))\\n top_line = \\\" \\\"\\n for c in range(self.col):\\n top_line += str(c) + \\\" \\\"\\n for row in range(self.row-1,-1,-1):\\n # for row in range(self.row):\\n line = str(row) + \\\" \\\"\\n for col in range(self.col):\\n if [row,col] == self.location:\\n line += \\\"[ @]\\\"\\n screen.blit(agentpic, ((col*rectangleWidth)+30, (row*rectangleHeight+rectangleHeight)+30)) \\n pygame.display.update()\\n '''pygame.draw.rect(screen, khaki, (col*rectangleWidth, row*rectangleHeight+rectangleHeight, rectangleWidth, rectangleHeight))\\n \\n pygame.draw.rect(screen, darkOliveGreen, (col*rectangleWidth-1, row*rectangleHeight+rectangleHeight-1, rectangleWidth-1, rectangleHeight-1))\\n pygame.display.update()'''\\n else:\\n score = str(self.board[row][col].score())\\n #if self.board[row][col].score()!=5:\\n\\n \\n #print(\\\"My score\\\",score )\\n if len(score) == 2:\\n line = line + \\\"[\\\" + str(self.board[row][col].score()) + \\\"]\\\"\\n else:\\n line = line + \\\"[ \\\" + str(self.board[row][col].score()) + \\\"]\\\"\\n print(line)\\n print(top_line + '\\\\n');\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b6310100da4bdc7408c643f81e28ba4d\",\n \"score\": \"0.5301851\",\n \"text\": \"def draw_ranks():\\n for y in range(SQUARE_SPACE + Y1, Y2-1, SQUARE_SPACE):\\n pygame.draw.line(screen, BLACKCOLOR, [X1, y], [X2, y], 1)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"35d1e816f3bb215a64141a82f151423b\",\n \"score\": \"0.5300731\",\n \"text\": \"def rd3leaderboard(request):\\n\\n #Add views\\n playing_players = Rd3SlotModel.objects.filter(player_name__isnull=False)\\n\\n #Add context\\n context = {\\n 'playing_players': playing_players,\\n }\\n\\n return render(request, 'rd3Leaderboard.html', context=context)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"77091a277a69ed4f4ef87f5eca07bf1c\",\n \"score\": \"0.52900624\",\n \"text\": \"def print_rounds(rounds):\\n win = Color.OKGREEN\\n end = Color.ENDC\\n for r in rounds:\\n print(f\\\"{Color.WARNING}{r.name}, start: {r.start}, end: {r.end}{Color.ENDC}\\\")\\n for i, game in enumerate(r.games):\\n for p in App.players:\\n if game[0][0] == p.id:\\n if game[0][1] == 1:\\n p1 = f\\\"{win}id: {p.id}, {p.surname} {p.name}, rank: {p.rank}, score: {game[0][1]}{end}\\\"\\n else:\\n p1 = f\\\"id: {p.id}, {p.surname} {p.name}, rank: {p.rank}, score: {game[0][1]}\\\"\\n if game[1][0] == p.id:\\n if game[1][1] == 1:\\n p2 = f\\\"{win}id: {p.id}, {p.surname} {p.name}, rank: {p.rank}, score: {game[1][1]}{end}\\\"\\n else:\\n p2 = f\\\"id: {p.id}, {p.surname} {p.name}, rank: {p.rank}, score: {game[1][1]}\\\"\\n print(f\\\"Game {i + 1} | {p1} vs. {p2}\\\")\\n return\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2fc809d126acf83546c14880505bc463\",\n \"score\": \"0.52662534\",\n \"text\": \"def to_rankings_form(self):\\n return UserRanking(\\n user_name=self.name,\\n games_played=self.games_played,\\n total_attempts=self.total_attempts,\\n total_points=self.total_points,\\n points_per_attempt=self.points_per_attempt)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"86f61654b22f949ed8424bc6bc678300\",\n \"score\": \"0.52253443\",\n \"text\": \"def new_round(self):\\n self.reset()\\n self.update_score_label() # updates score labels\\n self.change_label_p_name() # players name\\n self.clear_warning_label() # clear warning label\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6dfd252042867f7bbb8a7934741a04c9\",\n \"score\": \"0.5222292\",\n \"text\": \"def finish():\\n global change_leaderboard, leaderboard\\n screen.fill(BLACK)\\n screen.blit(Font_big.render('Вы уничтожили ' + str(points) + ' вирусов,', True, WHITE), (50, 50))\\n screen.blit(Font_big.render('физтех выздоровел, но все равно', True, WHITE), (50, 100))\\n screen.blit(Font_big.render('попал в дурку после сессии.', True, WHITE), (50, 150))\\n screen.blit(Font.render('leaderboard (score, name, amount of viruses, time)', True, WHITE), (50, 250))\\n input_leaders = open(\\\"leaderboard.txt\\\", \\\"r\\\")\\n leaderboard = input_leaders.readlines()\\n input_leaders.close()\\n output_leaders = open(\\\"leaderboard.txt\\\", \\\"w\\\")\\n for i in range(len(leaderboard)):\\n leaderboard[i] = leaderboard[i].split()\\n leaderboard[i][0] = int(leaderboard[i][0])\\n leaderboard.append([points, name, number_of_targets, str(play_time)])\\n leaderboard.sort(reverse=True)\\n for i in range(len(leaderboard)):\\n text = ''\\n for j in range(len(leaderboard[i])):\\n text += str(leaderboard[i][j]) + ' '\\n output_leaders.write(text + '\\\\n')\\n output_leaders.close()\\n for i in range(min(len(leaderboard), 18)):\\n text = ''\\n for j in range(len(leaderboard[i])):\\n text += str(leaderboard[i][j]) + ' '\\n screen.blit(Font.render(text, True, WHITE), (50 + 400 * (i // 9), 300 + 50 * (i % 9)))\\n change_leaderboard = False\\n pygame.display.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6a74d524d6d2049bef83f8d11cb552d5\",\n \"score\": \"0.52201647\",\n \"text\": \"def draftBoard(draftWindow, xwidth, yheight, numTeams, numRounds):\\r\\n \\r\\n #clear = Rectangle(Point(0,0),Point(1300,650))\\r\\n #clear.draw(draftWindow)\\r\\n #clear.setFill('white')\\r\\n\\r\\n #place round text\\r\\n for rd in range(numRounds): #gives me range from 0 to round-1\\r\\n roundText = Text(Point( (0.0385 * xwidth),\\r\\n ( (0.9 * yheight) - (rd *\\r\\n ( (0.7954 * yheight) /\\r\\n (numRounds - 1))))),\\r\\n 'Round '+str(rd+1))\\r\\n roundText.setSize(13)\\r\\n roundText.draw(draftWindow)\\r\\n\\r\\n \\\"\\\"\\\"\\r\\n rd1 = Text(Point(50,585),'Round 1')\\r\\n rd1.setSize(13)\\r\\n rd1.draw(draftWindow)\\r\\n rd2 = Text(Point(50,548.072),'Round 2')\\r\\n rd2.setSize(13)\\r\\n rd2.draw(draftWindow)\\r\\n rd3 = Text(Point(50,511.144),'Round 3')\\r\\n rd3.setSize(13)\\r\\n rd3.draw(draftWindow)\\r\\n rd4 = Text(Point(50,474.216),'Round 4')\\r\\n rd4.setSize(13)\\r\\n rd4.draw(draftWindow)\\r\\n rd5 = Text(Point(50,437.288),'Round 5')\\r\\n rd5.setSize(13)\\r\\n rd5.draw(draftWindow)\\r\\n rd6 = Text(Point(50,400.36),'Round 6')\\r\\n rd6.setSize(13)\\r\\n rd6.draw(draftWindow)\\r\\n rd7 = Text(Point(50,363.432),'Round 7')\\r\\n rd7.setSize(13)\\r\\n rd7.draw(draftWindow)\\r\\n rd8 = Text(Point(50,326.504),'Round 8')\\r\\n rd8.setSize(13)\\r\\n rd8.draw(draftWindow)\\r\\n rd9 = Text(Point(50,289.576),'Round 9')\\r\\n rd9.setSize(13)\\r\\n rd9.draw(draftWindow)\\r\\n rd10 = Text(Point(50,252.648),'Round 10')\\r\\n rd10.setSize(13)\\r\\n rd10.draw(draftWindow)\\r\\n rd11 = Text(Point(50,215.72),'Round 11')\\r\\n rd11.setSize(13)\\r\\n rd11.draw(draftWindow)\\r\\n rd12 = Text(Point(50,178.792),'Round 12')\\r\\n rd12.setSize(13)\\r\\n rd12.draw(draftWindow)\\r\\n rd13 = Text(Point(50,141.864),'Round 13')\\r\\n rd13.setSize(13)\\r\\n rd13.draw(draftWindow)\\r\\n rd14 = Text(Point(50,104.936),'Round 14')\\r\\n rd14.setSize(13)\\r\\n rd14.draw(draftWindow)\\r\\n rd15 = Text(Point(50,68.008),'Round 15')\\r\\n rd15.setSize(13)\\r\\n rd15.draw(draftWindow)\\r\\n \\\"\\\"\\\"\\r\\n\\r\\n \\\"\\\"\\\"\\r\\n #agghh, so ineficient, but works for team window\\r\\n rd1 = Text(Point(50,585),'QB')\\r\\n rd1.setSize(13)\\r\\n rd1.draw(teamWindow)\\r\\n rd2 = Text(Point(50,548.072),'RB')\\r\\n rd2.setSize(13)\\r\\n rd2.draw(teamWindow)\\r\\n rd3 = Text(Point(50,511.144),'RB')\\r\\n rd3.setSize(13)\\r\\n rd3.draw(teamWindow)\\r\\n rd4 = Text(Point(50,474.216),'WR')\\r\\n rd4.setSize(13)\\r\\n rd4.draw(teamWindow)\\r\\n rd5 = Text(Point(50,437.288),'WR')\\r\\n rd5.setSize(13)\\r\\n rd5.draw(teamWindow)\\r\\n rd6 = Text(Point(50,400.36),'TE')\\r\\n rd6.setSize(13)\\r\\n rd6.draw(teamWindow)\\r\\n rd7 = Text(Point(50,363.432),'FLEX')\\r\\n rd7.setSize(13)\\r\\n rd7.draw(teamWindow)\\r\\n rd8 = Text(Point(50,326.504),'K')\\r\\n rd8.setSize(13)\\r\\n rd8.draw(teamWindow)\\r\\n rd9 = Text(Point(50,289.576),'DST')\\r\\n rd9.setSize(13)\\r\\n rd9.draw(teamWindow)\\r\\n rd10 = Text(Point(50,252.648),'Bench')\\r\\n rd10.setSize(13)\\r\\n rd10.draw(teamWindow)\\r\\n rd11 = Text(Point(50,215.72),'Bench')\\r\\n rd11.setSize(13)\\r\\n rd11.draw(teamWindow)\\r\\n rd12 = Text(Point(50,178.792),'Bench')\\r\\n rd12.setSize(13)\\r\\n rd12.draw(teamWindow)\\r\\n rd13 = Text(Point(50,141.864),'Bench')\\r\\n rd13.setSize(13)\\r\\n rd13.draw(teamWindow)\\r\\n rd14 = Text(Point(50,104.936),'Bench')\\r\\n rd14.setSize(13)\\r\\n rd14.draw(teamWindow)\\r\\n rd15 = Text(Point(50,68.008),'Bench')\\r\\n rd15.setSize(13)\\r\\n rd15.draw(teamWindow)\\r\\n \\\"\\\"\\\"\\r\\n\\r\\n #vertical lines\\r\\n for v in range(numTeams+1):\\r\\n vertLine = Line( Point( ((0.104 * xwidth) + (v * ( (0.896 * xwidth) /\\r\\n numTeams))),\\r\\n (0.071 * yheight)),\\r\\n Point( ((0.104 * xwidth) + (v * ( (0.896 * xwidth) /\\r\\n numTeams))),\\r\\n yheight))\\r\\n vertLine.draw(draftWindow)\\r\\n\\r\\n\\r\\n #horizontal lines\\r\\n for h in range(numRounds+1):\\r\\n horizLine = Line( Point( 0,\\r\\n ( (0.923 * yheight) -\\r\\n (h * ( (0.7954 * yheight) /\\r\\n (numRounds - 1))))),\\r\\n Point( xwidth,\\r\\n ( (0.923 * yheight) -\\r\\n (h * ( (0.7954 * yheight) /\\r\\n (numRounds - 1))))))\\r\\n horizLine.draw(draftWindow)\\r\\n\\r\\n \\\"\\\"\\\"\\r\\n for x in range(15):\\r\\n line = Line(Point(135+(x*80.357),46.08), Point(135+(x*80.357),650))\\r\\n line.draw(draftWindow)\\r\\n #line = Line(Point(135+(x*80.357),46.08), Point(135+(x*80.357),650))\\r\\n #line.draw(teamWindow)\\r\\n for y in range(16):\\r\\n h = Line(Point(0,600-(y*36.928)), Point(1259.998,600-(y*36.928)))\\r\\n h.draw(draftWindow)\\r\\n #h = Line(Point(0,600-(y*36.928)), Point(1259.998,600-(y*36.928)))\\r\\n #h.draw(teamWindow)\\r\\n #so much shitty programming\\r\\n \\\"\\\"\\\" \\r\\n\\r\\n #button to submit team name\\r\\n submit = Button(draftWindow, Point( (0.6154 * xwidth),\\r\\n (0.0385 * yheight)),\\r\\n (0.058 * xwidth),\\r\\n (0.034 * yheight),\\r\\n 'Submit', 'red')\\r\\n submit.activate()\\r\\n\\r\\n \\\"\\\"\\\"\\r\\n #button to submit team name\\r\\n submit = Button(draftWindow,Point(800,25),75,22,'Submit','red')\\r\\n submit.activate()\\r\\n \\\"\\\"\\\"\\r\\n\\r\\n teamNum = 1 #The current team being labled\\r\\n\\r\\n while teamNum < numTeams + 1:\\r\\n\\r\\n #text to prompt user to enter the team names\\r\\n prompt = Text( Point( (0.40385 * xwidth), (0.03846 * yheight)),\\r\\n 'Enter Team '+str(teamNum))\\r\\n prompt.setSize(14)\\r\\n prompt.draw(draftWindow)\\r\\n\\r\\n #input window for entering team names\\r\\n teamNameInput = Entry( Point( (0.51923 * xwidth),\\r\\n (0.03846 * yheight)), 15)\\r\\n teamNameInput.draw(draftWindow)\\r\\n\\r\\n #wait for submit button to be pressed\\r\\n c = draftWindow.getMouse()\\r\\n while not submit.check(c) or teamNameInput.getText() == \\\"\\\":\\r\\n c = draftWindow.getMouse()\\r\\n\\r\\n team = Text( Point( ((0.1346 * xwidth) +\\r\\n ((0.064 * xwidth) * (teamNum - 1))),\\r\\n (0.9615 * y height)),\\r\\n teamNameInput.getText())\\r\\n team.setSize(12)\\r\\n team.draw(draftWindow)\\r\\n\\r\\n prompt.undraw()\\r\\n teamNum += 1\\r\\n\\r\\n#good to this point -----------------------------------\\r\\n\\r\\n\\r\\n \\\"\\\"\\\"\\r\\n\\r\\n #the number of the team\\r\\n tNum = 1\\r\\n\\r\\n while tNum < 15:\\r\\n \\r\\n #text to prompt user to enter the team names\\r\\n prompt = Text(Point(525,25),'Enter Team '+str(tNum))\\r\\n prompt.setSize(14)\\r\\n prompt.draw(draftWindow)\\r\\n \\r\\n #input window for entering the names\\r\\n tNameInput = Entry(Point(675,25),15)\\r\\n tNameInput.draw(draftWindow)\\r\\n \\r\\n c = draftWindow.getMouse()\\r\\n while not submit.check(c):\\r\\n c = draftWindow.getMouse()\\r\\n #lol, here comes more shitty programming\\r\\n if tNum == 1:\\r\\n t1 = Text(Point(175,625),tNameInput.getText())\\r\\n t1.setSize(12)\\r\\n t1.draw(draftWindow)\\r\\n #t1 = Text(Point(175,625),tNameInput.getText())\\r\\n #t1.setSize(12)\\r\\n #t1.draw(teamWindow)\\r\\n elif tNum == 2:\\r\\n t2 = Text(Point(250.357,625),tNameInput.getText())\\r\\n t2.setSize(12)\\r\\n t2.draw(draftWindow)\\r\\n #t2 = Text(Point(250.357,625),tNameInput.getText())\\r\\n #t2.setSize(12)\\r\\n #t2.draw(teamWindow)\\r\\n elif tNum == 3:\\r\\n t3 = Text(Point(330.714,625),tNameInput.getText())\\r\\n t3.setSize(12)\\r\\n t3.draw(draftWindow)\\r\\n #t3 = Text(Point(330.714,625),tNameInput.getText())\\r\\n #t3.setSize(12)\\r\\n #t3.draw(teamWindow)\\r\\n elif tNum == 4:\\r\\n t4 = Text(Point(411.071,625),tNameInput.getText())\\r\\n t4.setSize(12)\\r\\n t4.draw(draftWindow)\\r\\n #t4 = Text(Point(411.071,625),tNameInput.getText())\\r\\n #t4.setSize(12)\\r\\n #t4.draw(teamWindow)\\r\\n elif tNum == 5:\\r\\n t5 = Text(Point(491.428,625),tNameInput.getText())\\r\\n t5.setSize(12)\\r\\n t5.draw(draftWindow)\\r\\n #t5 = Text(Point(491.428,625),tNameInput.getText())\\r\\n #t5.setSize(12)\\r\\n #t5.draw(teamWindow)\\r\\n elif tNum == 6:\\r\\n t6 = Text(Point(571.785,625),tNameInput.getText())\\r\\n t6.setSize(12)\\r\\n t6.draw(draftWindow)\\r\\n #t6 = Text(Point(571.785,625),tNameInput.getText())\\r\\n #t6.setSize(12)\\r\\n #t6.draw(teamWindow)\\r\\n elif tNum == 7:\\r\\n t7 = Text(Point(652.142,625),tNameInput.getText())\\r\\n t7.setSize(12)\\r\\n t7.draw(draftWindow)\\r\\n #t7 = Text(Point(652.142,625),tNameInput.getText())\\r\\n #t7.setSize(12)\\r\\n #t7.draw(teamWindow)\\r\\n elif tNum == 8:\\r\\n t8 = Text(Point(732.499,625),tNameInput.getText())\\r\\n t8.setSize(12)\\r\\n t8.draw(draftWindow)\\r\\n #t8 = Text(Point(732.499,625),tNameInput.getText())\\r\\n #t8.setSize(12)\\r\\n #t8.draw(teamWindow)\\r\\n elif tNum == 9:\\r\\n t8 = Text(Point(812.856,625),tNameInput.getText())\\r\\n t8.setSize(12)\\r\\n t8.draw(draftWindow)\\r\\n #t8 = Text(Point(812.856,625),tNameInput.getText())\\r\\n #t8.setSize(12)\\r\\n #t8.draw(teamWindow)\\r\\n elif tNum == 10:\\r\\n t8 = Text(Point(893.213,625),tNameInput.getText())\\r\\n t8.setSize(12)\\r\\n t8.draw(draftWindow)\\r\\n #t8 = Text(Point(893.213,625),tNameInput.getText())\\r\\n #t8.setSize(12)\\r\\n #t8.draw(teamWindow)\\r\\n elif tNum == 11:\\r\\n t8 = Text(Point(973.57,625),tNameInput.getText())\\r\\n t8.setSize(12)\\r\\n t8.draw(draftWindow)\\r\\n #t8 = Text(Point(973.57,625),tNameInput.getText())\\r\\n #t8.setSize(12)\\r\\n #t8.draw(teamWindow)\\r\\n elif tNum == 12:\\r\\n t8 = Text(Point(1053.927,625),tNameInput.getText())\\r\\n t8.setSize(12)\\r\\n t8.draw(draftWindow)\\r\\n #t8 = Text(Point(1053.927,625),tNameInput.getText())\\r\\n #t8.setSize(12)\\r\\n #t8.draw(teamWindow)\\r\\n elif tNum == 13:\\r\\n t8 = Text(Point(1134.284,625),tNameInput.getText())\\r\\n t8.setSize(12)\\r\\n t8.draw(draftWindow)\\r\\n #t8 = Text(Point(1134.284,625),tNameInput.getText())\\r\\n #t8.setSize(12)\\r\\n #t8.draw(teamWindow)\\r\\n elif tNum == 14:\\r\\n t8 = Text(Point(1214.641,625),tNameInput.getText())\\r\\n t8.setSize(12)\\r\\n t8.draw(draftWindow)\\r\\n #t8 = Text(Point(1214.641,625),tNameInput.getText())\\r\\n #t8.setSize(12)\\r\\n #t8.draw(teamWindow)\\r\\n \\r\\n \\r\\n prompt.undraw()\\r\\n tNum += 1\\r\\n \\\"\\\"\\\"\\r\\n \\r\\n\\r\\n prompt = Text(Point(425,25),\\\"Enter Player Position and Name\\\")\\r\\n prompt.setSize(13)\\r\\n prompt.draw(draftWindow)\\r\\n\\r\\n pick = 1\\r\\n roundNum = 1\\r\\n\\r\\n while roundNum < 16: #number of pick in the draft will be 210\\r\\n tNameInput = Entry(Point(675,25),15)\\r\\n tNameInput.draw(draftWindow)\\r\\n #for player name\\r\\n\\r\\n #for player position\\r\\n pInput = Entry(Point(575,25),5)\\r\\n pInput.draw(draftWindow)\\r\\n c = draftWindow.getMouse()\\r\\n while not submit.check(c):\\r\\n c = draftWindow.getMouse()\\r\\n pPosition = pInput.getText()\\r\\n pName = tNameInput.getText()\\r\\n if pPosition == 'QB':\\r\\n pcolor = 'orange'\\r\\n elif pPosition == 'RB':\\r\\n pcolor = 'lightblue'\\r\\n elif pPosition == 'WR':\\r\\n pcolor = 'lightgreen'\\r\\n elif pPosition == 'TE':\\r\\n pcolor = 'pink'\\r\\n elif pPosition == 'K':\\r\\n pcolor = 'yellow'\\r\\n elif pPosition == 'DEF':\\r\\n pcolor = 'brown'\\r\\n elif pPosition == 'NA':\\r\\n pcolor = 'black'\\r\\n\\r\\n #here is where we need some demensions and to make the picks\\r\\n #snake back and fourth between the rounds\\r\\n if roundNum%2 == 1:\\r\\n placePick = Button(draftWindow,Point(175.1785+((pick-1)*80.357),581.536-((roundNum-1)*36.928)),80.357,36.928,pName,pcolor)\\r\\n placePick.activate()\\r\\n else:\\r\\n placePick = Button(draftWindow,Point((175.1785+(13*80.357))-((pick-1)*80.357),581.536-((roundNum-1)*36.928)),80.357,36.928,pName,pcolor)\\r\\n placePick.activate()\\r\\n\\r\\n pick = pick+1\\r\\n if pick == 15:\\r\\n pick = 1\\r\\n roundNum = roundNum + 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"288af7fd2976d7772ff78d16ce0b9589\",\n \"score\": \"0.5213266\",\n \"text\": \"def get_leader_board_split(self, date):\\n q = SQL.SQL(\\n '''\\n SELECT (((SUM(tbl.minutes) * 60) + SUM(tbl.seconds))::FLOAT / SUM(tbl.distance)) * 500 AS split, u.username\\n FROM (\\n SELECT user_id, minutes, seconds, distance\\n FROM workout AS w\\n JOIN erg AS e \\n ON w.workout_id = e.workout_id\\n WHERE w.time>{}\\n ) AS tbl\\n JOIN users AS u\\n ON u.user_id = tbl.user_id\\n GROUP BY u.username\\n ORDER BY split\\n '''\\n ).format(SQL.Placeholder())\\n\\n result = self.safe_execute(q, (date,), fetchone=False)\\n return result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fc90d7b48c2e96c47028b7b16b02475b\",\n \"score\": \"0.52115124\",\n \"text\": \"def show_add_to_leaderboard_screen(self):\\n self.clear()\\n self.add_button(\\\"Type Your Name\\\", None)\\n self.leaderboard_name = self.add_button(\\\"\\\", None)\\n self.add_button(\\\"Submit\\\", self.submit_leaderboard)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"054d2733a75f9694c50ec659998f2540\",\n \"score\": \"0.521088\",\n \"text\": \"def __init__(self):\\n\\n self.play = True\\n self.status = 'start_screen'\\n\\n self.winner = None\\n self.winning_tiles = []\\n self.win_combinations = []\\n\\n self.move_nr = 0\\n self.player_list = []\\n self.current_player_nr = 0\\n self.settings = {'vs_computer': False, 'board_size': 3}\\n\\n self.view = GameView()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ff2f754fd2e9d5b35564bcad28a725c2\",\n \"score\": \"0.5208663\",\n \"text\": \"def tournament(self):\\n\\n x_axis = []\\n y_axis = []\\n\\n for i in range(self.number_of_matches):\\n score = self.single_match()\\n\\n self.scores[0] += score[0]\\n self.scores[1] += score[1]\\n\\n self.percentage = self.scores[0] / (i + 1)\\n\\n x_axis.append(i + 1)\\n y_axis.append(self.percentage)\\n\\n print(\\\"The tournament completed:\\\\n\\\" +\\n str(self.player1) +\\n \\\": \\\" +\\n str(self.scores[0]) +\\n \\\" points.\\\\n\\\" +\\n str(self.player2) +\\n \\\": \\\" +\\n str(self.scores[1]) +\\n \\\" points.\\\")\\n\\n matplotlib.pyplot.plot(x_axis, y_axis)\\n matplotlib.pyplot.axis([0, self.number_of_matches, 0, 1])\\n matplotlib.pyplot.grid(True)\\n matplotlib.pyplot.axhline(y=0.5, linewidth=0.5, color=\\\"m\\\")\\n matplotlib.pyplot.xlabel(\\\"Number of games\\\")\\n matplotlib.pyplot.ylabel(\\n \\\"Winning percentage for \\\" + str(self.player1) + \\\" Vs.\\\\n\\\" + str(self.player2))\\n\\n print(\\\"player moves for \\\" + str(self.player1) + \\\": \\\\t\\\\t\\\" +\\n str(self.player1.get_results()[self.player1]))\\n print(\\\"player moves for \\\" + str(self.player2) + \\\": \\\\t\\\\t\\\" +\\n str(self.player2.get_results()[self.player2]))\\n\\n matplotlib.pyplot.show()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e61f02e56c7bbe55cfeb1df62165638b\",\n \"score\": \"0.52037007\",\n \"text\": \"def test_fetch_overall_leaderboard_position(self):\\n first_user = User.objects.create(username='SomeGuy', email='me@abv.bg', password='123', score=123, role=self.base_role)\\n second_user = User.objects.create(username='dGuy', email='d@abv.dg', password='123', score=122, role=self.base_role)\\n second_user2 = User.objects.create(username='dGumasky', email='molly@abv.bg', password='123', score=122, role=self.base_role)\\n second_user3 = User.objects.create(username='xdGumasky', email='xmolly@abv.bg', password='123', score=122, role=self.base_role)\\n fifth_user = User.objects.create(username='dbrr', email='dd@abv.bg', password='123', score=121, role=self.base_role)\\n fifth_user.save()\\n\\n self.assertEqual(fifth_user.fetch_overall_leaderboard_position(), 5)\\n self.assertEqual(second_user.fetch_overall_leaderboard_position(), 2)\\n self.assertEqual(second_user2.fetch_overall_leaderboard_position(), 2)\\n self.assertEqual(second_user3.fetch_overall_leaderboard_position(), 2)\\n self.assertEqual(first_user.fetch_overall_leaderboard_position(), 1)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ae1dfbff0883f6c0bae2341360719c0b\",\n \"score\": \"0.5200481\",\n \"text\": \"def showGameResultScreen(self, pla, sco, rounds_tot=None):\\n # pylint: disable=unused-argument,too-many-locals,too-many-statements\\n self.fadeUpDown(\\\"down\\\")\\n self.emptyGroup(self.disp_group)\\n\\n # Score list group + background + question mark for sorting\\n gs_group = Group()\\n\\n # Pale grey large GAME SCORES background\\n bg_scale = 6\\n sbg_dob1 = Label(self.font,\\n text=\\\"GAME\\\",\\n scale=bg_scale,\\n color=GS_COL)\\n sbg_dob1.x = (self.width - 4 * bg_scale * self.font_width) // 2\\n sbg_dob1.y = self.height // 4\\n sbg_dob2 = Label(self.font,\\n text=\\\"SCORES\\\",\\n scale=bg_scale,\\n color=GS_COL)\\n sbg_dob2.x = (self.width - 6 * bg_scale * self.font_width) // 2\\n sbg_dob2.y = self.height // 4 * 3\\n gs_group.append(sbg_dob1)\\n gs_group.append(sbg_dob2)\\n self.showGroup(gs_group)\\n self.fadeUpDown(\\\"up\\\")\\n\\n # Calculate maximum length player name\\n # and see if scores happen to already be in order\\n max_len = 0\\n prev_score = sco[0]\\n descending = True\\n for idx, (name, _) in enumerate(pla):\\n max_len = max(max_len, len(name))\\n if sco[idx] > prev_score:\\n descending = False\\n prev_score = sco[idx]\\n\\n fmt = \\\"{:\\\" + str(max_len) + \\\"s} {:2d}\\\"\\n x_pos = (self.width - (max_len + 3) * 2 * self.font_width) // 2\\n scale = 2\\n spacing = 4 if len(pla) <= 6 else 0\\n top_y_pos = round((self.height\\n - len(pla) * scale * self.font_height\\n - (len(pla) - 1) * spacing) / 2\\n + scale * self.font_height / 2)\\n scores_group = Group()\\n gs_group.append(scores_group)\\n for idx, (name, _) in enumerate(pla):\\n op_dob = Label(self.font,\\n text=fmt.format(name, sco[idx]),\\n scale=2,\\n color=(PLAYER_NAME_COL_FG if idx == 0 else OPP_NAME_COL_FG))\\n op_dob.x = x_pos\\n op_dob.y = top_y_pos + idx * (scale * self.font_height + spacing)\\n scores_group.append(op_dob)\\n time.sleep(0.2)\\n\\n # Sort the entries if needed\\n sort_scores = list(sco) # Make an independent local copy\\n if not descending:\\n empty_group = Group() # minor hack to aid swaps in scores_group\\n step = 3\\n qm_dob = Label(self.font,\\n text=\\\"?\\\",\\n scale=2,\\n color=QM_SORT_FG)\\n qm_dob.x = round(x_pos - 1.5 * scale * self.font_width)\\n gs_group.append(qm_dob)\\n while True:\\n swaps = 0\\n for idx in range(0, len(sort_scores) -1):\\n above_score = sort_scores[idx]\\n above_y = scores_group[idx].y\\n below_y = scores_group[idx + 1].y\\n qm_dob.y = (above_y + below_y) // 2\\n if above_score < sort_scores[idx + 1]:\\n qm_dob.text = \\\"<\\\"\\n qm_dob.color = QM_SORTING_FG\\n swaps += 1\\n\\n # make list of steps\\n range_y = below_y - above_y\\n offsets = list(range(step, range_y + 1, step))\\n # Ensure this goes to the exact final position\\n if offsets[-1] != range_y:\\n offsets.append(range_y)\\n\\n for offset in offsets:\\n scores_group[idx].y = above_y + offset\\n scores_group[idx + 1].y = below_y - offset\\n time.sleep(0.050)\\n\\n # swap the scores around\\n sort_scores[idx] = sort_scores[idx + 1]\\n sort_scores[idx + 1] = above_score\\n\\n # swap the graphical objects around using empty_group\\n # to avoid ValueError: Layer already in a group\\n old_above_dob = scores_group[idx]\\n old_below_dob = scores_group[idx + 1]\\n scores_group[idx + 1] = empty_group\\n scores_group[idx] = old_below_dob\\n scores_group[idx + 1] = old_above_dob\\n\\n qm_dob.text = \\\"?\\\"\\n qm_dob.color = QM_SORT_FG\\n time.sleep(0.2)\\n else:\\n time.sleep(0.6)\\n\\n if swaps == 0:\\n break # Sort complete if no values were swapped\\n gs_group.remove(qm_dob)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"72cee9051bbd5417c507c0515250e459\",\n \"score\": \"0.5199042\",\n \"text\": \"def new_game(self):\\n\\t\\tself.__self_setup(len(self.grid[0]), len(self.grid), self.min_score)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d196f67ffbd74386e379b65d3ec335f8\",\n \"score\": \"0.5162356\",\n \"text\": \"def refresh_score(self):\\n self._score_label = tk.Label(self._master, text=\\\"Score: {} - {}\\\".format(self._model.get_score()[0],self._model.get_score()[1]),font='Arial 15 bold')\\n self._score_label.grid(row=3, column =0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ee2ae19a7315996702b7de783a40bef9\",\n \"score\": \"0.5156803\",\n \"text\": \"def create_game_window(self):\\r\\n self.data_list = [int(self.entry.row.get()),\\r\\n int(self.entry.col.get()),\\r\\n str(self.entry.first.get()),\\r\\n str(self.entry.top_left.get()),\\r\\n self.entry.condition.get()]\\r\\n\\r\\n Othello_Gamewindow.GameWindow(self.master.master, self.data_list)\\r\\n # the game window launched, mainloop will be withdrawn\\r\\n\\r\\n print('Game started'\\r\\n '\\\\nrow number:', self.data_list[0],\\r\\n '\\\\ncol number:', self.data_list[1],\\r\\n '\\\\nfirst turn:', self.data_list[2],\\r\\n '\\\\ntop left piece:', self.data_list[3]\\r\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a8c2a38b031166b121f5556d2c3f8602\",\n \"score\": \"0.515397\",\n \"text\": \"def get_leaderboards():\\n top_scores = leaderboards.get_latest()\\n logger.debug('Current leaderboards top score: %s', top_scores)\\n return top_scores\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c72b004ac9ce3bd2fe058fdb0138d747\",\n \"score\": \"0.51447207\",\n \"text\": \"def board():\\n return render_template('board.html', data={\\\"active_player\\\": game.turn, \\\"passive_player\\\": game.next_player()})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"82cd4f473c4622de4fa8e29d9047aa1e\",\n \"score\": \"0.5139477\",\n \"text\": \"def __init__(self):\\n # starts with player 0's turn\\n self.whose_turn = 0\\n # positions on the grid are labeled as follows:\\n # 0 1 2\\n # 3 4 5\\n # 6 7 8\\n # will hold 1 or 0, indicating whether this player has occupied this position\\n self.player_0_positions = [0] * 9\\n self.player_1_positions = [0] * 9\\n # number of games won in this session\\n self.player_0_score = 0\\n self.player_1_score = 0\\n self.num_ties = 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c5f675c37c4c8d913607dafdbfe1ce7c\",\n \"score\": \"0.5138871\",\n \"text\": \"def construct_board():\\r\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9c5e000af1bbf8499c0d6ed4a36c38d5\",\n \"score\": \"0.5136407\",\n \"text\": \"def generate_matchs_firstRound(self, tournament):\\n list_players = tournament.list_players\\n all_list_players = []\\n for elt in list_players:\\n all_list_players.append(PlayerController().get_one(elt))\\n list_triee = sorted(\\n all_list_players,\\n key=attrgetter(\\\"rank\\\"),\\n reverse=True\\n )\\n tournament.matches_dones += [\\n f\\\"{list_triee[0].identifier}:{list_triee[4].identifier}\\\",\\n f\\\"{list_triee[1].identifier}:{list_triee[5].identifier}\\\",\\n f\\\"{list_triee[2].identifier}:{list_triee[6].identifier}\\\",\\n f\\\"{list_triee[3].identifier}:{list_triee[7].identifier}\\\"\\n ]\\n tournament.list_rounds.append(Round(\\\"Round 1\\\", [\\n Match(\\\"Match1\\\", list_triee[0], 0, list_triee[4], 0),\\n Match(\\\"Match2\\\", list_triee[1], 0, list_triee[5], 0),\\n Match(\\\"Match3\\\", list_triee[2], 0, list_triee[6], 0),\\n Match(\\\"Match4\\\", list_triee[3], 0, list_triee[7], 0)\\n ], \\\"\\\", \\\"\\\"))\\n return tournament\",\n \"title\": \"\"\n },\n {\n \"docid\": \"63e011e2bc5e082ac655bb0c83e02dd2\",\n \"score\": \"0.5134712\",\n \"text\": \"async def show(ctx, *args):\\n if len(server.user_list) < 1:\\n await ctx.send(\\\"The server dosen't have any data….\\\")\\n elif (len(args) < 1 or args[0] == \\\"--name\\\"):\\n user_name = ctx.author.name\\n if len(args) > 1 and \\\"--name\\\" == args[0]:\\n for m in ctx.guild.members:\\n if m.name == args[1] or m.nick == args[1]:\\n user_name = args[1]\\n break\\n else:\\n await ctx.send(\\\"Invalid user name\\\")\\n return\\n user = server.get(user_name)\\n ret = \\\"Win rate(when Impostor or Crewmate): {:.2%}\\\\n\\\".format(\\n user.win_num / user.data['Games Finished'])\\n ret += \\\"Win rate(when Impostor): {:.2%}\\\\n\\\".format(\\n user.impostor_win_num / user.data['Times Impostor'])\\n ret += \\\"Win rate(when Crewmate): {:.2%}\\\\n\\\".format(\\n user.crewmate_win_num / user.data['Times Crewmate'])\\n ret += \\\"Kills per Impostor: {:.2f}\\\\n\\\".format(\\n user.data['Impostor Kills'] / user.data['Times Impostor'])\\n ret += \\\"Tasks Completed rate: {:.2%}\\\\n\\\".format(\\n user.data['All Tasks Completed'] / user.data['Times Crewmate'])\\n ret += \\\"Sabotages Fixed / Games: {:.2f}\\\".format(\\n user.data['Sabotages Fixed'] / user.data['Games Finished'])\\n await ctx.send(ret)\\n elif args[0] == \\\"--rank\\\":\\n show_num = 3\\n if len(args) > 1 and is_num(args[1]):\\n show_num = int(args[1])\\n ret = \\\"leaderboard! (Win Rate) \\\\n\\\"\\n ret += \\\"\\\\n\\\".join(\\\"rank {2} {1} : {0:.2%} win\\\".format(tup[0], tup[1],\\n rank)\\n for rank, tup in enumerate(\\n server.rank_win_rate()[:show_num], start=1))\\n ret += \\\"\\\\n\\\\nleaderboard! (Impostor Win Rate) \\\\n\\\"\\n ret += \\\"\\\\n\\\".join(\\\"rank {2} {1} : {0:.2%} win\\\".format(tup[0], tup[1],\\n rank)\\n for rank, tup in enumerate(\\n server.rank_win_rate_when_impostor()[:show_num],\\n start=1))\\n ret += \\\"\\\\n\\\\nleaderboard! (Crewmate Win Rate) \\\\n\\\"\\n ret += \\\"\\\\n\\\".join(\\\"rank {2} {1} : {0:.2%} win\\\".format(tup[0], tup[1],\\n rank)\\n for rank, tup in enumerate(\\n server.rank_win_rate_when_crewmate()[:show_num],\\n start=1))\\n ret += \\\"\\\\n\\\\nleaderboard! (Kill / Times Impostor) \\\\n\\\"\\n ret += \\\"\\\\n\\\".join(\\\"rank {2} {1} : {0:.2f} killed\\\".format(tup[0], tup[1],\\n rank)\\n for rank, tup in enumerate(\\n server.rank_kill()[:show_num], start=1))\\n ret += \\\"\\\\n\\\\nleaderboard! (All Tasks Completed / Times Crewmate) \\\\n\\\"\\n ret += \\\"\\\\n\\\".join(\\\"rank {2} {1} : {0:.2%} completed\\\".format(\\n tup[0], tup[1],\\n rank)\\n for rank, tup in enumerate(\\n server.rank_alltask()[:show_num], start=1))\\n ret += \\\"\\\\n\\\\nleaderboard! (Sabotages Fixed / Number of Games) \\\\n\\\"\\n ret += \\\"\\\\n\\\".join(\\\"rank {2} {1} : {0:.2f} fixed\\\".format(tup[0], tup[1],\\n rank)\\n for rank, tup in enumerate(\\n server.rank_sabotagefix()[:show_num], start=1))\\n await ctx.send(ret)\\n elif args[0] == \\\"--diff\\\":\\n await ctx.send(\\\"I'll implement it one day!\\\")\\n elif args[0] == \\\"--userlist\\\":\\n await ctx.send(\\\", \\\".join([k for k in server.user_list.keys()]))\\n else:\\n await ctx.send(\\\"invalid command ><\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"effeee1ac4e2fa12decb59618caa1b25\",\n \"score\": \"0.51342463\",\n \"text\": \"def create_board(self):\\n self.add_piece(Floor(self, position=(1.5, -1, 5)))\\n for i, tile in enumerate(self.board):\\n if tile in [1, 2]:\\n self.add_piece(BoardTile(self, position=(i % 3, 0, i // 3), rosetta=tile == 2))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"51730b0ace2c1844e8597d3bb3a74469\",\n \"score\": \"0.5120348\",\n \"text\": \"def createGame(self):\\n\\t\\tself.columnconfigure(0, pad = 5)\\n\\t\\tself.columnconfigure(1, pad = 5)\\n\\t\\tself.rowconfigure(0, pad = 10)\\n\\t\\tself.rowconfigure(1, pad = 10)\\n\\t\\tself.numPlayersField = Entry(self)\\n\\t\\tself.numPlayersField.insert(0,\\\"1\\\")\\n\\t\\tself.setPlayersButton = Button(self, text = \\\"Set number of players\\\", command = self.setPlayers)\\n\\t\\tself.numPlayersField.grid(row=0, column = 0)\\n\\t\\tself.setPlayersButton.grid(row=0, column = 1)\\n\\t\\tself.gameCanvas = Canvas(self, bg = \\\"black\\\", height = self.canvasHeight, width = self.canvasWidth)\\n\\t\\tself.gameCanvas.grid(row = 1, column = 0, columnspan = 2)\\n\\t\\tself.newGameButton = Button(self, text=\\\"New game\\\", command = self.newGame)\\n\\t\\tself.quitGameButton = Button(self, text=\\\"Quit\\\", command = self.quit)\\n\\t\\tself.newGameButton.grid(row = 2, column = 0)\\n\\t\\tself.quitGameButton.grid(row = 2, column = 1)\\n\\t\\tself.pack()\\n\\t\\tself.createRectangles()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e8d42cf9252943714075b50c24037924\",\n \"score\": \"0.5118666\",\n \"text\": \"def test_get_leaderboard(self):\\n expected_positions = {\\n self.fifth_user.username: 5,\\n self.second_user.username: 2,\\n self.second_user2.username: 2,\\n self.second_user3.username: 2,\\n self.first_user.username: 1\\n }\\n auth_token = 'Token {}'.format(self.second_user3.auth_token.key)\\n\\n received_leaderboard = self.client.get('/challenges/getLeaderboard', HTTP_AUTHORIZATION=auth_token).data\\n\\n for lead in received_leaderboard:\\n user_name = lead['name']\\n self.assertEqual(lead['position'], expected_positions[user_name])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cc9df34f6da374dc65252ceb8c3fda96\",\n \"score\": \"0.5102245\",\n \"text\": \"def ranking_data(request):\\n # get the type of the last played round, even if there is no currently active round\\n latest_round = Round.objects.order_by('-id')[0] # this is the latest created round\\n print \\\"the latest round type was\\\"\\n print latest_round.type\\n if latest_round.type == 0:\\n roundtype = 'selection'\\n else:\\n roundtype = 'final'\\n\\n ranking_entries = get_ranking_entries()\\n\\n return render(request, 'ranking_data.xml', {\\n 'roundtype': roundtype,\\n 'ranking_entries': ranking_entries,\\n }, content_type=\\\"text/xml\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"864cd37be2a317b7b09ac7cf4913d726\",\n \"score\": \"0.51003873\",\n \"text\": \"def create_game_board(self):\\n self.fill_screen()\\n self.render_text(\\n 'Dealer Chip Number: ' + str(self.dealer_num_chips), \\n PLAYER_INFO_FONT_SIZE, \\n DEALER_INFO_LOCATION, \\n BLACK\\n )\\n self.render_text(\\n 'Your Chip Number: ' + str(self.player_num_chips),\\n PLAYER_INFO_FONT_SIZE,\\n PLAYER_INFO_LOCATION, \\n BLACK\\n )\\n self.render_image(DECK_IMG_PATH, DECK_IMG_LOCATION)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"92c9084d9287f80537d7ecdf906c08b6\",\n \"score\": \"0.5094188\",\n \"text\": \"def create_label(self):\\r\\n row_num_label = tkinter.Label(self.master, text='rows :',\\r\\n width=10, height=1, pady=8)\\r\\n col_num_label = tkinter.Label(self.master, text='columns :',\\r\\n width=10, height=1, pady=5)\\r\\n first_turn_label = tkinter.Label(self.master, text='first turn :',\\r\\n width=10, height=1, pady=6)\\r\\n topleft_label = tkinter.Label(self.master, text='top left :',\\r\\n width=10, height=1, pady=6)\\r\\n\\r\\n row_num_label.grid(row=0, column=0)\\r\\n col_num_label.grid(row=1, column=0)\\r\\n first_turn_label.grid(row=2, column=0)\\r\\n topleft_label.grid(row=3, column=0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f26bc1dd240605826c9cbcae40026569\",\n \"score\": \"0.5094108\",\n \"text\": \"def retrieve_team_leader(self, tl_pk: int):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f803e5acd91853816d9a434b3c435f07\",\n \"score\": \"0.50906175\",\n \"text\": \"def getleaderboarddisplay(leg_body, owner_filter):\\n try:\\n return ScoreDisplay.objects.get(name=\\\"%s_leader_%s\\\" % (leg_body.name,\\n owner_filter))\\n except:\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"26a338181e6564a8cbc07b220894291f\",\n \"score\": \"0.5077305\",\n \"text\": \"def print_scoreboard(self, gender):\\n print('Scoreboard for track %s in season %s' % (gender, self.name))\\n rank = 1\\n scoreboard = self.get_scoreboard(gender)\\n for points, stats in scoreboard:\\n print('#%d. %s at %.2f points' % (rank, stats.player.name, stats.points))\\n rank += 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aee7922d05c5b0a7c973cde5865dc91e\",\n \"score\": \"0.5076507\",\n \"text\": \"def display_result(name, list_of_score):\\r\\n all_round = 1\\r\\n print(\\\"\\\\nThanks for playing {0}\\\".format(name))\\r\\n\\r\\n for row in list_of_score:\\r\\n print(\\\"Round {0} : {1}.\\\".format(all_round, row))\\r\\n all_round += 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ca43b763c7d4490152090d439344a5f3\",\n \"score\": \"0.504961\",\n \"text\": \"def print_board(board, player1, player2):\\n row_len = len(board[0])\\n col_len = len(board)\\n rows_template = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I']\\n cols = []\\n for col_index in range(col_len):\\n cols.append(col_index + 1)\\n cols_str = list(map(str, cols))\\n rows = []\\n for row_index in range(row_len):\\n rows.append(rows_template[row_index])\\n line = []\\n for i in range(row_len):\\n line.append(\\\"---\\\")\\n \\n board_total_length = (row_len * 3) + (row_len - 1) + 2\\n score_names = f\\\"{player1['name']} : {player2['name']}\\\"\\n score = f\\\"{str(player1['points']).rjust(len(player1['name']))} : {player2['points']}\\\"\\n score_offset = int((board_total_length - len(score_names)) / 2)\\n print(\\\" \\\"*score_offset + score_names)\\n print(\\\" \\\"*score_offset + score)\\n print(\\\"\\\")\\n print(\\\" \\\", \\\" \\\".join(cols_str))\\n for index in range(col_len):\\n print(f\\\"{rows[index]} {' | '.join(board[index])}\\\")\\n if index < row_len - 1:\\n print(\\\" \\\", \\\"+\\\".join(line))\\n print(\\\"\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"12814ecde4093c1958c0ea26271b9777\",\n \"score\": \"0.5046536\",\n \"text\": \"def get_leaderboard(self, id=None, state=None, owner=None, tag=None, min_running_time=None):\\n\\n leaderboard_entries = self._fetch_leaderboard(id, state, owner, tag, min_running_time)\\n\\n def make_row(entry):\\n channels = dict((\\\"channel_{}\\\".format(ch.name), ch.trimmed_y) for ch in entry.channels)\\n\\n parameters = map_keys(\\\"parameter_{}\\\".format, entry.parameters)\\n properties = map_keys(\\\"property_{}\\\".format, entry.properties)\\n\\n r = {}\\n r.update(entry.system_properties)\\n r.update(channels)\\n r.update(parameters)\\n r.update(properties)\\n return r\\n\\n rows = ((n, make_row(e)) for (n, e) in enumerate(leaderboard_entries))\\n\\n df = pd.DataFrame.from_dict(data=dict(rows), orient=\\\"index\\\")\\n df = df.reindex(self._sort_leaderboard_columns(df.columns), axis=\\\"columns\\\")\\n return df\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8d8f46e2559b39b119d7febd6d19afad\",\n \"score\": \"0.5028831\",\n \"text\": \"def view_scores(self):\\n scores = { \\n **self.__score['upper'],\\n 'total upper': self.__score['total upper'],\\n **self.__score['lower'],\\n 'total lower': self.__score['total lower'],\\n 'grand total': self.__score['grand total'] \\n }\\n for score in scores:\\n s = scores[score]\\n if s == None:\\n s = 'blank'\\n print(f'\\\\t{score.title()}: {s}')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e230d6041e2b95be5542e23c2cdc6dcb\",\n \"score\": \"0.5024332\",\n \"text\": \"def refresh_rankings(self):\\n \\n self.team_ranks_panel.pack_forget() #Get rid of the old rankings\\n self.team_ranks_panel = tk.Frame(self.ranking_frame) #Make a new ranks panel\\n self.team_ranks_panel.grid(row=3, column=0) #Add the panel\\n \\n self.team_ranks_textbox = tk.Text(self.team_ranks_panel, width=24, wrap=tk.NONE) #The textbox with the ranking and score information\\n self.team_ranks_textbox.pack(side=tk.TOP) #Add the team ranks textbox\\n \\n r_teams = self.get_teams()[:] #The teams to show ranks for\\n r_teams.sort(key=lambda t:-self.score(t)) #Sort the teams by score in descending order\\n \\n for i in range(0, len(r_teams)): #Add the teams to the team ranks textbox one at a time\\n team = r_teams[i] #Get the team to add\\n num_string = str(i+1)\\n num_string = num_string + ':' + (' ' * (4-len(num_string)))\\n string = num_string + str(team) #The rank and the team\\n string += ' ' * (11-len(string)) + 'with ' + '%.2f' % self.score(team) #The score of the team\\n if i != len(r_teams) - 1: #Add newlines after every string but the last\\n string += '\\\\n'\\n self.team_ranks_textbox.insert(tk.INSERT, chars=string) #Add the string to the team ranks textbox\\n \\n self.team_ranks_textbox.config(state=tk.DISABLED, height=30) #Make it so the team ranks textbox can't be edited \\n \\n self.parent.do_easter_eggs() #Trigger any appropriate easter eggs\",\n \"title\": \"\"\n },\n {\n \"docid\": \"41f7fc8950403b823955a2b0ed50510a\",\n \"score\": \"0.50169355\",\n \"text\": \"def __init__(self, width=5, height=5, playerA=PLAYER_TYPE_HUMAN, playerB=PLAYER_TYPE_HUMAN, depth = 3, useDecisionTree= True, dynamicDepth= False):\\n self.width, self.height = width, height\\n assert 2 <= self.width and 2 <= self.height,\\\\\\n \\\"Game can't be played on this board's dimension.\\\"\\n self.board = {}\\n self.squares = {}\\n self.player = 0\\n self.players = {\\n 0: Player(self, playerA, 0, depth, useDecisionTree, dynamicDepth),\\n 1: Player(self, playerB, 1, depth, useDecisionTree, dynamicDepth),\\n }\\n\\n self.board_state_size = (self.width-1) * self.height * 2\\n self.board_state = np.zeros(shape = (1, (self.width-1) * self.height * 2))\\n self.empty_states = set()\\n\\n self.move_to_state = None\\n\\n for i in range(self.board_state_size):\\n self.empty_states.add(i)\\n \\n self.scores = [0,0]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"875bfe209602e303398b296f829a5739\",\n \"score\": \"0.5006537\",\n \"text\": \"def create_board(self):\\n\\t\\t\\n\\t\\tprint(\\\"This will print the board ready for playing.\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c74159b2631d46e409a8b4568f1d3d2e\",\n \"score\": \"0.49985194\",\n \"text\": \"def highlight_player(self):\\n if self._model.get_turn():\\n player_1=tk.Label(self._master,text=\\\"Player 1: X\\\",font='Arial 15 bold',bg=\\\"green\\\")\\n player_1.grid(row=1,column=0)\\n player_2=tk.Label(self._master,text=\\\"Player 2: O\\\",font='Arial 15 bold')\\n player_2.grid(row=2,column=0)\\n else:\\n player_1=tk.Label(self._master,text=\\\"Player 1: X\\\",font='Arial 15 bold')\\n player_1.grid(row=1,column=0)\\n player_2=tk.Label(self._master,text=\\\"Player 2: O\\\",font='Arial 15 bold',bg=\\\"green\\\")\\n player_2.grid(row=2,column=0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"85680912e9144fbb7a7965a4bbb6161a\",\n \"score\": \"0.49831086\",\n \"text\": \"def create_board(self):\\r\\n for i in range(ROW):\\r\\n temporary_list = []\\r\\n for j in range(COL):\\r\\n lable = tkinter.Label(self.frame2, image=self.photo,\\r\\n width=\\\"50\\\", height=\\\"50\\\", bg='#66B3FF')\\r\\n lable.photo = self.photo\\r\\n lable.grid(row=i, column =j)\\r\\n\\r\\n temporary_list.append(lable)\\r\\n self.cell_list.append(temporary_list)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3bb94d9db1b4e7ad432e09a4abbba736\",\n \"score\": \"0.49772006\",\n \"text\": \"def new_leader(self, number):\\n old_leader = self.get_leader_name()\\n self.leader_index = number\\n leader = self.get_leader_name()\\n print(leader, \\\"deposes\\\", old_leader, \\\"as the new leader of the pack\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"68110e28de7c91dfd5b54812844ec2ae\",\n \"score\": \"0.49769977\",\n \"text\": \"def __init__(self, master, model):\\n self._master = master\\n self._model = model\\n self._title=tk.Label(self._master,text=\\\"Tic-tac-toe Game\\\",font='Arial 20 bold',fg = 'red')\\n self._title.grid(row=0,column=0)\\n self._score_label = tk.Label(self._master, text=\\\"Score: {} - {}\\\".format(self._model.get_score()[0],self._model.get_score()[1]),font='Arial 15 bold')\\n self._score_label.grid(row=3, column =0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"75d99efdbe5c60d83a5b7acc199eb355\",\n \"score\": \"0.49751136\",\n \"text\": \"def show_winner(self, winners: [PlayerBase]):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b3e6bbfdb4d032ad04fb990948d68efc\",\n \"score\": \"0.4974871\",\n \"text\": \"def view_round(round_):\\n keys = [\\n 'id', 'title', 'status',\\n 'registration_opens_at', 'is_registration_open',\\n 'training_opens_at', 'is_training_open',\\n 'min_team_size', 'max_team_size', 'min_team_ratio',\\n 'allow_team_changes'\\n ]\\n return {key: round_[key] for key in keys}\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":381,"cells":{"query_id":{"kind":"string","value":"ce428872890f3297fc66b259f0a143e2"},"query":{"kind":"string","value":"Gets the bullets sprite group."},"positive_passages":{"kind":"list like","value":[{"docid":"02462abbbe3a9e237407eea959f7c752","score":"0.6066278","text":"def get_bullets (self):\n\n return self.bullets","title":""}],"string":"[\n {\n \"docid\": \"02462abbbe3a9e237407eea959f7c752\",\n \"score\": \"0.6066278\",\n \"text\": \"def get_bullets (self):\\n\\n return self.bullets\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"15d234b9db0d0fc7dd1acbff40c75c5b","score":"0.6432783","text":"def sprites(self):\n return self._group.sprites()","title":""},{"docid":"de6a149d4ec31f0f540233fe9e875647","score":"0.6042333","text":"def loadBullet(self):\n bullet = Projectile(self.x + 70, self.y + 47, self.facing_left)\n return bullet","title":""},{"docid":"5d08deda44d612b95e9cc7514dae379e","score":"0.5839755","text":"def getSprite(self):\n return self.image","title":""},{"docid":"ed2a8668934e3147d90c41e9897823ae","score":"0.5698468","text":"def make_sprite_group(self, sprites):\n tempgroup = pygame.sprite.LayeredDirty(sprites)\n return tempgroup","title":""},{"docid":"74c35ed97166d369ffd7bd1447cfec0c","score":"0.56705916","text":"def getSprites(self):\n\n ground = load_image('OW_Ground.png')\n grass = load_image('Grass.png')\n water = load_image('Water.png')\n tree = load_image('Tree.png')\n wall = load_image('BrickWall.png')\n breakableWall = [load_image('BreakableWall.png'), load_image('BrokenWall.png')]\n shooter = self.shooterImages()\n player = self.kingOWImages()\n passage = load_image('OW_Ground.png')\n cave = load_image('CaveEntrance.png')\n ball = self.ballImages()\n blank = load_image(\"Blank.png\")\n bomb = load_image(\"BlankBomb.png\")\n nums = self.numberImages()\n potion = load_image(\"Blank_Potion_Health.png\")\n heart = [load_image('Heart_0.png'), load_image(\"Heart_1.png\"), load_image(\"Heart_2.png\"), load_image(\"Heart_3.png\"), load_image(\"Heart_4.png\")]\n kingbomb = load_image(\"Bomb.png\")\n kingarrow = self.arrowImages()\n\n return [ground, grass, water, tree, wall, breakableWall, shooter, shooter, player, passage, cave, ball, blank, bomb, nums, potion, nums, heart, heart, heart, kingbomb, kingarrow]","title":""},{"docid":"7e37240fcc5dfe487b52499105727495","score":"0.56694347","text":"def getSprites(self):\n\n ground = load_image('CaveFloor.png')\n wall = load_image('CaveWall.png')\n BreakableWall = [load_image('CaveWallBreakable.png'), load_image('CaveWallBroken.png')]\n pickbomb = load_image('CaveBomb.png')\n player = self.kingCaveImages()\n passage = load_image('CaveEntrance.png')\n blank = load_image(\"Blank.png\")\n bomb = load_image(\"BlankBomb.png\")\n nums = self.numberImages()\n potion = load_image(\"Blank_Potion_Health.png\")\n heart = [load_image('Heart_0.png'), load_image(\"Heart_1.png\"), load_image(\"Heart_2.png\"), load_image(\"Heart_3.png\"), load_image(\"Heart_4.png\")]\n kingbomb = load_image(\"CaveBomb.png\")\n kingarrow = self.arrowImages()\n\n return [ground, wall, BreakableWall, blank, player, passage, pickbomb, blank, bomb, nums, potion, nums, heart, heart, heart, kingbomb, kingarrow]","title":""},{"docid":"273f5bec30716b37e9ce87cd63123f48","score":"0.56469","text":"def get_sprite(self, sprite_name: str) -> Sprite:\r\n return self.sprites[sprite_name]","title":""},{"docid":"af87d4c68e8aa78f98dd8062947868b3","score":"0.56391895","text":"def getSprites(self):\n ground = load_image('OW_Ground.png')\n grass = load_image('Grass.png')\n water = load_image('Water.png')\n tree = load_image('Tree.png')\n troll = self.trollImages()\n bat = self.batImages()\n player = self.kingOWImages()\n passage = load_image('OW_Ground.png')\n javelin = self.javelinImages()\n blank = load_image(\"Blank.png\")\n bomb = load_image(\"BlankBomb.png\")\n nums = self.numberImages()\n potion = load_image(\"Blank_Potion_Health.png\")\n heart = [load_image('Heart_0.png'), load_image(\"Heart_1.png\"), load_image(\"Heart_2.png\"), load_image(\"Heart_3.png\"), load_image(\"Heart_4.png\")]\n kingbomb = load_image(\"Bomb.png\")\n kingarrow = self.arrowImages()\n\n return [ground, grass, water, tree, troll, bat, player, passage, passage, javelin, blank, bomb, nums, potion, nums, heart, heart, heart, kingbomb, kingarrow]","title":""},{"docid":"d3f46e104f86b8435759121be7d1dcc3","score":"0.5470347","text":"def __spawn_bullet (self):\n\n mouse_pos = pygame.mouse.get_pos()\n new_bullet = Bullet(settings_game[\"bullet_type_string\"], mouse_pos,\n self.player.rect.center)\n self.bullets.add(new_bullet)\n self.player.bullets -= 1","title":""},{"docid":"c5ebffe304deb559e74685146db5381d","score":"0.52890384","text":"def LoadSprites(self):\n self.mainCloud = MainCloud()\n self.cloud_sprites = pygame.sprite.GroupSingle(self.mainCloud)\n self.grass_sprites = pygame.sprite.Group()\n for x in range(self.numOfCloudsHorizontal):\n for y in range(self.numOfCloudsVertical):\n self.grass_sprites.add(Grass(pygame.Rect(x*10,y*10,10,10))) # rect(left,top,w,h)\n self.black_clouds_sprites = pygame.sprite.Group()","title":""},{"docid":"8013222ce56a01f2c92d78980d7a934d","score":"0.5272742","text":"def get_drawables(self):\n return [self.my_group, self.background.grass, self.platform_handler.platforms, self.projectiles.shurikens]","title":""},{"docid":"cb1ebe1084a531c727f7478b50f0e5cd","score":"0.52546614","text":"def createExplosionTextureList():\r\n columns = 16\r\n count = 60\r\n sprite_width = 256\r\n sprite_height = 256\r\n file_name = \":resources:images/spritesheets/explosion.png\"\r\n list_textures = arcade.load_spritesheet(file_name, sprite_width, sprite_height, columns, count)\r\n return list_textures","title":""},{"docid":"5e0dbae9e78215f26efddb4f159a127e","score":"0.5230385","text":"def sprite(self, name):\n return sprite.Sprite(image=self.image,\n image_pos = self.sprites[name])","title":""},{"docid":"95c51affb86dda7bfc1736359af48926","score":"0.52288735","text":"def shoot_bullet(self):\n current_time = pygame.time.get_ticks()\n if current_time - self.last_bullet_shot > DELAY:\n self.last_bullet_shot = current_time\n bullet = Bullet(self.rect.centerx, self.rect.top)\n all_bullets.add(bullet)\n all_sprites.add(bullet)","title":""},{"docid":"1bcda63ad4bd80eda630120ed29e16b1","score":"0.51727575","text":"def draw_bullet(self):\r\n pygame.draw.rect(self.screen, self.color, self.rect)","title":""},{"docid":"0518ef58044ce52b20f27062eab966b6","score":"0.5167384","text":"def _fire_bullet(self):\n\t\tif len(self.bullets) < self.settings.bullet_allowed:\n\t\t\tnew_bullet = Bullet(self)\n\t\t\tself.bullets.add(new_bullet) # Add the new bullet to the group","title":""},{"docid":"999da1c5050c976ef42556ea849a18bc","score":"0.514254","text":"def bulletList(self):\n bullet_list = []\n for p in self.users:\n for b in p.bullet_list:\n b.update()\n bullet_list.append(b.toObj())\n return bullet_list","title":""},{"docid":"503cd7e90e43dd919eb7787b24aabc09","score":"0.51109165","text":"def get_overlapping_sprites(self):\n self._check_overlap()\n return self._overlapping_sprites","title":""},{"docid":"23c1f473ed2b4f8d01a1bcce8f2c4405","score":"0.5107428","text":"def draw_bullet(self):\n pygame.draw.rect(self.screen, self.color,self.rect)","title":""},{"docid":"bd067004ebf19648e4909101abc34a15","score":"0.5106111","text":"def draw_bullet(self):\n pygame.draw.rect(self.screen, self.color, self.rect)","title":""},{"docid":"bd067004ebf19648e4909101abc34a15","score":"0.5106111","text":"def draw_bullet(self):\n pygame.draw.rect(self.screen, self.color, self.rect)","title":""},{"docid":"bd067004ebf19648e4909101abc34a15","score":"0.5106111","text":"def draw_bullet(self):\n pygame.draw.rect(self.screen, self.color, self.rect)","title":""},{"docid":"bd067004ebf19648e4909101abc34a15","score":"0.5106111","text":"def draw_bullet(self):\n pygame.draw.rect(self.screen, self.color, self.rect)","title":""},{"docid":"bd067004ebf19648e4909101abc34a15","score":"0.5106111","text":"def draw_bullet(self):\n pygame.draw.rect(self.screen, self.color, self.rect)","title":""},{"docid":"35a504cc1d3d0966339865ca97be9c40","score":"0.5081203","text":"def draw_bullet(self):\n pygame.draw.rect(self._screen, self._color, self.rect)","title":""},{"docid":"ebc5554d77a51f7254a6b5c5d74e94ed","score":"0.50686556","text":"def player_shoot(self):\n self.playerbullet = PlayerBullet(self.player.rect.centerx, self.player.rect.top, -10, YELLOW)\n self.all_sprites.add(self.playerbullet)\n self.player_bullets.add(self.playerbullet)","title":""},{"docid":"2a01f034c1b151eb3455d2b9ec56705f","score":"0.5066055","text":"def loadSprite(filename):\n with open(filename) as f:\n sprite = []\n for line in f:\n sprite.append(line.rstrip())\n return sprite","title":""},{"docid":"5ce7635e763cdf23731ac05a8baf867c","score":"0.50316167","text":"def spriteType(self):\n return 'background'","title":""},{"docid":"cfabe96a7a3b0a7d720eeab0995f678e","score":"0.502615","text":"def handle_bullet_collisions(self):\r\n # reduce the health value of the enemy\r\n self.enemy_health.reduce_health(10)\r\n\r\n if self.enemy_health.current_health <= 0: # remove enemy sprite from enemies Group\r\n self.kill()\r\n self.inheritance_packs.update_enemy_pos(self.rect.x, self.rect.y)\r\n return self.inheritance_packs\r\n return None","title":""},{"docid":"705462825acf29f772e84fb92688bc4b","score":"0.50234526","text":"def get_bullet_points(self, product):\n bullet_points = ''\n for bullet in product.bullet_point_ids:\n bullet_point = \"\"\"<BulletPoint>%s</BulletPoint>\"\"\" % (html.escape(bullet.name))\n bullet_points = '%s %s' % (bullet_points, bullet_point)\n if product.bullet_point_ids:\n return bullet_points","title":""},{"docid":"59d71d576b1eb65d3abeb1e08cb7a5d2","score":"0.5013284","text":"def get_sprite_pack(self, sprite_pack_name: str) -> SpritePack:\r\n return self.sprite_packs[sprite_pack_name]","title":""},{"docid":"7238078d0a619f50cf7bc2e3cd00752c","score":"0.4974574","text":"def draw_bullet(bullet_obj, game_screen):\n game_screen.blit(bullet_obj.get_img(), (bullet_obj.get_x(), bullet_obj.get_y()))","title":""},{"docid":"37f4aa9392dcefe4fc82fa0217755438","score":"0.49725246","text":"def spriteType(self):\n return 'player'","title":""},{"docid":"74a6be708d11175815edbed73ceb2315","score":"0.49511772","text":"def show_pile(self):\n img_list = []\n for card in range(len(self.pile)):\n if card <= 2 :\n img = pygame.image.load(\"assets/\"+str(self.pile[card])+\".png\")\n img_list.append(img)\n return img_list","title":""},{"docid":"e7957c421206c66e6a8afce3e0238952","score":"0.49264708","text":"def sprite_layers(self) -> Iterator:\n return sorted(self, key=lambda s: getattr(s, \"layer\", 0))","title":""},{"docid":"f41aa2cfc170fc045a29f59b7ccd28fd","score":"0.49092758","text":"def _generate_level(self):\n for t in range(self.LEVEL_WIDTH * self.LEVEL_HEIGHT):\n tile = Tile(\"sprites/grass.png\")\n self.LEVEL.append(tile)\n self.sprite_group.add(tile)\n self.LEVEL[0].image.fill((0xff, 0xff, 0xff))\n self.LEVEL[self.LEVEL_WIDTH * self.LEVEL_HEIGHT - 1].image.fill((0, 0, 0))\n print(*self.sprite_group)","title":""},{"docid":"f52edde00d04810b1428c6129f752ce9","score":"0.490017","text":"def shoot(self):\n # Instantiates a bullet\n bullet = Bullet()\n bullet.center.x = self.center.x + \\\n math.cos(math.radians(self.angle)) * 10\n bullet.center.y = self.center.y + \\\n math.sin(math.radians(self.angle)) * 10\n bullet.angle = self.angle\n\n bullet.velocity.dx = math.cos(math.radians(self.angle)) * bullet.speed\n bullet.velocity.dy = math.sin(math.radians(self.angle)) * bullet.speed\n\n return bullet","title":""},{"docid":"b5a9306cc7e9f16f7c0f4badd90ff00c","score":"0.48826018","text":"def double_fire_smallBullet(self):\r\n \r\n leftB = SmallWeapon()\r\n rightB = SmallWeapon()\r\n leftB.rect.x, leftB.rect.y = self.rect.topleft\r\n rightB.rect.x, rightB.rect.y = self.rect.topright\r\n\r\n # reset the power value and bar\r\n self.power.clear_power(100)\r\n self.bullets_group.add(leftB, rightB)\r\n self.allSprites_group.add(leftB, rightB)","title":""},{"docid":"fd4669578bb9cdd05dacc0868372da21","score":"0.4875645","text":"def spritesheet() -> None:","title":""},{"docid":"ba1f50c7fa6efa77a4b47d7b5d81a7a3","score":"0.48697823","text":"def SpriteCollision(sprite, spriteGroup, kill=False):\n return pygame.sprite.spritecollide(sprite, spriteGroup, kill)","title":""},{"docid":"6f3055a8bc6772b3220b921c77f69546","score":"0.48484784","text":"def fire_bullet(ai_settings, screen, ship, bullets):\n # sounds for bullets\n shoot = pygame.mixer.Sound('sounds/laser.wav')\n\n # Create a new bullet and add it to the bullets group\n if len(bullets) < ai_settings.bullets_allowed:\n new_bullet = Bullet(ai_settings=ai_settings, screen=screen, ship=ship)\n bullets.add(new_bullet)\n shoot.play()","title":""},{"docid":"ef84ec9ed1bb5064cc838df8d15e8094","score":"0.4846823","text":"def _fire_bullet(self):\r\n\t\tif len(self.bullets) < 3:\r\n\t\t\tnew_bullet = Bullet(self)\r\n\t\t\tself.bullets.add(new_bullet)","title":""},{"docid":"f3a6842426109a35bdb55404c30189c3","score":"0.48170656","text":"def implode(self, player_x, screen_height):\n bullets = []\n for i in range(10):\n bullets.append(Knife(self.rect.x, self.rect.y, player_x, screen_height * i/10))\n return bullets","title":""},{"docid":"e158dd1ec5956c950b7acd816553cd5a","score":"0.48120666","text":"def get_drawables(self) -> List[Drawable]:\n return self.drawables","title":""},{"docid":"66257202c264e74a43435a3b5bb173d1","score":"0.4810104","text":"def remove_dead(group):\r\n for sprite in group:\r\n if not sprite.alive:\r\n group.remove(sprite)","title":""},{"docid":"1bf6549aa5524d8ce7df3bd8e692d6b7","score":"0.4807381","text":"def list_group_icons(self):\n return [(e.struct.Name, e.struct.OffsetToData)\n for e in self.groupiconres.directory.entries]","title":""},{"docid":"bf5a5eb76183666b69515bf710369418","score":"0.48047295","text":"def get_groups(self):\n return self._groups","title":""},{"docid":"61697237fc3a7480e7392ce1d652db50","score":"0.47825295","text":"def game_loop(self):\n clock = pygame.time.Clock()\n bullet_sound = pygame.mixer.Sound('Sound/bullet.wav')\n score_font = pygame.font.SysFont('arial', 30, True)\n shoot_loop = 0\n bullets = []\n dino = Player(self.level.get_player_start_position())\n\n while True:\n clock.tick(40)\n\n dino.gun = self.level.dino_gun\n\n if dino.pos.x + 350 > self.screen_width:\n self.level.shift_world(-5, 0)\n dino.slide(-5, 0)\n if dino.pos.x - 350 <= 0 and self.level.world_shift_x < 0:\n self.level.shift_world(5, 0)\n dino.slide(5, 0)\n if self.level.world_shift_x <= self.level.level_limit:\n print(self.levels.index(self.level) + 1)\n try:\n self.level = self.levels[self.levels.index(self.level) + 1]\n except IndexError:\n self.end_screen(dino)\n return False\n dino.reset()\n\n if shoot_loop > 0:\n shoot_loop += 1\n if shoot_loop > 4:\n shoot_loop = 0\n\n for event in pygame.event.get():\n if event.type == pygame.QUIT:\n return\n if event.type == pygame.KEYDOWN:\n if event.key == pygame.K_UP:\n dino.jump()\n if event.key == pygame.K_BACKQUOTE:\n for enemy in self.level.enemys:\n enemy.debug_draw(\n draw_bounds=not enemy.draw_bounds,\n draw_hitbox=not enemy.draw_hitbox)\n dino.debug_draw(draw_hitbox=not dino.draw_hitbox)\n\n if not self.jump_button.get_state():\n jump_flag = True\n if self.jump_button.get_state():\n if jump_flag:\n dino.jump()\n jump_flag = False\n\n for bullet in bullets:\n remove = False\n hits = pygame.sprite.spritecollide(bullet,\n self.level.platforms, False)\n if hits:\n remove = True\n if (bullet.pos.x < self.screen_width) and (bullet.pos.x > 0):\n bullet.update_location()\n else:\n remove = True\n\n hits = pygame.sprite.spritecollide(bullet, self.level.enemys,\n False)\n for hit in hits:\n self.score += 5\n hit.hit()\n remove = True\n\n if remove:\n bullets.pop(bullets.index(bullet))\n\n keys = pygame.key.get_pressed()\n\n if keys[pygame.K_LEFT] or self.left_button.get_state():\n dino.move_left()\n elif keys[pygame.K_RIGHT] or self.right_button.get_state():\n dino.move_right()\n else:\n dino.stop()\n\n if keys[pygame.K_ESCAPE]:\n return\n if keys[pygame.K_a]:\n print(dino.pos.x - self.level.world_shift_x)\n\n if (keys[pygame.K_SPACE] or self.shoot_button.get_state()) and (\n shoot_loop == 0) and dino.gun:\n if dino.facing_left:\n facing = -1\n else:\n facing = 1\n\n if len(bullets) < 5:\n bullets.append(\n Projectile(\n int(dino.rect.centerx), int(dino.rect.centery), 6,\n (0, 0, 0), facing))\n bullet_sound.play()\n shoot_loop = 1\n\n dino.update_location(self.screen_height)\n\n self.win.blit(self.level.background, (0, 0))\n text = score_font.render('Score:' + str(self.score), 1, (0, 0, 0))\n self.win.blit(text, (0, 10))\n text = score_font.render(\n 'Speed:' + str(self.ellip.get_speed()) + \" RPM\", 1, (0, 0, 0))\n self.win.blit(text, (0, 40))\n heart_rate = 132\n text = score_font.render('Heart Rate:' + str(heart_rate), 1,\n (0, 0, 0))\n self.win.blit(text, (0, 70))\n\n hits = pygame.sprite.spritecollide(dino, self.level.platforms,\n False)\n for hit in hits:\n dino.touch_down(hit.rect, hit.friction)\n\n hits = pygame.sprite.spritecollide(dino, self.level.enemys, False)\n for hit in hits:\n dino.hit(hit)\n if dino.rect.bottom <= (hit.rect.centery -\n (hit.rect.height // 4)\n ) and dino.rect.bottom >= hit.rect.top:\n self.score += 20\n if dino.dead:\n self.level.shift_world(0 - self.level.world_shift_x,\n 0 - self.level.world_shift_y)\n dino.reset()\n self.level.draw(self.win)\n dino.draw(self.win)\n for bullet in bullets:\n bullet.draw(self.win)\n pygame.display.update()","title":""},{"docid":"6017b8cd03ee3844893912aa72f7c490","score":"0.47737974","text":"def spriteType(self):\n #returns the type of sprite we've created\n return 'enemy'","title":""},{"docid":"443e85be50488c30952cc7b9962788fb","score":"0.47479936","text":"def initialize_tiles():\n sprite_sheet = spritesheet.SpriteSheet(TILES_TEXTURES)\n # Extracting sprites out of the linear sprite sheet\n tiles = sprite_sheet.all_sprites(\n mahjong_tiles_dictionary,\n SCREEN_WIDTH / 2,\n SCREEN_HEIGHT / 2)\n tile_sprite_group = pygame.sprite.Group()\n\n # Constructing the tile group for rendering and collision detection\n for i in range(len(tiles)):\n # print(tiles[i][0])\n tile_sprite_group.add(tiles[i][0])\n\n return tile_sprite_group","title":""},{"docid":"52e5d8d4c7d99e5597ff0fd4cc72156c","score":"0.47370762","text":"def update_bullets(self):\r\n #Update bullet positions\r\n self.bullets.update()\r\n\r\n #Get rid of bullets that have disappeared.\r\n\r\n for bullet in self.bullets.copy():\r\n if bullet.rect.bottom <= 0:\r\n self.bullets.remove(bullet)\r\n print(len(self.bullets))\r\n\r\n #Check for any bullets that have hit enemy planes\r\n\r\n #IF so, get rid of the bullet and the plane\r\n\r\n collisions = pygame.sprite.groupcollide(\r\n self.bullets, self.enemy_planes, True, True)","title":""},{"docid":"cdb2e121935fae972edc49c70f440b53","score":"0.47323436","text":"def double_fire_bigBullet(self):\r\n leftB = BigWeapon()\r\n rightB = BigWeapon()\r\n leftB.rect.x, leftB.rect.y = self.rect.topleft\r\n rightB.rect.x, rightB.rect.y = self.rect.topright\r\n\r\n # reset the power bar and value\r\n self.power.clear_power(200)\r\n self.bullets_group.add(leftB, rightB)\r\n self.allSprites_group.add(leftB, rightB)","title":""},{"docid":"000b755999bdcb33324f179208c65811","score":"0.47318715","text":"def __get_timer(self) -> ImageSpriteTimer:\n return self.__timer.sprite","title":""},{"docid":"ba04a1781c82d2fff62aadf884922d44","score":"0.47135156","text":"def BulletMove(self):","title":""},{"docid":"69c60a183bb23e2bb66fff7316927ce4","score":"0.47133464","text":"def spriteType(self):\n return 'health bar'","title":""},{"docid":"1e0943314bcde818d5833f50a5778dbd","score":"0.4692101","text":"def shoot(self, player_x, player_y):\n self.bullet_counter += 1\n self.bullet_counter %= self.bullet_counter_reset # modulo\n\n if self.bullet_counter in self.bullet_frames:\n self.pew_sound.play()\n return Knife2(self.rect.x, self.rect.y, player_x)\n else:\n return None","title":""},{"docid":"793e60563325970dd3ee6bf05780887a","score":"0.46920672","text":"def playercollideany(sprite, group):\n spritecollide = sprite.rect.colliderect\n for s in group:\n if spritecollide(s.rect) and s != sprite:\n return s\n return None","title":""},{"docid":"becdf8f3639deda811300b83c2646bfe","score":"0.46877676","text":"def fire_bullet(ai_settings, screen, ship, ship_bullets):\n # Create a new bullet and add it to the bullets group\n if len(ship_bullets) < ai_settings.ship_bullets_allowed:\n new_bullet = Ship_Bullet(ai_settings, screen, ship)\n ship_bullets.add(new_bullet)","title":""},{"docid":"0ada7620b420bef1ce111fa14fdfc236","score":"0.4684961","text":"def bullet(radius, outline, fill):\n \n # init drawing\n bitmap = wx.Bitmap(2*radius+2, 2*radius+2)\n mdc = wx.MemoryDC()\n mdc.SelectObject(bitmap)\n dc = wx.GCDC(mdc) if wx.Platform != \"__WXMSW__\" else mdc\n \n # draw bullet\n dc.SetPen(outline)\n dc.SetBrush(fill)\n dc.DrawCircle(radius+1, radius+1, radius)\n \n # release bitmap\n mdc.SelectObject(wx.NullBitmap)\n \n # set mask\n if wx.Platform == \"__WXMSW__\":\n bitmap.SetMaskColour(wx.BLACK)\n \n return bitmap","title":""},{"docid":"9492b3ca35f0f4164f1af65b7864e233","score":"0.46735826","text":"def fire_smallWeapon(self):\r\n now = pygame.time.get_ticks()\r\n if now - self.smBullet_timer >= self.sm_bullet_attack_interval:\r\n self.smBullet_timer = now\r\n\r\n sm_bullet = SmallWeapon()\r\n # place it the position of the player\r\n mid_x, mid_y = self.rect.midtop\r\n sm_bullet.rect.x = mid_x\r\n sm_bullet.rect.y = mid_y\r\n sm_bullet.add(self.allSprites_group, self.bullets_group)","title":""},{"docid":"7cfd270247041cd9d0dfa2755bd549e0","score":"0.46691424","text":"def _fire_bullet(self):\n if len(self.bullets) < self.settings.bullets_allowed:\n new_bullet = Bullet(self) # limit 3 at a time\n self.bullets.add(new_bullet) # add new bullets to bullets","title":""},{"docid":"7274b657148ea4334cec0234ca592566","score":"0.46582806","text":"def _fire_bullet(self):\n if len(self.bullets) < self.settings.bullets_allowed:\n new_bullet = Bullet(self)\n self.bullets.add(new_bullet)\n self.ship_fire_sound.play()","title":""},{"docid":"dee57bac06361bbf43bbe1fd1e92543d","score":"0.46534377","text":"def sprite(index: int, x: int, y: int) -> None:","title":""},{"docid":"a9d7302d7ac83511a0f779d5daeceaaf","score":"0.46506235","text":"def charger_sprite(self):\r\n for mouvement in self.animation: # Parcours des mouvements\r\n numero = 0 # Compteur utilisé dans le parcours des sprites\r\n for sprite in self.animation[mouvement]: # Parcours des sprites\r\n if isinstance(sprite, str): # Si le sprite est encore un texte\r\n img = pg.image.load(sprite).convert_alpha() # Charger Img\r\n self.animation[mouvement][numero] = img # Sauvegarder\r\n numero += 1 # Numéro du sprite actuel + 1\r","title":""},{"docid":"69fcc736a6c327a022d084a74ada7be3","score":"0.46479815","text":"def update_bullets(g_settings, screen, stats, ship, scores, \\\n\t\t\t\t\t\t\tprojectiles, powerups, enter, exit, \\\n\t\t\t\t\t\t\t\t\t\t\taliens=0, twits=0):\n\n\tglobal twits_list\n\tglobal total_twits\n\t# OPT maybe just pass them by index to functions? These reassign every time\n\tbombs \t= projectiles[0]\n\tbullets = projectiles[1]\n\tlazers \t= projectiles[2]\n\n\t\"\"\" \n\t\tThere are several ways to determine an explosion. \n\t\ti.e. use the global vars - determine where to mark \n\t\tan explosion based upon which twit disappeared. \n\n\t\tbullets is a general term, unfortunately. It could either\n\t\tbe a bomb, lazer, bullet or gun projectile\n\n\t\"\"\"\n\n\t# REFAC\n\tbullets.update()\n\tpowerups.update()\n\tlazers.update()\n\tbombs.update()\n\t# Flag\n\n\t# REFAC\n\tfor item in projectiles:\n\t\t# Copy, because you cannot modify the sprite group WHILE iterating over it. Pygame constraint\n\t\tfor proj in item.copy():\n\t\t\tif proj.rect.bottom <= 0 or proj.rect.top >= 800\\\n\t\t\t\tor proj.rect.x <= 0 or proj.rect.x >= 1200:\n\t\t\t\titem.remove(proj)\n\t\n\tfor power in powerups.copy():\n\t\tif power.rect.top > 800:\n\t\t\tpowerups.remove(power)\n\n\tshot_down = pygame.sprite.groupcollide(bullets, twits, True, False)\n\tbomb_down = pygame.sprite.groupcollide(bombs, twits, True, False)\n\tlaze_down = pygame.sprite.groupcollide(lazers, twits, False, False)\n\t\n\t# Shoosting\n\tif shot_down:\n\t\t\"\"\" specific to bullet hits \"\"\"\n\t\tfor members in shot_down.values():\n\t\t\t# Calculate score per kill and drop powerups\n\t\t\tcheck_kills(g_settings, screen, stats, twits, \\\n\t\t\t\t\t\tmembers, powerups, weapon=\"bullets\")\n\t\t\tbreak\n\t\t# Update Score\n\t\tscores.prep_score()\n\tif bomb_down:\n\n\t\t\"\"\" specific to bullet hits \"\"\"\n\t\tfor members in bomb_down.values():\n\t\t\t# Calculate score per kill and drop powerups\n\t\t\tcheck_kills(g_settings, screen, stats, twits, \\\n\t\t\t\t\t\t\tmembers, powerups, weapon=\"bomb\")\n\t\t\tbreak\n\t\t# Update Score\n\t\tscores.prep_score()\n\tif laze_down:\n\t\t\"\"\" specific to bullet hits \"\"\"\n\t\tfor members in laze_down.values():\n\t\t\t# Calculate score per kill and drop powerups\n\t\t\tcheck_kills(g_settings, screen, stats, twits, \\\n\t\t\t\t\t\t\tmembers, powerups, weapon=\"lazer\")\n\t\t\tbreak\n\t\t# Update Score\n\t\tscores.prep_score()\n\n\t\"\"\" insert other projectile instances here \"\"\"\n\n\t# Powah\n\tget_power = pygame.sprite.spritecollideany(ship, powerups)\n\tif get_power: # The power\n\n\t\t# Changes apply to g_settings values\n\t\t# Initializes ship power from g_settings\n\t\tship.power_up(pwr=apply_power(g_settings, stats, str(get_power.pwr), enter))\n\n\t\tpowerups.remove(get_power)","title":""},{"docid":"b8cdcce4f561a5a3ae76cf1be4e97431","score":"0.4646886","text":"def extrae_sprite(fichero_imagen):\n sprites_final = []\n return sprites_final","title":""},{"docid":"4b597e4a87c54b7eca6ca00a52cca347","score":"0.46461502","text":"def GFX(self):\n return self.GFXlist[0]","title":""},{"docid":"2aa1e6644d37c20aaca72c0d3d9d1f58","score":"0.46369523","text":"def draw(self, screen):\n for sprite in self._group:\n sprite.draw(screen)","title":""},{"docid":"1d54171f70aa40692be43a9efa6154ba","score":"0.46335545","text":"def bullet(r,h):\n sphere = Sphere(r=1)\n cut_cube = Cube(size=[3*r, 3*r, 3*r])\n cut_cube = Translate(cut_cube,v=[0,0,-1.5*r])\n bullet = Difference([sphere, cut_cube])\n vscale = [r,r,h]\n bullet = Scale(bullet,v=vscale)\n return [bullet]","title":""},{"docid":"37c986c1d4f0bcb32e802dc6d3758de7","score":"0.46294105","text":"def __init__(self, player):\r\n self.platform_list = pygame.sprite.Group()\r\n self.enemy_list = pygame.sprite.Group()\r\n \r\n self.player = player","title":""},{"docid":"4bf0ef06008ac263371cadc5515f3fb3","score":"0.46194234","text":"def __init__(self):\r\n pygame.sprite.Sprite.__init__(self)\r\n \r\n self.image = boss1\r\n \r\n self.rect = self.image.get_rect()","title":""},{"docid":"60ad9af90fe5cc7d9ae4068624166c65","score":"0.46187717","text":"def getGroups():","title":""},{"docid":"449d7293fdd1dc66f73f5ac335c166e5","score":"0.45991948","text":"def _fire_bullets(self):\r\n if len(self.bullets) <= self.settings.bullets_allowed:\r\n new_bullet = Bullet(self)\r\n self.bullets.add(new_bullet)\r\n se.bullet_sound.play()","title":""},{"docid":"29104e9720cfca955f441ba718bf39ea","score":"0.45642242","text":"def _fire_bullet(self):\r\n if len(self.bullets) < self.settings.bullets_allowed:\r\n new_bullet = Bullet(self)\r\n self.bullets.add(new_bullet)","title":""},{"docid":"29104e9720cfca955f441ba718bf39ea","score":"0.45642242","text":"def _fire_bullet(self):\r\n if len(self.bullets) < self.settings.bullets_allowed:\r\n new_bullet = Bullet(self)\r\n self.bullets.add(new_bullet)","title":""},{"docid":"222bc76c146747a66d2ea99a45de382d","score":"0.4561723","text":"def DrawBullet(self):\r\n self._display_surf.blit(self.bullet, self.bulletrect)\r\n self._display_surf.blit(self.plane, self.planerect)\r\n self.bulletrect = self.bulletrect.move(self.speed_down)","title":""},{"docid":"abd7def2c58198686c2289efc35b13b7","score":"0.45615393","text":"def fire_bigWeapon(self):\r\n now = pygame.time.get_ticks()\r\n if now - self.bgBullet_timer >= self.bg_bullet_attack_interval:\r\n self.bgBullet_timer = now\r\n\r\n bg_bullet = BigWeapon()\r\n # place it the position of the player\r\n mid_x, mid_y = self.rect.midtop\r\n bg_bullet.rect.x = mid_x\r\n bg_bullet.rect.y = mid_y\r\n bg_bullet.add(self.allSprites_group, self.bullets_group)","title":""},{"docid":"e7cd37a7d408d457a168468469c97785","score":"0.45562005","text":"def draw_bullet(self):\r\n pygame.Surface.blit( self.screen,self.rotatedSurface, self.rect)","title":""},{"docid":"a1149c2beb8e12473dd7e7f538e65f97","score":"0.45488045","text":"def _fire_bullet(self):\n if len(self.bullets) < self.settings.bullets_allowed:\n new_bullet = Bullet(self)\n self.bullets.add(new_bullet)","title":""},{"docid":"a1149c2beb8e12473dd7e7f538e65f97","score":"0.45488045","text":"def _fire_bullet(self):\n if len(self.bullets) < self.settings.bullets_allowed:\n new_bullet = Bullet(self)\n self.bullets.add(new_bullet)","title":""},{"docid":"a1149c2beb8e12473dd7e7f538e65f97","score":"0.45488045","text":"def _fire_bullet(self):\n if len(self.bullets) < self.settings.bullets_allowed:\n new_bullet = Bullet(self)\n self.bullets.add(new_bullet)","title":""},{"docid":"9ec008fdcd541120d3348fdc05adec70","score":"0.4543154","text":"def shooting(self):\n return self.skills[Skill.Shooting]","title":""},{"docid":"aa98bc992cbe2f9a8b15ad5f61048160","score":"0.45428386","text":"def update_bullets(bullets):\n bullets.update()\n\n #Get rid of bullets that have disappeared .\n for bullet in bullets.copy():\n if bullet.rect.bottom <= 0:\n bullets.remove(bullet)","title":""},{"docid":"b69e2ad9bc7d98756a7580463ee06a46","score":"0.45413607","text":"def create_and_add_digit(self, digit_group):\n digit_object = DigitSprite(self.settings, self.screen, self.settings.image_res.lcd_digit_images, 0)\n digit_group.add(digit_object)\n return digit_object","title":""},{"docid":"b0546d740d537048444ac1a0912e7437","score":"0.45328695","text":"def getSpritesbyClass(cls, sclass):\n return App._spritesdict.get(sclass, [])","title":""},{"docid":"0eb76d97571dd8fe8429455b15afd8ef","score":"0.45319355","text":"def fire_bullet(ai_settings, screen, ship, bullets):\n if len(bullets) < ai_settings.bullets_allowed:\n new_bullet = Bullet(ai_settings, screen, ship)\n bullets.add(new_bullet)","title":""},{"docid":"623572ac2bbf5301fd61024e05683afd","score":"0.45170495","text":"def update_bullets(ai_settings, screen, stats, score_board, ship, aliens, bullets):\n bullets.update()\n\n for bullet in bullets.copy():\n if bullet.rect.bottom <= 0:\n bullets.remove(bullet)\n\n check_bullet_alien_collision(ai_settings, screen, stats, score_board, ship, aliens, bullets)","title":""},{"docid":"00820041d56408b1fd99e76b9e8ad2ee","score":"0.4512272","text":"def __fire_bullet(self):\n if len(self.__bullets) < self.__ai_settings.bullets_allowed:\n new_bullet = Bullet(self.__ai_settings, self.__screen,\n self.__ship)\n self.__bullets.add(new_bullet)","title":""},{"docid":"bd3cac4a36a4104df67f554e49fb8d0b","score":"0.45053065","text":"def sprite(self, x, y, width, height):\n return Image(self.sheet, x, y, width, height)","title":""},{"docid":"3c49b51caad36257a76387911fa09063","score":"0.44994795","text":"def create_icons_children(children, batch_labels):\n i = 1\n icons = []\n for child in children:\n small_icon = pyglet.sprite.Sprite(child.img_happy, x=35, y=490 - i*19, batch=batch_labels)\n small_icon.scale = 0.11\n icons.append(small_icon)\n i += 1\n return icons","title":""},{"docid":"9bd26d07175332a724587ef3f2c6d2d5","score":"0.44973153","text":"def on_mouse_press(self, x, y, button, modifiers):\n\n # Only allow the user so many bullets on screen at a time to prevent\n # them from spamming bullets.\n if len(self.player_bullet_list) < MAX_PLAYER_BULLETS:\n\n # Gunshot sound\n gun_sounds = [\"throw1\", \"throw3\", \"throw4\", \"throw4\"]\n random_sound = gun_sounds[random.randrange(0, 4)]\n self.gun_sound = arcade.load_sound(str(Path(__file__).parent.resolve()) + f\"\\\\assets\\\\{random_sound}.wav\")\n arcade.play_sound(self.gun_sound)\n\n # Create a player bullet randomly from the list of options\n player_bullets = [\"frying_pan\", \"rolling_pin\", \"spoon\", \"knife\"]\n random_bullet = player_bullets[random.randrange(0, 4)]\n bullet_sprite_path = str(Path(__file__).parent.resolve()) + f\"\\\\assets\\\\{random_bullet}.png\"\n bullet = arcade.Sprite(bullet_sprite_path, SPRITE_SCALING_LASER)\n\n # The image points to the right, and we want it to point up. So\n # rotate it.\n # Set up the initial angle, and the \"spin\"\n bullet.angle = random.randrange(360)\n bullet.change_angle = random.randrange(15, 16)\n\n\n # Give the bullet a speed\n bullet.change_y = BULLET_SPEED\n\n # Position the bullet\n bullet.center_x = self.player_sprite.center_x\n bullet.bottom = self.player_sprite.top\n\n # Add the bullet to the appropriate lists\n self.player_bullet_list.append(bullet)","title":""},{"docid":"c1a3d411737694c89bfda90119f3d221","score":"0.4478823","text":"def _get_group_icon_entries(self, num=0):\n groupicon = self.groupiconres.directory.entries[num]\n if groupicon.struct.DataIsDirectory:\n # Select the first language from subfolders as needed.\n groupicon = groupicon.directory.entries[0]\n\n # Read the data pointed to by the group icon directory (GRPICONDIR) struct.\n rva = groupicon.data.struct.OffsetToData\n size = groupicon.data.struct.Size\n data = self._pe.get_data(rva, size)\n file_offset = self._pe.get_offset_from_rva(rva)\n\n grp_icon_dir = self._pe.__unpack_data__(GRPICONDIR_FORMAT, data, file_offset)\n # logger.debug(grp_icon_dir)\n\n if grp_icon_dir.Reserved:\n raise InvalidIconDefinitionError(\"Invalid group icon definition (got Reserved=%s instead of 0)\" % hex(grp_icon_dir.Reserved))\n\n # For each group icon entry (GRPICONDIRENTRY) that immediately follows, read its data and save it.\n grp_icons = []\n icon_offset = grp_icon_dir.sizeof()\n for idx in range(grp_icon_dir.Count):\n grp_icon = self._pe.__unpack_data__(GRPICONDIRENTRY_FORMAT, data[icon_offset:], file_offset+icon_offset)\n icon_offset += grp_icon.sizeof()\n grp_icons.append(grp_icon)\n # logger.debug(\"Got logical group icon %s\", grp_icon)\n\n return grp_icons","title":""},{"docid":"2b9973149da558072cb0d3533d6c0d92","score":"0.4469877","text":"def fire_bullet(ai_settings, screen, ship, bullets):\n #create a new bullet if limit not reached yet.\n if len(bullets) < ai_settings.bullet_allowed:\n new_bullet = Bullet(ai_settings, screen, ship)\n bullets.add(new_bullet)","title":""},{"docid":"6b28e48909366e80064165f63540e562","score":"0.4454238","text":"def getSpriteSheet(cls, filename):\n try:\n return cls.spritesheets[filename]\n except KeyError:\n pass\n\n # La feuille de sprite n'était pas en mémoire, on va donc l'ajouter\n spritesheet = SpriteSheet(filename)\n cls.spritesheets[filename] = spritesheet\n\n # Et on la retourne\n return spritesheet","title":""},{"docid":"ff2828373c176f42f5a35971bf1c0aa8","score":"0.44487923","text":"def _update_bullets(self):\n # Update bullet position.\n # Below we will control to get rid of the bullets that have\n # Dissapear.\n self.bullets.update()\n for bullet in self.bullets.copy():\n if bullet.rect.bottom <= 0:\n self.bullets.remove(bullet)\n # print(len(self.bullets))","title":""},{"docid":"468e8cc68c276656f2d2ab6a925d802d","score":"0.44471857","text":"def get_all_sprites(self):\n all_sprites = self.maze.walls + self.maze.gates + \\\n self.maze.items + self.maze.guardians\n all_sprites.append(self.character)\n\n return all_sprites","title":""},{"docid":"38dc2c8f0f81a1ee121b28b7e7b9e2b8","score":"0.44355947","text":"def bulletslide(self,\n title='Here goes the title of the slide',\n bullets=[], # list of bullet points\n dim=False, # dimming of bullet points\n intro='',\n outro='',\n figure=None, # filename(s) with figure(s)\n figure_pos='s', # north, east, south, west\n figure_fraction_width=1.0,\n figure_angle=0, # indicates rotation (90, 270)\n bullet_block=True,\n bullet_block_heading='',\n intro_block = True,\n intro_block_heading = '',\n outro_block = True,\n outro_block_heading = '',\n left_column_width=0.5,\n header_footer=None,\n hide=False,\n ):\n content = []\n if intro:\n if intro_block:\n if intro_block_heading:\n intro = TextBlock(intro, heading=intro_block_heading)\n else:\n intro = TextBlock(intro)\n else:\n intro = Text(intro)\n content.append(intro)\n if bullets:\n bulletblock = BulletBlock(bullets, heading=bullet_block_heading)\n content.append(bulletblock)\n if outro:\n if outro_block:\n if outro_block_heading:\n outro = TextBlock(outro, heading=outro)\n else:\n outro = TextBlock(outro)\n else:\n outro = TextBlock(outro)\n content.append(outro)\n return latexslides.Slide(title=title, content=content, dim=dim,\n figure=figure, figure_pos=figure_pos,\n figure_size=figure_fraction_width,\n figure_angle=figure_angle,\n left_column_width=left_column_width,\n hidden=hide)","title":""},{"docid":"18d870d2aff29216aa0f976435ee4f35","score":"0.4433096","text":"def create_background_sprites(self, k):\n\n for y in range(0, (k * ROAD_IMAGE_RECT.height), ROAD_IMAGE_RECT.height):\n self.background_tiles.add(Background_Sprite(0, y))","title":""},{"docid":"7689275140f4a67922e849a082ceec35","score":"0.44326815","text":"def r_group(self, name):\r\n return self.r_maps_groups().get(name)","title":""},{"docid":"8dda0edab3a2790bfebaaf3ba8198133","score":"0.443171","text":"def tile_list():\n\treturn [GrassTile, WaterTile, RockTile]","title":""}],"string":"[\n {\n \"docid\": \"15d234b9db0d0fc7dd1acbff40c75c5b\",\n \"score\": \"0.6432783\",\n \"text\": \"def sprites(self):\\n return self._group.sprites()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"de6a149d4ec31f0f540233fe9e875647\",\n \"score\": \"0.6042333\",\n \"text\": \"def loadBullet(self):\\n bullet = Projectile(self.x + 70, self.y + 47, self.facing_left)\\n return bullet\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5d08deda44d612b95e9cc7514dae379e\",\n \"score\": \"0.5839755\",\n \"text\": \"def getSprite(self):\\n return self.image\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ed2a8668934e3147d90c41e9897823ae\",\n \"score\": \"0.5698468\",\n \"text\": \"def make_sprite_group(self, sprites):\\n tempgroup = pygame.sprite.LayeredDirty(sprites)\\n return tempgroup\",\n \"title\": \"\"\n },\n {\n \"docid\": \"74c35ed97166d369ffd7bd1447cfec0c\",\n \"score\": \"0.56705916\",\n \"text\": \"def getSprites(self):\\n\\n ground = load_image('OW_Ground.png')\\n grass = load_image('Grass.png')\\n water = load_image('Water.png')\\n tree = load_image('Tree.png')\\n wall = load_image('BrickWall.png')\\n breakableWall = [load_image('BreakableWall.png'), load_image('BrokenWall.png')]\\n shooter = self.shooterImages()\\n player = self.kingOWImages()\\n passage = load_image('OW_Ground.png')\\n cave = load_image('CaveEntrance.png')\\n ball = self.ballImages()\\n blank = load_image(\\\"Blank.png\\\")\\n bomb = load_image(\\\"BlankBomb.png\\\")\\n nums = self.numberImages()\\n potion = load_image(\\\"Blank_Potion_Health.png\\\")\\n heart = [load_image('Heart_0.png'), load_image(\\\"Heart_1.png\\\"), load_image(\\\"Heart_2.png\\\"), load_image(\\\"Heart_3.png\\\"), load_image(\\\"Heart_4.png\\\")]\\n kingbomb = load_image(\\\"Bomb.png\\\")\\n kingarrow = self.arrowImages()\\n\\n return [ground, grass, water, tree, wall, breakableWall, shooter, shooter, player, passage, cave, ball, blank, bomb, nums, potion, nums, heart, heart, heart, kingbomb, kingarrow]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7e37240fcc5dfe487b52499105727495\",\n \"score\": \"0.56694347\",\n \"text\": \"def getSprites(self):\\n\\n ground = load_image('CaveFloor.png')\\n wall = load_image('CaveWall.png')\\n BreakableWall = [load_image('CaveWallBreakable.png'), load_image('CaveWallBroken.png')]\\n pickbomb = load_image('CaveBomb.png')\\n player = self.kingCaveImages()\\n passage = load_image('CaveEntrance.png')\\n blank = load_image(\\\"Blank.png\\\")\\n bomb = load_image(\\\"BlankBomb.png\\\")\\n nums = self.numberImages()\\n potion = load_image(\\\"Blank_Potion_Health.png\\\")\\n heart = [load_image('Heart_0.png'), load_image(\\\"Heart_1.png\\\"), load_image(\\\"Heart_2.png\\\"), load_image(\\\"Heart_3.png\\\"), load_image(\\\"Heart_4.png\\\")]\\n kingbomb = load_image(\\\"CaveBomb.png\\\")\\n kingarrow = self.arrowImages()\\n\\n return [ground, wall, BreakableWall, blank, player, passage, pickbomb, blank, bomb, nums, potion, nums, heart, heart, heart, kingbomb, kingarrow]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"273f5bec30716b37e9ce87cd63123f48\",\n \"score\": \"0.56469\",\n \"text\": \"def get_sprite(self, sprite_name: str) -> Sprite:\\r\\n return self.sprites[sprite_name]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"af87d4c68e8aa78f98dd8062947868b3\",\n \"score\": \"0.56391895\",\n \"text\": \"def getSprites(self):\\n ground = load_image('OW_Ground.png')\\n grass = load_image('Grass.png')\\n water = load_image('Water.png')\\n tree = load_image('Tree.png')\\n troll = self.trollImages()\\n bat = self.batImages()\\n player = self.kingOWImages()\\n passage = load_image('OW_Ground.png')\\n javelin = self.javelinImages()\\n blank = load_image(\\\"Blank.png\\\")\\n bomb = load_image(\\\"BlankBomb.png\\\")\\n nums = self.numberImages()\\n potion = load_image(\\\"Blank_Potion_Health.png\\\")\\n heart = [load_image('Heart_0.png'), load_image(\\\"Heart_1.png\\\"), load_image(\\\"Heart_2.png\\\"), load_image(\\\"Heart_3.png\\\"), load_image(\\\"Heart_4.png\\\")]\\n kingbomb = load_image(\\\"Bomb.png\\\")\\n kingarrow = self.arrowImages()\\n\\n return [ground, grass, water, tree, troll, bat, player, passage, passage, javelin, blank, bomb, nums, potion, nums, heart, heart, heart, kingbomb, kingarrow]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d3f46e104f86b8435759121be7d1dcc3\",\n \"score\": \"0.5470347\",\n \"text\": \"def __spawn_bullet (self):\\n\\n mouse_pos = pygame.mouse.get_pos()\\n new_bullet = Bullet(settings_game[\\\"bullet_type_string\\\"], mouse_pos,\\n self.player.rect.center)\\n self.bullets.add(new_bullet)\\n self.player.bullets -= 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c5ebffe304deb559e74685146db5381d\",\n \"score\": \"0.52890384\",\n \"text\": \"def LoadSprites(self):\\n self.mainCloud = MainCloud()\\n self.cloud_sprites = pygame.sprite.GroupSingle(self.mainCloud)\\n self.grass_sprites = pygame.sprite.Group()\\n for x in range(self.numOfCloudsHorizontal):\\n for y in range(self.numOfCloudsVertical):\\n self.grass_sprites.add(Grass(pygame.Rect(x*10,y*10,10,10))) # rect(left,top,w,h)\\n self.black_clouds_sprites = pygame.sprite.Group()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8013222ce56a01f2c92d78980d7a934d\",\n \"score\": \"0.5272742\",\n \"text\": \"def get_drawables(self):\\n return [self.my_group, self.background.grass, self.platform_handler.platforms, self.projectiles.shurikens]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cb1ebe1084a531c727f7478b50f0e5cd\",\n \"score\": \"0.52546614\",\n \"text\": \"def createExplosionTextureList():\\r\\n columns = 16\\r\\n count = 60\\r\\n sprite_width = 256\\r\\n sprite_height = 256\\r\\n file_name = \\\":resources:images/spritesheets/explosion.png\\\"\\r\\n list_textures = arcade.load_spritesheet(file_name, sprite_width, sprite_height, columns, count)\\r\\n return list_textures\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5e0dbae9e78215f26efddb4f159a127e\",\n \"score\": \"0.5230385\",\n \"text\": \"def sprite(self, name):\\n return sprite.Sprite(image=self.image,\\n image_pos = self.sprites[name])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"95c51affb86dda7bfc1736359af48926\",\n \"score\": \"0.52288735\",\n \"text\": \"def shoot_bullet(self):\\n current_time = pygame.time.get_ticks()\\n if current_time - self.last_bullet_shot > DELAY:\\n self.last_bullet_shot = current_time\\n bullet = Bullet(self.rect.centerx, self.rect.top)\\n all_bullets.add(bullet)\\n all_sprites.add(bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1bcda63ad4bd80eda630120ed29e16b1\",\n \"score\": \"0.51727575\",\n \"text\": \"def draw_bullet(self):\\r\\n pygame.draw.rect(self.screen, self.color, self.rect)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0518ef58044ce52b20f27062eab966b6\",\n \"score\": \"0.5167384\",\n \"text\": \"def _fire_bullet(self):\\n\\t\\tif len(self.bullets) < self.settings.bullet_allowed:\\n\\t\\t\\tnew_bullet = Bullet(self)\\n\\t\\t\\tself.bullets.add(new_bullet) # Add the new bullet to the group\",\n \"title\": \"\"\n },\n {\n \"docid\": \"999da1c5050c976ef42556ea849a18bc\",\n \"score\": \"0.514254\",\n \"text\": \"def bulletList(self):\\n bullet_list = []\\n for p in self.users:\\n for b in p.bullet_list:\\n b.update()\\n bullet_list.append(b.toObj())\\n return bullet_list\",\n \"title\": \"\"\n },\n {\n \"docid\": \"503cd7e90e43dd919eb7787b24aabc09\",\n \"score\": \"0.51109165\",\n \"text\": \"def get_overlapping_sprites(self):\\n self._check_overlap()\\n return self._overlapping_sprites\",\n \"title\": \"\"\n },\n {\n \"docid\": \"23c1f473ed2b4f8d01a1bcce8f2c4405\",\n \"score\": \"0.5107428\",\n \"text\": \"def draw_bullet(self):\\n pygame.draw.rect(self.screen, self.color,self.rect)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bd067004ebf19648e4909101abc34a15\",\n \"score\": \"0.5106111\",\n \"text\": \"def draw_bullet(self):\\n pygame.draw.rect(self.screen, self.color, self.rect)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bd067004ebf19648e4909101abc34a15\",\n \"score\": \"0.5106111\",\n \"text\": \"def draw_bullet(self):\\n pygame.draw.rect(self.screen, self.color, self.rect)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bd067004ebf19648e4909101abc34a15\",\n \"score\": \"0.5106111\",\n \"text\": \"def draw_bullet(self):\\n pygame.draw.rect(self.screen, self.color, self.rect)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bd067004ebf19648e4909101abc34a15\",\n \"score\": \"0.5106111\",\n \"text\": \"def draw_bullet(self):\\n pygame.draw.rect(self.screen, self.color, self.rect)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bd067004ebf19648e4909101abc34a15\",\n \"score\": \"0.5106111\",\n \"text\": \"def draw_bullet(self):\\n pygame.draw.rect(self.screen, self.color, self.rect)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"35a504cc1d3d0966339865ca97be9c40\",\n \"score\": \"0.5081203\",\n \"text\": \"def draw_bullet(self):\\n pygame.draw.rect(self._screen, self._color, self.rect)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ebc5554d77a51f7254a6b5c5d74e94ed\",\n \"score\": \"0.50686556\",\n \"text\": \"def player_shoot(self):\\n self.playerbullet = PlayerBullet(self.player.rect.centerx, self.player.rect.top, -10, YELLOW)\\n self.all_sprites.add(self.playerbullet)\\n self.player_bullets.add(self.playerbullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2a01f034c1b151eb3455d2b9ec56705f\",\n \"score\": \"0.5066055\",\n \"text\": \"def loadSprite(filename):\\n with open(filename) as f:\\n sprite = []\\n for line in f:\\n sprite.append(line.rstrip())\\n return sprite\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5ce7635e763cdf23731ac05a8baf867c\",\n \"score\": \"0.50316167\",\n \"text\": \"def spriteType(self):\\n return 'background'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cfabe96a7a3b0a7d720eeab0995f678e\",\n \"score\": \"0.502615\",\n \"text\": \"def handle_bullet_collisions(self):\\r\\n # reduce the health value of the enemy\\r\\n self.enemy_health.reduce_health(10)\\r\\n\\r\\n if self.enemy_health.current_health <= 0: # remove enemy sprite from enemies Group\\r\\n self.kill()\\r\\n self.inheritance_packs.update_enemy_pos(self.rect.x, self.rect.y)\\r\\n return self.inheritance_packs\\r\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"705462825acf29f772e84fb92688bc4b\",\n \"score\": \"0.50234526\",\n \"text\": \"def get_bullet_points(self, product):\\n bullet_points = ''\\n for bullet in product.bullet_point_ids:\\n bullet_point = \\\"\\\"\\\"<BulletPoint>%s</BulletPoint>\\\"\\\"\\\" % (html.escape(bullet.name))\\n bullet_points = '%s %s' % (bullet_points, bullet_point)\\n if product.bullet_point_ids:\\n return bullet_points\",\n \"title\": \"\"\n },\n {\n \"docid\": \"59d71d576b1eb65d3abeb1e08cb7a5d2\",\n \"score\": \"0.5013284\",\n \"text\": \"def get_sprite_pack(self, sprite_pack_name: str) -> SpritePack:\\r\\n return self.sprite_packs[sprite_pack_name]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7238078d0a619f50cf7bc2e3cd00752c\",\n \"score\": \"0.4974574\",\n \"text\": \"def draw_bullet(bullet_obj, game_screen):\\n game_screen.blit(bullet_obj.get_img(), (bullet_obj.get_x(), bullet_obj.get_y()))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"37f4aa9392dcefe4fc82fa0217755438\",\n \"score\": \"0.49725246\",\n \"text\": \"def spriteType(self):\\n return 'player'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"74a6be708d11175815edbed73ceb2315\",\n \"score\": \"0.49511772\",\n \"text\": \"def show_pile(self):\\n img_list = []\\n for card in range(len(self.pile)):\\n if card <= 2 :\\n img = pygame.image.load(\\\"assets/\\\"+str(self.pile[card])+\\\".png\\\")\\n img_list.append(img)\\n return img_list\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e7957c421206c66e6a8afce3e0238952\",\n \"score\": \"0.49264708\",\n \"text\": \"def sprite_layers(self) -> Iterator:\\n return sorted(self, key=lambda s: getattr(s, \\\"layer\\\", 0))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f41aa2cfc170fc045a29f59b7ccd28fd\",\n \"score\": \"0.49092758\",\n \"text\": \"def _generate_level(self):\\n for t in range(self.LEVEL_WIDTH * self.LEVEL_HEIGHT):\\n tile = Tile(\\\"sprites/grass.png\\\")\\n self.LEVEL.append(tile)\\n self.sprite_group.add(tile)\\n self.LEVEL[0].image.fill((0xff, 0xff, 0xff))\\n self.LEVEL[self.LEVEL_WIDTH * self.LEVEL_HEIGHT - 1].image.fill((0, 0, 0))\\n print(*self.sprite_group)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f52edde00d04810b1428c6129f752ce9\",\n \"score\": \"0.490017\",\n \"text\": \"def shoot(self):\\n # Instantiates a bullet\\n bullet = Bullet()\\n bullet.center.x = self.center.x + \\\\\\n math.cos(math.radians(self.angle)) * 10\\n bullet.center.y = self.center.y + \\\\\\n math.sin(math.radians(self.angle)) * 10\\n bullet.angle = self.angle\\n\\n bullet.velocity.dx = math.cos(math.radians(self.angle)) * bullet.speed\\n bullet.velocity.dy = math.sin(math.radians(self.angle)) * bullet.speed\\n\\n return bullet\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b5a9306cc7e9f16f7c0f4badd90ff00c\",\n \"score\": \"0.48826018\",\n \"text\": \"def double_fire_smallBullet(self):\\r\\n \\r\\n leftB = SmallWeapon()\\r\\n rightB = SmallWeapon()\\r\\n leftB.rect.x, leftB.rect.y = self.rect.topleft\\r\\n rightB.rect.x, rightB.rect.y = self.rect.topright\\r\\n\\r\\n # reset the power value and bar\\r\\n self.power.clear_power(100)\\r\\n self.bullets_group.add(leftB, rightB)\\r\\n self.allSprites_group.add(leftB, rightB)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fd4669578bb9cdd05dacc0868372da21\",\n \"score\": \"0.4875645\",\n \"text\": \"def spritesheet() -> None:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ba1f50c7fa6efa77a4b47d7b5d81a7a3\",\n \"score\": \"0.48697823\",\n \"text\": \"def SpriteCollision(sprite, spriteGroup, kill=False):\\n return pygame.sprite.spritecollide(sprite, spriteGroup, kill)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6f3055a8bc6772b3220b921c77f69546\",\n \"score\": \"0.48484784\",\n \"text\": \"def fire_bullet(ai_settings, screen, ship, bullets):\\n # sounds for bullets\\n shoot = pygame.mixer.Sound('sounds/laser.wav')\\n\\n # Create a new bullet and add it to the bullets group\\n if len(bullets) < ai_settings.bullets_allowed:\\n new_bullet = Bullet(ai_settings=ai_settings, screen=screen, ship=ship)\\n bullets.add(new_bullet)\\n shoot.play()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ef84ec9ed1bb5064cc838df8d15e8094\",\n \"score\": \"0.4846823\",\n \"text\": \"def _fire_bullet(self):\\r\\n\\t\\tif len(self.bullets) < 3:\\r\\n\\t\\t\\tnew_bullet = Bullet(self)\\r\\n\\t\\t\\tself.bullets.add(new_bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f3a6842426109a35bdb55404c30189c3\",\n \"score\": \"0.48170656\",\n \"text\": \"def implode(self, player_x, screen_height):\\n bullets = []\\n for i in range(10):\\n bullets.append(Knife(self.rect.x, self.rect.y, player_x, screen_height * i/10))\\n return bullets\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e158dd1ec5956c950b7acd816553cd5a\",\n \"score\": \"0.48120666\",\n \"text\": \"def get_drawables(self) -> List[Drawable]:\\n return self.drawables\",\n \"title\": \"\"\n },\n {\n \"docid\": \"66257202c264e74a43435a3b5bb173d1\",\n \"score\": \"0.4810104\",\n \"text\": \"def remove_dead(group):\\r\\n for sprite in group:\\r\\n if not sprite.alive:\\r\\n group.remove(sprite)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1bf6549aa5524d8ce7df3bd8e692d6b7\",\n \"score\": \"0.4807381\",\n \"text\": \"def list_group_icons(self):\\n return [(e.struct.Name, e.struct.OffsetToData)\\n for e in self.groupiconres.directory.entries]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bf5a5eb76183666b69515bf710369418\",\n \"score\": \"0.48047295\",\n \"text\": \"def get_groups(self):\\n return self._groups\",\n \"title\": \"\"\n },\n {\n \"docid\": \"61697237fc3a7480e7392ce1d652db50\",\n \"score\": \"0.47825295\",\n \"text\": \"def game_loop(self):\\n clock = pygame.time.Clock()\\n bullet_sound = pygame.mixer.Sound('Sound/bullet.wav')\\n score_font = pygame.font.SysFont('arial', 30, True)\\n shoot_loop = 0\\n bullets = []\\n dino = Player(self.level.get_player_start_position())\\n\\n while True:\\n clock.tick(40)\\n\\n dino.gun = self.level.dino_gun\\n\\n if dino.pos.x + 350 > self.screen_width:\\n self.level.shift_world(-5, 0)\\n dino.slide(-5, 0)\\n if dino.pos.x - 350 <= 0 and self.level.world_shift_x < 0:\\n self.level.shift_world(5, 0)\\n dino.slide(5, 0)\\n if self.level.world_shift_x <= self.level.level_limit:\\n print(self.levels.index(self.level) + 1)\\n try:\\n self.level = self.levels[self.levels.index(self.level) + 1]\\n except IndexError:\\n self.end_screen(dino)\\n return False\\n dino.reset()\\n\\n if shoot_loop > 0:\\n shoot_loop += 1\\n if shoot_loop > 4:\\n shoot_loop = 0\\n\\n for event in pygame.event.get():\\n if event.type == pygame.QUIT:\\n return\\n if event.type == pygame.KEYDOWN:\\n if event.key == pygame.K_UP:\\n dino.jump()\\n if event.key == pygame.K_BACKQUOTE:\\n for enemy in self.level.enemys:\\n enemy.debug_draw(\\n draw_bounds=not enemy.draw_bounds,\\n draw_hitbox=not enemy.draw_hitbox)\\n dino.debug_draw(draw_hitbox=not dino.draw_hitbox)\\n\\n if not self.jump_button.get_state():\\n jump_flag = True\\n if self.jump_button.get_state():\\n if jump_flag:\\n dino.jump()\\n jump_flag = False\\n\\n for bullet in bullets:\\n remove = False\\n hits = pygame.sprite.spritecollide(bullet,\\n self.level.platforms, False)\\n if hits:\\n remove = True\\n if (bullet.pos.x < self.screen_width) and (bullet.pos.x > 0):\\n bullet.update_location()\\n else:\\n remove = True\\n\\n hits = pygame.sprite.spritecollide(bullet, self.level.enemys,\\n False)\\n for hit in hits:\\n self.score += 5\\n hit.hit()\\n remove = True\\n\\n if remove:\\n bullets.pop(bullets.index(bullet))\\n\\n keys = pygame.key.get_pressed()\\n\\n if keys[pygame.K_LEFT] or self.left_button.get_state():\\n dino.move_left()\\n elif keys[pygame.K_RIGHT] or self.right_button.get_state():\\n dino.move_right()\\n else:\\n dino.stop()\\n\\n if keys[pygame.K_ESCAPE]:\\n return\\n if keys[pygame.K_a]:\\n print(dino.pos.x - self.level.world_shift_x)\\n\\n if (keys[pygame.K_SPACE] or self.shoot_button.get_state()) and (\\n shoot_loop == 0) and dino.gun:\\n if dino.facing_left:\\n facing = -1\\n else:\\n facing = 1\\n\\n if len(bullets) < 5:\\n bullets.append(\\n Projectile(\\n int(dino.rect.centerx), int(dino.rect.centery), 6,\\n (0, 0, 0), facing))\\n bullet_sound.play()\\n shoot_loop = 1\\n\\n dino.update_location(self.screen_height)\\n\\n self.win.blit(self.level.background, (0, 0))\\n text = score_font.render('Score:' + str(self.score), 1, (0, 0, 0))\\n self.win.blit(text, (0, 10))\\n text = score_font.render(\\n 'Speed:' + str(self.ellip.get_speed()) + \\\" RPM\\\", 1, (0, 0, 0))\\n self.win.blit(text, (0, 40))\\n heart_rate = 132\\n text = score_font.render('Heart Rate:' + str(heart_rate), 1,\\n (0, 0, 0))\\n self.win.blit(text, (0, 70))\\n\\n hits = pygame.sprite.spritecollide(dino, self.level.platforms,\\n False)\\n for hit in hits:\\n dino.touch_down(hit.rect, hit.friction)\\n\\n hits = pygame.sprite.spritecollide(dino, self.level.enemys, False)\\n for hit in hits:\\n dino.hit(hit)\\n if dino.rect.bottom <= (hit.rect.centery -\\n (hit.rect.height // 4)\\n ) and dino.rect.bottom >= hit.rect.top:\\n self.score += 20\\n if dino.dead:\\n self.level.shift_world(0 - self.level.world_shift_x,\\n 0 - self.level.world_shift_y)\\n dino.reset()\\n self.level.draw(self.win)\\n dino.draw(self.win)\\n for bullet in bullets:\\n bullet.draw(self.win)\\n pygame.display.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6017b8cd03ee3844893912aa72f7c490\",\n \"score\": \"0.47737974\",\n \"text\": \"def spriteType(self):\\n #returns the type of sprite we've created\\n return 'enemy'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"443e85be50488c30952cc7b9962788fb\",\n \"score\": \"0.47479936\",\n \"text\": \"def initialize_tiles():\\n sprite_sheet = spritesheet.SpriteSheet(TILES_TEXTURES)\\n # Extracting sprites out of the linear sprite sheet\\n tiles = sprite_sheet.all_sprites(\\n mahjong_tiles_dictionary,\\n SCREEN_WIDTH / 2,\\n SCREEN_HEIGHT / 2)\\n tile_sprite_group = pygame.sprite.Group()\\n\\n # Constructing the tile group for rendering and collision detection\\n for i in range(len(tiles)):\\n # print(tiles[i][0])\\n tile_sprite_group.add(tiles[i][0])\\n\\n return tile_sprite_group\",\n \"title\": \"\"\n },\n {\n \"docid\": \"52e5d8d4c7d99e5597ff0fd4cc72156c\",\n \"score\": \"0.47370762\",\n \"text\": \"def update_bullets(self):\\r\\n #Update bullet positions\\r\\n self.bullets.update()\\r\\n\\r\\n #Get rid of bullets that have disappeared.\\r\\n\\r\\n for bullet in self.bullets.copy():\\r\\n if bullet.rect.bottom <= 0:\\r\\n self.bullets.remove(bullet)\\r\\n print(len(self.bullets))\\r\\n\\r\\n #Check for any bullets that have hit enemy planes\\r\\n\\r\\n #IF so, get rid of the bullet and the plane\\r\\n\\r\\n collisions = pygame.sprite.groupcollide(\\r\\n self.bullets, self.enemy_planes, True, True)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cdb2e121935fae972edc49c70f440b53\",\n \"score\": \"0.47323436\",\n \"text\": \"def double_fire_bigBullet(self):\\r\\n leftB = BigWeapon()\\r\\n rightB = BigWeapon()\\r\\n leftB.rect.x, leftB.rect.y = self.rect.topleft\\r\\n rightB.rect.x, rightB.rect.y = self.rect.topright\\r\\n\\r\\n # reset the power bar and value\\r\\n self.power.clear_power(200)\\r\\n self.bullets_group.add(leftB, rightB)\\r\\n self.allSprites_group.add(leftB, rightB)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"000b755999bdcb33324f179208c65811\",\n \"score\": \"0.47318715\",\n \"text\": \"def __get_timer(self) -> ImageSpriteTimer:\\n return self.__timer.sprite\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ba04a1781c82d2fff62aadf884922d44\",\n \"score\": \"0.47135156\",\n \"text\": \"def BulletMove(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"69c60a183bb23e2bb66fff7316927ce4\",\n \"score\": \"0.47133464\",\n \"text\": \"def spriteType(self):\\n return 'health bar'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1e0943314bcde818d5833f50a5778dbd\",\n \"score\": \"0.4692101\",\n \"text\": \"def shoot(self, player_x, player_y):\\n self.bullet_counter += 1\\n self.bullet_counter %= self.bullet_counter_reset # modulo\\n\\n if self.bullet_counter in self.bullet_frames:\\n self.pew_sound.play()\\n return Knife2(self.rect.x, self.rect.y, player_x)\\n else:\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"793e60563325970dd3ee6bf05780887a\",\n \"score\": \"0.46920672\",\n \"text\": \"def playercollideany(sprite, group):\\n spritecollide = sprite.rect.colliderect\\n for s in group:\\n if spritecollide(s.rect) and s != sprite:\\n return s\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"becdf8f3639deda811300b83c2646bfe\",\n \"score\": \"0.46877676\",\n \"text\": \"def fire_bullet(ai_settings, screen, ship, ship_bullets):\\n # Create a new bullet and add it to the bullets group\\n if len(ship_bullets) < ai_settings.ship_bullets_allowed:\\n new_bullet = Ship_Bullet(ai_settings, screen, ship)\\n ship_bullets.add(new_bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0ada7620b420bef1ce111fa14fdfc236\",\n \"score\": \"0.4684961\",\n \"text\": \"def bullet(radius, outline, fill):\\n \\n # init drawing\\n bitmap = wx.Bitmap(2*radius+2, 2*radius+2)\\n mdc = wx.MemoryDC()\\n mdc.SelectObject(bitmap)\\n dc = wx.GCDC(mdc) if wx.Platform != \\\"__WXMSW__\\\" else mdc\\n \\n # draw bullet\\n dc.SetPen(outline)\\n dc.SetBrush(fill)\\n dc.DrawCircle(radius+1, radius+1, radius)\\n \\n # release bitmap\\n mdc.SelectObject(wx.NullBitmap)\\n \\n # set mask\\n if wx.Platform == \\\"__WXMSW__\\\":\\n bitmap.SetMaskColour(wx.BLACK)\\n \\n return bitmap\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9492b3ca35f0f4164f1af65b7864e233\",\n \"score\": \"0.46735826\",\n \"text\": \"def fire_smallWeapon(self):\\r\\n now = pygame.time.get_ticks()\\r\\n if now - self.smBullet_timer >= self.sm_bullet_attack_interval:\\r\\n self.smBullet_timer = now\\r\\n\\r\\n sm_bullet = SmallWeapon()\\r\\n # place it the position of the player\\r\\n mid_x, mid_y = self.rect.midtop\\r\\n sm_bullet.rect.x = mid_x\\r\\n sm_bullet.rect.y = mid_y\\r\\n sm_bullet.add(self.allSprites_group, self.bullets_group)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7cfd270247041cd9d0dfa2755bd549e0\",\n \"score\": \"0.46691424\",\n \"text\": \"def _fire_bullet(self):\\n if len(self.bullets) < self.settings.bullets_allowed:\\n new_bullet = Bullet(self) # limit 3 at a time\\n self.bullets.add(new_bullet) # add new bullets to bullets\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7274b657148ea4334cec0234ca592566\",\n \"score\": \"0.46582806\",\n \"text\": \"def _fire_bullet(self):\\n if len(self.bullets) < self.settings.bullets_allowed:\\n new_bullet = Bullet(self)\\n self.bullets.add(new_bullet)\\n self.ship_fire_sound.play()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dee57bac06361bbf43bbe1fd1e92543d\",\n \"score\": \"0.46534377\",\n \"text\": \"def sprite(index: int, x: int, y: int) -> None:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a9d7302d7ac83511a0f779d5daeceaaf\",\n \"score\": \"0.46506235\",\n \"text\": \"def charger_sprite(self):\\r\\n for mouvement in self.animation: # Parcours des mouvements\\r\\n numero = 0 # Compteur utilisé dans le parcours des sprites\\r\\n for sprite in self.animation[mouvement]: # Parcours des sprites\\r\\n if isinstance(sprite, str): # Si le sprite est encore un texte\\r\\n img = pg.image.load(sprite).convert_alpha() # Charger Img\\r\\n self.animation[mouvement][numero] = img # Sauvegarder\\r\\n numero += 1 # Numéro du sprite actuel + 1\\r\",\n \"title\": \"\"\n },\n {\n \"docid\": \"69fcc736a6c327a022d084a74ada7be3\",\n \"score\": \"0.46479815\",\n \"text\": \"def update_bullets(g_settings, screen, stats, ship, scores, \\\\\\n\\t\\t\\t\\t\\t\\t\\tprojectiles, powerups, enter, exit, \\\\\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\taliens=0, twits=0):\\n\\n\\tglobal twits_list\\n\\tglobal total_twits\\n\\t# OPT maybe just pass them by index to functions? These reassign every time\\n\\tbombs \\t= projectiles[0]\\n\\tbullets = projectiles[1]\\n\\tlazers \\t= projectiles[2]\\n\\n\\t\\\"\\\"\\\" \\n\\t\\tThere are several ways to determine an explosion. \\n\\t\\ti.e. use the global vars - determine where to mark \\n\\t\\tan explosion based upon which twit disappeared. \\n\\n\\t\\tbullets is a general term, unfortunately. It could either\\n\\t\\tbe a bomb, lazer, bullet or gun projectile\\n\\n\\t\\\"\\\"\\\"\\n\\n\\t# REFAC\\n\\tbullets.update()\\n\\tpowerups.update()\\n\\tlazers.update()\\n\\tbombs.update()\\n\\t# Flag\\n\\n\\t# REFAC\\n\\tfor item in projectiles:\\n\\t\\t# Copy, because you cannot modify the sprite group WHILE iterating over it. Pygame constraint\\n\\t\\tfor proj in item.copy():\\n\\t\\t\\tif proj.rect.bottom <= 0 or proj.rect.top >= 800\\\\\\n\\t\\t\\t\\tor proj.rect.x <= 0 or proj.rect.x >= 1200:\\n\\t\\t\\t\\titem.remove(proj)\\n\\t\\n\\tfor power in powerups.copy():\\n\\t\\tif power.rect.top > 800:\\n\\t\\t\\tpowerups.remove(power)\\n\\n\\tshot_down = pygame.sprite.groupcollide(bullets, twits, True, False)\\n\\tbomb_down = pygame.sprite.groupcollide(bombs, twits, True, False)\\n\\tlaze_down = pygame.sprite.groupcollide(lazers, twits, False, False)\\n\\t\\n\\t# Shoosting\\n\\tif shot_down:\\n\\t\\t\\\"\\\"\\\" specific to bullet hits \\\"\\\"\\\"\\n\\t\\tfor members in shot_down.values():\\n\\t\\t\\t# Calculate score per kill and drop powerups\\n\\t\\t\\tcheck_kills(g_settings, screen, stats, twits, \\\\\\n\\t\\t\\t\\t\\t\\tmembers, powerups, weapon=\\\"bullets\\\")\\n\\t\\t\\tbreak\\n\\t\\t# Update Score\\n\\t\\tscores.prep_score()\\n\\tif bomb_down:\\n\\n\\t\\t\\\"\\\"\\\" specific to bullet hits \\\"\\\"\\\"\\n\\t\\tfor members in bomb_down.values():\\n\\t\\t\\t# Calculate score per kill and drop powerups\\n\\t\\t\\tcheck_kills(g_settings, screen, stats, twits, \\\\\\n\\t\\t\\t\\t\\t\\t\\tmembers, powerups, weapon=\\\"bomb\\\")\\n\\t\\t\\tbreak\\n\\t\\t# Update Score\\n\\t\\tscores.prep_score()\\n\\tif laze_down:\\n\\t\\t\\\"\\\"\\\" specific to bullet hits \\\"\\\"\\\"\\n\\t\\tfor members in laze_down.values():\\n\\t\\t\\t# Calculate score per kill and drop powerups\\n\\t\\t\\tcheck_kills(g_settings, screen, stats, twits, \\\\\\n\\t\\t\\t\\t\\t\\t\\tmembers, powerups, weapon=\\\"lazer\\\")\\n\\t\\t\\tbreak\\n\\t\\t# Update Score\\n\\t\\tscores.prep_score()\\n\\n\\t\\\"\\\"\\\" insert other projectile instances here \\\"\\\"\\\"\\n\\n\\t# Powah\\n\\tget_power = pygame.sprite.spritecollideany(ship, powerups)\\n\\tif get_power: # The power\\n\\n\\t\\t# Changes apply to g_settings values\\n\\t\\t# Initializes ship power from g_settings\\n\\t\\tship.power_up(pwr=apply_power(g_settings, stats, str(get_power.pwr), enter))\\n\\n\\t\\tpowerups.remove(get_power)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b8cdcce4f561a5a3ae76cf1be4e97431\",\n \"score\": \"0.4646886\",\n \"text\": \"def extrae_sprite(fichero_imagen):\\n sprites_final = []\\n return sprites_final\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4b597e4a87c54b7eca6ca00a52cca347\",\n \"score\": \"0.46461502\",\n \"text\": \"def GFX(self):\\n return self.GFXlist[0]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2aa1e6644d37c20aaca72c0d3d9d1f58\",\n \"score\": \"0.46369523\",\n \"text\": \"def draw(self, screen):\\n for sprite in self._group:\\n sprite.draw(screen)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1d54171f70aa40692be43a9efa6154ba\",\n \"score\": \"0.46335545\",\n \"text\": \"def bullet(r,h):\\n sphere = Sphere(r=1)\\n cut_cube = Cube(size=[3*r, 3*r, 3*r])\\n cut_cube = Translate(cut_cube,v=[0,0,-1.5*r])\\n bullet = Difference([sphere, cut_cube])\\n vscale = [r,r,h]\\n bullet = Scale(bullet,v=vscale)\\n return [bullet]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"37c986c1d4f0bcb32e802dc6d3758de7\",\n \"score\": \"0.46294105\",\n \"text\": \"def __init__(self, player):\\r\\n self.platform_list = pygame.sprite.Group()\\r\\n self.enemy_list = pygame.sprite.Group()\\r\\n \\r\\n self.player = player\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4bf0ef06008ac263371cadc5515f3fb3\",\n \"score\": \"0.46194234\",\n \"text\": \"def __init__(self):\\r\\n pygame.sprite.Sprite.__init__(self)\\r\\n \\r\\n self.image = boss1\\r\\n \\r\\n self.rect = self.image.get_rect()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"60ad9af90fe5cc7d9ae4068624166c65\",\n \"score\": \"0.46187717\",\n \"text\": \"def getGroups():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"449d7293fdd1dc66f73f5ac335c166e5\",\n \"score\": \"0.45991948\",\n \"text\": \"def _fire_bullets(self):\\r\\n if len(self.bullets) <= self.settings.bullets_allowed:\\r\\n new_bullet = Bullet(self)\\r\\n self.bullets.add(new_bullet)\\r\\n se.bullet_sound.play()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"29104e9720cfca955f441ba718bf39ea\",\n \"score\": \"0.45642242\",\n \"text\": \"def _fire_bullet(self):\\r\\n if len(self.bullets) < self.settings.bullets_allowed:\\r\\n new_bullet = Bullet(self)\\r\\n self.bullets.add(new_bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"29104e9720cfca955f441ba718bf39ea\",\n \"score\": \"0.45642242\",\n \"text\": \"def _fire_bullet(self):\\r\\n if len(self.bullets) < self.settings.bullets_allowed:\\r\\n new_bullet = Bullet(self)\\r\\n self.bullets.add(new_bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"222bc76c146747a66d2ea99a45de382d\",\n \"score\": \"0.4561723\",\n \"text\": \"def DrawBullet(self):\\r\\n self._display_surf.blit(self.bullet, self.bulletrect)\\r\\n self._display_surf.blit(self.plane, self.planerect)\\r\\n self.bulletrect = self.bulletrect.move(self.speed_down)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"abd7def2c58198686c2289efc35b13b7\",\n \"score\": \"0.45615393\",\n \"text\": \"def fire_bigWeapon(self):\\r\\n now = pygame.time.get_ticks()\\r\\n if now - self.bgBullet_timer >= self.bg_bullet_attack_interval:\\r\\n self.bgBullet_timer = now\\r\\n\\r\\n bg_bullet = BigWeapon()\\r\\n # place it the position of the player\\r\\n mid_x, mid_y = self.rect.midtop\\r\\n bg_bullet.rect.x = mid_x\\r\\n bg_bullet.rect.y = mid_y\\r\\n bg_bullet.add(self.allSprites_group, self.bullets_group)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e7cd37a7d408d457a168468469c97785\",\n \"score\": \"0.45562005\",\n \"text\": \"def draw_bullet(self):\\r\\n pygame.Surface.blit( self.screen,self.rotatedSurface, self.rect)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a1149c2beb8e12473dd7e7f538e65f97\",\n \"score\": \"0.45488045\",\n \"text\": \"def _fire_bullet(self):\\n if len(self.bullets) < self.settings.bullets_allowed:\\n new_bullet = Bullet(self)\\n self.bullets.add(new_bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a1149c2beb8e12473dd7e7f538e65f97\",\n \"score\": \"0.45488045\",\n \"text\": \"def _fire_bullet(self):\\n if len(self.bullets) < self.settings.bullets_allowed:\\n new_bullet = Bullet(self)\\n self.bullets.add(new_bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a1149c2beb8e12473dd7e7f538e65f97\",\n \"score\": \"0.45488045\",\n \"text\": \"def _fire_bullet(self):\\n if len(self.bullets) < self.settings.bullets_allowed:\\n new_bullet = Bullet(self)\\n self.bullets.add(new_bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9ec008fdcd541120d3348fdc05adec70\",\n \"score\": \"0.4543154\",\n \"text\": \"def shooting(self):\\n return self.skills[Skill.Shooting]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aa98bc992cbe2f9a8b15ad5f61048160\",\n \"score\": \"0.45428386\",\n \"text\": \"def update_bullets(bullets):\\n bullets.update()\\n\\n #Get rid of bullets that have disappeared .\\n for bullet in bullets.copy():\\n if bullet.rect.bottom <= 0:\\n bullets.remove(bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b69e2ad9bc7d98756a7580463ee06a46\",\n \"score\": \"0.45413607\",\n \"text\": \"def create_and_add_digit(self, digit_group):\\n digit_object = DigitSprite(self.settings, self.screen, self.settings.image_res.lcd_digit_images, 0)\\n digit_group.add(digit_object)\\n return digit_object\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b0546d740d537048444ac1a0912e7437\",\n \"score\": \"0.45328695\",\n \"text\": \"def getSpritesbyClass(cls, sclass):\\n return App._spritesdict.get(sclass, [])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0eb76d97571dd8fe8429455b15afd8ef\",\n \"score\": \"0.45319355\",\n \"text\": \"def fire_bullet(ai_settings, screen, ship, bullets):\\n if len(bullets) < ai_settings.bullets_allowed:\\n new_bullet = Bullet(ai_settings, screen, ship)\\n bullets.add(new_bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"623572ac2bbf5301fd61024e05683afd\",\n \"score\": \"0.45170495\",\n \"text\": \"def update_bullets(ai_settings, screen, stats, score_board, ship, aliens, bullets):\\n bullets.update()\\n\\n for bullet in bullets.copy():\\n if bullet.rect.bottom <= 0:\\n bullets.remove(bullet)\\n\\n check_bullet_alien_collision(ai_settings, screen, stats, score_board, ship, aliens, bullets)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"00820041d56408b1fd99e76b9e8ad2ee\",\n \"score\": \"0.4512272\",\n \"text\": \"def __fire_bullet(self):\\n if len(self.__bullets) < self.__ai_settings.bullets_allowed:\\n new_bullet = Bullet(self.__ai_settings, self.__screen,\\n self.__ship)\\n self.__bullets.add(new_bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bd3cac4a36a4104df67f554e49fb8d0b\",\n \"score\": \"0.45053065\",\n \"text\": \"def sprite(self, x, y, width, height):\\n return Image(self.sheet, x, y, width, height)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3c49b51caad36257a76387911fa09063\",\n \"score\": \"0.44994795\",\n \"text\": \"def create_icons_children(children, batch_labels):\\n i = 1\\n icons = []\\n for child in children:\\n small_icon = pyglet.sprite.Sprite(child.img_happy, x=35, y=490 - i*19, batch=batch_labels)\\n small_icon.scale = 0.11\\n icons.append(small_icon)\\n i += 1\\n return icons\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9bd26d07175332a724587ef3f2c6d2d5\",\n \"score\": \"0.44973153\",\n \"text\": \"def on_mouse_press(self, x, y, button, modifiers):\\n\\n # Only allow the user so many bullets on screen at a time to prevent\\n # them from spamming bullets.\\n if len(self.player_bullet_list) < MAX_PLAYER_BULLETS:\\n\\n # Gunshot sound\\n gun_sounds = [\\\"throw1\\\", \\\"throw3\\\", \\\"throw4\\\", \\\"throw4\\\"]\\n random_sound = gun_sounds[random.randrange(0, 4)]\\n self.gun_sound = arcade.load_sound(str(Path(__file__).parent.resolve()) + f\\\"\\\\\\\\assets\\\\\\\\{random_sound}.wav\\\")\\n arcade.play_sound(self.gun_sound)\\n\\n # Create a player bullet randomly from the list of options\\n player_bullets = [\\\"frying_pan\\\", \\\"rolling_pin\\\", \\\"spoon\\\", \\\"knife\\\"]\\n random_bullet = player_bullets[random.randrange(0, 4)]\\n bullet_sprite_path = str(Path(__file__).parent.resolve()) + f\\\"\\\\\\\\assets\\\\\\\\{random_bullet}.png\\\"\\n bullet = arcade.Sprite(bullet_sprite_path, SPRITE_SCALING_LASER)\\n\\n # The image points to the right, and we want it to point up. So\\n # rotate it.\\n # Set up the initial angle, and the \\\"spin\\\"\\n bullet.angle = random.randrange(360)\\n bullet.change_angle = random.randrange(15, 16)\\n\\n\\n # Give the bullet a speed\\n bullet.change_y = BULLET_SPEED\\n\\n # Position the bullet\\n bullet.center_x = self.player_sprite.center_x\\n bullet.bottom = self.player_sprite.top\\n\\n # Add the bullet to the appropriate lists\\n self.player_bullet_list.append(bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c1a3d411737694c89bfda90119f3d221\",\n \"score\": \"0.4478823\",\n \"text\": \"def _get_group_icon_entries(self, num=0):\\n groupicon = self.groupiconres.directory.entries[num]\\n if groupicon.struct.DataIsDirectory:\\n # Select the first language from subfolders as needed.\\n groupicon = groupicon.directory.entries[0]\\n\\n # Read the data pointed to by the group icon directory (GRPICONDIR) struct.\\n rva = groupicon.data.struct.OffsetToData\\n size = groupicon.data.struct.Size\\n data = self._pe.get_data(rva, size)\\n file_offset = self._pe.get_offset_from_rva(rva)\\n\\n grp_icon_dir = self._pe.__unpack_data__(GRPICONDIR_FORMAT, data, file_offset)\\n # logger.debug(grp_icon_dir)\\n\\n if grp_icon_dir.Reserved:\\n raise InvalidIconDefinitionError(\\\"Invalid group icon definition (got Reserved=%s instead of 0)\\\" % hex(grp_icon_dir.Reserved))\\n\\n # For each group icon entry (GRPICONDIRENTRY) that immediately follows, read its data and save it.\\n grp_icons = []\\n icon_offset = grp_icon_dir.sizeof()\\n for idx in range(grp_icon_dir.Count):\\n grp_icon = self._pe.__unpack_data__(GRPICONDIRENTRY_FORMAT, data[icon_offset:], file_offset+icon_offset)\\n icon_offset += grp_icon.sizeof()\\n grp_icons.append(grp_icon)\\n # logger.debug(\\\"Got logical group icon %s\\\", grp_icon)\\n\\n return grp_icons\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2b9973149da558072cb0d3533d6c0d92\",\n \"score\": \"0.4469877\",\n \"text\": \"def fire_bullet(ai_settings, screen, ship, bullets):\\n #create a new bullet if limit not reached yet.\\n if len(bullets) < ai_settings.bullet_allowed:\\n new_bullet = Bullet(ai_settings, screen, ship)\\n bullets.add(new_bullet)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6b28e48909366e80064165f63540e562\",\n \"score\": \"0.4454238\",\n \"text\": \"def getSpriteSheet(cls, filename):\\n try:\\n return cls.spritesheets[filename]\\n except KeyError:\\n pass\\n\\n # La feuille de sprite n'était pas en mémoire, on va donc l'ajouter\\n spritesheet = SpriteSheet(filename)\\n cls.spritesheets[filename] = spritesheet\\n\\n # Et on la retourne\\n return spritesheet\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ff2828373c176f42f5a35971bf1c0aa8\",\n \"score\": \"0.44487923\",\n \"text\": \"def _update_bullets(self):\\n # Update bullet position.\\n # Below we will control to get rid of the bullets that have\\n # Dissapear.\\n self.bullets.update()\\n for bullet in self.bullets.copy():\\n if bullet.rect.bottom <= 0:\\n self.bullets.remove(bullet)\\n # print(len(self.bullets))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"468e8cc68c276656f2d2ab6a925d802d\",\n \"score\": \"0.44471857\",\n \"text\": \"def get_all_sprites(self):\\n all_sprites = self.maze.walls + self.maze.gates + \\\\\\n self.maze.items + self.maze.guardians\\n all_sprites.append(self.character)\\n\\n return all_sprites\",\n \"title\": \"\"\n },\n {\n \"docid\": \"38dc2c8f0f81a1ee121b28b7e7b9e2b8\",\n \"score\": \"0.44355947\",\n \"text\": \"def bulletslide(self,\\n title='Here goes the title of the slide',\\n bullets=[], # list of bullet points\\n dim=False, # dimming of bullet points\\n intro='',\\n outro='',\\n figure=None, # filename(s) with figure(s)\\n figure_pos='s', # north, east, south, west\\n figure_fraction_width=1.0,\\n figure_angle=0, # indicates rotation (90, 270)\\n bullet_block=True,\\n bullet_block_heading='',\\n intro_block = True,\\n intro_block_heading = '',\\n outro_block = True,\\n outro_block_heading = '',\\n left_column_width=0.5,\\n header_footer=None,\\n hide=False,\\n ):\\n content = []\\n if intro:\\n if intro_block:\\n if intro_block_heading:\\n intro = TextBlock(intro, heading=intro_block_heading)\\n else:\\n intro = TextBlock(intro)\\n else:\\n intro = Text(intro)\\n content.append(intro)\\n if bullets:\\n bulletblock = BulletBlock(bullets, heading=bullet_block_heading)\\n content.append(bulletblock)\\n if outro:\\n if outro_block:\\n if outro_block_heading:\\n outro = TextBlock(outro, heading=outro)\\n else:\\n outro = TextBlock(outro)\\n else:\\n outro = TextBlock(outro)\\n content.append(outro)\\n return latexslides.Slide(title=title, content=content, dim=dim,\\n figure=figure, figure_pos=figure_pos,\\n figure_size=figure_fraction_width,\\n figure_angle=figure_angle,\\n left_column_width=left_column_width,\\n hidden=hide)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"18d870d2aff29216aa0f976435ee4f35\",\n \"score\": \"0.4433096\",\n \"text\": \"def create_background_sprites(self, k):\\n\\n for y in range(0, (k * ROAD_IMAGE_RECT.height), ROAD_IMAGE_RECT.height):\\n self.background_tiles.add(Background_Sprite(0, y))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7689275140f4a67922e849a082ceec35\",\n \"score\": \"0.44326815\",\n \"text\": \"def r_group(self, name):\\r\\n return self.r_maps_groups().get(name)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8dda0edab3a2790bfebaaf3ba8198133\",\n \"score\": \"0.443171\",\n \"text\": \"def tile_list():\\n\\treturn [GrassTile, WaterTile, RockTile]\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":382,"cells":{"query_id":{"kind":"string","value":"9b1add6e10b15c71fe389d9b7764923e"},"query":{"kind":"string","value":"Whether node to node encryption is enabled."},"positive_passages":{"kind":"list like","value":[{"docid":"8b7f9b5071a1577ec845863ad1fdb178","score":"0.57095563","text":"def enabled(self) -> bool:\n return pulumi.get(self, \"enabled\")","title":""}],"string":"[\n {\n \"docid\": \"8b7f9b5071a1577ec845863ad1fdb178\",\n \"score\": \"0.57095563\",\n \"text\": \"def enabled(self) -> bool:\\n return pulumi.get(self, \\\"enabled\\\")\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"3fbe407ec13d3ca2f66c52dec688511e","score":"0.72343796","text":"def encryption_at_host_enabled(self) -> pulumi.Output[Optional[bool]]:\n return pulumi.get(self, \"encryption_at_host_enabled\")","title":""},{"docid":"87e151fc000a0308a51f52aafeee4a4e","score":"0.72056943","text":"def encryption_at_host_enabled(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"encryption_at_host_enabled\")","title":""},{"docid":"87e151fc000a0308a51f52aafeee4a4e","score":"0.72056943","text":"def encryption_at_host_enabled(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"encryption_at_host_enabled\")","title":""},{"docid":"e7bf5a0bba541079fa0d4e384f0097a6","score":"0.69992346","text":"def is_encrypted(self):\n return True","title":""},{"docid":"558056a25e4399eed971031660c498bd","score":"0.6929175","text":"def is_encrypted(self):\n return False","title":""},{"docid":"558056a25e4399eed971031660c498bd","score":"0.6929175","text":"def is_encrypted(self):\n return False","title":""},{"docid":"f027121bf255676a98dc4cb0fdbff744","score":"0.6759366","text":"def encrypted(self) -> bool:\n return pulumi.get(self, \"encrypted\")","title":""},{"docid":"f027121bf255676a98dc4cb0fdbff744","score":"0.6759366","text":"def encrypted(self) -> bool:\n return pulumi.get(self, \"encrypted\")","title":""},{"docid":"f027121bf255676a98dc4cb0fdbff744","score":"0.6759366","text":"def encrypted(self) -> bool:\n return pulumi.get(self, \"encrypted\")","title":""},{"docid":"f027121bf255676a98dc4cb0fdbff744","score":"0.6759366","text":"def encrypted(self) -> bool:\n return pulumi.get(self, \"encrypted\")","title":""},{"docid":"f027121bf255676a98dc4cb0fdbff744","score":"0.6759366","text":"def encrypted(self) -> bool:\n return pulumi.get(self, \"encrypted\")","title":""},{"docid":"f027121bf255676a98dc4cb0fdbff744","score":"0.6759366","text":"def encrypted(self) -> bool:\n return pulumi.get(self, \"encrypted\")","title":""},{"docid":"f027121bf255676a98dc4cb0fdbff744","score":"0.6759366","text":"def encrypted(self) -> bool:\n return pulumi.get(self, \"encrypted\")","title":""},{"docid":"bd77dd6301189b6715f1137edffce600","score":"0.67175406","text":"def data_node_disk_encrypted(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"data_node_disk_encrypted\")","title":""},{"docid":"bd77dd6301189b6715f1137edffce600","score":"0.67175406","text":"def data_node_disk_encrypted(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"data_node_disk_encrypted\")","title":""},{"docid":"6f0ee646334793784a15ce7a7c07d4c2","score":"0.65968424","text":"def get_enable_encryption_at_host(self) -> bool:\n # read the original value passed by the command\n enable_encryption_at_host = self.raw_param.get(\"enable_encryption_at_host\", False)\n # try to read the property value corresponding to the parameter from the `agentpool` object\n if (\n self.agentpool and\n hasattr(self.agentpool, \"enable_encryption_at_host\") and # backward compatibility\n self.agentpool.enable_encryption_at_host is not None\n ):\n enable_encryption_at_host = self.agentpool.enable_encryption_at_host\n\n # this parameter does not need dynamic completion\n # this parameter does not need validation\n return enable_encryption_at_host","title":""},{"docid":"3e1b6381e0f05ed9cc306baefd716988","score":"0.6583299","text":"def data_node_disk_encrypted(self) -> pulumi.Output[Optional[bool]]:\n return pulumi.get(self, \"data_node_disk_encrypted\")","title":""},{"docid":"5a53ea69b12b77cd3f4513c86f5260b1","score":"0.65536994","text":"def get_security_key_manager_nve_support(self, node):\n api_args = {'node': node}\n try:\n result = self.send_request(\n 'security-key-manager-volume-encryption-supported', api_args)\n vol_encryption_supported = result.get_child_content(\n 'vol-encryption-supported') or 'false'\n except netapp_api.NaApiError as e:\n LOG.debug(\"NVE disabled due to error code: %s - %s\",\n e.code, e.message)\n return False\n\n return strutils.bool_from_string(vol_encryption_supported)","title":""},{"docid":"e960fa63a98b8fc9cdacbc0d29307168","score":"0.6504919","text":"def is_encrypted(self) -> Optional[bool]:\n return pulumi.get(self, \"is_encrypted\")","title":""},{"docid":"41cbce4ead5a5bb43be0126023e45cda","score":"0.6412266","text":"def is_encrypted(self):\n if \"isEncrypted\" in self._prop_dict:\n return self._prop_dict[\"isEncrypted\"]\n else:\n return None","title":""},{"docid":"136a05d4bc973f9b0b823c4aa2075f13","score":"0.63555044","text":"def enable_inter_container_traffic_encryption(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_inter_container_traffic_encryption\")","title":""},{"docid":"136a05d4bc973f9b0b823c4aa2075f13","score":"0.63555044","text":"def enable_inter_container_traffic_encryption(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_inter_container_traffic_encryption\")","title":""},{"docid":"136a05d4bc973f9b0b823c4aa2075f13","score":"0.63555044","text":"def enable_inter_container_traffic_encryption(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_inter_container_traffic_encryption\")","title":""},{"docid":"136a05d4bc973f9b0b823c4aa2075f13","score":"0.63555044","text":"def enable_inter_container_traffic_encryption(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_inter_container_traffic_encryption\")","title":""},{"docid":"136a05d4bc973f9b0b823c4aa2075f13","score":"0.63555044","text":"def enable_inter_container_traffic_encryption(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_inter_container_traffic_encryption\")","title":""},{"docid":"5cd0b8f345d49b71526d222f799230fc","score":"0.6334567","text":"def require_infrastructure_encryption(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"require_infrastructure_encryption\")","title":""},{"docid":"38cb1e60596f682ddb556d27d496f584","score":"0.6291327","text":"def return_connection_password_encrypted(self) -> bool:\n return pulumi.get(self, \"return_connection_password_encrypted\")","title":""},{"docid":"38cb1e60596f682ddb556d27d496f584","score":"0.6291327","text":"def return_connection_password_encrypted(self) -> bool:\n return pulumi.get(self, \"return_connection_password_encrypted\")","title":""},{"docid":"52c5020d3ce9120ce176ba26f8602a12","score":"0.62867194","text":"def is_default_encrypted(self):\n return self.container['is_default_encrypted']","title":""},{"docid":"a32881ce716b670b741988a69882ca59","score":"0.62780434","text":"def storage_encrypted(self) -> bool:\n return pulumi.get(self, \"storage_encrypted\")","title":""},{"docid":"2d1c8aebffb1f9d53a4f7ebbb9a9bac5","score":"0.6211994","text":"def encryption_needed(self):\n\t\treturn ISC_REQ.CONFIDENTIALITY in self.flags","title":""},{"docid":"40bde7a6f545011189ed7b45e02db391","score":"0.6198789","text":"def encrypted(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"encrypted\")","title":""},{"docid":"b813116d31eba0a6caa507c9646cadb5","score":"0.6118295","text":"def _tx_enable(self):\n return bool(self._get_iio_dev_attr(\"tx_en\", self._ctrl))","title":""},{"docid":"5d5031b7c95007b16c4e9f3ba3b4c136","score":"0.6021948","text":"def tx_vm_enable(self):\n return bool(self._get_iio_dev_attr(\"tx_vm_enable\", self._ctrl))","title":""},{"docid":"81e3ecb440b23fb7579b56720fc9a531","score":"0.5994821","text":"def on_enabled(self, node_address):\n # pylint: disable=no-self-use\n return False","title":""},{"docid":"bc8220d316cd1d864edafffd5adf1543","score":"0.5970832","text":"def encrypt_root_block_device(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"encrypt_root_block_device\")","title":""},{"docid":"549f7648a673e8865da6c51c3bbfcf11","score":"0.58906674","text":"def enabled(self) -> ConfigNodePropertyBoolean:\n return self._enabled","title":""},{"docid":"fbdace2b8c3eb7f8ec205dcfbae1979a","score":"0.58827895","text":"def enable_vtpm(self) -> bool:\n return pulumi.get(self, \"enable_vtpm\")","title":""},{"docid":"21d8bfa7c2efaccd8b4c3e62094ef1ec","score":"0.58779424","text":"def enable_passivemode(self) -> pulumi.Output[Optional[bool]]:\n return pulumi.get(self, \"enable_passivemode\")","title":""},{"docid":"9cc01d29c8197ef41724509ed82e49db","score":"0.5809031","text":"def enabled(cls):\n return cls.connect_api_key and cls.secret_key","title":""},{"docid":"2597f0addf893227c4fe4aa056f5d6b7","score":"0.5794412","text":"def disable_app_encryption_if_device_encryption_is_enabled(self):\n if \"disableAppEncryptionIfDeviceEncryptionIsEnabled\" in self._prop_dict:\n return self._prop_dict[\"disableAppEncryptionIfDeviceEncryptionIsEnabled\"]\n else:\n return None","title":""},{"docid":"c9fbcf8dc891b346e64320f0e8ae6503","score":"0.5774297","text":"def protect_external_id(self) -> ConfigNodePropertyBoolean:\n return self._protect_external_id","title":""},{"docid":"d5c58d560e23cdc415bc92e281cda222","score":"0.5749571","text":"def eas_enable(self) -> pulumi.Output[Optional[bool]]:\n return pulumi.get(self, \"eas_enable\")","title":""},{"docid":"5fcd166a1e04624b135be41d7d08adae","score":"0.57307905","text":"def is_enabled(self):\r\n return True","title":""},{"docid":"4a1627254ac379b86364edeb3534de21","score":"0.57281464","text":"def get_is_enabled(self):\n return False","title":""},{"docid":"d013bcfa4104b376a2ec9f6ea8b0f366","score":"0.5714363","text":"def is_enabled(self) -> bool:\n return self.properties.get('enabled', False)","title":""},{"docid":"7e73275e972c2988c5effab4b5c256dd","score":"0.57100356","text":"def tx_pa_enable(self):\n return bool(self._get_iio_dev_attr(\"tx_drv_enable\", self._ctrl))","title":""},{"docid":"d749c635fca3403a3b4bcd934481d344","score":"0.5697388","text":"def IsEncrypted(self):\n if self.version == 1:\n return self._details['IsEncrypted']\n else:\n return self._details['vault']['encrypted']","title":""},{"docid":"8af91981e85ef91764f8297a36417b3f","score":"0.569568","text":"def enable_network_isolation(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_network_isolation\")","title":""},{"docid":"8af91981e85ef91764f8297a36417b3f","score":"0.569568","text":"def enable_network_isolation(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_network_isolation\")","title":""},{"docid":"8af91981e85ef91764f8297a36417b3f","score":"0.569568","text":"def enable_network_isolation(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_network_isolation\")","title":""},{"docid":"8af91981e85ef91764f8297a36417b3f","score":"0.569568","text":"def enable_network_isolation(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_network_isolation\")","title":""},{"docid":"8af91981e85ef91764f8297a36417b3f","score":"0.569568","text":"def enable_network_isolation(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_network_isolation\")","title":""},{"docid":"8838b04a0700093974bb33a247290efc","score":"0.56901956","text":"def enable_passivemode(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_passivemode\")","title":""},{"docid":"8838b04a0700093974bb33a247290efc","score":"0.56901956","text":"def enable_passivemode(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_passivemode\")","title":""},{"docid":"0757fddf3d7996484cb6012cd564683b","score":"0.5673478","text":"def get_secure_bool(cls, key):\n return False","title":""},{"docid":"46facffb9ac04d83f8bf343500ce78e2","score":"0.5667529","text":"def tx_vga_enable(self):\n return bool(self._get_iio_dev_attr(\"tx_vga_enable\", self._ctrl))","title":""},{"docid":"9800b65b9c5d7ce2263bd9584aac575b","score":"0.56520045","text":"def node_override_enabled(node):\n\n raise NotImplementedError()","title":""},{"docid":"dc7ab58f24c7a0607e90db39a94cac72","score":"0.56506175","text":"def encryption_mode(self) -> pulumi.Output[Optional[str]]:\n return pulumi.get(self, \"encryption_mode\")","title":""},{"docid":"4901a5bb46491d8bd1dc6f64703d98cb","score":"0.56451625","text":"def is_enabled(self):\n return False","title":""},{"docid":"4901a5bb46491d8bd1dc6f64703d98cb","score":"0.56451625","text":"def is_enabled(self):\n return False","title":""},{"docid":"9f9569b359400fd7d9e303f3ccf63317","score":"0.56451625","text":"def enabled(cls):\n if cls.ipmicap_ip != None:\n return True\n else:\n return False","title":""},{"docid":"65ca8668509609b140b76e78e75aae8a","score":"0.5640848","text":"def on_enabled(self, node_address):\n self._enable_node(node_address)\n return True","title":""},{"docid":"200a55007d787f95c5f91cfbad69de4f","score":"0.5640331","text":"def encryption_mode(self):\n return self._encryption_mode","title":""},{"docid":"aa5416637c18eb087a9a22b7bb1587b2","score":"0.56334734","text":"def require_infrastructure_encryption(self) -> Optional['outputs.WorkspaceCustomBooleanParameterResponse']:\n return pulumi.get(self, \"require_infrastructure_encryption\")","title":""},{"docid":"11e611c6a36ce10b8dbf7a792a13bd53","score":"0.5628905","text":"def enable(self) -> Optional[bool]:\n return pulumi.get(self, \"enable\")","title":""},{"docid":"c44a7a128204ac3360ae4af46cf8150a","score":"0.56287897","text":"def enabled(cls):\n return True","title":""},{"docid":"66d8af3bdbe51fa6ecbd031b9b540820","score":"0.5622277","text":"def vtpm_enabled(self) -> pulumi.Output[Optional[bool]]:\n return pulumi.get(self, \"vtpm_enabled\")","title":""},{"docid":"0c0ed1ec99ecab1ca75ec0548d4e7f07","score":"0.56167656","text":"def prepare_encryption(self) -> Optional['outputs.WorkspaceCustomBooleanParameterResponse']:\n return pulumi.get(self, \"prepare_encryption\")","title":""},{"docid":"c0de7d3fa6f654c81f75489794042090","score":"0.55842865","text":"def is_enabled(cls):\n return False","title":""},{"docid":"d7e7d23e288adacacfb651fa7e78ca58","score":"0.5580329","text":"def isNodeModel(self) -> bool:\n if self is AttackMode.EDGE:\n return False\n return True","title":""},{"docid":"e20d414784d0207334cf988bf2090250","score":"0.55722606","text":"def enable_xml(self) -> ConfigNodePropertyBoolean:\n return self._enable_xml","title":""},{"docid":"95804346c908bcb111b2b9494a82dd74","score":"0.55621606","text":"def is_enabled(self) -> bool:\n return pulumi.get(self, \"is_enabled\")","title":""},{"docid":"9158e67f75f16e47c7dcffca8935a3c6","score":"0.556087","text":"def is_enabled(self):\r\n return False","title":""},{"docid":"c4521e51ca2b7b6a56010764e412e7e5","score":"0.5555338","text":"def is_enabled(self, key):\n return key in self and self[key].enabled","title":""},{"docid":"7f6d65e403e8e69c204b04b9906b4a8d","score":"0.5554758","text":"def enabled(self) -> pulumi.Output[bool]:\n return pulumi.get(self, \"enabled\")","title":""},{"docid":"7f6d65e403e8e69c204b04b9906b4a8d","score":"0.5554758","text":"def enabled(self) -> pulumi.Output[bool]:\n return pulumi.get(self, \"enabled\")","title":""},{"docid":"948f8da864ad4a096e6f875232fcfab5","score":"0.5548992","text":"def is_enabled(self) -> bool:\n return self._redis_connection is not None","title":""},{"docid":"df7d5456caaabcac24d0fc23919880b1","score":"0.55483466","text":"def eas_enable(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"eas_enable\")","title":""},{"docid":"df7d5456caaabcac24d0fc23919880b1","score":"0.55483466","text":"def eas_enable(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"eas_enable\")","title":""},{"docid":"5e05928edec7900ef6284bef71caf1be","score":"0.55150837","text":"def vtpm_enabled(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"vtpm_enabled\")","title":""},{"docid":"5e05928edec7900ef6284bef71caf1be","score":"0.55150837","text":"def vtpm_enabled(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"vtpm_enabled\")","title":""},{"docid":"9124042b38276986cd4f47da93a5ce35","score":"0.54987264","text":"def _get_secure_session_enable(self):\n return self.__secure_session_enable","title":""},{"docid":"ee2c717cff280c4af3b483f38a129c46","score":"0.54901534","text":"def enabled(cls):\n return bool(\n setting(cls.SETTINGS_KEY_NAME) and setting(cls.SETTINGS_SECRET_NAME)\n )","title":""},{"docid":"dd644fa31fc45fd27de5cb35cebd35e1","score":"0.5473464","text":"def enable_txt(self) -> ConfigNodePropertyBoolean:\n return self._enable_txt","title":""},{"docid":"7232994f6b2a92922c96d48fb9867592","score":"0.5442348","text":"def enable_vtpm(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"enable_vtpm\")","title":""},{"docid":"7f8e6b1f71d920fc0350565ca7293c97","score":"0.54363567","text":"def enabled(self) -> bool:\n raise NotImplementedError()","title":""},{"docid":"313657514565519f13f28298785bc3c2","score":"0.5435427","text":"def __synchronize_encryption(self, mode='train'):\n # Send if this host use encryption or not\n use_encryption_id = self.transfer_variable.generate_transferid(\n self.transfer_variable.use_encrypt, mode\n )\n LOGGER.debug(\"Start to remote use_encrypt: {}, transfer_id: {}\".format(self.use_encrypt, use_encryption_id))\n\n federation.remote(self.use_encrypt,\n name=self.transfer_variable.use_encrypt.name,\n tag=use_encryption_id,\n role=consts.ARBITER,\n idx=0)\n\n # Set public key\n if self.use_encrypt:\n pubkey_id = self.transfer_variable.generate_transferid(self.transfer_variable.paillier_pubkey, mode)\n pubkey = federation.get(name=self.transfer_variable.paillier_pubkey.name,\n tag=pubkey_id,\n idx=0)\n LOGGER.debug(\"Received pubkey\")\n self.encrypt_operator.set_public_key(pubkey)\n LOGGER.info(\"Finish synchronized ecryption\")\n self.has_sychronized_encryption = True","title":""}],"string":"[\n {\n \"docid\": \"3fbe407ec13d3ca2f66c52dec688511e\",\n \"score\": \"0.72343796\",\n \"text\": \"def encryption_at_host_enabled(self) -> pulumi.Output[Optional[bool]]:\\n return pulumi.get(self, \\\"encryption_at_host_enabled\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"87e151fc000a0308a51f52aafeee4a4e\",\n \"score\": \"0.72056943\",\n \"text\": \"def encryption_at_host_enabled(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"encryption_at_host_enabled\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"87e151fc000a0308a51f52aafeee4a4e\",\n \"score\": \"0.72056943\",\n \"text\": \"def encryption_at_host_enabled(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"encryption_at_host_enabled\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e7bf5a0bba541079fa0d4e384f0097a6\",\n \"score\": \"0.69992346\",\n \"text\": \"def is_encrypted(self):\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"558056a25e4399eed971031660c498bd\",\n \"score\": \"0.6929175\",\n \"text\": \"def is_encrypted(self):\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"558056a25e4399eed971031660c498bd\",\n \"score\": \"0.6929175\",\n \"text\": \"def is_encrypted(self):\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f027121bf255676a98dc4cb0fdbff744\",\n \"score\": \"0.6759366\",\n \"text\": \"def encrypted(self) -> bool:\\n return pulumi.get(self, \\\"encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f027121bf255676a98dc4cb0fdbff744\",\n \"score\": \"0.6759366\",\n \"text\": \"def encrypted(self) -> bool:\\n return pulumi.get(self, \\\"encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f027121bf255676a98dc4cb0fdbff744\",\n \"score\": \"0.6759366\",\n \"text\": \"def encrypted(self) -> bool:\\n return pulumi.get(self, \\\"encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f027121bf255676a98dc4cb0fdbff744\",\n \"score\": \"0.6759366\",\n \"text\": \"def encrypted(self) -> bool:\\n return pulumi.get(self, \\\"encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f027121bf255676a98dc4cb0fdbff744\",\n \"score\": \"0.6759366\",\n \"text\": \"def encrypted(self) -> bool:\\n return pulumi.get(self, \\\"encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f027121bf255676a98dc4cb0fdbff744\",\n \"score\": \"0.6759366\",\n \"text\": \"def encrypted(self) -> bool:\\n return pulumi.get(self, \\\"encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f027121bf255676a98dc4cb0fdbff744\",\n \"score\": \"0.6759366\",\n \"text\": \"def encrypted(self) -> bool:\\n return pulumi.get(self, \\\"encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bd77dd6301189b6715f1137edffce600\",\n \"score\": \"0.67175406\",\n \"text\": \"def data_node_disk_encrypted(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"data_node_disk_encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bd77dd6301189b6715f1137edffce600\",\n \"score\": \"0.67175406\",\n \"text\": \"def data_node_disk_encrypted(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"data_node_disk_encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6f0ee646334793784a15ce7a7c07d4c2\",\n \"score\": \"0.65968424\",\n \"text\": \"def get_enable_encryption_at_host(self) -> bool:\\n # read the original value passed by the command\\n enable_encryption_at_host = self.raw_param.get(\\\"enable_encryption_at_host\\\", False)\\n # try to read the property value corresponding to the parameter from the `agentpool` object\\n if (\\n self.agentpool and\\n hasattr(self.agentpool, \\\"enable_encryption_at_host\\\") and # backward compatibility\\n self.agentpool.enable_encryption_at_host is not None\\n ):\\n enable_encryption_at_host = self.agentpool.enable_encryption_at_host\\n\\n # this parameter does not need dynamic completion\\n # this parameter does not need validation\\n return enable_encryption_at_host\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3e1b6381e0f05ed9cc306baefd716988\",\n \"score\": \"0.6583299\",\n \"text\": \"def data_node_disk_encrypted(self) -> pulumi.Output[Optional[bool]]:\\n return pulumi.get(self, \\\"data_node_disk_encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5a53ea69b12b77cd3f4513c86f5260b1\",\n \"score\": \"0.65536994\",\n \"text\": \"def get_security_key_manager_nve_support(self, node):\\n api_args = {'node': node}\\n try:\\n result = self.send_request(\\n 'security-key-manager-volume-encryption-supported', api_args)\\n vol_encryption_supported = result.get_child_content(\\n 'vol-encryption-supported') or 'false'\\n except netapp_api.NaApiError as e:\\n LOG.debug(\\\"NVE disabled due to error code: %s - %s\\\",\\n e.code, e.message)\\n return False\\n\\n return strutils.bool_from_string(vol_encryption_supported)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e960fa63a98b8fc9cdacbc0d29307168\",\n \"score\": \"0.6504919\",\n \"text\": \"def is_encrypted(self) -> Optional[bool]:\\n return pulumi.get(self, \\\"is_encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"41cbce4ead5a5bb43be0126023e45cda\",\n \"score\": \"0.6412266\",\n \"text\": \"def is_encrypted(self):\\n if \\\"isEncrypted\\\" in self._prop_dict:\\n return self._prop_dict[\\\"isEncrypted\\\"]\\n else:\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"136a05d4bc973f9b0b823c4aa2075f13\",\n \"score\": \"0.63555044\",\n \"text\": \"def enable_inter_container_traffic_encryption(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_inter_container_traffic_encryption\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"136a05d4bc973f9b0b823c4aa2075f13\",\n \"score\": \"0.63555044\",\n \"text\": \"def enable_inter_container_traffic_encryption(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_inter_container_traffic_encryption\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"136a05d4bc973f9b0b823c4aa2075f13\",\n \"score\": \"0.63555044\",\n \"text\": \"def enable_inter_container_traffic_encryption(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_inter_container_traffic_encryption\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"136a05d4bc973f9b0b823c4aa2075f13\",\n \"score\": \"0.63555044\",\n \"text\": \"def enable_inter_container_traffic_encryption(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_inter_container_traffic_encryption\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"136a05d4bc973f9b0b823c4aa2075f13\",\n \"score\": \"0.63555044\",\n \"text\": \"def enable_inter_container_traffic_encryption(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_inter_container_traffic_encryption\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5cd0b8f345d49b71526d222f799230fc\",\n \"score\": \"0.6334567\",\n \"text\": \"def require_infrastructure_encryption(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"require_infrastructure_encryption\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"38cb1e60596f682ddb556d27d496f584\",\n \"score\": \"0.6291327\",\n \"text\": \"def return_connection_password_encrypted(self) -> bool:\\n return pulumi.get(self, \\\"return_connection_password_encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"38cb1e60596f682ddb556d27d496f584\",\n \"score\": \"0.6291327\",\n \"text\": \"def return_connection_password_encrypted(self) -> bool:\\n return pulumi.get(self, \\\"return_connection_password_encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"52c5020d3ce9120ce176ba26f8602a12\",\n \"score\": \"0.62867194\",\n \"text\": \"def is_default_encrypted(self):\\n return self.container['is_default_encrypted']\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a32881ce716b670b741988a69882ca59\",\n \"score\": \"0.62780434\",\n \"text\": \"def storage_encrypted(self) -> bool:\\n return pulumi.get(self, \\\"storage_encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2d1c8aebffb1f9d53a4f7ebbb9a9bac5\",\n \"score\": \"0.6211994\",\n \"text\": \"def encryption_needed(self):\\n\\t\\treturn ISC_REQ.CONFIDENTIALITY in self.flags\",\n \"title\": \"\"\n },\n {\n \"docid\": \"40bde7a6f545011189ed7b45e02db391\",\n \"score\": \"0.6198789\",\n \"text\": \"def encrypted(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"encrypted\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b813116d31eba0a6caa507c9646cadb5\",\n \"score\": \"0.6118295\",\n \"text\": \"def _tx_enable(self):\\n return bool(self._get_iio_dev_attr(\\\"tx_en\\\", self._ctrl))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5d5031b7c95007b16c4e9f3ba3b4c136\",\n \"score\": \"0.6021948\",\n \"text\": \"def tx_vm_enable(self):\\n return bool(self._get_iio_dev_attr(\\\"tx_vm_enable\\\", self._ctrl))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"81e3ecb440b23fb7579b56720fc9a531\",\n \"score\": \"0.5994821\",\n \"text\": \"def on_enabled(self, node_address):\\n # pylint: disable=no-self-use\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc8220d316cd1d864edafffd5adf1543\",\n \"score\": \"0.5970832\",\n \"text\": \"def encrypt_root_block_device(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"encrypt_root_block_device\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"549f7648a673e8865da6c51c3bbfcf11\",\n \"score\": \"0.58906674\",\n \"text\": \"def enabled(self) -> ConfigNodePropertyBoolean:\\n return self._enabled\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fbdace2b8c3eb7f8ec205dcfbae1979a\",\n \"score\": \"0.58827895\",\n \"text\": \"def enable_vtpm(self) -> bool:\\n return pulumi.get(self, \\\"enable_vtpm\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"21d8bfa7c2efaccd8b4c3e62094ef1ec\",\n \"score\": \"0.58779424\",\n \"text\": \"def enable_passivemode(self) -> pulumi.Output[Optional[bool]]:\\n return pulumi.get(self, \\\"enable_passivemode\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9cc01d29c8197ef41724509ed82e49db\",\n \"score\": \"0.5809031\",\n \"text\": \"def enabled(cls):\\n return cls.connect_api_key and cls.secret_key\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2597f0addf893227c4fe4aa056f5d6b7\",\n \"score\": \"0.5794412\",\n \"text\": \"def disable_app_encryption_if_device_encryption_is_enabled(self):\\n if \\\"disableAppEncryptionIfDeviceEncryptionIsEnabled\\\" in self._prop_dict:\\n return self._prop_dict[\\\"disableAppEncryptionIfDeviceEncryptionIsEnabled\\\"]\\n else:\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c9fbcf8dc891b346e64320f0e8ae6503\",\n \"score\": \"0.5774297\",\n \"text\": \"def protect_external_id(self) -> ConfigNodePropertyBoolean:\\n return self._protect_external_id\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d5c58d560e23cdc415bc92e281cda222\",\n \"score\": \"0.5749571\",\n \"text\": \"def eas_enable(self) -> pulumi.Output[Optional[bool]]:\\n return pulumi.get(self, \\\"eas_enable\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5fcd166a1e04624b135be41d7d08adae\",\n \"score\": \"0.57307905\",\n \"text\": \"def is_enabled(self):\\r\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4a1627254ac379b86364edeb3534de21\",\n \"score\": \"0.57281464\",\n \"text\": \"def get_is_enabled(self):\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d013bcfa4104b376a2ec9f6ea8b0f366\",\n \"score\": \"0.5714363\",\n \"text\": \"def is_enabled(self) -> bool:\\n return self.properties.get('enabled', False)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7e73275e972c2988c5effab4b5c256dd\",\n \"score\": \"0.57100356\",\n \"text\": \"def tx_pa_enable(self):\\n return bool(self._get_iio_dev_attr(\\\"tx_drv_enable\\\", self._ctrl))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d749c635fca3403a3b4bcd934481d344\",\n \"score\": \"0.5697388\",\n \"text\": \"def IsEncrypted(self):\\n if self.version == 1:\\n return self._details['IsEncrypted']\\n else:\\n return self._details['vault']['encrypted']\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8af91981e85ef91764f8297a36417b3f\",\n \"score\": \"0.569568\",\n \"text\": \"def enable_network_isolation(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_network_isolation\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8af91981e85ef91764f8297a36417b3f\",\n \"score\": \"0.569568\",\n \"text\": \"def enable_network_isolation(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_network_isolation\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8af91981e85ef91764f8297a36417b3f\",\n \"score\": \"0.569568\",\n \"text\": \"def enable_network_isolation(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_network_isolation\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8af91981e85ef91764f8297a36417b3f\",\n \"score\": \"0.569568\",\n \"text\": \"def enable_network_isolation(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_network_isolation\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8af91981e85ef91764f8297a36417b3f\",\n \"score\": \"0.569568\",\n \"text\": \"def enable_network_isolation(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_network_isolation\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8838b04a0700093974bb33a247290efc\",\n \"score\": \"0.56901956\",\n \"text\": \"def enable_passivemode(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_passivemode\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8838b04a0700093974bb33a247290efc\",\n \"score\": \"0.56901956\",\n \"text\": \"def enable_passivemode(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_passivemode\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0757fddf3d7996484cb6012cd564683b\",\n \"score\": \"0.5673478\",\n \"text\": \"def get_secure_bool(cls, key):\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"46facffb9ac04d83f8bf343500ce78e2\",\n \"score\": \"0.5667529\",\n \"text\": \"def tx_vga_enable(self):\\n return bool(self._get_iio_dev_attr(\\\"tx_vga_enable\\\", self._ctrl))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9800b65b9c5d7ce2263bd9584aac575b\",\n \"score\": \"0.56520045\",\n \"text\": \"def node_override_enabled(node):\\n\\n raise NotImplementedError()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dc7ab58f24c7a0607e90db39a94cac72\",\n \"score\": \"0.56506175\",\n \"text\": \"def encryption_mode(self) -> pulumi.Output[Optional[str]]:\\n return pulumi.get(self, \\\"encryption_mode\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4901a5bb46491d8bd1dc6f64703d98cb\",\n \"score\": \"0.56451625\",\n \"text\": \"def is_enabled(self):\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4901a5bb46491d8bd1dc6f64703d98cb\",\n \"score\": \"0.56451625\",\n \"text\": \"def is_enabled(self):\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9f9569b359400fd7d9e303f3ccf63317\",\n \"score\": \"0.56451625\",\n \"text\": \"def enabled(cls):\\n if cls.ipmicap_ip != None:\\n return True\\n else:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"65ca8668509609b140b76e78e75aae8a\",\n \"score\": \"0.5640848\",\n \"text\": \"def on_enabled(self, node_address):\\n self._enable_node(node_address)\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"200a55007d787f95c5f91cfbad69de4f\",\n \"score\": \"0.5640331\",\n \"text\": \"def encryption_mode(self):\\n return self._encryption_mode\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aa5416637c18eb087a9a22b7bb1587b2\",\n \"score\": \"0.56334734\",\n \"text\": \"def require_infrastructure_encryption(self) -> Optional['outputs.WorkspaceCustomBooleanParameterResponse']:\\n return pulumi.get(self, \\\"require_infrastructure_encryption\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"11e611c6a36ce10b8dbf7a792a13bd53\",\n \"score\": \"0.5628905\",\n \"text\": \"def enable(self) -> Optional[bool]:\\n return pulumi.get(self, \\\"enable\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c44a7a128204ac3360ae4af46cf8150a\",\n \"score\": \"0.56287897\",\n \"text\": \"def enabled(cls):\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"66d8af3bdbe51fa6ecbd031b9b540820\",\n \"score\": \"0.5622277\",\n \"text\": \"def vtpm_enabled(self) -> pulumi.Output[Optional[bool]]:\\n return pulumi.get(self, \\\"vtpm_enabled\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0c0ed1ec99ecab1ca75ec0548d4e7f07\",\n \"score\": \"0.56167656\",\n \"text\": \"def prepare_encryption(self) -> Optional['outputs.WorkspaceCustomBooleanParameterResponse']:\\n return pulumi.get(self, \\\"prepare_encryption\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c0de7d3fa6f654c81f75489794042090\",\n \"score\": \"0.55842865\",\n \"text\": \"def is_enabled(cls):\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d7e7d23e288adacacfb651fa7e78ca58\",\n \"score\": \"0.5580329\",\n \"text\": \"def isNodeModel(self) -> bool:\\n if self is AttackMode.EDGE:\\n return False\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e20d414784d0207334cf988bf2090250\",\n \"score\": \"0.55722606\",\n \"text\": \"def enable_xml(self) -> ConfigNodePropertyBoolean:\\n return self._enable_xml\",\n \"title\": \"\"\n },\n {\n \"docid\": \"95804346c908bcb111b2b9494a82dd74\",\n \"score\": \"0.55621606\",\n \"text\": \"def is_enabled(self) -> bool:\\n return pulumi.get(self, \\\"is_enabled\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9158e67f75f16e47c7dcffca8935a3c6\",\n \"score\": \"0.556087\",\n \"text\": \"def is_enabled(self):\\r\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c4521e51ca2b7b6a56010764e412e7e5\",\n \"score\": \"0.5555338\",\n \"text\": \"def is_enabled(self, key):\\n return key in self and self[key].enabled\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7f6d65e403e8e69c204b04b9906b4a8d\",\n \"score\": \"0.5554758\",\n \"text\": \"def enabled(self) -> pulumi.Output[bool]:\\n return pulumi.get(self, \\\"enabled\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7f6d65e403e8e69c204b04b9906b4a8d\",\n \"score\": \"0.5554758\",\n \"text\": \"def enabled(self) -> pulumi.Output[bool]:\\n return pulumi.get(self, \\\"enabled\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"948f8da864ad4a096e6f875232fcfab5\",\n \"score\": \"0.5548992\",\n \"text\": \"def is_enabled(self) -> bool:\\n return self._redis_connection is not None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"df7d5456caaabcac24d0fc23919880b1\",\n \"score\": \"0.55483466\",\n \"text\": \"def eas_enable(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"eas_enable\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"df7d5456caaabcac24d0fc23919880b1\",\n \"score\": \"0.55483466\",\n \"text\": \"def eas_enable(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"eas_enable\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5e05928edec7900ef6284bef71caf1be\",\n \"score\": \"0.55150837\",\n \"text\": \"def vtpm_enabled(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"vtpm_enabled\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5e05928edec7900ef6284bef71caf1be\",\n \"score\": \"0.55150837\",\n \"text\": \"def vtpm_enabled(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"vtpm_enabled\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9124042b38276986cd4f47da93a5ce35\",\n \"score\": \"0.54987264\",\n \"text\": \"def _get_secure_session_enable(self):\\n return self.__secure_session_enable\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ee2c717cff280c4af3b483f38a129c46\",\n \"score\": \"0.54901534\",\n \"text\": \"def enabled(cls):\\n return bool(\\n setting(cls.SETTINGS_KEY_NAME) and setting(cls.SETTINGS_SECRET_NAME)\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dd644fa31fc45fd27de5cb35cebd35e1\",\n \"score\": \"0.5473464\",\n \"text\": \"def enable_txt(self) -> ConfigNodePropertyBoolean:\\n return self._enable_txt\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7232994f6b2a92922c96d48fb9867592\",\n \"score\": \"0.5442348\",\n \"text\": \"def enable_vtpm(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"enable_vtpm\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7f8e6b1f71d920fc0350565ca7293c97\",\n \"score\": \"0.54363567\",\n \"text\": \"def enabled(self) -> bool:\\n raise NotImplementedError()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"313657514565519f13f28298785bc3c2\",\n \"score\": \"0.5435427\",\n \"text\": \"def __synchronize_encryption(self, mode='train'):\\n # Send if this host use encryption or not\\n use_encryption_id = self.transfer_variable.generate_transferid(\\n self.transfer_variable.use_encrypt, mode\\n )\\n LOGGER.debug(\\\"Start to remote use_encrypt: {}, transfer_id: {}\\\".format(self.use_encrypt, use_encryption_id))\\n\\n federation.remote(self.use_encrypt,\\n name=self.transfer_variable.use_encrypt.name,\\n tag=use_encryption_id,\\n role=consts.ARBITER,\\n idx=0)\\n\\n # Set public key\\n if self.use_encrypt:\\n pubkey_id = self.transfer_variable.generate_transferid(self.transfer_variable.paillier_pubkey, mode)\\n pubkey = federation.get(name=self.transfer_variable.paillier_pubkey.name,\\n tag=pubkey_id,\\n idx=0)\\n LOGGER.debug(\\\"Received pubkey\\\")\\n self.encrypt_operator.set_public_key(pubkey)\\n LOGGER.info(\\\"Finish synchronized ecryption\\\")\\n self.has_sychronized_encryption = True\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":383,"cells":{"query_id":{"kind":"string","value":"b2e408f4c573f516b292aaff446c06b2"},"query":{"kind":"string","value":"r\"\"\" Return a Steiner Quadruple System on `n` points."},"positive_passages":{"kind":"list like","value":[{"docid":"d1bc147bc816209e50c649bbb8517d26","score":"0.7664719","text":"def steiner_quadruple_system(n, check = False):\n n = int(n)\n if not ((n%6) in [2, 4]):\n raise ValueError(\"n mod 6 must be equal to 2 or 4\")\n elif n == 4:\n sqs = IncidenceStructure(4, [[0,1,2,3]], copy = False, check = False)\n elif n == 14:\n sqs = IncidenceStructure(14, _SQS14(), copy = False, check = False)\n elif n == 38:\n sqs = IncidenceStructure(38, _SQS38(), copy = False, check = False)\n elif n%12 in [4,8]:\n nn = n // 2\n sqs = two_n(steiner_quadruple_system(nn, check = False))\n elif n%18 in [4,10]:\n nn = (n+2) // 3\n sqs = three_n_minus_two(steiner_quadruple_system(nn, check = False))\n elif (n%36) == 34:\n nn = (n+8) // 3\n sqs = three_n_minus_eight(steiner_quadruple_system(nn, check = False))\n elif (n%36) == 26 :\n nn = (n+4) // 3\n sqs = three_n_minus_four(steiner_quadruple_system(nn, check = False))\n elif n%24 in [2,10]:\n nn = (n+6) // 4\n sqs = four_n_minus_six(steiner_quadruple_system(nn, check = False))\n elif n%72 in [14,38]:\n nn = (n+10) // 12\n sqs = twelve_n_minus_ten(steiner_quadruple_system(nn, check = False))\n else:\n raise ValueError(\"This shouldn't happen !\")\n\n if check and not sqs.is_t_design(3,n,4,1):\n raise RuntimeError(\"Something is very very wrong.\")\n\n return sqs","title":""}],"string":"[\n {\n \"docid\": \"d1bc147bc816209e50c649bbb8517d26\",\n \"score\": \"0.7664719\",\n \"text\": \"def steiner_quadruple_system(n, check = False):\\n n = int(n)\\n if not ((n%6) in [2, 4]):\\n raise ValueError(\\\"n mod 6 must be equal to 2 or 4\\\")\\n elif n == 4:\\n sqs = IncidenceStructure(4, [[0,1,2,3]], copy = False, check = False)\\n elif n == 14:\\n sqs = IncidenceStructure(14, _SQS14(), copy = False, check = False)\\n elif n == 38:\\n sqs = IncidenceStructure(38, _SQS38(), copy = False, check = False)\\n elif n%12 in [4,8]:\\n nn = n // 2\\n sqs = two_n(steiner_quadruple_system(nn, check = False))\\n elif n%18 in [4,10]:\\n nn = (n+2) // 3\\n sqs = three_n_minus_two(steiner_quadruple_system(nn, check = False))\\n elif (n%36) == 34:\\n nn = (n+8) // 3\\n sqs = three_n_minus_eight(steiner_quadruple_system(nn, check = False))\\n elif (n%36) == 26 :\\n nn = (n+4) // 3\\n sqs = three_n_minus_four(steiner_quadruple_system(nn, check = False))\\n elif n%24 in [2,10]:\\n nn = (n+6) // 4\\n sqs = four_n_minus_six(steiner_quadruple_system(nn, check = False))\\n elif n%72 in [14,38]:\\n nn = (n+10) // 12\\n sqs = twelve_n_minus_ten(steiner_quadruple_system(nn, check = False))\\n else:\\n raise ValueError(\\\"This shouldn't happen !\\\")\\n\\n if check and not sqs.is_t_design(3,n,4,1):\\n raise RuntimeError(\\\"Something is very very wrong.\\\")\\n\\n return sqs\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"cf3f839797ef63cebb2f18a384cec215","score":"0.60831946","text":"def chebpts(n):\r\n\r\n # Special case (no points)\r\n if n == 0:\r\n x = []\r\n w = [] \r\n v = []\r\n t = []\r\n # Special case (single point)\r\n elif n == 1:\r\n x = 0 \r\n w = 2 \r\n v = 1 \r\n t = np.pi/2\r\n \r\n else:\r\n # Chebyshev points:\r\n m = n - 1\r\n # (Use of sine enforces symmetry.)\r\n x = np.sin(np.pi*(np.r_[-m:m+1:2]/(2*m)))\r\n \r\n # [TODO] how to do a nargout in python?\r\n # Quadrature weights: \r\n w = quadwts.quadwts(n)\r\n \r\n # Barycentric weights:\r\n v = barywts.barywts(n)\r\n \r\n # Angles:\r\n t = angles.angles(n);\r\n\r\n return x, w, v, t","title":""},{"docid":"a1e81c4047e3b439e5df8ea217f0d874","score":"0.6047414","text":"def climbStairs2(n):\n p = 1 \n q = 1\n for i in xrange(2, n + 1):\n tmp = q\n q = p + tmp\n p = tmp\n return q","title":""},{"docid":"7e1fe757d7344fa36a4106e03939d381","score":"0.6005188","text":"def qft(n: int) -> qiskit.circuit.Gate:\n def rotations(my_circuit: qiskit.circuit.Gate, m: int):\n if m == 0:\n return my_circuit\n else:\n my_circuit.h(m-1) #Add a Haddamard gate to the most significant qubit\n \n for i in range(m-1):\n my_circuit.crz(pi/(2**(m-1-i)), i, m-1)\n\n rotations(my_circuit, m-1) \n \n my_circuit = qiskit.QuantumCircuit(n, name='QFT')\n \n rotations(my_circuit, n)\n\n for m in range(n//2):\n my_circuit.swap(m, n-m-1)\n\n return my_circuit.to_gate()","title":""},{"docid":"bbaac5247bdaabdd669fc051f1302807","score":"0.5952135","text":"def speye(n):\n r = range(n)\n return spmatrix(1.0, r, r)","title":""},{"docid":"581d6fb3db6977e2460bc5b9a347b985","score":"0.5816251","text":"def trianglequadrature(n):\n\n x00,w00 = scipy.special.orthogonal.p_roots(n)\n x01,w01 = scipy.special.orthogonal.j_roots(n,1,0)\n x00s = (x00+1)/2\n x01s = (x01+1)/2\n w = numpy.outer(w01, w00).reshape(-1,1) / 8 # a factor of 2 for the legendres and 4 for the jacobi10\n x = numpy.outer(x01s, numpy.ones(x00s.shape)).reshape(-1,1)\n y = numpy.outer(1-x01s, x00s).reshape(-1,1)\n return numpy.hstack((x, y)), w","title":""},{"docid":"5b57c334762796d651f900b09c50d022","score":"0.5796928","text":"def bezier_curve_range(n, points):\n for i in range(n):\n t = i / float(n - 1)\n yield bezier(t, points)","title":""},{"docid":"4f70f34deecb57382c3eed0fad8ccb2a","score":"0.57019246","text":"def Stair(n):\n r = []\n u = [0]\n\n for i in xrange(1,n-1,2):\n r.append(i)\n r.append(i-1)\n u.append(i+1)\n u.append(i)\n\n if n%2:\n r.append(n-1)\n else:\n r.append(n-1)\n r.append(n-2)\n u.append(n-1)\n\n positions = [((i+1)//2,i//2) for i in xrange(n)]\n o = Origami(r,u,as_tuple=True,positions=positions,name=\"Stair origami with %d squares\" %n)\n return o","title":""},{"docid":"98fd71083614979ceec006e94a3a8aa7","score":"0.5669432","text":"def climbStairs(self, n):\n \n steps = [1,2]\n for i in range(n-2):\n steps.append(steps[-2]+steps[-1])\n \n return steps[n-1]","title":""},{"docid":"bb84d8f90a64502535d53641faa5e8f1","score":"0.56559414","text":"def generate_fibonacci_spiral_hemisphere(n):\n phi = (1 + 5 ** 0.5) / 2\n coordinates = []\n # We generate one more coordinate than we actually need, because the first point of the fibonacci spiral lies in\n # the (y, z)-plane and is therefore useless to center fourier support of a wavelet around.\n N = n + 1\n\n for i in range(N):\n lat = math.asin(2*i/(2*N + 1))\n lon = 2*math.pi*i*(1/phi)\n\n # swap x and z since we want a hemisphere with (1, 0, 0) as north pole.\n z, y, x = latlon_to_xyz(lat, lon)\n coordinates.append( (x, y, z) )\n\n return coordinates[1:]","title":""},{"docid":"a668db7abcab2b4dd24fdb2377c4baa3","score":"0.5645339","text":"def qft_gate_sequence(n=1, swapping=True):\n\n if n < 1:\n raise ValueError(\"Minimum value of n can be 1\")\n\n qc = QubitCircuit(n)\n if n == 1:\n qc.add_gate(\"SNOT\", targets=[0])\n else:\n for i in range(n):\n qc.add_gate(\"SNOT\", targets=[i])\n for j in range(2, n - i + 1):\n qc.add_gate(r\"CPHASE\", targets=[i], controls=[i + j - 1],\n arg_label=r\"{\\pi/2^{%d}}\" % (j - 1),\n arg_value=numpy.pi / (2 ** (j - 1)))\n if swapping is True:\n for i in range(n // 2):\n qc.add_gate(r\"SWAP\", targets=[i, n - 1 - i])\n\n return qc","title":""},{"docid":"e1ff6c3c8a4083b6b090d45c48ecf929","score":"0.5613465","text":"def spirals(n_points, noise=.5):\n\n n = np.sqrt(np.random.rand(n_points, 1)) * 780 * (2 * np.pi) / 360\n d1x = -np.cos(n) * n + np.random.rand(n_points, 1) * noise\n d1y = np.sin(n) * n + np.random.rand(n_points, 1) * noise\n return (np.vstack((np.hstack((d1x, d1y)), np.hstack((-d1x, -d1y)))),\n np.hstack((np.zeros(n_points), np.ones(n_points))))","title":""},{"docid":"1baf6e88d4e92ebccd44ea8ca1463039","score":"0.556967","text":"def spread_quaternions(points,num=100,quats_per_step=100):\n #cria uma matrix de zeros num por 4\n quats = np.zeros((num,4))\n #print quats\n # cria 'num' matrizes, cada uma com points.shape[0] linhas e 3 colunas\n rot_points = np.zeros((num,points.shape[0],3))\n #print rot_points\n #a primeira posição de quats fica =\n quats[0,:] = [0,0,0,1]\n #print quats\n # primeiro conjunto de matrizes fica igual aos points\n rot_points[0,:,:] = points\n #print rot_points\n for ix in range(1,num):\n # criar quats_per_step quaterniões aleatorios \n rand_quats = random_quaternions(quats_per_step) \n # fazer a rotação dos pontos usando os quaterniões aleatorios\n positioned = rotate_points(points,rand_quats)\n # ver as distancias (retorna já os mais proximos!)\n dists = point_dists(rot_points[:ix],positioned)\n # ir buscar o maximo das distancias mais proximas\n new_rot = np.argmax(dists)\n \n quats[ix,:]=rand_quats[new_rot,:]\n rot_points[ix,:,:] = positioned[new_rot,:,:]\n print \"number of quaternions: \",len(quats) \n return quats,rot_points","title":""},{"docid":"0295ab84e67b7afcea16bacaf65f712e","score":"0.55645245","text":"def make_corner_seq(n):\n seq = [1]\n step_size = 2\n while len(seq) < n:\n for i in range(4):\n seq.append(seq[-1] + step_size)\n step_size += 2\n return seq","title":""},{"docid":"92851d156b088fe7335f99405bfd890b","score":"0.5559808","text":"def Towers(n,fr,to,spare):\n if n ==1:\n printMove(fr,to)\n else:\n Towers(n-1,fr,spare,to)\n Towers(1,fr,to,spare)\n Towers(n-1,spare,to,fr)","title":""},{"docid":"9da986e885ae9cea60daca210fb2b528","score":"0.5547893","text":"def randpoints(n, hw=1000., hh=1000.):\n P = [(i, uniform(-hw,-hw/4), uniform(-hh,hh)) for i in range(n//2)]\n Q = [(i, uniform(hw/4, hw), uniform(-hh,hh)) for i in range(n//2,n//1)]\n \n return P,Q","title":""},{"docid":"1451e624529b62f6e70ee9c2303e3859","score":"0.54642177","text":"def generate_tri_seq(N, t):\n for i in range(1, N + 1):\n t.add(i * (i + 1) / 2)","title":""},{"docid":"d0c470728e0f4965d142190c20f437da","score":"0.54572886","text":"def get_spline_curve(points, n=11):\n order = len(points) - 1\n coef = Utils.pascal_triangle_row(order)\n offset = 1.0 / (n-1)\n curve_points = []\n curve_points.append(points[0]) # add start point as first curve point\n # add n-2 curve points in middle\n for factor in range(1, n-1):\n t = offset * factor\n x, y = 0.0, 0.0\n for i in range(order+1):\n x += coef[i] * (1-t)**(order-i) * t**(i) * points[i][0]\n y += coef[i] * (1-t)**(order-i) * t**(i) * points[i][1]\n curve_points.append((x, y))\n curve_points.append(points[-1]) # add end point as last curve point\n return curve_points","title":""},{"docid":"27395edd4876511e4af24e371086e207","score":"0.54327834","text":"def _triangular(n):\n return sum(range(n + 1))","title":""},{"docid":"a1ce280c30a9b4f6c2f41c813b9c2bac","score":"0.5419874","text":"def generate_vertices(self):\n self.vertices = []\n self.refinement = np.zeros(self.tri.shape[0],dtype=int)\n for n,tri in enumerate(self.tri):\n limits = []\n k1, k2, k3 = tri\n if np.abs(k1-k2-k3) <= self.dk or np.any(tri == self.dk): # configurations with non-cubical integration volume\n nstep = self.nstep[1]\n else: # cubic integration volume\n nstep = self.nstep[0]\n if k3*1./(k1+k2) < self.squeezed_cut: # highly squeezed configurations\n nstep = self.nstep[2]\n if (k2+k3)*1./k1 <= self.collinear_cut: # collinear (or close to coll.) configurations\n nstep = self.nstep[2]\n self.refinement[n] = nstep\n for x1 in range(nstep):\n for x2 in range(nstep):\n q1 = k1 - self.dk*1./2 + self.dk*1./(nstep-1)*x1\n q2 = k2 - self.dk*1./2 + self.dk*1./(nstep-1)*x2\n q3min = max(k3-self.dk*1./2,abs(q1-q2))\n q3max = min(k3+self.dk*1./2,q1+q2)\n if abs(q3min-q3max) < 1e-4:\n limits.append([q1,q2,q3min])\n elif q3min < q3max:\n limits.append([q1,q2,q3min])\n limits.append([q1,q2,q3max])\n if np.abs(q3max-q3min-self.dk) < 1e-4:\n for i in range(nstep-2):\n limits.append([q1,q2,q3min+(q3max-q3min)*1./(nstep-1)*(i+1)])\n elif np.abs(q3max-q3min-self.dk*1./2) < 1e-4:\n for i in range(nstep-4):\n limits.append([q1,q2,q3min+(q3max-q3min)*1./(nstep-3)*(i+1)])\n if nstep == 2 and self.midpoint:\n limits.append([k1,k2,k3])\n self.vertices.append(np.unique(np.array(limits),axis=0))","title":""},{"docid":"9e8590812ec69b284ce1f880a3e11704","score":"0.54086983","text":"def squad(self):\n raise NotImplementedError()","title":""},{"docid":"85f33a9c2f7587a21a1e9f1e447bb1f6","score":"0.5399124","text":"def spiral(n):\r\n \r\n total = 1\r\n for n in range(3, spiral_range + 1, 2):\r\n # Every turn in the spiral adds four terms.\r\n ur = n * n # up-right term\r\n ul = n * n - n + 1 # up-left term\r\n dl = n * n - 2 * n + 2 # down-left term\r\n dr = n * n - 3 * n + 3 # down-right term\r\n subtotal = ur + ul + dl + dr\r\n total += subtotal\r\n return total","title":""},{"docid":"1dfbd8a3ff8c4a0a3bd98f5d09863011","score":"0.5392255","text":"def quarters(n):\n if n<25:\n return dimes(n)\n else:\n return quarters(n-25)+dimes(n)","title":""},{"docid":"0e0a61ebc75e11715c7eaf71a3efe519","score":"0.53626245","text":"def triangular(n):\n triang = n * (n + 1) / 2\n return triang","title":""},{"docid":"1fb3d6e69021477f7cc222bbc4d1f7c8","score":"0.5330278","text":"def stepPatternForStar(n, step): # draw platform independent\n\ti = 0\n\tindexList = []\n\t# Skip around the points of the n-gon to create the draw-path for the star.\n\twhile True:\n\t\tbreakAfterThis = False\n\t\tnextIndex = (i*step)%n\n\t\tif nextIndex in indexList:\n\t\t\tbreakAfterThis = True\n\t\tindexList.append(nextIndex)\n\t\tif breakAfterThis:\n\t\t\tbreak\n\t\ti = i + 1\n\treturn indexList","title":""},{"docid":"94a2074d913e53f0afa1167ea748bcf2","score":"0.53275067","text":"def make_quad(points, row_size, col_size):\n # Start with generating a zig-zag shape in row direction and then take its reverse\n new_points = make_zigzag(points, row_size)\n new_points.reverse()\n\n # Start generating a zig-zag shape in col direction\n forward = True\n for row in range(0, row_size):\n temp = []\n for col in range(0, col_size):\n temp.append(points[row + (col * row_size)])\n if forward:\n forward = False\n else:\n forward = True\n temp.reverse()\n new_points += temp\n\n return new_points","title":""},{"docid":"271fce1869ad21ffd32616edd4bf1529","score":"0.5291062","text":"def _generate_segment(self, n: 'int', basis: 'ndarray',\n geometry: 'ndarray'):\n def out(x, y):\n \"\"\"Test if given point is outside the window.\"\"\"\n return x > 1 or x < -1 or y > 1 or y < - 1\n\n delta = 1 / n\n fwd_x, fwd_y = self._init_curve_algorithm(basis, geometry, delta)\n dim = basis.shape[0]\n\n prev_out = True\n prev_point = None\n for _ in range(n+1):\n if out(fwd_x[0], fwd_y[0]):\n if not prev_out: # Leaving the window\n self._cr.line_to(*self.resolution_transform(clip_line(\n [prev_point, (fwd_x[0], fwd_y[0])])[0]))\n self._cr.stroke()\n prev_out = True\n else:\n if prev_out: # Entering the window\n if prev_point is None:\n self._cr.move_to(\n *self.resolution_transform((fwd_x[0], fwd_y[0])))\n else:\n point_at_window = clip_line(\n [(fwd_x[0], fwd_y[0]), prev_point])[0]\n self._cr.move_to(\n *self.resolution_transform(point_at_window))\n self._cr.line_to(\n *self.resolution_transform((fwd_x[0], fwd_y[0])))\n prev_out = False\n else: # Already inside window\n self._cr.line_to(\n *self.resolution_transform((fwd_x[0], fwd_y[0])))\n\n prev_point = (fwd_x[0], fwd_y[0])\n\n for i in range(dim-1):\n fwd_x[i] += fwd_x[i+1]\n fwd_y[i] += fwd_y[i+1]\n self._cr.stroke()","title":""},{"docid":"408ae05ac1207400397e5a51dd26fcd9","score":"0.52766865","text":"def _get_quadrature_points(n, a, b):\n x, w = roots_legendre(n)\n x = np.real(x)\n\n # Legendre domain is [-1, 1], convert to [a, b]\n scalar = (b - a) * 0.5\n return scalar * (x + 1) + a, scalar * w","title":""},{"docid":"e1fc684c5ccc1c8f12787a0f053ffc13","score":"0.5271362","text":"def Fan(self, n, deg_three_verts=False):\n f = graphs.WheelGraph(n)\n if n>2:\n f.delete_edge(1,n-1)\n if deg_three_verts:\n f.allow_multiple_edges(True)\n f.add_edges([(0,1),(0,n-1)])\n return Sandpile(f,0)\n elif n==1:\n return Sandpile(f,0)\n elif n==2:\n if deg_three_verts:\n return Sandpile({0:{1:3}, 1:{0:3}})\n else:\n return Sandpile(f,0)","title":""},{"docid":"c629243a09bf6213500f9425dff9ec1b","score":"0.5268188","text":"def test_qft_dagger(self):\n n = 5\n qsve = QSVE(np.identity(4))\n qreg = QuantumRegister(n)\n circ = QuantumCircuit(qreg)\n qsve._iqft(circ, qreg)\n\n print(circ)","title":""},{"docid":"bce381020721bdaf1324a6be4e842c2d","score":"0.52361876","text":"def triangs(self):\n return self.polys(3)","title":""},{"docid":"6243f618cc6855274d65b3b151d1d984","score":"0.52284604","text":"def ten_pairs(n):\n \"*** YOUR CODE HERE ***\"\n return ten_pairs_helper(n, [0,0,0,0,0,0,0,0,0,0])","title":""},{"docid":"cf0ab0e6356867b0ac0c52d8570a1c11","score":"0.52240753","text":"def triangle(n):\n T = {'sink':{}}\n for i in range(n):\n for j in range(n-i):\n T[(i,j)] = {}\n if i<n-j-1:\n T[(i,j)][(i+1,j)] = 1\n T[(i,j)][(i,j+1)] = 1\n if i>0:\n T[(i,j)][(i-1,j+1)] = 1\n T[(i,j)][(i-1,j)] = 1\n if j>0:\n T[(i,j)][(i,j-1)] = 1\n T[(i,j)][(i+1,j-1)] = 1\n d = len(T[(i,j)])\n if d<6:\n T[(i,j)]['sink'] = 6-d\n T = sandpile(T,'sink')\n pos = {}\n for x in T.nonsink_vertices():\n coords = list(x)\n coords[0]+=1/2*coords[1]\n pos[x] = coords\n pos['sink'] = (-1,-1)\n T.set_pos(pos)\n return T","title":""},{"docid":"61d436f0aa397e103d7d1b4d6f6fcd66","score":"0.5217978","text":"def squareSpiral(n_squares=60, sep_degrees=5, init_length=5, increment_length=5):\n for s in range(n_squares):\n square(init_length + increment_length*s)\n rt(sep_degrees)","title":""},{"docid":"ec088477b33913dca17a9e20042eb6f6","score":"0.5209428","text":"def chain(\n n: int = 4,\n r: float = 1.0,\n) -> tuple[list[str], np.ndarray, str]:\n\n xyz = np.zeros((n, 3))\n atoms = [\"H\"] * n\n\n z = np.arange(-(n - 1) / 2, (n) / 2) * r\n assert len(z) == n\n assert sum(z) == 0.0\n\n xyz[:, 2] = z\n\n description = \"H\" + str(n) + \" 1D chain, \" + str(r) + \" Angstroms\\n\"\n\n return atoms, xyz, description","title":""},{"docid":"a54530c9f4b0259be9edac076d0a4d4c","score":"0.5197737","text":"def generate_pascal_triangle_summation(self, n):\n # Write your code here\n row=[]\n pt=[]\n if n>12:\n return pt\n for i in range(n):\n nr = []\n for i in range(len(row)):\n v = row[i]\n if i>0:\n v += row[i-1]\n nr.append(1)\n pt.append(\" \".join([str(x) for x in nr]))\n row = nr\n \n return pt","title":""},{"docid":"92876a73ad5321395d42cd35f7103f1e","score":"0.51925355","text":"def get_trapezoid_quadrature_nodes_and_weights(n, a, b):\n if n < 1:\n raise ValueError(\"n must be at least one\")\n\n nodes = np.linspace(a, b, n)\n dx = nodes[1] - nodes[0]\n\n weights = dx * np.ones(n)\n weights[0] *= 0.5\n weights[-1] *= 0.5\n\n return nodes, weights","title":""},{"docid":"01ebe9cf90d673f2c09d8c59cf1370f6","score":"0.5177878","text":"def farey_sequence(n) -> Generator[Tuple[int, int], None, None]:\n\ta, b, c, d = 0, 1, 1, n\n\tyield (a, b)\n\twhile c <= n:\n\t\tk = (n + b) // d\n\t\ta, b, c, d = c, d, (k * c - a), (k * d - b)\n\t\tyield (a, b)","title":""},{"docid":"c1a538bb4c69d1fdb1f6228d3615d5f0","score":"0.51766396","text":"def get_simpsons_quadrature_nodes_and_weights(n, a, b):\n nodes = np.linspace(a, b, n)\n dx = nodes[1] - nodes[0]\n weights = np.tile([2.0, 4.0], int((n + 1) / 2))\n weights = weights[:n]\n weights[0] = weights[-1] = 1\n weights = (dx / 3.0) * weights\n\n return nodes, weights","title":""},{"docid":"e332b4fde36cdbb9d0c5ebff8f563a9e","score":"0.51730764","text":"def newFSPRootGen(pins, n):\n\t#Does so by generating all canonical arrangments with newFullArrGen, and adding the ascending values using newPinPopulate.\n\treturn chain.from_iterable(newPinPopulate(a, pins, n) for a in newFullArrGen(pins))","title":""},{"docid":"1ecbf78672686ecd31b3fce64280a6b9","score":"0.51591086","text":"def complete_sandpile(n):\n return Sandpile(graphs.CompleteGraph(n), 0)","title":""},{"docid":"e5761ffa9734706078094d9bb840f183","score":"0.51550394","text":"def spine_tupled_SG(n):\n base = list(range(n))\n SG = [base]\n def helper(L):\n if len(L) == 1:\n return\n if len(L) == 2:\n SG.append([L[0]])\n SG.append([L[1]])\n return\n l = random.sample(L, k = 1)\n r = list(set(L) - set(l))\n l = sorted(l)\n r = sorted(r)\n SG.append(l)\n SG.append(r)\n helper(l)\n helper(r)\n\n helper(base)\n SG = (tuple(x) for x in SG)\n return tuple(SG)","title":""},{"docid":"b7f82df5afb3ea6f74bb139c04e88f2e","score":"0.5148555","text":"def path_tupled_SG(n):\n base = list(range(n))\n SG = [base]\n def helper(L):\n if len(L) == 1:\n return\n if len(L) == 2:\n SG.append([L[0]])\n SG.append([L[1]])\n return\n l = [i for i in L if L.index(i) <= len(L)//2]\n r = list(set(L) - set(l))\n l = sorted(l)\n r = sorted(r)\n SG.append(l)\n SG.append(r)\n helper(l)\n helper(r)\n\n helper(base)\n SG = (tuple(x) for x in SG)\n return tuple(SG)","title":""},{"docid":"8c81b46b3ff341efcca918340de21de5","score":"0.51460874","text":"def gen_vertices(n):\n\n k = np.arange(n) + 1\n theta = deg2rad((2*k - 1) * (180.0/n))\n x = np.cos(theta)\n y = np.sin(theta)\n dx = np.roll(x, -1) - x\n dy = np.roll(y, -1) - y\n dtheta = np.roll(theta, -1) - theta\n #return zip(theta, dtheta)\n return zip(theta, dx, dy)","title":""},{"docid":"9c422136d461cce6c612932adf167f25","score":"0.5142337","text":"def GenerateRandomQuadrantPointsSurvey(self, *args):\n return _stomp.Map_GenerateRandomQuadrantPointsSurvey(self, *args)","title":""},{"docid":"3ff9680e1d5fa17cf8762debc6ea00bd","score":"0.5140021","text":"def spiral_simple(x_range_egu, y_range_egu, dr_egu, nth):\n half_x = x_range_egu / 2\n half_y = y_range_egu / 2\n\n r_max_egu = np.sqrt(half_x ** 2 + half_y ** 2)\n num_ring = 1 + int(r_max_egu / dr_egu)\n\n x_points = []\n y_points = []\n for i_ring in range(1, num_ring + 2):\n radius_egu = i_ring * dr_egu\n angle_step = 2. * np.pi / (i_ring * nth)\n\n for i_angle in range(int(i_ring * nth)):\n angle = i_angle * angle_step\n x_egu = radius_egu * np.cos(angle)\n y_egu = radius_egu * np.sin(angle)\n if abs(x_egu) <= half_x and abs(y_egu) <= half_y:\n x_points.append(x_egu)\n y_points.append(y_egu)\n\n return x_points, y_points","title":""},{"docid":"cb4bc5f233deba4de14f86370ea4263d","score":"0.51391864","text":"def __pow__(self, n):\n r = Quaternion()\n for i in range(n):\n r = r * self\n return r","title":""},{"docid":"1924f2ca76e9089b586dab8e9127686f","score":"0.5116036","text":"def getcorners(n):\n corners = []\n corners.append(n * n - 3 * n + 3)\n corners.append(n * n -2 * n + 2)\n corners.append(n * n - n + 1)\n corners.append(n * n)\n return corners","title":""},{"docid":"bb3ef0bdd0eab677bdd3df63d96b0899","score":"0.51098365","text":"def latin_hypercube(n):\n\n low_lim = np.arange(0, n)/n\n up_lim = np.arange(1, n+1)/n\n\n #random points on grid\n points = np.random.uniform(low=low_lim, high = up_lim, size=[2,n]).T\n\n np.random.shuffle(points[:,1])\n\n print(\"LHS:\")\n print(points)\n\n return points","title":""},{"docid":"a4b9ca0d2c49edd42ebbd4af6e36a41a","score":"0.51075774","text":"def gwfs(S, N=6):\n return GridUtil.smooth(S, \"GWFS\", int(N))","title":""},{"docid":"f9a2884e25e2b9b8a82aa503955865ad","score":"0.51066434","text":"def compute_srideal(R, triang):\n k = R.ngens()\n n = len(triang[0])\n srideal = []\n for i in range(n):\n for c in map(set, combinations(range(k), i + 1)):\n # SR ideal generators must be minimal\n for prev_c in srideal:\n if prev_c.issubset(c):\n break\n else:\n for t in map(set, triang):\n # 1-cones in a simplex correspond to intersecting divisors\n if c.issubset(t):\n break\n else:\n srideal.append(c)\n X = R.gens()\n return [R.ideal(*[X[i] for i in s]) for s in srideal]","title":""},{"docid":"bce90c54af1dc1f2cca05a535dffbee7","score":"0.51010764","text":"def generateMatrix(self, n):\n '''\n 临场能写出\n def generateMatrix(self, n):\n A = [[n*n]]\n while A[0][0] > 1:\n A = [range(A[0][0] - len(A), A[0][0])] + zip(*A[::-1])\n return A * (n>0)\n 就相当了不起了\n '''\n matrix = []\n s = n * n + 1 # make it starting from 1 rather than 0\n while s > 1:\n s, e = s - len(matrix), s\n matrix = [range(s, e)] + zip(*matrix[::-1])\n return matrix # spiral counter clockwise return zip(*matrix)","title":""},{"docid":"143ee46b1b1eaa4aaec2524edc278990","score":"0.5097594","text":"def climbStairs(self, n):\n climb = {}\n climb[1] = 1\n climb[2] = 2\n for i in xrange(3, n + 1):\n climb[i] = climb[i - 1] + climb[i - 2]\n return climb[n]","title":""},{"docid":"25defad497f6dddbb8e427e6dd2a0fde","score":"0.5091647","text":"def Wheel(self, n):\n return Sandpile(graphs.WheelGraph(n),0)","title":""},{"docid":"97e6c2168176986341eaf055f142729e","score":"0.50915474","text":"def n_step(self,n=1 , plot=False):\n for i in range(n):\n if len(self.x) < self.N_max:\n self.next_point()\n self.model = GPR(kernel=self.kernel, normalize_y=True).fit(np.array(self.x).reshape(-1, 1), np.array(self.y).reshape(-1, 1))\n else:\n print(\"Optimisation terminee\")\n if plot:\n self.plot()","title":""},{"docid":"a0f6bde02e8aed08bc528258321e1a52","score":"0.50800806","text":"def sim(self, n):\n return Results(self.draw() for _ in range(n))","title":""},{"docid":"eda1fe42b0b2abaf47752f123840d80e","score":"0.5056638","text":"def triangle():\n \n triangle_points = np.linspace(0, 1, 500)\n return signal.sawtooth(10 * np.pi * triangle_points, 0.5)","title":""},{"docid":"46bd68766f6d0df76ba5505d23331eaa","score":"0.50512314","text":"def randQuad(n):\n A = np.random.rand(n,n)\n b = np.random.rand(n,1)\n Q = np.matmul(A.transpose(), A)\n return Q,b","title":""},{"docid":"9a70183fbcc523694538fd6831c4a074","score":"0.50500363","text":"def generate_random(n):\r\n points = random.Random()\r\n points_list = []\r\n for i in range(n):\r\n points_list.append((round(points.uniform(0, 1), 2), round(points.uniform(0, 1), 2)))\r\n return (points_list)","title":""},{"docid":"9a5f21e6f036819b5e231c9ed6b7f496","score":"0.5047165","text":"def outer(self, P, n):\n if n == 0:\n return Point(0, 1)\n Q = self.outer(P, n // 2)\n Q = self.inner(Q, Q)\n if n & 1:\n Q = self.inner(Q, P)\n return Q","title":""},{"docid":"1e473bd0756b4788239e9c5cc9fc1e4e","score":"0.50384766","text":"def get_quadratic_data_sample(n, add_noise=False, x_min=-1, x_max=1, noise=0.01, pow=2):\n\n ### Sanity Checks ###\n if type(n) is not int or n <= 0: raise Exception(\"Sample size must be a positive integer\")\n if type(pow) is not int or pow % 2 != 0 or pow <= 0: raise Exception(\"Power must be a positive even integer \")\n if x_min >= x_max: raise Exception(\"Min value ({}) is higher or equal than max value ({})\".format(x_min, x_max))\n\n x = uniform(x_min, x_max, n) # Points along x\n mid = (x_max-x_min)/2 + x_min # Middle point\n y = power((x-mid), pow) # Raise x\n\n if add_noise: y += (2 * random(n) - 1) * noise # Add noise to y\n\n # combine x and y as points in 2D plane\n coordinates = list(zip(x,y))\n # Return coordinates as numpy array\n return array(coordinates, dtype=float32)","title":""},{"docid":"b9863ad3ae6d67a52d606522b04ddb68","score":"0.5035669","text":"def twelve_n_minus_ten(B):\n n = B.num_points()\n B14 = steiner_quadruple_system(14)\n r = lambda i,x : i%(n-1)+(x%12)*(n-1)\n\n # Line 1.\n Y = []\n for s in B14._blocks:\n for i in range(n-1):\n Y.append([r(i,x) if x<= 11 else r(n-2,11)+x-11 for x in s])\n\n for s in B._blocks:\n if s[-1] == n-1:\n u,v,w,B = s\n dd = {0:u,1:v,2:w}\n d = lambda x:dd[x%3]\n for b in range(12):\n for bb in range(12):\n bbb = -(b+bb)%12\n for h in range(2):\n # Line 2\n Y.append([r(n-2,11)+1+h,r(u,b),r(v,bb),r(w,bbb+3*h)])\n\n for i in range(3):\n # Line 38.3\n Y.append([r(d(i),b+4+i), r(d(i),b+7+i), r(d(i+1),bb), r(d(i+2),bbb)])\n\n for j in range(12):\n for eps in range(2):\n for i in range(3):\n # Line 38.4-38.7\n Y.append([ r(d(i),j), r(d(i+1),j+6*eps ), r(d(i+2),6*eps-2*j+1), r(d(i+2),6*eps-2*j-1)])\n Y.append([ r(d(i),j), r(d(i+1),j+6*eps ), r(d(i+2),6*eps-2*j+2), r(d(i+2),6*eps-2*j-2)])\n Y.append([ r(d(i),j), r(d(i+1),j+6*eps-3), r(d(i+2),6*eps-2*j+1), r(d(i+2),6*eps-2*j+2)])\n Y.append([ r(d(i),j), r(d(i+1),j+6*eps+3), r(d(i+2),6*eps-2*j-1), r(d(i+2),6*eps-2*j-2)])\n\n for j in range(6):\n for i in range(3):\n for eps in range(2):\n # Line 38.8\n Y.append([ r(d(i),j), r(d(i),j+6), r(d(i+1),j+3*eps), r(d(i+1),j+6+3*eps)])\n\n for j in range(12):\n for i in range(3):\n for eps in range(4):\n # Line 38.11\n Y.append([ r(d(i),j), r(d(i),j+1), r(d(i+1),j+3*eps), r(d(i+1),j+3*eps+1)])\n # Line 38.12\n Y.append([ r(d(i),j), r(d(i),j+2), r(d(i+1),j+3*eps), r(d(i+1),j+3*eps+2)])\n # Line 38.13\n Y.append([ r(d(i),j), r(d(i),j+4), r(d(i+1),j+3*eps), r(d(i+1),j+3*eps+4)])\n\n for alpha in [4,5]:\n for ra,sa in P(alpha,6):\n for raa,saa in P(alpha,6):\n for i in range(3):\n for ii in range(i+1,3):\n # Line 38.14\n Y.append([ r(d(i),ra), r(d(i),sa), r(d(ii),raa), r(d(ii),saa)])\n\n for g in range(6):\n for eps in range(2):\n for i in range(3):\n for ii in range(3):\n if i == ii:\n continue\n # Line 38.9\n Y.append([ r(d(i),2*g+3*eps), r(d(i),2*g+6+3*eps), r(d(ii),2*g+1), r(d(ii),2*g+5)])\n # Line 38.10\n Y.append([ r(d(i),2*g+3*eps), r(d(i),2*g+6+3*eps), r(d(ii),2*g+2), r(d(ii),2*g+4)])\n\n else:\n x,y,z,t = s\n for a in range(12):\n for aa in range(12):\n for aaa in range(12):\n aaaa = -(a+aa+aaa)%12\n # Line 3\n Y.append([r(x,a), r(y,aa), r(z,aaa), r(t,aaaa)])\n return IncidenceStructure(12*n-10,Y,check=False,copy=False)","title":""},{"docid":"45030b70ce82664a8b29a7cd4d5e8e60","score":"0.5024016","text":"def calculate_squirrels(n, k):\n return k % n","title":""},{"docid":"aab0bdca5c38e6ade2118152e70a3863","score":"0.5020411","text":"def turan_graph(n, r):\n\n if not 1 <= r <= n:\n raise NetworkXError(\"Must satisfy 1 <= r <= n\")\n\n partitions = [n // r] * (r - (n % r)) + [n // r + 1] * (n % r)\n G = complete_multipartite_graph(*partitions)\n return G","title":""},{"docid":"fd19bd7c6ed80a258dafc6d099b3a545","score":"0.50122505","text":"def sqaure(t, length):\r\n\tpolygon(t, length, 4)","title":""},{"docid":"ed734147745756fdf920f35bee7c4210","score":"0.5011693","text":"def spheres(n):\n indices = np.arange(0, n, dtype=float) + 0.5\n golden_angle = np.pi * (1 + 5**0.5)\n phi = np.arccos(1 - 2*indices/n)\n theta = golden_angle * indices\n\n points = np.zeros((n, 3))\n points[:, 0] = np.cos(theta) * np.sin(phi)\n points[:, 1] = np.sin(theta) * np.sin(phi)\n points[:, 2] = np.cos(phi)\n\n return points","title":""},{"docid":"d34dc0411617dd44ecab62b78dc4c80d","score":"0.500812","text":"def S(n):\n return n * (n + 1) // 2 # Gauss's formula","title":""},{"docid":"c2c6875ce9e2df714e630f8513f97b70","score":"0.50018275","text":"def polys(self, n):\n candidate = 1\n m = 0\n while True:\n yield candidate\n candidate += n - 1 + m*(n - 2)\n m += 1","title":""},{"docid":"6d91aa91ea884915c86013e704300bf3","score":"0.49799803","text":"def RCUEWG(n): # Taken from lectures\n \n M = np.random.random((n, n))\n G = nx.Graph()\n for i in range(n):\n # notice we are using the upper triangle only\n # that is we discard M_ii and M_ji where j<i\n for j in range(i+1, n):\n G.add_edge(i, j, weight=M[i, j])\n return G","title":""},{"docid":"7c40a8c9b0d434bee08fc2410fb31aca","score":"0.49780157","text":"def count_stair_ways(n):\n def repeat(s):\n if s <= 1:\n return s \n return repeat(s - 1) + repeat(s - 2)\n return repeat(n + 1)","title":""},{"docid":"3705f8d01a520d2b16c7fe584d2db08a","score":"0.49743107","text":"def NRSur7dq4_samples(i):\n\n assert i in [0,1,2]\n\n if i==0:\n chiA = [-0.2, 0.4, 0.1]\n chiB = [-0.5, 0.2, -0.4]\n precessing_opts = {'init_quat': [1,0,0,0],\n 'return_dynamics': True,\n 'init_orbphase': 0.0}\n #'use_lalsimulation_conventions': True}\n return [2., chiA, chiB], None, precessing_opts\n elif i==1:\n chiA = [-0.2, 0.4, 0.1]\n chiB = [-0.5, 0.2, -0.4]\n precessing_opts = {'init_quat': [1,0,0,0],\n 'return_dynamics': True,\n 'init_orbphase': 1.0}\n #'use_lalsimulation_conventions': False}\n return [3., chiA, chiB], None, precessing_opts\n elif i==2:\n chiA = [-0.2, 0.4, 0.1]\n chiB = [-0.5, 0.2, -0.4]\n precessing_opts = {'init_quat': [1,0,0,0],\n 'return_dynamics': True,\n 'init_orbphase': 0.0}\n #'use_lalsimulation_conventions': True}\n return [5., chiA, chiB], None, precessing_opts","title":""},{"docid":"ec3ff4d653276546d707072f2617cc76","score":"0.4971743","text":"def calc_base_spline(n=50):\n\n x = np.linspace(0, 1, 4) # knot points to fit curve onto\n y = [0, 0.05, 0.07, 0]\n xvec = np.linspace(0, 1, n)\n tck = interpolate.splrep(x, y)\n yvec = interpolate.splev(xvec, tck, der=0)\n\n return xvec, yvec","title":""},{"docid":"59a79414a829df3d5e70cb42436b98e5","score":"0.49713317","text":"def first_n_cubes(n):\r\n output = []\r\n for i in range(1, (n + 1)):\r\n output = output + [i ** 3]\r\n return output","title":""},{"docid":"dd8be42f6af67ea82f02aa89d4568723","score":"0.49665156","text":"def step(self, n):\n return self.slice(step=n)","title":""},{"docid":"fbe638ee595af471754c1d06978ea601","score":"0.49548364","text":"def generate_pascal_triangle_binomial(self, n):\n # Write your code here\n row=[]\n pt=[]\n if n>12:\n return pt\n for i in range(n):\n nr = []\n for i in range(len(row)):\n v = row[i]\n if i>0:\n v += row[i-1]\n nr.append(1)\n pt.append(\" \".join([str(x) for x in nr]))\n row = nr\n \n return pt","title":""},{"docid":"95cf0a25e98934dfd769be3e84a14e81","score":"0.494955","text":"def triangle(n):\n return sum([n for n in range(1,n+1)])","title":""},{"docid":"9c11810778197f6a56fc6e0c47b3b295","score":"0.49451405","text":"def _twospirals(self,n_points, noise=.75):\n n = np.sqrt(np.random.rand(n_points,1)) * 780 * (2*np.pi)/360\n d1x = -np.cos(n)*n + np.random.rand(n_points,1) * noise\n d1y = np.sin(n)*n + np.random.rand(n_points,1) * noise\n return (np.vstack((np.hstack((d1x,d1y)),np.hstack((-d1x,-d1y)))), \n np.hstack((np.zeros(n_points),np.ones(n_points))))","title":""},{"docid":"fa3ab0e585ad5cf37cbb3c9fb2e4738c","score":"0.4933968","text":"def Make_Spiral_Matrix(n):\n dx,dy = 1,0 # Starting increments\n x,y = 0,0 # Starting location\n myarray = [[None]* n for j in range(n)]\n for i in range(n**2, 0, -1):\n myarray[x][y] = i\n nx,ny = x+dx, y+dy\n if 0<=nx<n and 0<=ny<n and myarray[nx][ny] == None:\n x,y = nx,ny\n else:\n dx,dy = -dy,dx\n x,y = x+dx, y+dy\n return np.fliplr(np.matrix(myarray).transpose())","title":""},{"docid":"2a9cb1abe54607768f1330ba2c81ade2","score":"0.49325886","text":"def generate_individual_series(N_points=3600):\n # toggles\n reorientation_chance = 10\n \n state = (0, 0, 0, 0)\n states = [state] \n\n while len(states) < N_points + 2:\n N_seg = int(sts.expon.rvs(scale=100))\n\n #intialize velocity and angular change\n new_v = random.choice([0, 0.01, 0.04])\n d_ang = 0\n if new_v > 0:\n d_ang = np.random.normal(0, 0.01)\n \n\n # before moving. try reorientation chance.\n rando = random.uniform(0, 1) * 100 \n if rando < reorientation_chance and new_v > 0:\n # reorientation make current direction equally randomly face anywhere.\n x, y, v, ang = states[-1]\n states[-1] = (x, y, v, np.random.uniform(- np.pi, np.pi)) \n \n # now generate all changes.\n x, y, v, ang = states[-1]\n for i in range(N_seg):\n x, y, v, ang = (x + v * np.cos(ang),\n y + v * np.sin(ang),\n new_v,\n ang+d_ang)\n states.append((x, y, v, ang)) \n\n\n # remove first point (which was dummy values) and cut down to N_points points\n x, y, vel, thetas = zip(*states[2:N_points +2])\n return x, y, vel, thetas","title":""},{"docid":"8acf3431b2b2c9befc762fae439a990b","score":"0.4931785","text":"def triangulate(self, n=None, symmetry=None, centroid=True, printout=False):\n # Inherit class arguments\n if symmetry is None:\n symmetry = self.symmetry\n # Build origin and supremum vectors\n origin = [i[0] for i in self.bounds]\n self.origin = origin\n supremum = [i[1] for i in self.bounds]\n\n self.supremum = supremum\n\n #TODO: Add check that len(symmetry) is equal to len(self.bounds)\n if symmetry is None:\n cbounds = self.bounds\n else:\n cbounds = copy.copy(self.bounds)\n for i, j in enumerate(symmetry):\n if i is not j:\n # pop second entry on second symmetry vars\n cbounds[i] = [self.bounds[symmetry[i]][0]]\n # Sole (first) entry is the sup value and there is no origin\n cbounds[i] = [self.bounds[symmetry[i]][1]]\n if self.bounds[symmetry[i]] is not self.bounds[symmetry[j]]:\n logging.warning(f\"Variable {i} was specified as \"\n f\"symmetetric to variable {j}, however,\"\n f\"the bounds {i} =\"\n f\" {self.bounds[symmetry[i]]} and {j} =\"\n f\" {self.bounds[symmetry[j]]} do not \"\n f\"match, the mismatch was ignored in \"\n f\"the initial triangulation.\")\n cbounds[i] = self.bounds[symmetry[j]]\n\n\n if n is None:\n # Build generator\n self.cp = self.cyclic_product(cbounds, origin, supremum, centroid,\n printout)\n for i in self.cp:\n i\n\n try:\n self.triangulated_vectors.append((tuple(self.origin),\n tuple(self.supremum)))\n except (AttributeError, KeyError):\n self.triangulated_vectors = [(tuple(self.origin),\n tuple(self.supremum))]\n\n else:\n #Check if generator already exists\n try:\n self.cp\n except (AttributeError, KeyError):\n self.cp = self.cyclic_product(cbounds, origin, supremum,\n centroid, printout)\n\n try:\n while len(self.V.cache) < n:\n next(self.cp)\n except StopIteration:\n #TODO: We should maybe append and add the possibility of\n # of starting new triangulated domains on different\n # complexes\n try:\n self.triangulated_vectors.append((tuple(self.origin),\n tuple(self.supremum)))\n except (AttributeError, KeyError):\n self.triangulated_vectors = [(tuple(self.origin),\n tuple(self.supremum))]\n\n\n if printout:\n print(\"=\" * 19)\n print(\"Initial hyper cube:\")\n print(\"=\" * 19)\n # for v in self.C0():\n # v.print_out()\n for v in self.V.cache:\n self.V[v].print_out()\n\n print(\"=\" * 19)\n\n return","title":""},{"docid":"f115e851e2e2de8d14e7ec1a1aff0129","score":"0.49307755","text":"def shifted(self, n_lanes: int):\n return StraightLane(self.p + self.n * self.w * n_lanes,\n self.q + self.n * self.w * n_lanes, self.w)","title":""},{"docid":"c28a1e2d4174e47918599c899ec2af96","score":"0.4926417","text":"def make_series_paired(n_parcels, n_samples, n_cut_samples=40, widths=range(5,6), time_shift=3, seed=None):\n \n decim_factor = 5\n n_parcels_half = n_parcels//2\n remainder = n_parcels%2\n time_shift = (0, time_shift) # Do not shift across parcels, only time.\n \n pairs = list(range(0, n_parcels-remainder))\n if seed != None: random.seed(seed)\n random.shuffle(pairs)\n pairs = np.reshape(pairs, (n_parcels_half, 2))\n \n # Do signals for half of the parcels. Time shift the other half from the first half.\n if seed != None: np.random.seed(seed)\n s = randn(n_parcels_half+remainder, n_samples*decim_factor+2*n_cut_samples)\n \n for i in np.arange(0, n_parcels_half+remainder):\n s[i, :] = signal.cwt(s[i, :], signal.ricker, widths)\n \n # Separate last sample of s in case there is an odd numbered number of parcels.\n if remainder == 1:\n s_rem = s[-1,:]\n s = np.delete(s, -1, 0) # Delete last row from s.\n s_rem = signal.hilbert(s_rem)\n s_rem = s_rem[n_cut_samples:-n_cut_samples]\n s_rem = scipy.signal.decimate(s_rem, decim_factor)\n \n s_shift = shift(s, time_shift, mode='wrap')\n s = signal.hilbert(s)\n s_shift = signal.hilbert(s_shift)\n s = s[:, n_cut_samples:-n_cut_samples]\n s_shift = s_shift[:, n_cut_samples:-n_cut_samples]\n # Decimate the signals separately.\n s = scipy.signal.decimate(s, decim_factor, axis=1)\n s_shift = scipy.signal.decimate(s_shift, decim_factor, axis=1)\n \n # Slice the generated signals to correct indices.\n s_comb = np.zeros((n_parcels, n_samples), dtype=complex)\n s_comb[pairs[:,0],:] = s\n s_comb[pairs[:,1],:] = s_shift\n if remainder == 1:\n s_comb[-1,:] = s_rem\n return s_comb, pairs","title":""},{"docid":"b253bb4e4fd6ca15bb0fa4beaec024d0","score":"0.49240783","text":"def row(n):\n return range((n**2-n+2)//2, n*(n+1)//2+1)","title":""},{"docid":"83f7a46f1411b3482bb579fc16a27b68","score":"0.49209148","text":"def rotation_matrices_fibonacci_spiral_unit_x(n):\n unit_x = np.array([1, 0, 0])\n points = generate_fibonacci_spiral_hemisphere(n)\n rotation_matrices = [ rotation_matrix(unit_x, np.array(point)) for point in points ]\n return rotation_matrices","title":""},{"docid":"7122126ca33c8a69a05cd615d25c99a0","score":"0.49208692","text":"def pis(self):\n\n q, r, t, k, n, l = 1, 0, 1, 1, 3, 3\n while True:\n if 4*q + r - t < n*t:\n yield n\n nr = 10*(r - n * t)\n n = ((10*(3*q + r))//t) - 10*n\n q *= 10\n r = nr\n else:\n nr = (2*q+r)*l\n nn = (q*(7*k)+2+(r*l))//(t*l)\n q *= k\n t *= l\n l += 2\n k += 1\n n = nn\n r = nr","title":""},{"docid":"376a072f2c80c1a1f2ef22d13e381590","score":"0.49205878","text":"def exo4():\n q = 30\n Tlist = linspace(2.5, 4, q)*sigma\n err = []\n for i in 1: q:\n fWT = Thresh(fW, Tlist(i))\n f1 = PsiS(fWT)\n err(i) = snr(f, f1)\n plot(Tlist/ sigma, err)\n axis('tight')\n set_label('T/ \\sigma', 'SNR')","title":""},{"docid":"58d1f45a679ea9d0e12b5259b3919caa","score":"0.49188805","text":"def generate_separated_square(lx, ly, c, p, n):\n ys = []\n yws = []\n xs = []\n xws = []\n wx = 2*lx/n\n wy = 2*ly/n\n for i in range(n):\n y, w = cheb(p, -ly + i*wy, -ly + (i+1)*wy)\n ys.append(y)\n yws.append(w)\n x, w = cheb(p, -lx + i*wx, -lx + (i+1)*wx)\n xs.append(x)\n xws.append(w)\n x = np.concatenate(xs)\n xw = np.concatenate(xws)\n y = np.concatenate(ys)\n yw = np.concatenate(yws)\n # stitch sides together to get nodes\n lxl = np.repeat(lx, p*n)\n lyl = np.repeat(ly, p*n)\n left = np.row_stack([ -lxl + c[0], y + c[1] ])\n right = np.row_stack([ lxl + c[0], y + c[1] ])\n bottom = np.row_stack([ x + c[0], -lyl + c[1] ])\n top = np.row_stack([ x + c[0], lyl + c[1] ])\n\n return left, right, bottom, top","title":""},{"docid":"b0ef0a753696aeffac1916309bedf972","score":"0.49136946","text":"def _idx_to_quadruple(cls, idx):\n\n row, col = divmod(idx, cls.get_number())\n id1, k1 = divmod(row-1, cls.k)\n id2, k2 = divmod(col-1, cls.k)\n return id1+1, k1+1, id2+1, k2+1","title":""},{"docid":"8f19be6fde47914afa233def65530b43","score":"0.49114504","text":"def get_sample_space(self, n=1000, gridding=False):\n if gridding:\n return self._get_grid_sample_space()\n else:\n return self._get_random_sample_space(n)","title":""},{"docid":"f6ae40f657423b9479569e79cca402ca","score":"0.49063462","text":"def triangle(n):\n return (n * (n + 1)) / 2","title":""},{"docid":"7f4507ce36e22217ef55cc6abe9c50b1","score":"0.49051","text":"def spiral(n):\n\n step = 20\n direc = \"e\"\n newddict = {\"e\": \"n\",\n \"n\": \"w\",\n \"w\": \"s\",\n \"s\": \"e\"}\n dummy = 1\n \n while n > 0:\n\n turtle.forward(step)\n turn(direc,newddict[direc])\n \n if dummy % 2 == 0:\n step += 20\n\n direc = newddict[direc]\n n += -1\n dummy += 1\n\n turtle.exitonclick()","title":""},{"docid":"cdcc57a3bb5b2480a95f16229931ea05","score":"0.4898313","text":"def generate(self, n):\n candidates = []\n scores = []\n nv = len(self.xmin)\n for i in np.arange(1, min(n, self._seed_size) + 1):\n if i < 3:\n # 1/2 points\n seed = delayed(np.arange(1, i + 1)[:, None] * np.ones(shape=(1, nv)))\n else:\n # Larger seeds using recursive division\n seed = LatinHypercube(self.xmin, self.xmax, self.use_logger, seed_size=i - 1).generate(i)\n\n # Create candidate designs and compute inter-site distance\n ns = seed.shape[0]\n x = self._tplhsdesign(n, seed, ns).compute()\n candidates.append(x)\n scores.append(np.min(pdist(x)))\n\n # Select the top-ranked candidate\n lhd = candidates[np.argmax(scores)]\n\n # Scale to [xmin, xmax]\n lhd_scaled = self.scale_to_new_domain(lhd, self.xmin, self.xmax)\n\n if self.use_logger:\n self.logger.info(\"Latin hypercube design: generated {0} points in {1} dimensions\".format(n, nv))\n\n return lhd_scaled","title":""},{"docid":"3e1466fb7c5b344c19a4f07b57f40bf7","score":"0.48947856","text":"def generateParenthesis(self, n: int) -> List[str]:\n res = []\n\n def util(cur_str, n_lb, n_rb):\n if n_lb > n or n_rb > n:\n return\n if n_lb == n_rb == n:\n res.append(cur_str)\n if n_lb == n_rb:\n util(cur_str+'(', n_lb+1, n_rb)\n if n_lb > n_rb:\n util(cur_str+'(', n_lb+1, n_rb)\n util(cur_str+')', n_lb, n_rb+1)\n if n_lb < n_rb:\n return\n\n util('', 0, 0)\n return res","title":""},{"docid":"37cbdd59a9813cb0ecab8491be77ea9d","score":"0.4889421","text":"def stools3(n, source, temp1, destination):\n \n if n == 1:\n model.move(source, destination)\n if animate:\n time.sleep(delay_btw_moves)\n print(str(model))\n else:\n stools3(n - 1, source, destination, temp1)\n model.move(source, destination)\n if animate:\n time.sleep(delay_btw_moves)\n print(str(model))\n stools3(n - 1, temp1, source, destination)","title":""},{"docid":"1c5ab84df5b008eb97a51ab96b08584e","score":"0.48801392","text":"def twospirals(n_points, noise=.5, random_state=920):\n n = np.sqrt(np.random.rand(n_points,1)) * 600 * (2*np.pi)/360\n d1x = -1.5*np.cos(n)*n + np.random.randn(n_points,1) * noise\n d1y = 1.5*np.sin(n)*n + np.random.randn(n_points,1) * noise\n return (np.vstack((np.hstack((d1x,d1y)),np.hstack((-d1x,-d1y)))),\n np.hstack((np.zeros(n_points),np.ones(n_points))))","title":""},{"docid":"d081fbe2ce24f2de3f61ccd19032295b","score":"0.48767608","text":"def trigrid(self, n=10):\n lam = []\n for lam1 in range(n):\n for lam2 in range(n - lam1):\n lam3 = n - lam1 - lam2\n lam.append([lam1, lam2, lam3])\n return np.array(lam) / float(n)","title":""},{"docid":"daf1a5792ee024d7757c43a80e7fa35c","score":"0.48743713","text":"def structure_factor(trj, Q_range=(0.5, 50), n_points=1000, framewise_rdf=False, method='fz'):\n rho = np.mean(trj.n_atoms / trj.unitcell_volumes)\n L = np.min(trj.unitcell_lengths)\n\n top = trj.topology\n elements = set([a.element for a in top.atoms])\n\n compositions = dict()\n form_factors = dict()\n rdfs = dict()\n\n Q = np.logspace(np.log10(Q_range[0]),\n np.log10(Q_range[1]),\n num=n_points)\n S = np.zeros(shape=(len(Q)))\n\n for elem in elements:\n compositions[elem.symbol] = len(top.select('element {}'.format(elem.symbol)))/trj.n_atoms\n form_factors[elem.symbol] = elem.atomic_number\n\n for i, q in enumerate(Q):\n num = 0\n denom = 0\n\n for elem in elements:\n denom += compositions[elem.symbol] * form_factors[elem.symbol]\n\n for (elem1, elem2) in it.product(elements, repeat=2):\n e1 = elem1.symbol\n e2 = elem2.symbol\n\n f_a = form_factors[e1]\n f_b = form_factors[e2]\n\n x_a = compositions[e1]\n x_b = compositions[e2]\n \n try:\n g_r = rdfs['{0}{1}'.format(e1, e2)]\n except KeyError:\n pairs = top.select_pairs(selection1='element {}'.format(e1),\n selection2='element {}'.format(e2))\n if framewise_rdf:\n r, g_r = rdf_by_frame(trj,\n pairs=pairs,\n r_range=(0, L / 2),\n bin_width=0.001)\n else:\n r, g_r = md.compute_rdf(trj,\n pairs=pairs,\n r_range=(0, L / 2),\n bin_width=0.001)\n rdfs['{0}{1}'.format(e1, e2)] = g_r\n integral = simps(r ** 2 * (g_r - 1) * np.sin(q * r) / (q * r), r)\n\n if method == 'al':\n pre_factor = np.sqrt(x_a * x_b) * 4 * np.pi * rho\n partial_sq = (integral*pre_factor) + int(e1==e2)\n num += (f_a*f_b) * (partial_sq+1) * np.sqrt(x_a*x_b)\n elif method == 'fz':\n pre_factor = 4 * np.pi * rho\n partial_sq = (integral*pre_factor) + 1\n num += (x_a*f_a*x_b*f_b) * (partial_sq)\n S[i] = (num/(denom**2))\n return Q, S","title":""},{"docid":"7b75b639d5883703a6a503ff70d28aa3","score":"0.48729777","text":"def symmetric_triangle(n: int = None, **kwargs) -> list:\n n = int(fabs(n)) if n is not None else 2\n\n if n == 2:\n triangle = [1, 1]\n\n if n > 2:\n if n % 2 == 0:\n front = [i + 1 for i in range(0, floor(n / 2))]\n triangle = front + front[::-1]\n else:\n front = [i + 1 for i in range(0, floor(0.5 * (n + 1)))]\n triangle = front.copy()\n front.pop()\n triangle += front[::-1]\n\n if kwargs.pop(\"weighted\", False):\n triangle_sum = npSum(triangle)\n triangle_weights = triangle / triangle_sum\n return triangle_weights\n\n return triangle","title":""},{"docid":"be678b1f1a4a5d2a66153e3294cd2525","score":"0.48695523","text":"def gen_triangle_nums(limit=None):\n n = 1\n while not limit or n < limit:\n yield n*(n+1)/2\n n += 1","title":""},{"docid":"15cb6d38612b2981bbdf69f27fb66308","score":"0.48652288","text":"def simulate(self, n, surv_df=False):\n raise NotImplementedError","title":""},{"docid":"dd4b3852ddd5b550df11103dbbd3184f","score":"0.48641437","text":"def ggpl_zstair(dx,dy,dz): \n\tvertex = [[0,0],[0,0.5],[2,0.5],[1,0]]\n\tcells = [[1,2,3,4]]\n\tpolls = None\n\t\"\"\"creation of the first step\"\"\"\n\txstep = MKPOL([vertex, cells, 1])\n\tstep = PROD([QUOTE([3]),xstep])\n\t\"\"\"calculation of the height of the ramps\"\"\"\n\trampeHeight = math.ceil(dz/2)\n\t\"\"\"calculation of the number of the steps according to the dimension of the box\"\"\"\n\tnumStep = math.ceil(dx)\n\t\"\"\"creation of the 2 ramps\"\"\"\n\txRampe= step\n\txRampe2= xRampe\n\tfor i in range(int(numStep)-3):\n\t\txRampe = STRUCT([xRampe,T([2,3])([1,0.5]),xRampe])\n\t\txRampe2 = STRUCT([xRampe2,T([2,3])([1,0.5]),xRampe2])\n\t\"\"\"creation of the platform on the last step\"\"\"\n\tfinalStep = CUBOID([dx,2,0.5])\n\t\"\"\"concatenation of the ramps with the platform\"\"\"\n\txRampe = STRUCT([xRampe,T([2,3])([(numStep-2)*1,(numStep-2)*0.5]),finalStep])\n\txRampe2 = STRUCT([xRampe2,T([2,3])([(numStep-3)*1,(numStep-3)*0.5]),finalStep])\n\t\"\"\"rotate the second ramp of 180 degrees\"\"\"\n\txRampe2= R([1,2])(PI)(xRampe2)\n\t\"\"\"create and display the box\"\"\"\n\tbox = SKEL_1(CUBOID([dx,dy,dz]))\n\tresult = STRUCT([box,xRampe])\n\t\"\"\"concatenation of the 2 ramps and display of the result\"\"\"\n\tresult = STRUCT([result,T([1,2,3])([dx,dy-1,(numStep-2)*0.5]),xRampe2])\n\tVIEW(result)\n\treturn result","title":""}],"string":"[\n {\n \"docid\": \"cf3f839797ef63cebb2f18a384cec215\",\n \"score\": \"0.60831946\",\n \"text\": \"def chebpts(n):\\r\\n\\r\\n # Special case (no points)\\r\\n if n == 0:\\r\\n x = []\\r\\n w = [] \\r\\n v = []\\r\\n t = []\\r\\n # Special case (single point)\\r\\n elif n == 1:\\r\\n x = 0 \\r\\n w = 2 \\r\\n v = 1 \\r\\n t = np.pi/2\\r\\n \\r\\n else:\\r\\n # Chebyshev points:\\r\\n m = n - 1\\r\\n # (Use of sine enforces symmetry.)\\r\\n x = np.sin(np.pi*(np.r_[-m:m+1:2]/(2*m)))\\r\\n \\r\\n # [TODO] how to do a nargout in python?\\r\\n # Quadrature weights: \\r\\n w = quadwts.quadwts(n)\\r\\n \\r\\n # Barycentric weights:\\r\\n v = barywts.barywts(n)\\r\\n \\r\\n # Angles:\\r\\n t = angles.angles(n);\\r\\n\\r\\n return x, w, v, t\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a1e81c4047e3b439e5df8ea217f0d874\",\n \"score\": \"0.6047414\",\n \"text\": \"def climbStairs2(n):\\n p = 1 \\n q = 1\\n for i in xrange(2, n + 1):\\n tmp = q\\n q = p + tmp\\n p = tmp\\n return q\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7e1fe757d7344fa36a4106e03939d381\",\n \"score\": \"0.6005188\",\n \"text\": \"def qft(n: int) -> qiskit.circuit.Gate:\\n def rotations(my_circuit: qiskit.circuit.Gate, m: int):\\n if m == 0:\\n return my_circuit\\n else:\\n my_circuit.h(m-1) #Add a Haddamard gate to the most significant qubit\\n \\n for i in range(m-1):\\n my_circuit.crz(pi/(2**(m-1-i)), i, m-1)\\n\\n rotations(my_circuit, m-1) \\n \\n my_circuit = qiskit.QuantumCircuit(n, name='QFT')\\n \\n rotations(my_circuit, n)\\n\\n for m in range(n//2):\\n my_circuit.swap(m, n-m-1)\\n\\n return my_circuit.to_gate()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bbaac5247bdaabdd669fc051f1302807\",\n \"score\": \"0.5952135\",\n \"text\": \"def speye(n):\\n r = range(n)\\n return spmatrix(1.0, r, r)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"581d6fb3db6977e2460bc5b9a347b985\",\n \"score\": \"0.5816251\",\n \"text\": \"def trianglequadrature(n):\\n\\n x00,w00 = scipy.special.orthogonal.p_roots(n)\\n x01,w01 = scipy.special.orthogonal.j_roots(n,1,0)\\n x00s = (x00+1)/2\\n x01s = (x01+1)/2\\n w = numpy.outer(w01, w00).reshape(-1,1) / 8 # a factor of 2 for the legendres and 4 for the jacobi10\\n x = numpy.outer(x01s, numpy.ones(x00s.shape)).reshape(-1,1)\\n y = numpy.outer(1-x01s, x00s).reshape(-1,1)\\n return numpy.hstack((x, y)), w\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5b57c334762796d651f900b09c50d022\",\n \"score\": \"0.5796928\",\n \"text\": \"def bezier_curve_range(n, points):\\n for i in range(n):\\n t = i / float(n - 1)\\n yield bezier(t, points)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4f70f34deecb57382c3eed0fad8ccb2a\",\n \"score\": \"0.57019246\",\n \"text\": \"def Stair(n):\\n r = []\\n u = [0]\\n\\n for i in xrange(1,n-1,2):\\n r.append(i)\\n r.append(i-1)\\n u.append(i+1)\\n u.append(i)\\n\\n if n%2:\\n r.append(n-1)\\n else:\\n r.append(n-1)\\n r.append(n-2)\\n u.append(n-1)\\n\\n positions = [((i+1)//2,i//2) for i in xrange(n)]\\n o = Origami(r,u,as_tuple=True,positions=positions,name=\\\"Stair origami with %d squares\\\" %n)\\n return o\",\n \"title\": \"\"\n },\n {\n \"docid\": \"98fd71083614979ceec006e94a3a8aa7\",\n \"score\": \"0.5669432\",\n \"text\": \"def climbStairs(self, n):\\n \\n steps = [1,2]\\n for i in range(n-2):\\n steps.append(steps[-2]+steps[-1])\\n \\n return steps[n-1]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bb84d8f90a64502535d53641faa5e8f1\",\n \"score\": \"0.56559414\",\n \"text\": \"def generate_fibonacci_spiral_hemisphere(n):\\n phi = (1 + 5 ** 0.5) / 2\\n coordinates = []\\n # We generate one more coordinate than we actually need, because the first point of the fibonacci spiral lies in\\n # the (y, z)-plane and is therefore useless to center fourier support of a wavelet around.\\n N = n + 1\\n\\n for i in range(N):\\n lat = math.asin(2*i/(2*N + 1))\\n lon = 2*math.pi*i*(1/phi)\\n\\n # swap x and z since we want a hemisphere with (1, 0, 0) as north pole.\\n z, y, x = latlon_to_xyz(lat, lon)\\n coordinates.append( (x, y, z) )\\n\\n return coordinates[1:]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a668db7abcab2b4dd24fdb2377c4baa3\",\n \"score\": \"0.5645339\",\n \"text\": \"def qft_gate_sequence(n=1, swapping=True):\\n\\n if n < 1:\\n raise ValueError(\\\"Minimum value of n can be 1\\\")\\n\\n qc = QubitCircuit(n)\\n if n == 1:\\n qc.add_gate(\\\"SNOT\\\", targets=[0])\\n else:\\n for i in range(n):\\n qc.add_gate(\\\"SNOT\\\", targets=[i])\\n for j in range(2, n - i + 1):\\n qc.add_gate(r\\\"CPHASE\\\", targets=[i], controls=[i + j - 1],\\n arg_label=r\\\"{\\\\pi/2^{%d}}\\\" % (j - 1),\\n arg_value=numpy.pi / (2 ** (j - 1)))\\n if swapping is True:\\n for i in range(n // 2):\\n qc.add_gate(r\\\"SWAP\\\", targets=[i, n - 1 - i])\\n\\n return qc\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e1ff6c3c8a4083b6b090d45c48ecf929\",\n \"score\": \"0.5613465\",\n \"text\": \"def spirals(n_points, noise=.5):\\n\\n n = np.sqrt(np.random.rand(n_points, 1)) * 780 * (2 * np.pi) / 360\\n d1x = -np.cos(n) * n + np.random.rand(n_points, 1) * noise\\n d1y = np.sin(n) * n + np.random.rand(n_points, 1) * noise\\n return (np.vstack((np.hstack((d1x, d1y)), np.hstack((-d1x, -d1y)))),\\n np.hstack((np.zeros(n_points), np.ones(n_points))))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1baf6e88d4e92ebccd44ea8ca1463039\",\n \"score\": \"0.556967\",\n \"text\": \"def spread_quaternions(points,num=100,quats_per_step=100):\\n #cria uma matrix de zeros num por 4\\n quats = np.zeros((num,4))\\n #print quats\\n # cria 'num' matrizes, cada uma com points.shape[0] linhas e 3 colunas\\n rot_points = np.zeros((num,points.shape[0],3))\\n #print rot_points\\n #a primeira posição de quats fica =\\n quats[0,:] = [0,0,0,1]\\n #print quats\\n # primeiro conjunto de matrizes fica igual aos points\\n rot_points[0,:,:] = points\\n #print rot_points\\n for ix in range(1,num):\\n # criar quats_per_step quaterniões aleatorios \\n rand_quats = random_quaternions(quats_per_step) \\n # fazer a rotação dos pontos usando os quaterniões aleatorios\\n positioned = rotate_points(points,rand_quats)\\n # ver as distancias (retorna já os mais proximos!)\\n dists = point_dists(rot_points[:ix],positioned)\\n # ir buscar o maximo das distancias mais proximas\\n new_rot = np.argmax(dists)\\n \\n quats[ix,:]=rand_quats[new_rot,:]\\n rot_points[ix,:,:] = positioned[new_rot,:,:]\\n print \\\"number of quaternions: \\\",len(quats) \\n return quats,rot_points\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0295ab84e67b7afcea16bacaf65f712e\",\n \"score\": \"0.55645245\",\n \"text\": \"def make_corner_seq(n):\\n seq = [1]\\n step_size = 2\\n while len(seq) < n:\\n for i in range(4):\\n seq.append(seq[-1] + step_size)\\n step_size += 2\\n return seq\",\n \"title\": \"\"\n },\n {\n \"docid\": \"92851d156b088fe7335f99405bfd890b\",\n \"score\": \"0.5559808\",\n \"text\": \"def Towers(n,fr,to,spare):\\n if n ==1:\\n printMove(fr,to)\\n else:\\n Towers(n-1,fr,spare,to)\\n Towers(1,fr,to,spare)\\n Towers(n-1,spare,to,fr)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9da986e885ae9cea60daca210fb2b528\",\n \"score\": \"0.5547893\",\n \"text\": \"def randpoints(n, hw=1000., hh=1000.):\\n P = [(i, uniform(-hw,-hw/4), uniform(-hh,hh)) for i in range(n//2)]\\n Q = [(i, uniform(hw/4, hw), uniform(-hh,hh)) for i in range(n//2,n//1)]\\n \\n return P,Q\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1451e624529b62f6e70ee9c2303e3859\",\n \"score\": \"0.54642177\",\n \"text\": \"def generate_tri_seq(N, t):\\n for i in range(1, N + 1):\\n t.add(i * (i + 1) / 2)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d0c470728e0f4965d142190c20f437da\",\n \"score\": \"0.54572886\",\n \"text\": \"def get_spline_curve(points, n=11):\\n order = len(points) - 1\\n coef = Utils.pascal_triangle_row(order)\\n offset = 1.0 / (n-1)\\n curve_points = []\\n curve_points.append(points[0]) # add start point as first curve point\\n # add n-2 curve points in middle\\n for factor in range(1, n-1):\\n t = offset * factor\\n x, y = 0.0, 0.0\\n for i in range(order+1):\\n x += coef[i] * (1-t)**(order-i) * t**(i) * points[i][0]\\n y += coef[i] * (1-t)**(order-i) * t**(i) * points[i][1]\\n curve_points.append((x, y))\\n curve_points.append(points[-1]) # add end point as last curve point\\n return curve_points\",\n \"title\": \"\"\n },\n {\n \"docid\": \"27395edd4876511e4af24e371086e207\",\n \"score\": \"0.54327834\",\n \"text\": \"def _triangular(n):\\n return sum(range(n + 1))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a1ce280c30a9b4f6c2f41c813b9c2bac\",\n \"score\": \"0.5419874\",\n \"text\": \"def generate_vertices(self):\\n self.vertices = []\\n self.refinement = np.zeros(self.tri.shape[0],dtype=int)\\n for n,tri in enumerate(self.tri):\\n limits = []\\n k1, k2, k3 = tri\\n if np.abs(k1-k2-k3) <= self.dk or np.any(tri == self.dk): # configurations with non-cubical integration volume\\n nstep = self.nstep[1]\\n else: # cubic integration volume\\n nstep = self.nstep[0]\\n if k3*1./(k1+k2) < self.squeezed_cut: # highly squeezed configurations\\n nstep = self.nstep[2]\\n if (k2+k3)*1./k1 <= self.collinear_cut: # collinear (or close to coll.) configurations\\n nstep = self.nstep[2]\\n self.refinement[n] = nstep\\n for x1 in range(nstep):\\n for x2 in range(nstep):\\n q1 = k1 - self.dk*1./2 + self.dk*1./(nstep-1)*x1\\n q2 = k2 - self.dk*1./2 + self.dk*1./(nstep-1)*x2\\n q3min = max(k3-self.dk*1./2,abs(q1-q2))\\n q3max = min(k3+self.dk*1./2,q1+q2)\\n if abs(q3min-q3max) < 1e-4:\\n limits.append([q1,q2,q3min])\\n elif q3min < q3max:\\n limits.append([q1,q2,q3min])\\n limits.append([q1,q2,q3max])\\n if np.abs(q3max-q3min-self.dk) < 1e-4:\\n for i in range(nstep-2):\\n limits.append([q1,q2,q3min+(q3max-q3min)*1./(nstep-1)*(i+1)])\\n elif np.abs(q3max-q3min-self.dk*1./2) < 1e-4:\\n for i in range(nstep-4):\\n limits.append([q1,q2,q3min+(q3max-q3min)*1./(nstep-3)*(i+1)])\\n if nstep == 2 and self.midpoint:\\n limits.append([k1,k2,k3])\\n self.vertices.append(np.unique(np.array(limits),axis=0))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9e8590812ec69b284ce1f880a3e11704\",\n \"score\": \"0.54086983\",\n \"text\": \"def squad(self):\\n raise NotImplementedError()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"85f33a9c2f7587a21a1e9f1e447bb1f6\",\n \"score\": \"0.5399124\",\n \"text\": \"def spiral(n):\\r\\n \\r\\n total = 1\\r\\n for n in range(3, spiral_range + 1, 2):\\r\\n # Every turn in the spiral adds four terms.\\r\\n ur = n * n # up-right term\\r\\n ul = n * n - n + 1 # up-left term\\r\\n dl = n * n - 2 * n + 2 # down-left term\\r\\n dr = n * n - 3 * n + 3 # down-right term\\r\\n subtotal = ur + ul + dl + dr\\r\\n total += subtotal\\r\\n return total\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1dfbd8a3ff8c4a0a3bd98f5d09863011\",\n \"score\": \"0.5392255\",\n \"text\": \"def quarters(n):\\n if n<25:\\n return dimes(n)\\n else:\\n return quarters(n-25)+dimes(n)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0e0a61ebc75e11715c7eaf71a3efe519\",\n \"score\": \"0.53626245\",\n \"text\": \"def triangular(n):\\n triang = n * (n + 1) / 2\\n return triang\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1fb3d6e69021477f7cc222bbc4d1f7c8\",\n \"score\": \"0.5330278\",\n \"text\": \"def stepPatternForStar(n, step): # draw platform independent\\n\\ti = 0\\n\\tindexList = []\\n\\t# Skip around the points of the n-gon to create the draw-path for the star.\\n\\twhile True:\\n\\t\\tbreakAfterThis = False\\n\\t\\tnextIndex = (i*step)%n\\n\\t\\tif nextIndex in indexList:\\n\\t\\t\\tbreakAfterThis = True\\n\\t\\tindexList.append(nextIndex)\\n\\t\\tif breakAfterThis:\\n\\t\\t\\tbreak\\n\\t\\ti = i + 1\\n\\treturn indexList\",\n \"title\": \"\"\n },\n {\n \"docid\": \"94a2074d913e53f0afa1167ea748bcf2\",\n \"score\": \"0.53275067\",\n \"text\": \"def make_quad(points, row_size, col_size):\\n # Start with generating a zig-zag shape in row direction and then take its reverse\\n new_points = make_zigzag(points, row_size)\\n new_points.reverse()\\n\\n # Start generating a zig-zag shape in col direction\\n forward = True\\n for row in range(0, row_size):\\n temp = []\\n for col in range(0, col_size):\\n temp.append(points[row + (col * row_size)])\\n if forward:\\n forward = False\\n else:\\n forward = True\\n temp.reverse()\\n new_points += temp\\n\\n return new_points\",\n \"title\": \"\"\n },\n {\n \"docid\": \"271fce1869ad21ffd32616edd4bf1529\",\n \"score\": \"0.5291062\",\n \"text\": \"def _generate_segment(self, n: 'int', basis: 'ndarray',\\n geometry: 'ndarray'):\\n def out(x, y):\\n \\\"\\\"\\\"Test if given point is outside the window.\\\"\\\"\\\"\\n return x > 1 or x < -1 or y > 1 or y < - 1\\n\\n delta = 1 / n\\n fwd_x, fwd_y = self._init_curve_algorithm(basis, geometry, delta)\\n dim = basis.shape[0]\\n\\n prev_out = True\\n prev_point = None\\n for _ in range(n+1):\\n if out(fwd_x[0], fwd_y[0]):\\n if not prev_out: # Leaving the window\\n self._cr.line_to(*self.resolution_transform(clip_line(\\n [prev_point, (fwd_x[0], fwd_y[0])])[0]))\\n self._cr.stroke()\\n prev_out = True\\n else:\\n if prev_out: # Entering the window\\n if prev_point is None:\\n self._cr.move_to(\\n *self.resolution_transform((fwd_x[0], fwd_y[0])))\\n else:\\n point_at_window = clip_line(\\n [(fwd_x[0], fwd_y[0]), prev_point])[0]\\n self._cr.move_to(\\n *self.resolution_transform(point_at_window))\\n self._cr.line_to(\\n *self.resolution_transform((fwd_x[0], fwd_y[0])))\\n prev_out = False\\n else: # Already inside window\\n self._cr.line_to(\\n *self.resolution_transform((fwd_x[0], fwd_y[0])))\\n\\n prev_point = (fwd_x[0], fwd_y[0])\\n\\n for i in range(dim-1):\\n fwd_x[i] += fwd_x[i+1]\\n fwd_y[i] += fwd_y[i+1]\\n self._cr.stroke()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"408ae05ac1207400397e5a51dd26fcd9\",\n \"score\": \"0.52766865\",\n \"text\": \"def _get_quadrature_points(n, a, b):\\n x, w = roots_legendre(n)\\n x = np.real(x)\\n\\n # Legendre domain is [-1, 1], convert to [a, b]\\n scalar = (b - a) * 0.5\\n return scalar * (x + 1) + a, scalar * w\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e1fc684c5ccc1c8f12787a0f053ffc13\",\n \"score\": \"0.5271362\",\n \"text\": \"def Fan(self, n, deg_three_verts=False):\\n f = graphs.WheelGraph(n)\\n if n>2:\\n f.delete_edge(1,n-1)\\n if deg_three_verts:\\n f.allow_multiple_edges(True)\\n f.add_edges([(0,1),(0,n-1)])\\n return Sandpile(f,0)\\n elif n==1:\\n return Sandpile(f,0)\\n elif n==2:\\n if deg_three_verts:\\n return Sandpile({0:{1:3}, 1:{0:3}})\\n else:\\n return Sandpile(f,0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c629243a09bf6213500f9425dff9ec1b\",\n \"score\": \"0.5268188\",\n \"text\": \"def test_qft_dagger(self):\\n n = 5\\n qsve = QSVE(np.identity(4))\\n qreg = QuantumRegister(n)\\n circ = QuantumCircuit(qreg)\\n qsve._iqft(circ, qreg)\\n\\n print(circ)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bce381020721bdaf1324a6be4e842c2d\",\n \"score\": \"0.52361876\",\n \"text\": \"def triangs(self):\\n return self.polys(3)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6243f618cc6855274d65b3b151d1d984\",\n \"score\": \"0.52284604\",\n \"text\": \"def ten_pairs(n):\\n \\\"*** YOUR CODE HERE ***\\\"\\n return ten_pairs_helper(n, [0,0,0,0,0,0,0,0,0,0])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cf0ab0e6356867b0ac0c52d8570a1c11\",\n \"score\": \"0.52240753\",\n \"text\": \"def triangle(n):\\n T = {'sink':{}}\\n for i in range(n):\\n for j in range(n-i):\\n T[(i,j)] = {}\\n if i<n-j-1:\\n T[(i,j)][(i+1,j)] = 1\\n T[(i,j)][(i,j+1)] = 1\\n if i>0:\\n T[(i,j)][(i-1,j+1)] = 1\\n T[(i,j)][(i-1,j)] = 1\\n if j>0:\\n T[(i,j)][(i,j-1)] = 1\\n T[(i,j)][(i+1,j-1)] = 1\\n d = len(T[(i,j)])\\n if d<6:\\n T[(i,j)]['sink'] = 6-d\\n T = sandpile(T,'sink')\\n pos = {}\\n for x in T.nonsink_vertices():\\n coords = list(x)\\n coords[0]+=1/2*coords[1]\\n pos[x] = coords\\n pos['sink'] = (-1,-1)\\n T.set_pos(pos)\\n return T\",\n \"title\": \"\"\n },\n {\n \"docid\": \"61d436f0aa397e103d7d1b4d6f6fcd66\",\n \"score\": \"0.5217978\",\n \"text\": \"def squareSpiral(n_squares=60, sep_degrees=5, init_length=5, increment_length=5):\\n for s in range(n_squares):\\n square(init_length + increment_length*s)\\n rt(sep_degrees)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ec088477b33913dca17a9e20042eb6f6\",\n \"score\": \"0.5209428\",\n \"text\": \"def chain(\\n n: int = 4,\\n r: float = 1.0,\\n) -> tuple[list[str], np.ndarray, str]:\\n\\n xyz = np.zeros((n, 3))\\n atoms = [\\\"H\\\"] * n\\n\\n z = np.arange(-(n - 1) / 2, (n) / 2) * r\\n assert len(z) == n\\n assert sum(z) == 0.0\\n\\n xyz[:, 2] = z\\n\\n description = \\\"H\\\" + str(n) + \\\" 1D chain, \\\" + str(r) + \\\" Angstroms\\\\n\\\"\\n\\n return atoms, xyz, description\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a54530c9f4b0259be9edac076d0a4d4c\",\n \"score\": \"0.5197737\",\n \"text\": \"def generate_pascal_triangle_summation(self, n):\\n # Write your code here\\n row=[]\\n pt=[]\\n if n>12:\\n return pt\\n for i in range(n):\\n nr = []\\n for i in range(len(row)):\\n v = row[i]\\n if i>0:\\n v += row[i-1]\\n nr.append(1)\\n pt.append(\\\" \\\".join([str(x) for x in nr]))\\n row = nr\\n \\n return pt\",\n \"title\": \"\"\n },\n {\n \"docid\": \"92876a73ad5321395d42cd35f7103f1e\",\n \"score\": \"0.51925355\",\n \"text\": \"def get_trapezoid_quadrature_nodes_and_weights(n, a, b):\\n if n < 1:\\n raise ValueError(\\\"n must be at least one\\\")\\n\\n nodes = np.linspace(a, b, n)\\n dx = nodes[1] - nodes[0]\\n\\n weights = dx * np.ones(n)\\n weights[0] *= 0.5\\n weights[-1] *= 0.5\\n\\n return nodes, weights\",\n \"title\": \"\"\n },\n {\n \"docid\": \"01ebe9cf90d673f2c09d8c59cf1370f6\",\n \"score\": \"0.5177878\",\n \"text\": \"def farey_sequence(n) -> Generator[Tuple[int, int], None, None]:\\n\\ta, b, c, d = 0, 1, 1, n\\n\\tyield (a, b)\\n\\twhile c <= n:\\n\\t\\tk = (n + b) // d\\n\\t\\ta, b, c, d = c, d, (k * c - a), (k * d - b)\\n\\t\\tyield (a, b)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c1a538bb4c69d1fdb1f6228d3615d5f0\",\n \"score\": \"0.51766396\",\n \"text\": \"def get_simpsons_quadrature_nodes_and_weights(n, a, b):\\n nodes = np.linspace(a, b, n)\\n dx = nodes[1] - nodes[0]\\n weights = np.tile([2.0, 4.0], int((n + 1) / 2))\\n weights = weights[:n]\\n weights[0] = weights[-1] = 1\\n weights = (dx / 3.0) * weights\\n\\n return nodes, weights\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e332b4fde36cdbb9d0c5ebff8f563a9e\",\n \"score\": \"0.51730764\",\n \"text\": \"def newFSPRootGen(pins, n):\\n\\t#Does so by generating all canonical arrangments with newFullArrGen, and adding the ascending values using newPinPopulate.\\n\\treturn chain.from_iterable(newPinPopulate(a, pins, n) for a in newFullArrGen(pins))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1ecbf78672686ecd31b3fce64280a6b9\",\n \"score\": \"0.51591086\",\n \"text\": \"def complete_sandpile(n):\\n return Sandpile(graphs.CompleteGraph(n), 0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e5761ffa9734706078094d9bb840f183\",\n \"score\": \"0.51550394\",\n \"text\": \"def spine_tupled_SG(n):\\n base = list(range(n))\\n SG = [base]\\n def helper(L):\\n if len(L) == 1:\\n return\\n if len(L) == 2:\\n SG.append([L[0]])\\n SG.append([L[1]])\\n return\\n l = random.sample(L, k = 1)\\n r = list(set(L) - set(l))\\n l = sorted(l)\\n r = sorted(r)\\n SG.append(l)\\n SG.append(r)\\n helper(l)\\n helper(r)\\n\\n helper(base)\\n SG = (tuple(x) for x in SG)\\n return tuple(SG)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b7f82df5afb3ea6f74bb139c04e88f2e\",\n \"score\": \"0.5148555\",\n \"text\": \"def path_tupled_SG(n):\\n base = list(range(n))\\n SG = [base]\\n def helper(L):\\n if len(L) == 1:\\n return\\n if len(L) == 2:\\n SG.append([L[0]])\\n SG.append([L[1]])\\n return\\n l = [i for i in L if L.index(i) <= len(L)//2]\\n r = list(set(L) - set(l))\\n l = sorted(l)\\n r = sorted(r)\\n SG.append(l)\\n SG.append(r)\\n helper(l)\\n helper(r)\\n\\n helper(base)\\n SG = (tuple(x) for x in SG)\\n return tuple(SG)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8c81b46b3ff341efcca918340de21de5\",\n \"score\": \"0.51460874\",\n \"text\": \"def gen_vertices(n):\\n\\n k = np.arange(n) + 1\\n theta = deg2rad((2*k - 1) * (180.0/n))\\n x = np.cos(theta)\\n y = np.sin(theta)\\n dx = np.roll(x, -1) - x\\n dy = np.roll(y, -1) - y\\n dtheta = np.roll(theta, -1) - theta\\n #return zip(theta, dtheta)\\n return zip(theta, dx, dy)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9c422136d461cce6c612932adf167f25\",\n \"score\": \"0.5142337\",\n \"text\": \"def GenerateRandomQuadrantPointsSurvey(self, *args):\\n return _stomp.Map_GenerateRandomQuadrantPointsSurvey(self, *args)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3ff9680e1d5fa17cf8762debc6ea00bd\",\n \"score\": \"0.5140021\",\n \"text\": \"def spiral_simple(x_range_egu, y_range_egu, dr_egu, nth):\\n half_x = x_range_egu / 2\\n half_y = y_range_egu / 2\\n\\n r_max_egu = np.sqrt(half_x ** 2 + half_y ** 2)\\n num_ring = 1 + int(r_max_egu / dr_egu)\\n\\n x_points = []\\n y_points = []\\n for i_ring in range(1, num_ring + 2):\\n radius_egu = i_ring * dr_egu\\n angle_step = 2. * np.pi / (i_ring * nth)\\n\\n for i_angle in range(int(i_ring * nth)):\\n angle = i_angle * angle_step\\n x_egu = radius_egu * np.cos(angle)\\n y_egu = radius_egu * np.sin(angle)\\n if abs(x_egu) <= half_x and abs(y_egu) <= half_y:\\n x_points.append(x_egu)\\n y_points.append(y_egu)\\n\\n return x_points, y_points\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cb4bc5f233deba4de14f86370ea4263d\",\n \"score\": \"0.51391864\",\n \"text\": \"def __pow__(self, n):\\n r = Quaternion()\\n for i in range(n):\\n r = r * self\\n return r\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1924f2ca76e9089b586dab8e9127686f\",\n \"score\": \"0.5116036\",\n \"text\": \"def getcorners(n):\\n corners = []\\n corners.append(n * n - 3 * n + 3)\\n corners.append(n * n -2 * n + 2)\\n corners.append(n * n - n + 1)\\n corners.append(n * n)\\n return corners\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bb3ef0bdd0eab677bdd3df63d96b0899\",\n \"score\": \"0.51098365\",\n \"text\": \"def latin_hypercube(n):\\n\\n low_lim = np.arange(0, n)/n\\n up_lim = np.arange(1, n+1)/n\\n\\n #random points on grid\\n points = np.random.uniform(low=low_lim, high = up_lim, size=[2,n]).T\\n\\n np.random.shuffle(points[:,1])\\n\\n print(\\\"LHS:\\\")\\n print(points)\\n\\n return points\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a4b9ca0d2c49edd42ebbd4af6e36a41a\",\n \"score\": \"0.51075774\",\n \"text\": \"def gwfs(S, N=6):\\n return GridUtil.smooth(S, \\\"GWFS\\\", int(N))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f9a2884e25e2b9b8a82aa503955865ad\",\n \"score\": \"0.51066434\",\n \"text\": \"def compute_srideal(R, triang):\\n k = R.ngens()\\n n = len(triang[0])\\n srideal = []\\n for i in range(n):\\n for c in map(set, combinations(range(k), i + 1)):\\n # SR ideal generators must be minimal\\n for prev_c in srideal:\\n if prev_c.issubset(c):\\n break\\n else:\\n for t in map(set, triang):\\n # 1-cones in a simplex correspond to intersecting divisors\\n if c.issubset(t):\\n break\\n else:\\n srideal.append(c)\\n X = R.gens()\\n return [R.ideal(*[X[i] for i in s]) for s in srideal]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bce90c54af1dc1f2cca05a535dffbee7\",\n \"score\": \"0.51010764\",\n \"text\": \"def generateMatrix(self, n):\\n '''\\n 临场能写出\\n def generateMatrix(self, n):\\n A = [[n*n]]\\n while A[0][0] > 1:\\n A = [range(A[0][0] - len(A), A[0][0])] + zip(*A[::-1])\\n return A * (n>0)\\n 就相当了不起了\\n '''\\n matrix = []\\n s = n * n + 1 # make it starting from 1 rather than 0\\n while s > 1:\\n s, e = s - len(matrix), s\\n matrix = [range(s, e)] + zip(*matrix[::-1])\\n return matrix # spiral counter clockwise return zip(*matrix)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"143ee46b1b1eaa4aaec2524edc278990\",\n \"score\": \"0.5097594\",\n \"text\": \"def climbStairs(self, n):\\n climb = {}\\n climb[1] = 1\\n climb[2] = 2\\n for i in xrange(3, n + 1):\\n climb[i] = climb[i - 1] + climb[i - 2]\\n return climb[n]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"25defad497f6dddbb8e427e6dd2a0fde\",\n \"score\": \"0.5091647\",\n \"text\": \"def Wheel(self, n):\\n return Sandpile(graphs.WheelGraph(n),0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"97e6c2168176986341eaf055f142729e\",\n \"score\": \"0.50915474\",\n \"text\": \"def n_step(self,n=1 , plot=False):\\n for i in range(n):\\n if len(self.x) < self.N_max:\\n self.next_point()\\n self.model = GPR(kernel=self.kernel, normalize_y=True).fit(np.array(self.x).reshape(-1, 1), np.array(self.y).reshape(-1, 1))\\n else:\\n print(\\\"Optimisation terminee\\\")\\n if plot:\\n self.plot()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a0f6bde02e8aed08bc528258321e1a52\",\n \"score\": \"0.50800806\",\n \"text\": \"def sim(self, n):\\n return Results(self.draw() for _ in range(n))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"eda1fe42b0b2abaf47752f123840d80e\",\n \"score\": \"0.5056638\",\n \"text\": \"def triangle():\\n \\n triangle_points = np.linspace(0, 1, 500)\\n return signal.sawtooth(10 * np.pi * triangle_points, 0.5)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"46bd68766f6d0df76ba5505d23331eaa\",\n \"score\": \"0.50512314\",\n \"text\": \"def randQuad(n):\\n A = np.random.rand(n,n)\\n b = np.random.rand(n,1)\\n Q = np.matmul(A.transpose(), A)\\n return Q,b\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9a70183fbcc523694538fd6831c4a074\",\n \"score\": \"0.50500363\",\n \"text\": \"def generate_random(n):\\r\\n points = random.Random()\\r\\n points_list = []\\r\\n for i in range(n):\\r\\n points_list.append((round(points.uniform(0, 1), 2), round(points.uniform(0, 1), 2)))\\r\\n return (points_list)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9a5f21e6f036819b5e231c9ed6b7f496\",\n \"score\": \"0.5047165\",\n \"text\": \"def outer(self, P, n):\\n if n == 0:\\n return Point(0, 1)\\n Q = self.outer(P, n // 2)\\n Q = self.inner(Q, Q)\\n if n & 1:\\n Q = self.inner(Q, P)\\n return Q\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1e473bd0756b4788239e9c5cc9fc1e4e\",\n \"score\": \"0.50384766\",\n \"text\": \"def get_quadratic_data_sample(n, add_noise=False, x_min=-1, x_max=1, noise=0.01, pow=2):\\n\\n ### Sanity Checks ###\\n if type(n) is not int or n <= 0: raise Exception(\\\"Sample size must be a positive integer\\\")\\n if type(pow) is not int or pow % 2 != 0 or pow <= 0: raise Exception(\\\"Power must be a positive even integer \\\")\\n if x_min >= x_max: raise Exception(\\\"Min value ({}) is higher or equal than max value ({})\\\".format(x_min, x_max))\\n\\n x = uniform(x_min, x_max, n) # Points along x\\n mid = (x_max-x_min)/2 + x_min # Middle point\\n y = power((x-mid), pow) # Raise x\\n\\n if add_noise: y += (2 * random(n) - 1) * noise # Add noise to y\\n\\n # combine x and y as points in 2D plane\\n coordinates = list(zip(x,y))\\n # Return coordinates as numpy array\\n return array(coordinates, dtype=float32)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b9863ad3ae6d67a52d606522b04ddb68\",\n \"score\": \"0.5035669\",\n \"text\": \"def twelve_n_minus_ten(B):\\n n = B.num_points()\\n B14 = steiner_quadruple_system(14)\\n r = lambda i,x : i%(n-1)+(x%12)*(n-1)\\n\\n # Line 1.\\n Y = []\\n for s in B14._blocks:\\n for i in range(n-1):\\n Y.append([r(i,x) if x<= 11 else r(n-2,11)+x-11 for x in s])\\n\\n for s in B._blocks:\\n if s[-1] == n-1:\\n u,v,w,B = s\\n dd = {0:u,1:v,2:w}\\n d = lambda x:dd[x%3]\\n for b in range(12):\\n for bb in range(12):\\n bbb = -(b+bb)%12\\n for h in range(2):\\n # Line 2\\n Y.append([r(n-2,11)+1+h,r(u,b),r(v,bb),r(w,bbb+3*h)])\\n\\n for i in range(3):\\n # Line 38.3\\n Y.append([r(d(i),b+4+i), r(d(i),b+7+i), r(d(i+1),bb), r(d(i+2),bbb)])\\n\\n for j in range(12):\\n for eps in range(2):\\n for i in range(3):\\n # Line 38.4-38.7\\n Y.append([ r(d(i),j), r(d(i+1),j+6*eps ), r(d(i+2),6*eps-2*j+1), r(d(i+2),6*eps-2*j-1)])\\n Y.append([ r(d(i),j), r(d(i+1),j+6*eps ), r(d(i+2),6*eps-2*j+2), r(d(i+2),6*eps-2*j-2)])\\n Y.append([ r(d(i),j), r(d(i+1),j+6*eps-3), r(d(i+2),6*eps-2*j+1), r(d(i+2),6*eps-2*j+2)])\\n Y.append([ r(d(i),j), r(d(i+1),j+6*eps+3), r(d(i+2),6*eps-2*j-1), r(d(i+2),6*eps-2*j-2)])\\n\\n for j in range(6):\\n for i in range(3):\\n for eps in range(2):\\n # Line 38.8\\n Y.append([ r(d(i),j), r(d(i),j+6), r(d(i+1),j+3*eps), r(d(i+1),j+6+3*eps)])\\n\\n for j in range(12):\\n for i in range(3):\\n for eps in range(4):\\n # Line 38.11\\n Y.append([ r(d(i),j), r(d(i),j+1), r(d(i+1),j+3*eps), r(d(i+1),j+3*eps+1)])\\n # Line 38.12\\n Y.append([ r(d(i),j), r(d(i),j+2), r(d(i+1),j+3*eps), r(d(i+1),j+3*eps+2)])\\n # Line 38.13\\n Y.append([ r(d(i),j), r(d(i),j+4), r(d(i+1),j+3*eps), r(d(i+1),j+3*eps+4)])\\n\\n for alpha in [4,5]:\\n for ra,sa in P(alpha,6):\\n for raa,saa in P(alpha,6):\\n for i in range(3):\\n for ii in range(i+1,3):\\n # Line 38.14\\n Y.append([ r(d(i),ra), r(d(i),sa), r(d(ii),raa), r(d(ii),saa)])\\n\\n for g in range(6):\\n for eps in range(2):\\n for i in range(3):\\n for ii in range(3):\\n if i == ii:\\n continue\\n # Line 38.9\\n Y.append([ r(d(i),2*g+3*eps), r(d(i),2*g+6+3*eps), r(d(ii),2*g+1), r(d(ii),2*g+5)])\\n # Line 38.10\\n Y.append([ r(d(i),2*g+3*eps), r(d(i),2*g+6+3*eps), r(d(ii),2*g+2), r(d(ii),2*g+4)])\\n\\n else:\\n x,y,z,t = s\\n for a in range(12):\\n for aa in range(12):\\n for aaa in range(12):\\n aaaa = -(a+aa+aaa)%12\\n # Line 3\\n Y.append([r(x,a), r(y,aa), r(z,aaa), r(t,aaaa)])\\n return IncidenceStructure(12*n-10,Y,check=False,copy=False)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"45030b70ce82664a8b29a7cd4d5e8e60\",\n \"score\": \"0.5024016\",\n \"text\": \"def calculate_squirrels(n, k):\\n return k % n\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aab0bdca5c38e6ade2118152e70a3863\",\n \"score\": \"0.5020411\",\n \"text\": \"def turan_graph(n, r):\\n\\n if not 1 <= r <= n:\\n raise NetworkXError(\\\"Must satisfy 1 <= r <= n\\\")\\n\\n partitions = [n // r] * (r - (n % r)) + [n // r + 1] * (n % r)\\n G = complete_multipartite_graph(*partitions)\\n return G\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fd19bd7c6ed80a258dafc6d099b3a545\",\n \"score\": \"0.50122505\",\n \"text\": \"def sqaure(t, length):\\r\\n\\tpolygon(t, length, 4)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ed734147745756fdf920f35bee7c4210\",\n \"score\": \"0.5011693\",\n \"text\": \"def spheres(n):\\n indices = np.arange(0, n, dtype=float) + 0.5\\n golden_angle = np.pi * (1 + 5**0.5)\\n phi = np.arccos(1 - 2*indices/n)\\n theta = golden_angle * indices\\n\\n points = np.zeros((n, 3))\\n points[:, 0] = np.cos(theta) * np.sin(phi)\\n points[:, 1] = np.sin(theta) * np.sin(phi)\\n points[:, 2] = np.cos(phi)\\n\\n return points\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d34dc0411617dd44ecab62b78dc4c80d\",\n \"score\": \"0.500812\",\n \"text\": \"def S(n):\\n return n * (n + 1) // 2 # Gauss's formula\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c2c6875ce9e2df714e630f8513f97b70\",\n \"score\": \"0.50018275\",\n \"text\": \"def polys(self, n):\\n candidate = 1\\n m = 0\\n while True:\\n yield candidate\\n candidate += n - 1 + m*(n - 2)\\n m += 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6d91aa91ea884915c86013e704300bf3\",\n \"score\": \"0.49799803\",\n \"text\": \"def RCUEWG(n): # Taken from lectures\\n \\n M = np.random.random((n, n))\\n G = nx.Graph()\\n for i in range(n):\\n # notice we are using the upper triangle only\\n # that is we discard M_ii and M_ji where j<i\\n for j in range(i+1, n):\\n G.add_edge(i, j, weight=M[i, j])\\n return G\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7c40a8c9b0d434bee08fc2410fb31aca\",\n \"score\": \"0.49780157\",\n \"text\": \"def count_stair_ways(n):\\n def repeat(s):\\n if s <= 1:\\n return s \\n return repeat(s - 1) + repeat(s - 2)\\n return repeat(n + 1)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3705f8d01a520d2b16c7fe584d2db08a\",\n \"score\": \"0.49743107\",\n \"text\": \"def NRSur7dq4_samples(i):\\n\\n assert i in [0,1,2]\\n\\n if i==0:\\n chiA = [-0.2, 0.4, 0.1]\\n chiB = [-0.5, 0.2, -0.4]\\n precessing_opts = {'init_quat': [1,0,0,0],\\n 'return_dynamics': True,\\n 'init_orbphase': 0.0}\\n #'use_lalsimulation_conventions': True}\\n return [2., chiA, chiB], None, precessing_opts\\n elif i==1:\\n chiA = [-0.2, 0.4, 0.1]\\n chiB = [-0.5, 0.2, -0.4]\\n precessing_opts = {'init_quat': [1,0,0,0],\\n 'return_dynamics': True,\\n 'init_orbphase': 1.0}\\n #'use_lalsimulation_conventions': False}\\n return [3., chiA, chiB], None, precessing_opts\\n elif i==2:\\n chiA = [-0.2, 0.4, 0.1]\\n chiB = [-0.5, 0.2, -0.4]\\n precessing_opts = {'init_quat': [1,0,0,0],\\n 'return_dynamics': True,\\n 'init_orbphase': 0.0}\\n #'use_lalsimulation_conventions': True}\\n return [5., chiA, chiB], None, precessing_opts\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ec3ff4d653276546d707072f2617cc76\",\n \"score\": \"0.4971743\",\n \"text\": \"def calc_base_spline(n=50):\\n\\n x = np.linspace(0, 1, 4) # knot points to fit curve onto\\n y = [0, 0.05, 0.07, 0]\\n xvec = np.linspace(0, 1, n)\\n tck = interpolate.splrep(x, y)\\n yvec = interpolate.splev(xvec, tck, der=0)\\n\\n return xvec, yvec\",\n \"title\": \"\"\n },\n {\n \"docid\": \"59a79414a829df3d5e70cb42436b98e5\",\n \"score\": \"0.49713317\",\n \"text\": \"def first_n_cubes(n):\\r\\n output = []\\r\\n for i in range(1, (n + 1)):\\r\\n output = output + [i ** 3]\\r\\n return output\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dd8be42f6af67ea82f02aa89d4568723\",\n \"score\": \"0.49665156\",\n \"text\": \"def step(self, n):\\n return self.slice(step=n)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fbe638ee595af471754c1d06978ea601\",\n \"score\": \"0.49548364\",\n \"text\": \"def generate_pascal_triangle_binomial(self, n):\\n # Write your code here\\n row=[]\\n pt=[]\\n if n>12:\\n return pt\\n for i in range(n):\\n nr = []\\n for i in range(len(row)):\\n v = row[i]\\n if i>0:\\n v += row[i-1]\\n nr.append(1)\\n pt.append(\\\" \\\".join([str(x) for x in nr]))\\n row = nr\\n \\n return pt\",\n \"title\": \"\"\n },\n {\n \"docid\": \"95cf0a25e98934dfd769be3e84a14e81\",\n \"score\": \"0.494955\",\n \"text\": \"def triangle(n):\\n return sum([n for n in range(1,n+1)])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9c11810778197f6a56fc6e0c47b3b295\",\n \"score\": \"0.49451405\",\n \"text\": \"def _twospirals(self,n_points, noise=.75):\\n n = np.sqrt(np.random.rand(n_points,1)) * 780 * (2*np.pi)/360\\n d1x = -np.cos(n)*n + np.random.rand(n_points,1) * noise\\n d1y = np.sin(n)*n + np.random.rand(n_points,1) * noise\\n return (np.vstack((np.hstack((d1x,d1y)),np.hstack((-d1x,-d1y)))), \\n np.hstack((np.zeros(n_points),np.ones(n_points))))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fa3ab0e585ad5cf37cbb3c9fb2e4738c\",\n \"score\": \"0.4933968\",\n \"text\": \"def Make_Spiral_Matrix(n):\\n dx,dy = 1,0 # Starting increments\\n x,y = 0,0 # Starting location\\n myarray = [[None]* n for j in range(n)]\\n for i in range(n**2, 0, -1):\\n myarray[x][y] = i\\n nx,ny = x+dx, y+dy\\n if 0<=nx<n and 0<=ny<n and myarray[nx][ny] == None:\\n x,y = nx,ny\\n else:\\n dx,dy = -dy,dx\\n x,y = x+dx, y+dy\\n return np.fliplr(np.matrix(myarray).transpose())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2a9cb1abe54607768f1330ba2c81ade2\",\n \"score\": \"0.49325886\",\n \"text\": \"def generate_individual_series(N_points=3600):\\n # toggles\\n reorientation_chance = 10\\n \\n state = (0, 0, 0, 0)\\n states = [state] \\n\\n while len(states) < N_points + 2:\\n N_seg = int(sts.expon.rvs(scale=100))\\n\\n #intialize velocity and angular change\\n new_v = random.choice([0, 0.01, 0.04])\\n d_ang = 0\\n if new_v > 0:\\n d_ang = np.random.normal(0, 0.01)\\n \\n\\n # before moving. try reorientation chance.\\n rando = random.uniform(0, 1) * 100 \\n if rando < reorientation_chance and new_v > 0:\\n # reorientation make current direction equally randomly face anywhere.\\n x, y, v, ang = states[-1]\\n states[-1] = (x, y, v, np.random.uniform(- np.pi, np.pi)) \\n \\n # now generate all changes.\\n x, y, v, ang = states[-1]\\n for i in range(N_seg):\\n x, y, v, ang = (x + v * np.cos(ang),\\n y + v * np.sin(ang),\\n new_v,\\n ang+d_ang)\\n states.append((x, y, v, ang)) \\n\\n\\n # remove first point (which was dummy values) and cut down to N_points points\\n x, y, vel, thetas = zip(*states[2:N_points +2])\\n return x, y, vel, thetas\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8acf3431b2b2c9befc762fae439a990b\",\n \"score\": \"0.4931785\",\n \"text\": \"def triangulate(self, n=None, symmetry=None, centroid=True, printout=False):\\n # Inherit class arguments\\n if symmetry is None:\\n symmetry = self.symmetry\\n # Build origin and supremum vectors\\n origin = [i[0] for i in self.bounds]\\n self.origin = origin\\n supremum = [i[1] for i in self.bounds]\\n\\n self.supremum = supremum\\n\\n #TODO: Add check that len(symmetry) is equal to len(self.bounds)\\n if symmetry is None:\\n cbounds = self.bounds\\n else:\\n cbounds = copy.copy(self.bounds)\\n for i, j in enumerate(symmetry):\\n if i is not j:\\n # pop second entry on second symmetry vars\\n cbounds[i] = [self.bounds[symmetry[i]][0]]\\n # Sole (first) entry is the sup value and there is no origin\\n cbounds[i] = [self.bounds[symmetry[i]][1]]\\n if self.bounds[symmetry[i]] is not self.bounds[symmetry[j]]:\\n logging.warning(f\\\"Variable {i} was specified as \\\"\\n f\\\"symmetetric to variable {j}, however,\\\"\\n f\\\"the bounds {i} =\\\"\\n f\\\" {self.bounds[symmetry[i]]} and {j} =\\\"\\n f\\\" {self.bounds[symmetry[j]]} do not \\\"\\n f\\\"match, the mismatch was ignored in \\\"\\n f\\\"the initial triangulation.\\\")\\n cbounds[i] = self.bounds[symmetry[j]]\\n\\n\\n if n is None:\\n # Build generator\\n self.cp = self.cyclic_product(cbounds, origin, supremum, centroid,\\n printout)\\n for i in self.cp:\\n i\\n\\n try:\\n self.triangulated_vectors.append((tuple(self.origin),\\n tuple(self.supremum)))\\n except (AttributeError, KeyError):\\n self.triangulated_vectors = [(tuple(self.origin),\\n tuple(self.supremum))]\\n\\n else:\\n #Check if generator already exists\\n try:\\n self.cp\\n except (AttributeError, KeyError):\\n self.cp = self.cyclic_product(cbounds, origin, supremum,\\n centroid, printout)\\n\\n try:\\n while len(self.V.cache) < n:\\n next(self.cp)\\n except StopIteration:\\n #TODO: We should maybe append and add the possibility of\\n # of starting new triangulated domains on different\\n # complexes\\n try:\\n self.triangulated_vectors.append((tuple(self.origin),\\n tuple(self.supremum)))\\n except (AttributeError, KeyError):\\n self.triangulated_vectors = [(tuple(self.origin),\\n tuple(self.supremum))]\\n\\n\\n if printout:\\n print(\\\"=\\\" * 19)\\n print(\\\"Initial hyper cube:\\\")\\n print(\\\"=\\\" * 19)\\n # for v in self.C0():\\n # v.print_out()\\n for v in self.V.cache:\\n self.V[v].print_out()\\n\\n print(\\\"=\\\" * 19)\\n\\n return\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f115e851e2e2de8d14e7ec1a1aff0129\",\n \"score\": \"0.49307755\",\n \"text\": \"def shifted(self, n_lanes: int):\\n return StraightLane(self.p + self.n * self.w * n_lanes,\\n self.q + self.n * self.w * n_lanes, self.w)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c28a1e2d4174e47918599c899ec2af96\",\n \"score\": \"0.4926417\",\n \"text\": \"def make_series_paired(n_parcels, n_samples, n_cut_samples=40, widths=range(5,6), time_shift=3, seed=None):\\n \\n decim_factor = 5\\n n_parcels_half = n_parcels//2\\n remainder = n_parcels%2\\n time_shift = (0, time_shift) # Do not shift across parcels, only time.\\n \\n pairs = list(range(0, n_parcels-remainder))\\n if seed != None: random.seed(seed)\\n random.shuffle(pairs)\\n pairs = np.reshape(pairs, (n_parcels_half, 2))\\n \\n # Do signals for half of the parcels. Time shift the other half from the first half.\\n if seed != None: np.random.seed(seed)\\n s = randn(n_parcels_half+remainder, n_samples*decim_factor+2*n_cut_samples)\\n \\n for i in np.arange(0, n_parcels_half+remainder):\\n s[i, :] = signal.cwt(s[i, :], signal.ricker, widths)\\n \\n # Separate last sample of s in case there is an odd numbered number of parcels.\\n if remainder == 1:\\n s_rem = s[-1,:]\\n s = np.delete(s, -1, 0) # Delete last row from s.\\n s_rem = signal.hilbert(s_rem)\\n s_rem = s_rem[n_cut_samples:-n_cut_samples]\\n s_rem = scipy.signal.decimate(s_rem, decim_factor)\\n \\n s_shift = shift(s, time_shift, mode='wrap')\\n s = signal.hilbert(s)\\n s_shift = signal.hilbert(s_shift)\\n s = s[:, n_cut_samples:-n_cut_samples]\\n s_shift = s_shift[:, n_cut_samples:-n_cut_samples]\\n # Decimate the signals separately.\\n s = scipy.signal.decimate(s, decim_factor, axis=1)\\n s_shift = scipy.signal.decimate(s_shift, decim_factor, axis=1)\\n \\n # Slice the generated signals to correct indices.\\n s_comb = np.zeros((n_parcels, n_samples), dtype=complex)\\n s_comb[pairs[:,0],:] = s\\n s_comb[pairs[:,1],:] = s_shift\\n if remainder == 1:\\n s_comb[-1,:] = s_rem\\n return s_comb, pairs\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b253bb4e4fd6ca15bb0fa4beaec024d0\",\n \"score\": \"0.49240783\",\n \"text\": \"def row(n):\\n return range((n**2-n+2)//2, n*(n+1)//2+1)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"83f7a46f1411b3482bb579fc16a27b68\",\n \"score\": \"0.49209148\",\n \"text\": \"def rotation_matrices_fibonacci_spiral_unit_x(n):\\n unit_x = np.array([1, 0, 0])\\n points = generate_fibonacci_spiral_hemisphere(n)\\n rotation_matrices = [ rotation_matrix(unit_x, np.array(point)) for point in points ]\\n return rotation_matrices\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7122126ca33c8a69a05cd615d25c99a0\",\n \"score\": \"0.49208692\",\n \"text\": \"def pis(self):\\n\\n q, r, t, k, n, l = 1, 0, 1, 1, 3, 3\\n while True:\\n if 4*q + r - t < n*t:\\n yield n\\n nr = 10*(r - n * t)\\n n = ((10*(3*q + r))//t) - 10*n\\n q *= 10\\n r = nr\\n else:\\n nr = (2*q+r)*l\\n nn = (q*(7*k)+2+(r*l))//(t*l)\\n q *= k\\n t *= l\\n l += 2\\n k += 1\\n n = nn\\n r = nr\",\n \"title\": \"\"\n },\n {\n \"docid\": \"376a072f2c80c1a1f2ef22d13e381590\",\n \"score\": \"0.49205878\",\n \"text\": \"def exo4():\\n q = 30\\n Tlist = linspace(2.5, 4, q)*sigma\\n err = []\\n for i in 1: q:\\n fWT = Thresh(fW, Tlist(i))\\n f1 = PsiS(fWT)\\n err(i) = snr(f, f1)\\n plot(Tlist/ sigma, err)\\n axis('tight')\\n set_label('T/ \\\\sigma', 'SNR')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"58d1f45a679ea9d0e12b5259b3919caa\",\n \"score\": \"0.49188805\",\n \"text\": \"def generate_separated_square(lx, ly, c, p, n):\\n ys = []\\n yws = []\\n xs = []\\n xws = []\\n wx = 2*lx/n\\n wy = 2*ly/n\\n for i in range(n):\\n y, w = cheb(p, -ly + i*wy, -ly + (i+1)*wy)\\n ys.append(y)\\n yws.append(w)\\n x, w = cheb(p, -lx + i*wx, -lx + (i+1)*wx)\\n xs.append(x)\\n xws.append(w)\\n x = np.concatenate(xs)\\n xw = np.concatenate(xws)\\n y = np.concatenate(ys)\\n yw = np.concatenate(yws)\\n # stitch sides together to get nodes\\n lxl = np.repeat(lx, p*n)\\n lyl = np.repeat(ly, p*n)\\n left = np.row_stack([ -lxl + c[0], y + c[1] ])\\n right = np.row_stack([ lxl + c[0], y + c[1] ])\\n bottom = np.row_stack([ x + c[0], -lyl + c[1] ])\\n top = np.row_stack([ x + c[0], lyl + c[1] ])\\n\\n return left, right, bottom, top\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b0ef0a753696aeffac1916309bedf972\",\n \"score\": \"0.49136946\",\n \"text\": \"def _idx_to_quadruple(cls, idx):\\n\\n row, col = divmod(idx, cls.get_number())\\n id1, k1 = divmod(row-1, cls.k)\\n id2, k2 = divmod(col-1, cls.k)\\n return id1+1, k1+1, id2+1, k2+1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8f19be6fde47914afa233def65530b43\",\n \"score\": \"0.49114504\",\n \"text\": \"def get_sample_space(self, n=1000, gridding=False):\\n if gridding:\\n return self._get_grid_sample_space()\\n else:\\n return self._get_random_sample_space(n)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f6ae40f657423b9479569e79cca402ca\",\n \"score\": \"0.49063462\",\n \"text\": \"def triangle(n):\\n return (n * (n + 1)) / 2\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7f4507ce36e22217ef55cc6abe9c50b1\",\n \"score\": \"0.49051\",\n \"text\": \"def spiral(n):\\n\\n step = 20\\n direc = \\\"e\\\"\\n newddict = {\\\"e\\\": \\\"n\\\",\\n \\\"n\\\": \\\"w\\\",\\n \\\"w\\\": \\\"s\\\",\\n \\\"s\\\": \\\"e\\\"}\\n dummy = 1\\n \\n while n > 0:\\n\\n turtle.forward(step)\\n turn(direc,newddict[direc])\\n \\n if dummy % 2 == 0:\\n step += 20\\n\\n direc = newddict[direc]\\n n += -1\\n dummy += 1\\n\\n turtle.exitonclick()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cdcc57a3bb5b2480a95f16229931ea05\",\n \"score\": \"0.4898313\",\n \"text\": \"def generate(self, n):\\n candidates = []\\n scores = []\\n nv = len(self.xmin)\\n for i in np.arange(1, min(n, self._seed_size) + 1):\\n if i < 3:\\n # 1/2 points\\n seed = delayed(np.arange(1, i + 1)[:, None] * np.ones(shape=(1, nv)))\\n else:\\n # Larger seeds using recursive division\\n seed = LatinHypercube(self.xmin, self.xmax, self.use_logger, seed_size=i - 1).generate(i)\\n\\n # Create candidate designs and compute inter-site distance\\n ns = seed.shape[0]\\n x = self._tplhsdesign(n, seed, ns).compute()\\n candidates.append(x)\\n scores.append(np.min(pdist(x)))\\n\\n # Select the top-ranked candidate\\n lhd = candidates[np.argmax(scores)]\\n\\n # Scale to [xmin, xmax]\\n lhd_scaled = self.scale_to_new_domain(lhd, self.xmin, self.xmax)\\n\\n if self.use_logger:\\n self.logger.info(\\\"Latin hypercube design: generated {0} points in {1} dimensions\\\".format(n, nv))\\n\\n return lhd_scaled\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3e1466fb7c5b344c19a4f07b57f40bf7\",\n \"score\": \"0.48947856\",\n \"text\": \"def generateParenthesis(self, n: int) -> List[str]:\\n res = []\\n\\n def util(cur_str, n_lb, n_rb):\\n if n_lb > n or n_rb > n:\\n return\\n if n_lb == n_rb == n:\\n res.append(cur_str)\\n if n_lb == n_rb:\\n util(cur_str+'(', n_lb+1, n_rb)\\n if n_lb > n_rb:\\n util(cur_str+'(', n_lb+1, n_rb)\\n util(cur_str+')', n_lb, n_rb+1)\\n if n_lb < n_rb:\\n return\\n\\n util('', 0, 0)\\n return res\",\n \"title\": \"\"\n },\n {\n \"docid\": \"37cbdd59a9813cb0ecab8491be77ea9d\",\n \"score\": \"0.4889421\",\n \"text\": \"def stools3(n, source, temp1, destination):\\n \\n if n == 1:\\n model.move(source, destination)\\n if animate:\\n time.sleep(delay_btw_moves)\\n print(str(model))\\n else:\\n stools3(n - 1, source, destination, temp1)\\n model.move(source, destination)\\n if animate:\\n time.sleep(delay_btw_moves)\\n print(str(model))\\n stools3(n - 1, temp1, source, destination)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1c5ab84df5b008eb97a51ab96b08584e\",\n \"score\": \"0.48801392\",\n \"text\": \"def twospirals(n_points, noise=.5, random_state=920):\\n n = np.sqrt(np.random.rand(n_points,1)) * 600 * (2*np.pi)/360\\n d1x = -1.5*np.cos(n)*n + np.random.randn(n_points,1) * noise\\n d1y = 1.5*np.sin(n)*n + np.random.randn(n_points,1) * noise\\n return (np.vstack((np.hstack((d1x,d1y)),np.hstack((-d1x,-d1y)))),\\n np.hstack((np.zeros(n_points),np.ones(n_points))))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d081fbe2ce24f2de3f61ccd19032295b\",\n \"score\": \"0.48767608\",\n \"text\": \"def trigrid(self, n=10):\\n lam = []\\n for lam1 in range(n):\\n for lam2 in range(n - lam1):\\n lam3 = n - lam1 - lam2\\n lam.append([lam1, lam2, lam3])\\n return np.array(lam) / float(n)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"daf1a5792ee024d7757c43a80e7fa35c\",\n \"score\": \"0.48743713\",\n \"text\": \"def structure_factor(trj, Q_range=(0.5, 50), n_points=1000, framewise_rdf=False, method='fz'):\\n rho = np.mean(trj.n_atoms / trj.unitcell_volumes)\\n L = np.min(trj.unitcell_lengths)\\n\\n top = trj.topology\\n elements = set([a.element for a in top.atoms])\\n\\n compositions = dict()\\n form_factors = dict()\\n rdfs = dict()\\n\\n Q = np.logspace(np.log10(Q_range[0]),\\n np.log10(Q_range[1]),\\n num=n_points)\\n S = np.zeros(shape=(len(Q)))\\n\\n for elem in elements:\\n compositions[elem.symbol] = len(top.select('element {}'.format(elem.symbol)))/trj.n_atoms\\n form_factors[elem.symbol] = elem.atomic_number\\n\\n for i, q in enumerate(Q):\\n num = 0\\n denom = 0\\n\\n for elem in elements:\\n denom += compositions[elem.symbol] * form_factors[elem.symbol]\\n\\n for (elem1, elem2) in it.product(elements, repeat=2):\\n e1 = elem1.symbol\\n e2 = elem2.symbol\\n\\n f_a = form_factors[e1]\\n f_b = form_factors[e2]\\n\\n x_a = compositions[e1]\\n x_b = compositions[e2]\\n \\n try:\\n g_r = rdfs['{0}{1}'.format(e1, e2)]\\n except KeyError:\\n pairs = top.select_pairs(selection1='element {}'.format(e1),\\n selection2='element {}'.format(e2))\\n if framewise_rdf:\\n r, g_r = rdf_by_frame(trj,\\n pairs=pairs,\\n r_range=(0, L / 2),\\n bin_width=0.001)\\n else:\\n r, g_r = md.compute_rdf(trj,\\n pairs=pairs,\\n r_range=(0, L / 2),\\n bin_width=0.001)\\n rdfs['{0}{1}'.format(e1, e2)] = g_r\\n integral = simps(r ** 2 * (g_r - 1) * np.sin(q * r) / (q * r), r)\\n\\n if method == 'al':\\n pre_factor = np.sqrt(x_a * x_b) * 4 * np.pi * rho\\n partial_sq = (integral*pre_factor) + int(e1==e2)\\n num += (f_a*f_b) * (partial_sq+1) * np.sqrt(x_a*x_b)\\n elif method == 'fz':\\n pre_factor = 4 * np.pi * rho\\n partial_sq = (integral*pre_factor) + 1\\n num += (x_a*f_a*x_b*f_b) * (partial_sq)\\n S[i] = (num/(denom**2))\\n return Q, S\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7b75b639d5883703a6a503ff70d28aa3\",\n \"score\": \"0.48729777\",\n \"text\": \"def symmetric_triangle(n: int = None, **kwargs) -> list:\\n n = int(fabs(n)) if n is not None else 2\\n\\n if n == 2:\\n triangle = [1, 1]\\n\\n if n > 2:\\n if n % 2 == 0:\\n front = [i + 1 for i in range(0, floor(n / 2))]\\n triangle = front + front[::-1]\\n else:\\n front = [i + 1 for i in range(0, floor(0.5 * (n + 1)))]\\n triangle = front.copy()\\n front.pop()\\n triangle += front[::-1]\\n\\n if kwargs.pop(\\\"weighted\\\", False):\\n triangle_sum = npSum(triangle)\\n triangle_weights = triangle / triangle_sum\\n return triangle_weights\\n\\n return triangle\",\n \"title\": \"\"\n },\n {\n \"docid\": \"be678b1f1a4a5d2a66153e3294cd2525\",\n \"score\": \"0.48695523\",\n \"text\": \"def gen_triangle_nums(limit=None):\\n n = 1\\n while not limit or n < limit:\\n yield n*(n+1)/2\\n n += 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"15cb6d38612b2981bbdf69f27fb66308\",\n \"score\": \"0.48652288\",\n \"text\": \"def simulate(self, n, surv_df=False):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dd4b3852ddd5b550df11103dbbd3184f\",\n \"score\": \"0.48641437\",\n \"text\": \"def ggpl_zstair(dx,dy,dz): \\n\\tvertex = [[0,0],[0,0.5],[2,0.5],[1,0]]\\n\\tcells = [[1,2,3,4]]\\n\\tpolls = None\\n\\t\\\"\\\"\\\"creation of the first step\\\"\\\"\\\"\\n\\txstep = MKPOL([vertex, cells, 1])\\n\\tstep = PROD([QUOTE([3]),xstep])\\n\\t\\\"\\\"\\\"calculation of the height of the ramps\\\"\\\"\\\"\\n\\trampeHeight = math.ceil(dz/2)\\n\\t\\\"\\\"\\\"calculation of the number of the steps according to the dimension of the box\\\"\\\"\\\"\\n\\tnumStep = math.ceil(dx)\\n\\t\\\"\\\"\\\"creation of the 2 ramps\\\"\\\"\\\"\\n\\txRampe= step\\n\\txRampe2= xRampe\\n\\tfor i in range(int(numStep)-3):\\n\\t\\txRampe = STRUCT([xRampe,T([2,3])([1,0.5]),xRampe])\\n\\t\\txRampe2 = STRUCT([xRampe2,T([2,3])([1,0.5]),xRampe2])\\n\\t\\\"\\\"\\\"creation of the platform on the last step\\\"\\\"\\\"\\n\\tfinalStep = CUBOID([dx,2,0.5])\\n\\t\\\"\\\"\\\"concatenation of the ramps with the platform\\\"\\\"\\\"\\n\\txRampe = STRUCT([xRampe,T([2,3])([(numStep-2)*1,(numStep-2)*0.5]),finalStep])\\n\\txRampe2 = STRUCT([xRampe2,T([2,3])([(numStep-3)*1,(numStep-3)*0.5]),finalStep])\\n\\t\\\"\\\"\\\"rotate the second ramp of 180 degrees\\\"\\\"\\\"\\n\\txRampe2= R([1,2])(PI)(xRampe2)\\n\\t\\\"\\\"\\\"create and display the box\\\"\\\"\\\"\\n\\tbox = SKEL_1(CUBOID([dx,dy,dz]))\\n\\tresult = STRUCT([box,xRampe])\\n\\t\\\"\\\"\\\"concatenation of the 2 ramps and display of the result\\\"\\\"\\\"\\n\\tresult = STRUCT([result,T([1,2,3])([dx,dy-1,(numStep-2)*0.5]),xRampe2])\\n\\tVIEW(result)\\n\\treturn result\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":384,"cells":{"query_id":{"kind":"string","value":"3a3a2e849b00f11158ef1aeb7e55f162"},"query":{"kind":"string","value":"See the real Accessor for a description."},"positive_passages":{"kind":"list like","value":[{"docid":"db55e38a64c281fd6e8ab26938b883f2","score":"0.0","text":"def fetch_points(self, metric_name, time_start, time_end, step,\n aggregator_func=None, _fake_query_results=None):\n if not _fake_query_results:\n points = self._metric_to_points[metric_name]\n rows = []\n for ts in points.irange(time_start, time_end):\n # A row is time_base_ms, time_offset_ms, value\n row = (ts * 1000.0, 0, float(points[ts]))\n rows.append(row)\n _fake_query_results = [(True, rows)]\n return self._real_accessor.fetch_points(\n metric_name, time_start, time_end, step, aggregator_func, _fake_query_results,\n )","title":""}],"string":"[\n {\n \"docid\": \"db55e38a64c281fd6e8ab26938b883f2\",\n \"score\": \"0.0\",\n \"text\": \"def fetch_points(self, metric_name, time_start, time_end, step,\\n aggregator_func=None, _fake_query_results=None):\\n if not _fake_query_results:\\n points = self._metric_to_points[metric_name]\\n rows = []\\n for ts in points.irange(time_start, time_end):\\n # A row is time_base_ms, time_offset_ms, value\\n row = (ts * 1000.0, 0, float(points[ts]))\\n rows.append(row)\\n _fake_query_results = [(True, rows)]\\n return self._real_accessor.fetch_points(\\n metric_name, time_start, time_end, step, aggregator_func, _fake_query_results,\\n )\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"9b1f057f9b6b248713bf759651dc2c80","score":"0.7138444","text":"def get(self, ):\n\t\tpass","title":""},{"docid":"4560c322427918f793eb8b1980ad174e","score":"0.71203256","text":"def _get(self):\n raise NotImplementedError","title":""},{"docid":"4560c322427918f793eb8b1980ad174e","score":"0.71203256","text":"def _get(self):\n raise NotImplementedError","title":""},{"docid":"116d39b46b0151afdec97424ca07055e","score":"0.7103711","text":"def getter(self, *args, **kwargs): # real signature unknown\n pass","title":""},{"docid":"fd29b7f91beb0c1b813cbb854c0ad837","score":"0.6972076","text":"def get(self):\r\n raise NotImplemented","title":""},{"docid":"584b5533eedcff65f50d97263b417e04","score":"0.6880212","text":"def get(self):\n raise NotImplementedError(\"get should have been implemented.\")","title":""},{"docid":"caa2aa3b7edf4bf733f0d9c702b82957","score":"0.6811639","text":"def value(self):","title":""},{"docid":"caa2aa3b7edf4bf733f0d9c702b82957","score":"0.6811639","text":"def value(self):","title":""},{"docid":"e5a6cb973d773fc2d2c0edfc9301a023","score":"0.6799362","text":"def Value(self) -> object:","title":""},{"docid":"e5a6cb973d773fc2d2c0edfc9301a023","score":"0.6799362","text":"def Value(self) -> object:","title":""},{"docid":"7696d6f4a2f087ca81c6a76bd6d630f7","score":"0.6743941","text":"def __get__(self, *args, **kwargs): # real signature unknown\n pass","title":""},{"docid":"10b3fd49f537277d9f5b9be39f6dc847","score":"0.672471","text":"def get(self):","title":""},{"docid":"10b3fd49f537277d9f5b9be39f6dc847","score":"0.672471","text":"def get(self):","title":""},{"docid":"2297141bdf3fcc25feae8a0e1435d07f","score":"0.6699795","text":"def get(self):\n ...","title":""},{"docid":"2f3f56e17906e180ec146610945de5e0","score":"0.6695477","text":"def Get(self):","title":""},{"docid":"67a4ba360513253a76eddd5044798cb4","score":"0.6689475","text":"def get(self):\n raise MethodNotDefined()","title":""},{"docid":"93844b9f79edf46512427d6223db171a","score":"0.6682644","text":"def get(self):\n pass","title":""},{"docid":"93844b9f79edf46512427d6223db171a","score":"0.6682644","text":"def get(self):\n pass","title":""},{"docid":"93844b9f79edf46512427d6223db171a","score":"0.6682644","text":"def get(self):\n pass","title":""},{"docid":"93844b9f79edf46512427d6223db171a","score":"0.6682644","text":"def get(self):\n pass","title":""},{"docid":"9b6866e04e46a65fd1f437802bf9498e","score":"0.66704756","text":"def Get(self):\n pass","title":""},{"docid":"9b6866e04e46a65fd1f437802bf9498e","score":"0.6670471","text":"def Get(self):\n pass","title":""},{"docid":"34d8effbe8936e74eead595d9793dd04","score":"0.6670356","text":"def GetValue(self):","title":""},{"docid":"34d8effbe8936e74eead595d9793dd04","score":"0.6670356","text":"def GetValue(self):","title":""},{"docid":"a2f3ca330cfb067924f901b45e1ee6d2","score":"0.6505851","text":"def get_value(self):","title":""},{"docid":"3fdbd4fd9d31a3aac9fef9b18b68a200","score":"0.64627343","text":"def __getitem__(self):","title":""},{"docid":"3fdbd4fd9d31a3aac9fef9b18b68a200","score":"0.64627343","text":"def __getitem__(self):","title":""},{"docid":"dcefa20cf12f87220b4df30394928906","score":"0.64367425","text":"def get(self):\n raise NotImplementedError(NOT_IMPLEMENTED_MESSAGE)","title":""},{"docid":"1defc4aac572247f7ac5567ab79a4c84","score":"0.6375044","text":"def attributes(self):","title":""},{"docid":"1defc4aac572247f7ac5567ab79a4c84","score":"0.6375044","text":"def attributes(self):","title":""},{"docid":"9c7049dbb8ee75c985da127807b7bc61","score":"0.63655734","text":"def _GetValue(self, obj, attr_name):\n raise NotImplementedError()","title":""},{"docid":"94d4ea76975b6937137437f466d8f573","score":"0.6365386","text":"def Dereference(self):","title":""},{"docid":"1d267e298a58889a7ecc74667e23de92","score":"0.63451064","text":"def get(self):\n pass","title":""},{"docid":"3babe54ee1d85a4be1a4e5b70ace171e","score":"0.63309646","text":"def get(self) -> object:\n return 0","title":""},{"docid":"0d8a17dc6764aef7191072c9cd06e3d7","score":"0.6325798","text":"def value(self):\n pass","title":""},{"docid":"489f64c21aa14dac331367333e77bfa9","score":"0.6324996","text":"def GetValue(self):\r\n pass","title":""},{"docid":"489f64c21aa14dac331367333e77bfa9","score":"0.6324996","text":"def GetValue(self):\r\n pass","title":""},{"docid":"5a8d8e8fac630a1ff164761499f50011","score":"0.6316454","text":"def value(self):\n raise NotImplementedError","title":""},{"docid":"46dcd9dc80ec46d4bfc65b9c112b850e","score":"0.6279591","text":"def __get__(self, instance, owner):\n pass","title":""},{"docid":"28eea685fdebe30274b7291fa93a99ed","score":"0.62328744","text":"def __index__(self):\n return self.value","title":""},{"docid":"288d61f111c4aef669b89cbb06ea35a4","score":"0.62171674","text":"def accessor(self):\n attr = self.attr or self.name\n\n if isinstance(attr, Accessor):\n return attr\n\n return Accessor(getter=attr, setter=attr)","title":""},{"docid":"586449bc2343fea361c6bd35bf525f81","score":"0.62025666","text":"def value(self):\n raise Exception('value attribute is read-only') # TODO what is the right exception for this?","title":""},{"docid":"a959245ec0987f719cb7db7b3b1cd620","score":"0.62014097","text":"def DataMember(self) -> str:","title":""},{"docid":"90d478c1d9a201b5abeb60164e4688d8","score":"0.6195045","text":"def Item(self) -> _n_0_t_17:","title":""},{"docid":"66b0e4f1dd27dcb8ff1c289823da41b9","score":"0.6180862","text":"def __getattr__(self, attr):\n return getattr(self.reader, attr)","title":""},{"docid":"856c2224d5909675fa4baa23b44f3e16","score":"0.6173647","text":"def ValueMember(self) -> str:","title":""},{"docid":"aaee88ff46d96687184105dbbd6e3e5a","score":"0.6166939","text":"def get_value(self):\n raise NotImplementedError","title":""},{"docid":"cda552e0a37764ff2a648560d3279145","score":"0.61566144","text":"def Item(self) -> _n_0_t_6:","title":""},{"docid":"aaea567392d958285cadbbd69ce3bf83","score":"0.6150415","text":"def Item(self) -> object:","title":""},{"docid":"8304bcaf57f785034e2a639014d35963","score":"0.6135629","text":"def __getitem__(self, name): # reliably restored by inspect\n pass","title":""},{"docid":"f1b33df859786a25cd38304e85eb5d94","score":"0.6128802","text":"def __getattr__(self, name):\n ...","title":""},{"docid":"3b176e30babec8ed5de54c31963e6014","score":"0.6122868","text":"def __getitem__(self, name):\n ...","title":""},{"docid":"b27e8206afa26bba268b66b080c5442a","score":"0.6116649","text":"def __getattr__(self, attrname):\n #print attrname\n raise\n return self.cord.__dict__[attrname]","title":""},{"docid":"4f10e913586a6e7055febfa7c378af6c","score":"0.6110326","text":"def PropertyDescriptor(self) -> PropertyDescriptor:","title":""},{"docid":"4f10e913586a6e7055febfa7c378af6c","score":"0.6110326","text":"def PropertyDescriptor(self) -> PropertyDescriptor:","title":""},{"docid":"4f10e913586a6e7055febfa7c378af6c","score":"0.6110326","text":"def PropertyDescriptor(self) -> PropertyDescriptor:","title":""},{"docid":"53669388caa9a740e56ec4240f0a8179","score":"0.6104911","text":"def _get(self, at):\n raise NotImplementedError","title":""},{"docid":"981d02c8e315fdfdddc358ee4ee65427","score":"0.6102636","text":"def detail(self):\n raise NotImplementedError","title":""},{"docid":"944fb2df87fb227ccee6471df3301cdd","score":"0.6102496","text":"def __call__(self):\n raise NotImplementedError","title":""},{"docid":"e678fc0d4987c64281943fbf20b611e9","score":"0.60937124","text":"def Value(self):\n raise NotImplementedError","title":""},{"docid":"50294053955bd84ebf0c33ca637c8ee7","score":"0.60913783","text":"def retrieve(self):\n raise NotImplementedError()","title":""},{"docid":"5cd1a6affda2ac3eec58816bc19a8d71","score":"0.6087685","text":"def __getitem__(self, name):","title":""},{"docid":"961421d2e73e188a9d52b08b78717f28","score":"0.60782784","text":"def GetProperty(self, name):","title":""},{"docid":"92b848d75b2aff59720ace7f3a46bc9c","score":"0.6076875","text":"def get(self):\n raise NotImplementedError(\n 'ValueProvider.get implemented in derived classes')","title":""},{"docid":"bec599f88c5b063e9fff36d4353aaac7","score":"0.6062502","text":"def __call__(self):\n return self.value","title":""},{"docid":"7a05aab78b7615cffbfcc5405a94e13d","score":"0.60552454","text":"def __aiter__(self):\n pass","title":""},{"docid":"7a05aab78b7615cffbfcc5405a94e13d","score":"0.60552454","text":"def __aiter__(self):\n pass","title":""},{"docid":"4344a295f7c8e2fa561e0317ae6b650e","score":"0.6047716","text":"def _get(self):\n return self._value","title":""},{"docid":"c701b538396e23eba5372b332513d6b8","score":"0.60210425","text":"def properties(self):","title":""},{"docid":"c701b538396e23eba5372b332513d6b8","score":"0.60210425","text":"def properties(self):","title":""},{"docid":"c701b538396e23eba5372b332513d6b8","score":"0.60210425","text":"def properties(self):","title":""},{"docid":"c701b538396e23eba5372b332513d6b8","score":"0.60210425","text":"def properties(self):","title":""},{"docid":"c701b538396e23eba5372b332513d6b8","score":"0.60210425","text":"def properties(self):","title":""},{"docid":"77cb6bc301522d34bb54d01c7dc38c1a","score":"0.6011629","text":"def details(self):\r\n raise NotImplementedError","title":""},{"docid":"d7d9e8ddbfca2dcd57773c0c45163e03","score":"0.5982891","text":"def __getitem__(self, key):\n pass","title":""},{"docid":"95fbbe5c9d3a01a21f1a09f12acb71f1","score":"0.59764487","text":"def __getitem__(self, key):\n return self.__getattribute__(key)","title":""},{"docid":"540ebc2af2399a790354af689ba3709b","score":"0.59499943","text":"def fields(self):","title":""},{"docid":"07175f9040bf12c04ee46ffd67d0644e","score":"0.5947179","text":"def retrieve(self):\n raise NotImplemented()","title":""},{"docid":"2d79fe3a29c6c98758d5372c19158019","score":"0.594129","text":"def GetPropertyDouble(self, name):","title":""},{"docid":"1632fe64f0dd2a22fc87f845ee70c33b","score":"0.5940678","text":"def getData(self, ):","title":""},{"docid":"b2bca5196c0c107ed3e00b05593b76be","score":"0.593788","text":"def get(self, name):\n raise NotImplementedError(\"The subclass must implement\")","title":""},{"docid":"aad9269ba4ef5d47753706d32e503abc","score":"0.5936652","text":"def Item(self) -> _n_0_t_8:","title":""},{"docid":"790c2aef1d04d5a584af8e8632c0e8c5","score":"0.5935721","text":"def __getattr__(self, key):\n return object.__getattribute__(self, key)","title":""},{"docid":"013018e4ed738a13ce1f21990c06ccc3","score":"0.5930763","text":"def val(self):\n pass","title":""},{"docid":"3c57498502488ccd416434e4efc46579","score":"0.59278953","text":"def __getattr__(self, key: str) -> t.Any:\n return getattr(self.description, key)","title":""},{"docid":"422a22090d1d9b29004906830e34fa45","score":"0.59277046","text":"def get(self, key):\n pass","title":""},{"docid":"0684b21394f419d22e84286f4b935186","score":"0.5924251","text":"def __getattr__(self, name):\n return self.metadata[name]","title":""},{"docid":"0684b21394f419d22e84286f4b935186","score":"0.5924251","text":"def __getattr__(self, name):\n return self.metadata[name]","title":""},{"docid":"c70cb8495f04c15923f6dae858e995ab","score":"0.59172446","text":"def __getattr__(self, name):\r\n return getattr(self._data, name)","title":""},{"docid":"0e2a95b6147e54f88911ad7751ec2ad4","score":"0.59099627","text":"def data(self):\n return NotImplementedError()","title":""},{"docid":"46cef4a8249e7271328778a86d5c18a9","score":"0.59029305","text":"def A(self):\n raise NotImplementedError()","title":""},{"docid":"46fcaac9ed86964f2064282cf3c0bc04","score":"0.59020084","text":"def _get_age(self):\n return self.__age","title":""},{"docid":"fa9f047ef9c5d678185f2e0eb34ad467","score":"0.58975035","text":"def __getattr__(self, item):\n pass","title":""},{"docid":"ee17aeef2f914527331859da09edf351","score":"0.58961254","text":"def Reference(self):","title":""},{"docid":"87ade92f7f21c7bb164f406d19097906","score":"0.5893345","text":"def __index__(self, *args, **kwargs): # real signature unknown\n pass","title":""},{"docid":"87ade92f7f21c7bb164f406d19097906","score":"0.5893345","text":"def __index__(self, *args, **kwargs): # real signature unknown\n pass","title":""},{"docid":"87ade92f7f21c7bb164f406d19097906","score":"0.5893345","text":"def __index__(self, *args, **kwargs): # real signature unknown\n pass","title":""},{"docid":"87ade92f7f21c7bb164f406d19097906","score":"0.5893345","text":"def __index__(self, *args, **kwargs): # real signature unknown\n pass","title":""},{"docid":"87ade92f7f21c7bb164f406d19097906","score":"0.5893345","text":"def __index__(self, *args, **kwargs): # real signature unknown\n pass","title":""},{"docid":"87ade92f7f21c7bb164f406d19097906","score":"0.5893345","text":"def __index__(self, *args, **kwargs): # real signature unknown\n pass","title":""},{"docid":"87ade92f7f21c7bb164f406d19097906","score":"0.5893345","text":"def __index__(self, *args, **kwargs): # real signature unknown\n pass","title":""}],"string":"[\n {\n \"docid\": \"9b1f057f9b6b248713bf759651dc2c80\",\n \"score\": \"0.7138444\",\n \"text\": \"def get(self, ):\\n\\t\\tpass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4560c322427918f793eb8b1980ad174e\",\n \"score\": \"0.71203256\",\n \"text\": \"def _get(self):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4560c322427918f793eb8b1980ad174e\",\n \"score\": \"0.71203256\",\n \"text\": \"def _get(self):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"116d39b46b0151afdec97424ca07055e\",\n \"score\": \"0.7103711\",\n \"text\": \"def getter(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fd29b7f91beb0c1b813cbb854c0ad837\",\n \"score\": \"0.6972076\",\n \"text\": \"def get(self):\\r\\n raise NotImplemented\",\n \"title\": \"\"\n },\n {\n \"docid\": \"584b5533eedcff65f50d97263b417e04\",\n \"score\": \"0.6880212\",\n \"text\": \"def get(self):\\n raise NotImplementedError(\\\"get should have been implemented.\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"caa2aa3b7edf4bf733f0d9c702b82957\",\n \"score\": \"0.6811639\",\n \"text\": \"def value(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"caa2aa3b7edf4bf733f0d9c702b82957\",\n \"score\": \"0.6811639\",\n \"text\": \"def value(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e5a6cb973d773fc2d2c0edfc9301a023\",\n \"score\": \"0.6799362\",\n \"text\": \"def Value(self) -> object:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e5a6cb973d773fc2d2c0edfc9301a023\",\n \"score\": \"0.6799362\",\n \"text\": \"def Value(self) -> object:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7696d6f4a2f087ca81c6a76bd6d630f7\",\n \"score\": \"0.6743941\",\n \"text\": \"def __get__(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"10b3fd49f537277d9f5b9be39f6dc847\",\n \"score\": \"0.672471\",\n \"text\": \"def get(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"10b3fd49f537277d9f5b9be39f6dc847\",\n \"score\": \"0.672471\",\n \"text\": \"def get(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2297141bdf3fcc25feae8a0e1435d07f\",\n \"score\": \"0.6699795\",\n \"text\": \"def get(self):\\n ...\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2f3f56e17906e180ec146610945de5e0\",\n \"score\": \"0.6695477\",\n \"text\": \"def Get(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"67a4ba360513253a76eddd5044798cb4\",\n \"score\": \"0.6689475\",\n \"text\": \"def get(self):\\n raise MethodNotDefined()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"93844b9f79edf46512427d6223db171a\",\n \"score\": \"0.6682644\",\n \"text\": \"def get(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"93844b9f79edf46512427d6223db171a\",\n \"score\": \"0.6682644\",\n \"text\": \"def get(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"93844b9f79edf46512427d6223db171a\",\n \"score\": \"0.6682644\",\n \"text\": \"def get(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"93844b9f79edf46512427d6223db171a\",\n \"score\": \"0.6682644\",\n \"text\": \"def get(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9b6866e04e46a65fd1f437802bf9498e\",\n \"score\": \"0.66704756\",\n \"text\": \"def Get(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9b6866e04e46a65fd1f437802bf9498e\",\n \"score\": \"0.6670471\",\n \"text\": \"def Get(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"34d8effbe8936e74eead595d9793dd04\",\n \"score\": \"0.6670356\",\n \"text\": \"def GetValue(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"34d8effbe8936e74eead595d9793dd04\",\n \"score\": \"0.6670356\",\n \"text\": \"def GetValue(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a2f3ca330cfb067924f901b45e1ee6d2\",\n \"score\": \"0.6505851\",\n \"text\": \"def get_value(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3fdbd4fd9d31a3aac9fef9b18b68a200\",\n \"score\": \"0.64627343\",\n \"text\": \"def __getitem__(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3fdbd4fd9d31a3aac9fef9b18b68a200\",\n \"score\": \"0.64627343\",\n \"text\": \"def __getitem__(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dcefa20cf12f87220b4df30394928906\",\n \"score\": \"0.64367425\",\n \"text\": \"def get(self):\\n raise NotImplementedError(NOT_IMPLEMENTED_MESSAGE)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1defc4aac572247f7ac5567ab79a4c84\",\n \"score\": \"0.6375044\",\n \"text\": \"def attributes(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1defc4aac572247f7ac5567ab79a4c84\",\n \"score\": \"0.6375044\",\n \"text\": \"def attributes(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9c7049dbb8ee75c985da127807b7bc61\",\n \"score\": \"0.63655734\",\n \"text\": \"def _GetValue(self, obj, attr_name):\\n raise NotImplementedError()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"94d4ea76975b6937137437f466d8f573\",\n \"score\": \"0.6365386\",\n \"text\": \"def Dereference(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1d267e298a58889a7ecc74667e23de92\",\n \"score\": \"0.63451064\",\n \"text\": \"def get(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3babe54ee1d85a4be1a4e5b70ace171e\",\n \"score\": \"0.63309646\",\n \"text\": \"def get(self) -> object:\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0d8a17dc6764aef7191072c9cd06e3d7\",\n \"score\": \"0.6325798\",\n \"text\": \"def value(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"489f64c21aa14dac331367333e77bfa9\",\n \"score\": \"0.6324996\",\n \"text\": \"def GetValue(self):\\r\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"489f64c21aa14dac331367333e77bfa9\",\n \"score\": \"0.6324996\",\n \"text\": \"def GetValue(self):\\r\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5a8d8e8fac630a1ff164761499f50011\",\n \"score\": \"0.6316454\",\n \"text\": \"def value(self):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"46dcd9dc80ec46d4bfc65b9c112b850e\",\n \"score\": \"0.6279591\",\n \"text\": \"def __get__(self, instance, owner):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"28eea685fdebe30274b7291fa93a99ed\",\n \"score\": \"0.62328744\",\n \"text\": \"def __index__(self):\\n return self.value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"288d61f111c4aef669b89cbb06ea35a4\",\n \"score\": \"0.62171674\",\n \"text\": \"def accessor(self):\\n attr = self.attr or self.name\\n\\n if isinstance(attr, Accessor):\\n return attr\\n\\n return Accessor(getter=attr, setter=attr)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"586449bc2343fea361c6bd35bf525f81\",\n \"score\": \"0.62025666\",\n \"text\": \"def value(self):\\n raise Exception('value attribute is read-only') # TODO what is the right exception for this?\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a959245ec0987f719cb7db7b3b1cd620\",\n \"score\": \"0.62014097\",\n \"text\": \"def DataMember(self) -> str:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"90d478c1d9a201b5abeb60164e4688d8\",\n \"score\": \"0.6195045\",\n \"text\": \"def Item(self) -> _n_0_t_17:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"66b0e4f1dd27dcb8ff1c289823da41b9\",\n \"score\": \"0.6180862\",\n \"text\": \"def __getattr__(self, attr):\\n return getattr(self.reader, attr)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"856c2224d5909675fa4baa23b44f3e16\",\n \"score\": \"0.6173647\",\n \"text\": \"def ValueMember(self) -> str:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aaee88ff46d96687184105dbbd6e3e5a\",\n \"score\": \"0.6166939\",\n \"text\": \"def get_value(self):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cda552e0a37764ff2a648560d3279145\",\n \"score\": \"0.61566144\",\n \"text\": \"def Item(self) -> _n_0_t_6:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aaea567392d958285cadbbd69ce3bf83\",\n \"score\": \"0.6150415\",\n \"text\": \"def Item(self) -> object:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8304bcaf57f785034e2a639014d35963\",\n \"score\": \"0.6135629\",\n \"text\": \"def __getitem__(self, name): # reliably restored by inspect\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f1b33df859786a25cd38304e85eb5d94\",\n \"score\": \"0.6128802\",\n \"text\": \"def __getattr__(self, name):\\n ...\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3b176e30babec8ed5de54c31963e6014\",\n \"score\": \"0.6122868\",\n \"text\": \"def __getitem__(self, name):\\n ...\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b27e8206afa26bba268b66b080c5442a\",\n \"score\": \"0.6116649\",\n \"text\": \"def __getattr__(self, attrname):\\n #print attrname\\n raise\\n return self.cord.__dict__[attrname]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4f10e913586a6e7055febfa7c378af6c\",\n \"score\": \"0.6110326\",\n \"text\": \"def PropertyDescriptor(self) -> PropertyDescriptor:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4f10e913586a6e7055febfa7c378af6c\",\n \"score\": \"0.6110326\",\n \"text\": \"def PropertyDescriptor(self) -> PropertyDescriptor:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4f10e913586a6e7055febfa7c378af6c\",\n \"score\": \"0.6110326\",\n \"text\": \"def PropertyDescriptor(self) -> PropertyDescriptor:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"53669388caa9a740e56ec4240f0a8179\",\n \"score\": \"0.6104911\",\n \"text\": \"def _get(self, at):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"981d02c8e315fdfdddc358ee4ee65427\",\n \"score\": \"0.6102636\",\n \"text\": \"def detail(self):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"944fb2df87fb227ccee6471df3301cdd\",\n \"score\": \"0.6102496\",\n \"text\": \"def __call__(self):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e678fc0d4987c64281943fbf20b611e9\",\n \"score\": \"0.60937124\",\n \"text\": \"def Value(self):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"50294053955bd84ebf0c33ca637c8ee7\",\n \"score\": \"0.60913783\",\n \"text\": \"def retrieve(self):\\n raise NotImplementedError()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5cd1a6affda2ac3eec58816bc19a8d71\",\n \"score\": \"0.6087685\",\n \"text\": \"def __getitem__(self, name):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"961421d2e73e188a9d52b08b78717f28\",\n \"score\": \"0.60782784\",\n \"text\": \"def GetProperty(self, name):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"92b848d75b2aff59720ace7f3a46bc9c\",\n \"score\": \"0.6076875\",\n \"text\": \"def get(self):\\n raise NotImplementedError(\\n 'ValueProvider.get implemented in derived classes')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bec599f88c5b063e9fff36d4353aaac7\",\n \"score\": \"0.6062502\",\n \"text\": \"def __call__(self):\\n return self.value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7a05aab78b7615cffbfcc5405a94e13d\",\n \"score\": \"0.60552454\",\n \"text\": \"def __aiter__(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7a05aab78b7615cffbfcc5405a94e13d\",\n \"score\": \"0.60552454\",\n \"text\": \"def __aiter__(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4344a295f7c8e2fa561e0317ae6b650e\",\n \"score\": \"0.6047716\",\n \"text\": \"def _get(self):\\n return self._value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c701b538396e23eba5372b332513d6b8\",\n \"score\": \"0.60210425\",\n \"text\": \"def properties(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c701b538396e23eba5372b332513d6b8\",\n \"score\": \"0.60210425\",\n \"text\": \"def properties(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c701b538396e23eba5372b332513d6b8\",\n \"score\": \"0.60210425\",\n \"text\": \"def properties(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c701b538396e23eba5372b332513d6b8\",\n \"score\": \"0.60210425\",\n \"text\": \"def properties(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c701b538396e23eba5372b332513d6b8\",\n \"score\": \"0.60210425\",\n \"text\": \"def properties(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"77cb6bc301522d34bb54d01c7dc38c1a\",\n \"score\": \"0.6011629\",\n \"text\": \"def details(self):\\r\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d7d9e8ddbfca2dcd57773c0c45163e03\",\n \"score\": \"0.5982891\",\n \"text\": \"def __getitem__(self, key):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"95fbbe5c9d3a01a21f1a09f12acb71f1\",\n \"score\": \"0.59764487\",\n \"text\": \"def __getitem__(self, key):\\n return self.__getattribute__(key)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"540ebc2af2399a790354af689ba3709b\",\n \"score\": \"0.59499943\",\n \"text\": \"def fields(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"07175f9040bf12c04ee46ffd67d0644e\",\n \"score\": \"0.5947179\",\n \"text\": \"def retrieve(self):\\n raise NotImplemented()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2d79fe3a29c6c98758d5372c19158019\",\n \"score\": \"0.594129\",\n \"text\": \"def GetPropertyDouble(self, name):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1632fe64f0dd2a22fc87f845ee70c33b\",\n \"score\": \"0.5940678\",\n \"text\": \"def getData(self, ):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b2bca5196c0c107ed3e00b05593b76be\",\n \"score\": \"0.593788\",\n \"text\": \"def get(self, name):\\n raise NotImplementedError(\\\"The subclass must implement\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aad9269ba4ef5d47753706d32e503abc\",\n \"score\": \"0.5936652\",\n \"text\": \"def Item(self) -> _n_0_t_8:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"790c2aef1d04d5a584af8e8632c0e8c5\",\n \"score\": \"0.5935721\",\n \"text\": \"def __getattr__(self, key):\\n return object.__getattribute__(self, key)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"013018e4ed738a13ce1f21990c06ccc3\",\n \"score\": \"0.5930763\",\n \"text\": \"def val(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3c57498502488ccd416434e4efc46579\",\n \"score\": \"0.59278953\",\n \"text\": \"def __getattr__(self, key: str) -> t.Any:\\n return getattr(self.description, key)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"422a22090d1d9b29004906830e34fa45\",\n \"score\": \"0.59277046\",\n \"text\": \"def get(self, key):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0684b21394f419d22e84286f4b935186\",\n \"score\": \"0.5924251\",\n \"text\": \"def __getattr__(self, name):\\n return self.metadata[name]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0684b21394f419d22e84286f4b935186\",\n \"score\": \"0.5924251\",\n \"text\": \"def __getattr__(self, name):\\n return self.metadata[name]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c70cb8495f04c15923f6dae858e995ab\",\n \"score\": \"0.59172446\",\n \"text\": \"def __getattr__(self, name):\\r\\n return getattr(self._data, name)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0e2a95b6147e54f88911ad7751ec2ad4\",\n \"score\": \"0.59099627\",\n \"text\": \"def data(self):\\n return NotImplementedError()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"46cef4a8249e7271328778a86d5c18a9\",\n \"score\": \"0.59029305\",\n \"text\": \"def A(self):\\n raise NotImplementedError()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"46fcaac9ed86964f2064282cf3c0bc04\",\n \"score\": \"0.59020084\",\n \"text\": \"def _get_age(self):\\n return self.__age\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fa9f047ef9c5d678185f2e0eb34ad467\",\n \"score\": \"0.58975035\",\n \"text\": \"def __getattr__(self, item):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ee17aeef2f914527331859da09edf351\",\n \"score\": \"0.58961254\",\n \"text\": \"def Reference(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"87ade92f7f21c7bb164f406d19097906\",\n \"score\": \"0.5893345\",\n \"text\": \"def __index__(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"87ade92f7f21c7bb164f406d19097906\",\n \"score\": \"0.5893345\",\n \"text\": \"def __index__(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"87ade92f7f21c7bb164f406d19097906\",\n \"score\": \"0.5893345\",\n \"text\": \"def __index__(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"87ade92f7f21c7bb164f406d19097906\",\n \"score\": \"0.5893345\",\n \"text\": \"def __index__(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"87ade92f7f21c7bb164f406d19097906\",\n \"score\": \"0.5893345\",\n \"text\": \"def __index__(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"87ade92f7f21c7bb164f406d19097906\",\n \"score\": \"0.5893345\",\n \"text\": \"def __index__(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"87ade92f7f21c7bb164f406d19097906\",\n \"score\": \"0.5893345\",\n \"text\": \"def __index__(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":385,"cells":{"query_id":{"kind":"string","value":"633bb61656b4648540046f3aadfbf43e"},"query":{"kind":"string","value":"main function for lcoal usage"},"positive_passages":{"kind":"list like","value":[{"docid":"a8ec5a21efbccc76636cc0ff1be8f8cc","score":"0.58221775","text":"def main():\r\n test()","title":""}],"string":"[\n {\n \"docid\": \"a8ec5a21efbccc76636cc0ff1be8f8cc\",\n \"score\": \"0.58221775\",\n \"text\": \"def main():\\r\\n test()\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"08aa0c5cc07c5efe590ba89320b45dbc","score":"0.69941837","text":"def main():","title":""},{"docid":"29e1f6ab065fa2f570f2241972e9c859","score":"0.6961694","text":"def\tmain():\r\n\t\r\n\tpass","title":""},{"docid":"6a72f0523c7f4b19a3ff495c1baaa5c5","score":"0.669952","text":"def main() -> None:","title":""},{"docid":"6a72f0523c7f4b19a3ff495c1baaa5c5","score":"0.669952","text":"def main() -> None:","title":""},{"docid":"a1e1239bd97fc0c2dd7ee8ea2003aadd","score":"0.65233755","text":"def main_CL():\r\n parser = OptionParser(usage=usage(), version='1.0')\r\n parser.add_option(\"-c\", \"--cmd\", dest=\"cmd\", default=\"unknown\", help=\"What command to run.\")\r\n parser.add_option(\"-w\", \"--walk\", dest=\"walk\", default=\"none\", help=\"Scope of status to walk in the directory.\")\r\n parser.add_option(\"-s\", \"--cs\", dest=\"code\", default=\"4\", help=\"The Code version <4|4.0|4.1|4.2|all> to use.\")\r\n parser.add_option(\"-t\", \"--tcId\", dest=\"tcId\", default=\"a0Q300000000Hj9\", help=\"Tech Campaign ID in SalesForce\")\r\n parser.add_option(\"-n\", \"--num\", dest=\"num\", default=\"4000\", help=\"Max number of items to process\")\r\n parser.add_option(\"-x\", \"--parm\", dest=\"parm\", default=\"\", help=\"Parms used by a method\")\r\n parser.add_option(\"-f\", \"--file\", dest=\"file\", default=\"\", help=\"path to the file to load, current dir if just a filename\")\r\n parser.add_option(\"-q\", \"--quiet\", dest='quiet',default=\"1\", help=\"Show less info in output\")\r\n parser.add_option(\"-d\", \"--debug\", dest='debug',action=\"count\",help=\"The debug level, use multiple to get more.\")\r\n (options, args) = parser.parse_args()\r\n if options.debug > 2:\r\n print ' verbose %s\\tdebug %s' %(options.quiet, options.debug)\r\n print ' command %s\\twalk %s' %(options.cmd, options.walk)\r\n print ' version %s' %options.code\r\n print ' tcId %s' %options.tcId\r\n print ' num %s' %options.num\r\n print ' file %s' %options.file\r\n print ' args: %s' %args\r\n else:\r\n options.debug = 0\r\n crList = []\r\n version = str(options.code)\r\n \r\n if options.cmd in ['load']:\r\n loadQOR(options=options)\r\n elif options.cmd in ['dir']:\r\n loadQORDir(options=options)\r\n elif options.cmd in ['rpt']:\r\n walk_list(options=options)\r\n else:\r\n print '%s' %usage()","title":""},{"docid":"7c948d070347c04c157c9bc1a32db75f","score":"0.6512523","text":"def main(self):","title":""},{"docid":"b7ec2b67be7af2e3e3f7abf4d1854636","score":"0.6511092","text":"def main():\n core.main()","title":""},{"docid":"318cdf2f663487bb0a9d9fa8d2987875","score":"0.64981115","text":"def main():\n return 0","title":""},{"docid":"737edbcdda02609a89cb40f455a292fb","score":"0.6491304","text":"def main(args):\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"bc0d536b098278d704e13b8e318d6af5","score":"0.64139795","text":"def main():\n pass","title":""},{"docid":"59a11114512ac46a2a2d976a77d1c6d6","score":"0.63336045","text":"def main(self, *args):\n pass","title":""},{"docid":"535c6e7d32028af3cc3d681a0804815d","score":"0.631539","text":"def main(args=None):\n return 0","title":""},{"docid":"535c6e7d32028af3cc3d681a0804815d","score":"0.631539","text":"def main(args=None):\n return 0","title":""},{"docid":"535c6e7d32028af3cc3d681a0804815d","score":"0.631539","text":"def main(args=None):\n return 0","title":""},{"docid":"8795b9ca19d8f12a8d63e1f20619a3ca","score":"0.6273365","text":"def lafs():","title":""},{"docid":"5aa4372be4d7b9d84cb0f1e4c22aa424","score":"0.62235725","text":"def main():\n if not os.path.exists(\"./data/features\"):\n os.makedirs(\"./data/features\")\n make_cts()\n make_coldata()\n command = \"Rscript ./src/features/r_scripts/lfc.R\"\n os.system(command)\n return","title":""},{"docid":"bdea5fa1d9b0ba3dfa8573d74c9cd641","score":"0.6218749","text":"def main(argv):","title":""},{"docid":"2230f3b32896a1d0f35daa753ea7307c","score":"0.61689687","text":"def main():\n Main()","title":""},{"docid":"64a1a4261cea121e609f61fd60d0b36f","score":"0.6127713","text":"def main():\n return None","title":""},{"docid":"c328a8e3f0c73dfb795255c779d6bb21","score":"0.6124877","text":"def main():\n # set up the program to take in arguments from the command line","title":""},{"docid":"04688cd98d9fcf835947139440a6440f","score":"0.60574085","text":"def main():\n\n pass\n\n return None","title":""},{"docid":"9849beb2becdf68e2bf5a55ba6c8e058","score":"0.6054235","text":"def main():\n\n BASIC.run(PROGRAM)","title":""},{"docid":"9849beb2becdf68e2bf5a55ba6c8e058","score":"0.6054235","text":"def main():\n\n BASIC.run(PROGRAM)","title":""},{"docid":"9849beb2becdf68e2bf5a55ba6c8e058","score":"0.6054235","text":"def main():\n\n BASIC.run(PROGRAM)","title":""},{"docid":"dc5586b84901eecdd4033d77b1277901","score":"0.6052881","text":"def main(args):\r\n\tprint args","title":""},{"docid":"693e66b4f00edb2c4872791ea15557fe","score":"0.60299456","text":"def main():\n parser = ArgumentParser(description='추출된 오분석 패치 후보를 검증하는 스크립트')\n parser.add_argument('-c', '--corpus-dir', help='corpus dir', metavar='DIR', required=True)\n parser.add_argument('--rsc-src', help='resource source dir <default: ../rsc/src>',\n metavar='DIR', default='../rsc/src')\n parser.add_argument('--lib-path', help='khaiii shared library path', metavar='FILE', default='')\n parser.add_argument('--rsc-dir', help='resource dir', metavar='DIR', default='')\n parser.add_argument('--input', help='input file <default: stdin>', metavar='FILE')\n parser.add_argument('--output', help='output file <default: stdout>', metavar='FILE')\n parser.add_argument('--debug', help='enable debug', action='store_true')\n args = parser.parse_args()\n\n if args.input:\n sys.stdin = open(args.input, 'r', encoding='UTF-8')\n if args.output:\n sys.stdout = open(args.output, 'w', encoding='UTF-8')\n if args.debug:\n logging.basicConfig(level=logging.DEBUG)\n else:\n logging.basicConfig(level=logging.INFO)\n\n run(args)","title":""},{"docid":"25d2156a2c147b735919830a88870675","score":"0.6025334","text":"def climain():\n pass","title":""},{"docid":"f5faf6af6fd1d678aa5d61b752570c5b","score":"0.60207397","text":"def main():\n CLI.from_command_line()\n exit(0)","title":""},{"docid":"50333a46fe2be3b14f8763c7450461cc","score":"0.5991564","text":"def main(args=None):\n pass","title":""},{"docid":"2dddb624e75a16297354fe192004dae4","score":"0.5971752","text":"def main() -> None:\n pass","title":""},{"docid":"03eab569e1fa019e05e3f17a76f89d8e","score":"0.5965668","text":"def main():\n\n\ta = LedSwitcher(sys.argv[1])\n\ta.parseFile()\n\tprint(a.getResult())","title":""},{"docid":"9474d60d1ad14443e46dc45f9d255de4","score":"0.5958696","text":"def main():\n args = parse_args()","title":""},{"docid":"ac7d54f6876130c19c424c66f5c633c3","score":"0.59350556","text":"def cli():\n\n print(\"Context of the main.\")","title":""},{"docid":"0c44f7b85e1489e30026e387428624fc","score":"0.59238666","text":"def EntryPoint(self) -> _n_5_t_1:","title":""},{"docid":"d7b8a92fa493427136b876598a229cee","score":"0.5900915","text":"def main_alt():\n print \"Hello, world!\"","title":""},{"docid":"8fa7ebb63b49d9b7b6661663eb1a9990","score":"0.58937246","text":"def main():\n ### read dump\n timestep, natoms, lx, ly, xs, ys = read_dump(ifname)\n ### correct pbcs for all molecules\n correct_pbcs(xs, ys, nfil, natoms)\n ### add new beads\n #xsd, ysd, natomsd, nfild = add_beads(xs,ys,nfil,natoms)\n ### add new per/atom information\n tpe, molid = add_per_atom_info(natoms, nfil)\n ### add new bond information\n bid, btpe, b1, b2 = add_bond_information(natoms, nfil)\n ### add new angle information\n aid, atpe, a1, a2, a3 = add_angle_information(natoms, nfil)\n ### scale xs and ys\n lx *= lscale\n ly *= lscale\n xs *= lx\n ys *= ly\n ### write results to xyz file\n write_xyz(xs,ys)\n ### write results to lammps data file\n write_data(natoms, lx,ly, tpe, molid, xs, ys, bid, btpe, b1, b2, aid, atpe, a1, a2, a3,ofname)\n return","title":""},{"docid":"ed20152113aec51270e2db79970f1f50","score":"0.58698523","text":"def llc(args=None):\n args = parser.parse_args(args)\n with LogSetup(args) as log_setup:\n march = get_arch_from_args(args)\n ir_module = api.llvm_to_ir(args.source)\n do_compile([ir_module], march, log_setup.reporter, log_setup.args)","title":""},{"docid":"ba8ad90da83a3ae86af26ef07a134e88","score":"0.5863602","text":"def test_lc_file():\n lc_from_file(lc, cache, X, y, F, wf, P, wp)","title":""},{"docid":"6b54c30c3c8ce763241d1d10b860290b","score":"0.58604974","text":"def main():\n\n read_config(os.path.join(os.path.dirname(os.path.realpath(__file__)), \"cupp.cfg\"))\n\n parser = get_parser()\n args = parser.parse_args()\n\n if not args.quiet:\n print_cow()\n\n if args.version:\n version()\n elif args.interactive:\n interactive()\n elif args.download_wordlist:\n download_wordlist()\n elif args.alecto:\n alectodb_download()\n elif args.improve:\n improve_dictionary(args.improve)\n else:\n parser.print_help()","title":""},{"docid":"6e57c8a0092568cb746b76b654f5c47f","score":"0.58221513","text":"def main() -> None:\n\n new_location_main(sys.argv[1:])","title":""},{"docid":"945a136452b0e0f7d5cc4dc0c0dc227c","score":"0.5822095","text":"def main():\n print(\"Welcome to the XY77 Battering Ram\")\n\n state = get_vault_state()\n print(\"State acquired. Let's start.\")\n\n print(\"\\n**History Layer**\")\n history_layer(state)\n\n print(\"\\n**Code Layer**\")\n code_layer(state)\n\n print(\"\\n**Switches Layer**\")\n switches_layer(state)\n\n print(\"\\n**Button Layer**\")\n button_layer(state)\n\n print(\"Layers bypassed.\")\n print(\"Wait\", state['suspicion level'],\n \"seconds or more to allow suspicion level to dissipate.\")","title":""},{"docid":"ab7c7f19a627fee85f5b4de482ebcb8d","score":"0.58100647","text":"def main():\n ibc_nlp_classification()","title":""},{"docid":"be5ec6cfb53f8bc192c6396a7b0c49a2","score":"0.5809807","text":"def main():\n User = os.environ.get(\"USER\", \"unknown\")\n Host = os.environ.get(\"HOSTNAME\",\"unknown\")\n # push User, host and command line on to XALT_Stack\n XALT_Stack.push(\"User: \" + User)\n XALT_Stack.push(\"Host: \" + Host)\n sA = []\n sA.append(\"CommandLine:\")\n for v in sys.argv:\n sA.append('\"'+v+'\"')\n\n s = \" \".join(sA)\n XALT_Stack.push(s)\n\n try:\n uuid = sys.argv[ 1]\n status = sys.argv[ 2]\n wd = sys.argv[ 3]\n syshost = sys.argv[ 4]\n execname = sys.argv[ 5]\n xaltobj = sys.argv[ 6]\n build_epoch = sys.argv[ 7]\n linklineFn = sys.argv[ 8]\n funclist = sys.argv[ 9]\t\t\t# ftrack2015\n resultFn = sys.argv[10] # ftrack2015\n\n if (execname.find(\"conftest\") != -1):\n return 1\n \n hash_line = capture(['sha1sum', execname]) \n if (hash_line.find(\"No such file or directory\") != -1):\n return 1\n hash_id = hash_line.split()[0]\n\n # Step one clean up linkline data\n sA = cleanup(xaltobj, linklineFn)\n sC = cleanfunc(funclist)\t\t\t# ftrack2015\n \n resultT = {}\n resultT['uuid'] = uuid\n resultT['link_program'] = extract_compiler()\n resultT['build_user'] = User\n resultT['exit_code'] = int(status)\n resultT['build_epoch'] = float(build_epoch)\n resultT['exec_path'] = os.path.abspath(execname)\n resultT['hash_id'] = hash_id\n resultT['wd'] = wd\n resultT['build_syshost'] = syshost\n resultT['func_list'] = sC\t\t#ftrack2015\n resultT['linkA'] = sA\n \n xfer = XALT_transmission_factory.build(XALT_TRANSMISSION_STYLE,\n syshost, \"link\", resultFn)\n xfer.save(resultT)\n\n except Exception as e:\n print(\"XALT_EXCEPTION(xalt_generate_linkdata.py): \",e)\n logger.exception(\"XALT_EXCEPTION:xalt_generate_linkdata\"+XALT_Stack.contents())\n\n return 0","title":""},{"docid":"13bc587f5a0ea07889f8b8ab9bd164fb","score":"0.57808703","text":"def main(): # everything that exists is coded in the main function\n # 1, 1, 2, 3, 5, 8, 13, 21, 34","title":""},{"docid":"59bf6ae06b4c2b766abb7b8f181776f7","score":"0.57786876","text":"def main():\n utils.vip_main(lPCBAgent, \n version=__version__)","title":""},{"docid":"22b3744ce64d4ee5aa8dcf390966664d","score":"0.5766914","text":"def main():\n\n # read config files using liftoff\n opt = read_config()\n\n # create paths if not using liftoff\n # liftoff takes care of this otherwise\n opt = create_paths(opt)\n\n # run your experiment\n run(opt)","title":""},{"docid":"9672271c1d73a534226a7ee696d2ba6b","score":"0.57410455","text":"def main():\n print(\"main\")","title":""},{"docid":"48738a5d4d3b5d381714ae989cc8e3b8","score":"0.57282174","text":"def main():\n parser = apollocaffe.base_parser()\n parser.add_argument('--config', required=True)\n args = parser.parse_args()\n config = json.load(open(args.config, 'r'))\n print (\"Test config file is \" + config[\"data\"][\"test_idl\"] )\n apollocaffe.set_random_seed(config[\"solver\"][\"random_seed\"])\n apollocaffe.set_device(0) # gpu\n test(config)","title":""},{"docid":"e605c23ee9e63769d916ba1b761e86b2","score":"0.5723054","text":"def main():\n args = cli()\n lines = args.sourcefile.readlines()\n #tuple is used to symbol table and error counter\n symbol_table, error_count = resolve_labels(lines)\n if error_count == 0:\n #increments the address counter and refers back to assembly instructional code\n transform_instructions(lines, symbol_table)\n for line in lines:\n #prints onto the object file being created\n print(line.strip(), file=args.objfile)","title":""},{"docid":"4181124ff189d7d93d38e464da14095c","score":"0.57198083","text":"def main(self):\n pass","title":""},{"docid":"60e1e9849df493a9f87b8e4f1fbf6759","score":"0.57158166","text":"def main():\n # TODO: 2. Implement and test this function.\n olympic_rings()","title":""},{"docid":"ad5aba213279aa0d3e812b1fef03749f","score":"0.5710833","text":"def main() -> int:\n return special_agent_main(parse_arguments, agent_dell_idrac_main)","title":""},{"docid":"4e8734cb90f3573fc922a5271fd4b22a","score":"0.5708046","text":"def main():\n\n pp = Sinuca_TracerPinPoints()\n result = pp.Run()\n return result","title":""},{"docid":"ebbac7fd45bc295e9f171e55d632a3ef","score":"0.57066834","text":"def main(arguments=None):\n # setup the command-line util settings\n su = tools(\n arguments=arguments,\n docString=__doc__,\n logLevel=\"WARNING\",\n options_first=True,\n projectName=\"panstamps\"\n )\n arguments, settings, log, dbConn = su.setup()\n\n #parser = self.add_options(usage=usagestring)\n #options, args = parser.parse_args()\n #self.options = options\n ra,dec = 0,0\n # unpack remaining cl arguments using `exec` to setup the variable names\n # automatically\n argdict = {}\n for arg, val in arguments.items():\n if arg[0] == \"-\":\n varname = arg.replace(\"-\", \"\") + \"Flag\"\n else:\n varname = arg.replace(\"<\", \"\").replace(\">\", \"\")\n #if isinstance(val, str) or isinstance(val, str):\n argdict[varname] = val\n #exec(\"%s = '%s'\" % (varname,val),globals(),globals())\n #else:\n # argdict[varname] = float(val)\n #exec(\"%s = %s\" % (varname,val,),globals(),globals())\n if arg == \"--dbConn\":\n dbConn = val\n log.debug('%s = %s' % (varname, val,))\n #if varname == 'ra': import pdb; pdb.set_trace()\n #print(ra,dec)\n #import pdb; pdb.set_trace()\n if argdict['ra']:\n try:\n argdict[ra] = float(argdict['ra'])\n except:\n if \":\" not in argdict['ra']:\n log.error(\n \"ERROR: ra must be in decimal degree or sexagesimal format\")\n return\n\n if argdict['dec']:\n try:\n argdict['dec'] = float(argdict['dec'])\n except:\n if \":\" not in argdict['dec']:\n log.error(\n \"ERROR: dec must be in decimal degree or sexagesimal format\")\n return\n\n ## START LOGGING ##\n startTime = times.get_now_sql_datetime()\n log.info(\n '--- STARTING TO RUN THE cl_utils.py AT %s' %\n (startTime,))\n\n # BUILD KEYWORD DICT\n kwargs = {}\n kwargs[\"log\"] = log\n kwargs[\"settings\"] = settings\n kwargs[\"ra\"] = argdict['ra']\n kwargs[\"dec\"] = argdict['dec']\n\n # FITS OPTIONS\n kwargs[\"fits\"] = True # DEFAULT\n if argdict['fitsFlag'] == False and argdict['nofitsFlag'] == True:\n kwargs[\"fits\"] = False\n\n # JPEG OPTIONS\n kwargs[\"jpeg\"] = False # DEFAULT\n if argdict['jpegFlag'] == True and argdict['nojpegFlag'] == False:\n kwargs[\"jpeg\"] = True\n\n # COLOR JPEG OPTIONS\n kwargs[\"color\"] = False # DEFAULT\n if argdict['colorFlag'] == True and argdict['nocolorFlag'] == False:\n kwargs[\"color\"] = True\n\n # WIDTH OPTION\n kwargs[\"arcsecSize\"] = 60\n if argdict['widthFlag']:\n kwargs[\"arcsecSize\"] = float(argdict['widthFlag']) * 60.\n\n # CHOOSE A FILTERSET\n kwargs[\"filterSet\"] = 'gri'\n if argdict['filtersFlag']:\n kwargs[\"filterSet\"] = argdict['filtersFlag']\n\n for i in kwargs[\"filterSet\"]:\n if i not in \"grizy\":\n log.error(\n \"ERROR: the requested filter must be in the grizy filter set\")\n return\n\n # WHICH IMAGE TYPE TO DOWNLOAD\n if argdict['stack']:\n kwargs[\"imageType\"] = \"stack\"\n if argdict['warp']:\n kwargs[\"imageType\"] = \"warp\"\n if argdict['closestFlag']:\n kwargs[\"imageType\"] = \"warp\"\n\n # MJD WINDOW\n kwargs[\"mjdStart\"] = argdict['mjdStart']\n kwargs[\"mjdEnd\"] = argdict['mjdEnd']\n kwargs[\"window\"] = False\n\n try:\n kwargs[\"window\"] = int(argdict['closestFlag'])\n except:\n pass\n\n if not kwargs[\"window\"]:\n if argdict['mjd'] and argdict['closestFlag'] == \"before\":\n kwargs[\"mjdEnd\"] = argdict['mjd']\n elif argdict['mjd'] and argdict['closestFlag'] == \"after\":\n kwargs[\"mjdStart\"] = argdict['mjd']\n else:\n if argdict['mjd'] and kwargs[\"window\"] < 0:\n kwargs[\"mjdEnd\"] = mjd\n elif argdict['mjd'] and kwargs[\"window\"] > 0:\n kwargs[\"mjdStart\"] = mjd\n\n # DOWNLOAD LOCATION\n if argdict['downloadFolderFlag']:\n home = expanduser(\"~\")\n downloadFolderFlag = argdict['downloadFolderFlag'].replace(\"~\", home)\n kwargs[\"downloadDirectory\"] = downloadFolderFlag\n\n # xt-kwarg_key_and_value\n\n # DOWNLOAD THE IMAGES\n images = downloader(**kwargs)\n fitsPaths, jpegPaths, colorPath = images.get()\n jpegPaths += colorPath\n\n # POST-DOWNLOAD PROCESS IMAGES\n kwargs = {}\n kwargs[\"log\"] = log\n kwargs[\"settings\"] = settings\n # WIDTH OPTION\n kwargs[\"arcsecSize\"] = 60\n if argdict['widthFlag']:\n kwargs[\"arcsecSize\"] = float(argdict['widthFlag']) * 60.\n\n # ANNOTATE JPEG OPTIONS\n kwargs[\"crosshairs\"] = True # DEFAULT\n kwargs[\"scale\"] = True\n if argdict['annotateFlag'] == False and argdict['noannotateFlag'] == True:\n kwargs[\"crosshairs\"] = False # DEFAULT\n kwargs[\"scale\"] = False\n\n # INVERT OPTIONS\n kwargs[\"invert\"] = False # DEFAULT\n if argdict['invertFlag'] == True and argdict['noinvertFlag'] == False:\n kwargs[\"invert\"] = True\n\n # GREYSCALE OPTIONS\n kwargs[\"greyscale\"] = False # DEFAULT\n if argdict['greyscaleFlag'] == True and argdict['nogreyscaleFlag'] == False:\n kwargs[\"greyscale\"] = True\n\n # TRANSIENT DOT OPTIONS\n kwargs[\"transient\"] = False # DEFAULT\n if argdict['transientFlag'] == True and argdict['notransientFlag'] == False:\n kwargs[\"transient\"] = True\n\n for j in jpegPaths:\n kwargs[\"imagePath\"] = j\n\n # kwargs[\"transient\"] = False\n\n # kwargs[\"invert\"] = False\n # kwargs[\"greyscale\"] = False\n oneImage = image(**kwargs)\n oneImage.get()\n\n # CALL FUNCTIONS/OBJECTS\n\n if \"dbConn\" in locals() and dbConn:\n dbConn.commit()\n dbConn.close()\n ## FINISH LOGGING ##\n endTime = times.get_now_sql_datetime()\n runningTime = times.calculate_time_difference(startTime, endTime)\n log.info('-- FINISHED ATTEMPT TO RUN THE cl_utils.py AT %s (RUNTIME: %s) --' %\n (endTime, runningTime, ))\n\n return","title":""},{"docid":"9cfc8caf73e0feac3ff58172854bbd68","score":"0.5703492","text":"def main(config_location):\n param = af.ParamParser()\n\n # Create artery network\n an = af.ArteryNetwork(param)\n\n # Solve problem and store data\n an.solve()","title":""},{"docid":"b2fbe374c60106763d0f1078a63025e7","score":"0.5690887","text":"def main():\n global CONFIG\n CONFIG = get_configuration_from_command_line_args()\n try:\n for line in ls_lines():\n print(line)\n except (FileNotFoundError, PermissionError) as e:\n print(e)\n sys.exit(1)\n except Exception as e:\n print(e)\n sys.exit(2)\n sys.exit(0)","title":""},{"docid":"fd0e15a8f4a3b79dd47de2efb306072d","score":"0.56873715","text":"def main():\n # start cluster analysis\n clusters = cluster_analysis()\n return","title":""},{"docid":"7d9d103bc66cee870d990d9f22b1764b","score":"0.5687207","text":"def main():\n # Process the command-line arguments\n doc = (\n \"Calculate the elastic properties of a fibrous composite laminate. \"\n \"See the manual (lamprop-manual.pdf) for more in-depth information.\"\n )\n opts = argparse.ArgumentParser(prog=\"lamprop\", description=doc)\n group = opts.add_mutually_exclusive_group()\n group.add_argument(\n \"-i\",\n \"--info\",\n action=\"store_true\",\n help=\"show information about source file (the default is not to)\",\n )\n group.add_argument(\n \"-l\",\n \"--latex\",\n action=\"store_true\",\n help=\"generate LaTeX output (the default is plain text)\",\n )\n group.add_argument(\"-H\", \"--html\", action=\"store_true\", help=\"generate HTML output\")\n opts.add_argument(\n \"-e\",\n \"--eng\",\n action=\"store_true\",\n help=\"output only the engineering properties\",\n )\n opts.add_argument(\n \"-m\",\n \"--mat\",\n action=\"store_true\",\n help=\"output only the ABD matrix and stiffness tensor\",\n )\n opts.add_argument(\n \"-f\", \"--fea\", action=\"store_true\", help=\"output only material data for FEA\"\n )\n group = opts.add_mutually_exclusive_group()\n group.add_argument(\n \"-L\", \"--license\", action=LicenseAction, nargs=0, help=\"print the license\"\n )\n group.add_argument(\"-v\", \"--version\", action=\"version\", version=lp.__version__)\n opts.add_argument(\n \"--log\",\n default=\"warning\",\n choices=[\"debug\", \"info\", \"warning\", \"error\"],\n help=\"logging level (defaults to 'warning')\",\n )\n opts.add_argument(\n \"files\", metavar=\"file\", nargs=\"*\", help=\"one or more files to process\"\n )\n args = opts.parse_args(sys.argv[1:])\n logging.basicConfig(\n level=getattr(logging, args.log.upper(), None),\n format=\"%(levelname)s: %(message)s\",\n )\n del opts, group\n if args.mat is False and args.eng is False and args.fea is False:\n args.eng = True\n args.mat = True\n args.fea = True\n # No files given to process.\n if len(args.files) == 0:\n sys.exit(1)\n # Set the output method.\n out = lp.text_output\n if args.latex:\n out = lp.latex_output\n elif args.html:\n out = lp.html_output\n # Force utf-8 encoding for stdout on ms-windows.\n # Because redirected output uses cp1252 by default.\n if os.name == \"nt\":\n sys.stdout.reconfigure(encoding=\"utf-8\")\n for f in args.files:\n logging.info(\"processing file '{}'\".format(f))\n laminates = lp.parse(f)\n if args.info and lp.info:\n print(f'Information for \"{f}\":')\n for ln in lp.info:\n print(ln)\n print()\n if lp.warn:\n print(f'Warnings for \"{f}\":')\n for ln in lp.warn:\n print(ln)\n print()\n for curlam in laminates:\n print(*out(curlam, args.eng, args.mat, args.fea), sep=\"\\n\")","title":""},{"docid":"db84ebe5716040ebd81902fff0b41cb5","score":"0.5673952","text":"def main( ):\n parser = argparse.ArgumentParser(description=\"Count major codes\")\n parser.add_argument('majors', type=argparse.FileType('r'),\n help=\"A text file containing major codes, one major code per line.\")\n args = parser.parse_args() # gets arguments from command line\n majors_file = args.majors\n count_codes(majors_file)","title":""},{"docid":"3037866dbb4d83e949ffdc3cb3c77656","score":"0.56514245","text":"def main():\n return 'daoserver'","title":""},{"docid":"e74896eb1e8ec3f7aadb4933b846d810","score":"0.564998","text":"def main():\n parser = argparse.ArgumentParser(\n description='Load data into the Neo4j database for the Alliance of Genome Resources.'\n )\n parser.add_argument(\n '-c',\n '--config', help='Specify the filename of the YAML config. It must reside in the src/config/ directory',\n default='default.yml'\n )\n parser.add_argument('-v',\n '--verbose',\n help='Enable DEBUG mode for logging.',\n action='store_true')\n args = parser.parse_args()\n\n # set context info\n context_info = ContextInfo()\n context_info.config_file_location = os.path.abspath('src/config/' + args.config)\n if args.verbose:\n context_info.env[\"DEBUG\"] = True\n\n debug_level = logging.DEBUG if context_info.env[\"DEBUG\"] else logging.INFO\n\n coloredlogs.install(level=debug_level,\n fmt='%(asctime)s %(levelname)s: %(name)s:%(lineno)d: %(message)s',\n field_styles={\n 'asctime': {'color': 'green'},\n 'hostname': {'color': 'magenta'},\n 'levelname': {'color': 'white', 'bold': True},\n 'name': {'color': 'blue'},\n 'programname': {'color': 'cyan'}\n })\n\n logger = logging.getLogger(__name__)\n logging.getLogger(\"ontobio\").setLevel(logging.ERROR)\n\n AggregateLoader(args, logger, context_info).run_loader()","title":""},{"docid":"c2166c86a540913a01f3dc8c9b3a17cd","score":"0.5635628","text":"def main():\n parser = cmdline_parser()\n args = parser.parse_args()\n\n if args.check is True:\n depen_list = [\"samtools\", \"bamtools\", \"R\", \"featurecounts\",\n \"hisat2\", \"star\", \"faqcs\", \"stringtie\",\n \"bedtools\", \"diamond\"]\n depen_list.sort()\n check_depen(depen_list)\n check_pydepen()\n sys.exit()\n\n #TODO: figure out why this is not working\n os.environ[\"LUIGI_CONFIG_PATH\"] = args.config\n\n # setting up logging files\n logger = create_logger(args.WORKDIR)\n\n # get parameters from the config file\n paras = parse_config(args.config)\n\n # check if correct options are selected\n check_input(paras, parser=parser)\n\n # getting absolute path of workdir\n workdir = os.path.abspath(args.WORKDIR)\n\n if check_exp_design(args.EXPDSN) is False: # check if experimental design file is OK\n sys.exit(\"Your experimental design file has formatting problems!\")\n\n # convert exerimental design file to a dictionary object\n samp_dic = CheckDesign(args.EXPDSN).extract_sample_fastqs()\n\n no_of_jobs = 1\n\n # assigns filenames for databases if not specified.\n db = check_aligner(aligner=paras[\"aligner\"],\n hisat_index=paras[\"hisat_index\"],\n workdir=workdir, star_db=paras[\"star_index\"])\n\n # TODO move this to log file\n summarize_run(aligner=paras[\"aligner\"]) # print run information in screen\n\n # assign universal fasta and gff variable\n if paras[\"kingdom\"] in [\"prokarya\", \"eukarya\"]:\n if paras[\"kingdom\"] == \"prokarya\":\n fasta = paras[\"fasta_prok\"]\n gff = paras[\"gff_prok\"]\n elif paras[\"kingdom\"] == \"eukarya\":\n fasta = paras[\"fasta_euk\"]\n gff = paras[\"gff_euk\"]\n single_seq = SingleSeq(qc=paras[\"qc\"],\n fastq_dic=samp_dic,\n aligner=paras[\"aligner\"],\n ref_fasta=fasta,\n num_cpus=paras[\"threads\"],\n local_scheduler=True,\n hisat_index=db,\n workdir=workdir,\n kingdom=paras[\"kingdom\"],\n no_of_jobs=no_of_jobs,\n p_value=paras[\"q_value\"],\n exp_desn_file=args.EXPDSN,\n stardb_dir=db,\n emap_dir=paras[\"emap_db\"],\n gff_file=gff,\n pathway=paras[\"pathway\"])\n\n # step 1, run qc\n qc_dic = single_seq.run_faqc()\n\n # step 2, create database, hisat2 or stardb\n single_seq.create_db()\n\n # step 3, map reads, hisat2 or stardb\n single_seq.map_reads(qc_dic=qc_dic)\n\n # step 4, summarize the mapped reads\n single_seq.map_summarize()\n\n # step 5, if needed\n if paras[\"novel\"] is True: # if novel regions are to be reported\n single_seq.extract_pp() # extract properly paired reads\n single_seq.NovelRegions() # find novel regions\n single_seq.create_new_gff() # create a new GFF file that has novel region info\n gff = os.path.join(workdir, \"processes\", \"novel\", \"updated.gff\") # update gff\n # step 6, run read counts\n single_seq.feature_count(new_gff=gff)\n single_seq.merge_stringtie(new_gff=gff)\n\n # find diff expressed gene using edgeR\n if \"edgeR\" in paras[\"method\"]:\n single_seq.run_edger()\n # use DESeq2\n if \"DESeq2\" in paras[\"method\"]:\n single_seq.run_deseq2()\n if \"ballgown\" in paras[\"method\"]:\n single_seq.restringtie()\n single_seq.run_ballgown()\n\n # run opaver pathway analysis\n if paras[\"pathway\"] is True:\n # run emapper\n single_seq.run_emapper(new_gff=gff)\n if \"edgeR\" in paras[\"method\"]:\n single_seq.run_opaver(method=\"edgeR\")\n if \"DESeq2\" in paras[\"method\"]:\n single_seq.run_opaver(method=\"DESeq2\")\n\n # summarize all results into one big json file.\n single_seq.summ_json(new_gff=gff, method=paras[\"method\"],\n NovelRegions=paras[\"novel\"])\n\n elif paras[\"kingdom\"] == \"both\":\n euk_fasta = paras[\"fasta_euk\"]\n euk_gff = paras[\"gff_euk\"]\n prok_fasta = paras[\"fasta_prok\"]\n prok_gff = paras[\"gff_prok\"]\n\n dual_seq = DualSeq(qc=paras[\"qc\"],\n fastq_dic=samp_dic, \n kingdom=paras[\"kingdom\"],\n aligner=paras[\"aligner\"],\n euk_fasta=paras[\"fasta_euk\"],\n prok_fasta=paras[\"fasta_prok\"],\n prok_gff=paras[\"gff_prok\"],\n euk_gff=paras[\"gff_euk\"],\n workdir=workdir,\n p_value=paras[\"q_value\"],\n exp_desn_file=args.EXPDSN,\n hisat_index=db,\n local_scheduler=True,\n pathway=paras[\"pathway\"],\n num_cpus=paras[\"threads\"],\n stardb_dir = paras[\"star_index\"],\n emap_dir=paras[\"emap_db\"])\n\n # step 1, run qc\n qc_dic = dual_seq.run_faqc()\n \n # step 2, create database, hisat2 or stardb\n dual_seq.create_db()\n\n # step 3, map reads, hisat2 or stardb\n dual_seq.map_reads()\n\n # step 4, summarize the mapped reads\n dual_seq.map_summarize()\n dual_seq.split_prokeuk()\n\n # step 5, if needed\n if paras[\"novel\"] is True: # if novel regions are to be reported\n dual_seq.extract_pp() # extract properly paired reads\n dual_seq.NovelRegions() # find novel regions\n dual_seq.create_new_gff() # create a new GFF file that has novel region info\n euk_gff = os.path.join(workdir,\n \"processes\", \"novel\",\n \"euk_updated.gff\") # update gff\n prok_gff = os.path.join(workdir, \"processes\", \"novel\",\n \"prok_updated.gff\") # update gff\n \n # step 6, run read counts\n print(\"Counting eukaryotes\")\n dual_seq.feature_counts(new_gff=euk_gff, kingdom=\"eukarya\")\n dual_seq.feature_counts(new_gff=prok_gff, kingdom=\"prokarya\")\n dual_seq.merge_stringtie(new_gff=prok_gff + \",\" + euk_gff)\n\n # find diff expressed gene using edgeR\n if \"edgeR\" in paras[\"method\"]:\n dual_seq.run_edger(kingdom=\"eukarya\")\n dual_seq.run_edger(kingdom=\"prokarya\")\n if \"DESeq2\" in paras[\"method\"]:\n dual_seq.run_deseq2(kingdom=\"eukarya\")\n dual_seq.run_deseq2(kingdom=\"prokarya\")\n if \"ballgown\" in paras[\"method\"]:\n dual_seq.restringtie()\n dual_seq.run_ballgown()\n\n if paras[\"pathway\"] is True:\n # run emapper\n dual_seq.run_emapper(new_gff=prok_gff, kingdom=\"prokarya\", fasta=prok_fasta)\n dual_seq.run_emapper(new_gff=euk_gff, kingdom=\"eukarya\", fasta=euk_fasta)\n if \"edgeR\" in paras[\"method\"]:\n dual_seq.run_opaver(method=\"edgeR\", kingdom=\"prokarya\")\n dual_seq.run_opaver(method=\"edgeR\", kingdom=\"eukarya\")\n if \"DESeq2\" in paras[\"method\"]:\n dual_seq.run_opaver(method=\"DESeq2\", kingdom=\"prokarya\")\n dual_seq.run_opaver(method=\"DESeq2\", kingdom=\"eukarya\")\n\n # summarize all results into one big json file.\n dual_seq.summ_json(new_gff=euk_gff, method=paras[\"method\"],\n NovelRegions=paras[\"novel\"],\n kingdom=\"eukarya\",\n fasta=euk_fasta)\n dual_seq.summ_json(new_gff=euk_gff, method=paras[\"method\"],\n NovelRegions=paras[\"novel\"],\n kingdom=\"prokarya\",\n fasta=prok_fasta)","title":""},{"docid":"e2338876881ec41fc2d19277660f010d","score":"0.5627442","text":"def main():\r\n params = get_configuration(print_diagnostics=True, with_neptune=True, inject_parameters_to_gin=True)\r\n LOG_PATH = os.path.join(params.BASE_PATH, 'tests', params.GAME)\r\n runner = RolloutsRunner(LOG_PATH,create_rainbow_rollouts_agent)\r\n runner.run_experiment()","title":""}],"string":"[\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08aa0c5cc07c5efe590ba89320b45dbc\",\n \"score\": \"0.69941837\",\n \"text\": \"def main():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"29e1f6ab065fa2f570f2241972e9c859\",\n \"score\": \"0.6961694\",\n \"text\": \"def\\tmain():\\r\\n\\t\\r\\n\\tpass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6a72f0523c7f4b19a3ff495c1baaa5c5\",\n \"score\": \"0.669952\",\n \"text\": \"def main() -> None:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6a72f0523c7f4b19a3ff495c1baaa5c5\",\n \"score\": \"0.669952\",\n \"text\": \"def main() -> None:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a1e1239bd97fc0c2dd7ee8ea2003aadd\",\n \"score\": \"0.65233755\",\n \"text\": \"def main_CL():\\r\\n parser = OptionParser(usage=usage(), version='1.0')\\r\\n parser.add_option(\\\"-c\\\", \\\"--cmd\\\", dest=\\\"cmd\\\", default=\\\"unknown\\\", help=\\\"What command to run.\\\")\\r\\n parser.add_option(\\\"-w\\\", \\\"--walk\\\", dest=\\\"walk\\\", default=\\\"none\\\", help=\\\"Scope of status to walk in the directory.\\\")\\r\\n parser.add_option(\\\"-s\\\", \\\"--cs\\\", dest=\\\"code\\\", default=\\\"4\\\", help=\\\"The Code version <4|4.0|4.1|4.2|all> to use.\\\")\\r\\n parser.add_option(\\\"-t\\\", \\\"--tcId\\\", dest=\\\"tcId\\\", default=\\\"a0Q300000000Hj9\\\", help=\\\"Tech Campaign ID in SalesForce\\\")\\r\\n parser.add_option(\\\"-n\\\", \\\"--num\\\", dest=\\\"num\\\", default=\\\"4000\\\", help=\\\"Max number of items to process\\\")\\r\\n parser.add_option(\\\"-x\\\", \\\"--parm\\\", dest=\\\"parm\\\", default=\\\"\\\", help=\\\"Parms used by a method\\\")\\r\\n parser.add_option(\\\"-f\\\", \\\"--file\\\", dest=\\\"file\\\", default=\\\"\\\", help=\\\"path to the file to load, current dir if just a filename\\\")\\r\\n parser.add_option(\\\"-q\\\", \\\"--quiet\\\", dest='quiet',default=\\\"1\\\", help=\\\"Show less info in output\\\")\\r\\n parser.add_option(\\\"-d\\\", \\\"--debug\\\", dest='debug',action=\\\"count\\\",help=\\\"The debug level, use multiple to get more.\\\")\\r\\n (options, args) = parser.parse_args()\\r\\n if options.debug > 2:\\r\\n print ' verbose %s\\\\tdebug %s' %(options.quiet, options.debug)\\r\\n print ' command %s\\\\twalk %s' %(options.cmd, options.walk)\\r\\n print ' version %s' %options.code\\r\\n print ' tcId %s' %options.tcId\\r\\n print ' num %s' %options.num\\r\\n print ' file %s' %options.file\\r\\n print ' args: %s' %args\\r\\n else:\\r\\n options.debug = 0\\r\\n crList = []\\r\\n version = str(options.code)\\r\\n \\r\\n if options.cmd in ['load']:\\r\\n loadQOR(options=options)\\r\\n elif options.cmd in ['dir']:\\r\\n loadQORDir(options=options)\\r\\n elif options.cmd in ['rpt']:\\r\\n walk_list(options=options)\\r\\n else:\\r\\n print '%s' %usage()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7c948d070347c04c157c9bc1a32db75f\",\n \"score\": \"0.6512523\",\n \"text\": \"def main(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b7ec2b67be7af2e3e3f7abf4d1854636\",\n \"score\": \"0.6511092\",\n \"text\": \"def main():\\n core.main()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"318cdf2f663487bb0a9d9fa8d2987875\",\n \"score\": \"0.64981115\",\n \"text\": \"def main():\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"737edbcdda02609a89cb40f455a292fb\",\n \"score\": \"0.6491304\",\n \"text\": \"def main(args):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc0d536b098278d704e13b8e318d6af5\",\n \"score\": \"0.64139795\",\n \"text\": \"def main():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"59a11114512ac46a2a2d976a77d1c6d6\",\n \"score\": \"0.63336045\",\n \"text\": \"def main(self, *args):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"535c6e7d32028af3cc3d681a0804815d\",\n \"score\": \"0.631539\",\n \"text\": \"def main(args=None):\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"535c6e7d32028af3cc3d681a0804815d\",\n \"score\": \"0.631539\",\n \"text\": \"def main(args=None):\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"535c6e7d32028af3cc3d681a0804815d\",\n \"score\": \"0.631539\",\n \"text\": \"def main(args=None):\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8795b9ca19d8f12a8d63e1f20619a3ca\",\n \"score\": \"0.6273365\",\n \"text\": \"def lafs():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5aa4372be4d7b9d84cb0f1e4c22aa424\",\n \"score\": \"0.62235725\",\n \"text\": \"def main():\\n if not os.path.exists(\\\"./data/features\\\"):\\n os.makedirs(\\\"./data/features\\\")\\n make_cts()\\n make_coldata()\\n command = \\\"Rscript ./src/features/r_scripts/lfc.R\\\"\\n os.system(command)\\n return\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bdea5fa1d9b0ba3dfa8573d74c9cd641\",\n \"score\": \"0.6218749\",\n \"text\": \"def main(argv):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2230f3b32896a1d0f35daa753ea7307c\",\n \"score\": \"0.61689687\",\n \"text\": \"def main():\\n Main()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"64a1a4261cea121e609f61fd60d0b36f\",\n \"score\": \"0.6127713\",\n \"text\": \"def main():\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c328a8e3f0c73dfb795255c779d6bb21\",\n \"score\": \"0.6124877\",\n \"text\": \"def main():\\n # set up the program to take in arguments from the command line\",\n \"title\": \"\"\n },\n {\n \"docid\": \"04688cd98d9fcf835947139440a6440f\",\n \"score\": \"0.60574085\",\n \"text\": \"def main():\\n\\n pass\\n\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9849beb2becdf68e2bf5a55ba6c8e058\",\n \"score\": \"0.6054235\",\n \"text\": \"def main():\\n\\n BASIC.run(PROGRAM)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9849beb2becdf68e2bf5a55ba6c8e058\",\n \"score\": \"0.6054235\",\n \"text\": \"def main():\\n\\n BASIC.run(PROGRAM)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9849beb2becdf68e2bf5a55ba6c8e058\",\n \"score\": \"0.6054235\",\n \"text\": \"def main():\\n\\n BASIC.run(PROGRAM)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dc5586b84901eecdd4033d77b1277901\",\n \"score\": \"0.6052881\",\n \"text\": \"def main(args):\\r\\n\\tprint args\",\n \"title\": \"\"\n },\n {\n \"docid\": \"693e66b4f00edb2c4872791ea15557fe\",\n \"score\": \"0.60299456\",\n \"text\": \"def main():\\n parser = ArgumentParser(description='추출된 오분석 패치 후보를 검증하는 스크립트')\\n parser.add_argument('-c', '--corpus-dir', help='corpus dir', metavar='DIR', required=True)\\n parser.add_argument('--rsc-src', help='resource source dir <default: ../rsc/src>',\\n metavar='DIR', default='../rsc/src')\\n parser.add_argument('--lib-path', help='khaiii shared library path', metavar='FILE', default='')\\n parser.add_argument('--rsc-dir', help='resource dir', metavar='DIR', default='')\\n parser.add_argument('--input', help='input file <default: stdin>', metavar='FILE')\\n parser.add_argument('--output', help='output file <default: stdout>', metavar='FILE')\\n parser.add_argument('--debug', help='enable debug', action='store_true')\\n args = parser.parse_args()\\n\\n if args.input:\\n sys.stdin = open(args.input, 'r', encoding='UTF-8')\\n if args.output:\\n sys.stdout = open(args.output, 'w', encoding='UTF-8')\\n if args.debug:\\n logging.basicConfig(level=logging.DEBUG)\\n else:\\n logging.basicConfig(level=logging.INFO)\\n\\n run(args)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"25d2156a2c147b735919830a88870675\",\n \"score\": \"0.6025334\",\n \"text\": \"def climain():\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f5faf6af6fd1d678aa5d61b752570c5b\",\n \"score\": \"0.60207397\",\n \"text\": \"def main():\\n CLI.from_command_line()\\n exit(0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"50333a46fe2be3b14f8763c7450461cc\",\n \"score\": \"0.5991564\",\n \"text\": \"def main(args=None):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2dddb624e75a16297354fe192004dae4\",\n \"score\": \"0.5971752\",\n \"text\": \"def main() -> None:\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"03eab569e1fa019e05e3f17a76f89d8e\",\n \"score\": \"0.5965668\",\n \"text\": \"def main():\\n\\n\\ta = LedSwitcher(sys.argv[1])\\n\\ta.parseFile()\\n\\tprint(a.getResult())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9474d60d1ad14443e46dc45f9d255de4\",\n \"score\": \"0.5958696\",\n \"text\": \"def main():\\n args = parse_args()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ac7d54f6876130c19c424c66f5c633c3\",\n \"score\": \"0.59350556\",\n \"text\": \"def cli():\\n\\n print(\\\"Context of the main.\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0c44f7b85e1489e30026e387428624fc\",\n \"score\": \"0.59238666\",\n \"text\": \"def EntryPoint(self) -> _n_5_t_1:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d7b8a92fa493427136b876598a229cee\",\n \"score\": \"0.5900915\",\n \"text\": \"def main_alt():\\n print \\\"Hello, world!\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8fa7ebb63b49d9b7b6661663eb1a9990\",\n \"score\": \"0.58937246\",\n \"text\": \"def main():\\n ### read dump\\n timestep, natoms, lx, ly, xs, ys = read_dump(ifname)\\n ### correct pbcs for all molecules\\n correct_pbcs(xs, ys, nfil, natoms)\\n ### add new beads\\n #xsd, ysd, natomsd, nfild = add_beads(xs,ys,nfil,natoms)\\n ### add new per/atom information\\n tpe, molid = add_per_atom_info(natoms, nfil)\\n ### add new bond information\\n bid, btpe, b1, b2 = add_bond_information(natoms, nfil)\\n ### add new angle information\\n aid, atpe, a1, a2, a3 = add_angle_information(natoms, nfil)\\n ### scale xs and ys\\n lx *= lscale\\n ly *= lscale\\n xs *= lx\\n ys *= ly\\n ### write results to xyz file\\n write_xyz(xs,ys)\\n ### write results to lammps data file\\n write_data(natoms, lx,ly, tpe, molid, xs, ys, bid, btpe, b1, b2, aid, atpe, a1, a2, a3,ofname)\\n return\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ed20152113aec51270e2db79970f1f50\",\n \"score\": \"0.58698523\",\n \"text\": \"def llc(args=None):\\n args = parser.parse_args(args)\\n with LogSetup(args) as log_setup:\\n march = get_arch_from_args(args)\\n ir_module = api.llvm_to_ir(args.source)\\n do_compile([ir_module], march, log_setup.reporter, log_setup.args)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ba8ad90da83a3ae86af26ef07a134e88\",\n \"score\": \"0.5863602\",\n \"text\": \"def test_lc_file():\\n lc_from_file(lc, cache, X, y, F, wf, P, wp)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6b54c30c3c8ce763241d1d10b860290b\",\n \"score\": \"0.58604974\",\n \"text\": \"def main():\\n\\n read_config(os.path.join(os.path.dirname(os.path.realpath(__file__)), \\\"cupp.cfg\\\"))\\n\\n parser = get_parser()\\n args = parser.parse_args()\\n\\n if not args.quiet:\\n print_cow()\\n\\n if args.version:\\n version()\\n elif args.interactive:\\n interactive()\\n elif args.download_wordlist:\\n download_wordlist()\\n elif args.alecto:\\n alectodb_download()\\n elif args.improve:\\n improve_dictionary(args.improve)\\n else:\\n parser.print_help()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6e57c8a0092568cb746b76b654f5c47f\",\n \"score\": \"0.58221513\",\n \"text\": \"def main() -> None:\\n\\n new_location_main(sys.argv[1:])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"945a136452b0e0f7d5cc4dc0c0dc227c\",\n \"score\": \"0.5822095\",\n \"text\": \"def main():\\n print(\\\"Welcome to the XY77 Battering Ram\\\")\\n\\n state = get_vault_state()\\n print(\\\"State acquired. Let's start.\\\")\\n\\n print(\\\"\\\\n**History Layer**\\\")\\n history_layer(state)\\n\\n print(\\\"\\\\n**Code Layer**\\\")\\n code_layer(state)\\n\\n print(\\\"\\\\n**Switches Layer**\\\")\\n switches_layer(state)\\n\\n print(\\\"\\\\n**Button Layer**\\\")\\n button_layer(state)\\n\\n print(\\\"Layers bypassed.\\\")\\n print(\\\"Wait\\\", state['suspicion level'],\\n \\\"seconds or more to allow suspicion level to dissipate.\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ab7c7f19a627fee85f5b4de482ebcb8d\",\n \"score\": \"0.58100647\",\n \"text\": \"def main():\\n ibc_nlp_classification()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"be5ec6cfb53f8bc192c6396a7b0c49a2\",\n \"score\": \"0.5809807\",\n \"text\": \"def main():\\n User = os.environ.get(\\\"USER\\\", \\\"unknown\\\")\\n Host = os.environ.get(\\\"HOSTNAME\\\",\\\"unknown\\\")\\n # push User, host and command line on to XALT_Stack\\n XALT_Stack.push(\\\"User: \\\" + User)\\n XALT_Stack.push(\\\"Host: \\\" + Host)\\n sA = []\\n sA.append(\\\"CommandLine:\\\")\\n for v in sys.argv:\\n sA.append('\\\"'+v+'\\\"')\\n\\n s = \\\" \\\".join(sA)\\n XALT_Stack.push(s)\\n\\n try:\\n uuid = sys.argv[ 1]\\n status = sys.argv[ 2]\\n wd = sys.argv[ 3]\\n syshost = sys.argv[ 4]\\n execname = sys.argv[ 5]\\n xaltobj = sys.argv[ 6]\\n build_epoch = sys.argv[ 7]\\n linklineFn = sys.argv[ 8]\\n funclist = sys.argv[ 9]\\t\\t\\t# ftrack2015\\n resultFn = sys.argv[10] # ftrack2015\\n\\n if (execname.find(\\\"conftest\\\") != -1):\\n return 1\\n \\n hash_line = capture(['sha1sum', execname]) \\n if (hash_line.find(\\\"No such file or directory\\\") != -1):\\n return 1\\n hash_id = hash_line.split()[0]\\n\\n # Step one clean up linkline data\\n sA = cleanup(xaltobj, linklineFn)\\n sC = cleanfunc(funclist)\\t\\t\\t# ftrack2015\\n \\n resultT = {}\\n resultT['uuid'] = uuid\\n resultT['link_program'] = extract_compiler()\\n resultT['build_user'] = User\\n resultT['exit_code'] = int(status)\\n resultT['build_epoch'] = float(build_epoch)\\n resultT['exec_path'] = os.path.abspath(execname)\\n resultT['hash_id'] = hash_id\\n resultT['wd'] = wd\\n resultT['build_syshost'] = syshost\\n resultT['func_list'] = sC\\t\\t#ftrack2015\\n resultT['linkA'] = sA\\n \\n xfer = XALT_transmission_factory.build(XALT_TRANSMISSION_STYLE,\\n syshost, \\\"link\\\", resultFn)\\n xfer.save(resultT)\\n\\n except Exception as e:\\n print(\\\"XALT_EXCEPTION(xalt_generate_linkdata.py): \\\",e)\\n logger.exception(\\\"XALT_EXCEPTION:xalt_generate_linkdata\\\"+XALT_Stack.contents())\\n\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"13bc587f5a0ea07889f8b8ab9bd164fb\",\n \"score\": \"0.57808703\",\n \"text\": \"def main(): # everything that exists is coded in the main function\\n # 1, 1, 2, 3, 5, 8, 13, 21, 34\",\n \"title\": \"\"\n },\n {\n \"docid\": \"59bf6ae06b4c2b766abb7b8f181776f7\",\n \"score\": \"0.57786876\",\n \"text\": \"def main():\\n utils.vip_main(lPCBAgent, \\n version=__version__)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"22b3744ce64d4ee5aa8dcf390966664d\",\n \"score\": \"0.5766914\",\n \"text\": \"def main():\\n\\n # read config files using liftoff\\n opt = read_config()\\n\\n # create paths if not using liftoff\\n # liftoff takes care of this otherwise\\n opt = create_paths(opt)\\n\\n # run your experiment\\n run(opt)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9672271c1d73a534226a7ee696d2ba6b\",\n \"score\": \"0.57410455\",\n \"text\": \"def main():\\n print(\\\"main\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"48738a5d4d3b5d381714ae989cc8e3b8\",\n \"score\": \"0.57282174\",\n \"text\": \"def main():\\n parser = apollocaffe.base_parser()\\n parser.add_argument('--config', required=True)\\n args = parser.parse_args()\\n config = json.load(open(args.config, 'r'))\\n print (\\\"Test config file is \\\" + config[\\\"data\\\"][\\\"test_idl\\\"] )\\n apollocaffe.set_random_seed(config[\\\"solver\\\"][\\\"random_seed\\\"])\\n apollocaffe.set_device(0) # gpu\\n test(config)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e605c23ee9e63769d916ba1b761e86b2\",\n \"score\": \"0.5723054\",\n \"text\": \"def main():\\n args = cli()\\n lines = args.sourcefile.readlines()\\n #tuple is used to symbol table and error counter\\n symbol_table, error_count = resolve_labels(lines)\\n if error_count == 0:\\n #increments the address counter and refers back to assembly instructional code\\n transform_instructions(lines, symbol_table)\\n for line in lines:\\n #prints onto the object file being created\\n print(line.strip(), file=args.objfile)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4181124ff189d7d93d38e464da14095c\",\n \"score\": \"0.57198083\",\n \"text\": \"def main(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"60e1e9849df493a9f87b8e4f1fbf6759\",\n \"score\": \"0.57158166\",\n \"text\": \"def main():\\n # TODO: 2. Implement and test this function.\\n olympic_rings()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ad5aba213279aa0d3e812b1fef03749f\",\n \"score\": \"0.5710833\",\n \"text\": \"def main() -> int:\\n return special_agent_main(parse_arguments, agent_dell_idrac_main)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4e8734cb90f3573fc922a5271fd4b22a\",\n \"score\": \"0.5708046\",\n \"text\": \"def main():\\n\\n pp = Sinuca_TracerPinPoints()\\n result = pp.Run()\\n return result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ebbac7fd45bc295e9f171e55d632a3ef\",\n \"score\": \"0.57066834\",\n \"text\": \"def main(arguments=None):\\n # setup the command-line util settings\\n su = tools(\\n arguments=arguments,\\n docString=__doc__,\\n logLevel=\\\"WARNING\\\",\\n options_first=True,\\n projectName=\\\"panstamps\\\"\\n )\\n arguments, settings, log, dbConn = su.setup()\\n\\n #parser = self.add_options(usage=usagestring)\\n #options, args = parser.parse_args()\\n #self.options = options\\n ra,dec = 0,0\\n # unpack remaining cl arguments using `exec` to setup the variable names\\n # automatically\\n argdict = {}\\n for arg, val in arguments.items():\\n if arg[0] == \\\"-\\\":\\n varname = arg.replace(\\\"-\\\", \\\"\\\") + \\\"Flag\\\"\\n else:\\n varname = arg.replace(\\\"<\\\", \\\"\\\").replace(\\\">\\\", \\\"\\\")\\n #if isinstance(val, str) or isinstance(val, str):\\n argdict[varname] = val\\n #exec(\\\"%s = '%s'\\\" % (varname,val),globals(),globals())\\n #else:\\n # argdict[varname] = float(val)\\n #exec(\\\"%s = %s\\\" % (varname,val,),globals(),globals())\\n if arg == \\\"--dbConn\\\":\\n dbConn = val\\n log.debug('%s = %s' % (varname, val,))\\n #if varname == 'ra': import pdb; pdb.set_trace()\\n #print(ra,dec)\\n #import pdb; pdb.set_trace()\\n if argdict['ra']:\\n try:\\n argdict[ra] = float(argdict['ra'])\\n except:\\n if \\\":\\\" not in argdict['ra']:\\n log.error(\\n \\\"ERROR: ra must be in decimal degree or sexagesimal format\\\")\\n return\\n\\n if argdict['dec']:\\n try:\\n argdict['dec'] = float(argdict['dec'])\\n except:\\n if \\\":\\\" not in argdict['dec']:\\n log.error(\\n \\\"ERROR: dec must be in decimal degree or sexagesimal format\\\")\\n return\\n\\n ## START LOGGING ##\\n startTime = times.get_now_sql_datetime()\\n log.info(\\n '--- STARTING TO RUN THE cl_utils.py AT %s' %\\n (startTime,))\\n\\n # BUILD KEYWORD DICT\\n kwargs = {}\\n kwargs[\\\"log\\\"] = log\\n kwargs[\\\"settings\\\"] = settings\\n kwargs[\\\"ra\\\"] = argdict['ra']\\n kwargs[\\\"dec\\\"] = argdict['dec']\\n\\n # FITS OPTIONS\\n kwargs[\\\"fits\\\"] = True # DEFAULT\\n if argdict['fitsFlag'] == False and argdict['nofitsFlag'] == True:\\n kwargs[\\\"fits\\\"] = False\\n\\n # JPEG OPTIONS\\n kwargs[\\\"jpeg\\\"] = False # DEFAULT\\n if argdict['jpegFlag'] == True and argdict['nojpegFlag'] == False:\\n kwargs[\\\"jpeg\\\"] = True\\n\\n # COLOR JPEG OPTIONS\\n kwargs[\\\"color\\\"] = False # DEFAULT\\n if argdict['colorFlag'] == True and argdict['nocolorFlag'] == False:\\n kwargs[\\\"color\\\"] = True\\n\\n # WIDTH OPTION\\n kwargs[\\\"arcsecSize\\\"] = 60\\n if argdict['widthFlag']:\\n kwargs[\\\"arcsecSize\\\"] = float(argdict['widthFlag']) * 60.\\n\\n # CHOOSE A FILTERSET\\n kwargs[\\\"filterSet\\\"] = 'gri'\\n if argdict['filtersFlag']:\\n kwargs[\\\"filterSet\\\"] = argdict['filtersFlag']\\n\\n for i in kwargs[\\\"filterSet\\\"]:\\n if i not in \\\"grizy\\\":\\n log.error(\\n \\\"ERROR: the requested filter must be in the grizy filter set\\\")\\n return\\n\\n # WHICH IMAGE TYPE TO DOWNLOAD\\n if argdict['stack']:\\n kwargs[\\\"imageType\\\"] = \\\"stack\\\"\\n if argdict['warp']:\\n kwargs[\\\"imageType\\\"] = \\\"warp\\\"\\n if argdict['closestFlag']:\\n kwargs[\\\"imageType\\\"] = \\\"warp\\\"\\n\\n # MJD WINDOW\\n kwargs[\\\"mjdStart\\\"] = argdict['mjdStart']\\n kwargs[\\\"mjdEnd\\\"] = argdict['mjdEnd']\\n kwargs[\\\"window\\\"] = False\\n\\n try:\\n kwargs[\\\"window\\\"] = int(argdict['closestFlag'])\\n except:\\n pass\\n\\n if not kwargs[\\\"window\\\"]:\\n if argdict['mjd'] and argdict['closestFlag'] == \\\"before\\\":\\n kwargs[\\\"mjdEnd\\\"] = argdict['mjd']\\n elif argdict['mjd'] and argdict['closestFlag'] == \\\"after\\\":\\n kwargs[\\\"mjdStart\\\"] = argdict['mjd']\\n else:\\n if argdict['mjd'] and kwargs[\\\"window\\\"] < 0:\\n kwargs[\\\"mjdEnd\\\"] = mjd\\n elif argdict['mjd'] and kwargs[\\\"window\\\"] > 0:\\n kwargs[\\\"mjdStart\\\"] = mjd\\n\\n # DOWNLOAD LOCATION\\n if argdict['downloadFolderFlag']:\\n home = expanduser(\\\"~\\\")\\n downloadFolderFlag = argdict['downloadFolderFlag'].replace(\\\"~\\\", home)\\n kwargs[\\\"downloadDirectory\\\"] = downloadFolderFlag\\n\\n # xt-kwarg_key_and_value\\n\\n # DOWNLOAD THE IMAGES\\n images = downloader(**kwargs)\\n fitsPaths, jpegPaths, colorPath = images.get()\\n jpegPaths += colorPath\\n\\n # POST-DOWNLOAD PROCESS IMAGES\\n kwargs = {}\\n kwargs[\\\"log\\\"] = log\\n kwargs[\\\"settings\\\"] = settings\\n # WIDTH OPTION\\n kwargs[\\\"arcsecSize\\\"] = 60\\n if argdict['widthFlag']:\\n kwargs[\\\"arcsecSize\\\"] = float(argdict['widthFlag']) * 60.\\n\\n # ANNOTATE JPEG OPTIONS\\n kwargs[\\\"crosshairs\\\"] = True # DEFAULT\\n kwargs[\\\"scale\\\"] = True\\n if argdict['annotateFlag'] == False and argdict['noannotateFlag'] == True:\\n kwargs[\\\"crosshairs\\\"] = False # DEFAULT\\n kwargs[\\\"scale\\\"] = False\\n\\n # INVERT OPTIONS\\n kwargs[\\\"invert\\\"] = False # DEFAULT\\n if argdict['invertFlag'] == True and argdict['noinvertFlag'] == False:\\n kwargs[\\\"invert\\\"] = True\\n\\n # GREYSCALE OPTIONS\\n kwargs[\\\"greyscale\\\"] = False # DEFAULT\\n if argdict['greyscaleFlag'] == True and argdict['nogreyscaleFlag'] == False:\\n kwargs[\\\"greyscale\\\"] = True\\n\\n # TRANSIENT DOT OPTIONS\\n kwargs[\\\"transient\\\"] = False # DEFAULT\\n if argdict['transientFlag'] == True and argdict['notransientFlag'] == False:\\n kwargs[\\\"transient\\\"] = True\\n\\n for j in jpegPaths:\\n kwargs[\\\"imagePath\\\"] = j\\n\\n # kwargs[\\\"transient\\\"] = False\\n\\n # kwargs[\\\"invert\\\"] = False\\n # kwargs[\\\"greyscale\\\"] = False\\n oneImage = image(**kwargs)\\n oneImage.get()\\n\\n # CALL FUNCTIONS/OBJECTS\\n\\n if \\\"dbConn\\\" in locals() and dbConn:\\n dbConn.commit()\\n dbConn.close()\\n ## FINISH LOGGING ##\\n endTime = times.get_now_sql_datetime()\\n runningTime = times.calculate_time_difference(startTime, endTime)\\n log.info('-- FINISHED ATTEMPT TO RUN THE cl_utils.py AT %s (RUNTIME: %s) --' %\\n (endTime, runningTime, ))\\n\\n return\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9cfc8caf73e0feac3ff58172854bbd68\",\n \"score\": \"0.5703492\",\n \"text\": \"def main(config_location):\\n param = af.ParamParser()\\n\\n # Create artery network\\n an = af.ArteryNetwork(param)\\n\\n # Solve problem and store data\\n an.solve()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b2fbe374c60106763d0f1078a63025e7\",\n \"score\": \"0.5690887\",\n \"text\": \"def main():\\n global CONFIG\\n CONFIG = get_configuration_from_command_line_args()\\n try:\\n for line in ls_lines():\\n print(line)\\n except (FileNotFoundError, PermissionError) as e:\\n print(e)\\n sys.exit(1)\\n except Exception as e:\\n print(e)\\n sys.exit(2)\\n sys.exit(0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fd0e15a8f4a3b79dd47de2efb306072d\",\n \"score\": \"0.56873715\",\n \"text\": \"def main():\\n # start cluster analysis\\n clusters = cluster_analysis()\\n return\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7d9d103bc66cee870d990d9f22b1764b\",\n \"score\": \"0.5687207\",\n \"text\": \"def main():\\n # Process the command-line arguments\\n doc = (\\n \\\"Calculate the elastic properties of a fibrous composite laminate. \\\"\\n \\\"See the manual (lamprop-manual.pdf) for more in-depth information.\\\"\\n )\\n opts = argparse.ArgumentParser(prog=\\\"lamprop\\\", description=doc)\\n group = opts.add_mutually_exclusive_group()\\n group.add_argument(\\n \\\"-i\\\",\\n \\\"--info\\\",\\n action=\\\"store_true\\\",\\n help=\\\"show information about source file (the default is not to)\\\",\\n )\\n group.add_argument(\\n \\\"-l\\\",\\n \\\"--latex\\\",\\n action=\\\"store_true\\\",\\n help=\\\"generate LaTeX output (the default is plain text)\\\",\\n )\\n group.add_argument(\\\"-H\\\", \\\"--html\\\", action=\\\"store_true\\\", help=\\\"generate HTML output\\\")\\n opts.add_argument(\\n \\\"-e\\\",\\n \\\"--eng\\\",\\n action=\\\"store_true\\\",\\n help=\\\"output only the engineering properties\\\",\\n )\\n opts.add_argument(\\n \\\"-m\\\",\\n \\\"--mat\\\",\\n action=\\\"store_true\\\",\\n help=\\\"output only the ABD matrix and stiffness tensor\\\",\\n )\\n opts.add_argument(\\n \\\"-f\\\", \\\"--fea\\\", action=\\\"store_true\\\", help=\\\"output only material data for FEA\\\"\\n )\\n group = opts.add_mutually_exclusive_group()\\n group.add_argument(\\n \\\"-L\\\", \\\"--license\\\", action=LicenseAction, nargs=0, help=\\\"print the license\\\"\\n )\\n group.add_argument(\\\"-v\\\", \\\"--version\\\", action=\\\"version\\\", version=lp.__version__)\\n opts.add_argument(\\n \\\"--log\\\",\\n default=\\\"warning\\\",\\n choices=[\\\"debug\\\", \\\"info\\\", \\\"warning\\\", \\\"error\\\"],\\n help=\\\"logging level (defaults to 'warning')\\\",\\n )\\n opts.add_argument(\\n \\\"files\\\", metavar=\\\"file\\\", nargs=\\\"*\\\", help=\\\"one or more files to process\\\"\\n )\\n args = opts.parse_args(sys.argv[1:])\\n logging.basicConfig(\\n level=getattr(logging, args.log.upper(), None),\\n format=\\\"%(levelname)s: %(message)s\\\",\\n )\\n del opts, group\\n if args.mat is False and args.eng is False and args.fea is False:\\n args.eng = True\\n args.mat = True\\n args.fea = True\\n # No files given to process.\\n if len(args.files) == 0:\\n sys.exit(1)\\n # Set the output method.\\n out = lp.text_output\\n if args.latex:\\n out = lp.latex_output\\n elif args.html:\\n out = lp.html_output\\n # Force utf-8 encoding for stdout on ms-windows.\\n # Because redirected output uses cp1252 by default.\\n if os.name == \\\"nt\\\":\\n sys.stdout.reconfigure(encoding=\\\"utf-8\\\")\\n for f in args.files:\\n logging.info(\\\"processing file '{}'\\\".format(f))\\n laminates = lp.parse(f)\\n if args.info and lp.info:\\n print(f'Information for \\\"{f}\\\":')\\n for ln in lp.info:\\n print(ln)\\n print()\\n if lp.warn:\\n print(f'Warnings for \\\"{f}\\\":')\\n for ln in lp.warn:\\n print(ln)\\n print()\\n for curlam in laminates:\\n print(*out(curlam, args.eng, args.mat, args.fea), sep=\\\"\\\\n\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"db84ebe5716040ebd81902fff0b41cb5\",\n \"score\": \"0.5673952\",\n \"text\": \"def main( ):\\n parser = argparse.ArgumentParser(description=\\\"Count major codes\\\")\\n parser.add_argument('majors', type=argparse.FileType('r'),\\n help=\\\"A text file containing major codes, one major code per line.\\\")\\n args = parser.parse_args() # gets arguments from command line\\n majors_file = args.majors\\n count_codes(majors_file)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3037866dbb4d83e949ffdc3cb3c77656\",\n \"score\": \"0.56514245\",\n \"text\": \"def main():\\n return 'daoserver'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e74896eb1e8ec3f7aadb4933b846d810\",\n \"score\": \"0.564998\",\n \"text\": \"def main():\\n parser = argparse.ArgumentParser(\\n description='Load data into the Neo4j database for the Alliance of Genome Resources.'\\n )\\n parser.add_argument(\\n '-c',\\n '--config', help='Specify the filename of the YAML config. It must reside in the src/config/ directory',\\n default='default.yml'\\n )\\n parser.add_argument('-v',\\n '--verbose',\\n help='Enable DEBUG mode for logging.',\\n action='store_true')\\n args = parser.parse_args()\\n\\n # set context info\\n context_info = ContextInfo()\\n context_info.config_file_location = os.path.abspath('src/config/' + args.config)\\n if args.verbose:\\n context_info.env[\\\"DEBUG\\\"] = True\\n\\n debug_level = logging.DEBUG if context_info.env[\\\"DEBUG\\\"] else logging.INFO\\n\\n coloredlogs.install(level=debug_level,\\n fmt='%(asctime)s %(levelname)s: %(name)s:%(lineno)d: %(message)s',\\n field_styles={\\n 'asctime': {'color': 'green'},\\n 'hostname': {'color': 'magenta'},\\n 'levelname': {'color': 'white', 'bold': True},\\n 'name': {'color': 'blue'},\\n 'programname': {'color': 'cyan'}\\n })\\n\\n logger = logging.getLogger(__name__)\\n logging.getLogger(\\\"ontobio\\\").setLevel(logging.ERROR)\\n\\n AggregateLoader(args, logger, context_info).run_loader()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c2166c86a540913a01f3dc8c9b3a17cd\",\n \"score\": \"0.5635628\",\n \"text\": \"def main():\\n parser = cmdline_parser()\\n args = parser.parse_args()\\n\\n if args.check is True:\\n depen_list = [\\\"samtools\\\", \\\"bamtools\\\", \\\"R\\\", \\\"featurecounts\\\",\\n \\\"hisat2\\\", \\\"star\\\", \\\"faqcs\\\", \\\"stringtie\\\",\\n \\\"bedtools\\\", \\\"diamond\\\"]\\n depen_list.sort()\\n check_depen(depen_list)\\n check_pydepen()\\n sys.exit()\\n\\n #TODO: figure out why this is not working\\n os.environ[\\\"LUIGI_CONFIG_PATH\\\"] = args.config\\n\\n # setting up logging files\\n logger = create_logger(args.WORKDIR)\\n\\n # get parameters from the config file\\n paras = parse_config(args.config)\\n\\n # check if correct options are selected\\n check_input(paras, parser=parser)\\n\\n # getting absolute path of workdir\\n workdir = os.path.abspath(args.WORKDIR)\\n\\n if check_exp_design(args.EXPDSN) is False: # check if experimental design file is OK\\n sys.exit(\\\"Your experimental design file has formatting problems!\\\")\\n\\n # convert exerimental design file to a dictionary object\\n samp_dic = CheckDesign(args.EXPDSN).extract_sample_fastqs()\\n\\n no_of_jobs = 1\\n\\n # assigns filenames for databases if not specified.\\n db = check_aligner(aligner=paras[\\\"aligner\\\"],\\n hisat_index=paras[\\\"hisat_index\\\"],\\n workdir=workdir, star_db=paras[\\\"star_index\\\"])\\n\\n # TODO move this to log file\\n summarize_run(aligner=paras[\\\"aligner\\\"]) # print run information in screen\\n\\n # assign universal fasta and gff variable\\n if paras[\\\"kingdom\\\"] in [\\\"prokarya\\\", \\\"eukarya\\\"]:\\n if paras[\\\"kingdom\\\"] == \\\"prokarya\\\":\\n fasta = paras[\\\"fasta_prok\\\"]\\n gff = paras[\\\"gff_prok\\\"]\\n elif paras[\\\"kingdom\\\"] == \\\"eukarya\\\":\\n fasta = paras[\\\"fasta_euk\\\"]\\n gff = paras[\\\"gff_euk\\\"]\\n single_seq = SingleSeq(qc=paras[\\\"qc\\\"],\\n fastq_dic=samp_dic,\\n aligner=paras[\\\"aligner\\\"],\\n ref_fasta=fasta,\\n num_cpus=paras[\\\"threads\\\"],\\n local_scheduler=True,\\n hisat_index=db,\\n workdir=workdir,\\n kingdom=paras[\\\"kingdom\\\"],\\n no_of_jobs=no_of_jobs,\\n p_value=paras[\\\"q_value\\\"],\\n exp_desn_file=args.EXPDSN,\\n stardb_dir=db,\\n emap_dir=paras[\\\"emap_db\\\"],\\n gff_file=gff,\\n pathway=paras[\\\"pathway\\\"])\\n\\n # step 1, run qc\\n qc_dic = single_seq.run_faqc()\\n\\n # step 2, create database, hisat2 or stardb\\n single_seq.create_db()\\n\\n # step 3, map reads, hisat2 or stardb\\n single_seq.map_reads(qc_dic=qc_dic)\\n\\n # step 4, summarize the mapped reads\\n single_seq.map_summarize()\\n\\n # step 5, if needed\\n if paras[\\\"novel\\\"] is True: # if novel regions are to be reported\\n single_seq.extract_pp() # extract properly paired reads\\n single_seq.NovelRegions() # find novel regions\\n single_seq.create_new_gff() # create a new GFF file that has novel region info\\n gff = os.path.join(workdir, \\\"processes\\\", \\\"novel\\\", \\\"updated.gff\\\") # update gff\\n # step 6, run read counts\\n single_seq.feature_count(new_gff=gff)\\n single_seq.merge_stringtie(new_gff=gff)\\n\\n # find diff expressed gene using edgeR\\n if \\\"edgeR\\\" in paras[\\\"method\\\"]:\\n single_seq.run_edger()\\n # use DESeq2\\n if \\\"DESeq2\\\" in paras[\\\"method\\\"]:\\n single_seq.run_deseq2()\\n if \\\"ballgown\\\" in paras[\\\"method\\\"]:\\n single_seq.restringtie()\\n single_seq.run_ballgown()\\n\\n # run opaver pathway analysis\\n if paras[\\\"pathway\\\"] is True:\\n # run emapper\\n single_seq.run_emapper(new_gff=gff)\\n if \\\"edgeR\\\" in paras[\\\"method\\\"]:\\n single_seq.run_opaver(method=\\\"edgeR\\\")\\n if \\\"DESeq2\\\" in paras[\\\"method\\\"]:\\n single_seq.run_opaver(method=\\\"DESeq2\\\")\\n\\n # summarize all results into one big json file.\\n single_seq.summ_json(new_gff=gff, method=paras[\\\"method\\\"],\\n NovelRegions=paras[\\\"novel\\\"])\\n\\n elif paras[\\\"kingdom\\\"] == \\\"both\\\":\\n euk_fasta = paras[\\\"fasta_euk\\\"]\\n euk_gff = paras[\\\"gff_euk\\\"]\\n prok_fasta = paras[\\\"fasta_prok\\\"]\\n prok_gff = paras[\\\"gff_prok\\\"]\\n\\n dual_seq = DualSeq(qc=paras[\\\"qc\\\"],\\n fastq_dic=samp_dic, \\n kingdom=paras[\\\"kingdom\\\"],\\n aligner=paras[\\\"aligner\\\"],\\n euk_fasta=paras[\\\"fasta_euk\\\"],\\n prok_fasta=paras[\\\"fasta_prok\\\"],\\n prok_gff=paras[\\\"gff_prok\\\"],\\n euk_gff=paras[\\\"gff_euk\\\"],\\n workdir=workdir,\\n p_value=paras[\\\"q_value\\\"],\\n exp_desn_file=args.EXPDSN,\\n hisat_index=db,\\n local_scheduler=True,\\n pathway=paras[\\\"pathway\\\"],\\n num_cpus=paras[\\\"threads\\\"],\\n stardb_dir = paras[\\\"star_index\\\"],\\n emap_dir=paras[\\\"emap_db\\\"])\\n\\n # step 1, run qc\\n qc_dic = dual_seq.run_faqc()\\n \\n # step 2, create database, hisat2 or stardb\\n dual_seq.create_db()\\n\\n # step 3, map reads, hisat2 or stardb\\n dual_seq.map_reads()\\n\\n # step 4, summarize the mapped reads\\n dual_seq.map_summarize()\\n dual_seq.split_prokeuk()\\n\\n # step 5, if needed\\n if paras[\\\"novel\\\"] is True: # if novel regions are to be reported\\n dual_seq.extract_pp() # extract properly paired reads\\n dual_seq.NovelRegions() # find novel regions\\n dual_seq.create_new_gff() # create a new GFF file that has novel region info\\n euk_gff = os.path.join(workdir,\\n \\\"processes\\\", \\\"novel\\\",\\n \\\"euk_updated.gff\\\") # update gff\\n prok_gff = os.path.join(workdir, \\\"processes\\\", \\\"novel\\\",\\n \\\"prok_updated.gff\\\") # update gff\\n \\n # step 6, run read counts\\n print(\\\"Counting eukaryotes\\\")\\n dual_seq.feature_counts(new_gff=euk_gff, kingdom=\\\"eukarya\\\")\\n dual_seq.feature_counts(new_gff=prok_gff, kingdom=\\\"prokarya\\\")\\n dual_seq.merge_stringtie(new_gff=prok_gff + \\\",\\\" + euk_gff)\\n\\n # find diff expressed gene using edgeR\\n if \\\"edgeR\\\" in paras[\\\"method\\\"]:\\n dual_seq.run_edger(kingdom=\\\"eukarya\\\")\\n dual_seq.run_edger(kingdom=\\\"prokarya\\\")\\n if \\\"DESeq2\\\" in paras[\\\"method\\\"]:\\n dual_seq.run_deseq2(kingdom=\\\"eukarya\\\")\\n dual_seq.run_deseq2(kingdom=\\\"prokarya\\\")\\n if \\\"ballgown\\\" in paras[\\\"method\\\"]:\\n dual_seq.restringtie()\\n dual_seq.run_ballgown()\\n\\n if paras[\\\"pathway\\\"] is True:\\n # run emapper\\n dual_seq.run_emapper(new_gff=prok_gff, kingdom=\\\"prokarya\\\", fasta=prok_fasta)\\n dual_seq.run_emapper(new_gff=euk_gff, kingdom=\\\"eukarya\\\", fasta=euk_fasta)\\n if \\\"edgeR\\\" in paras[\\\"method\\\"]:\\n dual_seq.run_opaver(method=\\\"edgeR\\\", kingdom=\\\"prokarya\\\")\\n dual_seq.run_opaver(method=\\\"edgeR\\\", kingdom=\\\"eukarya\\\")\\n if \\\"DESeq2\\\" in paras[\\\"method\\\"]:\\n dual_seq.run_opaver(method=\\\"DESeq2\\\", kingdom=\\\"prokarya\\\")\\n dual_seq.run_opaver(method=\\\"DESeq2\\\", kingdom=\\\"eukarya\\\")\\n\\n # summarize all results into one big json file.\\n dual_seq.summ_json(new_gff=euk_gff, method=paras[\\\"method\\\"],\\n NovelRegions=paras[\\\"novel\\\"],\\n kingdom=\\\"eukarya\\\",\\n fasta=euk_fasta)\\n dual_seq.summ_json(new_gff=euk_gff, method=paras[\\\"method\\\"],\\n NovelRegions=paras[\\\"novel\\\"],\\n kingdom=\\\"prokarya\\\",\\n fasta=prok_fasta)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e2338876881ec41fc2d19277660f010d\",\n \"score\": \"0.5627442\",\n \"text\": \"def main():\\r\\n params = get_configuration(print_diagnostics=True, with_neptune=True, inject_parameters_to_gin=True)\\r\\n LOG_PATH = os.path.join(params.BASE_PATH, 'tests', params.GAME)\\r\\n runner = RolloutsRunner(LOG_PATH,create_rainbow_rollouts_agent)\\r\\n runner.run_experiment()\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":386,"cells":{"query_id":{"kind":"string","value":"f12dbbd813dce1dfccea81d087209d5a"},"query":{"kind":"string","value":"Create a simple user that we link all the answers to."},"positive_passages":{"kind":"list like","value":[{"docid":"f841e3174f163c6984457f84a2649161","score":"0.0","text":"def begin(request):\n request.session.flush() # \"Logout\" from any previous session\n\n if request.method == \"POST\":\n new_name = request.POST[\"name\"]\n new_motto = request.POST[\"motto\"]\n # Try this again if they didn't put in a name\n if not new_name or not new_motto:\n context = {\"error_message\": \"Please pick a name and motto for yourself!\"}\n return render(request, \"ggpoll/begin.html\", context)\n # Create the new user and store the user info into the Session\n # then redirect to the first question\n new_user = GGUser(name=new_name, motto=new_motto)\n new_user.save()\n request.session['user_id'] = new_user.id # 'log in' with new user\n first_question = GGQuestion.objects.all()[0]\n return HttpResponseRedirect(reverse(\"ggpoll:ask_question\", args=(first_question.id, )))\n return render(request, \"ggpoll/begin.html\")","title":""}],"string":"[\n {\n \"docid\": \"f841e3174f163c6984457f84a2649161\",\n \"score\": \"0.0\",\n \"text\": \"def begin(request):\\n request.session.flush() # \\\"Logout\\\" from any previous session\\n\\n if request.method == \\\"POST\\\":\\n new_name = request.POST[\\\"name\\\"]\\n new_motto = request.POST[\\\"motto\\\"]\\n # Try this again if they didn't put in a name\\n if not new_name or not new_motto:\\n context = {\\\"error_message\\\": \\\"Please pick a name and motto for yourself!\\\"}\\n return render(request, \\\"ggpoll/begin.html\\\", context)\\n # Create the new user and store the user info into the Session\\n # then redirect to the first question\\n new_user = GGUser(name=new_name, motto=new_motto)\\n new_user.save()\\n request.session['user_id'] = new_user.id # 'log in' with new user\\n first_question = GGQuestion.objects.all()[0]\\n return HttpResponseRedirect(reverse(\\\"ggpoll:ask_question\\\", args=(first_question.id, )))\\n return render(request, \\\"ggpoll/begin.html\\\")\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"c40661dc617572feba289b687098d62c","score":"0.7658639","text":"def create_user(self, user_id: str, user_name: str) -> None:","title":""},{"docid":"32f5b47e07cd7cd2b99bba64fa162310","score":"0.7454858","text":"def createUser():\n user_data = fb.get_initial_user_data()\n raise NotImplementedError","title":""},{"docid":"cd8475fe2dd3bc95aa3e4373508424b9","score":"0.72297966","text":"def create_user(\n self,\n user: User,\n ) -> None:\n ...","title":""},{"docid":"ae44b8b6f5f40e693bb63ecf8660983e","score":"0.7228752","text":"def create_user():\n\n # Make the new user JSON from form data\n new_user = {\n \"username\": request.form.get('username'),\n \"password\": request.form.get('password'),\n \"bio\": request.form.get('bio'),\n }\n\n # Insert into PyMongo database\n db.users.insert_one(new_user)\n\n # Render some HTML\n return \"\"\"\n User created successfully!\n <a href=\"/users\">Back to Home</a>\n \"\"\"","title":""},{"docid":"1bf872781698788db2659a6f9af33942","score":"0.7165631","text":"def sample_user():\n return get_user_model()\\\n .objects.\\\n create_user({'email': fake.email(), 'password': fake.password()})","title":""},{"docid":"0121f67127784198ccbe51393bd12f5a","score":"0.7164468","text":"def sample_user(email=user_v['email'], password=user_v['password']):\n return get_user_model().objects.create_user(email, password)","title":""},{"docid":"bc9a94573866bc16c3c7a11df748f484","score":"0.7090674","text":"def sample_user(email='test@recipeapi.com', password='somethingrandom'):\n return get_user_model().objects.create_user(email=email, password=password)","title":""},{"docid":"71a6d34f87b4fec35f175451a28a63d8","score":"0.7038464","text":"def entry():\n new_user = User(username='myuser',\n email='myuser@example.com',\n created=dt.now(),\n bio=\"In West Philadelphia born and raised, on the playground is where I spent most of my days\",\n admin=False\n )\n db.session.add(new_user)\n db.session.commit()\n return make_response(\"User created!\")","title":""},{"docid":"7144ec956d7748793fd7ac99e6255e41","score":"0.7023137","text":"def sample_user(email='test@gmail.com', password='testpass'):\n return get_user_model().objects.create_user(email, password)","title":""},{"docid":"7144ec956d7748793fd7ac99e6255e41","score":"0.7023137","text":"def sample_user(email='test@gmail.com', password='testpass'):\n return get_user_model().objects.create_user(email, password)","title":""},{"docid":"d1030726edadce9706609bd1b1f868d6","score":"0.6992834","text":"def sample_user(email='test@londonappdev.com', password='testpass'):\n return get_user_model().objects.create_user(email, password)","title":""},{"docid":"d1030726edadce9706609bd1b1f868d6","score":"0.6992834","text":"def sample_user(email='test@londonappdev.com', password='testpass'):\n return get_user_model().objects.create_user(email, password)","title":""},{"docid":"31ae0d2f6eca9e31861496894c1e1462","score":"0.6927966","text":"def sample_user(email='test@testdomain.com', password='testpass'):\n return get_user_model().objects.create_user(email, password)","title":""},{"docid":"3cde5f7c1a7227f69a76666cd92abbdd","score":"0.69101703","text":"def create_user(self, name='Some name'):\n return self.database.insert(name)","title":""},{"docid":"9580115af87da74f76e86883ee807932","score":"0.68891996","text":"def sample_user(phone_number='4086432477', password='testpass'):\n return get_user_model().objects.create_user(phone_number, password)","title":""},{"docid":"da914aa06d2faf6057f3473728314bac","score":"0.6849761","text":"def create_sample_user(email=\"test@firstapp.com\", password=\"test1\"):\n return get_user_model().objects.create_user(email, password)","title":""},{"docid":"d310e4ae45928ccb60c82c9572fb57da","score":"0.68457526","text":"def _create_user(self):\n\n msg = QMessageBox()\n user = kks.create_user(self._username_line.text(), self._password_line.text())\n \n if not user:\n msg.setText('Käyttäjätunnus on jo käytössä')\n msg.exec_()\n else:\n msg.setText('Uusi käyttäjä luotu')\n msg.exec_()","title":""},{"docid":"0aa13ed1e1136f754de8e5124000d701","score":"0.684187","text":"def admin_create_user(self):\n resp = self.admin_register()\n reply = self.admin_login()\n token = reply['token']\n user = dict(\n name='Summer Love',\n username='love',\n password='Andela8',\n role='attendant'\n )\n\n resp = self.client.post(\n '/api/v1/users',\n content_type='application/json',\n data=json.dumps(user),\n headers={'Authorization': 'Bearer {}'.format(token)}\n )\n\n reply = json.loads(resp.data.decode())\n return reply","title":""},{"docid":"58d462e89e1fa02990ce29cdeb72043a","score":"0.68353564","text":"def create_new_user():\n\n return render_template('create_new_user.html')","title":""},{"docid":"ee862f60b59a9532b3352aeeaf7509f9","score":"0.68202496","text":"def create_user(context,galaxy,email,public_name,password,only_check,\n message_template):\n # Check message template is a .mako file\n if message_template:\n if not message_template.endswith(\".mako\"):\n logger.critical(\"Message template '%s' is not a .mako file\"\n % message_template)\n sys.exit(1)\n # Get a Galaxy instance\n gi = context.galaxy_instance(galaxy)\n if gi is None:\n logger.critical(\"Failed to connect to Galaxy instance\")\n sys.exit(1)\n # Sort out email and public name\n if public_name:\n if not users.check_username_format(public_name):\n logger.critical(\"Invalid public name: must contain only \"\n \"lower-case letters, numbers and '-'\")\n sys.exit(1)\n else:\n # No public name supplied, make from email address\n public_name = users.get_username_from_login(email)\n # Create user\n print(\"Email : %s\" % email)\n print(\"Name : %s\" % public_name)\n sys.exit(users.create_user(gi,email,public_name,password,\n only_check=only_check,\n mako_template=message_template))","title":""},{"docid":"bad2afd7b85622a4f1501681f04a73bd","score":"0.68134016","text":"def new_user(self):\n username = self.gui.username_entry.get()\n salt = bcrypt.gensalt()\n while not self.gui.client.dbcom.check_salt(salt):\n salt = bcrypt.gensalt()\n password = bcrypt.hashpw(self.gui.password_entry.get().encode(), salt)\n email = self.gui.mail_entry.get()\n phone_number = self.gui.number_entry.get()\n self.gui.client.dbcom.add_user(username, salt, password, email, phone_number)\n self.gui.build_log_in_ui()","title":""},{"docid":"df065ae1bb66009f3880b761a8b871a4","score":"0.68031585","text":"def create_new_user_node(i):\n pass","title":""},{"docid":"d7d099ce2dc3b0105b83c17b30d3a70c","score":"0.67799646","text":"def new_user(self, **kwargs):\n num = self._user_numbers.pop()\n kwargs.setdefault(\"first_name\", \"FIRST%04d\" % num)\n kwargs.setdefault(\"last_name\", \"LAST%04d\" % num)\n kwargs.setdefault(\"username\", \"user%04d\" % num)\n user = User(**kwargs)\n user.save()\n self._users.append(user)\n return user","title":""},{"docid":"2ffefdc305737cdba44876e77df1a479","score":"0.67655015","text":"def new_user():\n\n return render_template(\"user_form.html\")","title":""},{"docid":"cf022b77565799d4b87c4c2cf45bfc05","score":"0.6746994","text":"def create_askbot_user(zd_user):\n if zd_user.email is None:\n username = zd_user.name.replace(\" \", \"_\").lower()\n email = ''\n else:\n username = zd_user.email\n email = zd_user.email\n username = ensure_unique_username(username[:30])\n\n # last_seen cannot be null\n last_seen = zd_user.last_login\n if not last_seen:\n last_seen = zd_user.created_at\n\n # lookup organization name (todo: cache this)\n about = \"\"\n if zd_user.organization_id:\n try:\n org = zendesk_models.Organization.objects.get(organization_id=zd_user.organization_id)\n about = org.name\n except zendesk_models.Organization.DoesNotExist:\n pass\n\n ab_user = askbot_models.User(\n username = username,\n first_name = zd_user.name.rpartition(' ')[0].strip()[:30],\n last_name = zd_user.name.rpartition(' ')[2].strip()[:30],\n real_name = zd_user.name[:100],\n email = email,\n email_isvalid = zd_user.is_verified,\n date_joined = zd_user.created_at,\n last_seen = last_seen,\n is_active = zd_user.is_active,\n about = about,\n )\n ab_user.save()\n return ab_user","title":""},{"docid":"c8fee5047f2c9525534ff0983cc091b4","score":"0.67408246","text":"def _create_user(username,telefone,nome,endereço,data_de_nascimento):","title":""},{"docid":"2cdd0f157081e922b9a16a8f132fb790","score":"0.67324775","text":"def create_user(self) -> 'outputs.ActingUserResponse':\n return pulumi.get(self, \"create_user\")","title":""},{"docid":"e18f170f90740889ed20b07a68c1c9d5","score":"0.673237","text":"def create_new_user(self, redditor):\n print(\"Creating user: \" + str(redditor))\n\n new_user_item = {\n 'user_id' : redditor.id,\n 'username' : redditor.name,\n 'submission_score' : 0,\n 'distribution_score' :0,\n 'total_score' : 0\n }\n if self.put_item(DataAccess.Tables.USERS, new_user_item):\n print(\"Created user: \" + str(redditor))\n return True\n else:\n print(\"Failed to create user: \" + str(redditor))\n return False","title":""},{"docid":"68f8a28bf3ec4ce6a4527fd2d38973b9","score":"0.6729003","text":"def create_sample_user(email='test@webapps.agency', password='password123'):\n return get_user_model().objects.create_user(email, password)","title":""},{"docid":"3bdaafe6c0ff683d4f193ba80886bedf","score":"0.6703305","text":"def _create_user(self, email, password):\n self.parent.browser.find_element_by_id('create-user-button').click()\n time.sleep(DELAY)\n self.parent.browser.find_element_by_id('input-username').send_keys(email)\n time.sleep(DELAY)\n self.parent.browser.find_element_by_id('input-password').send_keys(password)\n time.sleep(DELAY)\n self.parent.browser.find_element_by_id('create-user-commit').click()\n print(\"user with [{}], [{}] created\".format(email, password))","title":""},{"docid":"88baf383dc76ab16135271232abd4d35","score":"0.6692833","text":"def create_user(fname,sname,number,password):\n new_user=User(fname,sname,number,password)\n return new_user","title":""},{"docid":"d92155b00dce49485f1c3abed4f2715c","score":"0.6691482","text":"def create_user(name, passw):\n new_user = User(name, passw)\n return new_user","title":""},{"docid":"9a9befb3540c8eb46cba6f293ba5302f","score":"0.66777927","text":"def create_user(fname, lname, email, password, consent=False):\n\n user = User(fname=fname, lname=lname, email=email, password=password, consent=False) # is consent default value added here as well as in arguments?\n\n db.session.add(user)\n db.session.commit()\n\n return user","title":""},{"docid":"2794fd3617db7cb79400305de31a6aae","score":"0.66645825","text":"def testCreate1User(self):\n request = self.factory.post(\"/api/user/create\", json.dumps({ 'username' : 'Tom',\n 'password' : '123456',\n 'user_type' : 'customer',\n 'email' : 'tommeng@berkeley.edu',\n }), content_type='application/json')\n response = views.create_user(request);\n respCreate = self.getDataFromResponse(response)\n\n self.assertSuccessResponse(respCreate)\n self.assertEquals(\"Tom\", respCreate['username'], \"Username wrong\")\n self.assertEquals(\"customer\", respCreate['user_type'])","title":""},{"docid":"f0fa4f9181e412ccd094cbc58c9909aa","score":"0.6648792","text":"def test_create_user(self):\n pass","title":""},{"docid":"537ad424e96fdd408cadd158c2e07b49","score":"0.66471165","text":"def new_user(cls, user_name, email):\n user = User(name=user_name, email=email)\n user.put()\n score = Score(parent=user.key, date=datetime.now(), attempts=0)\n score.put()\n return 'User {} created!'.format(user_name)","title":""},{"docid":"619dd5bad8b29b3c3dd02f094a3dcefa","score":"0.6639765","text":"async def create_user_open(user_in: schemas.UserCreateMe):\n user = await crud.user.get_by_email(email=user_in.email)\n if user:\n raise HTTPException(\n status_code=status.HTTP_400_BAD_REQUEST,\n detail=\"The user with this username already exists in the system\",\n )\n user = await crud.user.create_me(obj_in=user_in)\n return await schemas.UserPydantic.from_tortoise_orm(user)","title":""},{"docid":"a5ec0e6bd78a0b648535eb20644f0512","score":"0.6637918","text":"def create_user(fullname, username, password):\n new_user = User(fullname, username, password)\n return new_user","title":""},{"docid":"c65acb9091cd72fd493502f9140f9208","score":"0.6635635","text":"def userCreate(self, request, tag):\n userCreator = liveform.LiveForm(\n self.createUser,\n [liveform.Parameter(\n \"localpart\",\n liveform.TEXT_INPUT,\n unicode,\n \"localpart\"),\n liveform.Parameter(\n \"domain\",\n liveform.TEXT_INPUT,\n unicode,\n \"domain\"),\n liveform.Parameter(\n \"password\",\n liveform.PASSWORD_INPUT,\n unicode,\n \"password\")])\n userCreator.setFragmentParent(self)\n return userCreator","title":""},{"docid":"adb20631bd7cc235e7e2c9e07961b275","score":"0.66353905","text":"def create_empty_user():\n return User(email=\"\", nick=\"\", level=User.Level.Client)","title":""},{"docid":"fd85e2af2da79e7577fb232ded1fcf6a","score":"0.6633111","text":"def create_valid_user_test(self):","title":""},{"docid":"e7354e58a00fcbc8760e89d183e74283","score":"0.6626516","text":"def new_user(self, request):\r\n user = get_user_model()()\r\n return user","title":""},{"docid":"1a4e86afd86ebfb8fc145040f6fc99d0","score":"0.6608983","text":"def create_initial_user():\n\n # check if there is any user in the db\n if User.query.count() == 0:\n # create a user\n user = User(username=\"admin\", password=hashlib.sha256(\"admin\".encode(\"utf8\")).hexdigest(),\n email=\"webmaster@example.org\")\n user.is_admin = True\n db.session.add(user)\n db.session.commit()","title":""},{"docid":"d3fcc43785b4dee883cfe7dea5f13e95","score":"0.66077644","text":"def create_user():\n # check the token\n token = request.form['token']\n if token != ACCEPT_TOKEN:\n return 'Error: not authorized'\n\n u = User(es)\n return u.create_from_req(request)","title":""},{"docid":"2025ed72a4512000278c999195da4cdc","score":"0.65977323","text":"def create_user(fname, lname, password):\n new_user = User(fname, lname,password)\n return new_user","title":""},{"docid":"193ef5d2be5026820e55cbc4addeeae2","score":"0.6583698","text":"def post(self, user_id=None):\n name = self.get_argument(\"name\", \"\")\n email = self.get_argument(\"email_address\", \"\")\n password = self.get_argument(\"password\", \"\")\n new_user = self.create_user(name, email, password)\n self.write(new_user.to_dict())","title":""},{"docid":"200135420c1600bd526ff1fc6c262b37","score":"0.6582868","text":"def create_user(user_data: dict) -> User:\n user = User()\n user.admin = False\n user.name = user_data[\"display_name\"]\n user.external_id = user_data[\"id\"]\n return user","title":""},{"docid":"0a696796bc8685cb6ac69ad4887af3ce","score":"0.6565887","text":"def create(self, data):\n return User.objects.create_user(**data)","title":""},{"docid":"6e9db6bc9ce7f3781b7540ca82fbe10e","score":"0.6561448","text":"def create_user(backend, details, response, uid, username, user=None, *args, **kwargs):\n if user:\n return {'user': user}\n if not username:\n return None\n\n request = kwargs['request']\n user = UserSocialAuth.create_user(username = username)\n# profile = UserProfile.objects.create_user(user = user)\n\n return {\n 'user': user,\n 'is_new': True\n }","title":""},{"docid":"96e671b4273c7888f75bd6fcc1cd1d33","score":"0.65509975","text":"def _create_user(self, data):\n username = data[\"username\"]\n self._signup_user(data)\n validation_mail = mail.outbox[-1]\n self.assertTrue(\n \"signup\" in validation_mail.subject,\n \"There was no email\"\n \" sent which had 'signup' in the subject line\",\n )\n # validate the user with the link that was emailed\n pattern = \"/testserver(.*)\" + PI_LINE_END_REGEX\n validationlink_result = re.search(\n pattern, validation_mail.body, re.IGNORECASE\n )\n self.assertTrue(\n validationlink_result,\n \"could not find any link in\"\n \"registration email. Tried to match pattern '{}' but found no match in\"\n \"this email: {}{}\".format(\n pattern, PI_LINE_END_REGEX, validation_mail.body\n ),\n )\n validationlink = validationlink_result.group(1).strip()\n response = self.client.get(validationlink)\n self.assertEqual(\n response.status_code,\n 302,\n \"Could not load user validation link. Expected\"\n \" a redirect (HTTP 302), got HTTP {} instead\".format(\n response.status_code\n ),\n )\n resp = self.client.get(\"/accounts/\" + username + \"/\")\n self.assertEqual(\n resp.status_code,\n 200,\n \"Could not access user account after using\"\n \"validation link! Expected 200, got {} instead\".format(\n resp.status_code\n ),\n )\n User = get_user_model() # noqa: N806\n query_result = User.objects.filter(username=username)\n return query_result[0]","title":""},{"docid":"a9f718fd99fa61731669d3ecf918ee3c","score":"0.65470034","text":"def _create_user(self):\n self.user = User.objects.create_user('test', 'test@test.test', 'test')\n self.api_client.login(\n username='test',\n password='test',\n )","title":""},{"docid":"108f120df0fa6ca83aafd9bc0c87f356","score":"0.6538275","text":"def test_create_user(self):\n new_user = {\n \"_id\": ObjectId(\"000000000000000000000002\"),\n \"name\": \"Polly O'Donovan\",\n \"username\": \"pollypocket\",\n \"my_recipes\": [],\n \"favourite_recipes\": []\n }\n app.add_user(new_user)\n self.assertIn(new_user, list(app.get_users()))\n app.delete_user('000000000000000000000002')","title":""},{"docid":"e839f4f52e4b71bd3fdca345790076bb","score":"0.65374136","text":"def createuser(username=None, password=None, admin=None):\n u_name = username\n pw = password\n make_admin = admin\n\n if u_name is None:\n while True:\n u_name = prompt(\"User Name\")\n user = User.query.filter(User.name==u_name).first()\n if user is not None:\n print(\"{}: USER ALREADY EXISTS!\".format(u_name))\n else:\n break\n\n if pw is None:\n pw = prompt_pass(\"Password\")\n while True:\n pw_again = prompt_pass(\"Password Again\")\n if pw != pw_again:\n print(\"PASSWORDS DO NOT MATCH!\")\n else:\n break\n\n if make_admin is None:\n make_admin = prompt_bool(\"Do you wish to make {} an administrator?\".\\\n format(u_name))\n\n user = User(name=u_name, password=\"\", admin=make_admin, enabled=True)\n user.set_password(pw)\n\n db.session.add(user)\n db.session.commit()\n print(\"Successfully created '{}' with ID: {}.\".format(user.name, user.id))","title":""},{"docid":"a6f2d85cfa166855cd5d540d43452f9f","score":"0.6529134","text":"def user():\n return User()","title":""},{"docid":"36da2f39ee6de223831a14181e018ddd","score":"0.6527107","text":"def create(usr, level):\n toret = User()\n\n toret.email = usr.email()\n toret.nick = usr.nickname()\n toret.level = level\n\n return toret","title":""},{"docid":"a1dd381de65afc8bc914d2885f946173","score":"0.6525508","text":"def create_new_user( self, trans, **kwd ):\n return trans.response.send_redirect( web.url_for( controller='user',\n action='create_non_feide_user_in_GOLD',\n cntrller='project_admin' ) )","title":""},{"docid":"9ec00f3dae6522b9afe610072c8fcc76","score":"0.6521141","text":"def create_example_users(self):\n # TODO: implement the method to add the example users by using \"add_user\" function and return a string that\n # shows it has been added successfully write your code below\n # write your code below\n pass","title":""},{"docid":"3412d63f0dc16ecb34f5599cd9866ddb","score":"0.6511392","text":"def create_user(self):\n data = {\n \"username\": \"TestUserdsa\" + str(random.randrange(1, 1000000)),\n \"password\": \"Aa12Aa12\",\n \"email\": \"benharushtomer@gmail.com\"\n }\n response = requests.post(self.urls['create_user'],\n data=data)\n print(response.text)\n return self.get_token(data['username'], data['password'],)","title":""},{"docid":"df31516aaae7ab80e40fd0b6e0cae62c","score":"0.65057933","text":"def create_user() -> bool:\n\n # TODO: verify len, number, lower and upper\n\n name = input(\"Insert username: \")\n password = Encrypt.encrypt_data(key=constant.KEY, data=input(\"Insert Password: \"))\n email = input(\"Insert email: \")\n number = input(\"Insert phone number: \")\n\n # Creating user\n new_user = User(name=name, email=email, number=number)\n\n try:\n # Insert the user into the database\n user_id = conn.create_user(user=new_user, password=password)\n except Exception as e:\n print(\"Error in the Database, \", e)\n return False\n\n if user_id == -1:\n return False\n\n return True","title":""},{"docid":"47b8963597772187399b99c9fae530c7","score":"0.65010655","text":"def createUser(self):\r\n json = request.get_json()\r\n user = User(None, json[\"email\"], EncryptionService.hashPassword(json[\"password\"]), json[\"name\"],\r\n None, None, json[\"group_id\"], json[\"waterschap_id\"])\r\n user.addUser()\r\n return make_response(jsonify(user.json()))","title":""},{"docid":"d49772e9654759f4ebfbf1944b6ecb66","score":"0.64808685","text":"def create_user():\n return render_template('create_page.html')","title":""},{"docid":"6cae7e0251b9be9a04b2b84c43a7817f","score":"0.64792997","text":"def add_user():\n # get form variables from register_form.html\n fname = request.form['fname']\n lname = request.form['lname']\n email = request.form['email']\n password = request.form['password']\n mobile = request.form['mobile']\n\n user_id = add_to_users(fname, lname, email, password, mobile)\n flash('Wanda welcomes you! Please set up your preferences.')\n # add user's first name and user_id to session\n session['fname'] = fname\n session['user_id'] = user_id\n # send confirmation text to user's mobile using Twilio\n send_welcome_text(mobile, user_id)\n return render_template('/preferences.html')","title":""},{"docid":"954db34bc27ceea91f04ef40dff73708","score":"0.64756787","text":"def add_user(form):\n username = ws.get_cgi_parameter_str(form, PARAM.USERNAME)\n password_1 = ws.get_cgi_parameter_str(form, PARAM.PASSWORD_1)\n password_2 = ws.get_cgi_parameter_str(form, PARAM.PASSWORD_2)\n must_change_password = ws.get_cgi_parameter_bool(\n form, PARAM.MUST_CHANGE_PASSWORD)\n\n may_use_webviewer = ws.get_cgi_parameter_bool(\n form, PARAM.MAY_USE_WEBVIEWER)\n may_view_other_users_records = ws.get_cgi_parameter_bool(\n form, PARAM.MAY_VIEW_OTHER_USERS_RECORDS)\n view_all_patients_when_unfiltered = ws.get_cgi_parameter_bool(\n form, PARAM.VIEW_ALL_PTS_WHEN_UNFILTERED)\n may_upload = ws.get_cgi_parameter_bool(form, PARAM.MAY_UPLOAD)\n superuser = ws.get_cgi_parameter_bool(form, PARAM.SUPERUSER)\n may_register_devices = ws.get_cgi_parameter_bool(\n form, PARAM.MAY_REGISTER_DEVICES)\n may_use_webstorage = ws.get_cgi_parameter_bool(\n form, PARAM.MAY_USE_WEBSTORAGE)\n may_dump_data = ws.get_cgi_parameter_bool(form, PARAM.MAY_DUMP_DATA)\n may_run_reports = ws.get_cgi_parameter_bool(form, PARAM.MAY_RUN_REPORTS)\n may_add_notes = ws.get_cgi_parameter_bool(form, PARAM.MAY_ADD_NOTES)\n\n user = User(username, False)\n if user.user:\n return user_management_failure_message(\n \"User already exists: \" + username)\n if not is_username_permissible(username):\n return user_management_failure_message(\n \"Invalid username: \" + ws.webify(username))\n if password_1 != password_2:\n return user_management_failure_message(\"Passwords don't mach\")\n if len(password_1) < MINIMUM_PASSWORD_LENGTH:\n return user_management_failure_message(\n \"Password must be at least {} characters\".format(\n MINIMUM_PASSWORD_LENGTH\n ))\n\n user = User(username, True)\n user.set_password(password_1)\n\n user.may_use_webviewer = may_use_webviewer\n user.may_view_other_users_records = may_view_other_users_records\n user.view_all_patients_when_unfiltered = view_all_patients_when_unfiltered\n user.may_upload = may_upload\n user.superuser = superuser\n user.may_register_devices = may_register_devices\n user.may_use_webstorage = may_use_webstorage\n user.may_dump_data = may_dump_data\n user.may_run_reports = may_run_reports\n user.may_add_notes = may_add_notes\n\n user.save()\n if must_change_password:\n user.force_password_change()\n\n audit(\n (\n \"User created: {}: \"\n \"may_use_webviewer={}, \"\n \"may_view_other_users_records={}, \"\n \"view_all_patients_when_unfiltered={}, \"\n \"may_upload={}, \"\n \"superuser={}, \"\n \"may_register_devices={}, \"\n \"may_use_webstorage={}, \"\n \"may_dump_data={}, \"\n \"may_run_reports={}, \"\n \"may_add_notes={}, \"\n \"must_change_password={}\"\n ).format(\n user.user,\n may_use_webviewer,\n may_view_other_users_records,\n view_all_patients_when_unfiltered,\n may_upload,\n superuser,\n may_register_devices,\n may_use_webstorage,\n may_dump_data,\n may_run_reports,\n may_add_notes,\n must_change_password\n )\n )\n return user_management_success_message(\"User \" + user.user + \" created\")","title":""},{"docid":"4657cee1d7f3ac5630d6da2adf6c7007","score":"0.64742255","text":"def create_user(args):\n args = args_cleaner(args)\n \n # check if username has been passed.\n if args.get('username'): username = args.get('username')\n else: username = input_(msg='username: ')\n \n # check if username already exists.\n if auth.get_user(username):\n print (f\"'{username}' already exists.\")\n return\n \n password = input_(msg=f\"password for '{username}' (hidden): \", pswd=True)\n \n # create the user.\n created = auth.create_user(username, password)\n if not created:\n print ('Something went wrong. please try again.')\n return\n \n print (f\"user '{username}' has been created.\")","title":""},{"docid":"ef3e5841194e3b43517076b80d243866","score":"0.646342","text":"def create_user(self, **attrs):\n return self._create(user.User, **attrs)","title":""},{"docid":"217e2594f051ecb05875327043984191","score":"0.6452617","text":"def create_user(request, user, details, backend, *args, **kwargs):\n # If user already exists, don't create a user.\n if user is not None:\n return None\n\n is_new = False\n user = None\n\n username = '{0}-{1}'.format(details['username'], backend.name)\n email = details.get('email') or details['username']\n user = User.objects.create_user(username=username, email=email,\n password='!')\n is_new = True\n\n return {\n 'user': user,\n 'is_new': is_new\n }","title":""},{"docid":"593c75839170b6f9031a25f6dff92b11","score":"0.6444597","text":"def fake_single(self, fake, approved=True):\n user = self.create_user(\n email=fake.email(),\n password=fake.password(),\n first_name=fake.first_name(),\n last_name=fake.last_name(),\n )\n user.save()\n user.memberprofile.new_notify = not approved\n user.memberprofile.date_of_birth = fake.date_time_between(start_date='-99y', end_date='now').date()\n user.memberprofile.gender = random.choice(('m', 'f'))\n user.memberprofile.address = fake.address()\n user.memberprofile.postcode = fake.postcode()\n user.memberprofile.home_phone = fake.phone_number()\n user.memberprofile.mobile_phone = fake.phone_number()\n user.memberprofile.next_of_kin_name = fake.name()\n user.memberprofile.next_of_kin_relation = fake.first_name()\n user.memberprofile.next_of_kin_phone = fake.phone_number()\n user.memberprofile.save()\n return user","title":""},{"docid":"1d7839379860b0c5c49eb89942d1fb3d","score":"0.6443251","text":"def create_test_user(id = \"\"):\n username = f\"test_user{id}\"\n email = f\"example{id}@example.com\"\n password = \"password1\"\n return User.objects.create_user(username, email, password)","title":""},{"docid":"ee1dea61eab82c8a780938aa4afd8a2e","score":"0.6438962","text":"def test_create_users():\n User(username=\"\", password=\"\", last_trained_on=None, tbl_rating_user_id=0)","title":""},{"docid":"0b46bf67876d91a14d78d8c98a6164a9","score":"0.64366597","text":"def create_user(self, name, admin=False):\n return self.create_users([name], admin)","title":""},{"docid":"a442f9396c678d021a49a30354550049","score":"0.64342165","text":"async def create_user(self, username, hashed_password, role_id):\n pass","title":""},{"docid":"83feac2cec19518f591aff2932c27929","score":"0.641548","text":"def admin_create_user2(self):\n resp = self.admin_register()\n reply = self.admin_login()\n token = reply['token']\n user = dict(\n name='Paul Walker',\n username='walker',\n password='Andela8',\n role='attendant'\n )\n\n resp = self.client.post(\n '/api/v1/users',\n content_type='application/json',\n data=json.dumps(user),\n headers={'Authorization': 'Bearer {}'.format(token)}\n )\n\n reply = json.loads(resp.data.decode())\n return reply","title":""},{"docid":"aa9f39ba54fadcc24634c32b9b2d74d3","score":"0.6414347","text":"async def create_user(\n context: CommandContext,\n username: str,\n password: str,\n email: str,\n first_name: str,\n last_name: str,\n):\n user = User.objects.create_user(\n username=username,\n password=password,\n email=email,\n first_name=first_name,\n last_name=last_name,\n )\n runtime_user = RuntimeUser.from_persistent_user(user)\n context.runtime_user = runtime_user\n return {'user': {'id': user.id}}","title":""},{"docid":"f34a0bc3f8f643ae1275df5664b79b48","score":"0.6404594","text":"def create_user(db: Session, user: schemas.UserCreate) -> None:\n new_user = models.User(name=user.name)\n new_user.password = bcrypt.hashpw(user.password, bcrypt.gensalt())\n db.add(new_user)\n db.commit()","title":""},{"docid":"56b27a1e6d45c0527c10288003954da2","score":"0.6402819","text":"def add_one_user(p_user):\n print(' Adding user \"{}\" now.'.format(p_user))\n User._do_user_create(p_user)\n User._update_sudoers(p_user)\n User._create_workspace(p_user)","title":""},{"docid":"65bfc46101a35217ae2cec654f26bd8d","score":"0.6393311","text":"def create_a_user(self, username='test', email='info@test.co',\n password='Test123.'):\n user = User.objects.create_user(username, email, password)\n user.save()\n return user","title":""},{"docid":"dc2d4bb691278192512a3bc28da3c758","score":"0.63884735","text":"def _create_user(self, email, password, first_name, last_name, **extra_fields):\n if not email:\n raise ValueError('The email cannot be empty.')\n email = self.normalize_email(email)\n user = self.model(email=email, first_name=first_name, last_name=last_name, **extra_fields)\n user.set_password(password)\n user.save(using=self._db)\n\n # Send email to newly created user\n subject = 'Welcome to lifTUe!'\n message = 'Welcome to lifTUe!\\n\\n You can start using the application using the following credentials:\\n\\n' \\\n 'Email: ' + email + '\\n Password: ' + password + '\\n\\n You will need to change your password the ' \\\n 'first time you log in.'\n\n send_mail(subject, message, 'noreply@gelift.win.tue.nl', (user.email,), email)\n return user","title":""},{"docid":"683b900e23f13eb37ac73b63c8465e8d","score":"0.63817245","text":"def new_user():\n\n return render_template(\"register.html\")","title":""},{"docid":"3cbff842e8fbfe8f9b4609cd812eec10","score":"0.63801634","text":"def create_users(self):\n self.user = User._default_manager.create_user(\n email=\"test@example.com\",\n password=\"test\",\n )\n self.superuser = User._default_manager.create_superuser(\n email=\"test2@example.com\",\n password=\"test\",\n )","title":""},{"docid":"de2b5da051d57dad0f4e9c38badc901d","score":"0.6377397","text":"def create_user(cls, pseudonym_unique_id, sis_user_id, user_real_first, user_real_last):\n\n payload = {\n 'user[name]': user_real_first + \" \" + user_real_last,\n 'user[short_name]': user_real_first + \" \" + user_real_last,\n 'user[sortable_name]': user_real_last + \",\" + \" \" + user_real_first,\n 'pseudonym[unique_id]': pseudonym_unique_id + '@clark.edu', # ID that will be used to log into the site\n 'pseudonym[sis_user_id]': sis_user_id, # Unique employee identifier. PersonID in prometheus\n\n \"\"\" Due to how often these accounts are potentially being reactivated, I am going to disable the \n notification about account creation. We can probably get around this by tracking the latest CCID value \n and, if the value is higher, send confirmation:true else false.\n\n \"\"\"\n # Sends user an email letting them know of account creation (even upon SIS reactivation)\n # 'pseudonym[send_confirmation': 'True', \n \n # Automatically marks user as registered, making their account established and allowing notifications to be \n # sent, even without logging in\n 'user[skip_registration]': 'True',\n 'communication_channel[type]': 'email',\n\n # The email address the user is contacted at\n 'communication_channel[address]': pseudonym_unique_id + '@clark.edu',\n\n # Allows notifications to be sent to the user even if they don't log in\n 'communication_channel[skip_confirmation]': 'True',\n 'enable_sis_reactivation': 'True' # Reactivates a deleted account if the SIS IDs match\n }\n\n try:\n creation_request = super().request(\n 'POST', str(super().base_url+'api/v1/accounts/'+str(super().canvas_account))+'/users', params=payload)\n if 200 != creation_request.status_code:\n super().error_dump('Failed to create user {} {} with status code {}'.format(\n user_real_first, user_real_last, creation_request.status_code))\n return None\n #/// add logging here\n return creation_request.json()\n\n except Exception as e:\n super().error_dump(\n 'Encountered exception <{}> during user creation for {} {}'.format(e, user_real_first, user_real_last))\n return None","title":""},{"docid":"54e5edabd84ecd188d4137012ad0374b","score":"0.63752645","text":"def create_user(self, request):\n if User.query(User.name == request.user_name).get():\n raise endpoints.ConflictException(\n 'A User with that name already exist!')\n user = User(name=request.user_name, email=request.email)\n user.put()\n return StringMessage(message='User {} created!'.format(request.user_name))","title":""},{"docid":"ed2d5150c5eabfd5ce74506f708b5ef7","score":"0.6369612","text":"def create_user():\n username = custom_input(\"Enter user name: \\n\")\n position = custom_input(\"Enter user position (Manager/Salesman): \\n\")\n if position == \"Salesman\" or position == \"Manager\":\n exec_insert_query(\n \"INSERT OR IGNORE INTO users VALUES (NULL,'{}','{}','{}','{}')\".format(username, position, 0, 0))\n else:\n print(\"Incorrect position '{}'.\\nYou should specify position 'Manager' or 'Salesman'\".format(position))","title":""},{"docid":"b27a6767be48b03a35074f2b8a3299e9","score":"0.6366573","text":"def create_user(admin=False):\n username = prompt(\"Enter username\")\n email = prompt(\"Enter email\")\n password1 = prompt_pass(\"Enter password\")\n password2 = prompt_pass(\"Re-type password\")\n if password1 == password2:\n new_user = User(\n username=username,\n password=password1,\n email=email\n )\n new_user.is_admin = admin\n db.session.add(new_user)\n db.session.commit()\n print('User {0} successfully created'.format(username))\n else:\n print(\"Error: Passwords don't match\")","title":""},{"docid":"e50e626d184d5046733f5c9e53eca221","score":"0.6366382","text":"def create_unverified_user(self):\n self.client.post(\n '/api/users/',\n self.testUser2,\n format='json'\n )","title":""},{"docid":"b211b3d1a0cbc231c4f238413153f14f","score":"0.63663054","text":"def create_user() -> ci_demo.User:\n\n u = ci_demo.User.query.filter(ci_demo.User.id == BaseTestCase.user_id).first()\n if u is None:\n # Create user with name test and password test\n u = ci_demo.User(id=BaseTestCase.user_id, name=BaseTestCase.user_name)\n u.update_password(BaseTestCase.user_password)\n ci_demo.db.session.add(u)\n ci_demo.db.session.commit()\n\n return u","title":""},{"docid":"b2c80185f0b0718b3b3a025901232e20","score":"0.6365039","text":"def create_user():\n \n categories = crud.get_category_entries()\n countries = crud.get_country_entries()\n\n if request.method == 'POST':\n user = crud.create_user(\n #['string'] = the \"name\" field within the form\n request.form['fname'],\n request.form['lname'],\n request.form['email'],\n request.form['username'],\n request.form['password'],\n request.form['category_id'],\n request.form['country_id'])\n if user:\n #testing\n print(\"User has been created!\")\n return redirect('/login')\n else:\n flash(\"User exists. Please try again.\")\n\n\n return render_template(\n 'registration.html',\n categories=categories,\n countries=countries\n )","title":""},{"docid":"2d62fa365c43c1d33a31b0bf7358c80e","score":"0.6357508","text":"def test_user_can_create_new_user(self):\n\n # Edith goes to the register page\n self.browser.get(self.server_url + reverse('register'))\n\n # She fills in the inputs\n username_field = self.browser.find_element_by_name('username')\n username_field.send_keys('netuser')\n password_field = self.browser.find_element_by_name('password1')\n password_field.send_keys('password')\n password_confirmation_field = self.browser.find_element_by_name('password2')\n password_confirmation_field.send_keys('password')\n email_field = self.browser.find_element_by_name('email')\n email_field.send_keys('netuser@edith.com')\n\n password_field.send_keys(Keys.RETURN)\n\n body = self.browser.find_element_by_tag_name('body')\n\n # Edith sees a congratulations message\n self.assertIn('Congratulations! You are now registered and logged in!', body.text)\n\n # After successfully logged in she goes to her applications\n # self.browser.get(self.server_url + reverse('tokens:list'))\n\n # body = self.browser.find_element_by_tag_name('body')\n # self.assertIn('Your token', body.text)","title":""},{"docid":"ff0089320fd0b296b242ef5509e68354","score":"0.63571775","text":"def test_new_user():\n new_user = User('Test User', 'testuser')\n assert new_user.username == 'testuser'\n assert new_user.name == 'Test User'\n assert not new_user.name == 'Sooper User'","title":""},{"docid":"85f2db83c56894b3a800f0c609c26994","score":"0.63510406","text":"def create_user():\n\n # TODO: Validate server-side before adding to DB\n first_name = request.form[\"first_name\"]\n last_name = request.form[\"last_name\"]\n image_url = request.form[\"image_url\"]\n\n # TODO: Error handling\n user = User(first_name=first_name, last_name=last_name, image_url=image_url)\n db.session.add(user)\n db.session.commit()\n\n flash(f\"New User Created: {first_name} {last_name}\")\n return redirect(\"/users\")","title":""},{"docid":"3dbdedc0ab8fd2c47fdc5e9dd7a7c448","score":"0.6350954","text":"def new_user(self, request, sociallogin):\r\n return get_account_adapter().new_user(request)","title":""},{"docid":"90b98f229d839e3c25d8c09cbbdcf520","score":"0.63480407","text":"def _create_user(user):\n login = 'osf.' + user._id\n pw = str(uuid.uuid4())[:8]\n\n response = requests.post(\n url=settings.PIWIK_HOST,\n data={\n 'module': 'API',\n 'method': 'UsersManager.addUser',\n 'format': 'json',\n 'token_auth': settings.PIWIK_ADMIN_TOKEN,\n 'userLogin': login,\n 'password': pw,\n 'email': user._id + '@osf.io',\n 'alias': 'OSF User: {}'.format(user._id),\n }\n )\n\n if json.loads(response.content)['result'] == 'error':\n raise PiwikException('Piwik user not updated')\n\n user.piwik_token = md5(login + md5(pw).hexdigest()).hexdigest()\n\n user.save()","title":""},{"docid":"456863e96ce85ba2b0952c7e7b8555ed","score":"0.6346355","text":"def create_users(self):\n user_fields = ('user_name TEXT PRIMARY KEY', 'password TEXT', 'email TEXT',\\\n 'gender TEXT', 'in_calories_goal INT', 'out_calories_goal INT',\\\n 'budget INT', 'pts INT', 'height INT', 'weight INT', 'steps_goal INT'\\\n 'total_sleep_acquired INT', 'auth_token TEXT', 'user_id TEXT')\n self.tableCreator('users', *user_fields)\n return True","title":""},{"docid":"d9f20f91edcbc4d55ba4e0e405ea0607","score":"0.63422924","text":"def test_create_default_user_options():\n\n runner = CliRunner()\n result = runner.invoke(\n create_default_user, [\"--username\", \"Bob\", \"--password\", \"myprecious\"]\n )\n\n user = User.query.one()\n success_string = \"Default user 'Bob' created.\"\n\n assert not result.exception\n assert success_string in result.output\n assert isinstance(user, User)\n assert user.username == \"Bob\"\n assert bool(user.check_password(\"myprecious\"))\n assert bool(user.is_admin)","title":""},{"docid":"768783c8a671f57bd8e6e443e3a990ae","score":"0.63366306","text":"def test_create_default_user():\n\n runner = CliRunner()\n result = runner.invoke(create_default_user)\n\n user = User.query.one()\n success_string = \"Default user 'admin' created.\"\n\n assert not result.exception\n assert success_string in result.output\n assert isinstance(user, User)\n assert user.username == \"admin\"\n assert bool(user.check_password(\"farm_monitor\"))\n assert bool(user.is_admin)","title":""},{"docid":"8e60eac3d902fcc201a1a19b54341d25","score":"0.63360894","text":"def create_user(email, password, first, last, div, role, tag, is_sup, sup, budget_code=None, object_code=None,\n object_name=None):\n role_obj = Role.query.filter_by(name=role).first()\n sup_obj = User.query.filter_by(id=sup).first()\n u = User(email=email, first_name=first, last_name=last, password=password,\n division=div, role=role_obj, tag_id=tag, is_supervisor=is_sup, supervisor=sup_obj, budget_code=budget_code,\n object_code=object_code, object_name=object_name)\n db.session.add(u)\n db.session.commit()\n u.password_list.update(u.password_hash)\n _send_new_user_email(u, password)\n current_app.logger.info('{} successfully registered user with email {}'.format(current_user.email, u.email))\n return u.email","title":""},{"docid":"3534126b14a4d00d13a3962b8ed5800d","score":"0.63334095","text":"def create_user(self, body=None, *args, **_params):\n return self.post(self.user_create_path, body=body)","title":""},{"docid":"a1c629f7d52b34581a6b7fe845277225","score":"0.63300997","text":"def create_user(self, device):\r\n ip_address = self.device_id.ip_address\r\n port = self.device_id.port\r\n device_password = self.device_id.device_password\r\n user_id = str(self.device_user_id)\r\n\r\n with c.ConnectToDevice(ip_address, port, device_password) as conn:\r\n\r\n device_users = conn.get_users()\r\n device_user_ids = [int(x.user_id) for x in device_users]\r\n if self.device_user_id not in device_user_ids:\r\n conn.set_user(uid=self.device_user_id, name=self.name, privilege=const.USER_DEFAULT, user_id=user_id)\r\n self.device_uid = self.device_user_id\r\n return {\r\n \"type\": \"ir.actions.act_window\",\r\n \"res_model\": \"device.users\",\r\n \"views\": [[False, \"form\"]],\r\n \"res_id\": self.id,\r\n \"target\": \"main\",\r\n \"context\": {'show_message1': True},\r\n }\r\n\r\n else:\r\n return {\r\n \"type\": \"ir.actions.act_window\",\r\n \"res_model\": \"device.users\",\r\n \"views\": [[False, \"form\"]],\r\n \"res_id\": self.id,\r\n \"target\": \"main\",\r\n \"context\": {'show_message2': True},\r\n }","title":""},{"docid":"0db4070cf034fd0b0e8721137404bdb2","score":"0.6329164","text":"def _create_user(self, username, email, password, **extra_fields):\n # print(\"hi hassan\")\n if not username:\n raise ValueError('The given username must be set')\n email = self.normalize_email(email)\n username = self.model.normalize_username(username)\n user = self.model(username=username, email=email, **extra_fields)\n user.set_password(password)\n user.save(using=self._db)\n return user","title":""},{"docid":"e8779f53a68011cb36078e2ffa3d7643","score":"0.63256544","text":"def create_user(email, password, pen_name):\n\n signup_user = User()\n signup_user.email = email\n signup_user.password_hash = argon2.hash(password)\n signup_user.pen_name = pen_name\n\n try:\n signup_user.save()\n return signup_user\n except QueryException:\n return None","title":""},{"docid":"aac4513f33f85e64ac280edbb208cd56","score":"0.6303878","text":"def _do_user_create(p_user):\n print(' Creating user: \"{}\"'.format(p_user))\n try:\n pwd.getpwnam(p_user)\n print(' *** User \"{}\" already exixts! Skipping Add'.format(p_user))\n except KeyError:\n User._add_user(p_user)","title":""},{"docid":"a5c674d8e2c82809d20a57b6d7c51766","score":"0.63029075","text":"def create_new_user(user: UserRegistrationSchema, db: Session):\n\n user.password = generate_password_hash(user.dict()['password'], method='sha256')\n user_obj = User(**user.dict(exclude_unset=True))\n db.add(user_obj)\n db.commit()\n db.refresh(user_obj)\n\n token = generate_token(user.email, 'activate')\n url = f\"{USER_ACTIVATION_URL}?token={token}\"\n context = {\n 'url': url,\n 'email': user.email\n }\n template = 'activate_user.html'\n send_email.delay(\n subject=\"Activate your ChooseOne account\",\n template=template,\n recipients=[user.email],\n context=context\n )\n\n return UserSchema.from_orm(user_obj)","title":""}],"string":"[\n {\n \"docid\": \"c40661dc617572feba289b687098d62c\",\n \"score\": \"0.7658639\",\n \"text\": \"def create_user(self, user_id: str, user_name: str) -> None:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"32f5b47e07cd7cd2b99bba64fa162310\",\n \"score\": \"0.7454858\",\n \"text\": \"def createUser():\\n user_data = fb.get_initial_user_data()\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cd8475fe2dd3bc95aa3e4373508424b9\",\n \"score\": \"0.72297966\",\n \"text\": \"def create_user(\\n self,\\n user: User,\\n ) -> None:\\n ...\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ae44b8b6f5f40e693bb63ecf8660983e\",\n \"score\": \"0.7228752\",\n \"text\": \"def create_user():\\n\\n # Make the new user JSON from form data\\n new_user = {\\n \\\"username\\\": request.form.get('username'),\\n \\\"password\\\": request.form.get('password'),\\n \\\"bio\\\": request.form.get('bio'),\\n }\\n\\n # Insert into PyMongo database\\n db.users.insert_one(new_user)\\n\\n # Render some HTML\\n return \\\"\\\"\\\"\\n User created successfully!\\n <a href=\\\"/users\\\">Back to Home</a>\\n \\\"\\\"\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1bf872781698788db2659a6f9af33942\",\n \"score\": \"0.7165631\",\n \"text\": \"def sample_user():\\n return get_user_model()\\\\\\n .objects.\\\\\\n create_user({'email': fake.email(), 'password': fake.password()})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0121f67127784198ccbe51393bd12f5a\",\n \"score\": \"0.7164468\",\n \"text\": \"def sample_user(email=user_v['email'], password=user_v['password']):\\n return get_user_model().objects.create_user(email, password)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc9a94573866bc16c3c7a11df748f484\",\n \"score\": \"0.7090674\",\n \"text\": \"def sample_user(email='test@recipeapi.com', password='somethingrandom'):\\n return get_user_model().objects.create_user(email=email, password=password)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"71a6d34f87b4fec35f175451a28a63d8\",\n \"score\": \"0.7038464\",\n \"text\": \"def entry():\\n new_user = User(username='myuser',\\n email='myuser@example.com',\\n created=dt.now(),\\n bio=\\\"In West Philadelphia born and raised, on the playground is where I spent most of my days\\\",\\n admin=False\\n )\\n db.session.add(new_user)\\n db.session.commit()\\n return make_response(\\\"User created!\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7144ec956d7748793fd7ac99e6255e41\",\n \"score\": \"0.7023137\",\n \"text\": \"def sample_user(email='test@gmail.com', password='testpass'):\\n return get_user_model().objects.create_user(email, password)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7144ec956d7748793fd7ac99e6255e41\",\n \"score\": \"0.7023137\",\n \"text\": \"def sample_user(email='test@gmail.com', password='testpass'):\\n return get_user_model().objects.create_user(email, password)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d1030726edadce9706609bd1b1f868d6\",\n \"score\": \"0.6992834\",\n \"text\": \"def sample_user(email='test@londonappdev.com', password='testpass'):\\n return get_user_model().objects.create_user(email, password)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d1030726edadce9706609bd1b1f868d6\",\n \"score\": \"0.6992834\",\n \"text\": \"def sample_user(email='test@londonappdev.com', password='testpass'):\\n return get_user_model().objects.create_user(email, password)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"31ae0d2f6eca9e31861496894c1e1462\",\n \"score\": \"0.6927966\",\n \"text\": \"def sample_user(email='test@testdomain.com', password='testpass'):\\n return get_user_model().objects.create_user(email, password)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3cde5f7c1a7227f69a76666cd92abbdd\",\n \"score\": \"0.69101703\",\n \"text\": \"def create_user(self, name='Some name'):\\n return self.database.insert(name)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9580115af87da74f76e86883ee807932\",\n \"score\": \"0.68891996\",\n \"text\": \"def sample_user(phone_number='4086432477', password='testpass'):\\n return get_user_model().objects.create_user(phone_number, password)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"da914aa06d2faf6057f3473728314bac\",\n \"score\": \"0.6849761\",\n \"text\": \"def create_sample_user(email=\\\"test@firstapp.com\\\", password=\\\"test1\\\"):\\n return get_user_model().objects.create_user(email, password)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d310e4ae45928ccb60c82c9572fb57da\",\n \"score\": \"0.68457526\",\n \"text\": \"def _create_user(self):\\n\\n msg = QMessageBox()\\n user = kks.create_user(self._username_line.text(), self._password_line.text())\\n \\n if not user:\\n msg.setText('Käyttäjätunnus on jo käytössä')\\n msg.exec_()\\n else:\\n msg.setText('Uusi käyttäjä luotu')\\n msg.exec_()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0aa13ed1e1136f754de8e5124000d701\",\n \"score\": \"0.684187\",\n \"text\": \"def admin_create_user(self):\\n resp = self.admin_register()\\n reply = self.admin_login()\\n token = reply['token']\\n user = dict(\\n name='Summer Love',\\n username='love',\\n password='Andela8',\\n role='attendant'\\n )\\n\\n resp = self.client.post(\\n '/api/v1/users',\\n content_type='application/json',\\n data=json.dumps(user),\\n headers={'Authorization': 'Bearer {}'.format(token)}\\n )\\n\\n reply = json.loads(resp.data.decode())\\n return reply\",\n \"title\": \"\"\n },\n {\n \"docid\": \"58d462e89e1fa02990ce29cdeb72043a\",\n \"score\": \"0.68353564\",\n \"text\": \"def create_new_user():\\n\\n return render_template('create_new_user.html')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ee862f60b59a9532b3352aeeaf7509f9\",\n \"score\": \"0.68202496\",\n \"text\": \"def create_user(context,galaxy,email,public_name,password,only_check,\\n message_template):\\n # Check message template is a .mako file\\n if message_template:\\n if not message_template.endswith(\\\".mako\\\"):\\n logger.critical(\\\"Message template '%s' is not a .mako file\\\"\\n % message_template)\\n sys.exit(1)\\n # Get a Galaxy instance\\n gi = context.galaxy_instance(galaxy)\\n if gi is None:\\n logger.critical(\\\"Failed to connect to Galaxy instance\\\")\\n sys.exit(1)\\n # Sort out email and public name\\n if public_name:\\n if not users.check_username_format(public_name):\\n logger.critical(\\\"Invalid public name: must contain only \\\"\\n \\\"lower-case letters, numbers and '-'\\\")\\n sys.exit(1)\\n else:\\n # No public name supplied, make from email address\\n public_name = users.get_username_from_login(email)\\n # Create user\\n print(\\\"Email : %s\\\" % email)\\n print(\\\"Name : %s\\\" % public_name)\\n sys.exit(users.create_user(gi,email,public_name,password,\\n only_check=only_check,\\n mako_template=message_template))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bad2afd7b85622a4f1501681f04a73bd\",\n \"score\": \"0.68134016\",\n \"text\": \"def new_user(self):\\n username = self.gui.username_entry.get()\\n salt = bcrypt.gensalt()\\n while not self.gui.client.dbcom.check_salt(salt):\\n salt = bcrypt.gensalt()\\n password = bcrypt.hashpw(self.gui.password_entry.get().encode(), salt)\\n email = self.gui.mail_entry.get()\\n phone_number = self.gui.number_entry.get()\\n self.gui.client.dbcom.add_user(username, salt, password, email, phone_number)\\n self.gui.build_log_in_ui()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"df065ae1bb66009f3880b761a8b871a4\",\n \"score\": \"0.68031585\",\n \"text\": \"def create_new_user_node(i):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d7d099ce2dc3b0105b83c17b30d3a70c\",\n \"score\": \"0.67799646\",\n \"text\": \"def new_user(self, **kwargs):\\n num = self._user_numbers.pop()\\n kwargs.setdefault(\\\"first_name\\\", \\\"FIRST%04d\\\" % num)\\n kwargs.setdefault(\\\"last_name\\\", \\\"LAST%04d\\\" % num)\\n kwargs.setdefault(\\\"username\\\", \\\"user%04d\\\" % num)\\n user = User(**kwargs)\\n user.save()\\n self._users.append(user)\\n return user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2ffefdc305737cdba44876e77df1a479\",\n \"score\": \"0.67655015\",\n \"text\": \"def new_user():\\n\\n return render_template(\\\"user_form.html\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cf022b77565799d4b87c4c2cf45bfc05\",\n \"score\": \"0.6746994\",\n \"text\": \"def create_askbot_user(zd_user):\\n if zd_user.email is None:\\n username = zd_user.name.replace(\\\" \\\", \\\"_\\\").lower()\\n email = ''\\n else:\\n username = zd_user.email\\n email = zd_user.email\\n username = ensure_unique_username(username[:30])\\n\\n # last_seen cannot be null\\n last_seen = zd_user.last_login\\n if not last_seen:\\n last_seen = zd_user.created_at\\n\\n # lookup organization name (todo: cache this)\\n about = \\\"\\\"\\n if zd_user.organization_id:\\n try:\\n org = zendesk_models.Organization.objects.get(organization_id=zd_user.organization_id)\\n about = org.name\\n except zendesk_models.Organization.DoesNotExist:\\n pass\\n\\n ab_user = askbot_models.User(\\n username = username,\\n first_name = zd_user.name.rpartition(' ')[0].strip()[:30],\\n last_name = zd_user.name.rpartition(' ')[2].strip()[:30],\\n real_name = zd_user.name[:100],\\n email = email,\\n email_isvalid = zd_user.is_verified,\\n date_joined = zd_user.created_at,\\n last_seen = last_seen,\\n is_active = zd_user.is_active,\\n about = about,\\n )\\n ab_user.save()\\n return ab_user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c8fee5047f2c9525534ff0983cc091b4\",\n \"score\": \"0.67408246\",\n \"text\": \"def _create_user(username,telefone,nome,endereço,data_de_nascimento):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2cdd0f157081e922b9a16a8f132fb790\",\n \"score\": \"0.67324775\",\n \"text\": \"def create_user(self) -> 'outputs.ActingUserResponse':\\n return pulumi.get(self, \\\"create_user\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e18f170f90740889ed20b07a68c1c9d5\",\n \"score\": \"0.673237\",\n \"text\": \"def create_new_user(self, redditor):\\n print(\\\"Creating user: \\\" + str(redditor))\\n\\n new_user_item = {\\n 'user_id' : redditor.id,\\n 'username' : redditor.name,\\n 'submission_score' : 0,\\n 'distribution_score' :0,\\n 'total_score' : 0\\n }\\n if self.put_item(DataAccess.Tables.USERS, new_user_item):\\n print(\\\"Created user: \\\" + str(redditor))\\n return True\\n else:\\n print(\\\"Failed to create user: \\\" + str(redditor))\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"68f8a28bf3ec4ce6a4527fd2d38973b9\",\n \"score\": \"0.6729003\",\n \"text\": \"def create_sample_user(email='test@webapps.agency', password='password123'):\\n return get_user_model().objects.create_user(email, password)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3bdaafe6c0ff683d4f193ba80886bedf\",\n \"score\": \"0.6703305\",\n \"text\": \"def _create_user(self, email, password):\\n self.parent.browser.find_element_by_id('create-user-button').click()\\n time.sleep(DELAY)\\n self.parent.browser.find_element_by_id('input-username').send_keys(email)\\n time.sleep(DELAY)\\n self.parent.browser.find_element_by_id('input-password').send_keys(password)\\n time.sleep(DELAY)\\n self.parent.browser.find_element_by_id('create-user-commit').click()\\n print(\\\"user with [{}], [{}] created\\\".format(email, password))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"88baf383dc76ab16135271232abd4d35\",\n \"score\": \"0.6692833\",\n \"text\": \"def create_user(fname,sname,number,password):\\n new_user=User(fname,sname,number,password)\\n return new_user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d92155b00dce49485f1c3abed4f2715c\",\n \"score\": \"0.6691482\",\n \"text\": \"def create_user(name, passw):\\n new_user = User(name, passw)\\n return new_user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9a9befb3540c8eb46cba6f293ba5302f\",\n \"score\": \"0.66777927\",\n \"text\": \"def create_user(fname, lname, email, password, consent=False):\\n\\n user = User(fname=fname, lname=lname, email=email, password=password, consent=False) # is consent default value added here as well as in arguments?\\n\\n db.session.add(user)\\n db.session.commit()\\n\\n return user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2794fd3617db7cb79400305de31a6aae\",\n \"score\": \"0.66645825\",\n \"text\": \"def testCreate1User(self):\\n request = self.factory.post(\\\"/api/user/create\\\", json.dumps({ 'username' : 'Tom',\\n 'password' : '123456',\\n 'user_type' : 'customer',\\n 'email' : 'tommeng@berkeley.edu',\\n }), content_type='application/json')\\n response = views.create_user(request);\\n respCreate = self.getDataFromResponse(response)\\n\\n self.assertSuccessResponse(respCreate)\\n self.assertEquals(\\\"Tom\\\", respCreate['username'], \\\"Username wrong\\\")\\n self.assertEquals(\\\"customer\\\", respCreate['user_type'])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f0fa4f9181e412ccd094cbc58c9909aa\",\n \"score\": \"0.6648792\",\n \"text\": \"def test_create_user(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"537ad424e96fdd408cadd158c2e07b49\",\n \"score\": \"0.66471165\",\n \"text\": \"def new_user(cls, user_name, email):\\n user = User(name=user_name, email=email)\\n user.put()\\n score = Score(parent=user.key, date=datetime.now(), attempts=0)\\n score.put()\\n return 'User {} created!'.format(user_name)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"619dd5bad8b29b3c3dd02f094a3dcefa\",\n \"score\": \"0.6639765\",\n \"text\": \"async def create_user_open(user_in: schemas.UserCreateMe):\\n user = await crud.user.get_by_email(email=user_in.email)\\n if user:\\n raise HTTPException(\\n status_code=status.HTTP_400_BAD_REQUEST,\\n detail=\\\"The user with this username already exists in the system\\\",\\n )\\n user = await crud.user.create_me(obj_in=user_in)\\n return await schemas.UserPydantic.from_tortoise_orm(user)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a5ec0e6bd78a0b648535eb20644f0512\",\n \"score\": \"0.6637918\",\n \"text\": \"def create_user(fullname, username, password):\\n new_user = User(fullname, username, password)\\n return new_user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c65acb9091cd72fd493502f9140f9208\",\n \"score\": \"0.6635635\",\n \"text\": \"def userCreate(self, request, tag):\\n userCreator = liveform.LiveForm(\\n self.createUser,\\n [liveform.Parameter(\\n \\\"localpart\\\",\\n liveform.TEXT_INPUT,\\n unicode,\\n \\\"localpart\\\"),\\n liveform.Parameter(\\n \\\"domain\\\",\\n liveform.TEXT_INPUT,\\n unicode,\\n \\\"domain\\\"),\\n liveform.Parameter(\\n \\\"password\\\",\\n liveform.PASSWORD_INPUT,\\n unicode,\\n \\\"password\\\")])\\n userCreator.setFragmentParent(self)\\n return userCreator\",\n \"title\": \"\"\n },\n {\n \"docid\": \"adb20631bd7cc235e7e2c9e07961b275\",\n \"score\": \"0.66353905\",\n \"text\": \"def create_empty_user():\\n return User(email=\\\"\\\", nick=\\\"\\\", level=User.Level.Client)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fd85e2af2da79e7577fb232ded1fcf6a\",\n \"score\": \"0.6633111\",\n \"text\": \"def create_valid_user_test(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e7354e58a00fcbc8760e89d183e74283\",\n \"score\": \"0.6626516\",\n \"text\": \"def new_user(self, request):\\r\\n user = get_user_model()()\\r\\n return user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1a4e86afd86ebfb8fc145040f6fc99d0\",\n \"score\": \"0.6608983\",\n \"text\": \"def create_initial_user():\\n\\n # check if there is any user in the db\\n if User.query.count() == 0:\\n # create a user\\n user = User(username=\\\"admin\\\", password=hashlib.sha256(\\\"admin\\\".encode(\\\"utf8\\\")).hexdigest(),\\n email=\\\"webmaster@example.org\\\")\\n user.is_admin = True\\n db.session.add(user)\\n db.session.commit()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d3fcc43785b4dee883cfe7dea5f13e95\",\n \"score\": \"0.66077644\",\n \"text\": \"def create_user():\\n # check the token\\n token = request.form['token']\\n if token != ACCEPT_TOKEN:\\n return 'Error: not authorized'\\n\\n u = User(es)\\n return u.create_from_req(request)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2025ed72a4512000278c999195da4cdc\",\n \"score\": \"0.65977323\",\n \"text\": \"def create_user(fname, lname, password):\\n new_user = User(fname, lname,password)\\n return new_user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"193ef5d2be5026820e55cbc4addeeae2\",\n \"score\": \"0.6583698\",\n \"text\": \"def post(self, user_id=None):\\n name = self.get_argument(\\\"name\\\", \\\"\\\")\\n email = self.get_argument(\\\"email_address\\\", \\\"\\\")\\n password = self.get_argument(\\\"password\\\", \\\"\\\")\\n new_user = self.create_user(name, email, password)\\n self.write(new_user.to_dict())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"200135420c1600bd526ff1fc6c262b37\",\n \"score\": \"0.6582868\",\n \"text\": \"def create_user(user_data: dict) -> User:\\n user = User()\\n user.admin = False\\n user.name = user_data[\\\"display_name\\\"]\\n user.external_id = user_data[\\\"id\\\"]\\n return user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0a696796bc8685cb6ac69ad4887af3ce\",\n \"score\": \"0.6565887\",\n \"text\": \"def create(self, data):\\n return User.objects.create_user(**data)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6e9db6bc9ce7f3781b7540ca82fbe10e\",\n \"score\": \"0.6561448\",\n \"text\": \"def create_user(backend, details, response, uid, username, user=None, *args, **kwargs):\\n if user:\\n return {'user': user}\\n if not username:\\n return None\\n\\n request = kwargs['request']\\n user = UserSocialAuth.create_user(username = username)\\n# profile = UserProfile.objects.create_user(user = user)\\n\\n return {\\n 'user': user,\\n 'is_new': True\\n }\",\n \"title\": \"\"\n },\n {\n \"docid\": \"96e671b4273c7888f75bd6fcc1cd1d33\",\n \"score\": \"0.65509975\",\n \"text\": \"def _create_user(self, data):\\n username = data[\\\"username\\\"]\\n self._signup_user(data)\\n validation_mail = mail.outbox[-1]\\n self.assertTrue(\\n \\\"signup\\\" in validation_mail.subject,\\n \\\"There was no email\\\"\\n \\\" sent which had 'signup' in the subject line\\\",\\n )\\n # validate the user with the link that was emailed\\n pattern = \\\"/testserver(.*)\\\" + PI_LINE_END_REGEX\\n validationlink_result = re.search(\\n pattern, validation_mail.body, re.IGNORECASE\\n )\\n self.assertTrue(\\n validationlink_result,\\n \\\"could not find any link in\\\"\\n \\\"registration email. Tried to match pattern '{}' but found no match in\\\"\\n \\\"this email: {}{}\\\".format(\\n pattern, PI_LINE_END_REGEX, validation_mail.body\\n ),\\n )\\n validationlink = validationlink_result.group(1).strip()\\n response = self.client.get(validationlink)\\n self.assertEqual(\\n response.status_code,\\n 302,\\n \\\"Could not load user validation link. Expected\\\"\\n \\\" a redirect (HTTP 302), got HTTP {} instead\\\".format(\\n response.status_code\\n ),\\n )\\n resp = self.client.get(\\\"/accounts/\\\" + username + \\\"/\\\")\\n self.assertEqual(\\n resp.status_code,\\n 200,\\n \\\"Could not access user account after using\\\"\\n \\\"validation link! Expected 200, got {} instead\\\".format(\\n resp.status_code\\n ),\\n )\\n User = get_user_model() # noqa: N806\\n query_result = User.objects.filter(username=username)\\n return query_result[0]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a9f718fd99fa61731669d3ecf918ee3c\",\n \"score\": \"0.65470034\",\n \"text\": \"def _create_user(self):\\n self.user = User.objects.create_user('test', 'test@test.test', 'test')\\n self.api_client.login(\\n username='test',\\n password='test',\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"108f120df0fa6ca83aafd9bc0c87f356\",\n \"score\": \"0.6538275\",\n \"text\": \"def test_create_user(self):\\n new_user = {\\n \\\"_id\\\": ObjectId(\\\"000000000000000000000002\\\"),\\n \\\"name\\\": \\\"Polly O'Donovan\\\",\\n \\\"username\\\": \\\"pollypocket\\\",\\n \\\"my_recipes\\\": [],\\n \\\"favourite_recipes\\\": []\\n }\\n app.add_user(new_user)\\n self.assertIn(new_user, list(app.get_users()))\\n app.delete_user('000000000000000000000002')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e839f4f52e4b71bd3fdca345790076bb\",\n \"score\": \"0.65374136\",\n \"text\": \"def createuser(username=None, password=None, admin=None):\\n u_name = username\\n pw = password\\n make_admin = admin\\n\\n if u_name is None:\\n while True:\\n u_name = prompt(\\\"User Name\\\")\\n user = User.query.filter(User.name==u_name).first()\\n if user is not None:\\n print(\\\"{}: USER ALREADY EXISTS!\\\".format(u_name))\\n else:\\n break\\n\\n if pw is None:\\n pw = prompt_pass(\\\"Password\\\")\\n while True:\\n pw_again = prompt_pass(\\\"Password Again\\\")\\n if pw != pw_again:\\n print(\\\"PASSWORDS DO NOT MATCH!\\\")\\n else:\\n break\\n\\n if make_admin is None:\\n make_admin = prompt_bool(\\\"Do you wish to make {} an administrator?\\\".\\\\\\n format(u_name))\\n\\n user = User(name=u_name, password=\\\"\\\", admin=make_admin, enabled=True)\\n user.set_password(pw)\\n\\n db.session.add(user)\\n db.session.commit()\\n print(\\\"Successfully created '{}' with ID: {}.\\\".format(user.name, user.id))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a6f2d85cfa166855cd5d540d43452f9f\",\n \"score\": \"0.6529134\",\n \"text\": \"def user():\\n return User()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"36da2f39ee6de223831a14181e018ddd\",\n \"score\": \"0.6527107\",\n \"text\": \"def create(usr, level):\\n toret = User()\\n\\n toret.email = usr.email()\\n toret.nick = usr.nickname()\\n toret.level = level\\n\\n return toret\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a1dd381de65afc8bc914d2885f946173\",\n \"score\": \"0.6525508\",\n \"text\": \"def create_new_user( self, trans, **kwd ):\\n return trans.response.send_redirect( web.url_for( controller='user',\\n action='create_non_feide_user_in_GOLD',\\n cntrller='project_admin' ) )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9ec00f3dae6522b9afe610072c8fcc76\",\n \"score\": \"0.6521141\",\n \"text\": \"def create_example_users(self):\\n # TODO: implement the method to add the example users by using \\\"add_user\\\" function and return a string that\\n # shows it has been added successfully write your code below\\n # write your code below\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3412d63f0dc16ecb34f5599cd9866ddb\",\n \"score\": \"0.6511392\",\n \"text\": \"def create_user(self):\\n data = {\\n \\\"username\\\": \\\"TestUserdsa\\\" + str(random.randrange(1, 1000000)),\\n \\\"password\\\": \\\"Aa12Aa12\\\",\\n \\\"email\\\": \\\"benharushtomer@gmail.com\\\"\\n }\\n response = requests.post(self.urls['create_user'],\\n data=data)\\n print(response.text)\\n return self.get_token(data['username'], data['password'],)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"df31516aaae7ab80e40fd0b6e0cae62c\",\n \"score\": \"0.65057933\",\n \"text\": \"def create_user() -> bool:\\n\\n # TODO: verify len, number, lower and upper\\n\\n name = input(\\\"Insert username: \\\")\\n password = Encrypt.encrypt_data(key=constant.KEY, data=input(\\\"Insert Password: \\\"))\\n email = input(\\\"Insert email: \\\")\\n number = input(\\\"Insert phone number: \\\")\\n\\n # Creating user\\n new_user = User(name=name, email=email, number=number)\\n\\n try:\\n # Insert the user into the database\\n user_id = conn.create_user(user=new_user, password=password)\\n except Exception as e:\\n print(\\\"Error in the Database, \\\", e)\\n return False\\n\\n if user_id == -1:\\n return False\\n\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"47b8963597772187399b99c9fae530c7\",\n \"score\": \"0.65010655\",\n \"text\": \"def createUser(self):\\r\\n json = request.get_json()\\r\\n user = User(None, json[\\\"email\\\"], EncryptionService.hashPassword(json[\\\"password\\\"]), json[\\\"name\\\"],\\r\\n None, None, json[\\\"group_id\\\"], json[\\\"waterschap_id\\\"])\\r\\n user.addUser()\\r\\n return make_response(jsonify(user.json()))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d49772e9654759f4ebfbf1944b6ecb66\",\n \"score\": \"0.64808685\",\n \"text\": \"def create_user():\\n return render_template('create_page.html')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6cae7e0251b9be9a04b2b84c43a7817f\",\n \"score\": \"0.64792997\",\n \"text\": \"def add_user():\\n # get form variables from register_form.html\\n fname = request.form['fname']\\n lname = request.form['lname']\\n email = request.form['email']\\n password = request.form['password']\\n mobile = request.form['mobile']\\n\\n user_id = add_to_users(fname, lname, email, password, mobile)\\n flash('Wanda welcomes you! Please set up your preferences.')\\n # add user's first name and user_id to session\\n session['fname'] = fname\\n session['user_id'] = user_id\\n # send confirmation text to user's mobile using Twilio\\n send_welcome_text(mobile, user_id)\\n return render_template('/preferences.html')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"954db34bc27ceea91f04ef40dff73708\",\n \"score\": \"0.64756787\",\n \"text\": \"def add_user(form):\\n username = ws.get_cgi_parameter_str(form, PARAM.USERNAME)\\n password_1 = ws.get_cgi_parameter_str(form, PARAM.PASSWORD_1)\\n password_2 = ws.get_cgi_parameter_str(form, PARAM.PASSWORD_2)\\n must_change_password = ws.get_cgi_parameter_bool(\\n form, PARAM.MUST_CHANGE_PASSWORD)\\n\\n may_use_webviewer = ws.get_cgi_parameter_bool(\\n form, PARAM.MAY_USE_WEBVIEWER)\\n may_view_other_users_records = ws.get_cgi_parameter_bool(\\n form, PARAM.MAY_VIEW_OTHER_USERS_RECORDS)\\n view_all_patients_when_unfiltered = ws.get_cgi_parameter_bool(\\n form, PARAM.VIEW_ALL_PTS_WHEN_UNFILTERED)\\n may_upload = ws.get_cgi_parameter_bool(form, PARAM.MAY_UPLOAD)\\n superuser = ws.get_cgi_parameter_bool(form, PARAM.SUPERUSER)\\n may_register_devices = ws.get_cgi_parameter_bool(\\n form, PARAM.MAY_REGISTER_DEVICES)\\n may_use_webstorage = ws.get_cgi_parameter_bool(\\n form, PARAM.MAY_USE_WEBSTORAGE)\\n may_dump_data = ws.get_cgi_parameter_bool(form, PARAM.MAY_DUMP_DATA)\\n may_run_reports = ws.get_cgi_parameter_bool(form, PARAM.MAY_RUN_REPORTS)\\n may_add_notes = ws.get_cgi_parameter_bool(form, PARAM.MAY_ADD_NOTES)\\n\\n user = User(username, False)\\n if user.user:\\n return user_management_failure_message(\\n \\\"User already exists: \\\" + username)\\n if not is_username_permissible(username):\\n return user_management_failure_message(\\n \\\"Invalid username: \\\" + ws.webify(username))\\n if password_1 != password_2:\\n return user_management_failure_message(\\\"Passwords don't mach\\\")\\n if len(password_1) < MINIMUM_PASSWORD_LENGTH:\\n return user_management_failure_message(\\n \\\"Password must be at least {} characters\\\".format(\\n MINIMUM_PASSWORD_LENGTH\\n ))\\n\\n user = User(username, True)\\n user.set_password(password_1)\\n\\n user.may_use_webviewer = may_use_webviewer\\n user.may_view_other_users_records = may_view_other_users_records\\n user.view_all_patients_when_unfiltered = view_all_patients_when_unfiltered\\n user.may_upload = may_upload\\n user.superuser = superuser\\n user.may_register_devices = may_register_devices\\n user.may_use_webstorage = may_use_webstorage\\n user.may_dump_data = may_dump_data\\n user.may_run_reports = may_run_reports\\n user.may_add_notes = may_add_notes\\n\\n user.save()\\n if must_change_password:\\n user.force_password_change()\\n\\n audit(\\n (\\n \\\"User created: {}: \\\"\\n \\\"may_use_webviewer={}, \\\"\\n \\\"may_view_other_users_records={}, \\\"\\n \\\"view_all_patients_when_unfiltered={}, \\\"\\n \\\"may_upload={}, \\\"\\n \\\"superuser={}, \\\"\\n \\\"may_register_devices={}, \\\"\\n \\\"may_use_webstorage={}, \\\"\\n \\\"may_dump_data={}, \\\"\\n \\\"may_run_reports={}, \\\"\\n \\\"may_add_notes={}, \\\"\\n \\\"must_change_password={}\\\"\\n ).format(\\n user.user,\\n may_use_webviewer,\\n may_view_other_users_records,\\n view_all_patients_when_unfiltered,\\n may_upload,\\n superuser,\\n may_register_devices,\\n may_use_webstorage,\\n may_dump_data,\\n may_run_reports,\\n may_add_notes,\\n must_change_password\\n )\\n )\\n return user_management_success_message(\\\"User \\\" + user.user + \\\" created\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4657cee1d7f3ac5630d6da2adf6c7007\",\n \"score\": \"0.64742255\",\n \"text\": \"def create_user(args):\\n args = args_cleaner(args)\\n \\n # check if username has been passed.\\n if args.get('username'): username = args.get('username')\\n else: username = input_(msg='username: ')\\n \\n # check if username already exists.\\n if auth.get_user(username):\\n print (f\\\"'{username}' already exists.\\\")\\n return\\n \\n password = input_(msg=f\\\"password for '{username}' (hidden): \\\", pswd=True)\\n \\n # create the user.\\n created = auth.create_user(username, password)\\n if not created:\\n print ('Something went wrong. please try again.')\\n return\\n \\n print (f\\\"user '{username}' has been created.\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ef3e5841194e3b43517076b80d243866\",\n \"score\": \"0.646342\",\n \"text\": \"def create_user(self, **attrs):\\n return self._create(user.User, **attrs)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"217e2594f051ecb05875327043984191\",\n \"score\": \"0.6452617\",\n \"text\": \"def create_user(request, user, details, backend, *args, **kwargs):\\n # If user already exists, don't create a user.\\n if user is not None:\\n return None\\n\\n is_new = False\\n user = None\\n\\n username = '{0}-{1}'.format(details['username'], backend.name)\\n email = details.get('email') or details['username']\\n user = User.objects.create_user(username=username, email=email,\\n password='!')\\n is_new = True\\n\\n return {\\n 'user': user,\\n 'is_new': is_new\\n }\",\n \"title\": \"\"\n },\n {\n \"docid\": \"593c75839170b6f9031a25f6dff92b11\",\n \"score\": \"0.6444597\",\n \"text\": \"def fake_single(self, fake, approved=True):\\n user = self.create_user(\\n email=fake.email(),\\n password=fake.password(),\\n first_name=fake.first_name(),\\n last_name=fake.last_name(),\\n )\\n user.save()\\n user.memberprofile.new_notify = not approved\\n user.memberprofile.date_of_birth = fake.date_time_between(start_date='-99y', end_date='now').date()\\n user.memberprofile.gender = random.choice(('m', 'f'))\\n user.memberprofile.address = fake.address()\\n user.memberprofile.postcode = fake.postcode()\\n user.memberprofile.home_phone = fake.phone_number()\\n user.memberprofile.mobile_phone = fake.phone_number()\\n user.memberprofile.next_of_kin_name = fake.name()\\n user.memberprofile.next_of_kin_relation = fake.first_name()\\n user.memberprofile.next_of_kin_phone = fake.phone_number()\\n user.memberprofile.save()\\n return user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1d7839379860b0c5c49eb89942d1fb3d\",\n \"score\": \"0.6443251\",\n \"text\": \"def create_test_user(id = \\\"\\\"):\\n username = f\\\"test_user{id}\\\"\\n email = f\\\"example{id}@example.com\\\"\\n password = \\\"password1\\\"\\n return User.objects.create_user(username, email, password)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ee1dea61eab82c8a780938aa4afd8a2e\",\n \"score\": \"0.6438962\",\n \"text\": \"def test_create_users():\\n User(username=\\\"\\\", password=\\\"\\\", last_trained_on=None, tbl_rating_user_id=0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0b46bf67876d91a14d78d8c98a6164a9\",\n \"score\": \"0.64366597\",\n \"text\": \"def create_user(self, name, admin=False):\\n return self.create_users([name], admin)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a442f9396c678d021a49a30354550049\",\n \"score\": \"0.64342165\",\n \"text\": \"async def create_user(self, username, hashed_password, role_id):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"83feac2cec19518f591aff2932c27929\",\n \"score\": \"0.641548\",\n \"text\": \"def admin_create_user2(self):\\n resp = self.admin_register()\\n reply = self.admin_login()\\n token = reply['token']\\n user = dict(\\n name='Paul Walker',\\n username='walker',\\n password='Andela8',\\n role='attendant'\\n )\\n\\n resp = self.client.post(\\n '/api/v1/users',\\n content_type='application/json',\\n data=json.dumps(user),\\n headers={'Authorization': 'Bearer {}'.format(token)}\\n )\\n\\n reply = json.loads(resp.data.decode())\\n return reply\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aa9f39ba54fadcc24634c32b9b2d74d3\",\n \"score\": \"0.6414347\",\n \"text\": \"async def create_user(\\n context: CommandContext,\\n username: str,\\n password: str,\\n email: str,\\n first_name: str,\\n last_name: str,\\n):\\n user = User.objects.create_user(\\n username=username,\\n password=password,\\n email=email,\\n first_name=first_name,\\n last_name=last_name,\\n )\\n runtime_user = RuntimeUser.from_persistent_user(user)\\n context.runtime_user = runtime_user\\n return {'user': {'id': user.id}}\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f34a0bc3f8f643ae1275df5664b79b48\",\n \"score\": \"0.6404594\",\n \"text\": \"def create_user(db: Session, user: schemas.UserCreate) -> None:\\n new_user = models.User(name=user.name)\\n new_user.password = bcrypt.hashpw(user.password, bcrypt.gensalt())\\n db.add(new_user)\\n db.commit()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"56b27a1e6d45c0527c10288003954da2\",\n \"score\": \"0.6402819\",\n \"text\": \"def add_one_user(p_user):\\n print(' Adding user \\\"{}\\\" now.'.format(p_user))\\n User._do_user_create(p_user)\\n User._update_sudoers(p_user)\\n User._create_workspace(p_user)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"65bfc46101a35217ae2cec654f26bd8d\",\n \"score\": \"0.6393311\",\n \"text\": \"def create_a_user(self, username='test', email='info@test.co',\\n password='Test123.'):\\n user = User.objects.create_user(username, email, password)\\n user.save()\\n return user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dc2d4bb691278192512a3bc28da3c758\",\n \"score\": \"0.63884735\",\n \"text\": \"def _create_user(self, email, password, first_name, last_name, **extra_fields):\\n if not email:\\n raise ValueError('The email cannot be empty.')\\n email = self.normalize_email(email)\\n user = self.model(email=email, first_name=first_name, last_name=last_name, **extra_fields)\\n user.set_password(password)\\n user.save(using=self._db)\\n\\n # Send email to newly created user\\n subject = 'Welcome to lifTUe!'\\n message = 'Welcome to lifTUe!\\\\n\\\\n You can start using the application using the following credentials:\\\\n\\\\n' \\\\\\n 'Email: ' + email + '\\\\n Password: ' + password + '\\\\n\\\\n You will need to change your password the ' \\\\\\n 'first time you log in.'\\n\\n send_mail(subject, message, 'noreply@gelift.win.tue.nl', (user.email,), email)\\n return user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"683b900e23f13eb37ac73b63c8465e8d\",\n \"score\": \"0.63817245\",\n \"text\": \"def new_user():\\n\\n return render_template(\\\"register.html\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3cbff842e8fbfe8f9b4609cd812eec10\",\n \"score\": \"0.63801634\",\n \"text\": \"def create_users(self):\\n self.user = User._default_manager.create_user(\\n email=\\\"test@example.com\\\",\\n password=\\\"test\\\",\\n )\\n self.superuser = User._default_manager.create_superuser(\\n email=\\\"test2@example.com\\\",\\n password=\\\"test\\\",\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"de2b5da051d57dad0f4e9c38badc901d\",\n \"score\": \"0.6377397\",\n \"text\": \"def create_user(cls, pseudonym_unique_id, sis_user_id, user_real_first, user_real_last):\\n\\n payload = {\\n 'user[name]': user_real_first + \\\" \\\" + user_real_last,\\n 'user[short_name]': user_real_first + \\\" \\\" + user_real_last,\\n 'user[sortable_name]': user_real_last + \\\",\\\" + \\\" \\\" + user_real_first,\\n 'pseudonym[unique_id]': pseudonym_unique_id + '@clark.edu', # ID that will be used to log into the site\\n 'pseudonym[sis_user_id]': sis_user_id, # Unique employee identifier. PersonID in prometheus\\n\\n \\\"\\\"\\\" Due to how often these accounts are potentially being reactivated, I am going to disable the \\n notification about account creation. We can probably get around this by tracking the latest CCID value \\n and, if the value is higher, send confirmation:true else false.\\n\\n \\\"\\\"\\\"\\n # Sends user an email letting them know of account creation (even upon SIS reactivation)\\n # 'pseudonym[send_confirmation': 'True', \\n \\n # Automatically marks user as registered, making their account established and allowing notifications to be \\n # sent, even without logging in\\n 'user[skip_registration]': 'True',\\n 'communication_channel[type]': 'email',\\n\\n # The email address the user is contacted at\\n 'communication_channel[address]': pseudonym_unique_id + '@clark.edu',\\n\\n # Allows notifications to be sent to the user even if they don't log in\\n 'communication_channel[skip_confirmation]': 'True',\\n 'enable_sis_reactivation': 'True' # Reactivates a deleted account if the SIS IDs match\\n }\\n\\n try:\\n creation_request = super().request(\\n 'POST', str(super().base_url+'api/v1/accounts/'+str(super().canvas_account))+'/users', params=payload)\\n if 200 != creation_request.status_code:\\n super().error_dump('Failed to create user {} {} with status code {}'.format(\\n user_real_first, user_real_last, creation_request.status_code))\\n return None\\n #/// add logging here\\n return creation_request.json()\\n\\n except Exception as e:\\n super().error_dump(\\n 'Encountered exception <{}> during user creation for {} {}'.format(e, user_real_first, user_real_last))\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"54e5edabd84ecd188d4137012ad0374b\",\n \"score\": \"0.63752645\",\n \"text\": \"def create_user(self, request):\\n if User.query(User.name == request.user_name).get():\\n raise endpoints.ConflictException(\\n 'A User with that name already exist!')\\n user = User(name=request.user_name, email=request.email)\\n user.put()\\n return StringMessage(message='User {} created!'.format(request.user_name))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ed2d5150c5eabfd5ce74506f708b5ef7\",\n \"score\": \"0.6369612\",\n \"text\": \"def create_user():\\n username = custom_input(\\\"Enter user name: \\\\n\\\")\\n position = custom_input(\\\"Enter user position (Manager/Salesman): \\\\n\\\")\\n if position == \\\"Salesman\\\" or position == \\\"Manager\\\":\\n exec_insert_query(\\n \\\"INSERT OR IGNORE INTO users VALUES (NULL,'{}','{}','{}','{}')\\\".format(username, position, 0, 0))\\n else:\\n print(\\\"Incorrect position '{}'.\\\\nYou should specify position 'Manager' or 'Salesman'\\\".format(position))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b27a6767be48b03a35074f2b8a3299e9\",\n \"score\": \"0.6366573\",\n \"text\": \"def create_user(admin=False):\\n username = prompt(\\\"Enter username\\\")\\n email = prompt(\\\"Enter email\\\")\\n password1 = prompt_pass(\\\"Enter password\\\")\\n password2 = prompt_pass(\\\"Re-type password\\\")\\n if password1 == password2:\\n new_user = User(\\n username=username,\\n password=password1,\\n email=email\\n )\\n new_user.is_admin = admin\\n db.session.add(new_user)\\n db.session.commit()\\n print('User {0} successfully created'.format(username))\\n else:\\n print(\\\"Error: Passwords don't match\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e50e626d184d5046733f5c9e53eca221\",\n \"score\": \"0.6366382\",\n \"text\": \"def create_unverified_user(self):\\n self.client.post(\\n '/api/users/',\\n self.testUser2,\\n format='json'\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b211b3d1a0cbc231c4f238413153f14f\",\n \"score\": \"0.63663054\",\n \"text\": \"def create_user() -> ci_demo.User:\\n\\n u = ci_demo.User.query.filter(ci_demo.User.id == BaseTestCase.user_id).first()\\n if u is None:\\n # Create user with name test and password test\\n u = ci_demo.User(id=BaseTestCase.user_id, name=BaseTestCase.user_name)\\n u.update_password(BaseTestCase.user_password)\\n ci_demo.db.session.add(u)\\n ci_demo.db.session.commit()\\n\\n return u\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b2c80185f0b0718b3b3a025901232e20\",\n \"score\": \"0.6365039\",\n \"text\": \"def create_user():\\n \\n categories = crud.get_category_entries()\\n countries = crud.get_country_entries()\\n\\n if request.method == 'POST':\\n user = crud.create_user(\\n #['string'] = the \\\"name\\\" field within the form\\n request.form['fname'],\\n request.form['lname'],\\n request.form['email'],\\n request.form['username'],\\n request.form['password'],\\n request.form['category_id'],\\n request.form['country_id'])\\n if user:\\n #testing\\n print(\\\"User has been created!\\\")\\n return redirect('/login')\\n else:\\n flash(\\\"User exists. Please try again.\\\")\\n\\n\\n return render_template(\\n 'registration.html',\\n categories=categories,\\n countries=countries\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2d62fa365c43c1d33a31b0bf7358c80e\",\n \"score\": \"0.6357508\",\n \"text\": \"def test_user_can_create_new_user(self):\\n\\n # Edith goes to the register page\\n self.browser.get(self.server_url + reverse('register'))\\n\\n # She fills in the inputs\\n username_field = self.browser.find_element_by_name('username')\\n username_field.send_keys('netuser')\\n password_field = self.browser.find_element_by_name('password1')\\n password_field.send_keys('password')\\n password_confirmation_field = self.browser.find_element_by_name('password2')\\n password_confirmation_field.send_keys('password')\\n email_field = self.browser.find_element_by_name('email')\\n email_field.send_keys('netuser@edith.com')\\n\\n password_field.send_keys(Keys.RETURN)\\n\\n body = self.browser.find_element_by_tag_name('body')\\n\\n # Edith sees a congratulations message\\n self.assertIn('Congratulations! You are now registered and logged in!', body.text)\\n\\n # After successfully logged in she goes to her applications\\n # self.browser.get(self.server_url + reverse('tokens:list'))\\n\\n # body = self.browser.find_element_by_tag_name('body')\\n # self.assertIn('Your token', body.text)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ff0089320fd0b296b242ef5509e68354\",\n \"score\": \"0.63571775\",\n \"text\": \"def test_new_user():\\n new_user = User('Test User', 'testuser')\\n assert new_user.username == 'testuser'\\n assert new_user.name == 'Test User'\\n assert not new_user.name == 'Sooper User'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"85f2db83c56894b3a800f0c609c26994\",\n \"score\": \"0.63510406\",\n \"text\": \"def create_user():\\n\\n # TODO: Validate server-side before adding to DB\\n first_name = request.form[\\\"first_name\\\"]\\n last_name = request.form[\\\"last_name\\\"]\\n image_url = request.form[\\\"image_url\\\"]\\n\\n # TODO: Error handling\\n user = User(first_name=first_name, last_name=last_name, image_url=image_url)\\n db.session.add(user)\\n db.session.commit()\\n\\n flash(f\\\"New User Created: {first_name} {last_name}\\\")\\n return redirect(\\\"/users\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3dbdedc0ab8fd2c47fdc5e9dd7a7c448\",\n \"score\": \"0.6350954\",\n \"text\": \"def new_user(self, request, sociallogin):\\r\\n return get_account_adapter().new_user(request)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"90b98f229d839e3c25d8c09cbbdcf520\",\n \"score\": \"0.63480407\",\n \"text\": \"def _create_user(user):\\n login = 'osf.' + user._id\\n pw = str(uuid.uuid4())[:8]\\n\\n response = requests.post(\\n url=settings.PIWIK_HOST,\\n data={\\n 'module': 'API',\\n 'method': 'UsersManager.addUser',\\n 'format': 'json',\\n 'token_auth': settings.PIWIK_ADMIN_TOKEN,\\n 'userLogin': login,\\n 'password': pw,\\n 'email': user._id + '@osf.io',\\n 'alias': 'OSF User: {}'.format(user._id),\\n }\\n )\\n\\n if json.loads(response.content)['result'] == 'error':\\n raise PiwikException('Piwik user not updated')\\n\\n user.piwik_token = md5(login + md5(pw).hexdigest()).hexdigest()\\n\\n user.save()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"456863e96ce85ba2b0952c7e7b8555ed\",\n \"score\": \"0.6346355\",\n \"text\": \"def create_users(self):\\n user_fields = ('user_name TEXT PRIMARY KEY', 'password TEXT', 'email TEXT',\\\\\\n 'gender TEXT', 'in_calories_goal INT', 'out_calories_goal INT',\\\\\\n 'budget INT', 'pts INT', 'height INT', 'weight INT', 'steps_goal INT'\\\\\\n 'total_sleep_acquired INT', 'auth_token TEXT', 'user_id TEXT')\\n self.tableCreator('users', *user_fields)\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d9f20f91edcbc4d55ba4e0e405ea0607\",\n \"score\": \"0.63422924\",\n \"text\": \"def test_create_default_user_options():\\n\\n runner = CliRunner()\\n result = runner.invoke(\\n create_default_user, [\\\"--username\\\", \\\"Bob\\\", \\\"--password\\\", \\\"myprecious\\\"]\\n )\\n\\n user = User.query.one()\\n success_string = \\\"Default user 'Bob' created.\\\"\\n\\n assert not result.exception\\n assert success_string in result.output\\n assert isinstance(user, User)\\n assert user.username == \\\"Bob\\\"\\n assert bool(user.check_password(\\\"myprecious\\\"))\\n assert bool(user.is_admin)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"768783c8a671f57bd8e6e443e3a990ae\",\n \"score\": \"0.63366306\",\n \"text\": \"def test_create_default_user():\\n\\n runner = CliRunner()\\n result = runner.invoke(create_default_user)\\n\\n user = User.query.one()\\n success_string = \\\"Default user 'admin' created.\\\"\\n\\n assert not result.exception\\n assert success_string in result.output\\n assert isinstance(user, User)\\n assert user.username == \\\"admin\\\"\\n assert bool(user.check_password(\\\"farm_monitor\\\"))\\n assert bool(user.is_admin)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8e60eac3d902fcc201a1a19b54341d25\",\n \"score\": \"0.63360894\",\n \"text\": \"def create_user(email, password, first, last, div, role, tag, is_sup, sup, budget_code=None, object_code=None,\\n object_name=None):\\n role_obj = Role.query.filter_by(name=role).first()\\n sup_obj = User.query.filter_by(id=sup).first()\\n u = User(email=email, first_name=first, last_name=last, password=password,\\n division=div, role=role_obj, tag_id=tag, is_supervisor=is_sup, supervisor=sup_obj, budget_code=budget_code,\\n object_code=object_code, object_name=object_name)\\n db.session.add(u)\\n db.session.commit()\\n u.password_list.update(u.password_hash)\\n _send_new_user_email(u, password)\\n current_app.logger.info('{} successfully registered user with email {}'.format(current_user.email, u.email))\\n return u.email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3534126b14a4d00d13a3962b8ed5800d\",\n \"score\": \"0.63334095\",\n \"text\": \"def create_user(self, body=None, *args, **_params):\\n return self.post(self.user_create_path, body=body)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a1c629f7d52b34581a6b7fe845277225\",\n \"score\": \"0.63300997\",\n \"text\": \"def create_user(self, device):\\r\\n ip_address = self.device_id.ip_address\\r\\n port = self.device_id.port\\r\\n device_password = self.device_id.device_password\\r\\n user_id = str(self.device_user_id)\\r\\n\\r\\n with c.ConnectToDevice(ip_address, port, device_password) as conn:\\r\\n\\r\\n device_users = conn.get_users()\\r\\n device_user_ids = [int(x.user_id) for x in device_users]\\r\\n if self.device_user_id not in device_user_ids:\\r\\n conn.set_user(uid=self.device_user_id, name=self.name, privilege=const.USER_DEFAULT, user_id=user_id)\\r\\n self.device_uid = self.device_user_id\\r\\n return {\\r\\n \\\"type\\\": \\\"ir.actions.act_window\\\",\\r\\n \\\"res_model\\\": \\\"device.users\\\",\\r\\n \\\"views\\\": [[False, \\\"form\\\"]],\\r\\n \\\"res_id\\\": self.id,\\r\\n \\\"target\\\": \\\"main\\\",\\r\\n \\\"context\\\": {'show_message1': True},\\r\\n }\\r\\n\\r\\n else:\\r\\n return {\\r\\n \\\"type\\\": \\\"ir.actions.act_window\\\",\\r\\n \\\"res_model\\\": \\\"device.users\\\",\\r\\n \\\"views\\\": [[False, \\\"form\\\"]],\\r\\n \\\"res_id\\\": self.id,\\r\\n \\\"target\\\": \\\"main\\\",\\r\\n \\\"context\\\": {'show_message2': True},\\r\\n }\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0db4070cf034fd0b0e8721137404bdb2\",\n \"score\": \"0.6329164\",\n \"text\": \"def _create_user(self, username, email, password, **extra_fields):\\n # print(\\\"hi hassan\\\")\\n if not username:\\n raise ValueError('The given username must be set')\\n email = self.normalize_email(email)\\n username = self.model.normalize_username(username)\\n user = self.model(username=username, email=email, **extra_fields)\\n user.set_password(password)\\n user.save(using=self._db)\\n return user\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e8779f53a68011cb36078e2ffa3d7643\",\n \"score\": \"0.63256544\",\n \"text\": \"def create_user(email, password, pen_name):\\n\\n signup_user = User()\\n signup_user.email = email\\n signup_user.password_hash = argon2.hash(password)\\n signup_user.pen_name = pen_name\\n\\n try:\\n signup_user.save()\\n return signup_user\\n except QueryException:\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aac4513f33f85e64ac280edbb208cd56\",\n \"score\": \"0.6303878\",\n \"text\": \"def _do_user_create(p_user):\\n print(' Creating user: \\\"{}\\\"'.format(p_user))\\n try:\\n pwd.getpwnam(p_user)\\n print(' *** User \\\"{}\\\" already exixts! Skipping Add'.format(p_user))\\n except KeyError:\\n User._add_user(p_user)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a5c674d8e2c82809d20a57b6d7c51766\",\n \"score\": \"0.63029075\",\n \"text\": \"def create_new_user(user: UserRegistrationSchema, db: Session):\\n\\n user.password = generate_password_hash(user.dict()['password'], method='sha256')\\n user_obj = User(**user.dict(exclude_unset=True))\\n db.add(user_obj)\\n db.commit()\\n db.refresh(user_obj)\\n\\n token = generate_token(user.email, 'activate')\\n url = f\\\"{USER_ACTIVATION_URL}?token={token}\\\"\\n context = {\\n 'url': url,\\n 'email': user.email\\n }\\n template = 'activate_user.html'\\n send_email.delay(\\n subject=\\\"Activate your ChooseOne account\\\",\\n template=template,\\n recipients=[user.email],\\n context=context\\n )\\n\\n return UserSchema.from_orm(user_obj)\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":387,"cells":{"query_id":{"kind":"string","value":"96e071f315bfe84fab392617e3d43f4e"},"query":{"kind":"string","value":"Sets the signup_url of this GoogleEnterprise."},"positive_passages":{"kind":"list like","value":[{"docid":"c6aaf918a064923c95e551ecbc6b8ad3","score":"0.782311","text":"def signup_url(self, signup_url):\n if signup_url is not None and len(signup_url) < 1:\n raise ValueError(\"Invalid value for `signup_url`, length must be greater than or equal to `1`\")\n\n self._signup_url = signup_url","title":""}],"string":"[\n {\n \"docid\": \"c6aaf918a064923c95e551ecbc6b8ad3\",\n \"score\": \"0.782311\",\n \"text\": \"def signup_url(self, signup_url):\\n if signup_url is not None and len(signup_url) < 1:\\n raise ValueError(\\\"Invalid value for `signup_url`, length must be greater than or equal to `1`\\\")\\n\\n self._signup_url = signup_url\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"78bdf485adf3c2eb3ffcc3a06ee8dbac","score":"0.6903089","text":"def signup_url(self):\n return self._signup_url","title":""},{"docid":"c927cb649a708861b0d0105a9309bbd9","score":"0.57198805","text":"def ___set_url(self, url):\n self.__set_url(url)","title":""},{"docid":"23b6e2941c090cc70773e4471659f3e2","score":"0.5717212","text":"def __set_url(self, url):\n self._url = url","title":""},{"docid":"8e6af63622a10851db6c3007ac016719","score":"0.5499965","text":"def docu_sign_landing_url(self, docu_sign_landing_url):\n\n self._docu_sign_landing_url = docu_sign_landing_url","title":""},{"docid":"9bc70489089401fa77013aebca15d6b1","score":"0.54041976","text":"def set_storage_url(self, url):\n self.storage_url = url","title":""},{"docid":"4cc977f891f66f23bc523be078b47ac2","score":"0.53637964","text":"def url(self, url):\n if url is None:\n raise ValueError(\"Invalid value for `url`, must not be `None`\")\n\n self._url = url","title":""},{"docid":"fece6533edaf108438c9c814cd1d2a4c","score":"0.5357118","text":"def url(self, url: str):\n\n self._url = url","title":""},{"docid":"fece6533edaf108438c9c814cd1d2a4c","score":"0.5357118","text":"def url(self, url: str):\n\n self._url = url","title":""},{"docid":"fece6533edaf108438c9c814cd1d2a4c","score":"0.5357118","text":"def url(self, url: str):\n\n self._url = url","title":""},{"docid":"20e3a9485495f1e40d3d764079aeacf9","score":"0.5348516","text":"def url(self, url):\n\n self._url = url","title":""},{"docid":"20e3a9485495f1e40d3d764079aeacf9","score":"0.5348516","text":"def url(self, url):\n\n self._url = url","title":""},{"docid":"20e3a9485495f1e40d3d764079aeacf9","score":"0.5348516","text":"def url(self, url):\n\n self._url = url","title":""},{"docid":"20e3a9485495f1e40d3d764079aeacf9","score":"0.5348516","text":"def url(self, url):\n\n self._url = url","title":""},{"docid":"20e3a9485495f1e40d3d764079aeacf9","score":"0.5348516","text":"def url(self, url):\n\n self._url = url","title":""},{"docid":"20e3a9485495f1e40d3d764079aeacf9","score":"0.5348516","text":"def url(self, url):\n\n self._url = url","title":""},{"docid":"20e3a9485495f1e40d3d764079aeacf9","score":"0.5348516","text":"def url(self, url):\n\n self._url = url","title":""},{"docid":"20e3a9485495f1e40d3d764079aeacf9","score":"0.5348516","text":"def url(self, url):\n\n self._url = url","title":""},{"docid":"20e3a9485495f1e40d3d764079aeacf9","score":"0.5348516","text":"def url(self, url):\n\n self._url = url","title":""},{"docid":"20e3a9485495f1e40d3d764079aeacf9","score":"0.5348516","text":"def url(self, url):\n\n self._url = url","title":""},{"docid":"eb281553a5b535dc7300c8d5706075df","score":"0.53339446","text":"def set_server_url(self, new_url):\n self.url = new_url","title":""},{"docid":"e4cfff9ff6662eb4c9d73eb746c72c8a","score":"0.52958584","text":"def signup(self, request, user):\n pass","title":""},{"docid":"e4cfff9ff6662eb4c9d73eb746c72c8a","score":"0.52958584","text":"def signup(self, request, user):\n pass","title":""},{"docid":"3120b0d9e8036220fea0f9f452a5bd5f","score":"0.5294734","text":"def url_auth(self, url_auth):\n self._url_auth = url_auth","title":""},{"docid":"62590cc4de164a249fd15624b1b7f86c","score":"0.5209565","text":"def presigned_url(self, presigned_url):\n\n self._presigned_url = presigned_url","title":""},{"docid":"965592fef39f62a38b6b76fdc9053481","score":"0.5183946","text":"def callback_url(self, callback_url):\n if callback_url is not None and len(callback_url) < 1:\n raise ValueError(\"Invalid value for `callback_url`, length must be greater than or equal to `1`\")\n\n self._callback_url = callback_url","title":""},{"docid":"388e758bcf9850434523d1bfd3015941","score":"0.518234","text":"def add_url(self, url):\n self.resource_url = url\n self.put()","title":""},{"docid":"acaad552cd6bc5fc64e318018f113c84","score":"0.5175278","text":"def _create_url(self, endpoint):\r\n self.url = '%s://%s%s%s%s' % (self.PROTOCOL, self.auth.server,\r\n self.PORT, self.DEFAULT_URL, endpoint)","title":""},{"docid":"01b320942a5b4462eef3636e4ff181fe","score":"0.51287323","text":"def url(self, url) :\n\t\ttry :\n\t\t\tself._url = url\n\t\texcept Exception as e:\n\t\t\traise e","title":""},{"docid":"d779486e1040b316a3e0e44da8610c75","score":"0.5109642","text":"async def signup(self, request: web.Request, *args, **kwargs) -> web.Response:\n\n pass","title":""},{"docid":"0d8c9ff022541da43d2029ba43314a8f","score":"0.50804883","text":"def update_url(self, new_url):\n self.url = new_url","title":""},{"docid":"0d8c9ff022541da43d2029ba43314a8f","score":"0.50804883","text":"def update_url(self, new_url):\n self.url = new_url","title":""},{"docid":"0c451a2ee30b00e5463e717f1af34e39","score":"0.5079066","text":"def setURL(self,URL):\n\t\tpass","title":""},{"docid":"ffa536be882093e7a4ac8dacbb4898f9","score":"0.5042235","text":"def set_haskoin_url(self, haskoin_url:str):\n self.haskoin_url = haskoin_url","title":""},{"docid":"f5ec90bef968f3d2e81e183480de8686","score":"0.5032812","text":"def setPageURL(self, page_url):\n\t\tself.page_url = page_url","title":""},{"docid":"046100d80c7667415461f3991afd3ddd","score":"0.5015592","text":"def auth_url(self):\n raise NotImplementedError('Implement in subclass')","title":""},{"docid":"c6729f47877ed31629c67e3e73520528","score":"0.5010457","text":"def _set_url(self, v, load=False):\n parent = getattr(self, \"_parent\", None)\n if parent is not None and load is False:\n raise AttributeError(\"Cannot set keys directly when\" +\n \" within an instantiated list\")\n\n if hasattr(v, \"_utype\"):\n v = v._utype(v)\n try:\n t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name=\"url\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:ietf:params:xml:ns:yang:nfvo:vnfd', defining_module='vnfd', yang_type='string', is_config=True)\n except (TypeError, ValueError):\n raise ValueError({\n 'error-string': \"\"\"url must be of a type compatible with string\"\"\",\n 'defined-type': \"string\",\n 'generated-type': \"\"\"YANGDynClass(base=six.text_type, is_leaf=True, yang_name=\"url\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:ietf:params:xml:ns:yang:nfvo:vnfd', defining_module='vnfd', yang_type='string', is_config=True)\"\"\",\n })\n\n self.__url = t\n if hasattr(self, '_set'):\n self._set()","title":""},{"docid":"c6729f47877ed31629c67e3e73520528","score":"0.5010457","text":"def _set_url(self, v, load=False):\n parent = getattr(self, \"_parent\", None)\n if parent is not None and load is False:\n raise AttributeError(\"Cannot set keys directly when\" +\n \" within an instantiated list\")\n\n if hasattr(v, \"_utype\"):\n v = v._utype(v)\n try:\n t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name=\"url\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:ietf:params:xml:ns:yang:nfvo:vnfd', defining_module='vnfd', yang_type='string', is_config=True)\n except (TypeError, ValueError):\n raise ValueError({\n 'error-string': \"\"\"url must be of a type compatible with string\"\"\",\n 'defined-type': \"string\",\n 'generated-type': \"\"\"YANGDynClass(base=six.text_type, is_leaf=True, yang_name=\"url\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:ietf:params:xml:ns:yang:nfvo:vnfd', defining_module='vnfd', yang_type='string', is_config=True)\"\"\",\n })\n\n self.__url = t\n if hasattr(self, '_set'):\n self._set()","title":""},{"docid":"c6729f47877ed31629c67e3e73520528","score":"0.5010457","text":"def _set_url(self, v, load=False):\n parent = getattr(self, \"_parent\", None)\n if parent is not None and load is False:\n raise AttributeError(\"Cannot set keys directly when\" +\n \" within an instantiated list\")\n\n if hasattr(v, \"_utype\"):\n v = v._utype(v)\n try:\n t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name=\"url\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:ietf:params:xml:ns:yang:nfvo:vnfd', defining_module='vnfd', yang_type='string', is_config=True)\n except (TypeError, ValueError):\n raise ValueError({\n 'error-string': \"\"\"url must be of a type compatible with string\"\"\",\n 'defined-type': \"string\",\n 'generated-type': \"\"\"YANGDynClass(base=six.text_type, is_leaf=True, yang_name=\"url\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:ietf:params:xml:ns:yang:nfvo:vnfd', defining_module='vnfd', yang_type='string', is_config=True)\"\"\",\n })\n\n self.__url = t\n if hasattr(self, '_set'):\n self._set()","title":""},{"docid":"c38f6f1c3960d9e9d40671bcfa21bcb7","score":"0.5009564","text":"def url(self, new: str) -> None:\n self._url = new","title":""},{"docid":"35623e01ad5716cb1934a5684350e5c8","score":"0.50074023","text":"def updateURL(self):\n self.url = \"http://\" + self.hostname\n if self.port:\n self.url += \":\" + str(self.port)\n return self.url","title":""},{"docid":"4adb3ff35786cba3ae7d5ea231a160f5","score":"0.5001295","text":"def url(self, data):\n self._url = data","title":""},{"docid":"0ae3056c5b8fb72ac9192598ec277ebf","score":"0.49833047","text":"def redirect_url(self, redirect_url):\n\n self._redirect_url = redirect_url","title":""},{"docid":"947be940d274994907e17d5b9db21f03","score":"0.4976722","text":"def user_url(self):\n return self.properties.get('UserUrl', None)","title":""},{"docid":"b9651072d6bbba352af622b7c7a9f159","score":"0.4972217","text":"def set_link(self, url):\n self.URL = url","title":""},{"docid":"ec3a9187fc0f6b38d70fb663507487c2","score":"0.4956822","text":"def _meetup_post_url(self):\n # self.client.post(self.register_url, data = json.dumps(self.users[0]), content_type=\"application/json\")\n # self.client.post(self.login_url, data = json.dumps(self.loging_data), content_type=\"application/json\") \n \n self.post_meetup_url='api/v2/auth/meetups'\n\n return self.post_meetup_url","title":""},{"docid":"00a7e9b2ff9496acca80064708ed89b4","score":"0.49486363","text":"def signup_user(self):\n\n self.testuser3 = User.signup(\n username=\"testuser3\",\n email=\"abc@abc.com\",\n password=\"123456\",\n image_url=\"/test.jpg\")\n\n db.session.commit()","title":""},{"docid":"c977c0ff520e6ce2c9e864c98374c973","score":"0.4935947","text":"def vestorly_url(self, vestorly_url):\n\n self._vestorly_url = vestorly_url","title":""},{"docid":"e2044a5e897aeb77bfb9b1fbd9921ad9","score":"0.49208295","text":"def set_base_url(self, base_url):\n self.base_url = base_url","title":""},{"docid":"cce6b5ab8e66df700014b47cd319a682","score":"0.49193943","text":"def sign_up(self,event):\n sign_in_frame = Sign_up(None,self.client_actions)\n sign_in_frame.Show()\n self.Close()","title":""},{"docid":"83ca93c68bacb59fbe283a37f92f385f","score":"0.49059686","text":"def set_url(self):\n url_input = raw_input(\n 'Enter address of the CatDV Sever (eg. \\'localhost:8080\\'): ')\n self.url = 'http://' + url_input\n return self.url","title":""},{"docid":"c9f7b1322be03b9cd8523ed4b6e91217","score":"0.48371604","text":"def notify_url(self, notify_url):\n\n self._notify_url = notify_url","title":""},{"docid":"c43eb1ec2331a77a397b718461fa123b","score":"0.48288852","text":"def signUpEvent(self):\n if False in self.isFormValid.values():\n self.confirmButton.config(fg = self.errorColor, highlightbackground=self.errorColor, highlightcolor=self.errorColor, highlightthickness=1)\n else:\n self.confirmButton.config(fg = \"black\", highlightthickness=0)\n ret = self.client.register(self.usernameEntry.get(), self.passwordEntry.get(), self.nameEntry.get(), self.surnameEntry.get(), self.emailEntry.get())\n if ret == 1:\n self.cancelEvent()\n self.loginWindow.showMessage(\"Succefully Registered\", \"#4bf442\")\n elif ret == 0:\n self.showErrorLabel()","title":""},{"docid":"bac88bf8a2724a01b7c385c76c70db01","score":"0.4808926","text":"def url(self, value):\r\n self.logger.warn(\"Setting values on url will NOT update the remote Canvas instance.\")\r\n self._url = value","title":""},{"docid":"bac88bf8a2724a01b7c385c76c70db01","score":"0.4808926","text":"def url(self, value):\r\n self.logger.warn(\"Setting values on url will NOT update the remote Canvas instance.\")\r\n self._url = value","title":""},{"docid":"bac88bf8a2724a01b7c385c76c70db01","score":"0.4808926","text":"def url(self, value):\r\n self.logger.warn(\"Setting values on url will NOT update the remote Canvas instance.\")\r\n self._url = value","title":""},{"docid":"bac88bf8a2724a01b7c385c76c70db01","score":"0.4808926","text":"def url(self, value):\r\n self.logger.warn(\"Setting values on url will NOT update the remote Canvas instance.\")\r\n self._url = value","title":""},{"docid":"4a4fe7c8f6880ff27f92d630bccad029","score":"0.4807739","text":"def signup():\n params = {\n 'response_type': 'code',\n 'redirect_uri': get_redirect_uri(request),\n 'scopes': ','.join(config.get('scopes')),\n }\n url = generate_oauth_service().get_authorize_url(**params)\n return redirect(url)","title":""},{"docid":"4a4fe7c8f6880ff27f92d630bccad029","score":"0.4807739","text":"def signup():\n params = {\n 'response_type': 'code',\n 'redirect_uri': get_redirect_uri(request),\n 'scopes': ','.join(config.get('scopes')),\n }\n url = generate_oauth_service().get_authorize_url(**params)\n return redirect(url)","title":""},{"docid":"ea1c2ee634162a1621f2849e09a02314","score":"0.48050377","text":"def url(self, url):\n if url is None:\n raise ValueError(\"Invalid value for `url`, must not be `None`\")\n if url is not None and len(url) > 4096:\n raise ValueError(\"Invalid value for `url`, length must be less than or equal to `4096`\")\n if url is not None and len(url) < 1:\n raise ValueError(\"Invalid value for `url`, length must be greater than or equal to `1`\")\n\n self._url = url","title":""},{"docid":"438201b718bb4de98cef40e5d4838c73","score":"0.48035112","text":"def reset_url(self, url):\n\n self.url = url","title":""},{"docid":"9a848323656031d636a5b11ed5e9dbd8","score":"0.4796168","text":"def signup_user(self, username, email):\n\n self.testuser3 = User.signup(\n username=username,\n email=email,\n password=\"123456\",\n image_url=\"/test.jpg\")\n\n db.session.commit()","title":""},{"docid":"c335fe590c9cabff54ea15090ac9306f","score":"0.47913858","text":"async def sheet_url(self, ctx, url):\n try:\n server = ctx.message.server.id\n if server not in self.settings:\n self.settings[server] = {}\n is_pm = False\n except KeyError:\n is_pm = True\n\n if is_pm:\n await self.bot.say(\"I cannot set this in PM because it's\"\n \" a per-server value\")\n else:\n self.settings[server][\"project_url\"] = url\n dataIO.save_json(\"data/untappd/settings.json\", self.settings)\n await self.bot.say(\"The project endpoint URL has been set\")","title":""},{"docid":"04925737afcbcfdbe51c1e46dc3897bd","score":"0.47835475","text":"def set_notify_url( self, notify_url ):\n\t\tif (notify_url is None) or (len(notify_url) == 0): return\n\t\tif len(notify_url) > 2048:\n\t\t\traise ValueError( 'notify_url cannot exceed 2048 characters' )\n\n\t\tself._nvp_request['NOTIFYURL'] = notify_url","title":""},{"docid":"5d393caa2d5e4b334315e7a5a3713a4d","score":"0.47824097","text":"def after_signup(self, user, **kwargs):\n pass","title":""},{"docid":"b78ba70615347e953b95a660735f3cbb","score":"0.4779945","text":"def external_url(self, external_url):\n\n self._external_url = external_url","title":""},{"docid":"a5a8002ae398d7c8c5f85261eb421e5e","score":"0.47782236","text":"def google_sign_in(self):\n self.generate_state_token()\n auth_url = f\"\"\"\n {AuthClient.GOOGLE_AUTH_ENDPOINT}?\n scope=email%20profile&\n response_type=code&\n state={self.state_token}&\n redirect_uri={self.local_web_server.auth_url}&\n client_id={AuthClient.GOOGLE_CLIENT_ID}\n \"\"\".replace('\\n', '').replace(' ', '')\n webbrowser.open(auth_url)","title":""},{"docid":"987028da2420cd005bb619a49b8ba62c","score":"0.4756313","text":"def jwks_url(self, jwks_url):\n\n self._jwks_url = jwks_url","title":""},{"docid":"7706185723e510d6bdda0c3fc545a85b","score":"0.4754741","text":"def upload_url(self):\n if \"uploadUrl\" in self._prop_dict:\n return self._prop_dict[\"uploadUrl\"]\n else:\n return None","title":""},{"docid":"2d768ecc2ce66be3c874ff9342038b69","score":"0.47324818","text":"def base_url(self, base_url):\n if base_url is None:\n raise ValueError(\"Invalid value for `base_url`, must not be `None`\")\n\n self._base_url = base_url","title":""},{"docid":"8d5acd35e119f1841774f25fae548ce9","score":"0.47320354","text":"def auth_url(self):\n pass","title":""},{"docid":"72365cac79e54c1ba9f9411b9661534b","score":"0.47051036","text":"def redirecturl(self, redirecturl) :\n\t\ttry :\n\t\t\tself._redirecturl = redirecturl\n\t\texcept Exception as e:\n\t\t\traise e","title":""},{"docid":"332d1ac33f18c953218d6ca93df35173","score":"0.46979165","text":"def url(self, url):\n if (self.local_vars_configuration.client_side_validation and\n url is not None and len(url) > 2000):\n raise ValueError(\"Invalid value for `url`, length must be less than or equal to `2000`\") # noqa: E501\n if (self.local_vars_configuration.client_side_validation and\n url is not None and len(url) < 1):\n raise ValueError(\"Invalid value for `url`, length must be greater than or equal to `1`\") # noqa: E501\n if (self.local_vars_configuration.client_side_validation and\n url is not None and not re.search(r'[A-Za-z0-9\\-._~:\\/?#[]@!$&\\'()+,;=]*', url)): # noqa: E501\n raise ValueError(r\"Invalid value for `url`, must be a follow pattern or equal to `/[A-Za-z0-9\\-._~:\\/?#[]@!$&'()+,;=]*/`\") # noqa: E501\n\n self._url = url","title":""},{"docid":"343605401d1ee7b31e2c874892488a1f","score":"0.46773842","text":"def user_email(self, user_email):\n\n self._user_email = user_email","title":""},{"docid":"343605401d1ee7b31e2c874892488a1f","score":"0.46773842","text":"def user_email(self, user_email):\n\n self._user_email = user_email","title":""},{"docid":"1cc56d89ecabcebd22c82a1a1930f430","score":"0.4646073","text":"def __init__(__self__, *,\n google_group_email: str,\n user_email: str):\n pulumi.set(__self__, \"google_group_email\", google_group_email)\n pulumi.set(__self__, \"user_email\", user_email)","title":""},{"docid":"b4600091271a888357aed3c106dff623","score":"0.4645619","text":"def bot_url(self, bot_url):\n\n self._bot_url = bot_url","title":""},{"docid":"0498b587bd94f54e3d2a1a2f8bac7c9a","score":"0.46399748","text":"def set_auth_url(self, testing_on=False):\n # Update which URL to use for auth depending on\n if testing_on == False and use_active_directory == True:\n # If using AD and not testing, use live AD tenant\n self.cip_auth_url = live_100K_auth_url\n elif testing_on == True and use_active_directory == True:\n # If using AD and testing, use beta AD tenant\n self.cip_auth_url = beta_testing_auth_url\n elif testing_on == False and use_active_directory == False:\n # If using LDAP and not testing, use live CIPAPI get-token url\n self.cip_auth_url = live_100k_data_base_url + 'get-token/'\n elif testing_on == True and use_active_directory == False:\n raise ValueError(\n \"LDAP login no longer supported for testing. Please set use_active_directory to True in config.py\"\n )","title":""},{"docid":"f9b9623473fde2bad45ccdb7e9f69b20","score":"0.46297565","text":"def request_url(self, request_url):\n\n self._request_url = request_url","title":""},{"docid":"61366bd35588f6ab95d86460c2184664","score":"0.4627043","text":"def avatar_url(self, avatar_url: object):\n\n self._avatar_url = avatar_url","title":""},{"docid":"61366bd35588f6ab95d86460c2184664","score":"0.4627043","text":"def avatar_url(self, avatar_url: object):\n\n self._avatar_url = avatar_url","title":""},{"docid":"2814604b4cb5e057c8655682e88f81b3","score":"0.46224588","text":"def scm_url(self, scm_url):\n self._scm_url = scm_url","title":""},{"docid":"804f6967a2d252ce9c559227bd77b30f","score":"0.46167585","text":"def redeem_at_sign_up(self, invitation):\n self.request.session.update(\n {\n \"invitation:pk\": invitation.pk,\n # Auto-verify EmailAddress via django-allauth.\n \"account_verified_email\": invitation.to_email,\n }\n )\n url = reverse(\"account_signup\")\n\n obj = invitation.object\n organization = None\n if isinstance(obj, Team):\n organization = obj.organization\n elif isinstance(obj, Organization):\n organization = obj\n if organization and AdminPermission.has_sso_enabled(organization):\n url += f\"?organization={organization.slug}\"\n return HttpResponseRedirect(url)","title":""},{"docid":"5c2b398a13201cc7aa35b6d3e9f32770","score":"0.46138364","text":"def build_url(self):\n return \"https://api.meetup.com/{}/events\".format(self.group_url_name)","title":""},{"docid":"3edda176cb95d00051c3d2ccb6af96ba","score":"0.460809","text":"def email(self, email):\n self._email = email","title":""},{"docid":"c7b4c5287de8e4785a754b02f6d436d4","score":"0.46065032","text":"def authorise_url(self, callback_url: str = ''):\n authorise_url_endpoint = '/api/v4/oauth/authorise/?oauth_token={0}'.format(\n self.credentials.token\n )\n\n if callback_url:\n authorise_url_endpoint = '{0}&callback={1}'.format(authorise_url_endpoint, callback_url)\n\n return urljoin(self.base_url, authorise_url_endpoint)","title":""},{"docid":"584e6e574999bcbc408b09cb781502c7","score":"0.45981118","text":"def click_sign_in_up(self):\n self.browser.click_on_element(self.locator_login.SIGNIN)","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""},{"docid":"edf73bdd43acf1b4fa8bf69a59e0f338","score":"0.45980984","text":"def email(self, email):\n\n self._email = email","title":""}],"string":"[\n {\n \"docid\": \"78bdf485adf3c2eb3ffcc3a06ee8dbac\",\n \"score\": \"0.6903089\",\n \"text\": \"def signup_url(self):\\n return self._signup_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c927cb649a708861b0d0105a9309bbd9\",\n \"score\": \"0.57198805\",\n \"text\": \"def ___set_url(self, url):\\n self.__set_url(url)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"23b6e2941c090cc70773e4471659f3e2\",\n \"score\": \"0.5717212\",\n \"text\": \"def __set_url(self, url):\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8e6af63622a10851db6c3007ac016719\",\n \"score\": \"0.5499965\",\n \"text\": \"def docu_sign_landing_url(self, docu_sign_landing_url):\\n\\n self._docu_sign_landing_url = docu_sign_landing_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9bc70489089401fa77013aebca15d6b1\",\n \"score\": \"0.54041976\",\n \"text\": \"def set_storage_url(self, url):\\n self.storage_url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4cc977f891f66f23bc523be078b47ac2\",\n \"score\": \"0.53637964\",\n \"text\": \"def url(self, url):\\n if url is None:\\n raise ValueError(\\\"Invalid value for `url`, must not be `None`\\\")\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fece6533edaf108438c9c814cd1d2a4c\",\n \"score\": \"0.5357118\",\n \"text\": \"def url(self, url: str):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fece6533edaf108438c9c814cd1d2a4c\",\n \"score\": \"0.5357118\",\n \"text\": \"def url(self, url: str):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fece6533edaf108438c9c814cd1d2a4c\",\n \"score\": \"0.5357118\",\n \"text\": \"def url(self, url: str):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"20e3a9485495f1e40d3d764079aeacf9\",\n \"score\": \"0.5348516\",\n \"text\": \"def url(self, url):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"20e3a9485495f1e40d3d764079aeacf9\",\n \"score\": \"0.5348516\",\n \"text\": \"def url(self, url):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"20e3a9485495f1e40d3d764079aeacf9\",\n \"score\": \"0.5348516\",\n \"text\": \"def url(self, url):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"20e3a9485495f1e40d3d764079aeacf9\",\n \"score\": \"0.5348516\",\n \"text\": \"def url(self, url):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"20e3a9485495f1e40d3d764079aeacf9\",\n \"score\": \"0.5348516\",\n \"text\": \"def url(self, url):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"20e3a9485495f1e40d3d764079aeacf9\",\n \"score\": \"0.5348516\",\n \"text\": \"def url(self, url):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"20e3a9485495f1e40d3d764079aeacf9\",\n \"score\": \"0.5348516\",\n \"text\": \"def url(self, url):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"20e3a9485495f1e40d3d764079aeacf9\",\n \"score\": \"0.5348516\",\n \"text\": \"def url(self, url):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"20e3a9485495f1e40d3d764079aeacf9\",\n \"score\": \"0.5348516\",\n \"text\": \"def url(self, url):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"20e3a9485495f1e40d3d764079aeacf9\",\n \"score\": \"0.5348516\",\n \"text\": \"def url(self, url):\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"eb281553a5b535dc7300c8d5706075df\",\n \"score\": \"0.53339446\",\n \"text\": \"def set_server_url(self, new_url):\\n self.url = new_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e4cfff9ff6662eb4c9d73eb746c72c8a\",\n \"score\": \"0.52958584\",\n \"text\": \"def signup(self, request, user):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e4cfff9ff6662eb4c9d73eb746c72c8a\",\n \"score\": \"0.52958584\",\n \"text\": \"def signup(self, request, user):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3120b0d9e8036220fea0f9f452a5bd5f\",\n \"score\": \"0.5294734\",\n \"text\": \"def url_auth(self, url_auth):\\n self._url_auth = url_auth\",\n \"title\": \"\"\n },\n {\n \"docid\": \"62590cc4de164a249fd15624b1b7f86c\",\n \"score\": \"0.5209565\",\n \"text\": \"def presigned_url(self, presigned_url):\\n\\n self._presigned_url = presigned_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"965592fef39f62a38b6b76fdc9053481\",\n \"score\": \"0.5183946\",\n \"text\": \"def callback_url(self, callback_url):\\n if callback_url is not None and len(callback_url) < 1:\\n raise ValueError(\\\"Invalid value for `callback_url`, length must be greater than or equal to `1`\\\")\\n\\n self._callback_url = callback_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"388e758bcf9850434523d1bfd3015941\",\n \"score\": \"0.518234\",\n \"text\": \"def add_url(self, url):\\n self.resource_url = url\\n self.put()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"acaad552cd6bc5fc64e318018f113c84\",\n \"score\": \"0.5175278\",\n \"text\": \"def _create_url(self, endpoint):\\r\\n self.url = '%s://%s%s%s%s' % (self.PROTOCOL, self.auth.server,\\r\\n self.PORT, self.DEFAULT_URL, endpoint)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"01b320942a5b4462eef3636e4ff181fe\",\n \"score\": \"0.51287323\",\n \"text\": \"def url(self, url) :\\n\\t\\ttry :\\n\\t\\t\\tself._url = url\\n\\t\\texcept Exception as e:\\n\\t\\t\\traise e\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d779486e1040b316a3e0e44da8610c75\",\n \"score\": \"0.5109642\",\n \"text\": \"async def signup(self, request: web.Request, *args, **kwargs) -> web.Response:\\n\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0d8c9ff022541da43d2029ba43314a8f\",\n \"score\": \"0.50804883\",\n \"text\": \"def update_url(self, new_url):\\n self.url = new_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0d8c9ff022541da43d2029ba43314a8f\",\n \"score\": \"0.50804883\",\n \"text\": \"def update_url(self, new_url):\\n self.url = new_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0c451a2ee30b00e5463e717f1af34e39\",\n \"score\": \"0.5079066\",\n \"text\": \"def setURL(self,URL):\\n\\t\\tpass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ffa536be882093e7a4ac8dacbb4898f9\",\n \"score\": \"0.5042235\",\n \"text\": \"def set_haskoin_url(self, haskoin_url:str):\\n self.haskoin_url = haskoin_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f5ec90bef968f3d2e81e183480de8686\",\n \"score\": \"0.5032812\",\n \"text\": \"def setPageURL(self, page_url):\\n\\t\\tself.page_url = page_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"046100d80c7667415461f3991afd3ddd\",\n \"score\": \"0.5015592\",\n \"text\": \"def auth_url(self):\\n raise NotImplementedError('Implement in subclass')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c6729f47877ed31629c67e3e73520528\",\n \"score\": \"0.5010457\",\n \"text\": \"def _set_url(self, v, load=False):\\n parent = getattr(self, \\\"_parent\\\", None)\\n if parent is not None and load is False:\\n raise AttributeError(\\\"Cannot set keys directly when\\\" +\\n \\\" within an instantiated list\\\")\\n\\n if hasattr(v, \\\"_utype\\\"):\\n v = v._utype(v)\\n try:\\n t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name=\\\"url\\\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:ietf:params:xml:ns:yang:nfvo:vnfd', defining_module='vnfd', yang_type='string', is_config=True)\\n except (TypeError, ValueError):\\n raise ValueError({\\n 'error-string': \\\"\\\"\\\"url must be of a type compatible with string\\\"\\\"\\\",\\n 'defined-type': \\\"string\\\",\\n 'generated-type': \\\"\\\"\\\"YANGDynClass(base=six.text_type, is_leaf=True, yang_name=\\\"url\\\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:ietf:params:xml:ns:yang:nfvo:vnfd', defining_module='vnfd', yang_type='string', is_config=True)\\\"\\\"\\\",\\n })\\n\\n self.__url = t\\n if hasattr(self, '_set'):\\n self._set()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c6729f47877ed31629c67e3e73520528\",\n \"score\": \"0.5010457\",\n \"text\": \"def _set_url(self, v, load=False):\\n parent = getattr(self, \\\"_parent\\\", None)\\n if parent is not None and load is False:\\n raise AttributeError(\\\"Cannot set keys directly when\\\" +\\n \\\" within an instantiated list\\\")\\n\\n if hasattr(v, \\\"_utype\\\"):\\n v = v._utype(v)\\n try:\\n t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name=\\\"url\\\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:ietf:params:xml:ns:yang:nfvo:vnfd', defining_module='vnfd', yang_type='string', is_config=True)\\n except (TypeError, ValueError):\\n raise ValueError({\\n 'error-string': \\\"\\\"\\\"url must be of a type compatible with string\\\"\\\"\\\",\\n 'defined-type': \\\"string\\\",\\n 'generated-type': \\\"\\\"\\\"YANGDynClass(base=six.text_type, is_leaf=True, yang_name=\\\"url\\\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:ietf:params:xml:ns:yang:nfvo:vnfd', defining_module='vnfd', yang_type='string', is_config=True)\\\"\\\"\\\",\\n })\\n\\n self.__url = t\\n if hasattr(self, '_set'):\\n self._set()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c6729f47877ed31629c67e3e73520528\",\n \"score\": \"0.5010457\",\n \"text\": \"def _set_url(self, v, load=False):\\n parent = getattr(self, \\\"_parent\\\", None)\\n if parent is not None and load is False:\\n raise AttributeError(\\\"Cannot set keys directly when\\\" +\\n \\\" within an instantiated list\\\")\\n\\n if hasattr(v, \\\"_utype\\\"):\\n v = v._utype(v)\\n try:\\n t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name=\\\"url\\\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:ietf:params:xml:ns:yang:nfvo:vnfd', defining_module='vnfd', yang_type='string', is_config=True)\\n except (TypeError, ValueError):\\n raise ValueError({\\n 'error-string': \\\"\\\"\\\"url must be of a type compatible with string\\\"\\\"\\\",\\n 'defined-type': \\\"string\\\",\\n 'generated-type': \\\"\\\"\\\"YANGDynClass(base=six.text_type, is_leaf=True, yang_name=\\\"url\\\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:ietf:params:xml:ns:yang:nfvo:vnfd', defining_module='vnfd', yang_type='string', is_config=True)\\\"\\\"\\\",\\n })\\n\\n self.__url = t\\n if hasattr(self, '_set'):\\n self._set()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c38f6f1c3960d9e9d40671bcfa21bcb7\",\n \"score\": \"0.5009564\",\n \"text\": \"def url(self, new: str) -> None:\\n self._url = new\",\n \"title\": \"\"\n },\n {\n \"docid\": \"35623e01ad5716cb1934a5684350e5c8\",\n \"score\": \"0.50074023\",\n \"text\": \"def updateURL(self):\\n self.url = \\\"http://\\\" + self.hostname\\n if self.port:\\n self.url += \\\":\\\" + str(self.port)\\n return self.url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4adb3ff35786cba3ae7d5ea231a160f5\",\n \"score\": \"0.5001295\",\n \"text\": \"def url(self, data):\\n self._url = data\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0ae3056c5b8fb72ac9192598ec277ebf\",\n \"score\": \"0.49833047\",\n \"text\": \"def redirect_url(self, redirect_url):\\n\\n self._redirect_url = redirect_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"947be940d274994907e17d5b9db21f03\",\n \"score\": \"0.4976722\",\n \"text\": \"def user_url(self):\\n return self.properties.get('UserUrl', None)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b9651072d6bbba352af622b7c7a9f159\",\n \"score\": \"0.4972217\",\n \"text\": \"def set_link(self, url):\\n self.URL = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ec3a9187fc0f6b38d70fb663507487c2\",\n \"score\": \"0.4956822\",\n \"text\": \"def _meetup_post_url(self):\\n # self.client.post(self.register_url, data = json.dumps(self.users[0]), content_type=\\\"application/json\\\")\\n # self.client.post(self.login_url, data = json.dumps(self.loging_data), content_type=\\\"application/json\\\") \\n \\n self.post_meetup_url='api/v2/auth/meetups'\\n\\n return self.post_meetup_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"00a7e9b2ff9496acca80064708ed89b4\",\n \"score\": \"0.49486363\",\n \"text\": \"def signup_user(self):\\n\\n self.testuser3 = User.signup(\\n username=\\\"testuser3\\\",\\n email=\\\"abc@abc.com\\\",\\n password=\\\"123456\\\",\\n image_url=\\\"/test.jpg\\\")\\n\\n db.session.commit()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c977c0ff520e6ce2c9e864c98374c973\",\n \"score\": \"0.4935947\",\n \"text\": \"def vestorly_url(self, vestorly_url):\\n\\n self._vestorly_url = vestorly_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e2044a5e897aeb77bfb9b1fbd9921ad9\",\n \"score\": \"0.49208295\",\n \"text\": \"def set_base_url(self, base_url):\\n self.base_url = base_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cce6b5ab8e66df700014b47cd319a682\",\n \"score\": \"0.49193943\",\n \"text\": \"def sign_up(self,event):\\n sign_in_frame = Sign_up(None,self.client_actions)\\n sign_in_frame.Show()\\n self.Close()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"83ca93c68bacb59fbe283a37f92f385f\",\n \"score\": \"0.49059686\",\n \"text\": \"def set_url(self):\\n url_input = raw_input(\\n 'Enter address of the CatDV Sever (eg. \\\\'localhost:8080\\\\'): ')\\n self.url = 'http://' + url_input\\n return self.url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c9f7b1322be03b9cd8523ed4b6e91217\",\n \"score\": \"0.48371604\",\n \"text\": \"def notify_url(self, notify_url):\\n\\n self._notify_url = notify_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c43eb1ec2331a77a397b718461fa123b\",\n \"score\": \"0.48288852\",\n \"text\": \"def signUpEvent(self):\\n if False in self.isFormValid.values():\\n self.confirmButton.config(fg = self.errorColor, highlightbackground=self.errorColor, highlightcolor=self.errorColor, highlightthickness=1)\\n else:\\n self.confirmButton.config(fg = \\\"black\\\", highlightthickness=0)\\n ret = self.client.register(self.usernameEntry.get(), self.passwordEntry.get(), self.nameEntry.get(), self.surnameEntry.get(), self.emailEntry.get())\\n if ret == 1:\\n self.cancelEvent()\\n self.loginWindow.showMessage(\\\"Succefully Registered\\\", \\\"#4bf442\\\")\\n elif ret == 0:\\n self.showErrorLabel()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bac88bf8a2724a01b7c385c76c70db01\",\n \"score\": \"0.4808926\",\n \"text\": \"def url(self, value):\\r\\n self.logger.warn(\\\"Setting values on url will NOT update the remote Canvas instance.\\\")\\r\\n self._url = value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bac88bf8a2724a01b7c385c76c70db01\",\n \"score\": \"0.4808926\",\n \"text\": \"def url(self, value):\\r\\n self.logger.warn(\\\"Setting values on url will NOT update the remote Canvas instance.\\\")\\r\\n self._url = value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bac88bf8a2724a01b7c385c76c70db01\",\n \"score\": \"0.4808926\",\n \"text\": \"def url(self, value):\\r\\n self.logger.warn(\\\"Setting values on url will NOT update the remote Canvas instance.\\\")\\r\\n self._url = value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bac88bf8a2724a01b7c385c76c70db01\",\n \"score\": \"0.4808926\",\n \"text\": \"def url(self, value):\\r\\n self.logger.warn(\\\"Setting values on url will NOT update the remote Canvas instance.\\\")\\r\\n self._url = value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4a4fe7c8f6880ff27f92d630bccad029\",\n \"score\": \"0.4807739\",\n \"text\": \"def signup():\\n params = {\\n 'response_type': 'code',\\n 'redirect_uri': get_redirect_uri(request),\\n 'scopes': ','.join(config.get('scopes')),\\n }\\n url = generate_oauth_service().get_authorize_url(**params)\\n return redirect(url)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4a4fe7c8f6880ff27f92d630bccad029\",\n \"score\": \"0.4807739\",\n \"text\": \"def signup():\\n params = {\\n 'response_type': 'code',\\n 'redirect_uri': get_redirect_uri(request),\\n 'scopes': ','.join(config.get('scopes')),\\n }\\n url = generate_oauth_service().get_authorize_url(**params)\\n return redirect(url)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ea1c2ee634162a1621f2849e09a02314\",\n \"score\": \"0.48050377\",\n \"text\": \"def url(self, url):\\n if url is None:\\n raise ValueError(\\\"Invalid value for `url`, must not be `None`\\\")\\n if url is not None and len(url) > 4096:\\n raise ValueError(\\\"Invalid value for `url`, length must be less than or equal to `4096`\\\")\\n if url is not None and len(url) < 1:\\n raise ValueError(\\\"Invalid value for `url`, length must be greater than or equal to `1`\\\")\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"438201b718bb4de98cef40e5d4838c73\",\n \"score\": \"0.48035112\",\n \"text\": \"def reset_url(self, url):\\n\\n self.url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9a848323656031d636a5b11ed5e9dbd8\",\n \"score\": \"0.4796168\",\n \"text\": \"def signup_user(self, username, email):\\n\\n self.testuser3 = User.signup(\\n username=username,\\n email=email,\\n password=\\\"123456\\\",\\n image_url=\\\"/test.jpg\\\")\\n\\n db.session.commit()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c335fe590c9cabff54ea15090ac9306f\",\n \"score\": \"0.47913858\",\n \"text\": \"async def sheet_url(self, ctx, url):\\n try:\\n server = ctx.message.server.id\\n if server not in self.settings:\\n self.settings[server] = {}\\n is_pm = False\\n except KeyError:\\n is_pm = True\\n\\n if is_pm:\\n await self.bot.say(\\\"I cannot set this in PM because it's\\\"\\n \\\" a per-server value\\\")\\n else:\\n self.settings[server][\\\"project_url\\\"] = url\\n dataIO.save_json(\\\"data/untappd/settings.json\\\", self.settings)\\n await self.bot.say(\\\"The project endpoint URL has been set\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"04925737afcbcfdbe51c1e46dc3897bd\",\n \"score\": \"0.47835475\",\n \"text\": \"def set_notify_url( self, notify_url ):\\n\\t\\tif (notify_url is None) or (len(notify_url) == 0): return\\n\\t\\tif len(notify_url) > 2048:\\n\\t\\t\\traise ValueError( 'notify_url cannot exceed 2048 characters' )\\n\\n\\t\\tself._nvp_request['NOTIFYURL'] = notify_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5d393caa2d5e4b334315e7a5a3713a4d\",\n \"score\": \"0.47824097\",\n \"text\": \"def after_signup(self, user, **kwargs):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b78ba70615347e953b95a660735f3cbb\",\n \"score\": \"0.4779945\",\n \"text\": \"def external_url(self, external_url):\\n\\n self._external_url = external_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a5a8002ae398d7c8c5f85261eb421e5e\",\n \"score\": \"0.47782236\",\n \"text\": \"def google_sign_in(self):\\n self.generate_state_token()\\n auth_url = f\\\"\\\"\\\"\\n {AuthClient.GOOGLE_AUTH_ENDPOINT}?\\n scope=email%20profile&\\n response_type=code&\\n state={self.state_token}&\\n redirect_uri={self.local_web_server.auth_url}&\\n client_id={AuthClient.GOOGLE_CLIENT_ID}\\n \\\"\\\"\\\".replace('\\\\n', '').replace(' ', '')\\n webbrowser.open(auth_url)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"987028da2420cd005bb619a49b8ba62c\",\n \"score\": \"0.4756313\",\n \"text\": \"def jwks_url(self, jwks_url):\\n\\n self._jwks_url = jwks_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7706185723e510d6bdda0c3fc545a85b\",\n \"score\": \"0.4754741\",\n \"text\": \"def upload_url(self):\\n if \\\"uploadUrl\\\" in self._prop_dict:\\n return self._prop_dict[\\\"uploadUrl\\\"]\\n else:\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2d768ecc2ce66be3c874ff9342038b69\",\n \"score\": \"0.47324818\",\n \"text\": \"def base_url(self, base_url):\\n if base_url is None:\\n raise ValueError(\\\"Invalid value for `base_url`, must not be `None`\\\")\\n\\n self._base_url = base_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8d5acd35e119f1841774f25fae548ce9\",\n \"score\": \"0.47320354\",\n \"text\": \"def auth_url(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"72365cac79e54c1ba9f9411b9661534b\",\n \"score\": \"0.47051036\",\n \"text\": \"def redirecturl(self, redirecturl) :\\n\\t\\ttry :\\n\\t\\t\\tself._redirecturl = redirecturl\\n\\t\\texcept Exception as e:\\n\\t\\t\\traise e\",\n \"title\": \"\"\n },\n {\n \"docid\": \"332d1ac33f18c953218d6ca93df35173\",\n \"score\": \"0.46979165\",\n \"text\": \"def url(self, url):\\n if (self.local_vars_configuration.client_side_validation and\\n url is not None and len(url) > 2000):\\n raise ValueError(\\\"Invalid value for `url`, length must be less than or equal to `2000`\\\") # noqa: E501\\n if (self.local_vars_configuration.client_side_validation and\\n url is not None and len(url) < 1):\\n raise ValueError(\\\"Invalid value for `url`, length must be greater than or equal to `1`\\\") # noqa: E501\\n if (self.local_vars_configuration.client_side_validation and\\n url is not None and not re.search(r'[A-Za-z0-9\\\\-._~:\\\\/?#[]@!$&\\\\'()+,;=]*', url)): # noqa: E501\\n raise ValueError(r\\\"Invalid value for `url`, must be a follow pattern or equal to `/[A-Za-z0-9\\\\-._~:\\\\/?#[]@!$&'()+,;=]*/`\\\") # noqa: E501\\n\\n self._url = url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"343605401d1ee7b31e2c874892488a1f\",\n \"score\": \"0.46773842\",\n \"text\": \"def user_email(self, user_email):\\n\\n self._user_email = user_email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"343605401d1ee7b31e2c874892488a1f\",\n \"score\": \"0.46773842\",\n \"text\": \"def user_email(self, user_email):\\n\\n self._user_email = user_email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1cc56d89ecabcebd22c82a1a1930f430\",\n \"score\": \"0.4646073\",\n \"text\": \"def __init__(__self__, *,\\n google_group_email: str,\\n user_email: str):\\n pulumi.set(__self__, \\\"google_group_email\\\", google_group_email)\\n pulumi.set(__self__, \\\"user_email\\\", user_email)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b4600091271a888357aed3c106dff623\",\n \"score\": \"0.4645619\",\n \"text\": \"def bot_url(self, bot_url):\\n\\n self._bot_url = bot_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0498b587bd94f54e3d2a1a2f8bac7c9a\",\n \"score\": \"0.46399748\",\n \"text\": \"def set_auth_url(self, testing_on=False):\\n # Update which URL to use for auth depending on\\n if testing_on == False and use_active_directory == True:\\n # If using AD and not testing, use live AD tenant\\n self.cip_auth_url = live_100K_auth_url\\n elif testing_on == True and use_active_directory == True:\\n # If using AD and testing, use beta AD tenant\\n self.cip_auth_url = beta_testing_auth_url\\n elif testing_on == False and use_active_directory == False:\\n # If using LDAP and not testing, use live CIPAPI get-token url\\n self.cip_auth_url = live_100k_data_base_url + 'get-token/'\\n elif testing_on == True and use_active_directory == False:\\n raise ValueError(\\n \\\"LDAP login no longer supported for testing. Please set use_active_directory to True in config.py\\\"\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f9b9623473fde2bad45ccdb7e9f69b20\",\n \"score\": \"0.46297565\",\n \"text\": \"def request_url(self, request_url):\\n\\n self._request_url = request_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"61366bd35588f6ab95d86460c2184664\",\n \"score\": \"0.4627043\",\n \"text\": \"def avatar_url(self, avatar_url: object):\\n\\n self._avatar_url = avatar_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"61366bd35588f6ab95d86460c2184664\",\n \"score\": \"0.4627043\",\n \"text\": \"def avatar_url(self, avatar_url: object):\\n\\n self._avatar_url = avatar_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2814604b4cb5e057c8655682e88f81b3\",\n \"score\": \"0.46224588\",\n \"text\": \"def scm_url(self, scm_url):\\n self._scm_url = scm_url\",\n \"title\": \"\"\n },\n {\n \"docid\": \"804f6967a2d252ce9c559227bd77b30f\",\n \"score\": \"0.46167585\",\n \"text\": \"def redeem_at_sign_up(self, invitation):\\n self.request.session.update(\\n {\\n \\\"invitation:pk\\\": invitation.pk,\\n # Auto-verify EmailAddress via django-allauth.\\n \\\"account_verified_email\\\": invitation.to_email,\\n }\\n )\\n url = reverse(\\\"account_signup\\\")\\n\\n obj = invitation.object\\n organization = None\\n if isinstance(obj, Team):\\n organization = obj.organization\\n elif isinstance(obj, Organization):\\n organization = obj\\n if organization and AdminPermission.has_sso_enabled(organization):\\n url += f\\\"?organization={organization.slug}\\\"\\n return HttpResponseRedirect(url)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5c2b398a13201cc7aa35b6d3e9f32770\",\n \"score\": \"0.46138364\",\n \"text\": \"def build_url(self):\\n return \\\"https://api.meetup.com/{}/events\\\".format(self.group_url_name)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3edda176cb95d00051c3d2ccb6af96ba\",\n \"score\": \"0.460809\",\n \"text\": \"def email(self, email):\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c7b4c5287de8e4785a754b02f6d436d4\",\n \"score\": \"0.46065032\",\n \"text\": \"def authorise_url(self, callback_url: str = ''):\\n authorise_url_endpoint = '/api/v4/oauth/authorise/?oauth_token={0}'.format(\\n self.credentials.token\\n )\\n\\n if callback_url:\\n authorise_url_endpoint = '{0}&callback={1}'.format(authorise_url_endpoint, callback_url)\\n\\n return urljoin(self.base_url, authorise_url_endpoint)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"584e6e574999bcbc408b09cb781502c7\",\n \"score\": \"0.45981118\",\n \"text\": \"def click_sign_in_up(self):\\n self.browser.click_on_element(self.locator_login.SIGNIN)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n },\n {\n \"docid\": \"edf73bdd43acf1b4fa8bf69a59e0f338\",\n \"score\": \"0.45980984\",\n \"text\": \"def email(self, email):\\n\\n self._email = email\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":388,"cells":{"query_id":{"kind":"string","value":"850b14adc74914000ecee267cb5a171e"},"query":{"kind":"string","value":"Replaces 'pattern' in 'string' with 'sub' if 'pattern' starts 'string'."},"positive_passages":{"kind":"list like","value":[{"docid":"ebf3a6bfd34aa2c3d8d9c5914ab345ea","score":"0.77272403","text":"def lreplace(pattern, sub, string):\n return re.sub('^%s' % pattern, sub, string)","title":""}],"string":"[\n {\n \"docid\": \"ebf3a6bfd34aa2c3d8d9c5914ab345ea\",\n \"score\": \"0.77272403\",\n \"text\": \"def lreplace(pattern, sub, string):\\n return re.sub('^%s' % pattern, sub, string)\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"e224a45e914a1459828b24848b832fbe","score":"0.65532935","text":"def sub(self, pattern: str, repl: Union[str, callable], string: str, strict: bool = True, case_sensitive: bool = False) -> str:\n if case_sensitive:\n result = re.sub(pattern, repl, string)\n else:\n result = re.sub(pattern, repl, string, flags=re.IGNORECASE)\n if result == string: # No substitution happened!\n self._unexpected_behavior(\"sub\", pattern, \"did not yield any substitutions\", string, strict)\n return result # Returns only if sub happened or non strict behavior","title":""},{"docid":"4e8e907314ef0f2c22ab45f6a9aa1ead","score":"0.64997524","text":"def replacePattern( pattern, str ):\r\n\t\r\n\t# Do the thing~\r\n\ttry:\r\n\t\treturn str.replace(pattern[0],pattern[1])\r\n\texcept:\r\n\t\tprint(\"Error(replacePattern): Invalid transform syntax on pattern,\",pattern[0],\"! Skipping...\")\r\n\t\treturn str","title":""},{"docid":"8e5b1f2fe62bdfa29f306874ac2fb011","score":"0.6368721","text":"def __preg_replace_str(pat, rep, subject):\n reg = __preg_setup(pat)\n # function call\n if callable(rep):\n def __callback(match):\n match_list = list(match.groups())\n match_list.insert(0, subject)\n match_list = tuple(match_list)\n o = rep(match_list)\n return o\n return reg.sub(__callback, subject)\n # string\n else:\n return reg.sub(rep, subject)","title":""},{"docid":"54055af0b96e09ef37f942309440a4a4","score":"0.63533336","text":"def re_sub(pattern, repl, string):\n groups = []\n result = re.sub(pattern, lambda m: re_collect_groups(m, groups, repl), string)\n return result, groups","title":""},{"docid":"c485b5025d7e144d120a118135a08431","score":"0.6350744","text":"def worker(string, pattern, replacement, f):\n matches = []\n for i in range(pattern.__len__()):\n matches.extend(gregexpr(pattern[i], string, i, f))\n matches.sort(key=itemgetter(2), reverse=True)\n for i in range(matches.__len__()-1, -1, -1):\n if any([filter_matches(matches[i], m) for m in matches[:i]]):\n matches.pop(i)\n matches.sort(key=itemgetter(1))\n for i in range(matches.__len__()-1, -1, -1):\n s = matches[i][1]\n e = matches[i][3]\n p = pattern[matches[i][0]]\n r = replacement[matches[i][0]]\n pre = string[:s]\n r0 = re.sub(p, r, string[s:e], flags=f)\n end = string[e:]\n string = pre+r0+end\n return string","title":""},{"docid":"079b657a060e2f1b8a6990f6340e2d01","score":"0.61693805","text":"def regex_replacer(pattern, repl):\n return lambda x: sub(pattern, repl, x)","title":""},{"docid":"ac2ea56ed410bc70b3e467eedf93d37c","score":"0.611818","text":"def mgsub(string, pattern, replacement, flags=0):\n\n assert isinstance(pattern, list), \"Input pattern must be a list\"\n assert ((isinstance(replacement, list) & (replacement.__len__() == pattern.__len__())) |\n isinstance(replacement, str)), \"Input replacement must be a list of equal length to pattern or a string\"\n\n if isinstance(replacement, str):\n replacement = [replacement for p in pattern]\n\n if not isinstance(string, str) and isinstance(string, collections.Sequence):\n output = [worker(s, pattern, replacement, flags) for s in string]\n else:\n output = worker(string, pattern, replacement, flags)\n return output","title":""},{"docid":"1f19eebf28660f4a375263912b9d1aad","score":"0.60709614","text":"def replace_patterns(string, patterns):\n for old, new in patterns:\n string = string.replace(old, new)\n return string","title":""},{"docid":"d87f1611d7ec81d74916c5bc22b7f856","score":"0.6036524","text":"def sub(pattern,replacement,*,count=0,flags=0):\n regex = re.compile(pattern,flags)\n def _sub(input):\n yield from (regex.sub(repl=replacement,string=line,count=count) for line in input)\n return _sub","title":""},{"docid":"1ef2091d3319c9ea1f8815732a5d2143","score":"0.6011735","text":"def replace(pattern, replacement, value):\n return re.sub(pattern, replacement, value)","title":""},{"docid":"b6babf01def905307b7e6472748bc9c4","score":"0.5923076","text":"def replace(s, pattern, replacement):\n # the replacement string may contain invalid backreferences (like \\1 or \\g)\n # which will cause python's regex to blow up. Since this should emulate\n # the jam version exactly and the jam version didn't support\n # backreferences, this version shouldn't either. re.sub\n # allows replacement to be a callable; this is being used\n # to simply return the replacement string and avoid the hassle\n # of worrying about backreferences within the string.\n def _replacement(matchobj):\n return replacement\n return re.sub(pattern, _replacement, s)","title":""},{"docid":"6e80f6038cbf2f1f2303b671015b43c7","score":"0.58642614","text":"def match(pattern, string):\n return re.match(pattern, string)","title":""},{"docid":"6e9e69048806c5de93bc1a8bb52a17ea","score":"0.5853369","text":"def substitution(master_string, replace_string, sub_string):\n length = len(replace_string)\n escape_character = \"+\"\n for index in xrange(len(master_string) - length + 1):\n window = master_string[index: length + index]\n if window == replace_string:\n if master_string[:index].count(escape_character) % 2 == 1:\n # means the replace_string is in the middle of a already\n # replaced string\n continue\n new_string = master_string[:index] + escape_character + \\\n sub_string + escape_character + \\\n master_string[index + length:]\n return new_string\n else:\n return None","title":""},{"docid":"953cfbca525341a9e52621b4e8b55c88","score":"0.585088","text":"def replacePatterns( patterns, str ):\r\n\t\r\n\t# Make a copy of the string so we don't get weird behavior~\r\n\ts = str\r\n\t\r\n\t# For each pattern,\r\n\tfor pattern in patterns:\r\n\t\ts = replacePattern(pattern,s)\t# Replace the pattern\r\n\treturn s","title":""},{"docid":"f3fc268e872fdb1594c804010a684a3a","score":"0.5785354","text":"def update_word_pattern(word, pattern, letter):\r\n for i in range(len(word)):\r\n if word[i] == letter:\r\n pattern = pattern[:i] + letter + pattern[i + 1:]\r\n return pattern","title":""},{"docid":"801a6ccdf4b3be3e87a685727dd17546","score":"0.5764851","text":"def __str_replace_str(pat, rep, subject):\n return subject.replace(pat, rep)","title":""},{"docid":"3424580fb0bc73f4bc07ee3e0e7b39da","score":"0.57075423","text":"def apply_and_get_result(self, string):\n if self.is_multiline:\n compiled_pattern = re.compile(self.pattern, re.MULTILINE)\n else:\n compiled_pattern = re.compile(self.pattern)\n\n result = re.sub(compiled_pattern, self.repl, string)\n return result","title":""},{"docid":"e80b0687a31ef2ead799c97a9a359d58","score":"0.57067484","text":"def update_word_pattern(word,pattern,letter):\n new_pattern = list(pattern)\n for i in range(len(word)):\n if word[i] == letter:\n new_pattern[i] = letter\n return ''.join(new_pattern)","title":""},{"docid":"5ea8315953fc05cb799dc15312beca51","score":"0.56539804","text":"def update_word_pattern(word,pattern,letter):\n\n pattern=list(pattern) # convert the pattern from a string to list\n\n # checks if the the secret word contain the letter\n for j in range(len(word)):\n if letter==word[j]:\n pattern[j]=letter # updates the appropiate place in the pattern\n\n pattern=\"\".join(pattern)\n\n return pattern","title":""},{"docid":"8fd71418c1c1e58945cf6c5b57cfe7ee","score":"0.5649985","text":"def _substitute(self, str):\r\n\r\n return self._regex.sub(\r\n lambda mo: self._reflections[mo.string[mo.start() : mo.end()]], str.lower()\r\n )","title":""},{"docid":"69ad2964f41789690a6b699425d9826d","score":"0.5643551","text":"def replace_pattern(x, pattern_b, replacement):\n\n try:\n res = x.strip().replace(pattern_b,replacement)\n except:\n res = x\n # insert logging\n return res","title":""},{"docid":"88748eb2bc90038658882ab3ebc926aa","score":"0.56325567","text":"def lsub(self, directory,pattern):\n\t\tpass","title":""},{"docid":"c5e87494bf848cb94c4b29f650566e79","score":"0.5608165","text":"def sub(\n self, pattern: Union[bytes, str_scalars], repl: Union[bytes, str_scalars], count: int = 0\n ) -> Strings:\n if isinstance(repl, bytes):\n repl = repl.decode()\n return self._get_matcher(pattern).sub(repl, count)","title":""},{"docid":"8e1bf2f7f80d79d450ed5eba39fa0104","score":"0.5583376","text":"def sub_re(self, callback, msg):\n self.sub(callback, re.compile(msg))","title":""},{"docid":"8c59dac29c863aaf6a1e1be819df2b2c","score":"0.557107","text":"def replace(self, pattern, repl, *args, **kwargs):\n c = MessageMixin.replace(self, pattern, repl, *args, **kwargs)\n self.path, pc = utils.safe_subn(\n pattern, repl, self.path, *args, **kwargs\n )\n c += pc\n return c","title":""},{"docid":"cd6cf86e775803c0b243e67c1759a6d5","score":"0.5551831","text":"def _substitute(self, str):\n\n return self._regex.sub(\n lambda mo: self._reflections[mo.string[mo.start() : mo.end()]], str.lower()\n )","title":""},{"docid":"90e4557340c33caefa614d3d9fbf3169","score":"0.5439628","text":"def test_pattern_exists_in_string(self):\n self.assertTrue(self.pattern1 in self.string1)\n self.assertEqual(2, search(self.pattern1, self.string1))","title":""},{"docid":"5148954c882450b26ed80e12cabd6fbe","score":"0.54316485","text":"def preg_replace(pat, rep, subject):\n out = subject\n if isinstance(pat, list):\n repIsStr = isinstance(rep, list)\n for i in pat:\n if repIsStr:\n repStr = rep\n else:\n repStr = rep[i]\n out = __preg_replace_str(pat[i], repStr, out)\n else:\n out = __preg_replace_str(pat, rep, subject)\n return out","title":""},{"docid":"19209707837832cf55fec527bb92eca2","score":"0.54167587","text":"def _pattern(self, pattern, that, topic):\n\n if len(pattern) == 0:\n return None\n # Mutilate the input. Remove all punctuation and convert the\n # text to all caps.\n input = string.upper(pattern)\n input = re.sub(self._brain._puncStripRE, \" \", input)\n if that.strip() == u\"\": that = u\"ULTRABOGUSDUMMYTHAT\" # 'that' must never be empty\n thatInput = string.upper(that)\n thatInput = re.sub(self._brain._puncStripRE, \" \", thatInput)\n thatInput = re.sub(self._brain._whitespaceRE, \" \", thatInput)\n if topic.strip() == u\"\": topic = u\"ULTRABOGUSDUMMYTOPIC\" # 'topic' must never be empty\n topicInput = string.upper(topic)\n topicInput = re.sub(self._brain._puncStripRE, \" \", topicInput)\n \n\n # Pass the input off to the recursive call\n patMatch, template = self._brain._match(input.split(), thatInput.split(), topicInput.split(), self._brain._root)\n\n return patMatch, template","title":""},{"docid":"475358eea83883f9a01f694fadb79842","score":"0.5416043","text":"def regex_replace(regex, replacement, input):\n\treturn get_regex(regex).sub(replacement, input)","title":""},{"docid":"2391f2b16cc4985f21d010ffd4d168a2","score":"0.5412871","text":"def find(string, pattern):\n # implement find_iterative and find_recursive\n # assert isinstance(string, str)\n return find_iterative(string, pattern)\n # return find_recursive(string, pattern)","title":""},{"docid":"c17ec25f1ee5f4fee7c623b4f25e0047","score":"0.53997946","text":"def test_pattern_exists_in_string_and_returns_first_occurrence(self):\n self.assertTrue(self.pattern2 in self.string2)\n self.assertTrue(self.string2.count(self.pattern2) > 1)\n self.assertEqual(3, search(self.pattern2, self.string2))","title":""},{"docid":"2ec6bee06bba45068a8db99bd7f0ba1d","score":"0.53962237","text":"def _sub(self, reg, result):\n self._text = re.sub(reg, result, self._text)\n return self","title":""},{"docid":"c598f8fb80df0df95d821614b48d601b","score":"0.5372047","text":"def search(pattern, s):\n if pattern not in _regexp_compile_cache:\n _regexp_compile_cache[pattern] = sre_compile.compile(pattern)\n return _regexp_compile_cache[pattern].search(s)","title":""},{"docid":"01e0257a6af1edc45edfbf89f12292c7","score":"0.53491944","text":"def make_replacement(\n self, pattern: str, replacement: str, regex: bool = True\n ) -> None:\n if regex:\n self.body = re.sub(pattern, replacement, self.body)\n else:\n self.body = self.body.replace(pattern, replacement)\n for part in self.parts:\n part.make_replacement(pattern, replacement, regex=regex)","title":""},{"docid":"a27fd2ce055258eac810d4c73202901d","score":"0.5329081","text":"def regex_replace(s, find, replace):\n return re.sub(find, replace, s)","title":""},{"docid":"149a7f5cc43bbe1b0029e91ad8660c47","score":"0.53118736","text":"def match_tokenized_regex_pattern(pattern, string):\n\tif not pattern and not string: # if reach the end of both pattern and string\n\t\treturn True\n\tif not pattern or not string: # if reach the end of either pattern and string\n\t\treturn False\n\n\tp = pattern[0]\n\tc = string[0]\n\n\t# removes cases with (letter-symbol vs. letter) and (non-matching single letters)\n\tif p == c or p == '.':\n\t\treturn match_tokenized_regex_pattern(pattern[1:], string[1:])\n\n\t# X* --> X can appear 0 times, once, or more (3 cases)\n\telif len(pattern) > 1:\n\t\tif pattern[0] == c:\n\t\t\tis_match = match_tokenized_regex_pattern(pattern, string[1:]) # appear >= 1 times\n\t\t\tif is_match:\n\t\t\t\treturn True\n\t\treturn match_tokenized_regex_pattern(pattern[1:], string) # appear 0 times in string\n\n\t# non-matching single letters\n\telse:\n\t\treturn False","title":""},{"docid":"131b0595bca047d5615610417ed1ea8e","score":"0.53036594","text":"def _group(s, groups):\n for pattern, replacement in groups:\n if pattern.match(s):\n return replacement\n return s","title":""},{"docid":"45ca4a249418bea4c1a3520fe7d089a7","score":"0.5294655","text":"def __call__(self, value, pattern, replacement, data=None, engine=None):\n return sub(pattern, replacement, value)","title":""},{"docid":"6816948b2976bbf9428f34c2de76aa48","score":"0.5293176","text":"def match(pattern, s):\n # The regexp compilation caching is inlined in both Match and Search for\n # performance reasons; factoring it out into a separate function turns out\n # to be noticeably expensive.\n if pattern not in _regexp_compile_cache:\n _regexp_compile_cache[pattern] = sre_compile.compile(pattern)\n return _regexp_compile_cache[pattern].match(s)","title":""},{"docid":"405978c54777ac5b96280e88315f4a15","score":"0.52822506","text":"def replace(self, pattern, content):\n pass","title":""},{"docid":"32ae4555466b2f80bb2c191daeb6f875","score":"0.52768046","text":"def replace(\n self,\n pattern: StringValue,\n replacement: StringValue,\n ) -> StringValue:\n return ops.StringReplace(self, pattern, replacement).to_expr()","title":""},{"docid":"8372720021e963f8558a77960bdd1568","score":"0.527449","text":"def sub(self, text):\n if self._regexIsDirty:\n self._update_regex()\n return self._regex.sub(self, text)","title":""},{"docid":"6129eecad220c679072d1adcdba09ddb","score":"0.52710116","text":"def rfind_str(text, sub, start=None, end=None):\n assert isinstance(text,str), '%s is not a string' % text\n return text.rfind(sub,start,end)","title":""},{"docid":"d50782465a645681d1d5c092b9f0f291","score":"0.52637935","text":"def sub (cls, regex_, replace, query):\n\n cregex = cls.regex_cache.setdefault (\n regex_, regex.compile (regex_, regex.UNICODE | regex.VERSION1))\n return cregex.sub (replace, query)","title":""},{"docid":"419dd68d3f63e92821b6384617b21de8","score":"0.5258351","text":"def findfirst(pattern, string, flags=0):\n string_list = re.findall(pattern, string, flags)\n if string_list:\n result = string_list[0]\n else:\n result = \"\"\n return result","title":""},{"docid":"75d906ffab3bcb539473a45f01812a29","score":"0.5249003","text":"def make_one_sub(value, sub_list):\n for s in sub_list:\n formatted, n = s['regex'].subn(s['repl'], value, count = 1)\n if n > 0:\n value = formatted\n break\n return value","title":""},{"docid":"5bdffd5466b58d18a78b847bab12f217","score":"0.5246227","text":"def replace( self, pattern, replacement ) :\n if self._map == None : self._map = {}\n self._map[pattern] = replacement","title":""},{"docid":"2bee3285b8ddd9d123d27c819b34a4ed","score":"0.5211044","text":"def find_str(text, sub, start=None, end=None):\n assert isinstance(text,str), '%s is not a string' % text\n return text.find(sub,start,end)","title":""},{"docid":"61169a7f5e595c7af9e3b1f7c9eaa031","score":"0.5208249","text":"def _search_regex(pattern, string, group=None):\n\t\tif isinstance(pattern, (str, compat_str, type(re.compile('')))):\n\t\t\tmobj = re.search(pattern, string, 0)\n\t\telse:\n\t\t\tfor p in pattern:\n\t\t\t\tmobj = re.search(p, string, 0)\n\t\t\t\tif mobj:\n\t\t\t\t\tbreak\n\t\tif mobj:\n\t\t\tif group is None:\n\t\t\t\t# return the first matching group\n\t\t\t\treturn next(g for g in mobj.groups() if g is not None)\n\t\t\telse:\n\t\t\t\treturn mobj.group(group)\n\t\telse:\n\t\t\tprint('[YouTubeVideoUrl] unable extract pattern from string!')\n\t\t\treturn ''","title":""},{"docid":"ceb06e77d428b69be4e1c30f6da9abaa","score":"0.5192851","text":"def replace_line(s, start, replace):\n lines = s.split('\\n')\n found = False\n for i in range(len(lines)):\n if lines[i].startswith(start):\n lines[i] = replace\n found = True\n break\n if not found:\n raise ValueError('could not match string %s' % start)\n return '\\n'.join(lines)","title":""},{"docid":"9e8223743c7212570623c42f4bd4fe17","score":"0.5191779","text":"def re_replace(\n self,\n pattern: str | StringValue,\n replacement: str | StringValue,\n ) -> StringValue:\n return ops.RegexReplace(self, pattern, replacement).to_expr()","title":""},{"docid":"2a412fd90e17fb182f6ca3fbf6eebb78","score":"0.5191737","text":"def addPattern(self, text):\n def ms(s):\n if options.ignore_case:\n return s.lower()\n return s\n\n flags = 0\n if options.ignore_case:\n flags = re.I\n t = \"s\"\n isRegExp = False\n if text.startswith(\"d:\"):\n t = \"d\"\n text = text[2:]\n if text.startswith(\"s:\"):\n text = text[2:]\n if text.startswith(\"~\"):\n text = text[1:]\n isRegExp = True\n if isRegExp:\n try:\n p = re.compile(text, flags)\n except re.error as exc:\n sys.stderr.write(\"%r is not a valid regular expression\\n\" % text)\n sys.stderr.write(\" %s\\n\" % exc)\n sys.exit(1)\n if t == \"d\":\n self.descriptionPatterns.append(p)\n else:\n self.summaryPatterns.append(p)\n else:\n if t == \"d\":\n self.descriptionText.append(ms(text))\n else:\n self.summaryText.append(ms(text))","title":""},{"docid":"fe657592f8b634bacfdb5208ac2c2cd4","score":"0.5184157","text":"def genPattern(self,patternStr,ignoreCase=True):\n\t\tif ignoreCase:\n\t\t\treturn re.compile(patternStr,re.IGNORECASE)\n\t\telse:\n\t\t\treturn re.compile(patternStr)","title":""},{"docid":"12a2468e6e0f4532bb6c5050eb3120e3","score":"0.51750845","text":"def remove(sub, strng):\n if sub not in strng:\n return strng\n else:\n index = strng.find(sub)\n result = ''\n for i in range(index):\n result += strng[i]\n for i in range(index+len(sub), len(strng)):\n result += strng[i]\n return result","title":""},{"docid":"7167b5980a90c5a3ddd18f814fcfcdd3","score":"0.5170874","text":"def parse(expression, pattern, replacer):\n regex = [p[\"regexp\"] for p in Airbot.patterns if p[\"name\"] == pattern][0]\n return re.sub(regex, replacer, expression)","title":""},{"docid":"24eda24a2728378fb019effe84dcbfbf","score":"0.51561236","text":"def regexp_replace(\n string: \"ColumnOrName\", pattern: Union[str, Column], replacement: Union[str, Column]\n) -> Column:\n if isinstance(pattern, str):\n pattern_col = _create_column_from_literal(pattern)\n else:\n pattern_col = _to_java_column(pattern)\n if isinstance(replacement, str):\n replacement_col = _create_column_from_literal(replacement)\n else:\n replacement_col = _to_java_column(replacement)\n return _invoke_function(\"regexp_replace\", _to_java_column(string), pattern_col, replacement_col)","title":""},{"docid":"d6b82b230389afbd8225eaa562fef108","score":"0.51526624","text":"def make_all_subs(value, sub_list):\n for s in sub_list:\n value = s['regex'].sub(s['repl'], value, count = 1)\n return value","title":""},{"docid":"0ec4f45bfc2b348fc4314ad9eb4f903f","score":"0.514604","text":"def regex_replace(string, expr, repl):\n r = re.compile(raw(expr))\n return r.sub(repl, string)","title":""},{"docid":"4bae5403d87001cbc1a63dfc50496790","score":"0.51357526","text":"def replace_pattern(\n df: pd.DataFrame,\n column: str,\n *,\n pat: str,\n repl: str,\n new_column: Optional[str] = None,\n case: bool = True,\n regex: bool = True,\n) -> pd.DataFrame:\n new_column = new_column or column\n df.loc[:, new_column] = df[column].str.replace(pat, repl, case=case, regex=regex)\n return df","title":""},{"docid":"753503338cf964a7b9a2760b6771b28f","score":"0.5132225","text":"def set_name_from_pattern_xref(base_addr, end, name, pattern):\r\n pattern_offset = ida_search.find_binary(\r\n base_addr, end, pattern, 16, ida_search.SEARCH_DOWN\r\n )\r\n if pattern_offset == ida_idaapi.BADADDR or pattern_offset is None:\r\n return ida_idaapi.BADADDR\r\n\r\n xref = list(idautils.XrefsTo(pattern_offset))\r\n if len(xref) == 0:\r\n return ida_idaapi.BADADDR\r\n\r\n function = idaapi.get_func(xref[0].frm)\r\n if function is None:\r\n return ida_idaapi.BADADDR\r\n idc.set_name(function.start_ea, name, idc.SN_CHECK)\r\n print(f\"[+] {name} : {hex(function.start_ea)}\")\r\n return function.start_ea","title":""},{"docid":"7737a91fd8d061bd93c4dd0cabb7ae85","score":"0.5100343","text":"def regex_pattern(stem_str):\n str_list = stem_str.split('-')\n # add word boundary\n if len(str_list) == 2:\n pos = 2 - str_list.index('')*2\n pos2 = 3 - str_list.index('')*3\n str_list.insert(pos, '\\\\b')\n str_list.insert(pos2, '.*')\n # replace '-' with '.*'\n pat_str = ''.join([i if len(i) > 0 else '.*' for i in str_list])\n return pat_str","title":""},{"docid":"ac00ec9da264d03817acf850279af23a","score":"0.5071816","text":"def sub_cdn(self, s, m):\r\n res_fn = m.group(self.file_index)\r\n for sub in self.subs:\r\n pat = sub[\"pattern\"]\r\n rep = sub[\"replacement\"]\r\n m2 = re.search(pat, res_fn)\r\n if m2:\r\n s1 = s[:m.start(self.file_index)] + rep + s[m.end(self.file_index):]\r\n return s1\r\n return False","title":""},{"docid":"8d0a2c1561d25b5144a81e4d4db9e227","score":"0.5058605","text":"def replaceStrs(s, *args):\n if args == (): return s\n mapping = dict([(frm, to) for frm, to in args])\n return re.sub(\"|\".join(map(re.escape, mapping.keys())),\n lambda match:mapping[match.group(0)], s)","title":""},{"docid":"a63a679edf1e3b6acca19cc5d27d47b8","score":"0.5044197","text":"def find_replace_regex(chunk, out, find, sub=\"\"):\n util.write_annotation(out, ((key, re.sub(find, sub, val)) for (key, val) in util.read_annotation_iteritems(chunk)))","title":""},{"docid":"9ed960bf1ec5ca795855a2c463b33e55","score":"0.5035251","text":"def search(pattern, text, flags=0):\r\n\tmatch_obj = re.search(pattern, text, flags)\r\n\tdump_results(match_obj, text)","title":""},{"docid":"f69ece641595895143a6e65f4ce110c7","score":"0.50253934","text":"def match(pattern,word):\n if not pattern or pattern == '*':\n # No pattern/wildcard, matches everything\n return True\n # Only simple patterns considered for now\n if pattern.endswith('*'):\n # Match the start\n return word.startswith(pattern[:-1])\n else:\n # Match the whole word exactly\n return (word == pattern)","title":""},{"docid":"1f1d0bfab84c4d59b7c6302586f0ab24","score":"0.50040156","text":"def _matches(self, pattern: str, string: str) -> bool:\n regex_pattern = '^' + pattern.replace('*', '.*') + '$'\n return bool(re.match(regex_pattern, string))","title":""},{"docid":"14fd9e45f65f1aae8512785edab38951","score":"0.49961507","text":"def case_insensitive_replace(haystack: str, needle: str, replacement: str) -> str:\n regex = re.compile(re.escape(needle), re.IGNORECASE)\n return regex.sub(replacement, haystack)","title":""},{"docid":"6078d34c11aa9f1096ba5219677497b9","score":"0.4988578","text":"def strlookup(pattern, space):\n return fnmatch.filter(space, pattern)","title":""},{"docid":"d9e5964f7cda67bdebb29d995ba22ce1","score":"0.49839634","text":"def kmp(string, pattern):\n\n # either string or pattern is empty, return -1\n if len(string) * len(pattern) == 0:\n return -1\n\n # build table of shifts\n pattern = list(pattern)\n lp = len(pattern)\n shifts = [1] * (lp + 1)\n shift = 1\n for p in range(lp):\n while shift <= p and pattern[p] != pattern[p - shift]:\n shift += shifts[p - shift]\n shifts[p + 1] = shift\n\n # search\n start_pos = 0\n match_len = 0\n for c in string:\n while match_len == lp or \\\n match_len >= 0 and pattern[match_len] != c:\n start_pos += shifts[match_len]\n match_len -= shifts[match_len]\n\n match_len += 1\n\n if match_len == lp:\n return start_pos\n\n return -1","title":""},{"docid":"70c50827d50fb849904fbd45806d753c","score":"0.49817824","text":"def pattern(word, pat):\n matches = {}\n if len(word) < len(pat):\n return False\n for (w,p) in zip(word, pat):\n if p not in matches:\n matches[p] = w\n elif matches[p] != w:\n return pattern(word[1:], pat)\n return True","title":""},{"docid":"cef40f328bd2c914cd5377895fe02ac7","score":"0.4973586","text":"def replace_wildcard_with_time(aa,string1):\n # Set wild card string\n if aa.outfile_frequency=='year':\n x2=str(aa.year)\n elif aa.outfile_frequency=='month':\n x2=str(aa.year)+str(aa.month).zfill(2)\n else:\n raise ToDoError('Need to code up for different outfile_frequency')\n # Replace wild card characters\n string2=string1.replace(aa.wildcard,x2)\n\n return string2","title":""},{"docid":"a44739ef656aabd86cb9d4d050030768","score":"0.49441954","text":"def index_str(text, sub, start=None, end=None):\n assert isinstance(text,str), '%s is not a string' % text\n return text.index(sub,start,end)","title":""},{"docid":"6dd5b1ef8f5df62b3e3a077acbd1a7db","score":"0.493214","text":"def is_sublist_of(pattern, text):\n\n if len(pattern) > len(text):\n return False\n\n if not pattern:\n return True\n\n for possible_start in ifindall(pattern[0], text):\n if text[possible_start : possible_start+len(pattern)] == pattern:\n return True\n\n return False","title":""},{"docid":"ac8e594ba0b916545501499a10f85757","score":"0.49176946","text":"def __init__(self, pattern):\n self.idx = 0\n self.prefix, replace, self.suffix = re.split(\"(#+)\", pattern)\n self.sublen = len(replace)","title":""},{"docid":"9be0c1e60a1843a85548877ef24ff01d","score":"0.4915615","text":"def replace(self, pattern, repl, *args, **kwargs):\n c = self.request.replace(pattern, repl, *args, **kwargs)\n if self.response:\n c += self.response.replace(pattern, repl, *args, **kwargs)\n return c","title":""},{"docid":"7470cbf0d604dcc72e67e4ebdfb06de9","score":"0.49127653","text":"def similar_to_pattern(word,pattern):\r\n flag = True\r\n for i in range(len(word)):\r\n if pattern[i] == '_':\r\n continue\r\n elif word[i] != pattern[i]:\r\n flag = False\r\n return flag","title":""},{"docid":"1a916db5fd339a67adefb0a4fbe9ba4f","score":"0.49120873","text":"def test_replace(self):\n\n regex = \"th\"\n expected = \"Hello, htis is Fun Ilrys. I just wanted to know how htings goes around hte tests.\" # pylint: disable=line-too-long\n actual = Regex(regex).replace_match(self.data, \"ht\")\n\n self.assertEqual(expected, actual)","title":""},{"docid":"dfc257944cf1d6166c9f0f2fbbf3bbdf","score":"0.4909576","text":"def match(pattern, text):\n if pattern == '':\n return True\n elif pattern == '$':\n return (text == '')\n elif len(pattern) > 1 and pattern[1] in '*?':\n p, op, pat = pattern[0], pattern[1], pattern[2:]\n if op == '*':\n return match_star(p, pat, text)\n elif op == '?':\n if match1(p, text) and match(pat, text[1:]):\n return True\n else:\n return match(pat, text)\n else:\n return (match1(pattern[0], text) and\n match( pattern[1:],text[1:])) # fill in this line","title":""},{"docid":"3d377255580b54a0c740f2659da53268","score":"0.49065128","text":"def rindex_str(text, sub, start=None, end=None):\n assert isinstance(text,str), '%s is not a string' % text\n return text.rindex(sub,start,end)","title":""},{"docid":"b6997956d36c0ca6461c6cabbb12ae95","score":"0.49021098","text":"def substitute_chars(self, column, pattern, val_sub,\n val_exception=np.nan, val_none=np.nan,\n inplace=True, return_series=False,\n target_column=None):\n series = self.df[column].copy().astype(str).apply(\n lambda x: regex_sub_value(\n val=x,\n pattern=pattern,\n val_sub=val_sub,\n val_exception=val_exception,\n val_none=val_none,\n )\n )\n return inplace_return_series(self.df, column, series,\n inplace, return_series, target_column)","title":""},{"docid":"f8a98be8f3e0db7b718392cfab9fef5d","score":"0.48936597","text":"def prefix_sub (match_object):\n s = match_object.group (0)\n return cls.prefix_to_prefix.get (s, s)","title":""},{"docid":"f57227a1432322ff07f027d4a6c17e78","score":"0.48791716","text":"def apply_pattern(view, pattern, func):\n result = parameterNameRegex.sub(lambda m: func(getparameters_byname(view, m.group(1)),\n m.group(1)),\n pattern)\n result = parameterGuidRegex.sub(lambda m: func(getparameter(view, m.group()),\n m.group()),\n result)\n result = parameterBipRegex.sub(lambda m: func(getparameter(view, \"BuiltInParameter.\" + m.group(1)),\n m.group(1)),\n result)\n return result","title":""},{"docid":"38bb9fb5b3ce6bdf98661652978f5736","score":"0.48766243","text":"def matchPat(pre,str):\n if pre=='':\n return True\n pre=duplicateAsteriskRemover(pre)\n if len(pre)>len(str) and pre[0]!='*':\n return False\n elif len(pre) == 1:\n if pre[0]==str[0] or pre[0]=='*':\n return True\n else:\n return False\n elif pre[0]=='*':\n a=1\n c=0\n while c<len(str):\n if pre[a]==str[c]:\n return matchPat(pre[a:],str[c:])\n else:\n c+=1\n if pre[0]!=str[0]:\n return False\n else:\n return matchPat(pre[1:],str[1:])","title":""},{"docid":"729f5921190b2c2612d8932a3096adb0","score":"0.48736763","text":"def _glob_match(self, pattern, string):\r\n # regex flags Multi-line, Unicode, Locale\r\n return bool(re.match(fnmatch.translate(pattern), string,\r\n re.M | re.U | re.L))","title":""},{"docid":"25ad35abc2841933328d7853d2ca02bb","score":"0.4857707","text":"def generateRegexFromPattern( pattern ):\r\n\t\r\n\treturn re.compile(pattern)","title":""},{"docid":"47cb09b4813e5dfe57c4181928117855","score":"0.4857365","text":"def replace_identifiers(string):\n return re.sub(string=string, **RE['identifiers'])","title":""},{"docid":"d93ef63dd421280b5a7f218d356a710c","score":"0.4850763","text":"def contains(text, pattern):\n assert isinstance(text, str), 'text is not a string: {}'.format(text)\n assert isinstance(pattern, str), 'pattern is not a string: {}'.format(text)\n # TODO: Implement contains here (iteratively and/or recursively)\n num = 0 #index to keep track of which letter in pattern you're comparing to you\n if len(pattern) == 0:\n return True \n for letter in text:\n #if they arent equal and you're part of the way into comapring to the pattern\n if num>0 and letter != pattern[num]:\n num = 0\n # check if your current letter matches a letter in pattern\n if letter == pattern[num]:\n num+=1\n #if you're finished with the pattern then finish ahead of time\n if num > len(pattern)-1:\n return True\n \n return False","title":""},{"docid":"e09fcfc543e3aae86084548ae081e6c8","score":"0.48504576","text":"def match(word, pattern):\n # if the pattern is empty, only match empty word\n if len(pattern) == 0: return len(word) == 0\n # if the word is empty, only match \"*\"\n if len(word) == 0: return pattern == \"*\"\n \n # otherwise try to match first char in pattern\n if pattern[0] == \"?\" or pattern[0] == word[0]:\n # try to match pattern and word without first chars\n return match(word[1:], pattern[1:])\n elif pattern[0] == \"*\":\n # skip chars and try to match with rest of pattern\n for i in range(len(word)+1):\n if match(word[i:], pattern[1:]):\n return True\n return False\n else:\n return False","title":""},{"docid":"b7822c9b72166c429f17ed848a7d058a","score":"0.4846589","text":"def resolve(unresolved_pattern, pattern_dictionary, regex_pat=re.compile(\"\"\"%\\{(.+?)\\}\"\"\")):\n #Get all referenced patterns into set\n pattern_set = set(regex_pat.findall(unresolved_pattern))\n #Return original pattern if it does not reference any other patterns\n if not pattern_set:\n return \"(?:\"+unresolved_pattern+\")\"\n for unres_pat in pattern_set:\n #If a pattern is known:\n if unres_pat.split(\":\")[0] in pattern_dictionary.keys():\n #Resolve it\n unresolved_pattern = unresolved_pattern.replace(encaps(unres_pat), resolve(pattern_dictionary[unres_pat.split(\":\")[0]], pattern_dictionary))\n return unresolved_pattern","title":""},{"docid":"4ce31eca01966b34b22296f17c252384","score":"0.48435923","text":"def match(pattern='', priority=PRIORITY_LOW):\n return Match(pattern, priority=priority).decorate","title":""},{"docid":"97eb9a2ccbad49e876d552d19ca9b833","score":"0.48368943","text":"def convertPattern(pattern, sign):\n\n # Check for include vs exclude patterns.\n if pattern[:2] == \"+ \":\n pattern = pattern[2:]\n sign = \"+\"\n elif pattern[:2] == \"- \":\n pattern = pattern[2:]\n sign = \"-\"\n\n # Express windows, mac patterns in unix patterns (rsync.py extension).\n separator = os.path.normpath(\"/\")\n if separator != \"/\":\n pattern = re.sub(re.escape(separator), \"/\", pattern)\n\n # If pattern contains '/' it should match from the start.\n temp = pattern\n if pattern[0] == \"/\":\n pattern = pattern[1:]\n if temp[-1] == \"/\":\n temp = temp[:-1]\n\n # Convert pattern rules: ** * ? to regexp rules.\n pattern = re.escape(pattern)\n pattern = string.replace(pattern, \"\\\\?\", \".\")\n pattern = string.replace(pattern, \"\\\\*\\\\*\", \".*\")\n pattern = string.replace(pattern, \"\\\\*\", \"[^/]*\")\n pattern = string.replace(pattern, \"\\\\*\", \".*\")\n\n if \"/\" in temp:\n # If pattern contains '/' it should match from the start.\n pattern = \"^\\\\/\" + pattern\n else:\n # Else the pattern should match the all file or folder name.\n pattern = \"\\\\/\" + pattern\n\n if pattern[-2:] != \"\\\\/\" and pattern[-2:] != \".*\":\n # File patterns should match also folders.\n pattern = pattern + \"\\\\/?\"\n\n # Pattern should match till the end.\n pattern = pattern + \"$\"\n return (sign, pattern)","title":""},{"docid":"70beee47c206720b1c48a8cf9a4a2245","score":"0.48351344","text":"def reduce_lengthening(self, data, pattern):\n data.loc[:, self.tweets_col] = data.loc[:, self.tweets_col].apply(lambda tweet: pattern.sub(r\"\\1\\1\", tweet))\n return data","title":""},{"docid":"33a995c13cde0ca51549c28ee9104686","score":"0.48343244","text":"def assertInString(self, conn_string, pattern):\r\n found = conn_string.find(pattern) != -1\r\n self.assertTrue(found,\r\n \"pattern \\\"%s\\\" was not found in connection string \\\"%s\\\"\" % (pattern, conn_string))","title":""},{"docid":"00df529494eaee98878f970301328f02","score":"0.48266596","text":"def compile_pcre_pattern(pattern, additional_flags=0):\n try:\n if pattern[0] != '/':\n return re.compile(pattern, additional_flags)\n\n parts = pattern.split('/')\n modifiers = parts[-1]\n newpattern = pattern[1:-1 - len(modifiers)]\n flags_lut = {'i': re.I, 's': re.S, 'm': re.M, 'u': re.U}\n flags = re.U\n\n for i in modifiers:\n if i in flags_lut:\n flags |= flags_lut[i]\n\n flags |= additional_flags\n return re.compile(newpattern, flags)\n except Exception as e:\n raise type(e)(str(e) + \"\\nFailed pattern: %s, %s\" % (pattern, newpattern)) \\\n .with_traceback(sys.exc_info()[2])","title":""},{"docid":"f1612c4925ca8887d11f9b90513d286c","score":"0.48177585","text":"def nth_repl(s, sub, repl, nth):\n find = s.find(sub)\n # if find is not p1 we have found at least one match for the substring\n i = find != -1\n # loop util we find the nth or we find no match\n while find != -1 and i != nth:\n # find + 1 means we start at the last match start index + 1\n find = s.find(sub, find + 1)\n i += 1\n # if i is equal to nth we found nth matches so replace\n if i == nth:\n return s[:find]+repl+s[find + len(sub):]\n return s","title":""},{"docid":"6bbe3889ec0e5ff85302ce4d907f84a8","score":"0.48167387","text":"def copy_replace(src, dst, pattern=None, replace_value=None):\n file1 = open(src, 'r') if isinstance(src, str) else src\n file2 = open(dst, 'w') if isinstance(dst, str) else dst\n pattern = (\n [pattern] if isinstance(pattern, str)\n else pattern\n )\n replace_value = (\n [replace_value] if isinstance(replace_value, str)\n else replace_value\n )\n if replace_value and pattern:\n if len(replace_value) != len(pattern):\n raise Exception(\"Invalid parameters: pattern and replace_value\"\n \" have different sizes.\")\n rules = [\n (re.compile(regex, re.IGNORECASE), value)\n for regex, value in zip(pattern, replace_value)\n ]\n else:\n rules = []\n for line in file1:\n if rules:\n for rule in rules:\n line = re.sub(rule[0], rule[1], line)\n file2.write(line)\n if isinstance(src, str):\n file1.close()\n if isinstance(dst, str):\n file2.close()","title":""},{"docid":"d13cf393775558f61af4a4060f68f59c","score":"0.481368","text":"def substitute(self,command,callsign):\n if command.find(' *')>0:\n # placeholder not at the beginning\n command.replace('*',callsign.lower())\n elif command.find('*')>0:\n # placeholder at the beginning\n command.replace('*',callsign)\n else:\n # no placeholder, prepend callsign\n command = callsign + '; ' + command\n return command","title":""},{"docid":"4e3b1f3e4e7036edcadb41c14581bc2f","score":"0.48039755","text":"def transformPattern(self, pattern):\n raise NotImplementedError(\"Should have implemented this\")","title":""}],"string":"[\n {\n \"docid\": \"e224a45e914a1459828b24848b832fbe\",\n \"score\": \"0.65532935\",\n \"text\": \"def sub(self, pattern: str, repl: Union[str, callable], string: str, strict: bool = True, case_sensitive: bool = False) -> str:\\n if case_sensitive:\\n result = re.sub(pattern, repl, string)\\n else:\\n result = re.sub(pattern, repl, string, flags=re.IGNORECASE)\\n if result == string: # No substitution happened!\\n self._unexpected_behavior(\\\"sub\\\", pattern, \\\"did not yield any substitutions\\\", string, strict)\\n return result # Returns only if sub happened or non strict behavior\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4e8e907314ef0f2c22ab45f6a9aa1ead\",\n \"score\": \"0.64997524\",\n \"text\": \"def replacePattern( pattern, str ):\\r\\n\\t\\r\\n\\t# Do the thing~\\r\\n\\ttry:\\r\\n\\t\\treturn str.replace(pattern[0],pattern[1])\\r\\n\\texcept:\\r\\n\\t\\tprint(\\\"Error(replacePattern): Invalid transform syntax on pattern,\\\",pattern[0],\\\"! Skipping...\\\")\\r\\n\\t\\treturn str\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8e5b1f2fe62bdfa29f306874ac2fb011\",\n \"score\": \"0.6368721\",\n \"text\": \"def __preg_replace_str(pat, rep, subject):\\n reg = __preg_setup(pat)\\n # function call\\n if callable(rep):\\n def __callback(match):\\n match_list = list(match.groups())\\n match_list.insert(0, subject)\\n match_list = tuple(match_list)\\n o = rep(match_list)\\n return o\\n return reg.sub(__callback, subject)\\n # string\\n else:\\n return reg.sub(rep, subject)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"54055af0b96e09ef37f942309440a4a4\",\n \"score\": \"0.63533336\",\n \"text\": \"def re_sub(pattern, repl, string):\\n groups = []\\n result = re.sub(pattern, lambda m: re_collect_groups(m, groups, repl), string)\\n return result, groups\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c485b5025d7e144d120a118135a08431\",\n \"score\": \"0.6350744\",\n \"text\": \"def worker(string, pattern, replacement, f):\\n matches = []\\n for i in range(pattern.__len__()):\\n matches.extend(gregexpr(pattern[i], string, i, f))\\n matches.sort(key=itemgetter(2), reverse=True)\\n for i in range(matches.__len__()-1, -1, -1):\\n if any([filter_matches(matches[i], m) for m in matches[:i]]):\\n matches.pop(i)\\n matches.sort(key=itemgetter(1))\\n for i in range(matches.__len__()-1, -1, -1):\\n s = matches[i][1]\\n e = matches[i][3]\\n p = pattern[matches[i][0]]\\n r = replacement[matches[i][0]]\\n pre = string[:s]\\n r0 = re.sub(p, r, string[s:e], flags=f)\\n end = string[e:]\\n string = pre+r0+end\\n return string\",\n \"title\": \"\"\n },\n {\n \"docid\": \"079b657a060e2f1b8a6990f6340e2d01\",\n \"score\": \"0.61693805\",\n \"text\": \"def regex_replacer(pattern, repl):\\n return lambda x: sub(pattern, repl, x)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ac2ea56ed410bc70b3e467eedf93d37c\",\n \"score\": \"0.611818\",\n \"text\": \"def mgsub(string, pattern, replacement, flags=0):\\n\\n assert isinstance(pattern, list), \\\"Input pattern must be a list\\\"\\n assert ((isinstance(replacement, list) & (replacement.__len__() == pattern.__len__())) |\\n isinstance(replacement, str)), \\\"Input replacement must be a list of equal length to pattern or a string\\\"\\n\\n if isinstance(replacement, str):\\n replacement = [replacement for p in pattern]\\n\\n if not isinstance(string, str) and isinstance(string, collections.Sequence):\\n output = [worker(s, pattern, replacement, flags) for s in string]\\n else:\\n output = worker(string, pattern, replacement, flags)\\n return output\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1f19eebf28660f4a375263912b9d1aad\",\n \"score\": \"0.60709614\",\n \"text\": \"def replace_patterns(string, patterns):\\n for old, new in patterns:\\n string = string.replace(old, new)\\n return string\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d87f1611d7ec81d74916c5bc22b7f856\",\n \"score\": \"0.6036524\",\n \"text\": \"def sub(pattern,replacement,*,count=0,flags=0):\\n regex = re.compile(pattern,flags)\\n def _sub(input):\\n yield from (regex.sub(repl=replacement,string=line,count=count) for line in input)\\n return _sub\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1ef2091d3319c9ea1f8815732a5d2143\",\n \"score\": \"0.6011735\",\n \"text\": \"def replace(pattern, replacement, value):\\n return re.sub(pattern, replacement, value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b6babf01def905307b7e6472748bc9c4\",\n \"score\": \"0.5923076\",\n \"text\": \"def replace(s, pattern, replacement):\\n # the replacement string may contain invalid backreferences (like \\\\1 or \\\\g)\\n # which will cause python's regex to blow up. Since this should emulate\\n # the jam version exactly and the jam version didn't support\\n # backreferences, this version shouldn't either. re.sub\\n # allows replacement to be a callable; this is being used\\n # to simply return the replacement string and avoid the hassle\\n # of worrying about backreferences within the string.\\n def _replacement(matchobj):\\n return replacement\\n return re.sub(pattern, _replacement, s)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6e80f6038cbf2f1f2303b671015b43c7\",\n \"score\": \"0.58642614\",\n \"text\": \"def match(pattern, string):\\n return re.match(pattern, string)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6e9e69048806c5de93bc1a8bb52a17ea\",\n \"score\": \"0.5853369\",\n \"text\": \"def substitution(master_string, replace_string, sub_string):\\n length = len(replace_string)\\n escape_character = \\\"+\\\"\\n for index in xrange(len(master_string) - length + 1):\\n window = master_string[index: length + index]\\n if window == replace_string:\\n if master_string[:index].count(escape_character) % 2 == 1:\\n # means the replace_string is in the middle of a already\\n # replaced string\\n continue\\n new_string = master_string[:index] + escape_character + \\\\\\n sub_string + escape_character + \\\\\\n master_string[index + length:]\\n return new_string\\n else:\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"953cfbca525341a9e52621b4e8b55c88\",\n \"score\": \"0.585088\",\n \"text\": \"def replacePatterns( patterns, str ):\\r\\n\\t\\r\\n\\t# Make a copy of the string so we don't get weird behavior~\\r\\n\\ts = str\\r\\n\\t\\r\\n\\t# For each pattern,\\r\\n\\tfor pattern in patterns:\\r\\n\\t\\ts = replacePattern(pattern,s)\\t# Replace the pattern\\r\\n\\treturn s\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f3fc268e872fdb1594c804010a684a3a\",\n \"score\": \"0.5785354\",\n \"text\": \"def update_word_pattern(word, pattern, letter):\\r\\n for i in range(len(word)):\\r\\n if word[i] == letter:\\r\\n pattern = pattern[:i] + letter + pattern[i + 1:]\\r\\n return pattern\",\n \"title\": \"\"\n },\n {\n \"docid\": \"801a6ccdf4b3be3e87a685727dd17546\",\n \"score\": \"0.5764851\",\n \"text\": \"def __str_replace_str(pat, rep, subject):\\n return subject.replace(pat, rep)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3424580fb0bc73f4bc07ee3e0e7b39da\",\n \"score\": \"0.57075423\",\n \"text\": \"def apply_and_get_result(self, string):\\n if self.is_multiline:\\n compiled_pattern = re.compile(self.pattern, re.MULTILINE)\\n else:\\n compiled_pattern = re.compile(self.pattern)\\n\\n result = re.sub(compiled_pattern, self.repl, string)\\n return result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e80b0687a31ef2ead799c97a9a359d58\",\n \"score\": \"0.57067484\",\n \"text\": \"def update_word_pattern(word,pattern,letter):\\n new_pattern = list(pattern)\\n for i in range(len(word)):\\n if word[i] == letter:\\n new_pattern[i] = letter\\n return ''.join(new_pattern)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5ea8315953fc05cb799dc15312beca51\",\n \"score\": \"0.56539804\",\n \"text\": \"def update_word_pattern(word,pattern,letter):\\n\\n pattern=list(pattern) # convert the pattern from a string to list\\n\\n # checks if the the secret word contain the letter\\n for j in range(len(word)):\\n if letter==word[j]:\\n pattern[j]=letter # updates the appropiate place in the pattern\\n\\n pattern=\\\"\\\".join(pattern)\\n\\n return pattern\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8fd71418c1c1e58945cf6c5b57cfe7ee\",\n \"score\": \"0.5649985\",\n \"text\": \"def _substitute(self, str):\\r\\n\\r\\n return self._regex.sub(\\r\\n lambda mo: self._reflections[mo.string[mo.start() : mo.end()]], str.lower()\\r\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"69ad2964f41789690a6b699425d9826d\",\n \"score\": \"0.5643551\",\n \"text\": \"def replace_pattern(x, pattern_b, replacement):\\n\\n try:\\n res = x.strip().replace(pattern_b,replacement)\\n except:\\n res = x\\n # insert logging\\n return res\",\n \"title\": \"\"\n },\n {\n \"docid\": \"88748eb2bc90038658882ab3ebc926aa\",\n \"score\": \"0.56325567\",\n \"text\": \"def lsub(self, directory,pattern):\\n\\t\\tpass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c5e87494bf848cb94c4b29f650566e79\",\n \"score\": \"0.5608165\",\n \"text\": \"def sub(\\n self, pattern: Union[bytes, str_scalars], repl: Union[bytes, str_scalars], count: int = 0\\n ) -> Strings:\\n if isinstance(repl, bytes):\\n repl = repl.decode()\\n return self._get_matcher(pattern).sub(repl, count)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8e1bf2f7f80d79d450ed5eba39fa0104\",\n \"score\": \"0.5583376\",\n \"text\": \"def sub_re(self, callback, msg):\\n self.sub(callback, re.compile(msg))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8c59dac29c863aaf6a1e1be819df2b2c\",\n \"score\": \"0.557107\",\n \"text\": \"def replace(self, pattern, repl, *args, **kwargs):\\n c = MessageMixin.replace(self, pattern, repl, *args, **kwargs)\\n self.path, pc = utils.safe_subn(\\n pattern, repl, self.path, *args, **kwargs\\n )\\n c += pc\\n return c\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cd6cf86e775803c0b243e67c1759a6d5\",\n \"score\": \"0.5551831\",\n \"text\": \"def _substitute(self, str):\\n\\n return self._regex.sub(\\n lambda mo: self._reflections[mo.string[mo.start() : mo.end()]], str.lower()\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"90e4557340c33caefa614d3d9fbf3169\",\n \"score\": \"0.5439628\",\n \"text\": \"def test_pattern_exists_in_string(self):\\n self.assertTrue(self.pattern1 in self.string1)\\n self.assertEqual(2, search(self.pattern1, self.string1))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5148954c882450b26ed80e12cabd6fbe\",\n \"score\": \"0.54316485\",\n \"text\": \"def preg_replace(pat, rep, subject):\\n out = subject\\n if isinstance(pat, list):\\n repIsStr = isinstance(rep, list)\\n for i in pat:\\n if repIsStr:\\n repStr = rep\\n else:\\n repStr = rep[i]\\n out = __preg_replace_str(pat[i], repStr, out)\\n else:\\n out = __preg_replace_str(pat, rep, subject)\\n return out\",\n \"title\": \"\"\n },\n {\n \"docid\": \"19209707837832cf55fec527bb92eca2\",\n \"score\": \"0.54167587\",\n \"text\": \"def _pattern(self, pattern, that, topic):\\n\\n if len(pattern) == 0:\\n return None\\n # Mutilate the input. Remove all punctuation and convert the\\n # text to all caps.\\n input = string.upper(pattern)\\n input = re.sub(self._brain._puncStripRE, \\\" \\\", input)\\n if that.strip() == u\\\"\\\": that = u\\\"ULTRABOGUSDUMMYTHAT\\\" # 'that' must never be empty\\n thatInput = string.upper(that)\\n thatInput = re.sub(self._brain._puncStripRE, \\\" \\\", thatInput)\\n thatInput = re.sub(self._brain._whitespaceRE, \\\" \\\", thatInput)\\n if topic.strip() == u\\\"\\\": topic = u\\\"ULTRABOGUSDUMMYTOPIC\\\" # 'topic' must never be empty\\n topicInput = string.upper(topic)\\n topicInput = re.sub(self._brain._puncStripRE, \\\" \\\", topicInput)\\n \\n\\n # Pass the input off to the recursive call\\n patMatch, template = self._brain._match(input.split(), thatInput.split(), topicInput.split(), self._brain._root)\\n\\n return patMatch, template\",\n \"title\": \"\"\n },\n {\n \"docid\": \"475358eea83883f9a01f694fadb79842\",\n \"score\": \"0.5416043\",\n \"text\": \"def regex_replace(regex, replacement, input):\\n\\treturn get_regex(regex).sub(replacement, input)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2391f2b16cc4985f21d010ffd4d168a2\",\n \"score\": \"0.5412871\",\n \"text\": \"def find(string, pattern):\\n # implement find_iterative and find_recursive\\n # assert isinstance(string, str)\\n return find_iterative(string, pattern)\\n # return find_recursive(string, pattern)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c17ec25f1ee5f4fee7c623b4f25e0047\",\n \"score\": \"0.53997946\",\n \"text\": \"def test_pattern_exists_in_string_and_returns_first_occurrence(self):\\n self.assertTrue(self.pattern2 in self.string2)\\n self.assertTrue(self.string2.count(self.pattern2) > 1)\\n self.assertEqual(3, search(self.pattern2, self.string2))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2ec6bee06bba45068a8db99bd7f0ba1d\",\n \"score\": \"0.53962237\",\n \"text\": \"def _sub(self, reg, result):\\n self._text = re.sub(reg, result, self._text)\\n return self\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c598f8fb80df0df95d821614b48d601b\",\n \"score\": \"0.5372047\",\n \"text\": \"def search(pattern, s):\\n if pattern not in _regexp_compile_cache:\\n _regexp_compile_cache[pattern] = sre_compile.compile(pattern)\\n return _regexp_compile_cache[pattern].search(s)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"01e0257a6af1edc45edfbf89f12292c7\",\n \"score\": \"0.53491944\",\n \"text\": \"def make_replacement(\\n self, pattern: str, replacement: str, regex: bool = True\\n ) -> None:\\n if regex:\\n self.body = re.sub(pattern, replacement, self.body)\\n else:\\n self.body = self.body.replace(pattern, replacement)\\n for part in self.parts:\\n part.make_replacement(pattern, replacement, regex=regex)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a27fd2ce055258eac810d4c73202901d\",\n \"score\": \"0.5329081\",\n \"text\": \"def regex_replace(s, find, replace):\\n return re.sub(find, replace, s)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"149a7f5cc43bbe1b0029e91ad8660c47\",\n \"score\": \"0.53118736\",\n \"text\": \"def match_tokenized_regex_pattern(pattern, string):\\n\\tif not pattern and not string: # if reach the end of both pattern and string\\n\\t\\treturn True\\n\\tif not pattern or not string: # if reach the end of either pattern and string\\n\\t\\treturn False\\n\\n\\tp = pattern[0]\\n\\tc = string[0]\\n\\n\\t# removes cases with (letter-symbol vs. letter) and (non-matching single letters)\\n\\tif p == c or p == '.':\\n\\t\\treturn match_tokenized_regex_pattern(pattern[1:], string[1:])\\n\\n\\t# X* --> X can appear 0 times, once, or more (3 cases)\\n\\telif len(pattern) > 1:\\n\\t\\tif pattern[0] == c:\\n\\t\\t\\tis_match = match_tokenized_regex_pattern(pattern, string[1:]) # appear >= 1 times\\n\\t\\t\\tif is_match:\\n\\t\\t\\t\\treturn True\\n\\t\\treturn match_tokenized_regex_pattern(pattern[1:], string) # appear 0 times in string\\n\\n\\t# non-matching single letters\\n\\telse:\\n\\t\\treturn False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"131b0595bca047d5615610417ed1ea8e\",\n \"score\": \"0.53036594\",\n \"text\": \"def _group(s, groups):\\n for pattern, replacement in groups:\\n if pattern.match(s):\\n return replacement\\n return s\",\n \"title\": \"\"\n },\n {\n \"docid\": \"45ca4a249418bea4c1a3520fe7d089a7\",\n \"score\": \"0.5294655\",\n \"text\": \"def __call__(self, value, pattern, replacement, data=None, engine=None):\\n return sub(pattern, replacement, value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6816948b2976bbf9428f34c2de76aa48\",\n \"score\": \"0.5293176\",\n \"text\": \"def match(pattern, s):\\n # The regexp compilation caching is inlined in both Match and Search for\\n # performance reasons; factoring it out into a separate function turns out\\n # to be noticeably expensive.\\n if pattern not in _regexp_compile_cache:\\n _regexp_compile_cache[pattern] = sre_compile.compile(pattern)\\n return _regexp_compile_cache[pattern].match(s)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"405978c54777ac5b96280e88315f4a15\",\n \"score\": \"0.52822506\",\n \"text\": \"def replace(self, pattern, content):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"32ae4555466b2f80bb2c191daeb6f875\",\n \"score\": \"0.52768046\",\n \"text\": \"def replace(\\n self,\\n pattern: StringValue,\\n replacement: StringValue,\\n ) -> StringValue:\\n return ops.StringReplace(self, pattern, replacement).to_expr()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8372720021e963f8558a77960bdd1568\",\n \"score\": \"0.527449\",\n \"text\": \"def sub(self, text):\\n if self._regexIsDirty:\\n self._update_regex()\\n return self._regex.sub(self, text)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6129eecad220c679072d1adcdba09ddb\",\n \"score\": \"0.52710116\",\n \"text\": \"def rfind_str(text, sub, start=None, end=None):\\n assert isinstance(text,str), '%s is not a string' % text\\n return text.rfind(sub,start,end)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d50782465a645681d1d5c092b9f0f291\",\n \"score\": \"0.52637935\",\n \"text\": \"def sub (cls, regex_, replace, query):\\n\\n cregex = cls.regex_cache.setdefault (\\n regex_, regex.compile (regex_, regex.UNICODE | regex.VERSION1))\\n return cregex.sub (replace, query)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"419dd68d3f63e92821b6384617b21de8\",\n \"score\": \"0.5258351\",\n \"text\": \"def findfirst(pattern, string, flags=0):\\n string_list = re.findall(pattern, string, flags)\\n if string_list:\\n result = string_list[0]\\n else:\\n result = \\\"\\\"\\n return result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"75d906ffab3bcb539473a45f01812a29\",\n \"score\": \"0.5249003\",\n \"text\": \"def make_one_sub(value, sub_list):\\n for s in sub_list:\\n formatted, n = s['regex'].subn(s['repl'], value, count = 1)\\n if n > 0:\\n value = formatted\\n break\\n return value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5bdffd5466b58d18a78b847bab12f217\",\n \"score\": \"0.5246227\",\n \"text\": \"def replace( self, pattern, replacement ) :\\n if self._map == None : self._map = {}\\n self._map[pattern] = replacement\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2bee3285b8ddd9d123d27c819b34a4ed\",\n \"score\": \"0.5211044\",\n \"text\": \"def find_str(text, sub, start=None, end=None):\\n assert isinstance(text,str), '%s is not a string' % text\\n return text.find(sub,start,end)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"61169a7f5e595c7af9e3b1f7c9eaa031\",\n \"score\": \"0.5208249\",\n \"text\": \"def _search_regex(pattern, string, group=None):\\n\\t\\tif isinstance(pattern, (str, compat_str, type(re.compile('')))):\\n\\t\\t\\tmobj = re.search(pattern, string, 0)\\n\\t\\telse:\\n\\t\\t\\tfor p in pattern:\\n\\t\\t\\t\\tmobj = re.search(p, string, 0)\\n\\t\\t\\t\\tif mobj:\\n\\t\\t\\t\\t\\tbreak\\n\\t\\tif mobj:\\n\\t\\t\\tif group is None:\\n\\t\\t\\t\\t# return the first matching group\\n\\t\\t\\t\\treturn next(g for g in mobj.groups() if g is not None)\\n\\t\\t\\telse:\\n\\t\\t\\t\\treturn mobj.group(group)\\n\\t\\telse:\\n\\t\\t\\tprint('[YouTubeVideoUrl] unable extract pattern from string!')\\n\\t\\t\\treturn ''\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ceb06e77d428b69be4e1c30f6da9abaa\",\n \"score\": \"0.5192851\",\n \"text\": \"def replace_line(s, start, replace):\\n lines = s.split('\\\\n')\\n found = False\\n for i in range(len(lines)):\\n if lines[i].startswith(start):\\n lines[i] = replace\\n found = True\\n break\\n if not found:\\n raise ValueError('could not match string %s' % start)\\n return '\\\\n'.join(lines)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9e8223743c7212570623c42f4bd4fe17\",\n \"score\": \"0.5191779\",\n \"text\": \"def re_replace(\\n self,\\n pattern: str | StringValue,\\n replacement: str | StringValue,\\n ) -> StringValue:\\n return ops.RegexReplace(self, pattern, replacement).to_expr()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2a412fd90e17fb182f6ca3fbf6eebb78\",\n \"score\": \"0.5191737\",\n \"text\": \"def addPattern(self, text):\\n def ms(s):\\n if options.ignore_case:\\n return s.lower()\\n return s\\n\\n flags = 0\\n if options.ignore_case:\\n flags = re.I\\n t = \\\"s\\\"\\n isRegExp = False\\n if text.startswith(\\\"d:\\\"):\\n t = \\\"d\\\"\\n text = text[2:]\\n if text.startswith(\\\"s:\\\"):\\n text = text[2:]\\n if text.startswith(\\\"~\\\"):\\n text = text[1:]\\n isRegExp = True\\n if isRegExp:\\n try:\\n p = re.compile(text, flags)\\n except re.error as exc:\\n sys.stderr.write(\\\"%r is not a valid regular expression\\\\n\\\" % text)\\n sys.stderr.write(\\\" %s\\\\n\\\" % exc)\\n sys.exit(1)\\n if t == \\\"d\\\":\\n self.descriptionPatterns.append(p)\\n else:\\n self.summaryPatterns.append(p)\\n else:\\n if t == \\\"d\\\":\\n self.descriptionText.append(ms(text))\\n else:\\n self.summaryText.append(ms(text))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fe657592f8b634bacfdb5208ac2c2cd4\",\n \"score\": \"0.5184157\",\n \"text\": \"def genPattern(self,patternStr,ignoreCase=True):\\n\\t\\tif ignoreCase:\\n\\t\\t\\treturn re.compile(patternStr,re.IGNORECASE)\\n\\t\\telse:\\n\\t\\t\\treturn re.compile(patternStr)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"12a2468e6e0f4532bb6c5050eb3120e3\",\n \"score\": \"0.51750845\",\n \"text\": \"def remove(sub, strng):\\n if sub not in strng:\\n return strng\\n else:\\n index = strng.find(sub)\\n result = ''\\n for i in range(index):\\n result += strng[i]\\n for i in range(index+len(sub), len(strng)):\\n result += strng[i]\\n return result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7167b5980a90c5a3ddd18f814fcfcdd3\",\n \"score\": \"0.5170874\",\n \"text\": \"def parse(expression, pattern, replacer):\\n regex = [p[\\\"regexp\\\"] for p in Airbot.patterns if p[\\\"name\\\"] == pattern][0]\\n return re.sub(regex, replacer, expression)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"24eda24a2728378fb019effe84dcbfbf\",\n \"score\": \"0.51561236\",\n \"text\": \"def regexp_replace(\\n string: \\\"ColumnOrName\\\", pattern: Union[str, Column], replacement: Union[str, Column]\\n) -> Column:\\n if isinstance(pattern, str):\\n pattern_col = _create_column_from_literal(pattern)\\n else:\\n pattern_col = _to_java_column(pattern)\\n if isinstance(replacement, str):\\n replacement_col = _create_column_from_literal(replacement)\\n else:\\n replacement_col = _to_java_column(replacement)\\n return _invoke_function(\\\"regexp_replace\\\", _to_java_column(string), pattern_col, replacement_col)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d6b82b230389afbd8225eaa562fef108\",\n \"score\": \"0.51526624\",\n \"text\": \"def make_all_subs(value, sub_list):\\n for s in sub_list:\\n value = s['regex'].sub(s['repl'], value, count = 1)\\n return value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0ec4f45bfc2b348fc4314ad9eb4f903f\",\n \"score\": \"0.514604\",\n \"text\": \"def regex_replace(string, expr, repl):\\n r = re.compile(raw(expr))\\n return r.sub(repl, string)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4bae5403d87001cbc1a63dfc50496790\",\n \"score\": \"0.51357526\",\n \"text\": \"def replace_pattern(\\n df: pd.DataFrame,\\n column: str,\\n *,\\n pat: str,\\n repl: str,\\n new_column: Optional[str] = None,\\n case: bool = True,\\n regex: bool = True,\\n) -> pd.DataFrame:\\n new_column = new_column or column\\n df.loc[:, new_column] = df[column].str.replace(pat, repl, case=case, regex=regex)\\n return df\",\n \"title\": \"\"\n },\n {\n \"docid\": \"753503338cf964a7b9a2760b6771b28f\",\n \"score\": \"0.5132225\",\n \"text\": \"def set_name_from_pattern_xref(base_addr, end, name, pattern):\\r\\n pattern_offset = ida_search.find_binary(\\r\\n base_addr, end, pattern, 16, ida_search.SEARCH_DOWN\\r\\n )\\r\\n if pattern_offset == ida_idaapi.BADADDR or pattern_offset is None:\\r\\n return ida_idaapi.BADADDR\\r\\n\\r\\n xref = list(idautils.XrefsTo(pattern_offset))\\r\\n if len(xref) == 0:\\r\\n return ida_idaapi.BADADDR\\r\\n\\r\\n function = idaapi.get_func(xref[0].frm)\\r\\n if function is None:\\r\\n return ida_idaapi.BADADDR\\r\\n idc.set_name(function.start_ea, name, idc.SN_CHECK)\\r\\n print(f\\\"[+] {name} : {hex(function.start_ea)}\\\")\\r\\n return function.start_ea\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7737a91fd8d061bd93c4dd0cabb7ae85\",\n \"score\": \"0.5100343\",\n \"text\": \"def regex_pattern(stem_str):\\n str_list = stem_str.split('-')\\n # add word boundary\\n if len(str_list) == 2:\\n pos = 2 - str_list.index('')*2\\n pos2 = 3 - str_list.index('')*3\\n str_list.insert(pos, '\\\\\\\\b')\\n str_list.insert(pos2, '.*')\\n # replace '-' with '.*'\\n pat_str = ''.join([i if len(i) > 0 else '.*' for i in str_list])\\n return pat_str\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ac00ec9da264d03817acf850279af23a\",\n \"score\": \"0.5071816\",\n \"text\": \"def sub_cdn(self, s, m):\\r\\n res_fn = m.group(self.file_index)\\r\\n for sub in self.subs:\\r\\n pat = sub[\\\"pattern\\\"]\\r\\n rep = sub[\\\"replacement\\\"]\\r\\n m2 = re.search(pat, res_fn)\\r\\n if m2:\\r\\n s1 = s[:m.start(self.file_index)] + rep + s[m.end(self.file_index):]\\r\\n return s1\\r\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8d0a2c1561d25b5144a81e4d4db9e227\",\n \"score\": \"0.5058605\",\n \"text\": \"def replaceStrs(s, *args):\\n if args == (): return s\\n mapping = dict([(frm, to) for frm, to in args])\\n return re.sub(\\\"|\\\".join(map(re.escape, mapping.keys())),\\n lambda match:mapping[match.group(0)], s)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a63a679edf1e3b6acca19cc5d27d47b8\",\n \"score\": \"0.5044197\",\n \"text\": \"def find_replace_regex(chunk, out, find, sub=\\\"\\\"):\\n util.write_annotation(out, ((key, re.sub(find, sub, val)) for (key, val) in util.read_annotation_iteritems(chunk)))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9ed960bf1ec5ca795855a2c463b33e55\",\n \"score\": \"0.5035251\",\n \"text\": \"def search(pattern, text, flags=0):\\r\\n\\tmatch_obj = re.search(pattern, text, flags)\\r\\n\\tdump_results(match_obj, text)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f69ece641595895143a6e65f4ce110c7\",\n \"score\": \"0.50253934\",\n \"text\": \"def match(pattern,word):\\n if not pattern or pattern == '*':\\n # No pattern/wildcard, matches everything\\n return True\\n # Only simple patterns considered for now\\n if pattern.endswith('*'):\\n # Match the start\\n return word.startswith(pattern[:-1])\\n else:\\n # Match the whole word exactly\\n return (word == pattern)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1f1d0bfab84c4d59b7c6302586f0ab24\",\n \"score\": \"0.50040156\",\n \"text\": \"def _matches(self, pattern: str, string: str) -> bool:\\n regex_pattern = '^' + pattern.replace('*', '.*') + '$'\\n return bool(re.match(regex_pattern, string))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"14fd9e45f65f1aae8512785edab38951\",\n \"score\": \"0.49961507\",\n \"text\": \"def case_insensitive_replace(haystack: str, needle: str, replacement: str) -> str:\\n regex = re.compile(re.escape(needle), re.IGNORECASE)\\n return regex.sub(replacement, haystack)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6078d34c11aa9f1096ba5219677497b9\",\n \"score\": \"0.4988578\",\n \"text\": \"def strlookup(pattern, space):\\n return fnmatch.filter(space, pattern)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d9e5964f7cda67bdebb29d995ba22ce1\",\n \"score\": \"0.49839634\",\n \"text\": \"def kmp(string, pattern):\\n\\n # either string or pattern is empty, return -1\\n if len(string) * len(pattern) == 0:\\n return -1\\n\\n # build table of shifts\\n pattern = list(pattern)\\n lp = len(pattern)\\n shifts = [1] * (lp + 1)\\n shift = 1\\n for p in range(lp):\\n while shift <= p and pattern[p] != pattern[p - shift]:\\n shift += shifts[p - shift]\\n shifts[p + 1] = shift\\n\\n # search\\n start_pos = 0\\n match_len = 0\\n for c in string:\\n while match_len == lp or \\\\\\n match_len >= 0 and pattern[match_len] != c:\\n start_pos += shifts[match_len]\\n match_len -= shifts[match_len]\\n\\n match_len += 1\\n\\n if match_len == lp:\\n return start_pos\\n\\n return -1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"70c50827d50fb849904fbd45806d753c\",\n \"score\": \"0.49817824\",\n \"text\": \"def pattern(word, pat):\\n matches = {}\\n if len(word) < len(pat):\\n return False\\n for (w,p) in zip(word, pat):\\n if p not in matches:\\n matches[p] = w\\n elif matches[p] != w:\\n return pattern(word[1:], pat)\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cef40f328bd2c914cd5377895fe02ac7\",\n \"score\": \"0.4973586\",\n \"text\": \"def replace_wildcard_with_time(aa,string1):\\n # Set wild card string\\n if aa.outfile_frequency=='year':\\n x2=str(aa.year)\\n elif aa.outfile_frequency=='month':\\n x2=str(aa.year)+str(aa.month).zfill(2)\\n else:\\n raise ToDoError('Need to code up for different outfile_frequency')\\n # Replace wild card characters\\n string2=string1.replace(aa.wildcard,x2)\\n\\n return string2\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a44739ef656aabd86cb9d4d050030768\",\n \"score\": \"0.49441954\",\n \"text\": \"def index_str(text, sub, start=None, end=None):\\n assert isinstance(text,str), '%s is not a string' % text\\n return text.index(sub,start,end)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6dd5b1ef8f5df62b3e3a077acbd1a7db\",\n \"score\": \"0.493214\",\n \"text\": \"def is_sublist_of(pattern, text):\\n\\n if len(pattern) > len(text):\\n return False\\n\\n if not pattern:\\n return True\\n\\n for possible_start in ifindall(pattern[0], text):\\n if text[possible_start : possible_start+len(pattern)] == pattern:\\n return True\\n\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ac8e594ba0b916545501499a10f85757\",\n \"score\": \"0.49176946\",\n \"text\": \"def __init__(self, pattern):\\n self.idx = 0\\n self.prefix, replace, self.suffix = re.split(\\\"(#+)\\\", pattern)\\n self.sublen = len(replace)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9be0c1e60a1843a85548877ef24ff01d\",\n \"score\": \"0.4915615\",\n \"text\": \"def replace(self, pattern, repl, *args, **kwargs):\\n c = self.request.replace(pattern, repl, *args, **kwargs)\\n if self.response:\\n c += self.response.replace(pattern, repl, *args, **kwargs)\\n return c\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7470cbf0d604dcc72e67e4ebdfb06de9\",\n \"score\": \"0.49127653\",\n \"text\": \"def similar_to_pattern(word,pattern):\\r\\n flag = True\\r\\n for i in range(len(word)):\\r\\n if pattern[i] == '_':\\r\\n continue\\r\\n elif word[i] != pattern[i]:\\r\\n flag = False\\r\\n return flag\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1a916db5fd339a67adefb0a4fbe9ba4f\",\n \"score\": \"0.49120873\",\n \"text\": \"def test_replace(self):\\n\\n regex = \\\"th\\\"\\n expected = \\\"Hello, htis is Fun Ilrys. I just wanted to know how htings goes around hte tests.\\\" # pylint: disable=line-too-long\\n actual = Regex(regex).replace_match(self.data, \\\"ht\\\")\\n\\n self.assertEqual(expected, actual)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dfc257944cf1d6166c9f0f2fbbf3bbdf\",\n \"score\": \"0.4909576\",\n \"text\": \"def match(pattern, text):\\n if pattern == '':\\n return True\\n elif pattern == '$':\\n return (text == '')\\n elif len(pattern) > 1 and pattern[1] in '*?':\\n p, op, pat = pattern[0], pattern[1], pattern[2:]\\n if op == '*':\\n return match_star(p, pat, text)\\n elif op == '?':\\n if match1(p, text) and match(pat, text[1:]):\\n return True\\n else:\\n return match(pat, text)\\n else:\\n return (match1(pattern[0], text) and\\n match( pattern[1:],text[1:])) # fill in this line\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3d377255580b54a0c740f2659da53268\",\n \"score\": \"0.49065128\",\n \"text\": \"def rindex_str(text, sub, start=None, end=None):\\n assert isinstance(text,str), '%s is not a string' % text\\n return text.rindex(sub,start,end)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b6997956d36c0ca6461c6cabbb12ae95\",\n \"score\": \"0.49021098\",\n \"text\": \"def substitute_chars(self, column, pattern, val_sub,\\n val_exception=np.nan, val_none=np.nan,\\n inplace=True, return_series=False,\\n target_column=None):\\n series = self.df[column].copy().astype(str).apply(\\n lambda x: regex_sub_value(\\n val=x,\\n pattern=pattern,\\n val_sub=val_sub,\\n val_exception=val_exception,\\n val_none=val_none,\\n )\\n )\\n return inplace_return_series(self.df, column, series,\\n inplace, return_series, target_column)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f8a98be8f3e0db7b718392cfab9fef5d\",\n \"score\": \"0.48936597\",\n \"text\": \"def prefix_sub (match_object):\\n s = match_object.group (0)\\n return cls.prefix_to_prefix.get (s, s)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f57227a1432322ff07f027d4a6c17e78\",\n \"score\": \"0.48791716\",\n \"text\": \"def apply_pattern(view, pattern, func):\\n result = parameterNameRegex.sub(lambda m: func(getparameters_byname(view, m.group(1)),\\n m.group(1)),\\n pattern)\\n result = parameterGuidRegex.sub(lambda m: func(getparameter(view, m.group()),\\n m.group()),\\n result)\\n result = parameterBipRegex.sub(lambda m: func(getparameter(view, \\\"BuiltInParameter.\\\" + m.group(1)),\\n m.group(1)),\\n result)\\n return result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"38bb9fb5b3ce6bdf98661652978f5736\",\n \"score\": \"0.48766243\",\n \"text\": \"def matchPat(pre,str):\\n if pre=='':\\n return True\\n pre=duplicateAsteriskRemover(pre)\\n if len(pre)>len(str) and pre[0]!='*':\\n return False\\n elif len(pre) == 1:\\n if pre[0]==str[0] or pre[0]=='*':\\n return True\\n else:\\n return False\\n elif pre[0]=='*':\\n a=1\\n c=0\\n while c<len(str):\\n if pre[a]==str[c]:\\n return matchPat(pre[a:],str[c:])\\n else:\\n c+=1\\n if pre[0]!=str[0]:\\n return False\\n else:\\n return matchPat(pre[1:],str[1:])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"729f5921190b2c2612d8932a3096adb0\",\n \"score\": \"0.48736763\",\n \"text\": \"def _glob_match(self, pattern, string):\\r\\n # regex flags Multi-line, Unicode, Locale\\r\\n return bool(re.match(fnmatch.translate(pattern), string,\\r\\n re.M | re.U | re.L))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"25ad35abc2841933328d7853d2ca02bb\",\n \"score\": \"0.4857707\",\n \"text\": \"def generateRegexFromPattern( pattern ):\\r\\n\\t\\r\\n\\treturn re.compile(pattern)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"47cb09b4813e5dfe57c4181928117855\",\n \"score\": \"0.4857365\",\n \"text\": \"def replace_identifiers(string):\\n return re.sub(string=string, **RE['identifiers'])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d93ef63dd421280b5a7f218d356a710c\",\n \"score\": \"0.4850763\",\n \"text\": \"def contains(text, pattern):\\n assert isinstance(text, str), 'text is not a string: {}'.format(text)\\n assert isinstance(pattern, str), 'pattern is not a string: {}'.format(text)\\n # TODO: Implement contains here (iteratively and/or recursively)\\n num = 0 #index to keep track of which letter in pattern you're comparing to you\\n if len(pattern) == 0:\\n return True \\n for letter in text:\\n #if they arent equal and you're part of the way into comapring to the pattern\\n if num>0 and letter != pattern[num]:\\n num = 0\\n # check if your current letter matches a letter in pattern\\n if letter == pattern[num]:\\n num+=1\\n #if you're finished with the pattern then finish ahead of time\\n if num > len(pattern)-1:\\n return True\\n \\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e09fcfc543e3aae86084548ae081e6c8\",\n \"score\": \"0.48504576\",\n \"text\": \"def match(word, pattern):\\n # if the pattern is empty, only match empty word\\n if len(pattern) == 0: return len(word) == 0\\n # if the word is empty, only match \\\"*\\\"\\n if len(word) == 0: return pattern == \\\"*\\\"\\n \\n # otherwise try to match first char in pattern\\n if pattern[0] == \\\"?\\\" or pattern[0] == word[0]:\\n # try to match pattern and word without first chars\\n return match(word[1:], pattern[1:])\\n elif pattern[0] == \\\"*\\\":\\n # skip chars and try to match with rest of pattern\\n for i in range(len(word)+1):\\n if match(word[i:], pattern[1:]):\\n return True\\n return False\\n else:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b7822c9b72166c429f17ed848a7d058a\",\n \"score\": \"0.4846589\",\n \"text\": \"def resolve(unresolved_pattern, pattern_dictionary, regex_pat=re.compile(\\\"\\\"\\\"%\\\\{(.+?)\\\\}\\\"\\\"\\\")):\\n #Get all referenced patterns into set\\n pattern_set = set(regex_pat.findall(unresolved_pattern))\\n #Return original pattern if it does not reference any other patterns\\n if not pattern_set:\\n return \\\"(?:\\\"+unresolved_pattern+\\\")\\\"\\n for unres_pat in pattern_set:\\n #If a pattern is known:\\n if unres_pat.split(\\\":\\\")[0] in pattern_dictionary.keys():\\n #Resolve it\\n unresolved_pattern = unresolved_pattern.replace(encaps(unres_pat), resolve(pattern_dictionary[unres_pat.split(\\\":\\\")[0]], pattern_dictionary))\\n return unresolved_pattern\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4ce31eca01966b34b22296f17c252384\",\n \"score\": \"0.48435923\",\n \"text\": \"def match(pattern='', priority=PRIORITY_LOW):\\n return Match(pattern, priority=priority).decorate\",\n \"title\": \"\"\n },\n {\n \"docid\": \"97eb9a2ccbad49e876d552d19ca9b833\",\n \"score\": \"0.48368943\",\n \"text\": \"def convertPattern(pattern, sign):\\n\\n # Check for include vs exclude patterns.\\n if pattern[:2] == \\\"+ \\\":\\n pattern = pattern[2:]\\n sign = \\\"+\\\"\\n elif pattern[:2] == \\\"- \\\":\\n pattern = pattern[2:]\\n sign = \\\"-\\\"\\n\\n # Express windows, mac patterns in unix patterns (rsync.py extension).\\n separator = os.path.normpath(\\\"/\\\")\\n if separator != \\\"/\\\":\\n pattern = re.sub(re.escape(separator), \\\"/\\\", pattern)\\n\\n # If pattern contains '/' it should match from the start.\\n temp = pattern\\n if pattern[0] == \\\"/\\\":\\n pattern = pattern[1:]\\n if temp[-1] == \\\"/\\\":\\n temp = temp[:-1]\\n\\n # Convert pattern rules: ** * ? to regexp rules.\\n pattern = re.escape(pattern)\\n pattern = string.replace(pattern, \\\"\\\\\\\\?\\\", \\\".\\\")\\n pattern = string.replace(pattern, \\\"\\\\\\\\*\\\\\\\\*\\\", \\\".*\\\")\\n pattern = string.replace(pattern, \\\"\\\\\\\\*\\\", \\\"[^/]*\\\")\\n pattern = string.replace(pattern, \\\"\\\\\\\\*\\\", \\\".*\\\")\\n\\n if \\\"/\\\" in temp:\\n # If pattern contains '/' it should match from the start.\\n pattern = \\\"^\\\\\\\\/\\\" + pattern\\n else:\\n # Else the pattern should match the all file or folder name.\\n pattern = \\\"\\\\\\\\/\\\" + pattern\\n\\n if pattern[-2:] != \\\"\\\\\\\\/\\\" and pattern[-2:] != \\\".*\\\":\\n # File patterns should match also folders.\\n pattern = pattern + \\\"\\\\\\\\/?\\\"\\n\\n # Pattern should match till the end.\\n pattern = pattern + \\\"$\\\"\\n return (sign, pattern)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"70beee47c206720b1c48a8cf9a4a2245\",\n \"score\": \"0.48351344\",\n \"text\": \"def reduce_lengthening(self, data, pattern):\\n data.loc[:, self.tweets_col] = data.loc[:, self.tweets_col].apply(lambda tweet: pattern.sub(r\\\"\\\\1\\\\1\\\", tweet))\\n return data\",\n \"title\": \"\"\n },\n {\n \"docid\": \"33a995c13cde0ca51549c28ee9104686\",\n \"score\": \"0.48343244\",\n \"text\": \"def assertInString(self, conn_string, pattern):\\r\\n found = conn_string.find(pattern) != -1\\r\\n self.assertTrue(found,\\r\\n \\\"pattern \\\\\\\"%s\\\\\\\" was not found in connection string \\\\\\\"%s\\\\\\\"\\\" % (pattern, conn_string))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"00df529494eaee98878f970301328f02\",\n \"score\": \"0.48266596\",\n \"text\": \"def compile_pcre_pattern(pattern, additional_flags=0):\\n try:\\n if pattern[0] != '/':\\n return re.compile(pattern, additional_flags)\\n\\n parts = pattern.split('/')\\n modifiers = parts[-1]\\n newpattern = pattern[1:-1 - len(modifiers)]\\n flags_lut = {'i': re.I, 's': re.S, 'm': re.M, 'u': re.U}\\n flags = re.U\\n\\n for i in modifiers:\\n if i in flags_lut:\\n flags |= flags_lut[i]\\n\\n flags |= additional_flags\\n return re.compile(newpattern, flags)\\n except Exception as e:\\n raise type(e)(str(e) + \\\"\\\\nFailed pattern: %s, %s\\\" % (pattern, newpattern)) \\\\\\n .with_traceback(sys.exc_info()[2])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f1612c4925ca8887d11f9b90513d286c\",\n \"score\": \"0.48177585\",\n \"text\": \"def nth_repl(s, sub, repl, nth):\\n find = s.find(sub)\\n # if find is not p1 we have found at least one match for the substring\\n i = find != -1\\n # loop util we find the nth or we find no match\\n while find != -1 and i != nth:\\n # find + 1 means we start at the last match start index + 1\\n find = s.find(sub, find + 1)\\n i += 1\\n # if i is equal to nth we found nth matches so replace\\n if i == nth:\\n return s[:find]+repl+s[find + len(sub):]\\n return s\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6bbe3889ec0e5ff85302ce4d907f84a8\",\n \"score\": \"0.48167387\",\n \"text\": \"def copy_replace(src, dst, pattern=None, replace_value=None):\\n file1 = open(src, 'r') if isinstance(src, str) else src\\n file2 = open(dst, 'w') if isinstance(dst, str) else dst\\n pattern = (\\n [pattern] if isinstance(pattern, str)\\n else pattern\\n )\\n replace_value = (\\n [replace_value] if isinstance(replace_value, str)\\n else replace_value\\n )\\n if replace_value and pattern:\\n if len(replace_value) != len(pattern):\\n raise Exception(\\\"Invalid parameters: pattern and replace_value\\\"\\n \\\" have different sizes.\\\")\\n rules = [\\n (re.compile(regex, re.IGNORECASE), value)\\n for regex, value in zip(pattern, replace_value)\\n ]\\n else:\\n rules = []\\n for line in file1:\\n if rules:\\n for rule in rules:\\n line = re.sub(rule[0], rule[1], line)\\n file2.write(line)\\n if isinstance(src, str):\\n file1.close()\\n if isinstance(dst, str):\\n file2.close()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d13cf393775558f61af4a4060f68f59c\",\n \"score\": \"0.481368\",\n \"text\": \"def substitute(self,command,callsign):\\n if command.find(' *')>0:\\n # placeholder not at the beginning\\n command.replace('*',callsign.lower())\\n elif command.find('*')>0:\\n # placeholder at the beginning\\n command.replace('*',callsign)\\n else:\\n # no placeholder, prepend callsign\\n command = callsign + '; ' + command\\n return command\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4e3b1f3e4e7036edcadb41c14581bc2f\",\n \"score\": \"0.48039755\",\n \"text\": \"def transformPattern(self, pattern):\\n raise NotImplementedError(\\\"Should have implemented this\\\")\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":389,"cells":{"query_id":{"kind":"string","value":"6b82f7758ded5229235eb1ea75beaed1"},"query":{"kind":"string","value":"Show specific post comment"},"positive_passages":{"kind":"list like","value":[{"docid":"e37729c20a16f0bc02a8c8d3290c90c5","score":"0.59195065","text":"def comment(post_id, comment_id):\n check_comment(post_id, comment_id, False)\n\n db = get_db()\n comment_sql = get_comment_of_post(db, post_id, comment_id)\n\n comment = dict(comment_sql)\n return jsonify(comment)","title":""}],"string":"[\n {\n \"docid\": \"e37729c20a16f0bc02a8c8d3290c90c5\",\n \"score\": \"0.59195065\",\n \"text\": \"def comment(post_id, comment_id):\\n check_comment(post_id, comment_id, False)\\n\\n db = get_db()\\n comment_sql = get_comment_of_post(db, post_id, comment_id)\\n\\n comment = dict(comment_sql)\\n return jsonify(comment)\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"90b5fce23163cc1947185be27a583845","score":"0.7372231","text":"def post_detail(request, id):\n post = Post.objects.get(id=id)\n return render(request, 'comment/post_detail.html', {'post': post})","title":""},{"docid":"c7bd1ff09b7932f489e77bb54fe2afb7","score":"0.7263986","text":"def view_post(request, post_id):\n post = get_object_or_404(Post, id=post_id)\n comment_form = CommentForm()\n return render(request, 'view_post.html', {\n 'post': post,\n 'comment_form' : comment_form\n })","title":""},{"docid":"6d1c6f3636bd133d4ec45f8d970aa820","score":"0.71852803","text":"def view_post(post_id):\n post = dbmodel.Post.query.get_or_404(post_id)\n comments = dbmodel.Comment.query.filter_by(parent_post_id=post_id)\n return render_template('post.html', post=post, comments=comments)","title":""},{"docid":"8bc9074f80fa2da6473f3f6d35397ef8","score":"0.7105406","text":"def get(self, post):\n if not self.user:\n return self.redirect('/login')\n\n post_comments = post.get_all_comments()\n if not post_comments:\n post_comments = []\n return self.render('post.html', post=post, post_comments=post_comments)","title":""},{"docid":"38e1e370a77939dffb733075ce0e8821","score":"0.6943954","text":"def get(self, post_id):\n if self.user:\n self.render(\"blog_newcomment_page.html\")\n else:\n self.redirect(\"/login\")","title":""},{"docid":"4a50712a72eba1764a71c5ca05e82be2","score":"0.68175966","text":"def show_post(post_id):\n\n post = Post.query.get(post_id)\n\n return render_template('post.html', post=post)","title":""},{"docid":"2746b2faffaf877560839a959cd41301","score":"0.6796878","text":"def show_post(post_id):\n post = Post.query.get_or_404(post_id)\n return render_template(\"/post_details.html\", post=post)","title":""},{"docid":"441de05e103f9c735b95d721a066f112","score":"0.6696225","text":"def get(self, post_key):\n form = CommentForm()\n is_liked = Like.is_liked_by_user(self.user, self.post)\n\n self.render_viewpost(form, is_liked)","title":""},{"docid":"6981d4e2937bc56aa985e2bbca20128e","score":"0.66875017","text":"def show_post_details(post_id):\n\n post = Post.query.get_or_404(post_id)\n\n return render_template('posts/post.html', post= post)","title":""},{"docid":"5bbe9542b66267bf480f0dbbe09cb86c","score":"0.6674287","text":"def post(self, post_id):\n\n logging.info(\"comment\")\n if not self.user:\n self.redirect('/blog')\n return\n\n content = self.request.get(\"content\")\n user = self.user.name\n key = db.Key.from_path('Post', int(post_id), parent=blog_key())\n # blogpost = db.get(key)\n logging.info(user)\n\n #escaping the html to avoid xss\n escaped_cont = cgi.escape(content)\n\n if content and user:\n comment = Comments(content=escaped_cont, user=user, post=int(post_id))\n comment.put()\n\n self.redirect('/blog/%s' % str(post_id))\n else:\n error = \"Comment not included\"\n self.render(\"blog_newcomment_page.html\", content=content, error=error)","title":""},{"docid":"3e04684dcce46a0dee36a9db311807e5","score":"0.6658497","text":"def post_comment_on_fly(request):\n if request.method == 'GET':\n post_pk = request.GET['post_pk']\n comment_details = request.GET['comment_details']\n post = get_object_or_404(models.Post, pk=post_pk)\n comment = models.Comment.objects.create(post=post, detail=comment_details)\n date_time = comment.created_date.strftime(\"%B %d, %Y %H:%M %p\")\n body = \"\"\"\n <div class=\"comment\">\n <div class=\"date\">\n %s\n </div>\n <p>%s : by <strong>%s</strong></p>\n \"\"\" % (date_time, comment.detail, comment.post.author)\n return HttpResponse(body)","title":""},{"docid":"ae991de82c3276d932448bd15b943e45","score":"0.6642535","text":"def post_detail(request, pk):\n\n post = get_object_or_404(Post, pk=pk)\n post.views += 1\n post.save()\n\n post_comments = PostComment.objects.filter(\n post_id=post.id).order_by('-date_commented')\n\n if request.method == 'POST':\n create_comment_form = PostComment(\n comment_detail=request.POST.get('comment_detail'),\n user=request.user,\n post=post\n )\n create_comment_form.save()\n messages.success(request, 'Comment added to Post')\n return redirect('post_detail', pk)\n\n context = {\n 'post': post,\n 'form': AddComment,\n 'comments': post_comments\n }\n return render(request, \"blog/postdetail.html\", context)","title":""},{"docid":"5b22f4522434446a6820d638817bf23d","score":"0.6613093","text":"def comment(request, blog_id):\n blog = get_object_or_404(Blog, pk=blog_id)\n return render_to_response('comment.html', \n {'comments': blog.comment_set.all(), 'blog': blog})","title":""},{"docid":"ebc602237fbd1157a569f561a09da587","score":"0.6592421","text":"def detail(request, post_id):\n post = get_object_or_404(Post, pk=post_id)\n comments = post.comments.all()\n new_comment = None\n\n if request.method == 'POST':\n comment_form = CommentForm(request.POST)\n if comment_form.is_valid() and request.user.is_authenticated:\n new_comment = comment_form.save(commit=False)\n new_comment.post = post\n new_comment.author = request.user\n new_comment.save()\n messages.success(request, 'Comment added successfully!')\n return redirect(reverse('article-detail', args=[post.id]))\n else:\n messages.error(request, 'Please check the form for errors. \\\n Comment failed to post.')\n else:\n comment_form = CommentForm()\n\n template = 'article_details.html'\n\n context = {\n 'post': post,\n 'comments': comments,\n 'comment_form': comment_form,\n 'new_comment': new_comment,\n }\n\n return render(request, template, context)","title":""},{"docid":"42ddd5c1a8cc3be0762e3a3bc4f193d6","score":"0.6575711","text":"def post_detail(request, year, month, day, post):\n post = get_object_or_404(Post, slug=post,\n status='published',\n publish__year=year,\n publish__month=month,\n publish__day=day)\n\n # lista de comentarios para este post\n comments = post.comments.filter(active=True) # recupera todos comentários ativos\n\n new_comment = None\n\n if request.method == \"POST\":\n comment_form = CommentForm(data=request.POST)\n if comment_form.is_valid():\n new_comment = comment_form.save(commit=False)\n new_comment.post = post\n new_comment.save()\n\n else:\n comment_form = CommentForm()\n\n #lista de posts similares\n post_tags_id = post.tags.values_list('id', flat=True)\n\n similar_posts = Post.published.filter(tags__in=post_tags_id)\\\n .exclude(id=post.id)\n similar_posts = similar_posts.annotate(same_tags=Count('tags'))\\\n .order_by('-same_tags','-publish')[:4]\n\n\n return render(request, path_detalhe, {'post':post,\n 'comments':comments,\n 'new_comment':new_comment,\n 'comment_form':comment_form,\n 'similar_posts':similar_posts})","title":""},{"docid":"86c1a78f0f800b7a252a3375b7267dfd","score":"0.65154254","text":"def show_post(index):\r\n requested_post = None\r\n for blog_post in post_objects:\r\n if blog_post.id == index:\r\n requested_post = blog_post\r\n return render_template(\"post.html\", post=requested_post)","title":""},{"docid":"9803868473e014f9b0bd143b9b92a24b","score":"0.65096605","text":"def post_comment(request, post_pk):\n post = get_object_or_404(models.Post, pk=post_pk)\n form = forms.CommentForm()\n if request.method == 'POST':\n form = forms.CommentForm(request.POST)\n if form.is_valid():\n comment = form.save(commit=False)\n comment.post = post\n comment.save()\n\n return HttpResponseRedirect(post.get_absolute_url())","title":""},{"docid":"eb428f9e3fa1c8e15115e616a7be65d2","score":"0.6491254","text":"def post_show(request, pid):\n user = request.user\n\n # populate the session data\n sess = middleware.Session(request)\n tab = \"posts\"\n pill = sess.get_tab()\n \n auth = user.is_authenticated()\n layout = settings.USER_PILL_BAR if auth else settings.ANON_PILL_BAR\n \n params = html.Params(tab=tab, pill=pill, layout=layout)\n \n query = get_post_manager(request)\n\n try:\n root = query.get(id=pid)\n if not root.top_level:\n return html.redirect( root.get_absolute_url() )\n\n # update the views for the question\n models.update_post_views(post=root, request=request, minutes=const.POST_VIEW_UPDATE)\n counts = sess.get_counts()\n \n except models.Post.DoesNotExist, exc:\n messages.warning(request, 'The post that you are looking for does not exists. Perhaps it was deleted!')\n return html.redirect(\"/\")\n \n # get all answers to the root\n children = models.Post.objects.filter(root=root).exclude(type=POST_COMMENT, id=root.id).select_related('author', 'author__profile').order_by('-accepted', '-score', 'creation_date')\n \n # comments need to be displayed by creation date\n comments = models.Post.objects.filter(root=root, type=POST_COMMENT).select_related('author', 'author__profile').order_by('creation_date')\n\n all = [ root ] + list(children) + list(comments)\n # add the various decorators\n \n models.decorate_posts(all, user)\n \n # may this user accept answers on this root\n accept_flag = (user == root.author)\n \n # these are all the answers\n answers = [ o for o in children if o.type == POST_ANSWER ]\n for a in answers:\n a.accept_flag = accept_flag\n \n # get all the comments\n tree = defaultdict(list)\n for comment in comments: \n tree[comment.parent_id].append(comment)\n \n # generate the tag cloud\n #tags = models.Tag.objects.all().order_by('-count')[:50]\n \n return html.template( request, name='post.show.html', root=root, answers=answers, tree=tree, params=params, counts=counts)","title":""},{"docid":"2c8969424c554f552f3d0fff1277bd13","score":"0.64574575","text":"def post_comment(self):\n slug = str(self.article.slug)\n url = reverse(\"articles:comment\", args=[slug])\n return self.client.post(\n url, self.comment\n )","title":""},{"docid":"3da2d9f2dc3faae054ae941f4b649911","score":"0.64555997","text":"def display_post(post_id):\n\n post = Post.query.get(post_id)\n\n return render_template('post_details.html', post=post)","title":""},{"docid":"c260ed4702864ab81be87afb457f3b19","score":"0.6418798","text":"def show_wall_post(request, username, post_id):\n\n try:\n wall_post = UserActivity.objects.select_related().get(\n short_review__id = post_id,\n username__iexact = username,\n status = UserActivity.PUBLIC_STATUS)\n except UserActivity.DoesNotExist:\n raise Http404\n\n try:\n user = User.objects.get(username__iexact=username)\n except User.DoesNotExist:\n raise Http404\n\n data = {\n 'activity' : wall_post,\n 'user_profile': user\n }\n\n return render(\n request,\n templates['WALL_POST'],\n data,\n )","title":""},{"docid":"43416164e422f0829d7c89d459a53d3a","score":"0.6390816","text":"def view_post(post_id):\n post = mongo.db.reviews.find_one({\"_id\": ObjectId(post_id)})\n if post:\n comments = list(mongo.db.comments.find(\n {\"location_id\": post['location_id']}))\n if 'user' in session:\n fav_user = list(mongo.db.favourites.find(\n {\"favourite_user\": session['user']}))\n else:\n fav_user = None\n return render_template(\n \"view_post.html\", post=post, comments=comments, fav_user=fav_user)\n flash(\"Post does not exist\")\n return redirect(url_for('get_locations'))","title":""},{"docid":"7b7848bded87fe53154eefa999865b45","score":"0.6345191","text":"def show_post(self, request: foundation.Request) -> foundation.Response:\n\n id = request.params['id']\n\n orm_session = orm.sessionmaker(bind=self.get_engine())()\n\n post = orm_session.query(models.Post).filter_by(id=id).one()\n\n return self.render2response(request, 'blog/show.html', post=post,\n blog=self, url_for=self.url_for)","title":""},{"docid":"1dd4dd9dbb263f246a41cb257d4d2210","score":"0.6344819","text":"def view_post(request, post_id):\n\n def can_view_post(user, pid):\n post_ = models.Post.objects.get(pk=pid)\n for member in user.member_set.all():\n if member.Organization_id == post_.Creator.Organization_id:\n return True\n return False\n\n post = models.Post.objects.get(pk=post_id)\n if not post.Visible:\n if can_view_post(request.user, post_id):\n return render(request, 'view_post.html',\n {'title': post.Title, 'Content': post.Content,\n 'user': request.user,\n 'loginable': request.user.is_authenticated()})\n else:\n return render(request, 'Error.html',\n {'error_summary': 'Not visible',\n 'error_details': 'You must have permission to view '\n 'this post'})\n else:\n return render(request, 'view_post.html',\n {'title': post.Title, 'Content': post.Content,\n 'user': request.user,\n 'loginable': request.user.is_authenticated()})","title":""},{"docid":"ae89532ae37ecf3280171bbcd3b8dcf1","score":"0.6330918","text":"def post_comment(source_post, parent):\n try:\n askbot_comment = source_post.get_author().post_comment(\n parent_post = parent,\n body_text = source_post.get_body_text(),\n timestamp = source_post.created_at\n )\n return askbot_comment\n except Exception, e:\n msg = unicode(e)\n print \"Warning: post %d skipped: %s\" % (source_post.post_id, msg)","title":""},{"docid":"7f3c284c4abc8719b29277d1027512a0","score":"0.62737817","text":"def post_comment(request, post_id):\n if request.method == 'POST':\n post = get_object_or_404(Post, id=post_id)\n comment_form = CommentForm(request.POST)\n if comment_form.is_valid():\n comment = Comment(\n body = comment_form.cleaned_data['body'],\n date = datetime.now(),\n post = post,\n user = request.user\n )\n comment.save()\n messages.info(request, 'Comment Posted!')\n else:\n messages.error(request, 'Invalid comment')\n return HttpResponseRedirect(reverse('view_post', args=[post_id]))","title":""},{"docid":"29f2bee9380e862dd2ae637eb7322945","score":"0.6212544","text":"def detail(id):\n post = get_post(id, check_author=False)\n comments = get_comments_for_post(post_id=id)\n users_likes = get_users_liking_post(post_id=id)\n\n # Post existence is already checked in get_post\n return render_template(\n \"blog/detail.html\",\n post=post,\n comments=comments,\n users_likes=users_likes\n )","title":""},{"docid":"8085d8f8ff6981e0109333af03ef8f2c","score":"0.6203446","text":"def blogDetailView(request, pk):\n user = request.user\n post_detail = get_object_or_404(BlogPost, pk=pk)\n blogPostType = ContentType.objects.get(app_label='blog', model='blogpost')\n res = LikesAndDislikes.objects.filter(content_type=blogPostType, object_id=pk)\n num_of_likes = res.filter(like_type=False).count()\n num_of_dislikes = res.filter(like_type=True).count()\n\n comments = Comment.objects.filter(content_type=blogPostType, object_id=pk)\n\n initial_data = {\n 'user': user,\n 'content': \"leave your comment here ~\",\n 'content_type': blogPostType,\n 'object_id': pk,\n }\n form = CommentForm(initial=initial_data)\n\n context = {\n 'post_detail' : post_detail,\n 'num_of_likes' : num_of_likes,\n 'num_of_dislikes': num_of_dislikes,\n 'liked': False,\n 'disliked': False,\n 'form': form,\n 'comments': comments,\n }\n\n is_done = LikesAndDislikes.objects.filter(\n user=user,\n content_type=blogPostType,\n object_id=pk\n )\n\n if is_done:\n if is_done.get().like_type == False:\n context['liked'] = True\n else:\n context['disliked'] = True\n\n return render(request, 'blog/post.html', context)","title":""},{"docid":"ba490370835895b27530e850d9cc9ab6","score":"0.618974","text":"def get(self, post_id):\n blogpost_key = db.Key.from_path('BlogPost', int(post_id))\n blogpost_post = db.get(blogpost_key)\n content = blogpost_post.content\n title = blogpost_post.title\n self.render('edit.html', title=title, content=content)","title":""},{"docid":"2c92b6ae7b0d67da9e0626231a22a6cc","score":"0.6186363","text":"def view_post(request, post_id):\n post = get_object_or_404(BlogPost, pk=post_id)\n\n template = 'blog/blog_post.html'\n context = {\n 'post': post\n }\n return render(request, template, context)","title":""},{"docid":"8c58e5ee5f08f1af57fda658f347fe71","score":"0.6102145","text":"def post_detail(request, id):\n\n post = get_object_or_404(Post, pk=id)\n return render(request, \"postdetail.html\", {'post': post})","title":""},{"docid":"7c76e9439806fbd7aff6ace5cb7c0ab9","score":"0.6096827","text":"def showPost(self):\n print(\"{} ──────────────────────────\".format(self.owner.name))\n print(\"{:%d, %b %Y}\".format(self.timestamp))\n print(\"{}\".format(self.content), end=\"\\n\\n\")","title":""},{"docid":"a3abb50f740a2a601c2d51d2ed9ea94e","score":"0.6087277","text":"def blogpost(request, parametr):\n assert isinstance(request, HttpRequest)\n post_1 = Blog.objects.get(id=parametr)\n comments = Comment.objects.filter(post=parametr)\n \n if request.method == \"POST\":\n form = CommentForm(request.POST)\n if form.is_valid():\n comment_f = form.save(commit=False)\n comment_f.author = request.user\n comment_f.date = datetime.now()\n comment_f.post = Blog.objects.get(id=parametr)\n comment_f.save()\n return redirect('blogpost', parametr=post_1.id) \n else:\n form = CommentForm() \n \n return render(\n request,\n 'app/blogpost.html',\n \n {\n 'post_1': post_1,\n 'comments': comments,\n 'form': form,\n 'year':datetime.now().year,\n \n }\n \n )","title":""},{"docid":"b9197dec82e3d1cde8819f6695d820d9","score":"0.6073559","text":"def _show_comments(self):\n headers = {\"Authorization\": \"Token %s\" % cfg.koodous.token}\n\n try:\n content_file = __sessions__.current.file.data\n sha256 = hashlib.sha256(content_file).hexdigest()\n except Exception:\n self.log('error', 'You have no file loaded')\n return\n try:\n url = '%s/%s/comments' % (cfg.koodous.base_url, sha256)\n response = requests.get(url=url, headers=headers, proxies=cfg.koodous.proxies,\n verify=cfg.koodous.verify, cert=cfg.koodous.cert)\n\n if response.json().get('count') == 0:\n self.log('info', 'This sample has no comments.')\n return\n for result in response.json().get('results'):\n self.log('info', \"[{}]: {}\".format(result['author']['username'], result['text']))\n except Exception as err:\n self.log('error', 'Network problem, please try again.')\n log.error(\"Network problem, please try again: \\n{}\".format(err))","title":""},{"docid":"2d785282de48b6a4e8ec49022b1ca09a","score":"0.60732067","text":"def edit_comment(request, pk):\n comment = get_object_or_404(Comment, pk=pk)\n feed = comment.feed\n \n # Protecting the edit feed page.\n if comment.user != request.user:\n raise Http404\n\n if request.method != 'POST':\n # Initial request; pre-fill form with the current entry\n form = CommentForm(instance=comment)\n else:\n # POST data submitted; process data\n form = CommentForm(instance=comment, data=request.POST)\n if form.is_valid():\n form.save()\n messages.add_message(request, messages.SUCCESS, 'Comment updated')\n return redirect('feed:feed_detail', pk=feed.pk)\n\n context = {'feed': feed, 'comment': comment, 'form': form}\n return render(request, 'feed/edit_comment.html', context)","title":""},{"docid":"00bbd84ada5ba6fa7732c1e6788dedd5","score":"0.6059708","text":"def post(self, post_id, comment_id):\n comment = Comment.by_id(comment_id)\n if self.user and self.user.name == comment.username:\n save_clicked = self.request.get(\"save\")\n cancel_clicked = self.request.get(\"cancel\")\n delete_clicked = self.request.get(\"delete\")\n\n edited_comment = self.request.get(\"comment\")\n\n if save_clicked:\n self.save_edit(edited_comment, comment, post_id)\n elif cancel_clicked:\n self.cancel_edit(post_id)\n elif delete_clicked:\n self.delete_edit(comment, post_id)\n else:\n self.redirect(\"/blog\")\n else:\n self.redirect(\"/blog\")","title":""},{"docid":"449041abfd9c0c35e65163dd4b2448b4","score":"0.60335106","text":"def post(self):\n\n # keep reference to the post page for redirection later\n referrer = self.request.referer\n post_id = referrer.split(\"/\")[-1]\n\n post = Post.by_id(post_id)\n\n comment_text = self.request.get(\"comment\")\n self.write(comment_text)\n if comment_text:\n new_comment = Comment(post_id=post_id, username=self.user.name,\n comment=comment_text)\n new_comment.put()\n self.redirect(referrer)\n else:\n # TODO should render page with error\n self.redirect(referrer)","title":""},{"docid":"5da1fa25ec79aacc2972e2f5780268f4","score":"0.60311145","text":"def manage_comment():\n page = request.args.get('page', 1, type=int)\n logger.info('Visiting comment manage page {}.'.format(page))\n pagination = Comment.query.order_by(Comment.timestamp.desc()).paginate(page,\n per_page=current_app.config['FLASKY_POSTS_PER_PAGE'],\n error_out=False)\n comments = pagination.items\n return render_template('manage_comment.html', comments=comments, pagination=pagination)","title":""},{"docid":"77153d75906691e4cb26e341e493587e","score":"0.6026122","text":"def post(self):\n if self.authenticated():\n post_id = self.request.get('post_id')\n post = Post.get_by_id(int(post_id))\n comment_txt = self.request.get('comments')\n comment = Comment(comment = comment_txt, commenter = self.user, post = post)\n comment.put()\n self.redirect('/blog/%s' % (post_id))\n else:\n self.login_redirect()","title":""},{"docid":"435adb6c92bdce29612c05447271c8be","score":"0.6018611","text":"def show_edit_post_page(post_id):\n\n post = Post.query.get(post_id)\n\n return render_template('edit_post.html', post=post)","title":""},{"docid":"8a254a746c56282352dcc4740a1155ba","score":"0.601529","text":"def commentsindex(topic_id):\n post = get_post(topic_id)\n db = get_db()\n postcoms = query_db(\n \"SELECT * FROM postcomments p JOIN user u ON p.author_id=u.id WHERE topic_id = ?\",[topic_id]\n )\n return render_template(\"blog/commentsindex.html\", postcoms=postcoms, post=post)","title":""},{"docid":"6f7420a7dbd5f2dc7191672e8039fd45","score":"0.60079324","text":"def get_comment_by_id(self):\n parent_comment = self.create_comment()\n id = parent_comment.data['id']\n return self.client.get(reverse(\n \"articles:commentdetail\", args=[\"this-is-mine\", id]))","title":""},{"docid":"e9afdbc32d51a0bcf0c94198463f1105","score":"0.6005923","text":"def user_comment_post(sender, instance, *args, **kwargs):\n comment = instance\n post = comment.post\n text_preview = comment.body[:90] #take only first 90 chars as a preview.\n sender = comment.user\n\n notify = Notification(post=post, sender=sender, user=post.user, text_preview=text_preview, notification_type=2)\n notify.save()","title":""},{"docid":"c6af3cdc773174518d36eb7596da5090","score":"0.6001438","text":"def show(request, slug):\n\ttry:\n\t\tpage = Content.objects.get(slug=slug)\n\texcept Content.DoesNotExist:\n\t\treturn render_to_response('pages/bug.html',\n\t\t\t{'bug': _('Page does not exist')},\n\t\t\tcontext_instance=RequestContext(request))\n\t\n\tadd_topic = False\n\tif page.coment_forum:\n\t\trequest.forum_id = page.coment_forum.id\n\t\tcoment_forum_id = page.coment_forum.id\n\t\tperms = forumContext(request)\n\t\tif perms['perms']['add_topic']:\n\t\t\tadd_topic = True\n\telif page.place and page.place.coment_forum:\n\t\trequest.forum_id = page.place.coment_forum.id\n\t\tcoment_forum_id = page.place.coment_forum.id\n\t\tperms = forumContext(request)\n\t\tif perms['perms']['add_topic']:\n\t\t\tadd_topic = True\n\t\n\tif add_topic and not page.coment_topic:\n\t\tform = diamandaModelwrappers.AddTopicForm()\n\telif add_topic and page.coment_topic:\n\t\tform = diamandaModelwrappers.AddPostForm()\n\telse:\n\t\tform = False\n\t\n\tcomments = False\n\t# check if user wants to add a comment - show the form if possible\n\tif 'c' in request.GET:\n\t\tshow_comment = True\n\t\tif form and page.coment_topic:\n\t\t\tcomments = page.coment_topic.post_set.all().order_by('-id')[:10]\n\telse:\n\t\tshow_comment = False\n\t\n\tif request.POST and add_topic and not page.coment_topic:\n\t\tCOMMENT_POST = _('This is a discussion about article') + ': [url=/w/p/%s/]%s[/url].' % (page.slug, page.title)\n\t\tREDIRECT = (\"/w/p/\" + slug +\"/?c=ok\", _('Comment added succesfuly.'))\n\t\tTITLE = _('Comments for: %s') % page.title\n\t\treturn diamandaModelwrappers.add_topic(request, coment_forum_id, inject_post=COMMENT_POST, inject_title=TITLE, redirect_link=REDIRECT, content_obj=page)\n\telif request.POST and add_topic and page.coment_topic:\n\t\tREDIRECT = (\"/w/p/\" + slug +\"/?c=ok\", _('Comment added succesfuly.'))\n\t\treturn diamandaModelwrappers.add_post(request, page.coment_topic.id, redirect_link=REDIRECT, content_obj=page)\n\t\n\tif page.current_book:\n\t\tcb = page.current_book\n\t\n\tif page.content_type == 'news':\n\t\treturn render_to_response(\n\t\t\t'pages/show_news.html',\n\t\t\t{'page': page, 'add_topic': add_topic, 'form': form, 'show_comment': show_comment, 'comments': comments},\n\t\t\tcontext_instance=RequestContext(request, {'current_book': cb}))\n\treturn render_to_response(\n\t\t'pages/show.html',\n\t\t{'page': page, 'add_topic': add_topic, 'form': form, 'show_comment': show_comment, 'comments': comments},\n\t\tcontext_instance=RequestContext(request, {'current_book': cb}))","title":""},{"docid":"fea07b70f2ea2874392c5226c75175b9","score":"0.5996286","text":"def comments(game_id, post_id):\n\n db = get_db()\n\n if (request.method == 'POST') and (g.user != None):\n #If there is a post request and the user is logged in, insert their comment into the database\n\n comment = request.form['comment']\n\n db.execute(\"INSERT INTO comments(user_id, post_id, comment_id, content, hidden) VALUES (?, ?, NULL, ?, 0)\", (g.user['id'], post_id, comment))\n db.commit()\n\n\n #Retrieve all of the necessary data for the page\n post = db.execute(\"SELECT username, users.id, title, body, game_id FROM posts JOIN users ON user_id=users.id WHERE posts.id = ?\", str(post_id)).fetchone()\n\n game = db.execute(\"SELECT id, title FROM games WHERE id = ?\", str(post['game_id'])).fetchone()\n\n comments = db.execute(\"SELECT content, username, users.id FROM comments JOIN users ON user_id=users.id WHERE post_id = ?\", str(post_id)).fetchall()\n\n return render_template(\"layouts/comments.html\", post=post, comments=comments, game=game)","title":""},{"docid":"461d41775f2f75bd350a598908a50f08","score":"0.5989866","text":"def comment():\n if request.method == 'POST':\n if 'username' not in session:\n return render_template('login.html')\n\n message = request.form['message']\n post_id = request.form['post_id']\n username = session['username']\n user_id = session['user_id']\n\n print(post_id)\n print(user_id)\n\n # Use backend post api - Post\n body = {'user_id': user_id,\n 'username': username, 'message': message}\n\n # url = '{}/posts'.format(app.config[\"POST_BASE_URI\"])\n url = '{}/posts/{}/comments'.format(app.config[\"POST_BASE_URI\"], post_id)\n print(url)\n response = requests.post(url=url,\n json=body,\n headers={'content-type': 'application/json'},\n timeout=3)\n\n app.logger.info('Get %s with response status code %s',\n url, response.status_code)\n app.logger.info('Get %s with response text %s', url, response.text)\n\n return redirect('/viewpost/' + post_id)\n return render_template('login.html')","title":""},{"docid":"133c58bdaad85c0efe4c270497a91ae3","score":"0.59606856","text":"def post_comment(request, next=None):\r\n # Fill out some initial data fields from an authenticated user, if present\r\n data = request.POST.copy()\r\n if request.user.is_authenticated():\r\n if not data.get('name', ''):\r\n data[\"name\"] = request.user.get_full_name() or request.user.username\r\n if not data.get('email', ''):\r\n data[\"email\"] = request.user.email\r\n\r\n # Check to see if the POST data overrides the view's next argument.\r\n next = data.get(\"next\", next)\r\n\r\n # Look up the object we're trying to comment about\r\n ctype = data.get(\"content_type\")\r\n object_pk = data.get(\"object_pk\")\r\n if ctype is None or object_pk is None:\r\n return CommentPostBadRequest(\"Missing content_type or object_pk field.\")\r\n try:\r\n model = models.get_model(*ctype.split(\".\", 1))\r\n target = model._default_manager.get(pk=object_pk)\r\n except TypeError:\r\n return CommentPostBadRequest(\r\n \"Invalid content_type value: %r\" % escape(ctype))\r\n except AttributeError:\r\n return CommentPostBadRequest(\r\n \"The given content-type %r does not resolve to a valid model.\" % \\\r\n escape(ctype))\r\n except ObjectDoesNotExist:\r\n return CommentPostBadRequest(\r\n \"No object matching content-type %r and object PK %r exists.\" % \\\r\n (escape(ctype), escape(object_pk)))\r\n\r\n # Do we want to preview the comment?\r\n preview = \"preview\" in data\r\n\r\n # Construct the comment form\r\n form = comments.get_form()(target, data=data)\r\n\r\n # Check security information\r\n if form.security_errors():\r\n return CommentPostBadRequest(\r\n \"The comment form failed security verification: %s\" % \\\r\n escape(str(form.security_errors())))\r\n\r\n # If there are errors or if we requested a preview show the comment\r\n if form.errors or preview:\r\n template_list = [\r\n \"comments/%s_%s_preview.html\" % tuple(str(model._meta).split(\".\")),\r\n \"comments/%s_preview.html\" % model._meta.app_label,\r\n \"comments/preview.html\",\r\n ]\r\n return render_to_response(\r\n template_list, {\r\n \"comment\" : form.data.get(\"comment\", \"\"),\r\n \"form\" : form,\r\n \"next\": next,\r\n },\r\n RequestContext(request, {})\r\n )\r\n\r\n # Otherwise create the comment\r\n comment = form.get_comment_object()\r\n comment.ip_address = request.META.get(\"REMOTE_ADDR\", None)\r\n if request.user.is_authenticated():\r\n comment.user = request.user\r\n\r\n # Signal that the comment is about to be saved\r\n responses = signals.comment_will_be_posted.send(\r\n sender = comment.__class__,\r\n comment = comment,\r\n request = request\r\n )\r\n\r\n for (receiver, response) in responses:\r\n if response == False:\r\n return CommentPostBadRequest(\r\n \"comment_will_be_posted receiver %r killed the comment\" % receiver.__name__)\r\n\r\n # Save the comment and signal that it was saved\r\n comment.save()\r\n signals.comment_was_posted.send(\r\n sender = comment.__class__,\r\n comment = comment,\r\n request = request\r\n )\r\n\r\n return next_redirect(data, next, comment_done, c=comment._get_pk_val())","title":""},{"docid":"91818ccd34b7b916f67ef9df2bcc1735","score":"0.59462464","text":"def view_comments(request, product_id):\n reviews = Review.objects.filter(product=product_id)\n product = get_object_or_404(Product, pk=product_id)\n\n context = {\n \"reviews\": reviews,\n \"product\": product,\n }\n return render(request, \"products/reviews.html\", context)","title":""},{"docid":"6b06e3c34b4f68e6649bfaf23b58ac6b","score":"0.5928355","text":"def post(self, post_key):\n form = CommentForm(self.request.POST)\n is_liked = Like.is_liked_by_user(self.user, self.post)\n\n if form.validate():\n comment_key = Comment.new_comment(form.content.data, self.user,\n self.post)\n\n if comment_key:\n self.redirect_to(\"viewpost\", post_key=post_key,\n _fragment=str(comment_key))\n else:\n self.abort(500)\n\n self.render_viewpost(form, is_liked)","title":""},{"docid":"1573a05a8c90223786c44481e85adf69","score":"0.59153986","text":"def pickRepostComment(repostComments): \n return None","title":""},{"docid":"55ebbd6cb68713797bf7ff40c6db7f78","score":"0.591078","text":"def post_comment(request, next=None):\n # Fill out some initial data fields from an authenticated user, if present\n data = request.POST.copy()\n print data\n if request.user.is_authenticated():\n if not data.get('name', ''):\n data[\"name\"] = request.user.get_full_name() or request.user.username\n if not data.get('email', ''):\n data[\"email\"] = request.user.email\n\n # Look up the object we're trying to comment about\n ctype = data.get(\"content_type\")\n object_pk = data.get(\"object_pk\")\n print ctype\n if ctype is None or object_pk is None:\n return CommentPostBadRequest(\"Missing content_type or object_pk field.\")\n try:\n model = models.get_model(*ctype.split(\".\", 1))\n target = model._default_manager.get(pk=object_pk)\n except TypeError:\n return CommentPostBadRequest(\n \"Invalid content_type value: %r\" % escape(ctype))\n except AttributeError:\n return CommentPostBadRequest(\n \"The given content-type %r does not resolve to a valid model.\" % \\\n escape(ctype))\n except ObjectDoesNotExist:\n return CommentPostBadRequest(\n \"No object matching content-type %r and object PK %r exists.\" % \\\n (escape(ctype), escape(object_pk)))\n\n # Do we want to preview the comment?\n preview = \"preview\" in data\n\n # Construct the comment form\n form = comments.get_form()(target, data=data)\n\n # Check security information\n if form.security_errors():\n return CommentPostBadRequest(\n \"The comment form failed security verification: %s\" % \\\n escape(str(form.security_errors())))\n\n # If there are errors or if we requested a preview show the comment\n if preview:\n template_list = [\n \"comments/%s_%s_preview.html\" % tuple(str(model._meta).split(\".\")),\n \"comments/%s_preview.html\" % model._meta.app_label,\n \"comments/preview.html\",\n ]\n return render_to_response(\n template_list, {\n \"comment\" : form.data.get(\"comment\", \"\"),\n \"form\" : form,\n },\n RequestContext(request, {})\n )\n \n if form.errors:\n (view_func, view_args, view_kwargs) = resolve(target.get_absolute_url())\n view_kwargs.update({\n 'extra_context': {'comment_form': form}\n })\n return view_func(request, *view_args, **view_kwargs)\n\n # Otherwise create the comment\n comment = form.get_comment_object()\n comment.ip_address = request.META.get(\"REMOTE_ADDR\", None)\n if request.user.is_authenticated():\n comment.user = request.user\n\n # Signal that the comment is about to be saved\n responses = signals.comment_will_be_posted.send(\n sender = comment.__class__,\n comment = comment,\n request = request\n )\n\n for (receiver, response) in responses:\n if response == False:\n return CommentPostBadRequest(\n \"comment_will_be_posted receiver %r killed the comment\" % receiver.__name__)\n\n # Save the comment and signal that it was saved\n comment.save()\n signals.comment_was_posted.send(\n sender = comment.__class__,\n comment = comment,\n request = request\n )\n\n return next_redirect(data, next, comment_done, c=comment._get_pk_val())","title":""},{"docid":"c85bb1e58b7a038fd261394cc45b50da","score":"0.5903895","text":"def edit_comment(self, comment_object, pid):\n if self.user:\n comment_content = self.request.get('post_comment')\n if comment_content:\n comment_object.comment = comment_content\n CommentEntity.commit_comment(comment_object)\n return self.redirect('/{0}/{1}'.format('post',\n pid))\n\n self.redirect('/login')","title":""},{"docid":"b710bbc470070b1bc2d25ad3b1bcc0d3","score":"0.58985364","text":"def post(self, post_id):\n data = request.json\n comment = create_comment(data=data, post_id=post_id)\n return comment","title":""},{"docid":"4df99ef651670e5cb343ca4e9f7bc594","score":"0.5895393","text":"def get_blog_post(request, pk):\n return render(request, 'oikos/blog.html', {'post' : Post.objects.get(pk=pk)})","title":""},{"docid":"6e400562d59bb225386fd3713b126bb9","score":"0.58818877","text":"def comment_detail(request, company_slug, idea_id, comment_id): \n comment = get_object_or_404(Comment, idea__id=idea_id, pk=comment_id)\n\n if request.method == 'GET':\n serializer = CommentSerializer(comment)\n return Response(serializer.data)\n\n elif request.method == 'DELETE':\n if not has_admin_permission(request.user, comment.idea.company) and comment.created_by != request.user:\n return HttpResponseForbidden() \n\n try:\n member = Member.objects.get(company=comment.idea.company, user=request.user)\n if member.blocked:\n return HttpResponseForbidden() \n except:\n pass\n\n comment.delete()\n return Response(status=status.HTTP_204_NO_CONTENT)","title":""},{"docid":"0168b1f8b91b78e798e21abeca66e931","score":"0.58523023","text":"def comment_was_posted(request):\r\n obj = None\r\n if request.GET.has_key('c'):\r\n content_type_id, object_id = request.GET['c'].split(':')\r\n try:\r\n content_type = ContentType.objects.get(pk=content_type_id)\r\n obj = content_type.get_object_for_this_type(pk=object_id)\r\n except ObjectDoesNotExist:\r\n pass\r\n return render_to_response('comments/posted.html', {'object': obj}, context_instance=RequestContext(request))","title":""},{"docid":"8f00f0a3ee6137af6c5ae0af11863826","score":"0.583153","text":"def comment(self, content):","title":""},{"docid":"e4e9567f1b024e56a73e06b4e09111ea","score":"0.5820659","text":"def post(self, request, post_id):\n post = Post.object.filter(pk=post_id).first()\n title = self.request.POST.get(\"title\", \"\")\n comment = self.request.POST.get(\"comment\", \"\")\n user = self.request.user\n if not title or not comment:\n return JsonResponse({\"error\": \"Datos incompletos\"})\n obj = Comment.objects.create(\n title=title,\n comment=comment,\n user=user,\n post=post\n )\n obj.save()\n return redirect(\"view_post\", (self.post.pk,))","title":""},{"docid":"04b7a8c332af03fd5359469648dce53c","score":"0.5808202","text":"def email(self, comment, content_object, request):\r\n if comment.is_public:\r\n context = {\r\n 'comment': comment,\r\n 'entry': content_object,\r\n }\r\n email_body = render_to_string('blog/new_comment_email.txt', context)\r\n mail_managers(u'Comment on \"%s\"' % content_object, email_body)","title":""},{"docid":"9a016602aa842096c58b9ab3e09e7d05","score":"0.57942635","text":"def item_show(item_id):\n item = items.find_one({'_id': ObjectId(item_id)})\n # Add the below line:\n item_comments = comments.find({'item_id': ObjectId(item_id)})\n # Edit the return statement to be the following:\n return render_template('show.html', item=item, comments=item_comments)","title":""},{"docid":"78fef74fa042889e57ba462adab90e7e","score":"0.5741248","text":"def viewpost(post_id):\n # if request.method == 'POST':\n # if 'username' not in session:\n # return render_template('login.html')\n\n # message = request.form['message']\n # username = session['username']\n # user_id = session['user_id']\n\n # # Use backend post api - Post\n # body = {'user_id': user_id, 'username': username, 'message': message}\n # url = '{}/posts'.format(app.config[\"POST_BASE_URI\"])\n # response = requests.post(url=url,\n # json=body,\n # headers={'content-type': 'application/json'},\n # timeout=3)\n\n # app.logger.info('Get %s with response status code %s',\n # url, response.status_code)\n # app.logger.info('Get %s with response text %s', url, response.text)\n\n # return redirect(url_for('home'))\n\n url = '{}/posts/{}'.format(app.config[\"POST_BASE_URI\"], post_id)\n response = requests.get(url, timeout=3)\n\n app.logger.info('Get %s with response status code %s',\n url, response.status_code)\n # app.logger.info('Get %s with response text %s', url, response.text)\n\n post = json.loads(response.text)['data']['post']\n\n # comments = [{'message': 'Hello'}, {\n # 'message': 'Hello'}, {'message': 'Hello'}]\n comments = json.loads(response.text)['data']['comments']\n\n return render_template('postdetail.html', post=post, comments=comments)","title":""},{"docid":"842f86990df5806e6ca4e3b00c71c9ff","score":"0.57406366","text":"def post_detail(request, pk=None, slug=None):\n if slug:\n post = get_object_or_404(Post, slug=slug)\n elif pk:\n post = get_object_or_404(Post, pk=pk)\n\n return render(request, \"blog/blog_detail.html\", {\n \"page\": \"blog\",\n \"post\": post\n })","title":""},{"docid":"38d910e5a710ded2629a50f3d5a1e7c0","score":"0.5735533","text":"def post_comment():\n content = request.json['content']\n parent = request.json['parent']\n post_id = request.json['post_id']\n user_id = get_jwt_identity()\n comment = Comment(user_id, content, post_id, parent_id=parent)\n db.session.add(comment)\n db.session.commit()\n return respond(plain_response(comment.id))","title":""},{"docid":"45778fc0137795d32597f6ccbd8cbfbf","score":"0.57330495","text":"def feature_comment(request, pk):\n feature = get_object_or_404(Feature, pk=pk)\n if request.method == 'POST':\n comment_form = FeatureCommentForm(request.POST)\n if comment_form.is_valid():\n comment = comment_form.save(commit=False)\n comment.commenter = request.user\n comment.feature = feature\n comment.save()\n return redirect(feature_details, feature.pk)\n else:\n comment_form = FeatureCommentForm()\n return render(request, 'feature_comment.html', {'feature': feature, 'comment_form': comment_form})","title":""},{"docid":"99b506f7fd1b6539d847e8123bef16a3","score":"0.57282954","text":"def edit_comment(request, comment_id):\n user = community_helpers.get_logged_user(request)\n \n if user:\n comment = models.Comment.objects.get(id = comment_id)\n EditCommentForm = forms.build_edit_comment_form(comment)\n if request.POST:\n form = EditCommentForm(request.POST, request.FILES)\n if form.is_valid():\n form.handle_edit(user, comment)\n return http.HttpResponseRedirect(reverse('content-redirect-by-id', args=[comment.content_type.id, comment.object_id]))\n else:\n form = EditCommentForm()\n return shortcuts.render_to_response(\n 'comments/edit_comment.html', \n {'form':form, 'comment':comment, 'node_content_type':comment.content_type.id, 'node_object_id':comment.object_id}, \n context_instance = RequestContext(request)\n )","title":""},{"docid":"3960db6180e18800a9a24dc751dfddda","score":"0.5716266","text":"def post_comment(request, next=None, using=None):\r\n # Fill out some initial data fields from an authenticated user, if present\r\n data = request.POST.copy()\r\n if request.user.is_authenticated():\r\n if not data.get('name', ''):\r\n data[\"name\"] = request.user.get_full_name() or request.user.get_username()\r\n if not data.get('email', ''):\r\n data[\"email\"] = request.user.email\r\n\r\n # Look up the object we're trying to comment about\r\n ctype = data.get(\"content_type\")\r\n object_pk = data.get(\"object_pk\")\r\n if ctype is None or object_pk is None:\r\n return CommentPostBadRequest(\"Missing content_type or object_pk field.\")\r\n try:\r\n model = models.get_model(*ctype.split(\".\", 1))\r\n target = model._default_manager.using(using).get(pk=object_pk)\r\n except TypeError:\r\n return CommentPostBadRequest(\r\n \"Invalid content_type value: %r\" % escape(ctype))\r\n except AttributeError:\r\n return CommentPostBadRequest(\r\n \"The given content-type %r does not resolve to a valid model.\" % \\\r\n escape(ctype))\r\n except ObjectDoesNotExist:\r\n return CommentPostBadRequest(\r\n \"No object matching content-type %r and object PK %r exists.\" % \\\r\n (escape(ctype), escape(object_pk)))\r\n except (ValueError, ValidationError) as e:\r\n return CommentPostBadRequest(\r\n \"Attempting go get content-type %r and object PK %r exists raised %s\" % \\\r\n (escape(ctype), escape(object_pk), e.__class__.__name__))\r\n\r\n # Do we want to preview the comment?\r\n preview = \"preview\" in data\r\n\r\n # Construct the comment form\r\n form = django_comments.get_form()(target, data=data)\r\n\r\n # Check security information\r\n if form.security_errors():\r\n return CommentPostBadRequest(\r\n \"The comment form failed security verification: %s\" % \\\r\n escape(str(form.security_errors())))\r\n\r\n # If there are errors or if we requested a preview show the comment\r\n if form.errors or preview:\r\n template_list = [\r\n # These first two exist for purely historical reasons.\r\n # Django v1.0 and v1.1 allowed the underscore format for\r\n # preview templates, so we have to preserve that format.\r\n \"comments/%s_%s_preview.html\" % (model._meta.app_label, model._meta.module_name),\r\n \"comments/%s_preview.html\" % model._meta.app_label,\r\n # Now the usual directory based template hierarchy.\r\n \"comments/%s/%s/preview.html\" % (model._meta.app_label, model._meta.module_name),\r\n \"comments/%s/preview.html\" % model._meta.app_label,\r\n \"comments/preview.html\",\r\n ]\r\n return render_to_response(\r\n template_list, {\r\n \"comment\": form.data.get(\"comment\", \"\"),\r\n \"form\": form,\r\n \"next\": data.get(\"next\", next),\r\n },\r\n RequestContext(request, {})\r\n )\r\n\r\n # Otherwise create the comment\r\n comment = form.get_comment_object()\r\n comment.ip_address = request.META.get(\"REMOTE_ADDR\", None)\r\n if request.user.is_authenticated():\r\n comment.user = request.user\r\n\r\n # Signal that the comment is about to be saved\r\n responses = signals.comment_will_be_posted.send(\r\n sender=comment.__class__,\r\n comment=comment,\r\n request=request\r\n )\r\n\r\n for (receiver, response) in responses:\r\n if response == False:\r\n return CommentPostBadRequest(\r\n \"comment_will_be_posted receiver %r killed the comment\" % receiver.__name__)\r\n\r\n # Save the comment and signal that it was saved\r\n comment.save()\r\n signals.comment_was_posted.send(\r\n sender=comment.__class__,\r\n comment=comment,\r\n request=request\r\n )\r\n\r\n return next_redirect(request, fallback=next or 'comments-comment-done',\r\n c=comment._get_pk_val())","title":""},{"docid":"1bee138e51bed7498a8c981fb91a695f","score":"0.5714569","text":"def quick_url(comment):\n\n def to_id(fullname):\n return fullname.split(\"_\", 1)[1]\n\n return \"http://www.reddit.com/r/{}/comments/{}/_/{}?context=3\".format(\n comment.subreddit.display_name, to_id(comment.link_id), comment.id\n )","title":""},{"docid":"fae50ed823edcc7a7d1d6ae900d5b806","score":"0.57140905","text":"def get(self, post_id):\r\n if not self.user:\r\n self.redirect('/blog/login?error=You need to be logged')\r\n return\r\n else:\r\n key = db.Key.from_path('Blog', int(post_id))\r\n post = db.get(key)\r\n if not post:\r\n self.error(404)\r\n return\r\n user = post.user\r\n loggedUser = self.user\r\n if user == loggedUser:\r\n key = db.Key.from_path('Blog', int(post_id))\r\n post = db.get(key)\r\n error = \"\"\r\n self.render(\"editpost.html\", subject=post.subject,\r\n content=post.content, post_id=post_id,\r\n error=error)\r\n else:\r\n error = \"You can't edit this post\"\r\n self.render(\"error.html\", error=error)","title":""},{"docid":"663c1d8648303fcd021c55e8a906cf30","score":"0.5698372","text":"def add_comment_to_post(request, pk):\n post = get_object_or_404(Post, pk=pk)\n if request.method == \"POST\":\n form = CommentForm(request.POST)\n if form.is_valid():\n comment = form.save(commit=False)\n comment.post = post\n comment.save()\n return redirect('blog-post', pk=post.id)\n else:\n form = CommentForm()\n return render(request, 'add_comment_to_post.html', {'form': form})","title":""},{"docid":"af2a8d546f001eba74bd1bee97d966ed","score":"0.56928205","text":"def detail_post_view(session: Session, post_id: IdType) -> typing.List[PostType]:\n post = session.query(Post).get(post_id)\n\n if not post:\n return Response({'message': 'Post does not exist'}, status=204)\n else:\n post_data = dict(\n id=post.id,\n author_id=post.author_id,\n title=post.title,\n content=post.content,\n created_at=post.created_at.strftime(format='%Y-%m-%d %H:%M'),\n )\n return {'data': post_data}","title":""},{"docid":"7fdbe1ea50ca2ca3968768f0fe5590c4","score":"0.56762093","text":"def feature_details(request, pk):\n feature = get_object_or_404(Feature, pk=pk)\n comments = FeatureComment.objects.filter(feature=feature)\n return render(request, \"feature_details.html\", {'feature': feature, 'comments': comments})","title":""},{"docid":"ea10d8ed339a3bd1192b51cb0137c990","score":"0.5670916","text":"def check_comment(post_id, comment_id, check_author=True):\n\n db = get_db()\n\n comment = get_comment_of_post(db, post_id, comment_id)\n if comment is None:\n abort(404, \"Comment id {0} doesn't exist.\".format(comment_id))\n\n current_user = get_user_by_username(db, request.authorization[\"username\"])\n if check_author and comment[\"author_id\"] != current_user[\"id\"]:\n abort(403)\n\n return comment","title":""},{"docid":"74b91df995a745dd9214f66b529be32e","score":"0.5634377","text":"def post_detail(request, pk):\n post = get_object_or_404(Feedback, pk=pk)\n post.save()\n return render(request, \"feedbackdetail.html\", {\"post\":post})","title":""},{"docid":"ad72f193d51a44406eef966f0d461d8d","score":"0.5633675","text":"def add_comment(self, post):\n if self.user:\n comment_content = self.request.get('comment')\n if comment_content:\n comment = CommentEntity.register(user=self.user,\n post=post,\n comment=comment_content)\n CommentEntity.commit_comment(comment)\n return self.redirect('/{0}/{1}'.format('post',\n post.key().id()))\n\n self.redirect('/login')","title":""},{"docid":"c2b8f4fc62acdeaae105bce80552942d","score":"0.56218356","text":"def get(self, post_id):\n if self.user_id:\n params, user_info = disclaim(self)\n else:\n params = {} \n params['captchahtml'] = captchaBase(self)\n blog = models.BlogPost.get_by_id(long(post_id))\n if blog is not None:\n params['title'] = blog.title\n params['subtitle'] = blog.subtitle\n params['blob_key'] = blog.blob_key\n params['author'] = blog.author\n params['content'] = blog.content\n return self.render_template('materialize/landing/blogpost.html', **params)\n else:\n return self.error(404)","title":""},{"docid":"e6e46599cb7cdbfc08739013f522a6bb","score":"0.56055665","text":"def post(self, post_id):\n comment = request.form.get('comment')\n\n post = Post.get_by_id(post_id)\n post.comments.append(Comment(session.get('user_id'), post.id, comment))\n\n db.session.commit()\n\n return redirect(url_for('blog.post', post_id=post_id))","title":""},{"docid":"5357134e62722ca8f07e6e42f10dd1b0","score":"0.5603172","text":"def GetComment(self):\r\n pass","title":""},{"docid":"3073a414630f0449af65e90de18c7401","score":"0.55794376","text":"def representative_comment(self):\n p = self.root_posts\n if len(p) == 0:\n return None\n return p[0]","title":""},{"docid":"0156caa4dcd7416014144af7a52818b7","score":"0.55773926","text":"def show_movie(request, movie_slug):\n context_dict = {}\n \n\t# Attempt to retrieve the data to be displayed on the movies page\n try:\n movie = Movie.objects.get(slug=movie_slug)\n comments = Comment.objects.filter(movie=movie)\n\n context_dict['movie'] = movie\n\n context_dict['comments'] = sort_comments(comments)\n movie.views = movie.views + 1\n movie.save()\n\n\t\t# If the user is logged in allow them to comment and reply to comments\n if request.user.is_authenticated:\n author = UserProfile.objects.filter(\n user=request.user)[0]\n\n form = CommentForm(\n author=author,\n parent=None,\n movie=movie)\n\n context_dict['form'] = form\n\n else:\n context_dict['form'] = None\n\n\t# if the user posts the comment form\n if request.method == \"POST\":\n form = CommentForm(\n request.POST,\n author=author,\n parent=None,\n movie=movie)\n\t\t\t\n if form.is_valid():\n comment = form.save(commit=False)\n comment.save()\n request.method=\"GET\"\n return show_movie(request, movie_slug)\n\n else:\n print(form.errors)\n \n except Movie.DoesNotExist:\n context_dict['movie'] = None\n context_dict['comments'] = None\n context_dict['form'] = None\n\n return render(request, \n 'rate_my_movie_app/movie.html',\n context_dict)","title":""},{"docid":"d1d3c7fde4f8927ee58438241c2b6b73","score":"0.5576925","text":"def show_comments(item_format=' - {timestamp} -> {text} .::. {_ts}', admin_fmt=True, **kwargs):\n print('\\n'.join(get_comments(item_format=item_format, admin_fmt=admin_fmt, **kwargs)))","title":""},{"docid":"f1e860f91b2b7b1f367cf1d0028de4fa","score":"0.55709225","text":"def post_details(request, slug, post_pk):\n post, post_url = get_redirected(models.Post, {'pk': post_pk}, {'slug': slug})\n # return render(request, 'blog/post_details.html', {'post': post })\n if post_url:\n return HttpResponseRedirect(post_url)\n\n return render(request, 'blog/post_details.html', {'post': post})","title":""},{"docid":"747affcc5d5fbc52191a99b7a9ffa0b4","score":"0.5570872","text":"def get(self):\n\t\t# getting the numbers of all post comment\n\t\tpost_numdata_comments = numdata_comments_all_post()\n\t\t# getting the hottest comment\n\t\thottest_posts = hottest_dic(post_numdata_comments, 5)\n\t\t# getting all the numbers of comments by the category\n\t\t# ordering\n\t\t# data structure of this behavior\n\t\t# idpost\t\t\t\tnumber of comments, postentity\n\t\t# [('5710932114145280', [6, <models.blog_model.Blog object at 0x04428110>])\n\t\thottest_posts = sort_dictionary_desc(hottest_posts)\n\t\thottest_category = count_comments_by_category(post_numdata_comments)\n\t\thottest_category = hottest_dic(hottest_category, 5)\n\t\thottest_category = sort_dictionary_desc(hottest_category)\n\t\tlogging.error(hottest_category)\n\t\t\n\t\tself.render(\"hottest.html\", hottest_posts = hottest_posts, hottest_category = hottest_category)","title":""},{"docid":"18bd0b6db5005190a4b039255612e138","score":"0.5568248","text":"def show_article(request, article_id):\n posts = Post.objects.filter(article=article_id).order_by(\"created\")\n article = Article.objects.get(pk=article_id)\n return render(request, 'articles/article.html', {'posts': posts, 'article': article})","title":""},{"docid":"2cc3362e9e62a7119e7aa873d03193d1","score":"0.55588794","text":"def blogpost(request, slug):\n assert isinstance(request, HttpRequest)\n\n post_current = Post.objects.get(slug=slug) # запрос на выбор конкретной статьи по параметру\n comments = Comment.objects.filter(post=post_current)\n\n if request.method == \"POST\": # после отправки данных формы на сервер методом POST\n commentform = CommentForm(request.POST)\n\n if commentform.is_valid():\n comment_f = commentform.save(commit=False)\n comment_f.author = request.user # добавляем (так как этого поля нет в форме) в модель Комментария (Comment) в поле автор авторизованного пользователя\n comment_f.date = datetime.now() # добавляем в модель Комментария (Comment) текущую дату\n comment_f.post = post_current # Blog.objects.get(id=parametr) # добавляем в модель Комментария (Comment) статью, для которой данный комментарий\n comment_f.save() # сохраняем изменения после добавления полей\n\n return redirect('blogpost', slug=post_current.slug) # переадресация на ту же страницу статьи после отправки комментария\n\n else:\n commentform = CommentForm() # создание формы для ввода комментария\n\n data = {\n \"title\": post_current.title,\n 'post_current': post_current, # передача конкретной статьи в шаблон веб-страницы\n 'comments': comments,\n \"src\": '/media',\n 'image': post_current.image,\n 'commentform': commentform, # передача формы добавления комментария в шаблон веб-страницы\n 'year':datetime.now().year,\n }\n\n return render(request, 'blog/blogpost.html', data)","title":""},{"docid":"1fb0fba1fb39c954587f4c1878fdff2c","score":"0.5558202","text":"def render_post(id):\n return render_template(\"blog/post.html\", post=_get_post(id))","title":""},{"docid":"c12e42a1c60651c6789835aa21da038d","score":"0.5544281","text":"def add_comment(request, post_id, username):\n form = CommentForm(request.POST or None)\n if form.is_valid():\n post = get_object_or_404(Post, author__username=username, id=post_id)\n comment = form.save(commit=False)\n comment.post = post\n comment.author = request.user\n comment.save()\n return redirect(\"post\", username, post_id)","title":""},{"docid":"5ef6fa3b926f7136631aabd7573a6f76","score":"0.55422664","text":"def extract_random_comment(post, min_length=None):\n url = '%s.json?sort=random' % post['permalink'].rstrip('/')\n r = get(url)\n r.raise_for_status()\n j = r.json()\n comments = [c for c in j[1]['data']['children'] if 'body' in c['data']]\n if min_length:\n comments = [c for c in comments if len(c['data']['body']) >= min_length]\n if len(comments) > 0:\n global last_url\n last_url = normify_url(url)\n return comments[0]\n else:\n raise APIError('The selected post doesn\\'t have any comments')","title":""},{"docid":"5750a522894d6c3ca658308f7dfc74e8","score":"0.5538344","text":"def printPost(pid):\n query = ''' SELECT * FROM posts WHERE lower(pid)=?'''\n cursor.execute(query, (pid,))\n post = cursor.fetchone()\n connection.commit()\n\n Type = typeOfPost(pid)\n print('-' * 25 + 'Post Details' + '-' * 24)\n print('<'+Type.upper()+'Post>')\n print('Post ID: {}'.format(pid))\n print('Post date: {}'.format(post[1]))\n print('Post title: {}'.format(post[2]))\n print('Post body: {}'.format(post[3]))\n print('Poster: {}'.format(post[4]))\n print('-' * 60)","title":""},{"docid":"b805d7da964562b118dba51972d0a22a","score":"0.5532694","text":"def get_context_data(self, **kwargs):\n context = super(CommentCreate, self).get_context_data(**kwargs)\n # Call the base implementation first to get a context\n context['post'] = get_object_or_404(Post, slug = self.kwargs['slug'])\n # Get the post from id and add it to the context\n return context","title":""},{"docid":"173e1acdc2329e24cf58692ed1234c12","score":"0.55315","text":"def add_comment(request, slug):\n #print(\"looool\")\n p = request.POST\n\n if p[\"content\"]:\n author = \"Anonymous\"\n if p[\"author\"]: author = p[\"author\"]\n\n comment = Comment(post=Post.objects.get(slug=slug))\n cf = CommentForm(p, instance=comment)\n cf.fields[\"author\"].required = False\n\n comment = cf.save(commit=False)\n comment.author = author\n comment.save()\n return HttpResponseRedirect(reverse(\"blog.views.post\", args=[slug]))","title":""},{"docid":"bb932d93b732c09857387552fb26fea6","score":"0.55157614","text":"def comment(self, comment_text, email=\"\", name=\"\", pseud=None):\n \n if self.id is None:\n return self._work.comment(comment_text, email, name, pseud)\n \n if not self.loaded:\n raise utils.UnloadedError(\"Chapter isn't loaded. Have you tried calling Chapter.reload()?\")\n \n if self._session is None:\n raise utils.AuthError(\"Invalid session\")\n \n if self.id is not None:\n return utils.comment(self, comment_text, self._session, False, email=email, name=name, pseud=pseud)","title":""},{"docid":"e3e5d0eff498c13ff561e3f4e63a32cf","score":"0.55125606","text":"async def meme(self, ctx: commands.Context):\n subreddit = await self.config.guild(ctx.guild).subreddit()\n async with self.session.get(\n f\"https://www.reddit.com/{subreddit}/top.json?sort=new\"\n ) as resp:\n data = await resp.json()\n data = data[\"data\"]\n children = data[\"children\"]\n post = random.choice(children)[\"data\"]\n title = post[\"title\"]\n url = post[\"url_overridden_by_dest\"]\n link_url = f'https://reddit.com{post[\"permalink\"]}'\n ups = post[\"ups\"]\n comnts = post[\"num_comments\"]\n\n if post[\"over_18\"] is True:\n return await ctx.send(\n \"Cannot show content because it is nsfw,\"\n \" try changing the subreddit lol.\"\n )\n\n embed = (\n discord.Embed(title=title, url=link_url)\n .set_image(url=url)\n .set_footer(text=\"👍 {} | 💬 {}\".format(ups, comnts))\n )\n await ctx.send(embed=embed)","title":""},{"docid":"ed82cab84b16e1b0dfb3e9b6189891fa","score":"0.55006695","text":"def post_detail(request, year, month, day, slug):\r\n tt = time.strptime('-'.join([year, month, day]), '%Y-%b-%d')\r\n date = datetime.date(*tt[:3])\r\n try:\r\n post = Post.objects.published().get(slug=slug, pub_date__year=date.year, \r\n pub_date__month=date.month, pub_date__day=date.day)\r\n except Post.DoesNotExist:\r\n raise Http404\r\n \r\n return render_with_context(request, 'blog/post_detail.xhtml', {\r\n 'post': post,\r\n 'title': post.title, \r\n })","title":""},{"docid":"f9692cbb2827b959e5f57229a876b723","score":"0.54891664","text":"async def set_comment(self, ctx: commands.Context, *, comment: str = None):\n await sql.execute(\"UPDATE servers SET comment=? WHERE serverid=?\", comment, str(ctx.message.guild.id))\n em = discord.Embed(colour=discord.Colour.dark_green())\n if comment:\n em.title = f\"Successfully changed comment symbol to `{comment}`.\"\n else:\n em.title = \"Successfully removed comment symbol.\"\n await ctx.send(embed=em)","title":""},{"docid":"5a4539cc9e588fc2cfdf4ecca0054286","score":"0.54857767","text":"def post_comment(request, next=None):\n\n # Require POST\n if request.method != 'POST':\n return http.HttpResponseNotAllowed([\"POST\"])\n\n is_ajax = request.POST.get('is_ajax') and '_ajax' or ''\n\n # Fill out some initial data fields from an authenticated user, if present\n data = request.POST.copy()\n\n if request.user.is_authenticated():\n if not data.get('name', ''):\n data[\"name\"] = request.user.get_full_name()\n if not data.get('email', ''):\n data[\"email\"] = request.user.email\n\n # Look up the object we're trying to comment about\n ctype = data.get(\"content_type\")\n object_pk = data.get(\"object_pk\")\n parent_pk = data.get(\"parent_pk\")\n parent_comment = None\n if ctype is None or object_pk is None:\n return CommentPostBadRequest(\"Missing content_type or object_pk field.\")\n try:\n model = models.get_model(*ctype.split(\".\", 1))\n target = model._default_manager.get(pk=object_pk)\n if parent_pk:\n parent_comment = MpttComment.objects.get(pk=parent_pk)\n except TypeError:\n return CommentPostBadRequest(\n \"Invalid content_type value: %r\" % escape(ctype))\n except AttributeError:\n return CommentPostBadRequest(\n \"The given content-type %r does not resolve to a valid model.\" % \\\n escape(ctype))\n except MpttComment.DoesNotExist:\n return CommentPostBadRequest(\n \"Parent comment with PK %r does not exist.\" % \\\n escape(parent_pk))\n except ObjectDoesNotExist:\n return CommentPostBadRequest(\n \"No object matching content-type %r and object PK %r exists.\" % \\\n (escape(ctype), escape(object_pk)))\n\n # Do we want to preview the comment?\n preview = data.get(\"submit\", \"\").lower() == \"preview\" or \\\n data.get(\"preview\", None) is not None\n\n # Construct the comment form\n form = MpttCommentForm(target, parent_comment=parent_comment, data=data)\n\n # Check security information\n if form.security_errors():\n return CommentPostBadRequest(\n \"The comment form failed security verification: %s\" % \\\n escape(str(form.security_errors())))\n\n # If there are errors or if we requested a preview show the comment\n if form.errors or preview:\n template_list = [\n \"comments/%s_%s_preview%s.html\" % tuple(str(model._meta).split(\".\") + [is_ajax]),\n \"comments/%s_preview%s.html\" % (model._meta.app_label, is_ajax),\n \"comments/preview%s.html\" % is_ajax\n ]\n return render_to_response(\n template_list, {\n \"comment\" : form.data.get(\"comment\", \"\"),\n \"form\" : form,\n \"allow_post\": not form.errors\n },\n RequestContext(request, {})\n )\n\n # Otherwise create the comment\n comment = form.get_comment_object()\n comment.ip_address = request.META.get(\"REMOTE_ADDR\", None)\n if request.user.is_authenticated():\n comment.user = request.user\n\n # Signal that the comment is about to be saved\n responses = signals.comment_will_be_posted.send(\n sender = comment.__class__,\n comment = comment,\n request = request\n )\n\n for (receiver, response) in responses:\n if response == False:\n return CommentPostBadRequest(\n \"comment_will_be_posted receiver %r killed the comment\" % receiver.__name__)\n\n # Save the comment and signal that it was saved\n comment.save()\n signals.comment_was_posted.send(\n sender = comment.__class__,\n comment = comment,\n request = request\n )\n\n if is_ajax:\n data['next'] = None\n\n return next_redirect(data, next, 'comments_comment_done%s' % (is_ajax and '_ajax' or ''), c=comment._get_pk_val())","title":""},{"docid":"c3393ccc0ff923e37df4edc8880205e0","score":"0.5463447","text":"def test_issues_id_comments_issue_comment_id_post(self):\n pass","title":""},{"docid":"8eaeb2d2cfb921f90c66a034872c0b6f","score":"0.54462004","text":"def show_article(request, username, permalink):\n\n try:\n user = User.objects.get(username__iexact=username)\n except User.DoesNotExist:\n raise Http404\n\n try:\n # there should be always only one of those\n article = UserActivity.objects.select_related().get(\n username__iexact = username,\n post__permalink = permalink,\n status = UserActivity.PUBLIC_STATUS)\n except UserActivity.DoesNotExist:\n # check for draft articles\n articles = UserActivity.objects.select_related().filter(\n username__iexact = username, \n post__permalink = permalink,\n status = UserActivity.DRAFT_STATUS)\n if len(articles)==0:\n raise Http404\n else:\n article = articles[0] \n # show draft only if currently logged in user is viewing\n if (not request.user.is_superuser) and (request.user != user):\n raise Http404\n\n data = {\n 'activity' : article,\n 'user_profile': user,\n }\n\n return render(\n request,\n templates['ARTICLE'],\n data,\n )","title":""},{"docid":"b461cd019185f21f700becac53a9d450","score":"0.5431777","text":"def comment_handler(sender, instance, created, **kwargs):\n recipients = []\n if instance.parent and instance.parent.author != instance.author:\n # comment is part of a thread\n parent_comment_author = instance.parent.author\n recipients.append(parent_comment_author)\n comment_author = instance.author\n article = instance.article\n desc_string = \"{} posted a comment to {} on {}\"\n article_author = article.author\n if article_author.id != comment_author.id:\n recipients.append(article_author)\n url = reverse(\n \"articles:article-details\", args=[article.slug])\n resource_url = f\"{settings.DOMAIN}{url}\"\n\n notify.send(comment_author,\n recipient=recipients,\n description=desc_string.format(comment_author.username,\n article or instance,\n instance.created_at.strftime('%d-%B-%Y %H:%M')), # noqa\n verb=verbs.COMMENT_CREATED,\n target=article or instance,\n action_object=instance,\n resource_url=resource_url)","title":""},{"docid":"2eb07e6bfbb75ae544755f38237d11c4","score":"0.5428052","text":"def test_post_view_with_permalink(self):\n reset_db()\n p = create_post_with_comments()\n c = Client()\n response = c.get(reverse('blog.views.post_view', args=[p.permalink] ) )\n self.assertEqual(response.status_code, 200, 'Expected 200.')\n self.assertEqual(response.context['post'].id, p.id, 'Mismatch on post ids.')","title":""},{"docid":"41805d8194b675b04493a8233966397e","score":"0.5425533","text":"def test_single_post_view(self):\n reset_db()\n p = create_post_with_comments()\n c = Client()\n response = c.get('/post/%s/%s' % (p.id, p.permalink) )\n self.assertEqual(response.status_code, 200, 'HTTP error.')\n self.assertIsNotNone(response.context['post'], 'No post returned.')","title":""}],"string":"[\n {\n \"docid\": \"90b5fce23163cc1947185be27a583845\",\n \"score\": \"0.7372231\",\n \"text\": \"def post_detail(request, id):\\n post = Post.objects.get(id=id)\\n return render(request, 'comment/post_detail.html', {'post': post})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c7bd1ff09b7932f489e77bb54fe2afb7\",\n \"score\": \"0.7263986\",\n \"text\": \"def view_post(request, post_id):\\n post = get_object_or_404(Post, id=post_id)\\n comment_form = CommentForm()\\n return render(request, 'view_post.html', {\\n 'post': post,\\n 'comment_form' : comment_form\\n })\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6d1c6f3636bd133d4ec45f8d970aa820\",\n \"score\": \"0.71852803\",\n \"text\": \"def view_post(post_id):\\n post = dbmodel.Post.query.get_or_404(post_id)\\n comments = dbmodel.Comment.query.filter_by(parent_post_id=post_id)\\n return render_template('post.html', post=post, comments=comments)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8bc9074f80fa2da6473f3f6d35397ef8\",\n \"score\": \"0.7105406\",\n \"text\": \"def get(self, post):\\n if not self.user:\\n return self.redirect('/login')\\n\\n post_comments = post.get_all_comments()\\n if not post_comments:\\n post_comments = []\\n return self.render('post.html', post=post, post_comments=post_comments)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"38e1e370a77939dffb733075ce0e8821\",\n \"score\": \"0.6943954\",\n \"text\": \"def get(self, post_id):\\n if self.user:\\n self.render(\\\"blog_newcomment_page.html\\\")\\n else:\\n self.redirect(\\\"/login\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4a50712a72eba1764a71c5ca05e82be2\",\n \"score\": \"0.68175966\",\n \"text\": \"def show_post(post_id):\\n\\n post = Post.query.get(post_id)\\n\\n return render_template('post.html', post=post)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2746b2faffaf877560839a959cd41301\",\n \"score\": \"0.6796878\",\n \"text\": \"def show_post(post_id):\\n post = Post.query.get_or_404(post_id)\\n return render_template(\\\"/post_details.html\\\", post=post)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"441de05e103f9c735b95d721a066f112\",\n \"score\": \"0.6696225\",\n \"text\": \"def get(self, post_key):\\n form = CommentForm()\\n is_liked = Like.is_liked_by_user(self.user, self.post)\\n\\n self.render_viewpost(form, is_liked)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6981d4e2937bc56aa985e2bbca20128e\",\n \"score\": \"0.66875017\",\n \"text\": \"def show_post_details(post_id):\\n\\n post = Post.query.get_or_404(post_id)\\n\\n return render_template('posts/post.html', post= post)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5bbe9542b66267bf480f0dbbe09cb86c\",\n \"score\": \"0.6674287\",\n \"text\": \"def post(self, post_id):\\n\\n logging.info(\\\"comment\\\")\\n if not self.user:\\n self.redirect('/blog')\\n return\\n\\n content = self.request.get(\\\"content\\\")\\n user = self.user.name\\n key = db.Key.from_path('Post', int(post_id), parent=blog_key())\\n # blogpost = db.get(key)\\n logging.info(user)\\n\\n #escaping the html to avoid xss\\n escaped_cont = cgi.escape(content)\\n\\n if content and user:\\n comment = Comments(content=escaped_cont, user=user, post=int(post_id))\\n comment.put()\\n\\n self.redirect('/blog/%s' % str(post_id))\\n else:\\n error = \\\"Comment not included\\\"\\n self.render(\\\"blog_newcomment_page.html\\\", content=content, error=error)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3e04684dcce46a0dee36a9db311807e5\",\n \"score\": \"0.6658497\",\n \"text\": \"def post_comment_on_fly(request):\\n if request.method == 'GET':\\n post_pk = request.GET['post_pk']\\n comment_details = request.GET['comment_details']\\n post = get_object_or_404(models.Post, pk=post_pk)\\n comment = models.Comment.objects.create(post=post, detail=comment_details)\\n date_time = comment.created_date.strftime(\\\"%B %d, %Y %H:%M %p\\\")\\n body = \\\"\\\"\\\"\\n <div class=\\\"comment\\\">\\n <div class=\\\"date\\\">\\n %s\\n </div>\\n <p>%s : by <strong>%s</strong></p>\\n \\\"\\\"\\\" % (date_time, comment.detail, comment.post.author)\\n return HttpResponse(body)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ae991de82c3276d932448bd15b943e45\",\n \"score\": \"0.6642535\",\n \"text\": \"def post_detail(request, pk):\\n\\n post = get_object_or_404(Post, pk=pk)\\n post.views += 1\\n post.save()\\n\\n post_comments = PostComment.objects.filter(\\n post_id=post.id).order_by('-date_commented')\\n\\n if request.method == 'POST':\\n create_comment_form = PostComment(\\n comment_detail=request.POST.get('comment_detail'),\\n user=request.user,\\n post=post\\n )\\n create_comment_form.save()\\n messages.success(request, 'Comment added to Post')\\n return redirect('post_detail', pk)\\n\\n context = {\\n 'post': post,\\n 'form': AddComment,\\n 'comments': post_comments\\n }\\n return render(request, \\\"blog/postdetail.html\\\", context)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5b22f4522434446a6820d638817bf23d\",\n \"score\": \"0.6613093\",\n \"text\": \"def comment(request, blog_id):\\n blog = get_object_or_404(Blog, pk=blog_id)\\n return render_to_response('comment.html', \\n {'comments': blog.comment_set.all(), 'blog': blog})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ebc602237fbd1157a569f561a09da587\",\n \"score\": \"0.6592421\",\n \"text\": \"def detail(request, post_id):\\n post = get_object_or_404(Post, pk=post_id)\\n comments = post.comments.all()\\n new_comment = None\\n\\n if request.method == 'POST':\\n comment_form = CommentForm(request.POST)\\n if comment_form.is_valid() and request.user.is_authenticated:\\n new_comment = comment_form.save(commit=False)\\n new_comment.post = post\\n new_comment.author = request.user\\n new_comment.save()\\n messages.success(request, 'Comment added successfully!')\\n return redirect(reverse('article-detail', args=[post.id]))\\n else:\\n messages.error(request, 'Please check the form for errors. \\\\\\n Comment failed to post.')\\n else:\\n comment_form = CommentForm()\\n\\n template = 'article_details.html'\\n\\n context = {\\n 'post': post,\\n 'comments': comments,\\n 'comment_form': comment_form,\\n 'new_comment': new_comment,\\n }\\n\\n return render(request, template, context)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"42ddd5c1a8cc3be0762e3a3bc4f193d6\",\n \"score\": \"0.6575711\",\n \"text\": \"def post_detail(request, year, month, day, post):\\n post = get_object_or_404(Post, slug=post,\\n status='published',\\n publish__year=year,\\n publish__month=month,\\n publish__day=day)\\n\\n # lista de comentarios para este post\\n comments = post.comments.filter(active=True) # recupera todos comentários ativos\\n\\n new_comment = None\\n\\n if request.method == \\\"POST\\\":\\n comment_form = CommentForm(data=request.POST)\\n if comment_form.is_valid():\\n new_comment = comment_form.save(commit=False)\\n new_comment.post = post\\n new_comment.save()\\n\\n else:\\n comment_form = CommentForm()\\n\\n #lista de posts similares\\n post_tags_id = post.tags.values_list('id', flat=True)\\n\\n similar_posts = Post.published.filter(tags__in=post_tags_id)\\\\\\n .exclude(id=post.id)\\n similar_posts = similar_posts.annotate(same_tags=Count('tags'))\\\\\\n .order_by('-same_tags','-publish')[:4]\\n\\n\\n return render(request, path_detalhe, {'post':post,\\n 'comments':comments,\\n 'new_comment':new_comment,\\n 'comment_form':comment_form,\\n 'similar_posts':similar_posts})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"86c1a78f0f800b7a252a3375b7267dfd\",\n \"score\": \"0.65154254\",\n \"text\": \"def show_post(index):\\r\\n requested_post = None\\r\\n for blog_post in post_objects:\\r\\n if blog_post.id == index:\\r\\n requested_post = blog_post\\r\\n return render_template(\\\"post.html\\\", post=requested_post)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9803868473e014f9b0bd143b9b92a24b\",\n \"score\": \"0.65096605\",\n \"text\": \"def post_comment(request, post_pk):\\n post = get_object_or_404(models.Post, pk=post_pk)\\n form = forms.CommentForm()\\n if request.method == 'POST':\\n form = forms.CommentForm(request.POST)\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.post = post\\n comment.save()\\n\\n return HttpResponseRedirect(post.get_absolute_url())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"eb428f9e3fa1c8e15115e616a7be65d2\",\n \"score\": \"0.6491254\",\n \"text\": \"def post_show(request, pid):\\n user = request.user\\n\\n # populate the session data\\n sess = middleware.Session(request)\\n tab = \\\"posts\\\"\\n pill = sess.get_tab()\\n \\n auth = user.is_authenticated()\\n layout = settings.USER_PILL_BAR if auth else settings.ANON_PILL_BAR\\n \\n params = html.Params(tab=tab, pill=pill, layout=layout)\\n \\n query = get_post_manager(request)\\n\\n try:\\n root = query.get(id=pid)\\n if not root.top_level:\\n return html.redirect( root.get_absolute_url() )\\n\\n # update the views for the question\\n models.update_post_views(post=root, request=request, minutes=const.POST_VIEW_UPDATE)\\n counts = sess.get_counts()\\n \\n except models.Post.DoesNotExist, exc:\\n messages.warning(request, 'The post that you are looking for does not exists. Perhaps it was deleted!')\\n return html.redirect(\\\"/\\\")\\n \\n # get all answers to the root\\n children = models.Post.objects.filter(root=root).exclude(type=POST_COMMENT, id=root.id).select_related('author', 'author__profile').order_by('-accepted', '-score', 'creation_date')\\n \\n # comments need to be displayed by creation date\\n comments = models.Post.objects.filter(root=root, type=POST_COMMENT).select_related('author', 'author__profile').order_by('creation_date')\\n\\n all = [ root ] + list(children) + list(comments)\\n # add the various decorators\\n \\n models.decorate_posts(all, user)\\n \\n # may this user accept answers on this root\\n accept_flag = (user == root.author)\\n \\n # these are all the answers\\n answers = [ o for o in children if o.type == POST_ANSWER ]\\n for a in answers:\\n a.accept_flag = accept_flag\\n \\n # get all the comments\\n tree = defaultdict(list)\\n for comment in comments: \\n tree[comment.parent_id].append(comment)\\n \\n # generate the tag cloud\\n #tags = models.Tag.objects.all().order_by('-count')[:50]\\n \\n return html.template( request, name='post.show.html', root=root, answers=answers, tree=tree, params=params, counts=counts)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2c8969424c554f552f3d0fff1277bd13\",\n \"score\": \"0.64574575\",\n \"text\": \"def post_comment(self):\\n slug = str(self.article.slug)\\n url = reverse(\\\"articles:comment\\\", args=[slug])\\n return self.client.post(\\n url, self.comment\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3da2d9f2dc3faae054ae941f4b649911\",\n \"score\": \"0.64555997\",\n \"text\": \"def display_post(post_id):\\n\\n post = Post.query.get(post_id)\\n\\n return render_template('post_details.html', post=post)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c260ed4702864ab81be87afb457f3b19\",\n \"score\": \"0.6418798\",\n \"text\": \"def show_wall_post(request, username, post_id):\\n\\n try:\\n wall_post = UserActivity.objects.select_related().get(\\n short_review__id = post_id,\\n username__iexact = username,\\n status = UserActivity.PUBLIC_STATUS)\\n except UserActivity.DoesNotExist:\\n raise Http404\\n\\n try:\\n user = User.objects.get(username__iexact=username)\\n except User.DoesNotExist:\\n raise Http404\\n\\n data = {\\n 'activity' : wall_post,\\n 'user_profile': user\\n }\\n\\n return render(\\n request,\\n templates['WALL_POST'],\\n data,\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"43416164e422f0829d7c89d459a53d3a\",\n \"score\": \"0.6390816\",\n \"text\": \"def view_post(post_id):\\n post = mongo.db.reviews.find_one({\\\"_id\\\": ObjectId(post_id)})\\n if post:\\n comments = list(mongo.db.comments.find(\\n {\\\"location_id\\\": post['location_id']}))\\n if 'user' in session:\\n fav_user = list(mongo.db.favourites.find(\\n {\\\"favourite_user\\\": session['user']}))\\n else:\\n fav_user = None\\n return render_template(\\n \\\"view_post.html\\\", post=post, comments=comments, fav_user=fav_user)\\n flash(\\\"Post does not exist\\\")\\n return redirect(url_for('get_locations'))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7b7848bded87fe53154eefa999865b45\",\n \"score\": \"0.6345191\",\n \"text\": \"def show_post(self, request: foundation.Request) -> foundation.Response:\\n\\n id = request.params['id']\\n\\n orm_session = orm.sessionmaker(bind=self.get_engine())()\\n\\n post = orm_session.query(models.Post).filter_by(id=id).one()\\n\\n return self.render2response(request, 'blog/show.html', post=post,\\n blog=self, url_for=self.url_for)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1dd4dd9dbb263f246a41cb257d4d2210\",\n \"score\": \"0.6344819\",\n \"text\": \"def view_post(request, post_id):\\n\\n def can_view_post(user, pid):\\n post_ = models.Post.objects.get(pk=pid)\\n for member in user.member_set.all():\\n if member.Organization_id == post_.Creator.Organization_id:\\n return True\\n return False\\n\\n post = models.Post.objects.get(pk=post_id)\\n if not post.Visible:\\n if can_view_post(request.user, post_id):\\n return render(request, 'view_post.html',\\n {'title': post.Title, 'Content': post.Content,\\n 'user': request.user,\\n 'loginable': request.user.is_authenticated()})\\n else:\\n return render(request, 'Error.html',\\n {'error_summary': 'Not visible',\\n 'error_details': 'You must have permission to view '\\n 'this post'})\\n else:\\n return render(request, 'view_post.html',\\n {'title': post.Title, 'Content': post.Content,\\n 'user': request.user,\\n 'loginable': request.user.is_authenticated()})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ae89532ae37ecf3280171bbcd3b8dcf1\",\n \"score\": \"0.6330918\",\n \"text\": \"def post_comment(source_post, parent):\\n try:\\n askbot_comment = source_post.get_author().post_comment(\\n parent_post = parent,\\n body_text = source_post.get_body_text(),\\n timestamp = source_post.created_at\\n )\\n return askbot_comment\\n except Exception, e:\\n msg = unicode(e)\\n print \\\"Warning: post %d skipped: %s\\\" % (source_post.post_id, msg)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7f3c284c4abc8719b29277d1027512a0\",\n \"score\": \"0.62737817\",\n \"text\": \"def post_comment(request, post_id):\\n if request.method == 'POST':\\n post = get_object_or_404(Post, id=post_id)\\n comment_form = CommentForm(request.POST)\\n if comment_form.is_valid():\\n comment = Comment(\\n body = comment_form.cleaned_data['body'],\\n date = datetime.now(),\\n post = post,\\n user = request.user\\n )\\n comment.save()\\n messages.info(request, 'Comment Posted!')\\n else:\\n messages.error(request, 'Invalid comment')\\n return HttpResponseRedirect(reverse('view_post', args=[post_id]))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"29f2bee9380e862dd2ae637eb7322945\",\n \"score\": \"0.6212544\",\n \"text\": \"def detail(id):\\n post = get_post(id, check_author=False)\\n comments = get_comments_for_post(post_id=id)\\n users_likes = get_users_liking_post(post_id=id)\\n\\n # Post existence is already checked in get_post\\n return render_template(\\n \\\"blog/detail.html\\\",\\n post=post,\\n comments=comments,\\n users_likes=users_likes\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8085d8f8ff6981e0109333af03ef8f2c\",\n \"score\": \"0.6203446\",\n \"text\": \"def blogDetailView(request, pk):\\n user = request.user\\n post_detail = get_object_or_404(BlogPost, pk=pk)\\n blogPostType = ContentType.objects.get(app_label='blog', model='blogpost')\\n res = LikesAndDislikes.objects.filter(content_type=blogPostType, object_id=pk)\\n num_of_likes = res.filter(like_type=False).count()\\n num_of_dislikes = res.filter(like_type=True).count()\\n\\n comments = Comment.objects.filter(content_type=blogPostType, object_id=pk)\\n\\n initial_data = {\\n 'user': user,\\n 'content': \\\"leave your comment here ~\\\",\\n 'content_type': blogPostType,\\n 'object_id': pk,\\n }\\n form = CommentForm(initial=initial_data)\\n\\n context = {\\n 'post_detail' : post_detail,\\n 'num_of_likes' : num_of_likes,\\n 'num_of_dislikes': num_of_dislikes,\\n 'liked': False,\\n 'disliked': False,\\n 'form': form,\\n 'comments': comments,\\n }\\n\\n is_done = LikesAndDislikes.objects.filter(\\n user=user,\\n content_type=blogPostType,\\n object_id=pk\\n )\\n\\n if is_done:\\n if is_done.get().like_type == False:\\n context['liked'] = True\\n else:\\n context['disliked'] = True\\n\\n return render(request, 'blog/post.html', context)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ba490370835895b27530e850d9cc9ab6\",\n \"score\": \"0.618974\",\n \"text\": \"def get(self, post_id):\\n blogpost_key = db.Key.from_path('BlogPost', int(post_id))\\n blogpost_post = db.get(blogpost_key)\\n content = blogpost_post.content\\n title = blogpost_post.title\\n self.render('edit.html', title=title, content=content)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2c92b6ae7b0d67da9e0626231a22a6cc\",\n \"score\": \"0.6186363\",\n \"text\": \"def view_post(request, post_id):\\n post = get_object_or_404(BlogPost, pk=post_id)\\n\\n template = 'blog/blog_post.html'\\n context = {\\n 'post': post\\n }\\n return render(request, template, context)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8c58e5ee5f08f1af57fda658f347fe71\",\n \"score\": \"0.6102145\",\n \"text\": \"def post_detail(request, id):\\n\\n post = get_object_or_404(Post, pk=id)\\n return render(request, \\\"postdetail.html\\\", {'post': post})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7c76e9439806fbd7aff6ace5cb7c0ab9\",\n \"score\": \"0.6096827\",\n \"text\": \"def showPost(self):\\n print(\\\"{} ──────────────────────────\\\".format(self.owner.name))\\n print(\\\"{:%d, %b %Y}\\\".format(self.timestamp))\\n print(\\\"{}\\\".format(self.content), end=\\\"\\\\n\\\\n\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a3abb50f740a2a601c2d51d2ed9ea94e\",\n \"score\": \"0.6087277\",\n \"text\": \"def blogpost(request, parametr):\\n assert isinstance(request, HttpRequest)\\n post_1 = Blog.objects.get(id=parametr)\\n comments = Comment.objects.filter(post=parametr)\\n \\n if request.method == \\\"POST\\\":\\n form = CommentForm(request.POST)\\n if form.is_valid():\\n comment_f = form.save(commit=False)\\n comment_f.author = request.user\\n comment_f.date = datetime.now()\\n comment_f.post = Blog.objects.get(id=parametr)\\n comment_f.save()\\n return redirect('blogpost', parametr=post_1.id) \\n else:\\n form = CommentForm() \\n \\n return render(\\n request,\\n 'app/blogpost.html',\\n \\n {\\n 'post_1': post_1,\\n 'comments': comments,\\n 'form': form,\\n 'year':datetime.now().year,\\n \\n }\\n \\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b9197dec82e3d1cde8819f6695d820d9\",\n \"score\": \"0.6073559\",\n \"text\": \"def _show_comments(self):\\n headers = {\\\"Authorization\\\": \\\"Token %s\\\" % cfg.koodous.token}\\n\\n try:\\n content_file = __sessions__.current.file.data\\n sha256 = hashlib.sha256(content_file).hexdigest()\\n except Exception:\\n self.log('error', 'You have no file loaded')\\n return\\n try:\\n url = '%s/%s/comments' % (cfg.koodous.base_url, sha256)\\n response = requests.get(url=url, headers=headers, proxies=cfg.koodous.proxies,\\n verify=cfg.koodous.verify, cert=cfg.koodous.cert)\\n\\n if response.json().get('count') == 0:\\n self.log('info', 'This sample has no comments.')\\n return\\n for result in response.json().get('results'):\\n self.log('info', \\\"[{}]: {}\\\".format(result['author']['username'], result['text']))\\n except Exception as err:\\n self.log('error', 'Network problem, please try again.')\\n log.error(\\\"Network problem, please try again: \\\\n{}\\\".format(err))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2d785282de48b6a4e8ec49022b1ca09a\",\n \"score\": \"0.60732067\",\n \"text\": \"def edit_comment(request, pk):\\n comment = get_object_or_404(Comment, pk=pk)\\n feed = comment.feed\\n \\n # Protecting the edit feed page.\\n if comment.user != request.user:\\n raise Http404\\n\\n if request.method != 'POST':\\n # Initial request; pre-fill form with the current entry\\n form = CommentForm(instance=comment)\\n else:\\n # POST data submitted; process data\\n form = CommentForm(instance=comment, data=request.POST)\\n if form.is_valid():\\n form.save()\\n messages.add_message(request, messages.SUCCESS, 'Comment updated')\\n return redirect('feed:feed_detail', pk=feed.pk)\\n\\n context = {'feed': feed, 'comment': comment, 'form': form}\\n return render(request, 'feed/edit_comment.html', context)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"00bbd84ada5ba6fa7732c1e6788dedd5\",\n \"score\": \"0.6059708\",\n \"text\": \"def post(self, post_id, comment_id):\\n comment = Comment.by_id(comment_id)\\n if self.user and self.user.name == comment.username:\\n save_clicked = self.request.get(\\\"save\\\")\\n cancel_clicked = self.request.get(\\\"cancel\\\")\\n delete_clicked = self.request.get(\\\"delete\\\")\\n\\n edited_comment = self.request.get(\\\"comment\\\")\\n\\n if save_clicked:\\n self.save_edit(edited_comment, comment, post_id)\\n elif cancel_clicked:\\n self.cancel_edit(post_id)\\n elif delete_clicked:\\n self.delete_edit(comment, post_id)\\n else:\\n self.redirect(\\\"/blog\\\")\\n else:\\n self.redirect(\\\"/blog\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"449041abfd9c0c35e65163dd4b2448b4\",\n \"score\": \"0.60335106\",\n \"text\": \"def post(self):\\n\\n # keep reference to the post page for redirection later\\n referrer = self.request.referer\\n post_id = referrer.split(\\\"/\\\")[-1]\\n\\n post = Post.by_id(post_id)\\n\\n comment_text = self.request.get(\\\"comment\\\")\\n self.write(comment_text)\\n if comment_text:\\n new_comment = Comment(post_id=post_id, username=self.user.name,\\n comment=comment_text)\\n new_comment.put()\\n self.redirect(referrer)\\n else:\\n # TODO should render page with error\\n self.redirect(referrer)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5da1fa25ec79aacc2972e2f5780268f4\",\n \"score\": \"0.60311145\",\n \"text\": \"def manage_comment():\\n page = request.args.get('page', 1, type=int)\\n logger.info('Visiting comment manage page {}.'.format(page))\\n pagination = Comment.query.order_by(Comment.timestamp.desc()).paginate(page,\\n per_page=current_app.config['FLASKY_POSTS_PER_PAGE'],\\n error_out=False)\\n comments = pagination.items\\n return render_template('manage_comment.html', comments=comments, pagination=pagination)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"77153d75906691e4cb26e341e493587e\",\n \"score\": \"0.6026122\",\n \"text\": \"def post(self):\\n if self.authenticated():\\n post_id = self.request.get('post_id')\\n post = Post.get_by_id(int(post_id))\\n comment_txt = self.request.get('comments')\\n comment = Comment(comment = comment_txt, commenter = self.user, post = post)\\n comment.put()\\n self.redirect('/blog/%s' % (post_id))\\n else:\\n self.login_redirect()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"435adb6c92bdce29612c05447271c8be\",\n \"score\": \"0.6018611\",\n \"text\": \"def show_edit_post_page(post_id):\\n\\n post = Post.query.get(post_id)\\n\\n return render_template('edit_post.html', post=post)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8a254a746c56282352dcc4740a1155ba\",\n \"score\": \"0.601529\",\n \"text\": \"def commentsindex(topic_id):\\n post = get_post(topic_id)\\n db = get_db()\\n postcoms = query_db(\\n \\\"SELECT * FROM postcomments p JOIN user u ON p.author_id=u.id WHERE topic_id = ?\\\",[topic_id]\\n )\\n return render_template(\\\"blog/commentsindex.html\\\", postcoms=postcoms, post=post)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6f7420a7dbd5f2dc7191672e8039fd45\",\n \"score\": \"0.60079324\",\n \"text\": \"def get_comment_by_id(self):\\n parent_comment = self.create_comment()\\n id = parent_comment.data['id']\\n return self.client.get(reverse(\\n \\\"articles:commentdetail\\\", args=[\\\"this-is-mine\\\", id]))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e9afdbc32d51a0bcf0c94198463f1105\",\n \"score\": \"0.6005923\",\n \"text\": \"def user_comment_post(sender, instance, *args, **kwargs):\\n comment = instance\\n post = comment.post\\n text_preview = comment.body[:90] #take only first 90 chars as a preview.\\n sender = comment.user\\n\\n notify = Notification(post=post, sender=sender, user=post.user, text_preview=text_preview, notification_type=2)\\n notify.save()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c6af3cdc773174518d36eb7596da5090\",\n \"score\": \"0.6001438\",\n \"text\": \"def show(request, slug):\\n\\ttry:\\n\\t\\tpage = Content.objects.get(slug=slug)\\n\\texcept Content.DoesNotExist:\\n\\t\\treturn render_to_response('pages/bug.html',\\n\\t\\t\\t{'bug': _('Page does not exist')},\\n\\t\\t\\tcontext_instance=RequestContext(request))\\n\\t\\n\\tadd_topic = False\\n\\tif page.coment_forum:\\n\\t\\trequest.forum_id = page.coment_forum.id\\n\\t\\tcoment_forum_id = page.coment_forum.id\\n\\t\\tperms = forumContext(request)\\n\\t\\tif perms['perms']['add_topic']:\\n\\t\\t\\tadd_topic = True\\n\\telif page.place and page.place.coment_forum:\\n\\t\\trequest.forum_id = page.place.coment_forum.id\\n\\t\\tcoment_forum_id = page.place.coment_forum.id\\n\\t\\tperms = forumContext(request)\\n\\t\\tif perms['perms']['add_topic']:\\n\\t\\t\\tadd_topic = True\\n\\t\\n\\tif add_topic and not page.coment_topic:\\n\\t\\tform = diamandaModelwrappers.AddTopicForm()\\n\\telif add_topic and page.coment_topic:\\n\\t\\tform = diamandaModelwrappers.AddPostForm()\\n\\telse:\\n\\t\\tform = False\\n\\t\\n\\tcomments = False\\n\\t# check if user wants to add a comment - show the form if possible\\n\\tif 'c' in request.GET:\\n\\t\\tshow_comment = True\\n\\t\\tif form and page.coment_topic:\\n\\t\\t\\tcomments = page.coment_topic.post_set.all().order_by('-id')[:10]\\n\\telse:\\n\\t\\tshow_comment = False\\n\\t\\n\\tif request.POST and add_topic and not page.coment_topic:\\n\\t\\tCOMMENT_POST = _('This is a discussion about article') + ': [url=/w/p/%s/]%s[/url].' % (page.slug, page.title)\\n\\t\\tREDIRECT = (\\\"/w/p/\\\" + slug +\\\"/?c=ok\\\", _('Comment added succesfuly.'))\\n\\t\\tTITLE = _('Comments for: %s') % page.title\\n\\t\\treturn diamandaModelwrappers.add_topic(request, coment_forum_id, inject_post=COMMENT_POST, inject_title=TITLE, redirect_link=REDIRECT, content_obj=page)\\n\\telif request.POST and add_topic and page.coment_topic:\\n\\t\\tREDIRECT = (\\\"/w/p/\\\" + slug +\\\"/?c=ok\\\", _('Comment added succesfuly.'))\\n\\t\\treturn diamandaModelwrappers.add_post(request, page.coment_topic.id, redirect_link=REDIRECT, content_obj=page)\\n\\t\\n\\tif page.current_book:\\n\\t\\tcb = page.current_book\\n\\t\\n\\tif page.content_type == 'news':\\n\\t\\treturn render_to_response(\\n\\t\\t\\t'pages/show_news.html',\\n\\t\\t\\t{'page': page, 'add_topic': add_topic, 'form': form, 'show_comment': show_comment, 'comments': comments},\\n\\t\\t\\tcontext_instance=RequestContext(request, {'current_book': cb}))\\n\\treturn render_to_response(\\n\\t\\t'pages/show.html',\\n\\t\\t{'page': page, 'add_topic': add_topic, 'form': form, 'show_comment': show_comment, 'comments': comments},\\n\\t\\tcontext_instance=RequestContext(request, {'current_book': cb}))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fea07b70f2ea2874392c5226c75175b9\",\n \"score\": \"0.5996286\",\n \"text\": \"def comments(game_id, post_id):\\n\\n db = get_db()\\n\\n if (request.method == 'POST') and (g.user != None):\\n #If there is a post request and the user is logged in, insert their comment into the database\\n\\n comment = request.form['comment']\\n\\n db.execute(\\\"INSERT INTO comments(user_id, post_id, comment_id, content, hidden) VALUES (?, ?, NULL, ?, 0)\\\", (g.user['id'], post_id, comment))\\n db.commit()\\n\\n\\n #Retrieve all of the necessary data for the page\\n post = db.execute(\\\"SELECT username, users.id, title, body, game_id FROM posts JOIN users ON user_id=users.id WHERE posts.id = ?\\\", str(post_id)).fetchone()\\n\\n game = db.execute(\\\"SELECT id, title FROM games WHERE id = ?\\\", str(post['game_id'])).fetchone()\\n\\n comments = db.execute(\\\"SELECT content, username, users.id FROM comments JOIN users ON user_id=users.id WHERE post_id = ?\\\", str(post_id)).fetchall()\\n\\n return render_template(\\\"layouts/comments.html\\\", post=post, comments=comments, game=game)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"461d41775f2f75bd350a598908a50f08\",\n \"score\": \"0.5989866\",\n \"text\": \"def comment():\\n if request.method == 'POST':\\n if 'username' not in session:\\n return render_template('login.html')\\n\\n message = request.form['message']\\n post_id = request.form['post_id']\\n username = session['username']\\n user_id = session['user_id']\\n\\n print(post_id)\\n print(user_id)\\n\\n # Use backend post api - Post\\n body = {'user_id': user_id,\\n 'username': username, 'message': message}\\n\\n # url = '{}/posts'.format(app.config[\\\"POST_BASE_URI\\\"])\\n url = '{}/posts/{}/comments'.format(app.config[\\\"POST_BASE_URI\\\"], post_id)\\n print(url)\\n response = requests.post(url=url,\\n json=body,\\n headers={'content-type': 'application/json'},\\n timeout=3)\\n\\n app.logger.info('Get %s with response status code %s',\\n url, response.status_code)\\n app.logger.info('Get %s with response text %s', url, response.text)\\n\\n return redirect('/viewpost/' + post_id)\\n return render_template('login.html')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"133c58bdaad85c0efe4c270497a91ae3\",\n \"score\": \"0.59606856\",\n \"text\": \"def post_comment(request, next=None):\\r\\n # Fill out some initial data fields from an authenticated user, if present\\r\\n data = request.POST.copy()\\r\\n if request.user.is_authenticated():\\r\\n if not data.get('name', ''):\\r\\n data[\\\"name\\\"] = request.user.get_full_name() or request.user.username\\r\\n if not data.get('email', ''):\\r\\n data[\\\"email\\\"] = request.user.email\\r\\n\\r\\n # Check to see if the POST data overrides the view's next argument.\\r\\n next = data.get(\\\"next\\\", next)\\r\\n\\r\\n # Look up the object we're trying to comment about\\r\\n ctype = data.get(\\\"content_type\\\")\\r\\n object_pk = data.get(\\\"object_pk\\\")\\r\\n if ctype is None or object_pk is None:\\r\\n return CommentPostBadRequest(\\\"Missing content_type or object_pk field.\\\")\\r\\n try:\\r\\n model = models.get_model(*ctype.split(\\\".\\\", 1))\\r\\n target = model._default_manager.get(pk=object_pk)\\r\\n except TypeError:\\r\\n return CommentPostBadRequest(\\r\\n \\\"Invalid content_type value: %r\\\" % escape(ctype))\\r\\n except AttributeError:\\r\\n return CommentPostBadRequest(\\r\\n \\\"The given content-type %r does not resolve to a valid model.\\\" % \\\\\\r\\n escape(ctype))\\r\\n except ObjectDoesNotExist:\\r\\n return CommentPostBadRequest(\\r\\n \\\"No object matching content-type %r and object PK %r exists.\\\" % \\\\\\r\\n (escape(ctype), escape(object_pk)))\\r\\n\\r\\n # Do we want to preview the comment?\\r\\n preview = \\\"preview\\\" in data\\r\\n\\r\\n # Construct the comment form\\r\\n form = comments.get_form()(target, data=data)\\r\\n\\r\\n # Check security information\\r\\n if form.security_errors():\\r\\n return CommentPostBadRequest(\\r\\n \\\"The comment form failed security verification: %s\\\" % \\\\\\r\\n escape(str(form.security_errors())))\\r\\n\\r\\n # If there are errors or if we requested a preview show the comment\\r\\n if form.errors or preview:\\r\\n template_list = [\\r\\n \\\"comments/%s_%s_preview.html\\\" % tuple(str(model._meta).split(\\\".\\\")),\\r\\n \\\"comments/%s_preview.html\\\" % model._meta.app_label,\\r\\n \\\"comments/preview.html\\\",\\r\\n ]\\r\\n return render_to_response(\\r\\n template_list, {\\r\\n \\\"comment\\\" : form.data.get(\\\"comment\\\", \\\"\\\"),\\r\\n \\\"form\\\" : form,\\r\\n \\\"next\\\": next,\\r\\n },\\r\\n RequestContext(request, {})\\r\\n )\\r\\n\\r\\n # Otherwise create the comment\\r\\n comment = form.get_comment_object()\\r\\n comment.ip_address = request.META.get(\\\"REMOTE_ADDR\\\", None)\\r\\n if request.user.is_authenticated():\\r\\n comment.user = request.user\\r\\n\\r\\n # Signal that the comment is about to be saved\\r\\n responses = signals.comment_will_be_posted.send(\\r\\n sender = comment.__class__,\\r\\n comment = comment,\\r\\n request = request\\r\\n )\\r\\n\\r\\n for (receiver, response) in responses:\\r\\n if response == False:\\r\\n return CommentPostBadRequest(\\r\\n \\\"comment_will_be_posted receiver %r killed the comment\\\" % receiver.__name__)\\r\\n\\r\\n # Save the comment and signal that it was saved\\r\\n comment.save()\\r\\n signals.comment_was_posted.send(\\r\\n sender = comment.__class__,\\r\\n comment = comment,\\r\\n request = request\\r\\n )\\r\\n\\r\\n return next_redirect(data, next, comment_done, c=comment._get_pk_val())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"91818ccd34b7b916f67ef9df2bcc1735\",\n \"score\": \"0.59462464\",\n \"text\": \"def view_comments(request, product_id):\\n reviews = Review.objects.filter(product=product_id)\\n product = get_object_or_404(Product, pk=product_id)\\n\\n context = {\\n \\\"reviews\\\": reviews,\\n \\\"product\\\": product,\\n }\\n return render(request, \\\"products/reviews.html\\\", context)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6b06e3c34b4f68e6649bfaf23b58ac6b\",\n \"score\": \"0.5928355\",\n \"text\": \"def post(self, post_key):\\n form = CommentForm(self.request.POST)\\n is_liked = Like.is_liked_by_user(self.user, self.post)\\n\\n if form.validate():\\n comment_key = Comment.new_comment(form.content.data, self.user,\\n self.post)\\n\\n if comment_key:\\n self.redirect_to(\\\"viewpost\\\", post_key=post_key,\\n _fragment=str(comment_key))\\n else:\\n self.abort(500)\\n\\n self.render_viewpost(form, is_liked)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1573a05a8c90223786c44481e85adf69\",\n \"score\": \"0.59153986\",\n \"text\": \"def pickRepostComment(repostComments): \\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"55ebbd6cb68713797bf7ff40c6db7f78\",\n \"score\": \"0.591078\",\n \"text\": \"def post_comment(request, next=None):\\n # Fill out some initial data fields from an authenticated user, if present\\n data = request.POST.copy()\\n print data\\n if request.user.is_authenticated():\\n if not data.get('name', ''):\\n data[\\\"name\\\"] = request.user.get_full_name() or request.user.username\\n if not data.get('email', ''):\\n data[\\\"email\\\"] = request.user.email\\n\\n # Look up the object we're trying to comment about\\n ctype = data.get(\\\"content_type\\\")\\n object_pk = data.get(\\\"object_pk\\\")\\n print ctype\\n if ctype is None or object_pk is None:\\n return CommentPostBadRequest(\\\"Missing content_type or object_pk field.\\\")\\n try:\\n model = models.get_model(*ctype.split(\\\".\\\", 1))\\n target = model._default_manager.get(pk=object_pk)\\n except TypeError:\\n return CommentPostBadRequest(\\n \\\"Invalid content_type value: %r\\\" % escape(ctype))\\n except AttributeError:\\n return CommentPostBadRequest(\\n \\\"The given content-type %r does not resolve to a valid model.\\\" % \\\\\\n escape(ctype))\\n except ObjectDoesNotExist:\\n return CommentPostBadRequest(\\n \\\"No object matching content-type %r and object PK %r exists.\\\" % \\\\\\n (escape(ctype), escape(object_pk)))\\n\\n # Do we want to preview the comment?\\n preview = \\\"preview\\\" in data\\n\\n # Construct the comment form\\n form = comments.get_form()(target, data=data)\\n\\n # Check security information\\n if form.security_errors():\\n return CommentPostBadRequest(\\n \\\"The comment form failed security verification: %s\\\" % \\\\\\n escape(str(form.security_errors())))\\n\\n # If there are errors or if we requested a preview show the comment\\n if preview:\\n template_list = [\\n \\\"comments/%s_%s_preview.html\\\" % tuple(str(model._meta).split(\\\".\\\")),\\n \\\"comments/%s_preview.html\\\" % model._meta.app_label,\\n \\\"comments/preview.html\\\",\\n ]\\n return render_to_response(\\n template_list, {\\n \\\"comment\\\" : form.data.get(\\\"comment\\\", \\\"\\\"),\\n \\\"form\\\" : form,\\n },\\n RequestContext(request, {})\\n )\\n \\n if form.errors:\\n (view_func, view_args, view_kwargs) = resolve(target.get_absolute_url())\\n view_kwargs.update({\\n 'extra_context': {'comment_form': form}\\n })\\n return view_func(request, *view_args, **view_kwargs)\\n\\n # Otherwise create the comment\\n comment = form.get_comment_object()\\n comment.ip_address = request.META.get(\\\"REMOTE_ADDR\\\", None)\\n if request.user.is_authenticated():\\n comment.user = request.user\\n\\n # Signal that the comment is about to be saved\\n responses = signals.comment_will_be_posted.send(\\n sender = comment.__class__,\\n comment = comment,\\n request = request\\n )\\n\\n for (receiver, response) in responses:\\n if response == False:\\n return CommentPostBadRequest(\\n \\\"comment_will_be_posted receiver %r killed the comment\\\" % receiver.__name__)\\n\\n # Save the comment and signal that it was saved\\n comment.save()\\n signals.comment_was_posted.send(\\n sender = comment.__class__,\\n comment = comment,\\n request = request\\n )\\n\\n return next_redirect(data, next, comment_done, c=comment._get_pk_val())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c85bb1e58b7a038fd261394cc45b50da\",\n \"score\": \"0.5903895\",\n \"text\": \"def edit_comment(self, comment_object, pid):\\n if self.user:\\n comment_content = self.request.get('post_comment')\\n if comment_content:\\n comment_object.comment = comment_content\\n CommentEntity.commit_comment(comment_object)\\n return self.redirect('/{0}/{1}'.format('post',\\n pid))\\n\\n self.redirect('/login')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b710bbc470070b1bc2d25ad3b1bcc0d3\",\n \"score\": \"0.58985364\",\n \"text\": \"def post(self, post_id):\\n data = request.json\\n comment = create_comment(data=data, post_id=post_id)\\n return comment\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4df99ef651670e5cb343ca4e9f7bc594\",\n \"score\": \"0.5895393\",\n \"text\": \"def get_blog_post(request, pk):\\n return render(request, 'oikos/blog.html', {'post' : Post.objects.get(pk=pk)})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6e400562d59bb225386fd3713b126bb9\",\n \"score\": \"0.58818877\",\n \"text\": \"def comment_detail(request, company_slug, idea_id, comment_id): \\n comment = get_object_or_404(Comment, idea__id=idea_id, pk=comment_id)\\n\\n if request.method == 'GET':\\n serializer = CommentSerializer(comment)\\n return Response(serializer.data)\\n\\n elif request.method == 'DELETE':\\n if not has_admin_permission(request.user, comment.idea.company) and comment.created_by != request.user:\\n return HttpResponseForbidden() \\n\\n try:\\n member = Member.objects.get(company=comment.idea.company, user=request.user)\\n if member.blocked:\\n return HttpResponseForbidden() \\n except:\\n pass\\n\\n comment.delete()\\n return Response(status=status.HTTP_204_NO_CONTENT)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0168b1f8b91b78e798e21abeca66e931\",\n \"score\": \"0.58523023\",\n \"text\": \"def comment_was_posted(request):\\r\\n obj = None\\r\\n if request.GET.has_key('c'):\\r\\n content_type_id, object_id = request.GET['c'].split(':')\\r\\n try:\\r\\n content_type = ContentType.objects.get(pk=content_type_id)\\r\\n obj = content_type.get_object_for_this_type(pk=object_id)\\r\\n except ObjectDoesNotExist:\\r\\n pass\\r\\n return render_to_response('comments/posted.html', {'object': obj}, context_instance=RequestContext(request))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8f00f0a3ee6137af6c5ae0af11863826\",\n \"score\": \"0.583153\",\n \"text\": \"def comment(self, content):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e4e9567f1b024e56a73e06b4e09111ea\",\n \"score\": \"0.5820659\",\n \"text\": \"def post(self, request, post_id):\\n post = Post.object.filter(pk=post_id).first()\\n title = self.request.POST.get(\\\"title\\\", \\\"\\\")\\n comment = self.request.POST.get(\\\"comment\\\", \\\"\\\")\\n user = self.request.user\\n if not title or not comment:\\n return JsonResponse({\\\"error\\\": \\\"Datos incompletos\\\"})\\n obj = Comment.objects.create(\\n title=title,\\n comment=comment,\\n user=user,\\n post=post\\n )\\n obj.save()\\n return redirect(\\\"view_post\\\", (self.post.pk,))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"04b7a8c332af03fd5359469648dce53c\",\n \"score\": \"0.5808202\",\n \"text\": \"def email(self, comment, content_object, request):\\r\\n if comment.is_public:\\r\\n context = {\\r\\n 'comment': comment,\\r\\n 'entry': content_object,\\r\\n }\\r\\n email_body = render_to_string('blog/new_comment_email.txt', context)\\r\\n mail_managers(u'Comment on \\\"%s\\\"' % content_object, email_body)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9a016602aa842096c58b9ab3e09e7d05\",\n \"score\": \"0.57942635\",\n \"text\": \"def item_show(item_id):\\n item = items.find_one({'_id': ObjectId(item_id)})\\n # Add the below line:\\n item_comments = comments.find({'item_id': ObjectId(item_id)})\\n # Edit the return statement to be the following:\\n return render_template('show.html', item=item, comments=item_comments)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"78fef74fa042889e57ba462adab90e7e\",\n \"score\": \"0.5741248\",\n \"text\": \"def viewpost(post_id):\\n # if request.method == 'POST':\\n # if 'username' not in session:\\n # return render_template('login.html')\\n\\n # message = request.form['message']\\n # username = session['username']\\n # user_id = session['user_id']\\n\\n # # Use backend post api - Post\\n # body = {'user_id': user_id, 'username': username, 'message': message}\\n # url = '{}/posts'.format(app.config[\\\"POST_BASE_URI\\\"])\\n # response = requests.post(url=url,\\n # json=body,\\n # headers={'content-type': 'application/json'},\\n # timeout=3)\\n\\n # app.logger.info('Get %s with response status code %s',\\n # url, response.status_code)\\n # app.logger.info('Get %s with response text %s', url, response.text)\\n\\n # return redirect(url_for('home'))\\n\\n url = '{}/posts/{}'.format(app.config[\\\"POST_BASE_URI\\\"], post_id)\\n response = requests.get(url, timeout=3)\\n\\n app.logger.info('Get %s with response status code %s',\\n url, response.status_code)\\n # app.logger.info('Get %s with response text %s', url, response.text)\\n\\n post = json.loads(response.text)['data']['post']\\n\\n # comments = [{'message': 'Hello'}, {\\n # 'message': 'Hello'}, {'message': 'Hello'}]\\n comments = json.loads(response.text)['data']['comments']\\n\\n return render_template('postdetail.html', post=post, comments=comments)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"842f86990df5806e6ca4e3b00c71c9ff\",\n \"score\": \"0.57406366\",\n \"text\": \"def post_detail(request, pk=None, slug=None):\\n if slug:\\n post = get_object_or_404(Post, slug=slug)\\n elif pk:\\n post = get_object_or_404(Post, pk=pk)\\n\\n return render(request, \\\"blog/blog_detail.html\\\", {\\n \\\"page\\\": \\\"blog\\\",\\n \\\"post\\\": post\\n })\",\n \"title\": \"\"\n },\n {\n \"docid\": \"38d910e5a710ded2629a50f3d5a1e7c0\",\n \"score\": \"0.5735533\",\n \"text\": \"def post_comment():\\n content = request.json['content']\\n parent = request.json['parent']\\n post_id = request.json['post_id']\\n user_id = get_jwt_identity()\\n comment = Comment(user_id, content, post_id, parent_id=parent)\\n db.session.add(comment)\\n db.session.commit()\\n return respond(plain_response(comment.id))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"45778fc0137795d32597f6ccbd8cbfbf\",\n \"score\": \"0.57330495\",\n \"text\": \"def feature_comment(request, pk):\\n feature = get_object_or_404(Feature, pk=pk)\\n if request.method == 'POST':\\n comment_form = FeatureCommentForm(request.POST)\\n if comment_form.is_valid():\\n comment = comment_form.save(commit=False)\\n comment.commenter = request.user\\n comment.feature = feature\\n comment.save()\\n return redirect(feature_details, feature.pk)\\n else:\\n comment_form = FeatureCommentForm()\\n return render(request, 'feature_comment.html', {'feature': feature, 'comment_form': comment_form})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"99b506f7fd1b6539d847e8123bef16a3\",\n \"score\": \"0.57282954\",\n \"text\": \"def edit_comment(request, comment_id):\\n user = community_helpers.get_logged_user(request)\\n \\n if user:\\n comment = models.Comment.objects.get(id = comment_id)\\n EditCommentForm = forms.build_edit_comment_form(comment)\\n if request.POST:\\n form = EditCommentForm(request.POST, request.FILES)\\n if form.is_valid():\\n form.handle_edit(user, comment)\\n return http.HttpResponseRedirect(reverse('content-redirect-by-id', args=[comment.content_type.id, comment.object_id]))\\n else:\\n form = EditCommentForm()\\n return shortcuts.render_to_response(\\n 'comments/edit_comment.html', \\n {'form':form, 'comment':comment, 'node_content_type':comment.content_type.id, 'node_object_id':comment.object_id}, \\n context_instance = RequestContext(request)\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3960db6180e18800a9a24dc751dfddda\",\n \"score\": \"0.5716266\",\n \"text\": \"def post_comment(request, next=None, using=None):\\r\\n # Fill out some initial data fields from an authenticated user, if present\\r\\n data = request.POST.copy()\\r\\n if request.user.is_authenticated():\\r\\n if not data.get('name', ''):\\r\\n data[\\\"name\\\"] = request.user.get_full_name() or request.user.get_username()\\r\\n if not data.get('email', ''):\\r\\n data[\\\"email\\\"] = request.user.email\\r\\n\\r\\n # Look up the object we're trying to comment about\\r\\n ctype = data.get(\\\"content_type\\\")\\r\\n object_pk = data.get(\\\"object_pk\\\")\\r\\n if ctype is None or object_pk is None:\\r\\n return CommentPostBadRequest(\\\"Missing content_type or object_pk field.\\\")\\r\\n try:\\r\\n model = models.get_model(*ctype.split(\\\".\\\", 1))\\r\\n target = model._default_manager.using(using).get(pk=object_pk)\\r\\n except TypeError:\\r\\n return CommentPostBadRequest(\\r\\n \\\"Invalid content_type value: %r\\\" % escape(ctype))\\r\\n except AttributeError:\\r\\n return CommentPostBadRequest(\\r\\n \\\"The given content-type %r does not resolve to a valid model.\\\" % \\\\\\r\\n escape(ctype))\\r\\n except ObjectDoesNotExist:\\r\\n return CommentPostBadRequest(\\r\\n \\\"No object matching content-type %r and object PK %r exists.\\\" % \\\\\\r\\n (escape(ctype), escape(object_pk)))\\r\\n except (ValueError, ValidationError) as e:\\r\\n return CommentPostBadRequest(\\r\\n \\\"Attempting go get content-type %r and object PK %r exists raised %s\\\" % \\\\\\r\\n (escape(ctype), escape(object_pk), e.__class__.__name__))\\r\\n\\r\\n # Do we want to preview the comment?\\r\\n preview = \\\"preview\\\" in data\\r\\n\\r\\n # Construct the comment form\\r\\n form = django_comments.get_form()(target, data=data)\\r\\n\\r\\n # Check security information\\r\\n if form.security_errors():\\r\\n return CommentPostBadRequest(\\r\\n \\\"The comment form failed security verification: %s\\\" % \\\\\\r\\n escape(str(form.security_errors())))\\r\\n\\r\\n # If there are errors or if we requested a preview show the comment\\r\\n if form.errors or preview:\\r\\n template_list = [\\r\\n # These first two exist for purely historical reasons.\\r\\n # Django v1.0 and v1.1 allowed the underscore format for\\r\\n # preview templates, so we have to preserve that format.\\r\\n \\\"comments/%s_%s_preview.html\\\" % (model._meta.app_label, model._meta.module_name),\\r\\n \\\"comments/%s_preview.html\\\" % model._meta.app_label,\\r\\n # Now the usual directory based template hierarchy.\\r\\n \\\"comments/%s/%s/preview.html\\\" % (model._meta.app_label, model._meta.module_name),\\r\\n \\\"comments/%s/preview.html\\\" % model._meta.app_label,\\r\\n \\\"comments/preview.html\\\",\\r\\n ]\\r\\n return render_to_response(\\r\\n template_list, {\\r\\n \\\"comment\\\": form.data.get(\\\"comment\\\", \\\"\\\"),\\r\\n \\\"form\\\": form,\\r\\n \\\"next\\\": data.get(\\\"next\\\", next),\\r\\n },\\r\\n RequestContext(request, {})\\r\\n )\\r\\n\\r\\n # Otherwise create the comment\\r\\n comment = form.get_comment_object()\\r\\n comment.ip_address = request.META.get(\\\"REMOTE_ADDR\\\", None)\\r\\n if request.user.is_authenticated():\\r\\n comment.user = request.user\\r\\n\\r\\n # Signal that the comment is about to be saved\\r\\n responses = signals.comment_will_be_posted.send(\\r\\n sender=comment.__class__,\\r\\n comment=comment,\\r\\n request=request\\r\\n )\\r\\n\\r\\n for (receiver, response) in responses:\\r\\n if response == False:\\r\\n return CommentPostBadRequest(\\r\\n \\\"comment_will_be_posted receiver %r killed the comment\\\" % receiver.__name__)\\r\\n\\r\\n # Save the comment and signal that it was saved\\r\\n comment.save()\\r\\n signals.comment_was_posted.send(\\r\\n sender=comment.__class__,\\r\\n comment=comment,\\r\\n request=request\\r\\n )\\r\\n\\r\\n return next_redirect(request, fallback=next or 'comments-comment-done',\\r\\n c=comment._get_pk_val())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1bee138e51bed7498a8c981fb91a695f\",\n \"score\": \"0.5714569\",\n \"text\": \"def quick_url(comment):\\n\\n def to_id(fullname):\\n return fullname.split(\\\"_\\\", 1)[1]\\n\\n return \\\"http://www.reddit.com/r/{}/comments/{}/_/{}?context=3\\\".format(\\n comment.subreddit.display_name, to_id(comment.link_id), comment.id\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fae50ed823edcc7a7d1d6ae900d5b806\",\n \"score\": \"0.57140905\",\n \"text\": \"def get(self, post_id):\\r\\n if not self.user:\\r\\n self.redirect('/blog/login?error=You need to be logged')\\r\\n return\\r\\n else:\\r\\n key = db.Key.from_path('Blog', int(post_id))\\r\\n post = db.get(key)\\r\\n if not post:\\r\\n self.error(404)\\r\\n return\\r\\n user = post.user\\r\\n loggedUser = self.user\\r\\n if user == loggedUser:\\r\\n key = db.Key.from_path('Blog', int(post_id))\\r\\n post = db.get(key)\\r\\n error = \\\"\\\"\\r\\n self.render(\\\"editpost.html\\\", subject=post.subject,\\r\\n content=post.content, post_id=post_id,\\r\\n error=error)\\r\\n else:\\r\\n error = \\\"You can't edit this post\\\"\\r\\n self.render(\\\"error.html\\\", error=error)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"663c1d8648303fcd021c55e8a906cf30\",\n \"score\": \"0.5698372\",\n \"text\": \"def add_comment_to_post(request, pk):\\n post = get_object_or_404(Post, pk=pk)\\n if request.method == \\\"POST\\\":\\n form = CommentForm(request.POST)\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.post = post\\n comment.save()\\n return redirect('blog-post', pk=post.id)\\n else:\\n form = CommentForm()\\n return render(request, 'add_comment_to_post.html', {'form': form})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"af2a8d546f001eba74bd1bee97d966ed\",\n \"score\": \"0.56928205\",\n \"text\": \"def detail_post_view(session: Session, post_id: IdType) -> typing.List[PostType]:\\n post = session.query(Post).get(post_id)\\n\\n if not post:\\n return Response({'message': 'Post does not exist'}, status=204)\\n else:\\n post_data = dict(\\n id=post.id,\\n author_id=post.author_id,\\n title=post.title,\\n content=post.content,\\n created_at=post.created_at.strftime(format='%Y-%m-%d %H:%M'),\\n )\\n return {'data': post_data}\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7fdbe1ea50ca2ca3968768f0fe5590c4\",\n \"score\": \"0.56762093\",\n \"text\": \"def feature_details(request, pk):\\n feature = get_object_or_404(Feature, pk=pk)\\n comments = FeatureComment.objects.filter(feature=feature)\\n return render(request, \\\"feature_details.html\\\", {'feature': feature, 'comments': comments})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ea10d8ed339a3bd1192b51cb0137c990\",\n \"score\": \"0.5670916\",\n \"text\": \"def check_comment(post_id, comment_id, check_author=True):\\n\\n db = get_db()\\n\\n comment = get_comment_of_post(db, post_id, comment_id)\\n if comment is None:\\n abort(404, \\\"Comment id {0} doesn't exist.\\\".format(comment_id))\\n\\n current_user = get_user_by_username(db, request.authorization[\\\"username\\\"])\\n if check_author and comment[\\\"author_id\\\"] != current_user[\\\"id\\\"]:\\n abort(403)\\n\\n return comment\",\n \"title\": \"\"\n },\n {\n \"docid\": \"74b91df995a745dd9214f66b529be32e\",\n \"score\": \"0.5634377\",\n \"text\": \"def post_detail(request, pk):\\n post = get_object_or_404(Feedback, pk=pk)\\n post.save()\\n return render(request, \\\"feedbackdetail.html\\\", {\\\"post\\\":post})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ad72f193d51a44406eef966f0d461d8d\",\n \"score\": \"0.5633675\",\n \"text\": \"def add_comment(self, post):\\n if self.user:\\n comment_content = self.request.get('comment')\\n if comment_content:\\n comment = CommentEntity.register(user=self.user,\\n post=post,\\n comment=comment_content)\\n CommentEntity.commit_comment(comment)\\n return self.redirect('/{0}/{1}'.format('post',\\n post.key().id()))\\n\\n self.redirect('/login')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c2b8f4fc62acdeaae105bce80552942d\",\n \"score\": \"0.56218356\",\n \"text\": \"def get(self, post_id):\\n if self.user_id:\\n params, user_info = disclaim(self)\\n else:\\n params = {} \\n params['captchahtml'] = captchaBase(self)\\n blog = models.BlogPost.get_by_id(long(post_id))\\n if blog is not None:\\n params['title'] = blog.title\\n params['subtitle'] = blog.subtitle\\n params['blob_key'] = blog.blob_key\\n params['author'] = blog.author\\n params['content'] = blog.content\\n return self.render_template('materialize/landing/blogpost.html', **params)\\n else:\\n return self.error(404)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e6e46599cb7cdbfc08739013f522a6bb\",\n \"score\": \"0.56055665\",\n \"text\": \"def post(self, post_id):\\n comment = request.form.get('comment')\\n\\n post = Post.get_by_id(post_id)\\n post.comments.append(Comment(session.get('user_id'), post.id, comment))\\n\\n db.session.commit()\\n\\n return redirect(url_for('blog.post', post_id=post_id))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5357134e62722ca8f07e6e42f10dd1b0\",\n \"score\": \"0.5603172\",\n \"text\": \"def GetComment(self):\\r\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3073a414630f0449af65e90de18c7401\",\n \"score\": \"0.55794376\",\n \"text\": \"def representative_comment(self):\\n p = self.root_posts\\n if len(p) == 0:\\n return None\\n return p[0]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0156caa4dcd7416014144af7a52818b7\",\n \"score\": \"0.55773926\",\n \"text\": \"def show_movie(request, movie_slug):\\n context_dict = {}\\n \\n\\t# Attempt to retrieve the data to be displayed on the movies page\\n try:\\n movie = Movie.objects.get(slug=movie_slug)\\n comments = Comment.objects.filter(movie=movie)\\n\\n context_dict['movie'] = movie\\n\\n context_dict['comments'] = sort_comments(comments)\\n movie.views = movie.views + 1\\n movie.save()\\n\\n\\t\\t# If the user is logged in allow them to comment and reply to comments\\n if request.user.is_authenticated:\\n author = UserProfile.objects.filter(\\n user=request.user)[0]\\n\\n form = CommentForm(\\n author=author,\\n parent=None,\\n movie=movie)\\n\\n context_dict['form'] = form\\n\\n else:\\n context_dict['form'] = None\\n\\n\\t# if the user posts the comment form\\n if request.method == \\\"POST\\\":\\n form = CommentForm(\\n request.POST,\\n author=author,\\n parent=None,\\n movie=movie)\\n\\t\\t\\t\\n if form.is_valid():\\n comment = form.save(commit=False)\\n comment.save()\\n request.method=\\\"GET\\\"\\n return show_movie(request, movie_slug)\\n\\n else:\\n print(form.errors)\\n \\n except Movie.DoesNotExist:\\n context_dict['movie'] = None\\n context_dict['comments'] = None\\n context_dict['form'] = None\\n\\n return render(request, \\n 'rate_my_movie_app/movie.html',\\n context_dict)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d1d3c7fde4f8927ee58438241c2b6b73\",\n \"score\": \"0.5576925\",\n \"text\": \"def show_comments(item_format=' - {timestamp} -> {text} .::. {_ts}', admin_fmt=True, **kwargs):\\n print('\\\\n'.join(get_comments(item_format=item_format, admin_fmt=admin_fmt, **kwargs)))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f1e860f91b2b7b1f367cf1d0028de4fa\",\n \"score\": \"0.55709225\",\n \"text\": \"def post_details(request, slug, post_pk):\\n post, post_url = get_redirected(models.Post, {'pk': post_pk}, {'slug': slug})\\n # return render(request, 'blog/post_details.html', {'post': post })\\n if post_url:\\n return HttpResponseRedirect(post_url)\\n\\n return render(request, 'blog/post_details.html', {'post': post})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"747affcc5d5fbc52191a99b7a9ffa0b4\",\n \"score\": \"0.5570872\",\n \"text\": \"def get(self):\\n\\t\\t# getting the numbers of all post comment\\n\\t\\tpost_numdata_comments = numdata_comments_all_post()\\n\\t\\t# getting the hottest comment\\n\\t\\thottest_posts = hottest_dic(post_numdata_comments, 5)\\n\\t\\t# getting all the numbers of comments by the category\\n\\t\\t# ordering\\n\\t\\t# data structure of this behavior\\n\\t\\t# idpost\\t\\t\\t\\tnumber of comments, postentity\\n\\t\\t# [('5710932114145280', [6, <models.blog_model.Blog object at 0x04428110>])\\n\\t\\thottest_posts = sort_dictionary_desc(hottest_posts)\\n\\t\\thottest_category = count_comments_by_category(post_numdata_comments)\\n\\t\\thottest_category = hottest_dic(hottest_category, 5)\\n\\t\\thottest_category = sort_dictionary_desc(hottest_category)\\n\\t\\tlogging.error(hottest_category)\\n\\t\\t\\n\\t\\tself.render(\\\"hottest.html\\\", hottest_posts = hottest_posts, hottest_category = hottest_category)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"18bd0b6db5005190a4b039255612e138\",\n \"score\": \"0.5568248\",\n \"text\": \"def show_article(request, article_id):\\n posts = Post.objects.filter(article=article_id).order_by(\\\"created\\\")\\n article = Article.objects.get(pk=article_id)\\n return render(request, 'articles/article.html', {'posts': posts, 'article': article})\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2cc3362e9e62a7119e7aa873d03193d1\",\n \"score\": \"0.55588794\",\n \"text\": \"def blogpost(request, slug):\\n assert isinstance(request, HttpRequest)\\n\\n post_current = Post.objects.get(slug=slug) # запрос на выбор конкретной статьи по параметру\\n comments = Comment.objects.filter(post=post_current)\\n\\n if request.method == \\\"POST\\\": # после отправки данных формы на сервер методом POST\\n commentform = CommentForm(request.POST)\\n\\n if commentform.is_valid():\\n comment_f = commentform.save(commit=False)\\n comment_f.author = request.user # добавляем (так как этого поля нет в форме) в модель Комментария (Comment) в поле автор авторизованного пользователя\\n comment_f.date = datetime.now() # добавляем в модель Комментария (Comment) текущую дату\\n comment_f.post = post_current # Blog.objects.get(id=parametr) # добавляем в модель Комментария (Comment) статью, для которой данный комментарий\\n comment_f.save() # сохраняем изменения после добавления полей\\n\\n return redirect('blogpost', slug=post_current.slug) # переадресация на ту же страницу статьи после отправки комментария\\n\\n else:\\n commentform = CommentForm() # создание формы для ввода комментария\\n\\n data = {\\n \\\"title\\\": post_current.title,\\n 'post_current': post_current, # передача конкретной статьи в шаблон веб-страницы\\n 'comments': comments,\\n \\\"src\\\": '/media',\\n 'image': post_current.image,\\n 'commentform': commentform, # передача формы добавления комментария в шаблон веб-страницы\\n 'year':datetime.now().year,\\n }\\n\\n return render(request, 'blog/blogpost.html', data)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1fb0fba1fb39c954587f4c1878fdff2c\",\n \"score\": \"0.5558202\",\n \"text\": \"def render_post(id):\\n return render_template(\\\"blog/post.html\\\", post=_get_post(id))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c12e42a1c60651c6789835aa21da038d\",\n \"score\": \"0.5544281\",\n \"text\": \"def add_comment(request, post_id, username):\\n form = CommentForm(request.POST or None)\\n if form.is_valid():\\n post = get_object_or_404(Post, author__username=username, id=post_id)\\n comment = form.save(commit=False)\\n comment.post = post\\n comment.author = request.user\\n comment.save()\\n return redirect(\\\"post\\\", username, post_id)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5ef6fa3b926f7136631aabd7573a6f76\",\n \"score\": \"0.55422664\",\n \"text\": \"def extract_random_comment(post, min_length=None):\\n url = '%s.json?sort=random' % post['permalink'].rstrip('/')\\n r = get(url)\\n r.raise_for_status()\\n j = r.json()\\n comments = [c for c in j[1]['data']['children'] if 'body' in c['data']]\\n if min_length:\\n comments = [c for c in comments if len(c['data']['body']) >= min_length]\\n if len(comments) > 0:\\n global last_url\\n last_url = normify_url(url)\\n return comments[0]\\n else:\\n raise APIError('The selected post doesn\\\\'t have any comments')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5750a522894d6c3ca658308f7dfc74e8\",\n \"score\": \"0.5538344\",\n \"text\": \"def printPost(pid):\\n query = ''' SELECT * FROM posts WHERE lower(pid)=?'''\\n cursor.execute(query, (pid,))\\n post = cursor.fetchone()\\n connection.commit()\\n\\n Type = typeOfPost(pid)\\n print('-' * 25 + 'Post Details' + '-' * 24)\\n print('<'+Type.upper()+'Post>')\\n print('Post ID: {}'.format(pid))\\n print('Post date: {}'.format(post[1]))\\n print('Post title: {}'.format(post[2]))\\n print('Post body: {}'.format(post[3]))\\n print('Poster: {}'.format(post[4]))\\n print('-' * 60)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b805d7da964562b118dba51972d0a22a\",\n \"score\": \"0.5532694\",\n \"text\": \"def get_context_data(self, **kwargs):\\n context = super(CommentCreate, self).get_context_data(**kwargs)\\n # Call the base implementation first to get a context\\n context['post'] = get_object_or_404(Post, slug = self.kwargs['slug'])\\n # Get the post from id and add it to the context\\n return context\",\n \"title\": \"\"\n },\n {\n \"docid\": \"173e1acdc2329e24cf58692ed1234c12\",\n \"score\": \"0.55315\",\n \"text\": \"def add_comment(request, slug):\\n #print(\\\"looool\\\")\\n p = request.POST\\n\\n if p[\\\"content\\\"]:\\n author = \\\"Anonymous\\\"\\n if p[\\\"author\\\"]: author = p[\\\"author\\\"]\\n\\n comment = Comment(post=Post.objects.get(slug=slug))\\n cf = CommentForm(p, instance=comment)\\n cf.fields[\\\"author\\\"].required = False\\n\\n comment = cf.save(commit=False)\\n comment.author = author\\n comment.save()\\n return HttpResponseRedirect(reverse(\\\"blog.views.post\\\", args=[slug]))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bb932d93b732c09857387552fb26fea6\",\n \"score\": \"0.55157614\",\n \"text\": \"def comment(self, comment_text, email=\\\"\\\", name=\\\"\\\", pseud=None):\\n \\n if self.id is None:\\n return self._work.comment(comment_text, email, name, pseud)\\n \\n if not self.loaded:\\n raise utils.UnloadedError(\\\"Chapter isn't loaded. Have you tried calling Chapter.reload()?\\\")\\n \\n if self._session is None:\\n raise utils.AuthError(\\\"Invalid session\\\")\\n \\n if self.id is not None:\\n return utils.comment(self, comment_text, self._session, False, email=email, name=name, pseud=pseud)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e3e5d0eff498c13ff561e3f4e63a32cf\",\n \"score\": \"0.55125606\",\n \"text\": \"async def meme(self, ctx: commands.Context):\\n subreddit = await self.config.guild(ctx.guild).subreddit()\\n async with self.session.get(\\n f\\\"https://www.reddit.com/{subreddit}/top.json?sort=new\\\"\\n ) as resp:\\n data = await resp.json()\\n data = data[\\\"data\\\"]\\n children = data[\\\"children\\\"]\\n post = random.choice(children)[\\\"data\\\"]\\n title = post[\\\"title\\\"]\\n url = post[\\\"url_overridden_by_dest\\\"]\\n link_url = f'https://reddit.com{post[\\\"permalink\\\"]}'\\n ups = post[\\\"ups\\\"]\\n comnts = post[\\\"num_comments\\\"]\\n\\n if post[\\\"over_18\\\"] is True:\\n return await ctx.send(\\n \\\"Cannot show content because it is nsfw,\\\"\\n \\\" try changing the subreddit lol.\\\"\\n )\\n\\n embed = (\\n discord.Embed(title=title, url=link_url)\\n .set_image(url=url)\\n .set_footer(text=\\\"👍 {} | 💬 {}\\\".format(ups, comnts))\\n )\\n await ctx.send(embed=embed)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ed82cab84b16e1b0dfb3e9b6189891fa\",\n \"score\": \"0.55006695\",\n \"text\": \"def post_detail(request, year, month, day, slug):\\r\\n tt = time.strptime('-'.join([year, month, day]), '%Y-%b-%d')\\r\\n date = datetime.date(*tt[:3])\\r\\n try:\\r\\n post = Post.objects.published().get(slug=slug, pub_date__year=date.year, \\r\\n pub_date__month=date.month, pub_date__day=date.day)\\r\\n except Post.DoesNotExist:\\r\\n raise Http404\\r\\n \\r\\n return render_with_context(request, 'blog/post_detail.xhtml', {\\r\\n 'post': post,\\r\\n 'title': post.title, \\r\\n })\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f9692cbb2827b959e5f57229a876b723\",\n \"score\": \"0.54891664\",\n \"text\": \"async def set_comment(self, ctx: commands.Context, *, comment: str = None):\\n await sql.execute(\\\"UPDATE servers SET comment=? WHERE serverid=?\\\", comment, str(ctx.message.guild.id))\\n em = discord.Embed(colour=discord.Colour.dark_green())\\n if comment:\\n em.title = f\\\"Successfully changed comment symbol to `{comment}`.\\\"\\n else:\\n em.title = \\\"Successfully removed comment symbol.\\\"\\n await ctx.send(embed=em)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5a4539cc9e588fc2cfdf4ecca0054286\",\n \"score\": \"0.54857767\",\n \"text\": \"def post_comment(request, next=None):\\n\\n # Require POST\\n if request.method != 'POST':\\n return http.HttpResponseNotAllowed([\\\"POST\\\"])\\n\\n is_ajax = request.POST.get('is_ajax') and '_ajax' or ''\\n\\n # Fill out some initial data fields from an authenticated user, if present\\n data = request.POST.copy()\\n\\n if request.user.is_authenticated():\\n if not data.get('name', ''):\\n data[\\\"name\\\"] = request.user.get_full_name()\\n if not data.get('email', ''):\\n data[\\\"email\\\"] = request.user.email\\n\\n # Look up the object we're trying to comment about\\n ctype = data.get(\\\"content_type\\\")\\n object_pk = data.get(\\\"object_pk\\\")\\n parent_pk = data.get(\\\"parent_pk\\\")\\n parent_comment = None\\n if ctype is None or object_pk is None:\\n return CommentPostBadRequest(\\\"Missing content_type or object_pk field.\\\")\\n try:\\n model = models.get_model(*ctype.split(\\\".\\\", 1))\\n target = model._default_manager.get(pk=object_pk)\\n if parent_pk:\\n parent_comment = MpttComment.objects.get(pk=parent_pk)\\n except TypeError:\\n return CommentPostBadRequest(\\n \\\"Invalid content_type value: %r\\\" % escape(ctype))\\n except AttributeError:\\n return CommentPostBadRequest(\\n \\\"The given content-type %r does not resolve to a valid model.\\\" % \\\\\\n escape(ctype))\\n except MpttComment.DoesNotExist:\\n return CommentPostBadRequest(\\n \\\"Parent comment with PK %r does not exist.\\\" % \\\\\\n escape(parent_pk))\\n except ObjectDoesNotExist:\\n return CommentPostBadRequest(\\n \\\"No object matching content-type %r and object PK %r exists.\\\" % \\\\\\n (escape(ctype), escape(object_pk)))\\n\\n # Do we want to preview the comment?\\n preview = data.get(\\\"submit\\\", \\\"\\\").lower() == \\\"preview\\\" or \\\\\\n data.get(\\\"preview\\\", None) is not None\\n\\n # Construct the comment form\\n form = MpttCommentForm(target, parent_comment=parent_comment, data=data)\\n\\n # Check security information\\n if form.security_errors():\\n return CommentPostBadRequest(\\n \\\"The comment form failed security verification: %s\\\" % \\\\\\n escape(str(form.security_errors())))\\n\\n # If there are errors or if we requested a preview show the comment\\n if form.errors or preview:\\n template_list = [\\n \\\"comments/%s_%s_preview%s.html\\\" % tuple(str(model._meta).split(\\\".\\\") + [is_ajax]),\\n \\\"comments/%s_preview%s.html\\\" % (model._meta.app_label, is_ajax),\\n \\\"comments/preview%s.html\\\" % is_ajax\\n ]\\n return render_to_response(\\n template_list, {\\n \\\"comment\\\" : form.data.get(\\\"comment\\\", \\\"\\\"),\\n \\\"form\\\" : form,\\n \\\"allow_post\\\": not form.errors\\n },\\n RequestContext(request, {})\\n )\\n\\n # Otherwise create the comment\\n comment = form.get_comment_object()\\n comment.ip_address = request.META.get(\\\"REMOTE_ADDR\\\", None)\\n if request.user.is_authenticated():\\n comment.user = request.user\\n\\n # Signal that the comment is about to be saved\\n responses = signals.comment_will_be_posted.send(\\n sender = comment.__class__,\\n comment = comment,\\n request = request\\n )\\n\\n for (receiver, response) in responses:\\n if response == False:\\n return CommentPostBadRequest(\\n \\\"comment_will_be_posted receiver %r killed the comment\\\" % receiver.__name__)\\n\\n # Save the comment and signal that it was saved\\n comment.save()\\n signals.comment_was_posted.send(\\n sender = comment.__class__,\\n comment = comment,\\n request = request\\n )\\n\\n if is_ajax:\\n data['next'] = None\\n\\n return next_redirect(data, next, 'comments_comment_done%s' % (is_ajax and '_ajax' or ''), c=comment._get_pk_val())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c3393ccc0ff923e37df4edc8880205e0\",\n \"score\": \"0.5463447\",\n \"text\": \"def test_issues_id_comments_issue_comment_id_post(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8eaeb2d2cfb921f90c66a034872c0b6f\",\n \"score\": \"0.54462004\",\n \"text\": \"def show_article(request, username, permalink):\\n\\n try:\\n user = User.objects.get(username__iexact=username)\\n except User.DoesNotExist:\\n raise Http404\\n\\n try:\\n # there should be always only one of those\\n article = UserActivity.objects.select_related().get(\\n username__iexact = username,\\n post__permalink = permalink,\\n status = UserActivity.PUBLIC_STATUS)\\n except UserActivity.DoesNotExist:\\n # check for draft articles\\n articles = UserActivity.objects.select_related().filter(\\n username__iexact = username, \\n post__permalink = permalink,\\n status = UserActivity.DRAFT_STATUS)\\n if len(articles)==0:\\n raise Http404\\n else:\\n article = articles[0] \\n # show draft only if currently logged in user is viewing\\n if (not request.user.is_superuser) and (request.user != user):\\n raise Http404\\n\\n data = {\\n 'activity' : article,\\n 'user_profile': user,\\n }\\n\\n return render(\\n request,\\n templates['ARTICLE'],\\n data,\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b461cd019185f21f700becac53a9d450\",\n \"score\": \"0.5431777\",\n \"text\": \"def comment_handler(sender, instance, created, **kwargs):\\n recipients = []\\n if instance.parent and instance.parent.author != instance.author:\\n # comment is part of a thread\\n parent_comment_author = instance.parent.author\\n recipients.append(parent_comment_author)\\n comment_author = instance.author\\n article = instance.article\\n desc_string = \\\"{} posted a comment to {} on {}\\\"\\n article_author = article.author\\n if article_author.id != comment_author.id:\\n recipients.append(article_author)\\n url = reverse(\\n \\\"articles:article-details\\\", args=[article.slug])\\n resource_url = f\\\"{settings.DOMAIN}{url}\\\"\\n\\n notify.send(comment_author,\\n recipient=recipients,\\n description=desc_string.format(comment_author.username,\\n article or instance,\\n instance.created_at.strftime('%d-%B-%Y %H:%M')), # noqa\\n verb=verbs.COMMENT_CREATED,\\n target=article or instance,\\n action_object=instance,\\n resource_url=resource_url)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2eb07e6bfbb75ae544755f38237d11c4\",\n \"score\": \"0.5428052\",\n \"text\": \"def test_post_view_with_permalink(self):\\n reset_db()\\n p = create_post_with_comments()\\n c = Client()\\n response = c.get(reverse('blog.views.post_view', args=[p.permalink] ) )\\n self.assertEqual(response.status_code, 200, 'Expected 200.')\\n self.assertEqual(response.context['post'].id, p.id, 'Mismatch on post ids.')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"41805d8194b675b04493a8233966397e\",\n \"score\": \"0.5425533\",\n \"text\": \"def test_single_post_view(self):\\n reset_db()\\n p = create_post_with_comments()\\n c = Client()\\n response = c.get('/post/%s/%s' % (p.id, p.permalink) )\\n self.assertEqual(response.status_code, 200, 'HTTP error.')\\n self.assertIsNotNone(response.context['post'], 'No post returned.')\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":390,"cells":{"query_id":{"kind":"string","value":"d892852aa3e7a6ea40c368be4d467adc"},"query":{"kind":"string","value":"Convert value to boolean."},"positive_passages":{"kind":"list like","value":[{"docid":"62d72b52a5d57f1f68f69a09dd84d2d0","score":"0.80972165","text":"def toBool(self, val: Any) -> bool:\n if type(val) == bool:\n return val\n elif type(val) == int:\n return val != 0\n elif type(val) == str:\n v = val.lower()\n return not (v == \"no\" or v == \"false\" or v == \"0\")\n _LOGGER.warning(\n \"Visonic unable to decode boolean value %s type is %s\", val, type(val)\n )\n return False","title":""}],"string":"[\n {\n \"docid\": \"62d72b52a5d57f1f68f69a09dd84d2d0\",\n \"score\": \"0.80972165\",\n \"text\": \"def toBool(self, val: Any) -> bool:\\n if type(val) == bool:\\n return val\\n elif type(val) == int:\\n return val != 0\\n elif type(val) == str:\\n v = val.lower()\\n return not (v == \\\"no\\\" or v == \\\"false\\\" or v == \\\"0\\\")\\n _LOGGER.warning(\\n \\\"Visonic unable to decode boolean value %s type is %s\\\", val, type(val)\\n )\\n return False\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"5d4bd8517d78334032a46f042455bfcc","score":"0.863882","text":"def to_boolean(value: Any) -> bool:\n return BooleanConverter.to_boolean_with_default(value, False)","title":""},{"docid":"fee659ff6685b59b558ebd84f3dfcd34","score":"0.85566324","text":"def _asBool(self):\n return bool(self.value)","title":""},{"docid":"5549e9521f472bef0c2e79ce6fadbfee","score":"0.8505888","text":"def Boolean(value):\n return asbool(value)","title":""},{"docid":"152a19f4ccb3cf31bcd5e49f3215af9f","score":"0.8140877","text":"def ToBool(value):\n if str(value).lower() in (\"yes\", \"y\", \"true\", \"t\", \"1\"): return True\n if str(value).lower() in (\"no\", \"n\", \"false\", \"f\", \"0\", \"0.0\", \"\", \"none\", \"[]\", \"{}\"): return False\n raise Exception('Invalid value for boolean conversion: ' + str(value))","title":""},{"docid":"aa3afed99a944fa7ea8ee3c511dfb7dd","score":"0.8091099","text":"def to_bool(value):\n return str(value).lower() in ['1', 't', 'true', 'y', 'yes']","title":""},{"docid":"5b6a6f43f74198e575baa21b4b31dc46","score":"0.805445","text":"def _cast_boolean(self, value):\n value = str(value)\n if value == '':\n return False\n else:\n return value.strip() in ['True', 'true', '1']","title":""},{"docid":"5d0b1f098787a4c1345d5ddbc97bff83","score":"0.79466623","text":"def Bool(value):\n return get_env().formula_manager.Bool(value)","title":""},{"docid":"4b2de0974683f4b14a70e9eac5686603","score":"0.7910972","text":"def to_bool(val) -> bool:\n\n if type(val) == bool:\n return val\n else:\n return bool(strtobool(val))","title":""},{"docid":"5ecc9b7699d7f12da4a3338cfffcc4c9","score":"0.7887335","text":"def to_bool(value):\n if str(value).lower() in (\"yes\", \"y\", \"true\", \"t\", \"1\"): return True\n if str(value).lower() in (\"no\", \"n\", \"false\", \"f\", \"0\", \"0.0\", \"\", \"none\", \"[]\", \"{}\"): return False\n raise Exception('Invalid value for boolean conversion: ' + str(value))","title":""},{"docid":"0b7e2fd26e6ba7ad0241181964ee8c83","score":"0.78812224","text":"def to_bool(value):\n if value is None:\n return False\n if str(value).lower() in (\"yes\", \"y\", \"true\", \"t\", \"1\"):\n return True\n if str(value).lower() in (\"no\", \"n\", \"false\", \"f\", \"0\", \"0.0\", \"\", \"none\", \"[]\", \"{}\"):\n return False\n raise Exception('Invalid value for boolean conversion: ' + str(value))","title":""},{"docid":"a05ebade6b6931beb40494e0aed19ddc","score":"0.778305","text":"def boolean_argument(value):\n return bool(strtobool(value))","title":""},{"docid":"a05ebade6b6931beb40494e0aed19ddc","score":"0.778305","text":"def boolean_argument(value):\n return bool(strtobool(value))","title":""},{"docid":"b9b5c3ec5dea158c5f87928bc5a796a5","score":"0.77716255","text":"def asbool(value):\n if value is None:\n return False\n\n if isinstance(value, bool):\n return value\n\n return value.lower() in (\"true\", \"1\")","title":""},{"docid":"f2a9974c3e0df6f237cf448194d5193d","score":"0.77589124","text":"def cast_value(self, value: str) -> typing.Any:\n if value.lower() in ['true', '1']:\n return True\n elif value.lower() in ['false', '0']:\n return False\n else:\n return bool(value)","title":""},{"docid":"b822c642ed923e6f3ef73368f40c4a98","score":"0.77273583","text":"def convert_to_boolean(value):\n if isinstance(value, string_types):\n if value.lower() in ['t', 'true', 'on', 'yes', '1']:\n return True\n elif value.lower() in ['f', 'false', 'off', 'no', '0']:\n return False\n\n return value","title":""},{"docid":"d904a4d5d3cfc3ef0854072941be1289","score":"0.77238077","text":"def to_bool(value=\"\"):\n # type: (str) -> bool\n return str(value).lower() in {\"true\", \"on\", \"1\", \"yes\", \"oui\"}","title":""},{"docid":"c82741facae2627581e676a65edd8a5b","score":"0.7716701","text":"def __bool__(self):\n return bool(self._value)","title":""},{"docid":"dd3be86b0e8a070111f687720078ae91","score":"0.7668287","text":"def _convert_to_boolean(value):\n if value.lower() not in Config.BOOLEAN_STATES:\n raise ValueError('Not a boolean: %s' % value)\n return Config.BOOLEAN_STATES[value.lower()]","title":""},{"docid":"ddcba74d8e55d97272a649011032af42","score":"0.766755","text":"def _bool(value):\r\n if value == 0 or isinstance(value, (str, native_str)):\r\n return True\r\n return bool(value)","title":""},{"docid":"e9ad4b790d01e118633f57d689acb3ea","score":"0.7658754","text":"def boolean_converter(val):\n\n boolean_vals = ('true', '1', 'yes', 'y')\n\n if val and (str(val).lower() in boolean_vals):\n return True\n return False","title":""},{"docid":"90f61bd8b0e8a39d176557a4ef303050","score":"0.7608571","text":"def to_python(self, value):\r\n if value in (True, 'True', '1'):\r\n return True\r\n elif value in (False, 'False', '0'):\r\n return False\r\n else:\r\n return None","title":""},{"docid":"f740c93fce8cfd419b3ff77dff114296","score":"0.7589277","text":"def to_boolean(value):\n _BOOL_STATES = {'1': True, 'yes': True, 'true': True, 'on': True,\n '0': False, 'no': False, 'false': False, 'off': False}\n\n value = str(value).lower().strip()\n if value not in _BOOL_STATES:\n raise ValueError(value)\n return _BOOL_STATES[value]","title":""},{"docid":"b6ab2da8d9699ed2a31aa3a953649393","score":"0.7586434","text":"def __bool__(self) -> bool:\n return bool(self._value)","title":""},{"docid":"f34b30f231730d7f6c9bf972c49e7f72","score":"0.75436604","text":"def get_boolean_value(self):\n if self._type != Value.BOOLEAN:\n raise Exception(\"Illegal boolean\")\n return self._value","title":""},{"docid":"ce57f426af424934d2deeabfb2412a22","score":"0.7542982","text":"def asBool(*args, **kwargs):\n \n pass","title":""},{"docid":"ce57f426af424934d2deeabfb2412a22","score":"0.7542982","text":"def asBool(*args, **kwargs):\n \n pass","title":""},{"docid":"ecad8791f970f3723fd59de75ffc284f","score":"0.7542822","text":"def test_to_value(self, data, value):\n assert value == Boolean.to_value(data)","title":""},{"docid":"6599dd8409758766cc99868194981aa4","score":"0.75231975","text":"def is_true(value):\n return value is True","title":""},{"docid":"ad565e81ac837d09fd25a83fd2ac3e97","score":"0.7481766","text":"def _getValueAsBoolean(self, node):\n value = node.attrib[\"value\"]\n assert value in (\"True\", \"False\",), \\\n \"Unexpected boolean value '%s' in tag <%s>\" % (value, node.tag)\n return value == \"True\"","title":""},{"docid":"df59fb4f07aad74e40eebe0be6f83683","score":"0.7478464","text":"def tobool( val ):\n\n if val.lower() in [ \"y\", \"yes\", \"t\", \"true\", \"1\", 1 ]:\n return True\n\n else:\n return False","title":""},{"docid":"bc8bfe7d7d2c500b9c511901b45d15bb","score":"0.74751365","text":"def to_bool(value: str) -> bool:\n if value in [\"True\", \"true\", True]:\n return True\n if value in [\"False\", \"false\", False]:\n return False\n raise ValueError(f\"Value {value} cannot be converted into a bool\")","title":""},{"docid":"3a863b5224795c599adf7234f7f187cf","score":"0.7473932","text":"def __bool__(self) -> bool:\n return bool(self.value())","title":""},{"docid":"f480182054800cbca996c685b76317db","score":"0.7471968","text":"def _convert_bools(self, name: str, value) -> bool:\n if isinstance(value, bool):\n return value\n\n if value == None:\n return None\n\n value = str(value).lower()\n # Try to convert values to the positive.\n if value == '1' or value == 'true':\n return True\n # Try to convert values to the negative.\n elif value == '0' or value == 'false':\n return False\n else:\n AttributeError('%s field %s should be type bool.' % (\n __class__.__name__, name))\n logging.error('%s field %s should be type bool.' % (\n __class__.__name__, name))","title":""},{"docid":"ad80c7e306973716e36fac67f06192a9","score":"0.74677265","text":"def convert(self, value, db=None):\n if value is UNASSIGNED:\n return value\n elif value == self.false_label:\n return False\n elif value == self.true_label:\n return True\n return bool(value)","title":""},{"docid":"b163d580bcb1c750caf0b71030346de0","score":"0.74324596","text":"def is_true(value):\n\n return (value is True)","title":""},{"docid":"047685bb875f18d9a673013d8ded321a","score":"0.7405042","text":"def cast(self, val):\n if isinstance(val, bool):\n return BoolVal(val, self.ctx)\n if z3_debug():\n if not is_expr(val):\n msg = \"True, False or Z3 Boolean expression expected. Received %s of type %s\"\n _z3_assert(is_expr(val), msg % (val, type(val)))\n if not self.eq(val.sort()):\n _z3_assert(self.eq(val.sort()), \"Value cannot be converted into a Z3 Boolean value\")\n return val","title":""},{"docid":"fd7c1a085118afb1096d5f8cacbabeed","score":"0.73866117","text":"def convert_tobooleanvalue(i: bytes) -> bool:\n return bool(int(i))","title":""},{"docid":"58d8cf9c812e8cb9aa79f282a7264d58","score":"0.7379311","text":"def int_to_bool(value: int) -> bool:\n return False if value == 0 else True","title":""},{"docid":"b560a25aefc9503e378b1a25d83d3cf4","score":"0.73696303","text":"def ToBool(value, default=_DEFAULT):\n value = str(value).lower()\n if value in constants.TRUE_VALUES:\n return True\n if value in constants.FALSE_VALUES:\n return False\n if default is _DEFAULT:\n raise ConversionError('Cannot convert %r to bool' % value)\n return default","title":""},{"docid":"18924c11bd08910462a714d3aadd9ffa","score":"0.73639184","text":"def _isBool(self):\n return isinstance(self.value, bool)","title":""},{"docid":"303968e630cce419da26a43e15ad30b2","score":"0.73460144","text":"def str_to_bool(value):\n\n\treturn bool(value) and value.lower() != 'false'","title":""},{"docid":"fa7f24fa1a2b7dba88d9ea2f63cfd825","score":"0.73320675","text":"def str2bool(value: str):\r\n if type(value) == bool:\r\n return_val = value\r\n else:\r\n return_val = value.lower() in (\"yes\", \"true\", \"t\", \"1\")\r\n\r\n return return_val","title":""},{"docid":"308d960b2394d3cf356386255060a57d","score":"0.72950953","text":"def coerceBoolean(value, mode = \"best\"):\n\n # convert true values\n if value in [ 1, \"true\", u\"true\", \"yes\", u\"yes\" ]:\n return True\n\n # convert false values\n if value in [ 0, \"false\", u\"false\", \"no\", u\"no\" ]:\n return False\n\n return _handleMode(value, \"boolean\", mode)","title":""},{"docid":"af5884d6985969a1ae66b7b768681847","score":"0.728786","text":"def str_to_bool(value):\n value = value.lower()\n return value in ['true', '1', 'up', 'on']","title":""},{"docid":"b63c7737c56ecb65287daf11935571ce","score":"0.72775364","text":"def _to_bool(x):\n return x.astype(bool)","title":""},{"docid":"d1fc6eee2a24c6d115f05d08b17b3fe4","score":"0.72260445","text":"def get_as_boolean(self, index):\n value = self[index]\n return BooleanConverter.to_boolean(value)","title":""},{"docid":"1b0710f5c864160a2ee4636c9df306ca","score":"0.7219768","text":"def isBool(self, input_val):\n if isinstance(input_val, str):\n if input_val.upper() in ['FALSE', '0', 'NO']:\n input_val = False\n elif input_val.upper() in ['TRUE', '1', 'YES']:\n input_val = True\n else:\n input_val = None\n elif isinstance(input_val, int):\n if input_val == 0:\n input_val = False\n if input_val == 1:\n input_val = True\n return input_val","title":""},{"docid":"10ed659e88d76c16a8c08cf0686aa763","score":"0.71981543","text":"def bool_value(self):\n if self.value:\n if self.value.lower() in self.MEANS_YES:\n return True\n return False\n return None","title":""},{"docid":"85517e0e1cc5c6324b0a30b20d2927e4","score":"0.71761125","text":"def check_value(self, value: typing.Any) -> bool:\n return isinstance(value, bool)","title":""},{"docid":"19f9780982e16e4347626a635cf3a936","score":"0.71621436","text":"def coerce_boolean(value):\n if is_string(value):\n normalized = value.strip().lower()\n if normalized in ('1', 'yes', 'true', 'on'):\n return True\n elif normalized in ('0', 'no', 'false', 'off', ''):\n return False\n else:\n msg = \"Failed to coerce string to boolean! (%r)\"\n raise ValueError(format(msg, value))\n else:\n return bool(value)","title":""},{"docid":"0d0e9305d874b730505cb9d61668baf6","score":"0.7159789","text":"def getValue(self) -> \"bool\" :\n return _quickfix.BoolField_getValue(self)","title":""},{"docid":"aa9b9533dd98cb4c8e0be397fe7e88ae","score":"0.71549124","text":"def __nonzero__(self):\n return bool(self.value)","title":""},{"docid":"17b96aafb0ade443469d31af099aea25","score":"0.7142359","text":"def boolean(value, context=None):\n try:\n return bool(value)\n except (TypeError, ValueError):\n raise ValidationException('This field is suppose to be boolean')","title":""},{"docid":"9fb1ff055a4a07904cc53e5b4ccbe379","score":"0.71229684","text":"def toBool(x):\n if x.lower() == 'true':\n return True\n elif x.lower() == 'false':\n return False\n else:\n raise ValueError","title":""},{"docid":"3152c4dc4abd610c93e6df0d969d5a85","score":"0.71187764","text":"def boolean(val):\n\n return str(val).lower() in ('1', 'yes', 'true', 'on')","title":""},{"docid":"5ff118df1008664795ea658297365504","score":"0.7100943","text":"def return_true(value):\n\n return True","title":""},{"docid":"53a0bd3c59e574e293c4f3dbb6e9abc2","score":"0.70947546","text":"def test_boolean_true_returns_true(self):\n self.assertEqual(to_bool(True), True)","title":""},{"docid":"9fc411687c2f88283d0a4a9acb423ad3","score":"0.7082532","text":"def create_boolean(value):\n return jpath4.query.data.StandardSequence([jpath4.query.data.StandardBoolean(value)])","title":""},{"docid":"88492eeb0a75a5a12a18e2982043c974","score":"0.7072428","text":"def as_bool(self, key):\n val = self[key]\n if val == True:\n return True\n elif val == False:\n return False\n else:\n try:\n if not isinstance(val, StringTypes):\n raise KeyError\n else:\n return self.main._bools[val.lower()]\n except KeyError:\n raise ValueError('Value \"%s\" is neither True nor False' % val)","title":""},{"docid":"694b34e0e0a4e600e9f4259b9eac7dcc","score":"0.70704985","text":"def _createBool(newvalue):\n return CableValue(bool(newvalue))","title":""},{"docid":"7deb4fa56286f58f427fb660228af857","score":"0.7061925","text":"def to_nullable_boolean(value: Any) -> Optional[bool]:\n # Shortcuts\n if value is None:\n return None\n if type(value) is type(True):\n return value\n\n str_value = str(value).lower()\n # All true values\n if str_value in ['1', 'true', 't', 'yes', 'y']:\n return True\n # All false values\n if str_value in ['0', 'false', 'f', 'no', 'n']:\n return False\n\n # Everything else:\n return None","title":""},{"docid":"8b803f187ea1c634faafc873dd25c193","score":"0.7034297","text":"def process_value(self, value):\n if value == self.TRUE_VALUE:\n return True\n elif value == self.FALSE_VALUE:\n return False\n else:\n raise QueryParameterInvalidError(self.name, value)","title":""},{"docid":"ac3ef8af0471644195044b0f76e57e09","score":"0.70269805","text":"def _isValueBoolean(actuator):\n return actuator.value == 0 or \\\n actuator.value == 1 or \\\n actuator.value.upper == \"TRUE\" or \\\n actuator.value.upper == \"FALSE\"","title":""},{"docid":"7083dc2fa0d3116edfc60c91e3d3867b","score":"0.702437","text":"def str2bool(val):\n if val not in [u\"True\", u\"False\"]:\n # Not using ValueError intentionally: all config errors are RuntimeError\n raise RuntimeError(\"Found %s instead of 'True' of 'False'\" % val)\n elif val == u\"True\":\n return True\n else:\n return False","title":""},{"docid":"efa7c3dcdb41fd829b58f2086e05dd18","score":"0.702407","text":"def str2bool(value: Union[bool, str]) -> bool:\n\n value2 = False\n\n if isinstance(value, bool):\n value2 = value\n else:\n value2 = value.lower() in ('yes', 'true', 't', '1', 'on')\n\n return value2","title":""},{"docid":"5bb497518166dcd48c2db5cf81d5ed56","score":"0.70188636","text":"def boolean(value):\n def _boolean():\n return value\n return _boolean","title":""},{"docid":"9d2d9cd5b0141f91dd51756100b0f12c","score":"0.7016583","text":"def boolval(b):\n b = str(b).lower()\n if b in [ 'true', '1', 'yes']:\n return True\n elif b in [ 'false', '0', 'no']:\n return False\n return False","title":""},{"docid":"c30fd04719265bc7eba35aa0d9638f19","score":"0.7000714","text":"def create_boolean(b):\n return Value(Value.BOOLEAN, b)","title":""},{"docid":"202d7a8ae17ab603e07755240e67ebf3","score":"0.698797","text":"def to_python(self, value):\n # Explicitly check for the string 'False', which is what a hidden field\n # will submit for False. Also check for '0', since this is what\n # RadioSelect will provide. Because bool(\"True\") == bool('1') == True,\n # we don't need to handle that explicitly.\n\n if isinstance(value, six.string_types) and value.lower() in ('false', '0'):\n value = False\n\n elif value is None:\n value = False\n\n elif value is False:\n value = False\n\n elif isinstance(value, six.string_types) and value.lower() in ('true', '1'):\n value = True\n\n elif value is True:\n value = True\n\n else:\n raise ValidationError(u'%s is not boolean' % value)\n\n return value","title":""},{"docid":"65e141b751c949981991292048b86e74","score":"0.6986076","text":"def booleanize(value):\n true_values = (\"yes\", \"true\", \"1\")\n false_values = (\"no\", \"false\", \"0\")\n if isinstance(value, bool):\n return value\n if value.lower() in true_values:\n return True\n elif value.lower() in false_values:\n return False\n raise TypeError(\"Cannot booleanize ambiguous value '%s'\" % value)","title":""},{"docid":"4eaaaeb9cf23123e283c45ddd5f97da4","score":"0.69842726","text":"def b(value):\n return 'true' if value else 'false'","title":""},{"docid":"b1c9f2d3469c5d1bd869f6034e393c0d","score":"0.69831014","text":"def get_boolean(self, key):\n def convert(val, context):\n if val in [True, False, None]:\n return val\n elif str(val).lower() in [\"y\", \"yes\", \"true\", \"on\", \"1\"]:\n return True\n elif str(val).upper() in [\"n\", \"no\", \"false\", \"off\", \"0\"]:\n return False\n else:\n raise ConfigConversionError(\n \"must be y/n, yes/no, true/false, on/off, or 0/1\")\n return self.get(key, convert)","title":""},{"docid":"3afa7882bea0c527b43a43bf1c02b506","score":"0.6974749","text":"def convert_config_value(self, value, label):\n if isinstance(value, six.string_types):\n value = value.lower()\n\n if value in self.TRUTHY_VALUES:\n return True\n elif value in self.FALSY_VALUES:\n return False\n else:\n raise YapconfValueError(\n \"Cowardly refusing to interpret \"\n \"config value as a boolean. Name: \"\n \"{0}, Value: {1}\".format(self.name, value)\n )","title":""},{"docid":"242c4390159ee9604ee6a46601eada41","score":"0.695988","text":"def tgread_bool(self):\n value = self.read_int(signed=False)\n if value == 0x997275b5: # boolTrue\n return True\n elif value == 0xbc799737: # boolFalse\n return False\n else:\n raise RuntimeError('Invalid boolean code {}'.format(hex(value)))","title":""},{"docid":"6c06cf052cbb81a503c348c4594111ef","score":"0.6923948","text":"def read_boolean(self):\n s = self.read_typed(str).lower()\n if s == 'true':\n return True\n elif s == 'false':\n return False\n else:\n raise ValueError('Cannot convert \\'%s\\' to a boolean' % s)","title":""},{"docid":"d65e63e8967b9ebdda6dc4700d43058c","score":"0.69234395","text":"def is_bool(value: int) -> bool:\n return TypeRanges.BOOL.inf <= remove_base_prefix(value) <= TypeRanges.BOOL.max","title":""},{"docid":"f571247350ec7d632b26ddf7a1996965","score":"0.69179946","text":"def parse_bool(value):\n try:\n return bool(int(value))\n except ValueError:\n lowercase = value.lower()\n if lowercase == 'true':\n return True\n elif lowercase == 'false':\n return False\n raise ValueError('Unable to parse {} as a bool'.format(value))","title":""},{"docid":"3160f070a603119490211288df8f978b","score":"0.69152445","text":"def bool_from_header_value(value):\n if isinstance(value, bool):\n return value\n elif isinstance(value, (basestring, unicode)):\n if str(value).lower() == 'true':\n return True\n return False","title":""},{"docid":"30ff6569861b4352f1e780a8026ff96e","score":"0.69151366","text":"def value_to_bool(value: Optional[OptionValue]) -> Optional[bool]:\n retval: Optional[bool]\n\n if value is None:\n retval = None\n else:\n if isinstance(value, bool):\n retval = value\n elif isinstance(value, (int, float)):\n retval = bool(value)\n elif isinstance(value, str):\n if value in TRUE_VALUES:\n retval = True\n elif value in FALSE_VALUES:\n retval = False\n else:\n raise ValueError\n else:\n raise ValueError\n\n return retval","title":""},{"docid":"7de6fbe87543b2a089fff9fe43df98c8","score":"0.68959","text":"def BoolVal(val, ctx=None):\n ctx = _get_ctx(ctx)\n if val:\n return BoolRef(Z3_mk_true(ctx.ref()), ctx)\n else:\n return BoolRef(Z3_mk_false(ctx.ref()), ctx)","title":""},{"docid":"ee062ebe39a4b56b955fe272b71e5e2b","score":"0.68944204","text":"def to_bool_arg(self, arg):\n if arg == 1:\n return True\n elif arg == -1:\n return False\n else:\n Exception(\n f\"Unknown int value for the trarnsformation to bool: {arg}\")","title":""},{"docid":"8620873d239787c909fd657f33a36606","score":"0.6894205","text":"def _booleanConverter(self, input):\n if input in [True, False]:\n return input\n\n if input in [1, '1']:\n return True\n\n if input in [0, '0']:\n return False\n\n try:\n input_lower = input.lower()\n except:\n raise ValueError('Not a boolean value: %s' % (input))\n\n if input_lower in ['yes', 'true']:\n return True\n if input_lower in ['no', 'false']:\n return False\n\n raise ValueError('Not a boolean value: %s' % (input))","title":""},{"docid":"a917be036c9e4971b80a0a83c05a4cd0","score":"0.68868613","text":"def _bool(v):\n try:\n if isinstance(v, basestring):\n return v.lower() in ['t', 'true', '1']\n return bool(v)\n except Exception:\n return False","title":""},{"docid":"678b468f331a8cdc82c7cd764d3eac5e","score":"0.6871099","text":"def as_bool(self, key):\r\n val = self[key]\r\n if val == True:\r\n return True\r\n elif val == False:\r\n return False\r\n else:\r\n try:\r\n if not isinstance(val, basestring):\r\n # TODO: Why do we raise a KeyError here?\r\n raise KeyError()\r\n else:\r\n return self.main._bools[val.lower()]\r\n except KeyError:\r\n raise ValueError('Value \"%s\" is neither True nor False' % val)","title":""},{"docid":"2bb29530594fcdb50b95db11ead3166f","score":"0.6866402","text":"def get_bool(value: str) -> Union[bool, None]:\n lowered = str(value).lower()\n\n if lowered in (\"yes\", \"y\", \"true\", \"t\", \"1\", \"enable\", \"on\"):\n val = True\n elif lowered in (\"no\", \"n\", \"false\", \"f\", \"0\", \"disable\", \"off\"):\n val = False\n else:\n val = None\n\n return val","title":""},{"docid":"18c821be7834ef5744dbb6c01b41fc2b","score":"0.6851357","text":"def bool(self, python_bool_var):\n return \"true\" if python_bool_var else \"false\"","title":""},{"docid":"ad5815754f4fdf1824bb472f7daccf41","score":"0.684874","text":"def str_to_bool(value):\n if isinstance(value, bool):\n return value\n if value.lower() in ('yes', 'true', 't', 'y', '1'):\n return True\n elif value.lower() in ('no', 'false', 'f', 'n', '0'):\n return False\n else:\n raise argparse.ArgumentTypeError('Boolean value expected.')","title":""},{"docid":"0b5cafaf8828264b59281d1e57772aa0","score":"0.68455356","text":"def encode_boolean(self, b):\r\n if bool(b):\r\n return 'true'\r\n return 'false'","title":""},{"docid":"c17a19290ec6accd24b975d73ebc2c0e","score":"0.68455225","text":"def to_python(self, value):\r\n # Explicitly check for the string 'False', which is what a hidden field\r\n # will submit for False. Also check for '0', since this is what\r\n # RadioSelect will provide. Because bool(\"True\") == bool('1') == True,\r\n # we don't need to handle that explicitly.\r\n if value in ('False', '0'):\r\n value = False\r\n else:\r\n value = bool(value)\r\n value = super(BooleanField, self).to_python(value)\r\n if not value and self.required:\r\n raise ValidationError(self.error_messages['required'])\r\n return value","title":""},{"docid":"ffbce9bfcfe147945be164c5bb1fa622","score":"0.68400574","text":"def to_be_a_bool(self, message: Optional[str] = \"\") -> bool:\n return cast(bool, self.to_be_a(ExpectedType.BOOLEAN, message))","title":""},{"docid":"5f0c34b070eec24419d7041290065b0a","score":"0.6823493","text":"def str_to_bool(value):\n if not value:\n return False\n if value.lower() in STR_FALSE:\n return False\n if value.lower() in STR_TRUE:\n return True\n raise ValueError(\"Invalid truth value '%s'\" % value)","title":""},{"docid":"17ca97bc6a0078427e1e55826c4b9d5e","score":"0.6804988","text":"def to_bool(var):\n if isinstance(var, str):\n if var == '' or var.lower() == 'false':\n return False\n else:\n return True\n return bool(var)","title":""},{"docid":"35a5b9c43e8c6805dec62e2fbe010672","score":"0.6801289","text":"def convert_to_boolean(obj):\n istrue = ('true', 'yes', 'ok', '1', 'on', '+', 'True', 'Yes', 'Ok', 'On', 'TRUE', 'YES', 'OK', 'ON', 1, 1.0)\n isfalse = ('false', 'no', '0', '-', 'off', 'False', 'No', 'Off', 'FALSE', 'NO', 'OFF', 0, 0.0)\n\n if isinstance(obj, (str, int, float)):\n if obj in istrue:\n return True\n elif obj in isfalse:\n return False\n else:\n raise TypeError('could not convert to boolean')\n\n elif hasattr(obj, '__bool__'):\n return bool(obj)\n\n raise TypeError('could not convert to boolean')","title":""},{"docid":"58f18e3557b8c79019f8017bfa25cf8b","score":"0.68012357","text":"def str2bool(v):\n if isinstance(v, bool):\n return v\n if v.lower() in ('yes', 'true', 't', 'y', '1'):\n return True\n elif v.lower() in ('no', 'false', 'f', 'n', '0'):\n return False\n else:\n raise NameError('Boolean value expected.')","title":""},{"docid":"5936cac0641299577fb3f7276714bea4","score":"0.68003225","text":"def boolean_attribute(value: bool) -> bool:\n return attr.ib(default=value, type=bool, kw_only=True)","title":""},{"docid":"753c94461979fb53b449a8a06d3cedef","score":"0.6795977","text":"def test_to_data(self, value, data):\n assert data == Boolean.to_data(value)","title":""},{"docid":"ed23ee9b97a79f52093d9773eb6a3ecb","score":"0.67912906","text":"def str2bool(v:Union[str, bool]) -> bool:\n if isinstance(v, bool):\n b = v\n elif v.lower() in ('yes', 'true', 't', 'y', '1'):\n b = True\n elif v.lower() in ('no', 'false', 'f', 'n', '0'):\n b = False\n else:\n raise ValueError('Boolean value expected.')\n return b","title":""},{"docid":"db971e7830655710e22e31b611ef5080","score":"0.67856514","text":"def to_boolean_with_default(value: Any, default_value: bool) -> bool:\n result = BooleanConverter.to_nullable_boolean(value)\n return result if not (result is None) else bool(default_value)","title":""},{"docid":"a911ead5ace1e02ccb1b9eb40e9ce23f","score":"0.6782127","text":"def boolify(var):\n\n if isinstance(var, str):\n var = strtobool(var)\n if not isinstance(var, bool):\n var = bool(var)\n return var","title":""},{"docid":"e2d502d114c71f9348dda3ad98f23769","score":"0.6767168","text":"def str2bool(v):\n if isinstance(v, bool):\n return v\n if v.lower() in ('yes', 'true', 't', 'y', '1'):\n return True\n elif v.lower() in ('no', 'false', 'f', 'n', '0'):\n return False\n else:\n raise ValueError('Boolean value expected.')","title":""}],"string":"[\n {\n \"docid\": \"5d4bd8517d78334032a46f042455bfcc\",\n \"score\": \"0.863882\",\n \"text\": \"def to_boolean(value: Any) -> bool:\\n return BooleanConverter.to_boolean_with_default(value, False)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fee659ff6685b59b558ebd84f3dfcd34\",\n \"score\": \"0.85566324\",\n \"text\": \"def _asBool(self):\\n return bool(self.value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5549e9521f472bef0c2e79ce6fadbfee\",\n \"score\": \"0.8505888\",\n \"text\": \"def Boolean(value):\\n return asbool(value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"152a19f4ccb3cf31bcd5e49f3215af9f\",\n \"score\": \"0.8140877\",\n \"text\": \"def ToBool(value):\\n if str(value).lower() in (\\\"yes\\\", \\\"y\\\", \\\"true\\\", \\\"t\\\", \\\"1\\\"): return True\\n if str(value).lower() in (\\\"no\\\", \\\"n\\\", \\\"false\\\", \\\"f\\\", \\\"0\\\", \\\"0.0\\\", \\\"\\\", \\\"none\\\", \\\"[]\\\", \\\"{}\\\"): return False\\n raise Exception('Invalid value for boolean conversion: ' + str(value))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aa3afed99a944fa7ea8ee3c511dfb7dd\",\n \"score\": \"0.8091099\",\n \"text\": \"def to_bool(value):\\n return str(value).lower() in ['1', 't', 'true', 'y', 'yes']\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5b6a6f43f74198e575baa21b4b31dc46\",\n \"score\": \"0.805445\",\n \"text\": \"def _cast_boolean(self, value):\\n value = str(value)\\n if value == '':\\n return False\\n else:\\n return value.strip() in ['True', 'true', '1']\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5d0b1f098787a4c1345d5ddbc97bff83\",\n \"score\": \"0.79466623\",\n \"text\": \"def Bool(value):\\n return get_env().formula_manager.Bool(value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4b2de0974683f4b14a70e9eac5686603\",\n \"score\": \"0.7910972\",\n \"text\": \"def to_bool(val) -> bool:\\n\\n if type(val) == bool:\\n return val\\n else:\\n return bool(strtobool(val))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5ecc9b7699d7f12da4a3338cfffcc4c9\",\n \"score\": \"0.7887335\",\n \"text\": \"def to_bool(value):\\n if str(value).lower() in (\\\"yes\\\", \\\"y\\\", \\\"true\\\", \\\"t\\\", \\\"1\\\"): return True\\n if str(value).lower() in (\\\"no\\\", \\\"n\\\", \\\"false\\\", \\\"f\\\", \\\"0\\\", \\\"0.0\\\", \\\"\\\", \\\"none\\\", \\\"[]\\\", \\\"{}\\\"): return False\\n raise Exception('Invalid value for boolean conversion: ' + str(value))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0b7e2fd26e6ba7ad0241181964ee8c83\",\n \"score\": \"0.78812224\",\n \"text\": \"def to_bool(value):\\n if value is None:\\n return False\\n if str(value).lower() in (\\\"yes\\\", \\\"y\\\", \\\"true\\\", \\\"t\\\", \\\"1\\\"):\\n return True\\n if str(value).lower() in (\\\"no\\\", \\\"n\\\", \\\"false\\\", \\\"f\\\", \\\"0\\\", \\\"0.0\\\", \\\"\\\", \\\"none\\\", \\\"[]\\\", \\\"{}\\\"):\\n return False\\n raise Exception('Invalid value for boolean conversion: ' + str(value))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a05ebade6b6931beb40494e0aed19ddc\",\n \"score\": \"0.778305\",\n \"text\": \"def boolean_argument(value):\\n return bool(strtobool(value))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a05ebade6b6931beb40494e0aed19ddc\",\n \"score\": \"0.778305\",\n \"text\": \"def boolean_argument(value):\\n return bool(strtobool(value))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b9b5c3ec5dea158c5f87928bc5a796a5\",\n \"score\": \"0.77716255\",\n \"text\": \"def asbool(value):\\n if value is None:\\n return False\\n\\n if isinstance(value, bool):\\n return value\\n\\n return value.lower() in (\\\"true\\\", \\\"1\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f2a9974c3e0df6f237cf448194d5193d\",\n \"score\": \"0.77589124\",\n \"text\": \"def cast_value(self, value: str) -> typing.Any:\\n if value.lower() in ['true', '1']:\\n return True\\n elif value.lower() in ['false', '0']:\\n return False\\n else:\\n return bool(value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b822c642ed923e6f3ef73368f40c4a98\",\n \"score\": \"0.77273583\",\n \"text\": \"def convert_to_boolean(value):\\n if isinstance(value, string_types):\\n if value.lower() in ['t', 'true', 'on', 'yes', '1']:\\n return True\\n elif value.lower() in ['f', 'false', 'off', 'no', '0']:\\n return False\\n\\n return value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d904a4d5d3cfc3ef0854072941be1289\",\n \"score\": \"0.77238077\",\n \"text\": \"def to_bool(value=\\\"\\\"):\\n # type: (str) -> bool\\n return str(value).lower() in {\\\"true\\\", \\\"on\\\", \\\"1\\\", \\\"yes\\\", \\\"oui\\\"}\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c82741facae2627581e676a65edd8a5b\",\n \"score\": \"0.7716701\",\n \"text\": \"def __bool__(self):\\n return bool(self._value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dd3be86b0e8a070111f687720078ae91\",\n \"score\": \"0.7668287\",\n \"text\": \"def _convert_to_boolean(value):\\n if value.lower() not in Config.BOOLEAN_STATES:\\n raise ValueError('Not a boolean: %s' % value)\\n return Config.BOOLEAN_STATES[value.lower()]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ddcba74d8e55d97272a649011032af42\",\n \"score\": \"0.766755\",\n \"text\": \"def _bool(value):\\r\\n if value == 0 or isinstance(value, (str, native_str)):\\r\\n return True\\r\\n return bool(value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e9ad4b790d01e118633f57d689acb3ea\",\n \"score\": \"0.7658754\",\n \"text\": \"def boolean_converter(val):\\n\\n boolean_vals = ('true', '1', 'yes', 'y')\\n\\n if val and (str(val).lower() in boolean_vals):\\n return True\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"90f61bd8b0e8a39d176557a4ef303050\",\n \"score\": \"0.7608571\",\n \"text\": \"def to_python(self, value):\\r\\n if value in (True, 'True', '1'):\\r\\n return True\\r\\n elif value in (False, 'False', '0'):\\r\\n return False\\r\\n else:\\r\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f740c93fce8cfd419b3ff77dff114296\",\n \"score\": \"0.7589277\",\n \"text\": \"def to_boolean(value):\\n _BOOL_STATES = {'1': True, 'yes': True, 'true': True, 'on': True,\\n '0': False, 'no': False, 'false': False, 'off': False}\\n\\n value = str(value).lower().strip()\\n if value not in _BOOL_STATES:\\n raise ValueError(value)\\n return _BOOL_STATES[value]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b6ab2da8d9699ed2a31aa3a953649393\",\n \"score\": \"0.7586434\",\n \"text\": \"def __bool__(self) -> bool:\\n return bool(self._value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f34b30f231730d7f6c9bf972c49e7f72\",\n \"score\": \"0.75436604\",\n \"text\": \"def get_boolean_value(self):\\n if self._type != Value.BOOLEAN:\\n raise Exception(\\\"Illegal boolean\\\")\\n return self._value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ce57f426af424934d2deeabfb2412a22\",\n \"score\": \"0.7542982\",\n \"text\": \"def asBool(*args, **kwargs):\\n \\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ce57f426af424934d2deeabfb2412a22\",\n \"score\": \"0.7542982\",\n \"text\": \"def asBool(*args, **kwargs):\\n \\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ecad8791f970f3723fd59de75ffc284f\",\n \"score\": \"0.7542822\",\n \"text\": \"def test_to_value(self, data, value):\\n assert value == Boolean.to_value(data)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6599dd8409758766cc99868194981aa4\",\n \"score\": \"0.75231975\",\n \"text\": \"def is_true(value):\\n return value is True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ad565e81ac837d09fd25a83fd2ac3e97\",\n \"score\": \"0.7481766\",\n \"text\": \"def _getValueAsBoolean(self, node):\\n value = node.attrib[\\\"value\\\"]\\n assert value in (\\\"True\\\", \\\"False\\\",), \\\\\\n \\\"Unexpected boolean value '%s' in tag <%s>\\\" % (value, node.tag)\\n return value == \\\"True\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"df59fb4f07aad74e40eebe0be6f83683\",\n \"score\": \"0.7478464\",\n \"text\": \"def tobool( val ):\\n\\n if val.lower() in [ \\\"y\\\", \\\"yes\\\", \\\"t\\\", \\\"true\\\", \\\"1\\\", 1 ]:\\n return True\\n\\n else:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc8bfe7d7d2c500b9c511901b45d15bb\",\n \"score\": \"0.74751365\",\n \"text\": \"def to_bool(value: str) -> bool:\\n if value in [\\\"True\\\", \\\"true\\\", True]:\\n return True\\n if value in [\\\"False\\\", \\\"false\\\", False]:\\n return False\\n raise ValueError(f\\\"Value {value} cannot be converted into a bool\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3a863b5224795c599adf7234f7f187cf\",\n \"score\": \"0.7473932\",\n \"text\": \"def __bool__(self) -> bool:\\n return bool(self.value())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f480182054800cbca996c685b76317db\",\n \"score\": \"0.7471968\",\n \"text\": \"def _convert_bools(self, name: str, value) -> bool:\\n if isinstance(value, bool):\\n return value\\n\\n if value == None:\\n return None\\n\\n value = str(value).lower()\\n # Try to convert values to the positive.\\n if value == '1' or value == 'true':\\n return True\\n # Try to convert values to the negative.\\n elif value == '0' or value == 'false':\\n return False\\n else:\\n AttributeError('%s field %s should be type bool.' % (\\n __class__.__name__, name))\\n logging.error('%s field %s should be type bool.' % (\\n __class__.__name__, name))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ad80c7e306973716e36fac67f06192a9\",\n \"score\": \"0.74677265\",\n \"text\": \"def convert(self, value, db=None):\\n if value is UNASSIGNED:\\n return value\\n elif value == self.false_label:\\n return False\\n elif value == self.true_label:\\n return True\\n return bool(value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b163d580bcb1c750caf0b71030346de0\",\n \"score\": \"0.74324596\",\n \"text\": \"def is_true(value):\\n\\n return (value is True)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"047685bb875f18d9a673013d8ded321a\",\n \"score\": \"0.7405042\",\n \"text\": \"def cast(self, val):\\n if isinstance(val, bool):\\n return BoolVal(val, self.ctx)\\n if z3_debug():\\n if not is_expr(val):\\n msg = \\\"True, False or Z3 Boolean expression expected. Received %s of type %s\\\"\\n _z3_assert(is_expr(val), msg % (val, type(val)))\\n if not self.eq(val.sort()):\\n _z3_assert(self.eq(val.sort()), \\\"Value cannot be converted into a Z3 Boolean value\\\")\\n return val\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fd7c1a085118afb1096d5f8cacbabeed\",\n \"score\": \"0.73866117\",\n \"text\": \"def convert_tobooleanvalue(i: bytes) -> bool:\\n return bool(int(i))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"58d8cf9c812e8cb9aa79f282a7264d58\",\n \"score\": \"0.7379311\",\n \"text\": \"def int_to_bool(value: int) -> bool:\\n return False if value == 0 else True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b560a25aefc9503e378b1a25d83d3cf4\",\n \"score\": \"0.73696303\",\n \"text\": \"def ToBool(value, default=_DEFAULT):\\n value = str(value).lower()\\n if value in constants.TRUE_VALUES:\\n return True\\n if value in constants.FALSE_VALUES:\\n return False\\n if default is _DEFAULT:\\n raise ConversionError('Cannot convert %r to bool' % value)\\n return default\",\n \"title\": \"\"\n },\n {\n \"docid\": \"18924c11bd08910462a714d3aadd9ffa\",\n \"score\": \"0.73639184\",\n \"text\": \"def _isBool(self):\\n return isinstance(self.value, bool)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"303968e630cce419da26a43e15ad30b2\",\n \"score\": \"0.73460144\",\n \"text\": \"def str_to_bool(value):\\n\\n\\treturn bool(value) and value.lower() != 'false'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fa7f24fa1a2b7dba88d9ea2f63cfd825\",\n \"score\": \"0.73320675\",\n \"text\": \"def str2bool(value: str):\\r\\n if type(value) == bool:\\r\\n return_val = value\\r\\n else:\\r\\n return_val = value.lower() in (\\\"yes\\\", \\\"true\\\", \\\"t\\\", \\\"1\\\")\\r\\n\\r\\n return return_val\",\n \"title\": \"\"\n },\n {\n \"docid\": \"308d960b2394d3cf356386255060a57d\",\n \"score\": \"0.72950953\",\n \"text\": \"def coerceBoolean(value, mode = \\\"best\\\"):\\n\\n # convert true values\\n if value in [ 1, \\\"true\\\", u\\\"true\\\", \\\"yes\\\", u\\\"yes\\\" ]:\\n return True\\n\\n # convert false values\\n if value in [ 0, \\\"false\\\", u\\\"false\\\", \\\"no\\\", u\\\"no\\\" ]:\\n return False\\n\\n return _handleMode(value, \\\"boolean\\\", mode)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"af5884d6985969a1ae66b7b768681847\",\n \"score\": \"0.728786\",\n \"text\": \"def str_to_bool(value):\\n value = value.lower()\\n return value in ['true', '1', 'up', 'on']\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b63c7737c56ecb65287daf11935571ce\",\n \"score\": \"0.72775364\",\n \"text\": \"def _to_bool(x):\\n return x.astype(bool)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d1fc6eee2a24c6d115f05d08b17b3fe4\",\n \"score\": \"0.72260445\",\n \"text\": \"def get_as_boolean(self, index):\\n value = self[index]\\n return BooleanConverter.to_boolean(value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1b0710f5c864160a2ee4636c9df306ca\",\n \"score\": \"0.7219768\",\n \"text\": \"def isBool(self, input_val):\\n if isinstance(input_val, str):\\n if input_val.upper() in ['FALSE', '0', 'NO']:\\n input_val = False\\n elif input_val.upper() in ['TRUE', '1', 'YES']:\\n input_val = True\\n else:\\n input_val = None\\n elif isinstance(input_val, int):\\n if input_val == 0:\\n input_val = False\\n if input_val == 1:\\n input_val = True\\n return input_val\",\n \"title\": \"\"\n },\n {\n \"docid\": \"10ed659e88d76c16a8c08cf0686aa763\",\n \"score\": \"0.71981543\",\n \"text\": \"def bool_value(self):\\n if self.value:\\n if self.value.lower() in self.MEANS_YES:\\n return True\\n return False\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"85517e0e1cc5c6324b0a30b20d2927e4\",\n \"score\": \"0.71761125\",\n \"text\": \"def check_value(self, value: typing.Any) -> bool:\\n return isinstance(value, bool)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"19f9780982e16e4347626a635cf3a936\",\n \"score\": \"0.71621436\",\n \"text\": \"def coerce_boolean(value):\\n if is_string(value):\\n normalized = value.strip().lower()\\n if normalized in ('1', 'yes', 'true', 'on'):\\n return True\\n elif normalized in ('0', 'no', 'false', 'off', ''):\\n return False\\n else:\\n msg = \\\"Failed to coerce string to boolean! (%r)\\\"\\n raise ValueError(format(msg, value))\\n else:\\n return bool(value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0d0e9305d874b730505cb9d61668baf6\",\n \"score\": \"0.7159789\",\n \"text\": \"def getValue(self) -> \\\"bool\\\" :\\n return _quickfix.BoolField_getValue(self)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aa9b9533dd98cb4c8e0be397fe7e88ae\",\n \"score\": \"0.71549124\",\n \"text\": \"def __nonzero__(self):\\n return bool(self.value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"17b96aafb0ade443469d31af099aea25\",\n \"score\": \"0.7142359\",\n \"text\": \"def boolean(value, context=None):\\n try:\\n return bool(value)\\n except (TypeError, ValueError):\\n raise ValidationException('This field is suppose to be boolean')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9fb1ff055a4a07904cc53e5b4ccbe379\",\n \"score\": \"0.71229684\",\n \"text\": \"def toBool(x):\\n if x.lower() == 'true':\\n return True\\n elif x.lower() == 'false':\\n return False\\n else:\\n raise ValueError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3152c4dc4abd610c93e6df0d969d5a85\",\n \"score\": \"0.71187764\",\n \"text\": \"def boolean(val):\\n\\n return str(val).lower() in ('1', 'yes', 'true', 'on')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5ff118df1008664795ea658297365504\",\n \"score\": \"0.7100943\",\n \"text\": \"def return_true(value):\\n\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"53a0bd3c59e574e293c4f3dbb6e9abc2\",\n \"score\": \"0.70947546\",\n \"text\": \"def test_boolean_true_returns_true(self):\\n self.assertEqual(to_bool(True), True)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9fc411687c2f88283d0a4a9acb423ad3\",\n \"score\": \"0.7082532\",\n \"text\": \"def create_boolean(value):\\n return jpath4.query.data.StandardSequence([jpath4.query.data.StandardBoolean(value)])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"88492eeb0a75a5a12a18e2982043c974\",\n \"score\": \"0.7072428\",\n \"text\": \"def as_bool(self, key):\\n val = self[key]\\n if val == True:\\n return True\\n elif val == False:\\n return False\\n else:\\n try:\\n if not isinstance(val, StringTypes):\\n raise KeyError\\n else:\\n return self.main._bools[val.lower()]\\n except KeyError:\\n raise ValueError('Value \\\"%s\\\" is neither True nor False' % val)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"694b34e0e0a4e600e9f4259b9eac7dcc\",\n \"score\": \"0.70704985\",\n \"text\": \"def _createBool(newvalue):\\n return CableValue(bool(newvalue))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7deb4fa56286f58f427fb660228af857\",\n \"score\": \"0.7061925\",\n \"text\": \"def to_nullable_boolean(value: Any) -> Optional[bool]:\\n # Shortcuts\\n if value is None:\\n return None\\n if type(value) is type(True):\\n return value\\n\\n str_value = str(value).lower()\\n # All true values\\n if str_value in ['1', 'true', 't', 'yes', 'y']:\\n return True\\n # All false values\\n if str_value in ['0', 'false', 'f', 'no', 'n']:\\n return False\\n\\n # Everything else:\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8b803f187ea1c634faafc873dd25c193\",\n \"score\": \"0.7034297\",\n \"text\": \"def process_value(self, value):\\n if value == self.TRUE_VALUE:\\n return True\\n elif value == self.FALSE_VALUE:\\n return False\\n else:\\n raise QueryParameterInvalidError(self.name, value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ac3ef8af0471644195044b0f76e57e09\",\n \"score\": \"0.70269805\",\n \"text\": \"def _isValueBoolean(actuator):\\n return actuator.value == 0 or \\\\\\n actuator.value == 1 or \\\\\\n actuator.value.upper == \\\"TRUE\\\" or \\\\\\n actuator.value.upper == \\\"FALSE\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7083dc2fa0d3116edfc60c91e3d3867b\",\n \"score\": \"0.702437\",\n \"text\": \"def str2bool(val):\\n if val not in [u\\\"True\\\", u\\\"False\\\"]:\\n # Not using ValueError intentionally: all config errors are RuntimeError\\n raise RuntimeError(\\\"Found %s instead of 'True' of 'False'\\\" % val)\\n elif val == u\\\"True\\\":\\n return True\\n else:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"efa7c3dcdb41fd829b58f2086e05dd18\",\n \"score\": \"0.702407\",\n \"text\": \"def str2bool(value: Union[bool, str]) -> bool:\\n\\n value2 = False\\n\\n if isinstance(value, bool):\\n value2 = value\\n else:\\n value2 = value.lower() in ('yes', 'true', 't', '1', 'on')\\n\\n return value2\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5bb497518166dcd48c2db5cf81d5ed56\",\n \"score\": \"0.70188636\",\n \"text\": \"def boolean(value):\\n def _boolean():\\n return value\\n return _boolean\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9d2d9cd5b0141f91dd51756100b0f12c\",\n \"score\": \"0.7016583\",\n \"text\": \"def boolval(b):\\n b = str(b).lower()\\n if b in [ 'true', '1', 'yes']:\\n return True\\n elif b in [ 'false', '0', 'no']:\\n return False\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c30fd04719265bc7eba35aa0d9638f19\",\n \"score\": \"0.7000714\",\n \"text\": \"def create_boolean(b):\\n return Value(Value.BOOLEAN, b)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"202d7a8ae17ab603e07755240e67ebf3\",\n \"score\": \"0.698797\",\n \"text\": \"def to_python(self, value):\\n # Explicitly check for the string 'False', which is what a hidden field\\n # will submit for False. Also check for '0', since this is what\\n # RadioSelect will provide. Because bool(\\\"True\\\") == bool('1') == True,\\n # we don't need to handle that explicitly.\\n\\n if isinstance(value, six.string_types) and value.lower() in ('false', '0'):\\n value = False\\n\\n elif value is None:\\n value = False\\n\\n elif value is False:\\n value = False\\n\\n elif isinstance(value, six.string_types) and value.lower() in ('true', '1'):\\n value = True\\n\\n elif value is True:\\n value = True\\n\\n else:\\n raise ValidationError(u'%s is not boolean' % value)\\n\\n return value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"65e141b751c949981991292048b86e74\",\n \"score\": \"0.6986076\",\n \"text\": \"def booleanize(value):\\n true_values = (\\\"yes\\\", \\\"true\\\", \\\"1\\\")\\n false_values = (\\\"no\\\", \\\"false\\\", \\\"0\\\")\\n if isinstance(value, bool):\\n return value\\n if value.lower() in true_values:\\n return True\\n elif value.lower() in false_values:\\n return False\\n raise TypeError(\\\"Cannot booleanize ambiguous value '%s'\\\" % value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4eaaaeb9cf23123e283c45ddd5f97da4\",\n \"score\": \"0.69842726\",\n \"text\": \"def b(value):\\n return 'true' if value else 'false'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b1c9f2d3469c5d1bd869f6034e393c0d\",\n \"score\": \"0.69831014\",\n \"text\": \"def get_boolean(self, key):\\n def convert(val, context):\\n if val in [True, False, None]:\\n return val\\n elif str(val).lower() in [\\\"y\\\", \\\"yes\\\", \\\"true\\\", \\\"on\\\", \\\"1\\\"]:\\n return True\\n elif str(val).upper() in [\\\"n\\\", \\\"no\\\", \\\"false\\\", \\\"off\\\", \\\"0\\\"]:\\n return False\\n else:\\n raise ConfigConversionError(\\n \\\"must be y/n, yes/no, true/false, on/off, or 0/1\\\")\\n return self.get(key, convert)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3afa7882bea0c527b43a43bf1c02b506\",\n \"score\": \"0.6974749\",\n \"text\": \"def convert_config_value(self, value, label):\\n if isinstance(value, six.string_types):\\n value = value.lower()\\n\\n if value in self.TRUTHY_VALUES:\\n return True\\n elif value in self.FALSY_VALUES:\\n return False\\n else:\\n raise YapconfValueError(\\n \\\"Cowardly refusing to interpret \\\"\\n \\\"config value as a boolean. Name: \\\"\\n \\\"{0}, Value: {1}\\\".format(self.name, value)\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"242c4390159ee9604ee6a46601eada41\",\n \"score\": \"0.695988\",\n \"text\": \"def tgread_bool(self):\\n value = self.read_int(signed=False)\\n if value == 0x997275b5: # boolTrue\\n return True\\n elif value == 0xbc799737: # boolFalse\\n return False\\n else:\\n raise RuntimeError('Invalid boolean code {}'.format(hex(value)))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6c06cf052cbb81a503c348c4594111ef\",\n \"score\": \"0.6923948\",\n \"text\": \"def read_boolean(self):\\n s = self.read_typed(str).lower()\\n if s == 'true':\\n return True\\n elif s == 'false':\\n return False\\n else:\\n raise ValueError('Cannot convert \\\\'%s\\\\' to a boolean' % s)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d65e63e8967b9ebdda6dc4700d43058c\",\n \"score\": \"0.69234395\",\n \"text\": \"def is_bool(value: int) -> bool:\\n return TypeRanges.BOOL.inf <= remove_base_prefix(value) <= TypeRanges.BOOL.max\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f571247350ec7d632b26ddf7a1996965\",\n \"score\": \"0.69179946\",\n \"text\": \"def parse_bool(value):\\n try:\\n return bool(int(value))\\n except ValueError:\\n lowercase = value.lower()\\n if lowercase == 'true':\\n return True\\n elif lowercase == 'false':\\n return False\\n raise ValueError('Unable to parse {} as a bool'.format(value))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3160f070a603119490211288df8f978b\",\n \"score\": \"0.69152445\",\n \"text\": \"def bool_from_header_value(value):\\n if isinstance(value, bool):\\n return value\\n elif isinstance(value, (basestring, unicode)):\\n if str(value).lower() == 'true':\\n return True\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"30ff6569861b4352f1e780a8026ff96e\",\n \"score\": \"0.69151366\",\n \"text\": \"def value_to_bool(value: Optional[OptionValue]) -> Optional[bool]:\\n retval: Optional[bool]\\n\\n if value is None:\\n retval = None\\n else:\\n if isinstance(value, bool):\\n retval = value\\n elif isinstance(value, (int, float)):\\n retval = bool(value)\\n elif isinstance(value, str):\\n if value in TRUE_VALUES:\\n retval = True\\n elif value in FALSE_VALUES:\\n retval = False\\n else:\\n raise ValueError\\n else:\\n raise ValueError\\n\\n return retval\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7de6fbe87543b2a089fff9fe43df98c8\",\n \"score\": \"0.68959\",\n \"text\": \"def BoolVal(val, ctx=None):\\n ctx = _get_ctx(ctx)\\n if val:\\n return BoolRef(Z3_mk_true(ctx.ref()), ctx)\\n else:\\n return BoolRef(Z3_mk_false(ctx.ref()), ctx)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ee062ebe39a4b56b955fe272b71e5e2b\",\n \"score\": \"0.68944204\",\n \"text\": \"def to_bool_arg(self, arg):\\n if arg == 1:\\n return True\\n elif arg == -1:\\n return False\\n else:\\n Exception(\\n f\\\"Unknown int value for the trarnsformation to bool: {arg}\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8620873d239787c909fd657f33a36606\",\n \"score\": \"0.6894205\",\n \"text\": \"def _booleanConverter(self, input):\\n if input in [True, False]:\\n return input\\n\\n if input in [1, '1']:\\n return True\\n\\n if input in [0, '0']:\\n return False\\n\\n try:\\n input_lower = input.lower()\\n except:\\n raise ValueError('Not a boolean value: %s' % (input))\\n\\n if input_lower in ['yes', 'true']:\\n return True\\n if input_lower in ['no', 'false']:\\n return False\\n\\n raise ValueError('Not a boolean value: %s' % (input))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a917be036c9e4971b80a0a83c05a4cd0\",\n \"score\": \"0.68868613\",\n \"text\": \"def _bool(v):\\n try:\\n if isinstance(v, basestring):\\n return v.lower() in ['t', 'true', '1']\\n return bool(v)\\n except Exception:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"678b468f331a8cdc82c7cd764d3eac5e\",\n \"score\": \"0.6871099\",\n \"text\": \"def as_bool(self, key):\\r\\n val = self[key]\\r\\n if val == True:\\r\\n return True\\r\\n elif val == False:\\r\\n return False\\r\\n else:\\r\\n try:\\r\\n if not isinstance(val, basestring):\\r\\n # TODO: Why do we raise a KeyError here?\\r\\n raise KeyError()\\r\\n else:\\r\\n return self.main._bools[val.lower()]\\r\\n except KeyError:\\r\\n raise ValueError('Value \\\"%s\\\" is neither True nor False' % val)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2bb29530594fcdb50b95db11ead3166f\",\n \"score\": \"0.6866402\",\n \"text\": \"def get_bool(value: str) -> Union[bool, None]:\\n lowered = str(value).lower()\\n\\n if lowered in (\\\"yes\\\", \\\"y\\\", \\\"true\\\", \\\"t\\\", \\\"1\\\", \\\"enable\\\", \\\"on\\\"):\\n val = True\\n elif lowered in (\\\"no\\\", \\\"n\\\", \\\"false\\\", \\\"f\\\", \\\"0\\\", \\\"disable\\\", \\\"off\\\"):\\n val = False\\n else:\\n val = None\\n\\n return val\",\n \"title\": \"\"\n },\n {\n \"docid\": \"18c821be7834ef5744dbb6c01b41fc2b\",\n \"score\": \"0.6851357\",\n \"text\": \"def bool(self, python_bool_var):\\n return \\\"true\\\" if python_bool_var else \\\"false\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ad5815754f4fdf1824bb472f7daccf41\",\n \"score\": \"0.684874\",\n \"text\": \"def str_to_bool(value):\\n if isinstance(value, bool):\\n return value\\n if value.lower() in ('yes', 'true', 't', 'y', '1'):\\n return True\\n elif value.lower() in ('no', 'false', 'f', 'n', '0'):\\n return False\\n else:\\n raise argparse.ArgumentTypeError('Boolean value expected.')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0b5cafaf8828264b59281d1e57772aa0\",\n \"score\": \"0.68455356\",\n \"text\": \"def encode_boolean(self, b):\\r\\n if bool(b):\\r\\n return 'true'\\r\\n return 'false'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c17a19290ec6accd24b975d73ebc2c0e\",\n \"score\": \"0.68455225\",\n \"text\": \"def to_python(self, value):\\r\\n # Explicitly check for the string 'False', which is what a hidden field\\r\\n # will submit for False. Also check for '0', since this is what\\r\\n # RadioSelect will provide. Because bool(\\\"True\\\") == bool('1') == True,\\r\\n # we don't need to handle that explicitly.\\r\\n if value in ('False', '0'):\\r\\n value = False\\r\\n else:\\r\\n value = bool(value)\\r\\n value = super(BooleanField, self).to_python(value)\\r\\n if not value and self.required:\\r\\n raise ValidationError(self.error_messages['required'])\\r\\n return value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ffbce9bfcfe147945be164c5bb1fa622\",\n \"score\": \"0.68400574\",\n \"text\": \"def to_be_a_bool(self, message: Optional[str] = \\\"\\\") -> bool:\\n return cast(bool, self.to_be_a(ExpectedType.BOOLEAN, message))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5f0c34b070eec24419d7041290065b0a\",\n \"score\": \"0.6823493\",\n \"text\": \"def str_to_bool(value):\\n if not value:\\n return False\\n if value.lower() in STR_FALSE:\\n return False\\n if value.lower() in STR_TRUE:\\n return True\\n raise ValueError(\\\"Invalid truth value '%s'\\\" % value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"17ca97bc6a0078427e1e55826c4b9d5e\",\n \"score\": \"0.6804988\",\n \"text\": \"def to_bool(var):\\n if isinstance(var, str):\\n if var == '' or var.lower() == 'false':\\n return False\\n else:\\n return True\\n return bool(var)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"35a5b9c43e8c6805dec62e2fbe010672\",\n \"score\": \"0.6801289\",\n \"text\": \"def convert_to_boolean(obj):\\n istrue = ('true', 'yes', 'ok', '1', 'on', '+', 'True', 'Yes', 'Ok', 'On', 'TRUE', 'YES', 'OK', 'ON', 1, 1.0)\\n isfalse = ('false', 'no', '0', '-', 'off', 'False', 'No', 'Off', 'FALSE', 'NO', 'OFF', 0, 0.0)\\n\\n if isinstance(obj, (str, int, float)):\\n if obj in istrue:\\n return True\\n elif obj in isfalse:\\n return False\\n else:\\n raise TypeError('could not convert to boolean')\\n\\n elif hasattr(obj, '__bool__'):\\n return bool(obj)\\n\\n raise TypeError('could not convert to boolean')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"58f18e3557b8c79019f8017bfa25cf8b\",\n \"score\": \"0.68012357\",\n \"text\": \"def str2bool(v):\\n if isinstance(v, bool):\\n return v\\n if v.lower() in ('yes', 'true', 't', 'y', '1'):\\n return True\\n elif v.lower() in ('no', 'false', 'f', 'n', '0'):\\n return False\\n else:\\n raise NameError('Boolean value expected.')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5936cac0641299577fb3f7276714bea4\",\n \"score\": \"0.68003225\",\n \"text\": \"def boolean_attribute(value: bool) -> bool:\\n return attr.ib(default=value, type=bool, kw_only=True)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"753c94461979fb53b449a8a06d3cedef\",\n \"score\": \"0.6795977\",\n \"text\": \"def test_to_data(self, value, data):\\n assert data == Boolean.to_data(value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ed23ee9b97a79f52093d9773eb6a3ecb\",\n \"score\": \"0.67912906\",\n \"text\": \"def str2bool(v:Union[str, bool]) -> bool:\\n if isinstance(v, bool):\\n b = v\\n elif v.lower() in ('yes', 'true', 't', 'y', '1'):\\n b = True\\n elif v.lower() in ('no', 'false', 'f', 'n', '0'):\\n b = False\\n else:\\n raise ValueError('Boolean value expected.')\\n return b\",\n \"title\": \"\"\n },\n {\n \"docid\": \"db971e7830655710e22e31b611ef5080\",\n \"score\": \"0.67856514\",\n \"text\": \"def to_boolean_with_default(value: Any, default_value: bool) -> bool:\\n result = BooleanConverter.to_nullable_boolean(value)\\n return result if not (result is None) else bool(default_value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a911ead5ace1e02ccb1b9eb40e9ce23f\",\n \"score\": \"0.6782127\",\n \"text\": \"def boolify(var):\\n\\n if isinstance(var, str):\\n var = strtobool(var)\\n if not isinstance(var, bool):\\n var = bool(var)\\n return var\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e2d502d114c71f9348dda3ad98f23769\",\n \"score\": \"0.6767168\",\n \"text\": \"def str2bool(v):\\n if isinstance(v, bool):\\n return v\\n if v.lower() in ('yes', 'true', 't', 'y', '1'):\\n return True\\n elif v.lower() in ('no', 'false', 'f', 'n', '0'):\\n return False\\n else:\\n raise ValueError('Boolean value expected.')\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":391,"cells":{"query_id":{"kind":"string","value":"5f2376e139bf9216035dd5e8721f8c77"},"query":{"kind":"string","value":"Get a 2d numpy array of obstacles in the form [[x, y], [x, y], ...]"},"positive_passages":{"kind":"list like","value":[{"docid":"74d1869550c2ceeb24977a200a7bdbae","score":"0.7013155","text":"def get_obstacles(self):\n return np.argwhere(self.obstacles == True) * self.config.grid_reso","title":""}],"string":"[\n {\n \"docid\": \"74d1869550c2ceeb24977a200a7bdbae\",\n \"score\": \"0.7013155\",\n \"text\": \"def get_obstacles(self):\\n return np.argwhere(self.obstacles == True) * self.config.grid_reso\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"3e0ccacd4db9e4bc1fcb1726c1a0fa96","score":"0.7382825","text":"def obstacles(self):\n return list(self._obstacles)","title":""},{"docid":"6586c95dc5ce60c31e82d33802373a2e","score":"0.7301217","text":"def get_obstacles_positions(obstacles: []) -> List[Position]:\n obstacles_positions: List[Position] = []\n # Iterate over two-dimensional array\n for obstacle in obstacles:\n # Create a position object to append to a list\n position = Position(obstacle[0], obstacle[1])\n obstacles_positions.append(position)\n \n return obstacles_positions","title":""},{"docid":"9cfec27324a94fe3b91b1970dca4f753","score":"0.66640806","text":"def get_static_obstacles(self):\n # gap = 0.20/self.difficulty\n #\n # # Vertical bars\n # self.O1 = (0.47, 0, 0.47 + self.wall_width, 0.17 - gap)\n # self.O2 = (0.47, 0.15 + gap, 0.47 + self.wall_width, 0.85 - gap)\n # self.O3 = (0.47, 0.85 + gap, 0.47 + self.wall_width, 1)\n #\n # # Top horizontal bars\n # self.O4 = (0, 0.65, 0.25 - gap, 0.65 + self.wall_width)\n # self.O5 = (0.25 + gap, 0.65, 0.75 - gap, 0.65 + self.wall_width)\n # self.O6 = (0.75 + gap, 0.65, 1, 0.65 + self.wall_width)\n #\n # # Bottom Horizontal bars\n # self.O7 = (0, 0.3, 0.75 - gap, 0.3 + self.wall_width)\n # self.O8 = (0.75 + gap, 0.3, 1, 0.3 + self.wall_width)\n #\n # obstacles = [self.O1, self.O2, self.O3, self.O4, self.O5, self.O6, self.O7, self.O8]\n #\n\n self.O1 = (0, 0.25, 0 + self.wall_width + 0.45, 0.25 + self.wall_width) # (0, 0.25, 0.5, 0.3)\n self.O2 = (0.5, 0.25, 0.5 + self.wall_width, 0.25 + self.wall_width + 0.5) # (0.5, 0.25, 0.55, 0.8)\n obstacles = [self.O1, self.O2]\n\n # obstacles = []\n return obstacles","title":""},{"docid":"02b235591e00832cd6400ac079a719e0","score":"0.64403796","text":"def generate_obstacles(self, num_obs):\n obs_list = []\n while len(obs_list) < num_obs:\n obs = [random.randint(1, self.x_axis_max - 1), random.randint(1, self.y_axis_max - 1)]\n if obs in obs_list:\n continue\n elif obs[0] == self.goal[0] and obs[1] == self.goal[1]:\n continue\n elif obs[0] == self.start[0] and obs[1] == self.start[1]:\n continue\n else:\n obs_list.append(obs)\n\n # set grid map boundary as obstacles as well\n for x in range(1, self.x_axis_max):\n obs_list.append([x, 0])\n obs_list.append([x, self.y_axis_max])\n for y in range(1, self.y_axis_max):\n obs_list.append([0, y])\n obs_list.append([self.x_axis_max, y])\n obs_list.append([0, 0])\n obs_list.append([0, self.y_axis_max])\n obs_list.append([self.x_axis_max, 0])\n obs_list.append([self.x_axis_max, self.y_axis_max])\n\n # print(obs_list)\n # print(len(obs_list))\n return obs_list","title":""},{"docid":"efdc794cce2a38b3c931f0fe59dd7a6e","score":"0.618513","text":"def get_1D_neighbors(self):\n adjacents = [(-1,-1), (-1,0), (-1,1), (0,1), (1,1), (1,0), (1,-1), (0,-1)]\n \n nb = np.full((self.obstacle_map.size,8), -1, dtype=np.int)\n \n for [x,y] in self.visible_cells:\n index_1D = self.indexFromXY(x,y,self.obstacle_map.shape[1])\n for i, (xpos,ypos) in enumerate(adjacents):\n if 0 <= x+xpos < self.obstacle_map.shape[0] and 0 <= y+ypos < self.obstacle_map.shape[1]:\n if not self.obstacle_map[x+xpos, y+ypos] < 0:\n nb[index_1D, i] = self.indexFromXY(xpos+x, ypos+y, self.obstacle_map.shape[1])\n return nb","title":""},{"docid":"b338602d20022ae37fde0d07b8fba14c","score":"0.61557966","text":"def get_neighbors(x, y):\n return[\n (x, y - 1), (x + 1, y), (x - 1, y), (x - 1, y - 1),\n (x, y + 1), (x + 1, y + 1), (x - 1, y + 1), (x + 1, y - 1)\n ]","title":""},{"docid":"a48168b025bfb05d13efde67a68fabbb","score":"0.61122984","text":"def createObstacles():\n for ob in obs_list:\n pygame.draw.rect(screen, red, pygame.Rect(ob))","title":""},{"docid":"665be9bda3cf36bfb24363aec0b888fd","score":"0.59382457","text":"def GetPositions2D(self):\r\n return np.resize(self.positions,(4,2))","title":""},{"docid":"08860687d915a45eacd0be063a273d76","score":"0.5890589","text":"def add_obstacles(self, obstacles):\n for obstacle in obstacles:\n x1, y1, x2, y2 = (np.array(obstacle) / self.grid_res).astype(int)\n self.grid_data[x1:x2, y1:y2] = 1.0","title":""},{"docid":"a8b2155e725bf652598d49cae4c975f8","score":"0.58401555","text":"def draw_obstacles(self, obstacles, robot_state):\n # type: (list, RobotState) -> None\n points = []\n for position in obstacles:\n point = _global2local_point(position, robot_state.exact_position, robot_state.exact_rotation)\n points.append(point)\n\n self._draw_sphere_list(0, OBSTACLE_NAMESPACE, OBSTACLE_SCALE, points, color=OBSTACLE_COLOR)","title":""},{"docid":"28be91ac12ce86ef03461bb658876b7f","score":"0.581147","text":"def neighbor_coords(self,x,y):\n neighbors = []\n if self.in_bounds(x+1, y+1): neighbors.append([x+1,y+1])\n if self.in_bounds(x+1, y): neighbors.append([x+1,y])\n if self.in_bounds(x-1, y-1): neighbors.append([x-1,y-1])\n if self.in_bounds(x-1, y): neighbors.append([x-1,y])\n if self.in_bounds(x-1, y+1): neighbors.append([x-1,y+1])\n if self.in_bounds(x, y+1): neighbors.append([x,y+1])\n if self.in_bounds(x+1, y-1): neighbors.append([x+1,y-1])\n if self.in_bounds(x, y-1): neighbors.append([x,y-1])\n return neighbors","title":""},{"docid":"36f12c6bae039b83fd995eb5b47e89ff","score":"0.58062243","text":"def findNeighbours(x,y,img):\n n_img = img\n x_1, y_1, x1, y1 = x-1, y-1, x+1, y+1;\n return [ n_img[x_1][y], n_img[x_1][y1], n_img[x][y1], n_img[x1][y1], n_img[x1][y], n_img[x1][y_1], n_img[x][y_1], img[x_1][y_1] ]","title":""},{"docid":"8d7b14dedce791e218b0a273888c34c2","score":"0.5802935","text":"def _neighbours(self, y, x):\r\n neighbours = []\r\n for dy in range(-1, 2):\r\n for dx in range(-1, 2):\r\n if dy == 0 and dx == 0:\r\n continue\r\n else:\r\n if self._valid_position(y+dy, x+dx):\r\n neighbours.append((y+dy, x+dx))\r\n return neighbours","title":""},{"docid":"722c12cb2d88e712f700a6b9785402c6","score":"0.579285","text":"def getNeighborhood(self):\n neighborhood = \"[\"\n for ry in xrange(-self.radius,self.radius+1,1):\n for rx in xrange(-self.radius,self.radius+1,1):\n if ((ry != 0) or (rx != 0)):\n if (self.neighborhood_select):\n if ((abs(rx) + abs(ry)) <= self.radius):\n arg = \"\".join((\"scratchgrid[rr+\",str(ry),\",cc+\",str(rx),\"],\"))\n neighborhood += \"\".join(arg)\n else:\n pass\n elif (not self.neighborhood_select):\n arg = \"\".join((\"scratchgrid[rr+\",str(ry),\",cc+\",str(rx),\"],\"))\n neighborhood += \"\".join(arg) \n neighborhood = neighborhood[:-1]\n neighborhood += \"\".join(\"]\")\n return neighborhood","title":""},{"docid":"6ce0f2960ed091d59184bd0553c62d73","score":"0.5735862","text":"def find_obstacles(puzzle) -> List[List[int]]:\n for subset in puzzle:\n global side1, side2, side3\n side1 = []\n side2 = []\n side3 = []\n solution = solve(0, subset)\n if not solution:\n return subset\n return []","title":""},{"docid":"3a5855ca4bde28425315368df460d98d","score":"0.57353014","text":"def voisins(pos, obstacles, taille):\r\n res = []\r\n x, y = pos\r\n for i, j in [(0,1),(0,-1),(1,0),(-1,0)]:\r\n if ((x + i,y + j) not in obstacles) and (x + i) >= 0 and (x + i) < taille[0] and (y + j) >= 0 and (y + j) < taille[1]:\r\n res.append((x+i, y + j))\r\n return res","title":""},{"docid":"8acd5edd26f033a0f8bbfcc6513de961","score":"0.57002795","text":"def coord2d(x,y):\n return np.array([x,y])","title":""},{"docid":"7e6a568b8e5248964709a075088d1786","score":"0.5696858","text":"def obstacles_between(self, ship, target, ignore=()):\n obstacles = []\n excl = [ship, target]\n entities = ([] if issubclass(Planet, ignore) else self.all_planets(exclude=excl)) \\\n + ([] if issubclass(Ship, ignore) else self.all_ships(exclude=excl))\n for foreign_entity in entities:\n if collision.intersect_segment_circle(ship, target, foreign_entity, fudge=ship.radius + 0.1):\n obstacles.append(foreign_entity)\n return obstacles","title":""},{"docid":"1bbbe8597e7f7a2affd14d80f986ec10","score":"0.56554735","text":"def return_neighborhoods_coordinates():\r\n return neighborhoods_coordinates","title":""},{"docid":"3a98c3a6c5a23dc3583693ae58219517","score":"0.56311774","text":"def create_grid(width, height):\n return [[0 for _x in range(width)] for _y in range(height)]","title":""},{"docid":"9eb3e2e6703bb0657c870969a6124a53","score":"0.5616334","text":"def get_neighbours(self, coordinates, img):\n nrows = len(img)\n ncols = len(img[0])\n r = coordinates[0]\n c = coordinates[1]\n to_return = [\n [r - 1, c],\n [r + 1, c],\n [r, c - 1],\n [r, c + 1]\n ]\n return [t for t in to_return if 0 <= t[0] < nrows and 0 <= t[1] < ncols]","title":""},{"docid":"96ff6d6f33926296012fa87e1f8870f4","score":"0.56038684","text":"def add_obstacles(self, obs) -> None:\n for o in obs:\n # Convert each bound to xy coordinate\n # Forward converts from latlon to cartesian\n x, y, *_ = self.cartesian.forward(o[\"latitude\"], o[\"longitude\"])\n\n # Add each point to the list and the graph\n obi = Obstacle(Point(x, y, self.alt_bounds[0]), o[\"radius\"], o[\"height\"])\n self.obstacles.append(obi)\n for n in obi.points():\n p = Point(*n)\n if self.boundary_poly.contains(p):\n self.graph.add_node(n)","title":""},{"docid":"7fcf712b9bbeef93e45556a43338e66f","score":"0.5597686","text":"def visible_vertices(p, visible_obstacles):\n V = []\n\n for obstacle in visible_obstacles:\n for vertex in [v[0] for v in obstacle.lines]:\n if line_is_unblocked(p, vertex, visible_obstacles):\n V.append(vertex)\n\n return V","title":""},{"docid":"950907efec3f54bb248e0cd42ad73f30","score":"0.55852616","text":"def array_coords(shape):\n\ty = shape[0]\n\tx = shape[1]\n\tout = scipy.empty((2,y,x))\n\tt = scipy.arange(y,dtype='f8')\n\tout[0] = scipy.tile(t,(x,1)).T\n\tt = scipy.arange(x,dtype='f8')\n\tout[1] = scipy.tile(t,(y,1))\n\treturn out","title":""},{"docid":"bc6a82d54045e6261a88309960cef190","score":"0.5583301","text":"def living_cells(self):\n cells = [(i,j,self.grid[i][j]) for i in range(self.size) for j in range(self.size) if self.grid[i][j] != 0]\n return zip(*cells)","title":""},{"docid":"eebb92d0e81d3bd242ae8a0fa66cb64d","score":"0.55758065","text":"def get_neighbours(self,x_coord, y_coord):\n\t\treturn [(x_coord - 1, y_coord - 1), (x_coord, y_coord - 1), (x_coord + 1, y_coord - 1), \\\n\t\t\t(x_coord - 1, y_coord), (x_coord + 1, y_coord), \\\n\t\t\t(x_coord - 1, y_coord + 1), (x_coord, y_coord + 1), (x_coord + 1, y_coord + 1)]","title":""},{"docid":"7b1fb962f32356f524ad2d0879e3619b","score":"0.5570699","text":"def get_new_position(obstacles, x_bounds, y_bounds):\n while True:\n x = randint(0, x_bounds)\n y = randint(0, y_bounds)\n\n if not geom.point_in_any_obstacle(geom.Point(x, y), obstacles):\n return geom.Point(x, y)","title":""},{"docid":"21e6a90c346db6d339f62ea5fb6f6838","score":"0.55528706","text":"def _determine_cell_neighbours(self, pos):\n x = pos[0]\n y = pos[1]\n\n return [\n (x + 1, y), (x + 1, y + 1), (x, y + 1), (x - 1, y + 1), (x - 1, y),\n (x - 1, y - 1), (x, y - 1), (x + 1, y - 1)\n ]","title":""},{"docid":"a966d58caeb8a7aaeac8f264ce79f89b","score":"0.55523187","text":"def get_available_tiles(self):\r\n self._coordinates = []\r\n available_tiles = []\r\n row = -1\r\n \r\n for segment in self._grid:\r\n temp_coordinates = []\r\n col = -1\r\n row += 1\r\n \r\n for tile in segment:\r\n col += 1\r\n temp_coordinates.append([row,col])\r\n \r\n if tile == 0:\r\n available_tiles.append([row,col])\r\n self._coordinates.append(temp_coordinates)\r\n \r\n return available_tiles","title":""},{"docid":"39d473ea60e1e7374f6108e1507f799c","score":"0.55498344","text":"def neighbors(board, i, j):\n return [board[j - 1][i], board[j + 1][i], board[j][i + 1], board[j][i - 1]]","title":""},{"docid":"99391287badbe6eea36e36d0fa8724c3","score":"0.5535299","text":"def get_dead_board(self):\n return [[0 for x in range(self.width)]\n for x in range(self.height)]","title":""},{"docid":"b3c2ddf5f7225ebfe07107ac53f9dd7b","score":"0.5525028","text":"def find_path(self, obstacles, start, end):\n # type: (list, (float, float), (float, float)) -> list\n return self._a_star(obstacles, position2grid(start), position2grid(end))","title":""},{"docid":"9be7b4b935e618b98c64dd49dc065a68","score":"0.5506782","text":"def draw_map(self):\n for i in range(self.N + 1):\n self.cells.append([])\n for j in range(1, self.N):\n rect(self.screen, (0, 0, 0), (i * self.cell_size, j * self.cell_size, self.cell_size, self.cell_size),\n 2)\n self.cells[i].append([i * self.cell_size, j * self.cell_size, 0])\n self.draw_walls()\n return self.cells","title":""},{"docid":"176ef192ec4ebd700a29c8026d7d83b6","score":"0.54961437","text":"def new_game():\n return np.array([[None] * 3] * 3)","title":""},{"docid":"de42eaec6c23445a3c1603bfe3b63ed5","score":"0.54925996","text":"def detect_obstacles_while_moving(self):\n if self.state == self.STATE_EXPLORATION_RIGHT:\n if any(np.array(self.front_list < self.SCANNER)):\n\n # Get ids in list where obstacle near\n idx_list = np.where(np.array(self.front_list) < self.SCANNER)\n # convert ids into y coordinate\n y_obstacles = self.y_before_step - idx_list[0]*9/100*self.STEP\n scan = np.array(self.front_list)\n # calculate x coordinate of obstacles basted on sensor value\n x_obstacles = self.x + scan[idx_list[0]]\n\n return y_obstacles, x_obstacles\n\n elif self.state == self.STATE_EXPLORATION_LEFT:\n if any(np.array(self.front_list < self.SCANNER)):\n\n idx_list = np.where(np.array(self.front_list) < self.SCANNER)\n y_obstacles = self.y_before_step + idx_list[0]*9/100*self.STEP\n scan = np.array(self.front_list)\n x_obstacles = self.x + scan[idx_list[0]]\n\n return y_obstacles, x_obstacles\n\n elif self.state == self.STATE_FORWARD:\n if any(np.array(self.left_list < self.SCANNER)):\n\n idx_list = np.where(np.array(self.front_list) < self.SCANNER)\n x_obstacles = self.x_before_step + idx_list[0] * 9 / 100 * self.STEP # step when going forward\n scan = np.array(self.front_list)\n y_obstacles = self.x + scan[idx_list[0]]\n\n return y_obstacles, x_obstacles\n\n if any(np.array(self.right_list < self.SCANNER)):\n\n idx_list = np.where(np.array(self.front_list) < self.SCANNER)\n x_obstacles = self.x_before_step + idx_list[0] * 9 / 100 * self.STEP # step when going forward\n scan = np.array(self.front_list)\n y_obstacles = self.x - scan[idx_list[0]]\n\n return y_obstacles, x_obstacles\n else:\n pass","title":""},{"docid":"89848869c8b927f7d71b7b67f98859c1","score":"0.548818","text":"def obstacles_between(ship, target,game_map, ignore_ships = False, ignore_planets= False):\n obstacles = []\n entities = []\n if not ignore_planets :\n entities.extend(game_map.all_planets())\n if not ignore_ships :\n entities.extend(game_map.all_ships())\n for foreign_entity in entities:\n if foreign_entity == ship or foreign_entity == target:\n continue\n if intersect_segment_circle(ship, target, foreign_entity, fudge=ship.radius + 0.1):\n return True\n return False","title":""},{"docid":"715d765c4754e1b6264f6f829777e1e0","score":"0.5478086","text":"def uniquePathsWithObstacles(self, obstacleGrid):\n m = len(obstacleGrid)\n n = len(obstacleGrid[0])\n for i in range(n):\n if obstacleGrid[0][i] == 1:\n for j in range(i, n):\n obstacleGrid[0][j] = 0\n break\n else:\n obstacleGrid[0][i] = 1\n\n for i in range(1, m):\n for j in range(n):\n if obstacleGrid[i][j] == 1:\n obstacleGrid[i][j] = 0\n else:\n if j == 0:\n obstacleGrid[i][j] = obstacleGrid[i-1][j]\n else:\n obstacleGrid[i][j] = obstacleGrid[i-1][j] + obstacleGrid[i][j-1]\n return obstacleGrid[m-1][n-1]","title":""},{"docid":"2b216f471f2998ae4ec097e921ba15be","score":"0.5475305","text":"def matrix_neighbors(row, col, width, height):\n return [(row + i, col + j) for i in (-1, 0, 1) for j in (-1, 0, 1) if 0 <= row + i < width and 0 <= col + j < height]","title":""},{"docid":"00e590855875db5cb6f9c291004724d1","score":"0.54677457","text":"def is_hit_obstacle(self, x, y):\n x = (x / self.config.grid_reso).astype(int)\n y = (y / self.config.grid_reso).astype(int)\n # assuming [0, 0] is always an obstacle because of the boundary\n return self.obstacles[x * ~self.is_out_of_boundary(x, y), y * ~self.is_out_of_boundary(x, y)]","title":""},{"docid":"df392214fec4134c6fe7720b4fff92e4","score":"0.545878","text":"def get_locations(percepts, obstacles):\n possible_locations = []\n possible_starting_points = []\n unique_points = []\n\n # TODO We should add a check to make sure we don't consider\n # any points inside an obstacle\n for obstacle in obstacles:\n for line in obstacle.lines:\n possible_starting_points.append(geom.Point((line[0].x - percepts[0].x),\n (line[0].y - percepts[0].y)))\n unique_points.append(line[0])\n\n for v in possible_starting_points:\n # Create a new point from v (possible agent start position) and percepts.\n # If all new points are actual vertice in on obstacle, v is valid\n valid_point = True\n\n for percept in percepts:\n vertex = geom.Point((v.x + percept.x), (v.y + percept.y))\n\n if not any([vertex == p for p in unique_points]):\n valid_point = False\n break\n\n if valid_point:\n possible_locations.append(v)\n\n return possible_locations","title":""},{"docid":"6796c680ff8ce7cb0ec393e40c6b9f02","score":"0.5443998","text":"def game_board():\r\n board = np.zeros((rows, columns))\r\n return board","title":""},{"docid":"c6bd69a1de3d69b37e1914b0fa0b070f","score":"0.5442009","text":"def nested_coordinates_list(self):\n self._nested_list = []\n map_size = self.rossumoya.map_size\n x, y = map_size\n for x_index in range(x):\n self._nested_list.append([])\n for _ in range(y):\n self._nested_list[x_index].append(None)\n return self._nested_list","title":""},{"docid":"d23198ec76574ba6bee9d5055f462599","score":"0.5438812","text":"def new_board():\n return [[EMPTY for _ in range(NROWS)] for _ in range(NCOLS)]","title":""},{"docid":"e36f51ee15182f0618f30d545e4dada7","score":"0.54108936","text":"def neighbor_cells(arr, coords):\n ndim = arr.ndim\n shape = arr.shape\n return [arr[coords[:d] + (coords[d] + 1,) + coords[d + 1:]]\n for d in range(ndim) if coords[d] + 1 < shape[d]] + \\\n [arr[coords[:d] + (coords[d] - 1,) + coords[d + 1:]]\n for d in range(ndim) if coords[d] > 0]","title":""},{"docid":"f9b9846c09ba117cab379e74958eb571","score":"0.54068756","text":"def get_2D_grid(start_point, end_point, spacing):\n \n x, y = numpy.mgrid[start_point.x:end_point.x:spacing,\n start_point.y:end_point.y:spacing]\n\n x = x.ravel(); y = y.ravel()\n\n return x, y","title":""},{"docid":"818d68e149ce40fccc04bebc7596afc1","score":"0.54047805","text":"def visited_board_16x16() -> List[List[int]]:\r\n return [\r\n [-1, -1, -1, -1],\r\n [-1, -1, -1, -1],\r\n [-1, -1, -1, -1],\r\n [-1, -1, -1, -1]\r\n ]","title":""},{"docid":"2a36047ab1aa9e6215234dd8ba20f20e","score":"0.5374832","text":"def actions(state):\n return visible_vertices(state, env.visible_obstacles)","title":""},{"docid":"9322f5312cc3ec3fedbc43255e6234fa","score":"0.537227","text":"def coords():\n return np.array(\n [[39, 6, -32], [29, 40, 1], [-20, -74, 35], [-29, -59, -37]]\n )","title":""},{"docid":"38a994bc7e87de1533f5ae67549f7432","score":"0.5362488","text":"def get_traffic(self, format=0):\n \n trafficMap = np.zeros(self.obstacle_map.size,dtype=np.int)\n\n # Ground cells\n vCells = np.argwhere(self.obstacle_map.flatten()==0).flatten()\n \n # Update traffic map\n for k in vCells:\n self.get_cell_traffic(k, trafficMap)\n \n if format == 0:\n return trafficMap\n elif format == 1:\n return np.reshape(trafficMap, self.obstacle_map.shape)","title":""},{"docid":"2d9c61b5f44275466c9ad168f53d417f","score":"0.5361387","text":"def get_neighbours(coords):\n\n dxdy = [(-1, -2), (0, -2), (1, -2), (-2, -1), (-1, -1), (0, -1), (1, -1), (2, -1),\n (-2, 0), (-1, 0), (1, 0), (2, 0), (-2, 1), (-1, 1), (0, 1), (1, 1), (2, 1),\n (-1, 2), (0, 2), (1, 2), (0, 0)]\n\n neighbours = []\n for dx, dy in dxdy:\n neighbour_coords = coords[0] + dx, coords[1] + dy\n if not (0 <= neighbour_coords[0] < nx and\n 0 <= neighbour_coords[1] < ny):\n # We're off the grid: no neighbours here.\n continue\n neighbour_cell = cells[neighbour_coords]\n if neighbour_cell is not None:\n # This cell is occupied: store this index of the contained point.\n neighbours.append(neighbour_cell)\n return neighbours","title":""},{"docid":"8e361cd5d0ef02f166bc75ee3e1d8650","score":"0.53555095","text":"def get_neighbours(self, src):\r\n directions = [(0, -1), (1, 0), (0, 1), (-1, 0)]\r\n neighbours = []\r\n for dx,dy in directions:\r\n x = src[0] + dx\r\n y = src[1] + dy\r\n if x in range(self.size) and y in range(self.size):\r\n neighbours.append((x, y))\r\n return sorted(neighbours)","title":""},{"docid":"c76b37f610a3509150e9518a964ef7fa","score":"0.5353335","text":"def create_vertical_roadmap(self, from_: Position, to: Position) -> list[Cell]:\n\n y_shift = to.y - from_.y\n assert (y_shift > 0 or y_shift < 0), \"unchecked path\"\n y_step = 1 if y_shift > 0 else -1\n x = from_.x\n roadmap = [self._board[y][x]\n for y in range(from_.y, to.y + y_step, y_step)]\n return roadmap[1:]","title":""},{"docid":"5d9a4eefee39433d9de8c4c66c649f52","score":"0.5353084","text":"def get_tile_neighbours(self, x, y):\n res = list()\n for key in cons.DIRECTIONS:\n tup = cons.DIRECTIONS.get(key)\n res.append(self.get_tile_neighbour(x, y, tup))\n return res","title":""},{"docid":"bd3ec523a398d964588e22580ac6bf84","score":"0.53426754","text":"def neighbours(self, currTile):\n X = currTile[0]\n Y = currTile[1]\n l = [(x,y) for x in range(X-1, X+2) for y in range(Y-1, Y+2) if 0 <= x < self.config.N if 0 <= y < self.config.N if (x != X or y != Y)]\n return l","title":""},{"docid":"9c1efdc4c72eb7fd2e76ca851d377d97","score":"0.5339586","text":"def get_neighbours(self, square: int) -> [int]:\n x, y = square % self.cols, square // self.rows\n neighbours = [(p[0] + x, p[1] + y) for p in [(0, -1), (-1, 0), (0, 1), (1, 0)]] \n return [n[0] + n[1] * self.cols for n in neighbours if 0 <= n[0] < self.cols and 0 <= n[1] < self.rows]","title":""},{"docid":"ad4d5a806800463852f6b8986ce47f30","score":"0.5322932","text":"def create_grid_2_5d(data, safe_distance):\n # minimum and maximum north coordinates\n north_min = np.floor(np.min(data[:, 0] - data[:, 3]))\n north_max = np.ceil(np.max(data[:, 0] + data[:, 3]))\n\n # minimum and maximum east coordinates\n east_min = np.floor(np.min(data[:, 1] - data[:, 4]))\n east_max = np.ceil(np.max(data[:, 1] + data[:, 4]))\n\n # given the minimum and maximum coordinates we can\n # calculate the size of the grid.\n north_size = int(np.ceil((north_max - north_min + 1)))\n east_size = int(np.ceil((east_max - east_min + 1)))\n\n # Initialize an empty grid\n grid = np.zeros((north_size, east_size))\n\n # Populate the grid with obstacles\n for i in range(data.shape[0]):\n north, east, alt, d_north, d_east, d_alt = data[i, :]\n obstacle = [\n int(np.clip(north - d_north - safe_distance - north_min, 0, north_size - 1)),\n int(np.clip(north + d_north + safe_distance - north_min, 0, north_size - 1)),\n int(np.clip(east - d_east - safe_distance - east_min, 0, east_size - 1)),\n int(np.clip(east + d_east + safe_distance - east_min, 0, east_size - 1)),\n ]\n obs = grid[obstacle[0]:obstacle[1] + 1, obstacle[2]:obstacle[3] + 1]\n np.maximum(obs, np.ceil(alt + d_alt + safe_distance), obs)\n\n return grid, int(north_min), int(east_min)","title":""},{"docid":"ad2632666a072c8d24eda89c5292e835","score":"0.5317036","text":"def create_knight_roadmap(self, from_: Position, to: Position) -> list[Cell]:\n\n return [self._board[to.y][to.x]]","title":""},{"docid":"daecb0b845e234930686b2e49d98639a","score":"0.5313709","text":"def __init__(self):\n\n ##2D array of Tile objects\n self.board = []","title":""},{"docid":"c935410154d1f2d0f466f0d6f730fcc9","score":"0.53093815","text":"def make_locs(n, m) -> NDArray:\n return np.array([[i, j] for i in range(n) for j in range(m)])","title":""},{"docid":"f84cecad7f66235e3f432dfc9567d760","score":"0.5304875","text":"def _emptyMaze(self, width: int, height: int) -> list:\n return [[Cell() for x in range(width)] for y in range(height)]","title":""},{"docid":"1c47c86de7666745948015c58bc5dc49","score":"0.5303785","text":"def getNeighbours(image,i,j):\n nbg = []\n for k in np.arange(i-1, i+2):\n for l in np.arange(j-1, j+2):\n try:\n nbg.append(image[k,l])\n except Exception as e:\n pass\n return np.array(nbg)","title":""},{"docid":"e33c6c29202fc171158fb68e028ea698","score":"0.5295464","text":"def extracted_array_2d_from(\r\n array_2d: np.ndarray, y0: int, y1: int, x0: int, x1: int\r\n) -> np.ndarray:\r\n\r\n new_shape = (y1 - y0, x1 - x0)\r\n\r\n resized_array = np.zeros(shape=new_shape)\r\n\r\n for y_resized, y in enumerate(range(y0, y1)):\r\n for x_resized, x in enumerate(range(x0, x1)):\r\n if (\r\n y >= 0\r\n and x >= 0\r\n and y <= array_2d.shape[0] - 1\r\n and x <= array_2d.shape[1] - 1\r\n ):\r\n resized_array[y_resized, x_resized] = array_2d[y, x]\r\n\r\n return resized_array","title":""},{"docid":"34e282ff6a2c1986891b60289effe7e1","score":"0.5289425","text":"def neighbors(self, cell):\n i, j = self._world_to_map(cell[0], cell[1])\n neigh = []\n if self._is_open(i-1,j):\n neigh.append((self._map_to_world(i-1,j)))\n if self._is_open(i+1,j):\n neigh.append((self._map_to_world(i+1,j)))\n if self._is_open(i,j-1):\n neigh.append((self._map_to_world(i,j-1)))\n if self._is_open(i,j+1):\n neigh.append((self._map_to_world(i,j+1)))\n # rounding done in map_to_world too but this seems to help\n neigh = [(round(x,2), round(y,2)) for x,y in neigh]\n return neigh","title":""},{"docid":"31772bf4307dd3eb29112032613d6497","score":"0.5288454","text":"def neighbours(self, board, pos):\n res = []\n x,y = pos[0], pos[1]\n I = x-1\n J = y-1\n\n for i in range(I, I+3):\n for j in range(J, J+3):\n if i < 0 or j < 0 or i > 4 or j > 4 or (i,j) == pos:\n continue\n else:\n if self.canCapture(board, (x, y), (i,j)) :\n res.append((i, j))\n return res","title":""},{"docid":"fa1d04456022e8275a042b12c1d5e236","score":"0.5269025","text":"def cell_list(self):\n final_lst = [] # this will be the returned list\n for row in range(0, len(self.board)):\n for col in range(0, len(self.board)):\n final_lst.append((row, col))\n final_lst.append(self.target_location()) # adds the target location\n # In this board, returns a list containing the cells in the square\n # from (0,0) to (6,6) and the target cell (3,7)\n return final_lst","title":""},{"docid":"41bf0badd86c90949f8db0909f893c21","score":"0.52671003","text":"def neighborhood(arr: np.ndarray, pos: tuple, n: int):\n sx, sy = max(0, pos[0] - n), max(0, pos[1] - n)\n ex, ey = min(pos[0] + n + 1, arr.shape[0]), min(pos[1] + n + 1, arr.shape[1])\n return arr[sx: ex, sy: ey]","title":""},{"docid":"5c86b099b34e3cb435e1a5ed81cdcfc3","score":"0.52669704","text":"def vector_2d():\n return [0.0, 1.0]","title":""},{"docid":"4f17838913ff5b81f4fad731e6248563","score":"0.5266566","text":"def get_neighbouring_coordinates(position):\n row = position[0]\n col = position[1]\n\n neighbours = [\n (row - 1, col),\n (row + 1, col),\n (row, col - 1),\n (row, col + 1)\n ]\n\n return [n for n in neighbours if 0 <= n[0] < len(current_image) and 0 <= n[1] < len(current_image[1])]","title":""},{"docid":"6fcb2315866d9203149f9f134993ed6e","score":"0.5264142","text":"def _get_obs(self) -> np.array:\n return self.board","title":""},{"docid":"1e798af90fde4507b5bb756d2d67a5f0","score":"0.5260177","text":"def getAvailableTiles(self):\n emptyPos = []\n for x in range(self.size):\n for y in range(self.size):\n if self.tile[x][y] == 0:\n emptyPos.append([x, y])\n return emptyPos","title":""},{"docid":"5b2122bd7efda1395a803bb6b9c9df07","score":"0.52600324","text":"def getNeighbors(self):\n return [self.north, self.south, self.east, self.west]","title":""},{"docid":"3a278765f36da44fe426d3790dc0f556","score":"0.52579004","text":"def cell_list(self):\n # In this __board, returns a list containing the cells in the square\n # from (0,0) to (6,6) and the __target cell (3,7)\n res = [(i, j) for i in range(len(self.__grid))\n for j in range(len(self.__grid))]\n res.append(self.target_location())\n return res","title":""},{"docid":"31d4cb2e911fd013c438d9d9106e8faf","score":"0.5257545","text":"def __init__(self, contamination):\n self.rows = len(contamination) + 2\n self.columns = len(contamination[0]) + 2\n self.robots = []\n for i in range(self.rows):\n temp = []\n for j in range(self.columns):\n temp.append(0)\n self.robots.append(temp)\n # everything below this line surrounds the 2-D array with a border of 0's for the bases\n tempList = contamination\n tempList.insert(0, [0] * (self.columns - 2))\n tempList.append([0] * (self.columns - 2))\n for i in range(len(tempList)):\n l = tempList[i]\n l.insert(0, 0)\n l.append(0)\n tempList[i] = l \n self.contamination = tempList","title":""},{"docid":"b2d2955b07ebd0434edc32b5e3d324cd","score":"0.5249533","text":"def get_neighbours(self, coordinate, nrows, ncols):\n row = coordinate[0]\n col = coordinate[1]\n\n neighbours = [\n (row - 1, col),\n (row + 1, col),\n (row, col - 1),\n (row, col + 1)\n ]\n\n return [n for n in neighbours if 0 <= n[0] < nrows and 0 <= n[1] < ncols]","title":""},{"docid":"f636ff6ad12395e5c66a551e71881178","score":"0.52467364","text":"def make_obstacles_scan(scan_list):\n\t#Convert the scan to a numoy arra of points\n\tpt_ang = np.arange(0,2*np.pi,np.pi/180)\n\tpt_scan = np.array(scan_list)\n\tpts = [] #To be returned cartesian form of scan\n\tpt_x = np.multiply(pt_scan,np.cos(pt_ang))\n\tpt_y = np.multiply(pt_scan,np.sin(pt_ang))\n\n\tfor a,b in zip(pt_x,pt_y):\n\t\tpts.append((a,b))\n\n\tpt_scan = np.array(scan_list)\n\t#Shifting the scan values\n\tpt_scan_prev = np.append(pt_scan[1:],pt_scan[0])\n\t# Taking the absolute difference and comparing with Threshold\n\tline_obst = abs(pt_scan_prev - pt_scan)>2*THRESHOLD\n\tind=np.argwhere(line_obst==True)\n\tind = np.append(0 , ind)\n\tind = np.append(ind, len(scan_list))\n\n\tline_obstacles = []\n\tpt_scan_enum = list(enumerate(scan_list))\n\tfor i in range(len(ind)-1):\n\t\tline = [(pt[0] , pt[1]) for pt in pts[ind[i]+1:ind[i+1]+1]]\n\t\tline_obstacles.append(line)\n\n\treturn (line_obstacles , pts)","title":""},{"docid":"948878e944fe674097ffbb433226a4a1","score":"0.5244176","text":"def find_neighbourhood(row, col, layers):\n neighbourhood = []\n for i in range(6):\n if check_boundary(row - 1, col, layers) and i == 0:\n neighbourhood.append((row - 1, col))\n elif check_boundary(row + 1, col, layers) and i == 1:\n neighbourhood.append((row + 1, col))\n elif check_boundary(row, col - 1, layers) and i == 2:\n neighbourhood.append((row, col - 1))\n elif check_boundary(row, col + 1, layers) and i == 3:\n neighbourhood.append((row, col + 1))\n elif check_boundary(row - 1, col + 1, layers) and i == 4:\n neighbourhood.append((row - 1, col + 1))\n elif check_boundary(row + 1, col - 1, layers) and i == 5:\n neighbourhood.append((row + 1, col - 1))\n\n return neighbourhood","title":""},{"docid":"5d448636e69d1bd5815974889382f7ae","score":"0.5243242","text":"def return_bounding_box_2d(x, y, xsize, ysize):\n if xsize <= 0 or ysize <= 0:\n print(\"ERROR: can't compute bounding box, xsize or height has no positive value\")\n return []\n return [x-xsize/2, y-ysize/2, x+xsize/2, y+ysize/2]","title":""},{"docid":"047c1262949f27f69e90db231cbfeb0f","score":"0.52294093","text":"def get_random_board(self):\n return [[random.randint(0,1) for x in range(self.width)]\n for x in range(self.height)]","title":""},{"docid":"6291f073381e88c37e33c35ead9aaa53","score":"0.5227485","text":"def get_grid_observation(self):\n cursor_bit = np.zeros(self.board.grid_size + (1,))\n cursor_bit[tuple(self.cursor)] = 1\n\n n_grid = np.prod(self.board.grid_size)\n population_normalized = np.full(cursor_bit.shape, self.population / n_grid)\n room_normalized = np.full(cursor_bit.shape, self.room / n_grid)\n\n obs = np.concatenate([\n self.board.to_one_hot(self.player_id),\n cursor_bit,\n population_normalized,\n room_normalized\n ], axis=-1)\n return obs","title":""},{"docid":"84302bb268aeb0b1fad6ee1a26958faa","score":"0.521875","text":"def detectorResponseMatrix():\n vec = []\n for i in range(GRID_RESOLUTION):\n vec2 = []\n for j in range(GRID_RESOLUTION):\n vec2.append(detectorResponseToCell(i, j))\n vec.append(vec2)\n return vec","title":""},{"docid":"71c8c609dc184d69ba3adf1adb6d50f9","score":"0.5208937","text":"def getNeighbors(row,col,i,j):\n neigb = []\n\n for m in [i-1,i,i+1]:\n for n in [j-1,j,j+1]:\n if (not (m == i and j == n)) and row > m >= 0 and col > n >= 0: #within bound\n neigb.append((m,n))\n\n return neigb","title":""},{"docid":"0df036c31880816a2463961d5fe62bf5","score":"0.51994836","text":"def createObstacles():\r\n # Select a random number, 0 - 4\r\n r = random.randrange(4)\r\n\r\n # If the number is 0, create a spike obstacle\r\n if r == 0:\r\n obstacles.append(Spike(1200, 415, .25, \"assets/images/obstacles/Spikes.png\", window))\r\n\r\n # If the number is 1, create a creepy crawly obstacle\r\n elif r == 1:\r\n obstacles.append(CreepyCrawly(1200, 415, .25,\"assets/images/obstacles/CreepyCrawly.png\", window))\r\n\r\n # If the number is 2, create a rocket obstacle\r\n elif r == 2:\r\n obstacles.append(Rocket(1200, 340, .25, \"assets/images/obstacles/Rocket.png\", window))\r\n\r\n # If the number is 3, create a space invader obstacle\r\n elif r == 3:\r\n obstacles.append(SpaceInvader(1200, 340, .3, \"assets/images/obstacles/SpaceInvader.png\", window))\r\n\r\n # If the number is, create a monkey obstacle\r\n else:\r\n obstacles.append(Monkey(1200, 310, .5, \"assets/images/obstacles/Monkey.png\", window))","title":""},{"docid":"f9b58c38ae81397e941384fc7abd8210","score":"0.5197234","text":"def get_boundary_coords():\n coords = []\n for x in range(NUM_PIX_X):\n for y in range(NUM_PIX_Y):\n if get_chip_coords(x,y)[0] == -1:\n coords.append((x,y))\n \n return coords","title":""},{"docid":"3299d834a1418a142ebdabb82650d850","score":"0.519159","text":"def findNeighbours(self, x, y, board=None):\n board, _ = self.setBoardAndPlayer(board)\n\n neighbours = []\n # min/max take care of the edge cases\n for i in range(max(0, x-1), min(x+2, self.spanX)):\n for j in range(max(0, y-1), min(y+2, self.spanY)):\n if board[i][j] != BLANK:\n neighbours.append((i, j))\n return neighbours","title":""},{"docid":"4e5a9d3eb5d66cef6ca767308b8b31d2","score":"0.5182894","text":"def getBoardArray(self):\r\n a = zeros(self.outdim)\r\n for i, p in enumerate(self._iterPos()):\r\n if self.b[p] == self.WHITE:\r\n a[2 * i] = 1\r\n elif self.b[p] == self.BLACK:\r\n a[2 * i + 1] = 1\r\n return a","title":""},{"docid":"4e5a9d3eb5d66cef6ca767308b8b31d2","score":"0.5182894","text":"def getBoardArray(self):\r\n a = zeros(self.outdim)\r\n for i, p in enumerate(self._iterPos()):\r\n if self.b[p] == self.WHITE:\r\n a[2 * i] = 1\r\n elif self.b[p] == self.BLACK:\r\n a[2 * i + 1] = 1\r\n return a","title":""},{"docid":"80e8c7eb525fadb65254ebc6c96c60c9","score":"0.5179019","text":"def to_arrays(self):\n players = range(self.num_players)\n maps = [self.halite_map]\n for player_id in players:\n ship_dict = self.ships[player_id]\n ship_indicators = np.zeros_like(self.halite_map)\n ship_energy = np.zeros_like(self.halite_map)\n for (x, y), energy in ship_dict.items():\n ship_energy[x, y] = energy\n ship_indicators[x, y] = 1\n maps.extend([ship_energy, ship_indicators])\n for player_id in players:\n factory_loc = self.factory_locs[player_id]\n factory_loc_map = np.zeros_like(self.halite_map)\n factory_loc_map[factory_loc[0], factory_loc[1]] = 1\n maps.append(factory_loc_map)\n for player_id in players:\n dropoff_locs = self.dropoff_locs[player_id]\n dropoff_loc_map = np.zeros_like(self.halite_map)\n for dropoff_loc in dropoff_locs:\n dropoff_loc_map[dropoff_loc[0], dropoff_loc[1]] = 1\n maps.append(dropoff_loc_map)\n map_arr = np.array(maps)\n\n other_state = [self.turns_remaining]\n for player_id in players:\n other_state.append(self.scores[player_id])\n other_arr = np.array(other_state, dtype=np.float64)\n map_arr = np.moveaxis(map_arr, 0, -1)\n assert map_arr.shape == (\n self.map_width,\n self.map_width,\n 9 if self.num_players == 2 else 17,\n )\n return map_arr, other_arr","title":""},{"docid":"d9ccab57a18b890f6947ed0794694f93","score":"0.517024","text":"def neigh(Node, step):\n\tx, y = Node[0], Node[1]\n\treturn [[x, y+step], [x, y-step], [x+step, y], [x-step, y]]","title":""},{"docid":"67c0d9a0c0ae6642e6f982423d2b8518","score":"0.5164656","text":"def as_list(self, key=True):\n grid_list = []\n\n for x in range(self.width):\n for y in range(self.height):\n if self[x][y] == key:\n grid_list.append((x, y))\n\n return grid_list","title":""},{"docid":"f4b993679c5f5fa463f39a6cea142bd8","score":"0.51613635","text":"def _grid(self, coords):\n rows = max(r for (r, _, _) in coords) + 1 if coords != [] else 0\n unpadded_grid = [[p for (r, _, p) in coords if r == row] for row in\n range(rows)]\n return unpadded_grid","title":""},{"docid":"92f43c3d510b9cb2ee21c92cddc1550e","score":"0.5159394","text":"def loadObstacles(self,obstaclefile):\n\n # Initiate data structures.\n data = open(obstaclefile,\"r\")\n obs_sizes = [];\n obs_positions = [];\n obs_masses = [];\n reading = \"None\"\n\n # Parse the obstacle text file.\n for line in data:\n linesplit = line.split()\n if linesplit != []:\n if linesplit[0] != \"#\":\n obs_sizes.append([float(linesplit[0]),float(linesplit[1]),float(linesplit[2])])\n obs_positions.append([float(linesplit[3]),float(linesplit[4]),float(linesplit[5])])\n obs_masses.append(float(linesplit[6])) \n\n # Go through all the obstacles in the list and spawn them.\n for i in range(len(obs_sizes)):\n\n obs_size = obs_sizes[i]\n obs_pos = obs_positions[i]\n obs_mass = obs_masses[i]\n \n # Create the obstacle.\n body = ode.Body(self.world)\n geom = ode.GeomBox(space=self.space, lengths=obs_size )\n geom.setBody(body)\n geom.setPosition(obs_pos)\n M = ode.Mass()\n M.setBox(obs_mass,obs_size[0],obs_size[1],obs_size[2])\n body.setMass(M)\n\n # Append all these new pointers to the simulator class.\n self._geoms.append(geom)","title":""},{"docid":"63d42b555366d584f5d111f988865943","score":"0.5158857","text":"def get_neighbors(self, x, y):\n neighbors = []\n for y_ in [y - 1, y, y + 1]:\n if y_ < 0 or y_ > self.height - 1: # If Y coordinate is invalid\n continue\n for x_ in [x - 1, x, x + 1]:\n if x_ == x and y_ == y: # If center\n continue\n if x_ < 0 or x_ > self.width - 1: # If X coordinate is invalid\n continue\n neighbors.append((x_, y_))\n return neighbors","title":""},{"docid":"1af892c93d788ccbb26b8892dcf935ae","score":"0.5157673","text":"def _generate_grid(self):\n return [[self.make_square(row, col) for col in range(self.dim_col)]\n for row in range(self.dim_row)]","title":""},{"docid":"bb6468015a52974d7a263795bb81f899","score":"0.5153086","text":"def cell_list(self):\n lst = [(i, j) for i in range(self.BOARD_LENGTH) for j in\n range(self.BOARD_LENGTH)]\n lst.append(self.GOAL_LOCATION)\n return lst","title":""},{"docid":"593493a9e5c93e5ebd28b476e91ad340","score":"0.51493853","text":"def neighbors(self, pos, diagonals=False):\r\n x, y = pos\r\n neighbors = [(x + 1, y), (x - 1, y), (x, y - 1), (x, y + 1)]\r\n if diagonals:\r\n neighbors += [(x + 1, y + 1), (x - 1, y + 1), (x + 1, y - 1), (x - 1, y - 1)]\r\n if (x + y) % 2 == 0: neighbors.reverse()\r\n results = filter(self.in_bounds, neighbors)\r\n results = filter(self.no_obstacle, results)\r\n return results","title":""},{"docid":"926358c52e9b65966852b514fcceb712","score":"0.5146556","text":"def neighbors8(self, coord):\n (x,y) = coord\n results = [(x+1, y+1), (x+1, y), (x+1, y-1),\n (x, y+1), (x, y-1),\n (x-1, y+1), (x-1, y), (x-1, y-1)]\n results = list(filter(self.in_bounds, results))\n results = list(filter(self.passable, results))\n return results","title":""},{"docid":"bb38c47eec0f3ca2ad2715da8c36114c","score":"0.51445603","text":"def generate(self):\n newBoards = []\n\n # For each point\n for p in self.board:\n # Generate all neighboring points\n for newy in range(self.N):\n if newy == p[1]:\n continue\n newp = (p[0], newy)\n if newp not in self.board:\n newboard = self.board[:]\n newboard[newboard.index(p)] = newp\n newBoards.append(newboard)\n\n return newBoards","title":""},{"docid":"e68169fb1fe6eedc1ca858b065a8d956","score":"0.51392007","text":"def get_nozzle_positions():\n nozzle_positions = [(0.0)] * n_nozzles\n d_between = boom_length / (n_nozzles - 1)\n for i in range(n_nozzles):\n nozzle_positions[i] = (boom_offset, i * d_between - boom_length / 2, inp['H'] - boom_height)\n return nozzle_positions","title":""},{"docid":"969fa007597b157725a2a56afbb51451","score":"0.51356924","text":"def get_movables_tiles(board, player_value=0):\n movable = []\n for x in range(len(board)):\n for y in range(len(board[x])):\n value = board[x][y]\n if is_movable_tile(x, y) and (value == 0 or value == player_value):\n movable.append((x, y))\n\n return movable","title":""},{"docid":"3268ff3c8861c2fa7c275a12b6c862db","score":"0.5132038","text":"def hit_box(self) -> list:\n hit_box = []\n\n x_max = self.largeur_screen // LARGEUR_TUILE\n y_max = self.hauteur_screen // HAUTEUR_TUILE\n\n for i in range(0, y_max):\n for j in range(0, x_max):\n x = j * LARGEUR_TUILE\n y = i * HAUTEUR_TUILE\n item = self.niveau[i][j]\n\n if item != \"V\":\n hit_box.append((x, y))\n\n return hit_box","title":""}],"string":"[\n {\n \"docid\": \"3e0ccacd4db9e4bc1fcb1726c1a0fa96\",\n \"score\": \"0.7382825\",\n \"text\": \"def obstacles(self):\\n return list(self._obstacles)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6586c95dc5ce60c31e82d33802373a2e\",\n \"score\": \"0.7301217\",\n \"text\": \"def get_obstacles_positions(obstacles: []) -> List[Position]:\\n obstacles_positions: List[Position] = []\\n # Iterate over two-dimensional array\\n for obstacle in obstacles:\\n # Create a position object to append to a list\\n position = Position(obstacle[0], obstacle[1])\\n obstacles_positions.append(position)\\n \\n return obstacles_positions\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9cfec27324a94fe3b91b1970dca4f753\",\n \"score\": \"0.66640806\",\n \"text\": \"def get_static_obstacles(self):\\n # gap = 0.20/self.difficulty\\n #\\n # # Vertical bars\\n # self.O1 = (0.47, 0, 0.47 + self.wall_width, 0.17 - gap)\\n # self.O2 = (0.47, 0.15 + gap, 0.47 + self.wall_width, 0.85 - gap)\\n # self.O3 = (0.47, 0.85 + gap, 0.47 + self.wall_width, 1)\\n #\\n # # Top horizontal bars\\n # self.O4 = (0, 0.65, 0.25 - gap, 0.65 + self.wall_width)\\n # self.O5 = (0.25 + gap, 0.65, 0.75 - gap, 0.65 + self.wall_width)\\n # self.O6 = (0.75 + gap, 0.65, 1, 0.65 + self.wall_width)\\n #\\n # # Bottom Horizontal bars\\n # self.O7 = (0, 0.3, 0.75 - gap, 0.3 + self.wall_width)\\n # self.O8 = (0.75 + gap, 0.3, 1, 0.3 + self.wall_width)\\n #\\n # obstacles = [self.O1, self.O2, self.O3, self.O4, self.O5, self.O6, self.O7, self.O8]\\n #\\n\\n self.O1 = (0, 0.25, 0 + self.wall_width + 0.45, 0.25 + self.wall_width) # (0, 0.25, 0.5, 0.3)\\n self.O2 = (0.5, 0.25, 0.5 + self.wall_width, 0.25 + self.wall_width + 0.5) # (0.5, 0.25, 0.55, 0.8)\\n obstacles = [self.O1, self.O2]\\n\\n # obstacles = []\\n return obstacles\",\n \"title\": \"\"\n },\n {\n \"docid\": \"02b235591e00832cd6400ac079a719e0\",\n \"score\": \"0.64403796\",\n \"text\": \"def generate_obstacles(self, num_obs):\\n obs_list = []\\n while len(obs_list) < num_obs:\\n obs = [random.randint(1, self.x_axis_max - 1), random.randint(1, self.y_axis_max - 1)]\\n if obs in obs_list:\\n continue\\n elif obs[0] == self.goal[0] and obs[1] == self.goal[1]:\\n continue\\n elif obs[0] == self.start[0] and obs[1] == self.start[1]:\\n continue\\n else:\\n obs_list.append(obs)\\n\\n # set grid map boundary as obstacles as well\\n for x in range(1, self.x_axis_max):\\n obs_list.append([x, 0])\\n obs_list.append([x, self.y_axis_max])\\n for y in range(1, self.y_axis_max):\\n obs_list.append([0, y])\\n obs_list.append([self.x_axis_max, y])\\n obs_list.append([0, 0])\\n obs_list.append([0, self.y_axis_max])\\n obs_list.append([self.x_axis_max, 0])\\n obs_list.append([self.x_axis_max, self.y_axis_max])\\n\\n # print(obs_list)\\n # print(len(obs_list))\\n return obs_list\",\n \"title\": \"\"\n },\n {\n \"docid\": \"efdc794cce2a38b3c931f0fe59dd7a6e\",\n \"score\": \"0.618513\",\n \"text\": \"def get_1D_neighbors(self):\\n adjacents = [(-1,-1), (-1,0), (-1,1), (0,1), (1,1), (1,0), (1,-1), (0,-1)]\\n \\n nb = np.full((self.obstacle_map.size,8), -1, dtype=np.int)\\n \\n for [x,y] in self.visible_cells:\\n index_1D = self.indexFromXY(x,y,self.obstacle_map.shape[1])\\n for i, (xpos,ypos) in enumerate(adjacents):\\n if 0 <= x+xpos < self.obstacle_map.shape[0] and 0 <= y+ypos < self.obstacle_map.shape[1]:\\n if not self.obstacle_map[x+xpos, y+ypos] < 0:\\n nb[index_1D, i] = self.indexFromXY(xpos+x, ypos+y, self.obstacle_map.shape[1])\\n return nb\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b338602d20022ae37fde0d07b8fba14c\",\n \"score\": \"0.61557966\",\n \"text\": \"def get_neighbors(x, y):\\n return[\\n (x, y - 1), (x + 1, y), (x - 1, y), (x - 1, y - 1),\\n (x, y + 1), (x + 1, y + 1), (x - 1, y + 1), (x + 1, y - 1)\\n ]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a48168b025bfb05d13efde67a68fabbb\",\n \"score\": \"0.61122984\",\n \"text\": \"def createObstacles():\\n for ob in obs_list:\\n pygame.draw.rect(screen, red, pygame.Rect(ob))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"665be9bda3cf36bfb24363aec0b888fd\",\n \"score\": \"0.59382457\",\n \"text\": \"def GetPositions2D(self):\\r\\n return np.resize(self.positions,(4,2))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08860687d915a45eacd0be063a273d76\",\n \"score\": \"0.5890589\",\n \"text\": \"def add_obstacles(self, obstacles):\\n for obstacle in obstacles:\\n x1, y1, x2, y2 = (np.array(obstacle) / self.grid_res).astype(int)\\n self.grid_data[x1:x2, y1:y2] = 1.0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a8b2155e725bf652598d49cae4c975f8\",\n \"score\": \"0.58401555\",\n \"text\": \"def draw_obstacles(self, obstacles, robot_state):\\n # type: (list, RobotState) -> None\\n points = []\\n for position in obstacles:\\n point = _global2local_point(position, robot_state.exact_position, robot_state.exact_rotation)\\n points.append(point)\\n\\n self._draw_sphere_list(0, OBSTACLE_NAMESPACE, OBSTACLE_SCALE, points, color=OBSTACLE_COLOR)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"28be91ac12ce86ef03461bb658876b7f\",\n \"score\": \"0.581147\",\n \"text\": \"def neighbor_coords(self,x,y):\\n neighbors = []\\n if self.in_bounds(x+1, y+1): neighbors.append([x+1,y+1])\\n if self.in_bounds(x+1, y): neighbors.append([x+1,y])\\n if self.in_bounds(x-1, y-1): neighbors.append([x-1,y-1])\\n if self.in_bounds(x-1, y): neighbors.append([x-1,y])\\n if self.in_bounds(x-1, y+1): neighbors.append([x-1,y+1])\\n if self.in_bounds(x, y+1): neighbors.append([x,y+1])\\n if self.in_bounds(x+1, y-1): neighbors.append([x+1,y-1])\\n if self.in_bounds(x, y-1): neighbors.append([x,y-1])\\n return neighbors\",\n \"title\": \"\"\n },\n {\n \"docid\": \"36f12c6bae039b83fd995eb5b47e89ff\",\n \"score\": \"0.58062243\",\n \"text\": \"def findNeighbours(x,y,img):\\n n_img = img\\n x_1, y_1, x1, y1 = x-1, y-1, x+1, y+1;\\n return [ n_img[x_1][y], n_img[x_1][y1], n_img[x][y1], n_img[x1][y1], n_img[x1][y], n_img[x1][y_1], n_img[x][y_1], img[x_1][y_1] ]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8d7b14dedce791e218b0a273888c34c2\",\n \"score\": \"0.5802935\",\n \"text\": \"def _neighbours(self, y, x):\\r\\n neighbours = []\\r\\n for dy in range(-1, 2):\\r\\n for dx in range(-1, 2):\\r\\n if dy == 0 and dx == 0:\\r\\n continue\\r\\n else:\\r\\n if self._valid_position(y+dy, x+dx):\\r\\n neighbours.append((y+dy, x+dx))\\r\\n return neighbours\",\n \"title\": \"\"\n },\n {\n \"docid\": \"722c12cb2d88e712f700a6b9785402c6\",\n \"score\": \"0.579285\",\n \"text\": \"def getNeighborhood(self):\\n neighborhood = \\\"[\\\"\\n for ry in xrange(-self.radius,self.radius+1,1):\\n for rx in xrange(-self.radius,self.radius+1,1):\\n if ((ry != 0) or (rx != 0)):\\n if (self.neighborhood_select):\\n if ((abs(rx) + abs(ry)) <= self.radius):\\n arg = \\\"\\\".join((\\\"scratchgrid[rr+\\\",str(ry),\\\",cc+\\\",str(rx),\\\"],\\\"))\\n neighborhood += \\\"\\\".join(arg)\\n else:\\n pass\\n elif (not self.neighborhood_select):\\n arg = \\\"\\\".join((\\\"scratchgrid[rr+\\\",str(ry),\\\",cc+\\\",str(rx),\\\"],\\\"))\\n neighborhood += \\\"\\\".join(arg) \\n neighborhood = neighborhood[:-1]\\n neighborhood += \\\"\\\".join(\\\"]\\\")\\n return neighborhood\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6ce0f2960ed091d59184bd0553c62d73\",\n \"score\": \"0.5735862\",\n \"text\": \"def find_obstacles(puzzle) -> List[List[int]]:\\n for subset in puzzle:\\n global side1, side2, side3\\n side1 = []\\n side2 = []\\n side3 = []\\n solution = solve(0, subset)\\n if not solution:\\n return subset\\n return []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3a5855ca4bde28425315368df460d98d\",\n \"score\": \"0.57353014\",\n \"text\": \"def voisins(pos, obstacles, taille):\\r\\n res = []\\r\\n x, y = pos\\r\\n for i, j in [(0,1),(0,-1),(1,0),(-1,0)]:\\r\\n if ((x + i,y + j) not in obstacles) and (x + i) >= 0 and (x + i) < taille[0] and (y + j) >= 0 and (y + j) < taille[1]:\\r\\n res.append((x+i, y + j))\\r\\n return res\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8acd5edd26f033a0f8bbfcc6513de961\",\n \"score\": \"0.57002795\",\n \"text\": \"def coord2d(x,y):\\n return np.array([x,y])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7e6a568b8e5248964709a075088d1786\",\n \"score\": \"0.5696858\",\n \"text\": \"def obstacles_between(self, ship, target, ignore=()):\\n obstacles = []\\n excl = [ship, target]\\n entities = ([] if issubclass(Planet, ignore) else self.all_planets(exclude=excl)) \\\\\\n + ([] if issubclass(Ship, ignore) else self.all_ships(exclude=excl))\\n for foreign_entity in entities:\\n if collision.intersect_segment_circle(ship, target, foreign_entity, fudge=ship.radius + 0.1):\\n obstacles.append(foreign_entity)\\n return obstacles\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1bbbe8597e7f7a2affd14d80f986ec10\",\n \"score\": \"0.56554735\",\n \"text\": \"def return_neighborhoods_coordinates():\\r\\n return neighborhoods_coordinates\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3a98c3a6c5a23dc3583693ae58219517\",\n \"score\": \"0.56311774\",\n \"text\": \"def create_grid(width, height):\\n return [[0 for _x in range(width)] for _y in range(height)]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9eb3e2e6703bb0657c870969a6124a53\",\n \"score\": \"0.5616334\",\n \"text\": \"def get_neighbours(self, coordinates, img):\\n nrows = len(img)\\n ncols = len(img[0])\\n r = coordinates[0]\\n c = coordinates[1]\\n to_return = [\\n [r - 1, c],\\n [r + 1, c],\\n [r, c - 1],\\n [r, c + 1]\\n ]\\n return [t for t in to_return if 0 <= t[0] < nrows and 0 <= t[1] < ncols]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"96ff6d6f33926296012fa87e1f8870f4\",\n \"score\": \"0.56038684\",\n \"text\": \"def add_obstacles(self, obs) -> None:\\n for o in obs:\\n # Convert each bound to xy coordinate\\n # Forward converts from latlon to cartesian\\n x, y, *_ = self.cartesian.forward(o[\\\"latitude\\\"], o[\\\"longitude\\\"])\\n\\n # Add each point to the list and the graph\\n obi = Obstacle(Point(x, y, self.alt_bounds[0]), o[\\\"radius\\\"], o[\\\"height\\\"])\\n self.obstacles.append(obi)\\n for n in obi.points():\\n p = Point(*n)\\n if self.boundary_poly.contains(p):\\n self.graph.add_node(n)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7fcf712b9bbeef93e45556a43338e66f\",\n \"score\": \"0.5597686\",\n \"text\": \"def visible_vertices(p, visible_obstacles):\\n V = []\\n\\n for obstacle in visible_obstacles:\\n for vertex in [v[0] for v in obstacle.lines]:\\n if line_is_unblocked(p, vertex, visible_obstacles):\\n V.append(vertex)\\n\\n return V\",\n \"title\": \"\"\n },\n {\n \"docid\": \"950907efec3f54bb248e0cd42ad73f30\",\n \"score\": \"0.55852616\",\n \"text\": \"def array_coords(shape):\\n\\ty = shape[0]\\n\\tx = shape[1]\\n\\tout = scipy.empty((2,y,x))\\n\\tt = scipy.arange(y,dtype='f8')\\n\\tout[0] = scipy.tile(t,(x,1)).T\\n\\tt = scipy.arange(x,dtype='f8')\\n\\tout[1] = scipy.tile(t,(y,1))\\n\\treturn out\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc6a82d54045e6261a88309960cef190\",\n \"score\": \"0.5583301\",\n \"text\": \"def living_cells(self):\\n cells = [(i,j,self.grid[i][j]) for i in range(self.size) for j in range(self.size) if self.grid[i][j] != 0]\\n return zip(*cells)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"eebb92d0e81d3bd242ae8a0fa66cb64d\",\n \"score\": \"0.55758065\",\n \"text\": \"def get_neighbours(self,x_coord, y_coord):\\n\\t\\treturn [(x_coord - 1, y_coord - 1), (x_coord, y_coord - 1), (x_coord + 1, y_coord - 1), \\\\\\n\\t\\t\\t(x_coord - 1, y_coord), (x_coord + 1, y_coord), \\\\\\n\\t\\t\\t(x_coord - 1, y_coord + 1), (x_coord, y_coord + 1), (x_coord + 1, y_coord + 1)]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7b1fb962f32356f524ad2d0879e3619b\",\n \"score\": \"0.5570699\",\n \"text\": \"def get_new_position(obstacles, x_bounds, y_bounds):\\n while True:\\n x = randint(0, x_bounds)\\n y = randint(0, y_bounds)\\n\\n if not geom.point_in_any_obstacle(geom.Point(x, y), obstacles):\\n return geom.Point(x, y)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"21e6a90c346db6d339f62ea5fb6f6838\",\n \"score\": \"0.55528706\",\n \"text\": \"def _determine_cell_neighbours(self, pos):\\n x = pos[0]\\n y = pos[1]\\n\\n return [\\n (x + 1, y), (x + 1, y + 1), (x, y + 1), (x - 1, y + 1), (x - 1, y),\\n (x - 1, y - 1), (x, y - 1), (x + 1, y - 1)\\n ]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a966d58caeb8a7aaeac8f264ce79f89b\",\n \"score\": \"0.55523187\",\n \"text\": \"def get_available_tiles(self):\\r\\n self._coordinates = []\\r\\n available_tiles = []\\r\\n row = -1\\r\\n \\r\\n for segment in self._grid:\\r\\n temp_coordinates = []\\r\\n col = -1\\r\\n row += 1\\r\\n \\r\\n for tile in segment:\\r\\n col += 1\\r\\n temp_coordinates.append([row,col])\\r\\n \\r\\n if tile == 0:\\r\\n available_tiles.append([row,col])\\r\\n self._coordinates.append(temp_coordinates)\\r\\n \\r\\n return available_tiles\",\n \"title\": \"\"\n },\n {\n \"docid\": \"39d473ea60e1e7374f6108e1507f799c\",\n \"score\": \"0.55498344\",\n \"text\": \"def neighbors(board, i, j):\\n return [board[j - 1][i], board[j + 1][i], board[j][i + 1], board[j][i - 1]]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"99391287badbe6eea36e36d0fa8724c3\",\n \"score\": \"0.5535299\",\n \"text\": \"def get_dead_board(self):\\n return [[0 for x in range(self.width)]\\n for x in range(self.height)]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b3c2ddf5f7225ebfe07107ac53f9dd7b\",\n \"score\": \"0.5525028\",\n \"text\": \"def find_path(self, obstacles, start, end):\\n # type: (list, (float, float), (float, float)) -> list\\n return self._a_star(obstacles, position2grid(start), position2grid(end))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9be7b4b935e618b98c64dd49dc065a68\",\n \"score\": \"0.5506782\",\n \"text\": \"def draw_map(self):\\n for i in range(self.N + 1):\\n self.cells.append([])\\n for j in range(1, self.N):\\n rect(self.screen, (0, 0, 0), (i * self.cell_size, j * self.cell_size, self.cell_size, self.cell_size),\\n 2)\\n self.cells[i].append([i * self.cell_size, j * self.cell_size, 0])\\n self.draw_walls()\\n return self.cells\",\n \"title\": \"\"\n },\n {\n \"docid\": \"176ef192ec4ebd700a29c8026d7d83b6\",\n \"score\": \"0.54961437\",\n \"text\": \"def new_game():\\n return np.array([[None] * 3] * 3)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"de42eaec6c23445a3c1603bfe3b63ed5\",\n \"score\": \"0.54925996\",\n \"text\": \"def detect_obstacles_while_moving(self):\\n if self.state == self.STATE_EXPLORATION_RIGHT:\\n if any(np.array(self.front_list < self.SCANNER)):\\n\\n # Get ids in list where obstacle near\\n idx_list = np.where(np.array(self.front_list) < self.SCANNER)\\n # convert ids into y coordinate\\n y_obstacles = self.y_before_step - idx_list[0]*9/100*self.STEP\\n scan = np.array(self.front_list)\\n # calculate x coordinate of obstacles basted on sensor value\\n x_obstacles = self.x + scan[idx_list[0]]\\n\\n return y_obstacles, x_obstacles\\n\\n elif self.state == self.STATE_EXPLORATION_LEFT:\\n if any(np.array(self.front_list < self.SCANNER)):\\n\\n idx_list = np.where(np.array(self.front_list) < self.SCANNER)\\n y_obstacles = self.y_before_step + idx_list[0]*9/100*self.STEP\\n scan = np.array(self.front_list)\\n x_obstacles = self.x + scan[idx_list[0]]\\n\\n return y_obstacles, x_obstacles\\n\\n elif self.state == self.STATE_FORWARD:\\n if any(np.array(self.left_list < self.SCANNER)):\\n\\n idx_list = np.where(np.array(self.front_list) < self.SCANNER)\\n x_obstacles = self.x_before_step + idx_list[0] * 9 / 100 * self.STEP # step when going forward\\n scan = np.array(self.front_list)\\n y_obstacles = self.x + scan[idx_list[0]]\\n\\n return y_obstacles, x_obstacles\\n\\n if any(np.array(self.right_list < self.SCANNER)):\\n\\n idx_list = np.where(np.array(self.front_list) < self.SCANNER)\\n x_obstacles = self.x_before_step + idx_list[0] * 9 / 100 * self.STEP # step when going forward\\n scan = np.array(self.front_list)\\n y_obstacles = self.x - scan[idx_list[0]]\\n\\n return y_obstacles, x_obstacles\\n else:\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"89848869c8b927f7d71b7b67f98859c1\",\n \"score\": \"0.548818\",\n \"text\": \"def obstacles_between(ship, target,game_map, ignore_ships = False, ignore_planets= False):\\n obstacles = []\\n entities = []\\n if not ignore_planets :\\n entities.extend(game_map.all_planets())\\n if not ignore_ships :\\n entities.extend(game_map.all_ships())\\n for foreign_entity in entities:\\n if foreign_entity == ship or foreign_entity == target:\\n continue\\n if intersect_segment_circle(ship, target, foreign_entity, fudge=ship.radius + 0.1):\\n return True\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"715d765c4754e1b6264f6f829777e1e0\",\n \"score\": \"0.5478086\",\n \"text\": \"def uniquePathsWithObstacles(self, obstacleGrid):\\n m = len(obstacleGrid)\\n n = len(obstacleGrid[0])\\n for i in range(n):\\n if obstacleGrid[0][i] == 1:\\n for j in range(i, n):\\n obstacleGrid[0][j] = 0\\n break\\n else:\\n obstacleGrid[0][i] = 1\\n\\n for i in range(1, m):\\n for j in range(n):\\n if obstacleGrid[i][j] == 1:\\n obstacleGrid[i][j] = 0\\n else:\\n if j == 0:\\n obstacleGrid[i][j] = obstacleGrid[i-1][j]\\n else:\\n obstacleGrid[i][j] = obstacleGrid[i-1][j] + obstacleGrid[i][j-1]\\n return obstacleGrid[m-1][n-1]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2b216f471f2998ae4ec097e921ba15be\",\n \"score\": \"0.5475305\",\n \"text\": \"def matrix_neighbors(row, col, width, height):\\n return [(row + i, col + j) for i in (-1, 0, 1) for j in (-1, 0, 1) if 0 <= row + i < width and 0 <= col + j < height]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"00e590855875db5cb6f9c291004724d1\",\n \"score\": \"0.54677457\",\n \"text\": \"def is_hit_obstacle(self, x, y):\\n x = (x / self.config.grid_reso).astype(int)\\n y = (y / self.config.grid_reso).astype(int)\\n # assuming [0, 0] is always an obstacle because of the boundary\\n return self.obstacles[x * ~self.is_out_of_boundary(x, y), y * ~self.is_out_of_boundary(x, y)]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"df392214fec4134c6fe7720b4fff92e4\",\n \"score\": \"0.545878\",\n \"text\": \"def get_locations(percepts, obstacles):\\n possible_locations = []\\n possible_starting_points = []\\n unique_points = []\\n\\n # TODO We should add a check to make sure we don't consider\\n # any points inside an obstacle\\n for obstacle in obstacles:\\n for line in obstacle.lines:\\n possible_starting_points.append(geom.Point((line[0].x - percepts[0].x),\\n (line[0].y - percepts[0].y)))\\n unique_points.append(line[0])\\n\\n for v in possible_starting_points:\\n # Create a new point from v (possible agent start position) and percepts.\\n # If all new points are actual vertice in on obstacle, v is valid\\n valid_point = True\\n\\n for percept in percepts:\\n vertex = geom.Point((v.x + percept.x), (v.y + percept.y))\\n\\n if not any([vertex == p for p in unique_points]):\\n valid_point = False\\n break\\n\\n if valid_point:\\n possible_locations.append(v)\\n\\n return possible_locations\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6796c680ff8ce7cb0ec393e40c6b9f02\",\n \"score\": \"0.5443998\",\n \"text\": \"def game_board():\\r\\n board = np.zeros((rows, columns))\\r\\n return board\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c6bd69a1de3d69b37e1914b0fa0b070f\",\n \"score\": \"0.5442009\",\n \"text\": \"def nested_coordinates_list(self):\\n self._nested_list = []\\n map_size = self.rossumoya.map_size\\n x, y = map_size\\n for x_index in range(x):\\n self._nested_list.append([])\\n for _ in range(y):\\n self._nested_list[x_index].append(None)\\n return self._nested_list\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d23198ec76574ba6bee9d5055f462599\",\n \"score\": \"0.5438812\",\n \"text\": \"def new_board():\\n return [[EMPTY for _ in range(NROWS)] for _ in range(NCOLS)]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e36f51ee15182f0618f30d545e4dada7\",\n \"score\": \"0.54108936\",\n \"text\": \"def neighbor_cells(arr, coords):\\n ndim = arr.ndim\\n shape = arr.shape\\n return [arr[coords[:d] + (coords[d] + 1,) + coords[d + 1:]]\\n for d in range(ndim) if coords[d] + 1 < shape[d]] + \\\\\\n [arr[coords[:d] + (coords[d] - 1,) + coords[d + 1:]]\\n for d in range(ndim) if coords[d] > 0]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f9b9846c09ba117cab379e74958eb571\",\n \"score\": \"0.54068756\",\n \"text\": \"def get_2D_grid(start_point, end_point, spacing):\\n \\n x, y = numpy.mgrid[start_point.x:end_point.x:spacing,\\n start_point.y:end_point.y:spacing]\\n\\n x = x.ravel(); y = y.ravel()\\n\\n return x, y\",\n \"title\": \"\"\n },\n {\n \"docid\": \"818d68e149ce40fccc04bebc7596afc1\",\n \"score\": \"0.54047805\",\n \"text\": \"def visited_board_16x16() -> List[List[int]]:\\r\\n return [\\r\\n [-1, -1, -1, -1],\\r\\n [-1, -1, -1, -1],\\r\\n [-1, -1, -1, -1],\\r\\n [-1, -1, -1, -1]\\r\\n ]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2a36047ab1aa9e6215234dd8ba20f20e\",\n \"score\": \"0.5374832\",\n \"text\": \"def actions(state):\\n return visible_vertices(state, env.visible_obstacles)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9322f5312cc3ec3fedbc43255e6234fa\",\n \"score\": \"0.537227\",\n \"text\": \"def coords():\\n return np.array(\\n [[39, 6, -32], [29, 40, 1], [-20, -74, 35], [-29, -59, -37]]\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"38a994bc7e87de1533f5ae67549f7432\",\n \"score\": \"0.5362488\",\n \"text\": \"def get_traffic(self, format=0):\\n \\n trafficMap = np.zeros(self.obstacle_map.size,dtype=np.int)\\n\\n # Ground cells\\n vCells = np.argwhere(self.obstacle_map.flatten()==0).flatten()\\n \\n # Update traffic map\\n for k in vCells:\\n self.get_cell_traffic(k, trafficMap)\\n \\n if format == 0:\\n return trafficMap\\n elif format == 1:\\n return np.reshape(trafficMap, self.obstacle_map.shape)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2d9c61b5f44275466c9ad168f53d417f\",\n \"score\": \"0.5361387\",\n \"text\": \"def get_neighbours(coords):\\n\\n dxdy = [(-1, -2), (0, -2), (1, -2), (-2, -1), (-1, -1), (0, -1), (1, -1), (2, -1),\\n (-2, 0), (-1, 0), (1, 0), (2, 0), (-2, 1), (-1, 1), (0, 1), (1, 1), (2, 1),\\n (-1, 2), (0, 2), (1, 2), (0, 0)]\\n\\n neighbours = []\\n for dx, dy in dxdy:\\n neighbour_coords = coords[0] + dx, coords[1] + dy\\n if not (0 <= neighbour_coords[0] < nx and\\n 0 <= neighbour_coords[1] < ny):\\n # We're off the grid: no neighbours here.\\n continue\\n neighbour_cell = cells[neighbour_coords]\\n if neighbour_cell is not None:\\n # This cell is occupied: store this index of the contained point.\\n neighbours.append(neighbour_cell)\\n return neighbours\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8e361cd5d0ef02f166bc75ee3e1d8650\",\n \"score\": \"0.53555095\",\n \"text\": \"def get_neighbours(self, src):\\r\\n directions = [(0, -1), (1, 0), (0, 1), (-1, 0)]\\r\\n neighbours = []\\r\\n for dx,dy in directions:\\r\\n x = src[0] + dx\\r\\n y = src[1] + dy\\r\\n if x in range(self.size) and y in range(self.size):\\r\\n neighbours.append((x, y))\\r\\n return sorted(neighbours)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c76b37f610a3509150e9518a964ef7fa\",\n \"score\": \"0.5353335\",\n \"text\": \"def create_vertical_roadmap(self, from_: Position, to: Position) -> list[Cell]:\\n\\n y_shift = to.y - from_.y\\n assert (y_shift > 0 or y_shift < 0), \\\"unchecked path\\\"\\n y_step = 1 if y_shift > 0 else -1\\n x = from_.x\\n roadmap = [self._board[y][x]\\n for y in range(from_.y, to.y + y_step, y_step)]\\n return roadmap[1:]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5d9a4eefee39433d9de8c4c66c649f52\",\n \"score\": \"0.5353084\",\n \"text\": \"def get_tile_neighbours(self, x, y):\\n res = list()\\n for key in cons.DIRECTIONS:\\n tup = cons.DIRECTIONS.get(key)\\n res.append(self.get_tile_neighbour(x, y, tup))\\n return res\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bd3ec523a398d964588e22580ac6bf84\",\n \"score\": \"0.53426754\",\n \"text\": \"def neighbours(self, currTile):\\n X = currTile[0]\\n Y = currTile[1]\\n l = [(x,y) for x in range(X-1, X+2) for y in range(Y-1, Y+2) if 0 <= x < self.config.N if 0 <= y < self.config.N if (x != X or y != Y)]\\n return l\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9c1efdc4c72eb7fd2e76ca851d377d97\",\n \"score\": \"0.5339586\",\n \"text\": \"def get_neighbours(self, square: int) -> [int]:\\n x, y = square % self.cols, square // self.rows\\n neighbours = [(p[0] + x, p[1] + y) for p in [(0, -1), (-1, 0), (0, 1), (1, 0)]] \\n return [n[0] + n[1] * self.cols for n in neighbours if 0 <= n[0] < self.cols and 0 <= n[1] < self.rows]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ad4d5a806800463852f6b8986ce47f30\",\n \"score\": \"0.5322932\",\n \"text\": \"def create_grid_2_5d(data, safe_distance):\\n # minimum and maximum north coordinates\\n north_min = np.floor(np.min(data[:, 0] - data[:, 3]))\\n north_max = np.ceil(np.max(data[:, 0] + data[:, 3]))\\n\\n # minimum and maximum east coordinates\\n east_min = np.floor(np.min(data[:, 1] - data[:, 4]))\\n east_max = np.ceil(np.max(data[:, 1] + data[:, 4]))\\n\\n # given the minimum and maximum coordinates we can\\n # calculate the size of the grid.\\n north_size = int(np.ceil((north_max - north_min + 1)))\\n east_size = int(np.ceil((east_max - east_min + 1)))\\n\\n # Initialize an empty grid\\n grid = np.zeros((north_size, east_size))\\n\\n # Populate the grid with obstacles\\n for i in range(data.shape[0]):\\n north, east, alt, d_north, d_east, d_alt = data[i, :]\\n obstacle = [\\n int(np.clip(north - d_north - safe_distance - north_min, 0, north_size - 1)),\\n int(np.clip(north + d_north + safe_distance - north_min, 0, north_size - 1)),\\n int(np.clip(east - d_east - safe_distance - east_min, 0, east_size - 1)),\\n int(np.clip(east + d_east + safe_distance - east_min, 0, east_size - 1)),\\n ]\\n obs = grid[obstacle[0]:obstacle[1] + 1, obstacle[2]:obstacle[3] + 1]\\n np.maximum(obs, np.ceil(alt + d_alt + safe_distance), obs)\\n\\n return grid, int(north_min), int(east_min)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ad2632666a072c8d24eda89c5292e835\",\n \"score\": \"0.5317036\",\n \"text\": \"def create_knight_roadmap(self, from_: Position, to: Position) -> list[Cell]:\\n\\n return [self._board[to.y][to.x]]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"daecb0b845e234930686b2e49d98639a\",\n \"score\": \"0.5313709\",\n \"text\": \"def __init__(self):\\n\\n ##2D array of Tile objects\\n self.board = []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c935410154d1f2d0f466f0d6f730fcc9\",\n \"score\": \"0.53093815\",\n \"text\": \"def make_locs(n, m) -> NDArray:\\n return np.array([[i, j] for i in range(n) for j in range(m)])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f84cecad7f66235e3f432dfc9567d760\",\n \"score\": \"0.5304875\",\n \"text\": \"def _emptyMaze(self, width: int, height: int) -> list:\\n return [[Cell() for x in range(width)] for y in range(height)]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1c47c86de7666745948015c58bc5dc49\",\n \"score\": \"0.5303785\",\n \"text\": \"def getNeighbours(image,i,j):\\n nbg = []\\n for k in np.arange(i-1, i+2):\\n for l in np.arange(j-1, j+2):\\n try:\\n nbg.append(image[k,l])\\n except Exception as e:\\n pass\\n return np.array(nbg)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e33c6c29202fc171158fb68e028ea698\",\n \"score\": \"0.5295464\",\n \"text\": \"def extracted_array_2d_from(\\r\\n array_2d: np.ndarray, y0: int, y1: int, x0: int, x1: int\\r\\n) -> np.ndarray:\\r\\n\\r\\n new_shape = (y1 - y0, x1 - x0)\\r\\n\\r\\n resized_array = np.zeros(shape=new_shape)\\r\\n\\r\\n for y_resized, y in enumerate(range(y0, y1)):\\r\\n for x_resized, x in enumerate(range(x0, x1)):\\r\\n if (\\r\\n y >= 0\\r\\n and x >= 0\\r\\n and y <= array_2d.shape[0] - 1\\r\\n and x <= array_2d.shape[1] - 1\\r\\n ):\\r\\n resized_array[y_resized, x_resized] = array_2d[y, x]\\r\\n\\r\\n return resized_array\",\n \"title\": \"\"\n },\n {\n \"docid\": \"34e282ff6a2c1986891b60289effe7e1\",\n \"score\": \"0.5289425\",\n \"text\": \"def neighbors(self, cell):\\n i, j = self._world_to_map(cell[0], cell[1])\\n neigh = []\\n if self._is_open(i-1,j):\\n neigh.append((self._map_to_world(i-1,j)))\\n if self._is_open(i+1,j):\\n neigh.append((self._map_to_world(i+1,j)))\\n if self._is_open(i,j-1):\\n neigh.append((self._map_to_world(i,j-1)))\\n if self._is_open(i,j+1):\\n neigh.append((self._map_to_world(i,j+1)))\\n # rounding done in map_to_world too but this seems to help\\n neigh = [(round(x,2), round(y,2)) for x,y in neigh]\\n return neigh\",\n \"title\": \"\"\n },\n {\n \"docid\": \"31772bf4307dd3eb29112032613d6497\",\n \"score\": \"0.5288454\",\n \"text\": \"def neighbours(self, board, pos):\\n res = []\\n x,y = pos[0], pos[1]\\n I = x-1\\n J = y-1\\n\\n for i in range(I, I+3):\\n for j in range(J, J+3):\\n if i < 0 or j < 0 or i > 4 or j > 4 or (i,j) == pos:\\n continue\\n else:\\n if self.canCapture(board, (x, y), (i,j)) :\\n res.append((i, j))\\n return res\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fa1d04456022e8275a042b12c1d5e236\",\n \"score\": \"0.5269025\",\n \"text\": \"def cell_list(self):\\n final_lst = [] # this will be the returned list\\n for row in range(0, len(self.board)):\\n for col in range(0, len(self.board)):\\n final_lst.append((row, col))\\n final_lst.append(self.target_location()) # adds the target location\\n # In this board, returns a list containing the cells in the square\\n # from (0,0) to (6,6) and the target cell (3,7)\\n return final_lst\",\n \"title\": \"\"\n },\n {\n \"docid\": \"41bf0badd86c90949f8db0909f893c21\",\n \"score\": \"0.52671003\",\n \"text\": \"def neighborhood(arr: np.ndarray, pos: tuple, n: int):\\n sx, sy = max(0, pos[0] - n), max(0, pos[1] - n)\\n ex, ey = min(pos[0] + n + 1, arr.shape[0]), min(pos[1] + n + 1, arr.shape[1])\\n return arr[sx: ex, sy: ey]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5c86b099b34e3cb435e1a5ed81cdcfc3\",\n \"score\": \"0.52669704\",\n \"text\": \"def vector_2d():\\n return [0.0, 1.0]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4f17838913ff5b81f4fad731e6248563\",\n \"score\": \"0.5266566\",\n \"text\": \"def get_neighbouring_coordinates(position):\\n row = position[0]\\n col = position[1]\\n\\n neighbours = [\\n (row - 1, col),\\n (row + 1, col),\\n (row, col - 1),\\n (row, col + 1)\\n ]\\n\\n return [n for n in neighbours if 0 <= n[0] < len(current_image) and 0 <= n[1] < len(current_image[1])]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6fcb2315866d9203149f9f134993ed6e\",\n \"score\": \"0.5264142\",\n \"text\": \"def _get_obs(self) -> np.array:\\n return self.board\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1e798af90fde4507b5bb756d2d67a5f0\",\n \"score\": \"0.5260177\",\n \"text\": \"def getAvailableTiles(self):\\n emptyPos = []\\n for x in range(self.size):\\n for y in range(self.size):\\n if self.tile[x][y] == 0:\\n emptyPos.append([x, y])\\n return emptyPos\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5b2122bd7efda1395a803bb6b9c9df07\",\n \"score\": \"0.52600324\",\n \"text\": \"def getNeighbors(self):\\n return [self.north, self.south, self.east, self.west]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3a278765f36da44fe426d3790dc0f556\",\n \"score\": \"0.52579004\",\n \"text\": \"def cell_list(self):\\n # In this __board, returns a list containing the cells in the square\\n # from (0,0) to (6,6) and the __target cell (3,7)\\n res = [(i, j) for i in range(len(self.__grid))\\n for j in range(len(self.__grid))]\\n res.append(self.target_location())\\n return res\",\n \"title\": \"\"\n },\n {\n \"docid\": \"31d4cb2e911fd013c438d9d9106e8faf\",\n \"score\": \"0.5257545\",\n \"text\": \"def __init__(self, contamination):\\n self.rows = len(contamination) + 2\\n self.columns = len(contamination[0]) + 2\\n self.robots = []\\n for i in range(self.rows):\\n temp = []\\n for j in range(self.columns):\\n temp.append(0)\\n self.robots.append(temp)\\n # everything below this line surrounds the 2-D array with a border of 0's for the bases\\n tempList = contamination\\n tempList.insert(0, [0] * (self.columns - 2))\\n tempList.append([0] * (self.columns - 2))\\n for i in range(len(tempList)):\\n l = tempList[i]\\n l.insert(0, 0)\\n l.append(0)\\n tempList[i] = l \\n self.contamination = tempList\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b2d2955b07ebd0434edc32b5e3d324cd\",\n \"score\": \"0.5249533\",\n \"text\": \"def get_neighbours(self, coordinate, nrows, ncols):\\n row = coordinate[0]\\n col = coordinate[1]\\n\\n neighbours = [\\n (row - 1, col),\\n (row + 1, col),\\n (row, col - 1),\\n (row, col + 1)\\n ]\\n\\n return [n for n in neighbours if 0 <= n[0] < nrows and 0 <= n[1] < ncols]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f636ff6ad12395e5c66a551e71881178\",\n \"score\": \"0.52467364\",\n \"text\": \"def make_obstacles_scan(scan_list):\\n\\t#Convert the scan to a numoy arra of points\\n\\tpt_ang = np.arange(0,2*np.pi,np.pi/180)\\n\\tpt_scan = np.array(scan_list)\\n\\tpts = [] #To be returned cartesian form of scan\\n\\tpt_x = np.multiply(pt_scan,np.cos(pt_ang))\\n\\tpt_y = np.multiply(pt_scan,np.sin(pt_ang))\\n\\n\\tfor a,b in zip(pt_x,pt_y):\\n\\t\\tpts.append((a,b))\\n\\n\\tpt_scan = np.array(scan_list)\\n\\t#Shifting the scan values\\n\\tpt_scan_prev = np.append(pt_scan[1:],pt_scan[0])\\n\\t# Taking the absolute difference and comparing with Threshold\\n\\tline_obst = abs(pt_scan_prev - pt_scan)>2*THRESHOLD\\n\\tind=np.argwhere(line_obst==True)\\n\\tind = np.append(0 , ind)\\n\\tind = np.append(ind, len(scan_list))\\n\\n\\tline_obstacles = []\\n\\tpt_scan_enum = list(enumerate(scan_list))\\n\\tfor i in range(len(ind)-1):\\n\\t\\tline = [(pt[0] , pt[1]) for pt in pts[ind[i]+1:ind[i+1]+1]]\\n\\t\\tline_obstacles.append(line)\\n\\n\\treturn (line_obstacles , pts)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"948878e944fe674097ffbb433226a4a1\",\n \"score\": \"0.5244176\",\n \"text\": \"def find_neighbourhood(row, col, layers):\\n neighbourhood = []\\n for i in range(6):\\n if check_boundary(row - 1, col, layers) and i == 0:\\n neighbourhood.append((row - 1, col))\\n elif check_boundary(row + 1, col, layers) and i == 1:\\n neighbourhood.append((row + 1, col))\\n elif check_boundary(row, col - 1, layers) and i == 2:\\n neighbourhood.append((row, col - 1))\\n elif check_boundary(row, col + 1, layers) and i == 3:\\n neighbourhood.append((row, col + 1))\\n elif check_boundary(row - 1, col + 1, layers) and i == 4:\\n neighbourhood.append((row - 1, col + 1))\\n elif check_boundary(row + 1, col - 1, layers) and i == 5:\\n neighbourhood.append((row + 1, col - 1))\\n\\n return neighbourhood\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5d448636e69d1bd5815974889382f7ae\",\n \"score\": \"0.5243242\",\n \"text\": \"def return_bounding_box_2d(x, y, xsize, ysize):\\n if xsize <= 0 or ysize <= 0:\\n print(\\\"ERROR: can't compute bounding box, xsize or height has no positive value\\\")\\n return []\\n return [x-xsize/2, y-ysize/2, x+xsize/2, y+ysize/2]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"047c1262949f27f69e90db231cbfeb0f\",\n \"score\": \"0.52294093\",\n \"text\": \"def get_random_board(self):\\n return [[random.randint(0,1) for x in range(self.width)]\\n for x in range(self.height)]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6291f073381e88c37e33c35ead9aaa53\",\n \"score\": \"0.5227485\",\n \"text\": \"def get_grid_observation(self):\\n cursor_bit = np.zeros(self.board.grid_size + (1,))\\n cursor_bit[tuple(self.cursor)] = 1\\n\\n n_grid = np.prod(self.board.grid_size)\\n population_normalized = np.full(cursor_bit.shape, self.population / n_grid)\\n room_normalized = np.full(cursor_bit.shape, self.room / n_grid)\\n\\n obs = np.concatenate([\\n self.board.to_one_hot(self.player_id),\\n cursor_bit,\\n population_normalized,\\n room_normalized\\n ], axis=-1)\\n return obs\",\n \"title\": \"\"\n },\n {\n \"docid\": \"84302bb268aeb0b1fad6ee1a26958faa\",\n \"score\": \"0.521875\",\n \"text\": \"def detectorResponseMatrix():\\n vec = []\\n for i in range(GRID_RESOLUTION):\\n vec2 = []\\n for j in range(GRID_RESOLUTION):\\n vec2.append(detectorResponseToCell(i, j))\\n vec.append(vec2)\\n return vec\",\n \"title\": \"\"\n },\n {\n \"docid\": \"71c8c609dc184d69ba3adf1adb6d50f9\",\n \"score\": \"0.5208937\",\n \"text\": \"def getNeighbors(row,col,i,j):\\n neigb = []\\n\\n for m in [i-1,i,i+1]:\\n for n in [j-1,j,j+1]:\\n if (not (m == i and j == n)) and row > m >= 0 and col > n >= 0: #within bound\\n neigb.append((m,n))\\n\\n return neigb\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0df036c31880816a2463961d5fe62bf5\",\n \"score\": \"0.51994836\",\n \"text\": \"def createObstacles():\\r\\n # Select a random number, 0 - 4\\r\\n r = random.randrange(4)\\r\\n\\r\\n # If the number is 0, create a spike obstacle\\r\\n if r == 0:\\r\\n obstacles.append(Spike(1200, 415, .25, \\\"assets/images/obstacles/Spikes.png\\\", window))\\r\\n\\r\\n # If the number is 1, create a creepy crawly obstacle\\r\\n elif r == 1:\\r\\n obstacles.append(CreepyCrawly(1200, 415, .25,\\\"assets/images/obstacles/CreepyCrawly.png\\\", window))\\r\\n\\r\\n # If the number is 2, create a rocket obstacle\\r\\n elif r == 2:\\r\\n obstacles.append(Rocket(1200, 340, .25, \\\"assets/images/obstacles/Rocket.png\\\", window))\\r\\n\\r\\n # If the number is 3, create a space invader obstacle\\r\\n elif r == 3:\\r\\n obstacles.append(SpaceInvader(1200, 340, .3, \\\"assets/images/obstacles/SpaceInvader.png\\\", window))\\r\\n\\r\\n # If the number is, create a monkey obstacle\\r\\n else:\\r\\n obstacles.append(Monkey(1200, 310, .5, \\\"assets/images/obstacles/Monkey.png\\\", window))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f9b58c38ae81397e941384fc7abd8210\",\n \"score\": \"0.5197234\",\n \"text\": \"def get_boundary_coords():\\n coords = []\\n for x in range(NUM_PIX_X):\\n for y in range(NUM_PIX_Y):\\n if get_chip_coords(x,y)[0] == -1:\\n coords.append((x,y))\\n \\n return coords\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3299d834a1418a142ebdabb82650d850\",\n \"score\": \"0.519159\",\n \"text\": \"def findNeighbours(self, x, y, board=None):\\n board, _ = self.setBoardAndPlayer(board)\\n\\n neighbours = []\\n # min/max take care of the edge cases\\n for i in range(max(0, x-1), min(x+2, self.spanX)):\\n for j in range(max(0, y-1), min(y+2, self.spanY)):\\n if board[i][j] != BLANK:\\n neighbours.append((i, j))\\n return neighbours\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4e5a9d3eb5d66cef6ca767308b8b31d2\",\n \"score\": \"0.5182894\",\n \"text\": \"def getBoardArray(self):\\r\\n a = zeros(self.outdim)\\r\\n for i, p in enumerate(self._iterPos()):\\r\\n if self.b[p] == self.WHITE:\\r\\n a[2 * i] = 1\\r\\n elif self.b[p] == self.BLACK:\\r\\n a[2 * i + 1] = 1\\r\\n return a\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4e5a9d3eb5d66cef6ca767308b8b31d2\",\n \"score\": \"0.5182894\",\n \"text\": \"def getBoardArray(self):\\r\\n a = zeros(self.outdim)\\r\\n for i, p in enumerate(self._iterPos()):\\r\\n if self.b[p] == self.WHITE:\\r\\n a[2 * i] = 1\\r\\n elif self.b[p] == self.BLACK:\\r\\n a[2 * i + 1] = 1\\r\\n return a\",\n \"title\": \"\"\n },\n {\n \"docid\": \"80e8c7eb525fadb65254ebc6c96c60c9\",\n \"score\": \"0.5179019\",\n \"text\": \"def to_arrays(self):\\n players = range(self.num_players)\\n maps = [self.halite_map]\\n for player_id in players:\\n ship_dict = self.ships[player_id]\\n ship_indicators = np.zeros_like(self.halite_map)\\n ship_energy = np.zeros_like(self.halite_map)\\n for (x, y), energy in ship_dict.items():\\n ship_energy[x, y] = energy\\n ship_indicators[x, y] = 1\\n maps.extend([ship_energy, ship_indicators])\\n for player_id in players:\\n factory_loc = self.factory_locs[player_id]\\n factory_loc_map = np.zeros_like(self.halite_map)\\n factory_loc_map[factory_loc[0], factory_loc[1]] = 1\\n maps.append(factory_loc_map)\\n for player_id in players:\\n dropoff_locs = self.dropoff_locs[player_id]\\n dropoff_loc_map = np.zeros_like(self.halite_map)\\n for dropoff_loc in dropoff_locs:\\n dropoff_loc_map[dropoff_loc[0], dropoff_loc[1]] = 1\\n maps.append(dropoff_loc_map)\\n map_arr = np.array(maps)\\n\\n other_state = [self.turns_remaining]\\n for player_id in players:\\n other_state.append(self.scores[player_id])\\n other_arr = np.array(other_state, dtype=np.float64)\\n map_arr = np.moveaxis(map_arr, 0, -1)\\n assert map_arr.shape == (\\n self.map_width,\\n self.map_width,\\n 9 if self.num_players == 2 else 17,\\n )\\n return map_arr, other_arr\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d9ccab57a18b890f6947ed0794694f93\",\n \"score\": \"0.517024\",\n \"text\": \"def neigh(Node, step):\\n\\tx, y = Node[0], Node[1]\\n\\treturn [[x, y+step], [x, y-step], [x+step, y], [x-step, y]]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"67c0d9a0c0ae6642e6f982423d2b8518\",\n \"score\": \"0.5164656\",\n \"text\": \"def as_list(self, key=True):\\n grid_list = []\\n\\n for x in range(self.width):\\n for y in range(self.height):\\n if self[x][y] == key:\\n grid_list.append((x, y))\\n\\n return grid_list\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f4b993679c5f5fa463f39a6cea142bd8\",\n \"score\": \"0.51613635\",\n \"text\": \"def _grid(self, coords):\\n rows = max(r for (r, _, _) in coords) + 1 if coords != [] else 0\\n unpadded_grid = [[p for (r, _, p) in coords if r == row] for row in\\n range(rows)]\\n return unpadded_grid\",\n \"title\": \"\"\n },\n {\n \"docid\": \"92f43c3d510b9cb2ee21c92cddc1550e\",\n \"score\": \"0.5159394\",\n \"text\": \"def loadObstacles(self,obstaclefile):\\n\\n # Initiate data structures.\\n data = open(obstaclefile,\\\"r\\\")\\n obs_sizes = [];\\n obs_positions = [];\\n obs_masses = [];\\n reading = \\\"None\\\"\\n\\n # Parse the obstacle text file.\\n for line in data:\\n linesplit = line.split()\\n if linesplit != []:\\n if linesplit[0] != \\\"#\\\":\\n obs_sizes.append([float(linesplit[0]),float(linesplit[1]),float(linesplit[2])])\\n obs_positions.append([float(linesplit[3]),float(linesplit[4]),float(linesplit[5])])\\n obs_masses.append(float(linesplit[6])) \\n\\n # Go through all the obstacles in the list and spawn them.\\n for i in range(len(obs_sizes)):\\n\\n obs_size = obs_sizes[i]\\n obs_pos = obs_positions[i]\\n obs_mass = obs_masses[i]\\n \\n # Create the obstacle.\\n body = ode.Body(self.world)\\n geom = ode.GeomBox(space=self.space, lengths=obs_size )\\n geom.setBody(body)\\n geom.setPosition(obs_pos)\\n M = ode.Mass()\\n M.setBox(obs_mass,obs_size[0],obs_size[1],obs_size[2])\\n body.setMass(M)\\n\\n # Append all these new pointers to the simulator class.\\n self._geoms.append(geom)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"63d42b555366d584f5d111f988865943\",\n \"score\": \"0.5158857\",\n \"text\": \"def get_neighbors(self, x, y):\\n neighbors = []\\n for y_ in [y - 1, y, y + 1]:\\n if y_ < 0 or y_ > self.height - 1: # If Y coordinate is invalid\\n continue\\n for x_ in [x - 1, x, x + 1]:\\n if x_ == x and y_ == y: # If center\\n continue\\n if x_ < 0 or x_ > self.width - 1: # If X coordinate is invalid\\n continue\\n neighbors.append((x_, y_))\\n return neighbors\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1af892c93d788ccbb26b8892dcf935ae\",\n \"score\": \"0.5157673\",\n \"text\": \"def _generate_grid(self):\\n return [[self.make_square(row, col) for col in range(self.dim_col)]\\n for row in range(self.dim_row)]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bb6468015a52974d7a263795bb81f899\",\n \"score\": \"0.5153086\",\n \"text\": \"def cell_list(self):\\n lst = [(i, j) for i in range(self.BOARD_LENGTH) for j in\\n range(self.BOARD_LENGTH)]\\n lst.append(self.GOAL_LOCATION)\\n return lst\",\n \"title\": \"\"\n },\n {\n \"docid\": \"593493a9e5c93e5ebd28b476e91ad340\",\n \"score\": \"0.51493853\",\n \"text\": \"def neighbors(self, pos, diagonals=False):\\r\\n x, y = pos\\r\\n neighbors = [(x + 1, y), (x - 1, y), (x, y - 1), (x, y + 1)]\\r\\n if diagonals:\\r\\n neighbors += [(x + 1, y + 1), (x - 1, y + 1), (x + 1, y - 1), (x - 1, y - 1)]\\r\\n if (x + y) % 2 == 0: neighbors.reverse()\\r\\n results = filter(self.in_bounds, neighbors)\\r\\n results = filter(self.no_obstacle, results)\\r\\n return results\",\n \"title\": \"\"\n },\n {\n \"docid\": \"926358c52e9b65966852b514fcceb712\",\n \"score\": \"0.5146556\",\n \"text\": \"def neighbors8(self, coord):\\n (x,y) = coord\\n results = [(x+1, y+1), (x+1, y), (x+1, y-1),\\n (x, y+1), (x, y-1),\\n (x-1, y+1), (x-1, y), (x-1, y-1)]\\n results = list(filter(self.in_bounds, results))\\n results = list(filter(self.passable, results))\\n return results\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bb38c47eec0f3ca2ad2715da8c36114c\",\n \"score\": \"0.51445603\",\n \"text\": \"def generate(self):\\n newBoards = []\\n\\n # For each point\\n for p in self.board:\\n # Generate all neighboring points\\n for newy in range(self.N):\\n if newy == p[1]:\\n continue\\n newp = (p[0], newy)\\n if newp not in self.board:\\n newboard = self.board[:]\\n newboard[newboard.index(p)] = newp\\n newBoards.append(newboard)\\n\\n return newBoards\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e68169fb1fe6eedc1ca858b065a8d956\",\n \"score\": \"0.51392007\",\n \"text\": \"def get_nozzle_positions():\\n nozzle_positions = [(0.0)] * n_nozzles\\n d_between = boom_length / (n_nozzles - 1)\\n for i in range(n_nozzles):\\n nozzle_positions[i] = (boom_offset, i * d_between - boom_length / 2, inp['H'] - boom_height)\\n return nozzle_positions\",\n \"title\": \"\"\n },\n {\n \"docid\": \"969fa007597b157725a2a56afbb51451\",\n \"score\": \"0.51356924\",\n \"text\": \"def get_movables_tiles(board, player_value=0):\\n movable = []\\n for x in range(len(board)):\\n for y in range(len(board[x])):\\n value = board[x][y]\\n if is_movable_tile(x, y) and (value == 0 or value == player_value):\\n movable.append((x, y))\\n\\n return movable\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3268ff3c8861c2fa7c275a12b6c862db\",\n \"score\": \"0.5132038\",\n \"text\": \"def hit_box(self) -> list:\\n hit_box = []\\n\\n x_max = self.largeur_screen // LARGEUR_TUILE\\n y_max = self.hauteur_screen // HAUTEUR_TUILE\\n\\n for i in range(0, y_max):\\n for j in range(0, x_max):\\n x = j * LARGEUR_TUILE\\n y = i * HAUTEUR_TUILE\\n item = self.niveau[i][j]\\n\\n if item != \\\"V\\\":\\n hit_box.append((x, y))\\n\\n return hit_box\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":392,"cells":{"query_id":{"kind":"string","value":"d9b703dfa0713d148772683e9d85d349"},"query":{"kind":"string","value":"Reduce the items in this list to identifiers that can be used to recreate them from scratch. This adds each item to the cache too."},"positive_passages":{"kind":"list like","value":[{"docid":"b0417d0cd78b920baa1079318656fc4c","score":"0.69286984","text":"def _pack_items(self):\n identifiers = tuple(self.identify_items(self))\n cache_keys = self.make_cache_keys(identifiers)\n cache_items = dict(izip(cache_keys, self))\n self.cache.set_many(cache_items, self.cache_timeout)\n return identifiers","title":""}],"string":"[\n {\n \"docid\": \"b0417d0cd78b920baa1079318656fc4c\",\n \"score\": \"0.69286984\",\n \"text\": \"def _pack_items(self):\\n identifiers = tuple(self.identify_items(self))\\n cache_keys = self.make_cache_keys(identifiers)\\n cache_items = dict(izip(cache_keys, self))\\n self.cache.set_many(cache_items, self.cache_timeout)\\n return identifiers\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"04f3496398ff04367f08c593ebc8f7c4","score":"0.71066976","text":"def _unpack_items(self):\n\n # Prevent the unpack operation from occurring more than once.\n if hasattr(self, '_unpack'):\n delattr(self, '_unpack')\n else:\n return\n\n # The list contains identifiers that will be unpacked into real items.\n # Copy them so they won't be lost when the list values are altered.\n identifiers = self[:]\n\n cache_keys = dict(izip(identifiers, self.make_cache_keys(identifiers)))\n cached_items = self.cache_backend.get_many(cache_keys.values())\n\n items = {}\n missed = []\n for identifier, cache_key in cache_keys.items():\n try:\n item = cached_items[cache_key]\n assert item is not None\n except (AssertionError, KeyError):\n missed.append(identifier)\n else:\n items[identifier] = item\n\n if missed:\n\n # Rebuild the missing items using their identifiers and\n # replace the contents of this list with those new items.\n self[:] = self.rebuild_items(missed)\n\n # Use the pack_items method to add them to the cache and also\n # get back their identifiers. Finally, put the new items into\n # the items dict to be returned at the end.\n found_identifiers = self._pack_items()\n items.update(izip(found_identifiers, self))\n\n # Replace the value of this list with the final result.\n del self[:]\n for identifier in identifiers:\n item = items.get(identifier)\n if item is not None:\n self.append(item)","title":""},{"docid":"fd95c30102e1eb9b54c5b5913727ada8","score":"0.65366846","text":"def rebuild_items(self, identifiers):\n raise NotImplementedError","title":""},{"docid":"89d5610230e58fa085046f10e4c06c5f","score":"0.6319896","text":"def UpdateIds(self):\r\n removed = set(self.item_itemId.keys()) - set(self.data.keys())\r\n for item in removed:\r\n itemId = self.item_itemId[item]\r\n del self.item_itemId[item]\r\n del self.itemId_item[itemId]","title":""},{"docid":"8aac78c071b4804a50c8441963bb9100","score":"0.6208331","text":"def __reduce__(self):\n init_args = (\n self.__class__,\n self._pack_items(),\n )\n if self.cache_timeout:\n init_kwargs = {'cache_timeout': self.cache_timeout}\n else:\n init_kwargs = {}\n return (_unpickle_cached_list, init_args, init_kwargs)","title":""},{"docid":"719aae5ffbb29c6b379af986fa5e37a5","score":"0.61230433","text":"def learn_ids(self, item_list):\n self._reset_sequence()\n for item in item_list:\n key = self.nondup_key_for_item(item)\n self.ids[key] = item[self.id_key]","title":""},{"docid":"405476beaecdf6d402cdcc71a0f9e9f5","score":"0.6076083","text":"def set_ids(self, item_list):\n self._reset_sequence()\n for item in item_list:\n key = self.nondup_key_for_item(item)\n item[self.id_key] = self.ids.get(key) or self._get_next_id()","title":""},{"docid":"70624459dc155a8c7515bf792e28e123","score":"0.5991048","text":"def fillCache(self):\n items = self.source.getRecent()\n items.reverse() # make sure the most recent ones are added last to the cache\n for item in items:\n self.cache.append(item.title)","title":""},{"docid":"0029a129d6ea9529f86fea0bf93e576f","score":"0.5884281","text":"def rehash(self):\n old = list()\n # use iteration to record existing items\n for i in range(self.capacity // 2):\n if self.table[i] is not None:\n old.append(self.table[i])\n self.table = self.capacity * [None] # then reset table to desired capacity\n self.size = 0\n for i in old:\n index = self.quadratic_probe(i.key)\n self.table[index] = i\n self.size += 1","title":""},{"docid":"d4a8cd859e3895cb5b72bb40991911e7","score":"0.58541334","text":"def testRemovingDuplicates(self):\n\n item1 = {KEY: 'one', 'name': 'foo'}\n item2 = {KEY: 'two', 'name': 'bar'}\n item3 = {KEY: 'three', 'name': 'baz'}\n dup_item1 = {KEY: 'one', 'name': 'foo'}\n dup_item2 = {KEY: 'two', 'name': 'qux'}\n\n list_with_duplicates = [item1, item2, item3, dup_item1, dup_item2]\n # duplicate items should not be present in the cached list\n expected_list = [item1, item2, item3]\n\n cached_list_logic.setCacheItems('test_list', list_with_duplicates)\n cached_list = cached_list_model.CachedList.get_by_id('test_list')\n self.assertListEqual(cached_list.list_data, expected_list)","title":""},{"docid":"ec79bf68b3cc9ade46e621262956863b","score":"0.5630425","text":"def remove_duplicates_in_items(items: list, id_key: str) -> list:\n ids = {}\n new_items = []\n for item in items:\n item_id = item.get(id_key)\n if item_id not in ids:\n ids[item_id] = True\n new_items.append(item)\n\n return new_items","title":""},{"docid":"2cf41babfc15555765cec21ea4efcf47","score":"0.5608932","text":"def Deduplicate(items):\n seen = set()\n for it in items:\n if it not in seen:\n seen.add(it)\n yield it","title":""},{"docid":"6b3f058576245b08a98c4e29c0dbfd46","score":"0.5596204","text":"def _hashed_items(self):\n return self","title":""},{"docid":"362eebce24f40328b63fa390e70c0c79","score":"0.55942404","text":"def _reset_track_lst(self):\n del self._track_item\n self._track_item = {key : [] for key in self._track_lst}\n return self._track_item","title":""},{"docid":"700cb8953104865f413da2221aa61eb3","score":"0.55431926","text":"def OldItems(self) -> _n_1_t_7:","title":""},{"docid":"9cf9511193f5fcbf4050f362f6a20828","score":"0.55386627","text":"def collate(items):\n # return batch items as a list\n return items","title":""},{"docid":"981de5cb377c8c0713c7fdd006f2296d","score":"0.5511309","text":"def _cache(item_label, item_list):\n id_label = item_label + '_id'\n mbid_label = item_label + '_mbid'\n echonest_id_label = item_label + '_echonest_id'\n items = {}\n for item in item_list:\n key = '/%s/%s' % (item_label, item[id_label])\n items[key] = item\n musicbrainz_id = item.get(mbid_label, None)\n if musicbrainz_id:\n items['/musicbrainz/%s/%s' % (item_label, musicbrainz_id)] = key\n # echonest_id = item.get(echonest_id_label, None)\n # if echonest_id:\n # items['/echonest/%s/%s' % (item_label, echonest_id)] = key\n application.config.get('CACHE').set_many(items)","title":""},{"docid":"c81a69b566689e9502235bf06ce8ab51","score":"0.54834604","text":"def clean_up_map(self):\n self.items = [i for i in self.items if i.quantity != 0]","title":""},{"docid":"037eb212aeb81bbc51022678d212b6c4","score":"0.546661","text":"def cache_all(self):\n if not self._cached_all:\n poss = range(len(self))\n uuids = self.vars['uuid']\n\n cls_names = self.variables['cls'][:]\n samples_idxss = self.variables['samples'][:]\n subchanges_idxss = self.variables['subchanges'][:]\n mover_idxs = self.variables['mover'][:]\n details_idxs = self.variables['details'][:]\n try:\n input_samples_vars = self.variables['input_samples']\n except KeyError:\n # BACKWARD COMPATIBILITY: REMOVE IN 2.0\n input_samples_idxss = [[] for _ in samples_idxss]\n else:\n input_samples_idxss = input_samples_vars[:]\n\n [self._add_empty_to_cache(*v) for v in zip(\n poss,\n uuids,\n cls_names,\n samples_idxss,\n input_samples_idxss,\n mover_idxs,\n details_idxs)]\n\n [self._load_partial_subchanges(c, s) for c, s in zip(\n self,\n subchanges_idxss)]\n\n self._cached_all = True","title":""},{"docid":"768778ac6290dd31ad58bda94e7f950a","score":"0.5451933","text":"def uniquify_list(seq, idfun=None):\n\n if idfun is None:\n\n def idfun(x):\n return x\n\n seen = {}\n result = []\n for item in seq:\n marker = idfun(item)\n if marker in seen:\n continue\n seen[marker] = 1\n result.append(item)\n return result","title":""},{"docid":"27056edd253e5a0fc73c653f8cf72b50","score":"0.5417399","text":"def concat_duplicate_ids(self) -> None:\n # Rebuilt list instead of removing duplicated one at a time at the cost of O(n).\n self.data.clear()\n\n # This implementation takes advantage of the ordering of the duplicated in the __init__ method\n\n has_external_ids = set()\n for ext_id, items in self._external_id_to_item.items():\n if not isinstance(items, list):\n self.data.append(items)\n if items.id is not None:\n has_external_ids.add(items.id)\n continue\n concatenated = DatapointsArray.create_from_arrays(*items)\n self._external_id_to_item[ext_id] = concatenated\n if concatenated.id is not None:\n has_external_ids.add(concatenated.id)\n self._id_to_item[concatenated.id] = concatenated\n self.data.append(concatenated)\n\n if not (only_ids := set(self._id_to_item) - has_external_ids):\n return\n\n for id_, items in self._id_to_item.items():\n if id_ not in only_ids:\n continue\n if not isinstance(items, list):\n self.data.append(items)\n continue\n concatenated = DatapointsArray.create_from_arrays(*items)\n self._id_to_item[id_] = concatenated\n self.data.append(concatenated)","title":""},{"docid":"0f465738f7d88199fb3e96d16f08925f","score":"0.54072","text":"def unique_residue_ids(self): \n # Convenience abbreviations.\n identifiers = self.identifiers\n res_ids = self.res_ids\n res_cnt = self.res_cnt \n # Preparing the list of unique residue identifiers.\n # In the end it should be: res_cnt == len(res_ids)-1.\n # The 'elif' line is controlling that only unique\n # identifiers are collected.\n for identifier in identifiers:\n if len(res_ids) == 0:\n # Require 'deepcopy', otherwise constant change\n # of 'res_ids[res_cnt]' with 'identifier'.\n res_ids.append(deepcopy(identifier))\n elif identifier[1] == res_ids[res_cnt][1]: \n pass\n else:\n res_ids.append(deepcopy(identifier))\n res_cnt += 1 \n # Return assignments to object scope.\n self.res_ids = res_ids\n self.res_cnt = res_cnt","title":""},{"docid":"7887abe496fd6fd9c547ffe44eb6ee68","score":"0.5397846","text":"def _expand_priority_order(self, id_list):\n res = self.id_priority_list.copy()\n for key in id_list:\n if key not in self.id_priority_list:\n res.append(key)\n return res","title":""},{"docid":"f9d0ec9d39cfb94b73770923cc6880f8","score":"0.5388973","text":"def compactify(self):\n logger.debug(\"rebuilding dictionary, shrinking gaps\")\n\n # build mapping from old id -> new id\n idmap = dict(zip(sorted(itervalues(self.token2id)), range(len(self.token2id))))\n\n # reassign mappings to new ids\n self.token2id = {token: idmap[tokenid] for token, tokenid in iteritems(self.token2id)}\n self.id2token = {}\n self.dfs = {idmap[tokenid]: freq for tokenid, freq in iteritems(self.dfs)}","title":""},{"docid":"15cd6d40f564fe8f6db34d783ab295c7","score":"0.5363779","text":"def _update_unused(self, key):\n try:\n item_list = self.parent.dataset[key]\n max_id = max(item['id'] for item in item_list) if item_list else 0\n next_id = max(max_id + 1, len(item_list))\n except KeyError:\n # The table doesn't exist, so we can use anything\n next_id = 1\n self.unused[key] = next_id","title":""},{"docid":"3a081b6d2f5907a4cca610f268f2754f","score":"0.53463596","text":"def reset(self):\n for i in range(self.k):\n self.list[i] = self.dic[i]\n return self.list","title":""},{"docid":"52319bc27440f01d24b5f7f7d990c9bc","score":"0.5338179","text":"def update(self):\r\n self.data = [self.make_item_tuple(i) for i in self.query]\r\n self._fetched = True\r\n query_cache.set(self.iden, self.data)","title":""},{"docid":"4426012ea6e97d7223fbe4ca71c77f83","score":"0.5335431","text":"def make_cache_keys(self, identifiers):\n\n raise NotImplementedError","title":""},{"docid":"d0455dbf0a4c0f80171edacef755f2b3","score":"0.5325638","text":"def _unpickle_cached_list(cls, *args, **kwargs):\n new_list = cls(*args, **kwargs)\n new_list._unpack = True\n return new_list","title":""},{"docid":"3d0878b3d86025381140c859c9f882f7","score":"0.53181565","text":"def remove_duplicates(data):\n already_used_items = {}\n return_data = []\n\n for item in data:\n # Yes, I know that I can find used items in the return_data,\n # but HW requires this logic.\n if not already_used_items.get(item):\n return_data.append(item)\n already_used_items[item] = True\n\n return return_data","title":""},{"docid":"6da9f8f02ea1dab3c752f7bc1f152e37","score":"0.52880013","text":"def _increase_size(self) -> None:\n keys_vals_to_move = [item for item in self.HashMap if item]\n self.length = 0\n self.capacity = self.capacity * 2\n self.HashMap = [None] * self.capacity\n for item in keys_vals_to_move:\n while len(item) > 0:\n self.add(item[0], item[1])\n item.pop(0)\n item.pop(0)","title":""},{"docid":"75e5962c6bb6e899a567f9886a797905","score":"0.5285236","text":"def GetItemsFromIterablesCached(self):\n items = []\n assert len(self.state_id) == len(self.iterables)\n for iter_num, iter_counter in enumerate(self.state_id):\n item = self.history_items[iter_num].get(iter_counter+1, \"unexplored\")\n if item == \"unexplored\":\n try:\n item = self.iterables[iter_num].next()\n except StopIteration:\n item = None\n self.history_items[iter_num][iter_counter+1] = item\n items.append(item)\n return items","title":""},{"docid":"ce8347208ee33e6fd2c938f0509aedf1","score":"0.52832246","text":"def clear_cache(self):\n ida_strlist.clear_strlist()","title":""},{"docid":"0a6692985258457ba9a782cf0a6d9198","score":"0.5281415","text":"def remove_duplicates_for_fetch(items: list, last_fetched_ids: list) -> list:\n return [\n item\n for item in items\n if item.get('id') and item.get('id') not in last_fetched_ids\n ]","title":""},{"docid":"21583c27bcaf64ae76a948825eacbf04","score":"0.52663577","text":"def fill_from_cache(self):\n move_count = min(\n len(self._replacement_cache),\n constants.K - len(self._contacts)\n )\n\n for _ in range(move_count):\n self.add_contact(self._replacement_cache.pop())","title":""},{"docid":"9fdcda24368d43c68d039a458ccd6446","score":"0.52637416","text":"def large_train_collection(train_items: List[JSONDict]) -> TrainCollection:\n items = []\n\n item = train_items[0]\n for i in range(3000):\n copy = item.copy()\n copy[\"url\"] = copy[\"url\"].replace(\"post1\", f\"post{i}\")\n items.append(copy)\n\n collection = TrainCollection(items=items)\n return collection","title":""},{"docid":"990715882cbcb3b4c793a97c0ee772f0","score":"0.5230081","text":"def clear_flush_lists(self, keys):\r\n cache.delete_many(keys)","title":""},{"docid":"a61766dec7c0c946a54fcb5b1631ac45","score":"0.5229862","text":"def trim_items(self, items):\r\n\t\tlogger.debug(\"Enter\")\r\n\t\t\r\n\t\tif self.transactions:\r\n\t\t\tall_items = set.union(*[self.transactions[u][-1] for u in self.transactions.keys()])\r\n\t\telse:\r\n\t\t\treturn items\r\n\t\t\t\r\n\t\ttmp = items.copy()\r\n\t\t\r\n\t\tfor i in items:\r\n\t\t\tif i in all_items:\r\n\t\t\t\tlogger.debug(\"Removing %r\" % i)\r\n\t\t\t\ttmp.remove(i)\r\n\t\t\t\t\r\n\t\tlogger.debug(\"Exit\")\r\n\t\treturn tmp","title":""},{"docid":"e315ec3a484517b576a5a8b4eb6c6880","score":"0.52169263","text":"def evict_or_add (self, item):","title":""},{"docid":"c7a06bcf5829018a8e58a369e038a602","score":"0.521555","text":"def cache_db_items(self, key, items, item_key='id'):\n db_items = self._extension_data['db_items'].setdefault(key, {})\n for item in items:\n db_items[item[item_key]] = item","title":""},{"docid":"e02d6bcaaa4b546441050e042af93801","score":"0.52053124","text":"def untie_everything(self):\r\n self.tied_indices = []","title":""},{"docid":"80a4055d21c6dd78745d80ec67cba51e","score":"0.5204175","text":"def remove_duplicate_items(cls, items_in, prior_batch_ids):\n items_out = []\n item_ids = set(prior_batch_ids)\n for item in items_in:\n if item[\"id\"] not in item_ids:\n item_ids.add(item[\"id\"])\n items_out.append(item)\n else:\n continue\n return items_out","title":""},{"docid":"27b93b9260cc5dce0097053577cd0ac5","score":"0.51884717","text":"def delete_duplicate(x):\n return list(dict.fromkeys(x))","title":""},{"docid":"914725600bf52a10842be4db18e10034","score":"0.5184313","text":"def prune(self): # HashMap.prune\n for hashval, list in self.contentHash.iteritems():\n newlist=[]\n for entry in list:\n if not entry.deleted:\n newlist.append(entry)\n self.contentHash[hashval]=newlist","title":""},{"docid":"8489e3ee6eb773ff17078793c717ffd4","score":"0.51667583","text":"def _fillcache(self, n: int | None) -> None:\n if not n:\n n = 1\n try:\n while len(self._cache) < n:\n self._cache.append(self.modifier(next(self._iterable))) # type: ignore\n except StopIteration:\n while len(self._cache) < n:\n self._cache.append(self.sentinel)","title":""},{"docid":"312868e6563227ce5e3cbfe5a72b841e","score":"0.5164763","text":"def remove_duplicates(input_list):\n return list(dict.fromkeys(input_list))","title":""},{"docid":"681a06ca9b01daaf8a4dd09169de8563","score":"0.5159341","text":"def _change_objs_to_IDs(self):\n if self.location:\n self.location = self.location.id\n if self.contents:\n self.contents = [obj.id for obj in self.contents]","title":""},{"docid":"59ee1707485a948778f73bcfd255ec48","score":"0.51530373","text":"def _hash(self, item):\r\n pass # TODO\r","title":""},{"docid":"f012f5379aad31fe74cd1eae0b390801","score":"0.51485205","text":"def _shrink(self):\n self.capacity = round(self.capacity / self.factor)\n temp = [None] * self.capacity\n for i in range(self.capacity):\n temp[i] = self.store[i]\n self.store = temp","title":""},{"docid":"98a5993a5cee476306e6864df5d4e925","score":"0.51277685","text":"def dedupe(items):\n seen = set()\n for item in items:\n if item not in seen:\n yield item\n seen.add(item)","title":""},{"docid":"288d9d2a080beb0d9cc12e0cc0d60fbe","score":"0.5118063","text":"def remove_duplicates(self):\n names: Dict[str, int] = dict()\n for step in self.Sequence:\n if isinstance(step, Repeater):\n continue\n name = step.Name\n if name != '':\n if name not in names:\n names[name] = 1\n else:\n names[name] += 1\n for step in reversed(self.Sequence):\n if isinstance(step, Repeater):\n continue\n name = step.Name\n if name and (names[name] > 1):\n names[name] -= 1\n step.Name = name + \"_%i\" % names[name]","title":""},{"docid":"e42f9fdac48b633a57e1b1ed05b3313e","score":"0.5107073","text":"def _update_use(self, key):\n\t\tif (self._replace_pol == Cache.LRU):\n\t\t\tself.cache[key]= self.hashmap[key]\n\t\tif (self._replace_pol == Cache.LRU_S):\n\t\t\tself.cache[key] = self.hashmap[key]","title":""},{"docid":"066452b6998349caf8cfe8c6554ca6f7","score":"0.51054615","text":"def removeOldItems(self):\n pass","title":""},{"docid":"0fbe1bb26e47641f1f92e3af341696b8","score":"0.51044595","text":"def shuffled_data_reset(self):\n self.unique_data = {}\n for stock in self.stocks:\n self.unique_data[stock] = []\n for date in self.dates:\n self.unique_data[stock] += [date]","title":""},{"docid":"1261f1cd1f279cb3ea82516fa1d986fb","score":"0.5082867","text":"def hash_fieldlist(cls):\n for field in cls.fieldlist:\n cls.fieldhash[field.id] = field","title":""},{"docid":"aa1760328e5c1293629bd24921c1bcbf","score":"0.5079646","text":"def mixed_train_items(train_items: List[JSONDict]) -> List[JSONDict]:\n train_items[1][\"categoryid\"] = 9107252648\n return train_items","title":""},{"docid":"707f627a09c9f7f6a0e572774bb508e5","score":"0.50749475","text":"def __init__(self):\n self.items = []\n self.indexes: Dict[int, Set] = defaultdict(set)","title":""},{"docid":"5cce20cbf558401cc8c1d179de3b56b6","score":"0.5070577","text":"def deduped(items):\n \n return list(set(items))","title":""},{"docid":"cfe0fac80127b37b024e0b8dad1328c3","score":"0.506829","text":"def reap():\n\n # This might be more efficient by paginating manually and do memcache.get_multi\n for counter in get_all_counters():\n value = memcache.get(counter.key.string_id(), namespace=NAMESPACE)\n # if value is None:\n # continue\n _increment_db(counter, value)\n memcache.decr(counter.key.string_id(), value, namespace=NAMESPACE)\n print 'memcache: %s => %s' % (counter.key.string_id(), memcache.get(counter.key.string_id(), namespace=NAMESPACE))","title":""},{"docid":"64a232a9c4b886445179f8217d1dbe63","score":"0.5066847","text":"def __init__(self):\n self.ids_seen = set()","title":""},{"docid":"37a39cdbeeb3e27bcc1fb4eb342d6fa1","score":"0.506516","text":"def potentials(self, potential_list):\n for item in potential_list:\n item.store()\n potential_list_uuids = [item.uuid for item in potential_list]\n self.set_attribute('potentials', potential_list_uuids)","title":""},{"docid":"105ce627edef9178252460b3bdf9e8c1","score":"0.5062378","text":"def map_items(self) -> None:\n self.__attribute_columns = list(self.__DataFrame.columns)\n self.__attribute_columns.remove(self.__surv_col_name)\n self.__attribute_columns.remove(self.__status_col_name)\n\n mapped_int = 0\n\n for attribute in self.__attribute_columns:\n for value in self.__DataFrame[attribute].unique():\n item_reference = (attribute, value)\n self.__item_map[item_reference] = mapped_int\n self.items_list.append(item_reference)\n mapped_int += 1","title":""},{"docid":"d1358b98e41139369442a74ad2a3db1d","score":"0.5051759","text":"def expand_id_map(id_map, all_ids):\n\n unmapped_ids = list(set(all_ids).difference(id_map.keys()))\n\n for i in unmapped_ids:\n id_map[i] = i\n\n return id_map","title":""},{"docid":"b1668ee6e1df57e8925590d2e042e93e","score":"0.50455356","text":"def rehash(self):\n new_cap = self._get_new_capacity() # Choose not to handle the ValueError thrown by _get_new_capacity()\n new_table = HashTable(new_cap) # Create a new hash table directly\n for i in range(self.size):\n if self.keys[i] is not None: # Only put() when there exists a key (no Nones)\n new_table[self.keys[i]] = self.values[i] # Rehash and insert into the new table\n\n self.keys = new_table.keys # Update instance variables\n self.values = new_table.values\n self.size = new_cap # Update N\n self.count_rehashes += 1 # Increment total rehashes","title":""},{"docid":"e3d60e32e91c980445d6d1e66f08977e","score":"0.5032233","text":"def __fillCache(self):\n assert (not self.__modelCache)\n\n # Assemble a list of model IDs to look up\n numModelIDs = len(self.__modelIDs) if self.__modelIDs else 0\n\n if self.__nextIndex >= numModelIDs:\n return\n\n idRange = self.__nextIndex + self.__CACHE_LIMIT\n if idRange > numModelIDs:\n idRange = numModelIDs\n\n lookupIDs = self.__modelIDs[self.__nextIndex:idRange]\n\n self.__nextIndex += (idRange - self.__nextIndex)\n\n # Query Nupic for model info of all models in the look-up list\n # NOTE: the order of results may not be the same as lookupIDs\n infoList = _clientJobsDB().modelsInfo(lookupIDs)\n assert len(infoList) == len(lookupIDs), \\\n \"modelsInfo returned %s elements; expected %s.\" % \\\n (len(infoList), len(lookupIDs))\n\n # Create _NupicModelInfo instances and add them to cache\n for rawInfo in infoList:\n modelInfo = _NupicModelInfo(rawInfo=rawInfo)\n self.__modelCache.append(modelInfo)\n\n assert len(self.__modelCache) == len(lookupIDs), \\\n \"Added %s elements to modelCache; expected %s.\" % \\\n (len(self.__modelCache), len(lookupIDs))\n\n if self.debug:\n _emit(Verbosity.DEBUG,\n \"MODELITERATOR: Leaving __fillCache(); modelCacheLen=%s\" % \\\n (len(self.__modelCache),))","title":""},{"docid":"f774b8e5bed3aa9569453565162825db","score":"0.50301826","text":"def _remove_duplicates(input_list):\n return list(OrderedDict.fromkeys(input_list))","title":""},{"docid":"c2b2f4395e0c3820a7e3587e355598ae","score":"0.50289893","text":"def mapper_get_items_init(self):\n if int(self.options.iteration) > 1:\n with open(self.options.f, 'r') as fh:\n self.frequent_items = set(fh.read().splitlines())\n else:\n self.frequent_items = {}","title":""},{"docid":"867ffc91a746827266f061a3c0ae9897","score":"0.50242746","text":"def test_unsized(self):\n cache = LRUCache()\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","title":""},{"docid":"89ed3790f153ec8739030c451e4af4c3","score":"0.50208384","text":"def _fillcache(self, n: int | None) -> None:\n if not n:\n n = 1\n try:\n while len(self._cache) < n:\n self._cache.append(next(self._iterable)) # type: ignore\n except StopIteration:\n while len(self._cache) < n:\n self._cache.append(self.sentinel)","title":""},{"docid":"084dc13ea4b269548970835742e2e48d","score":"0.501621","text":"def add(self, item):\n self.update(set([item]))","title":""},{"docid":"761ac9d24d795bc18846babfe10ea551","score":"0.50095797","text":"def removeDuplicatesInList(self, data):\n newDataList = []\n for i in data:\n if newDataList.count(i) == 0:\n newDataList.append(i)\n data.clear()\n data += newDataList","title":""},{"docid":"89e4d0319dfeac13114d90db0bfe8255","score":"0.5009236","text":"def duplicate_train_items(train_items: List[JSONDict]) -> List[JSONDict]:\n train_items[1][\"url\"] = train_items[0][\"url\"]\n return train_items","title":""},{"docid":"66f4c343d416d8f4427b63c0ab29a170","score":"0.50060844","text":"def item2id(self):\n if self._item2id is None:\n self._item2id = dict(zip(self.item_unique_vals, range(self.n_items)))\n return self._item2id","title":""},{"docid":"27a87ab4211569e026551ad5c47e9c81","score":"0.5004679","text":"def customized_retained_list(self, base_day, day_list=[]):\n auBitmap = self.make_bitmap(base_day, 'dau')\n return [(base_day, auBitmap.count())] + \\\n zip(day_list, self._retained_value(base_day, day_list, 'dau'))","title":""},{"docid":"f03f7c7b4a76609a03dd5702e72a26b7","score":"0.4989525","text":"def evict_purged(self, entity_ids: Iterable[str]) -> None:\n for entity_id in entity_ids:\n self._id_map.pop(entity_id, None)","title":""},{"docid":"ad5c6f1d98a8bd7ccf01f8feb7706eed","score":"0.4983754","text":"def all_reduce(self):\n return {k: reduce_number(v) for k, v in self.items()}","title":""},{"docid":"f52c5d3224a282b90a85cc7d9a214ff1","score":"0.49834982","text":"def purify(l):\n return set([item.replace('B-', '').replace('I-', '') for item in l])","title":""},{"docid":"c8ace0f1a644421dec91924729cb3207","score":"0.4974587","text":"def remove_duplicate_urls(seq, id_fun=None):\n\n if id_fun is None:\n def id_fun(x):\n return x\n seen = {}\n result = []\n for item in seq:\n marker = id_fun(item)\n if marker in seen:\n continue\n seen[marker] = 1\n result.append(item)\n\n return result","title":""},{"docid":"c33aaffbadb012dec2a4c4231ab05208","score":"0.49692756","text":"def setA(cls,*items):\n cls.A = sympy.FiniteSet(*items)\n cls.id2items= {}\n num = 0\n for i in cls.A:\n cls.id2items[num] = i\n num = num + 1","title":""},{"docid":"264b7a9220432c6e5decdcd8d48cbb3a","score":"0.4964221","text":"def dedupe(self):\n elems = []\n for x in self.elems:\n if x not in elems:\n elems.append(x)\n return _coconut_tail_call(self.__class__, *elems)","title":""},{"docid":"57508bd0a67b85f81e74c3eeb789319b","score":"0.49561846","text":"def frequentOneItem(self):\n\n candidate = {}\n # global finalPatterns, minSup, Database\n # self.minSup = self.minSup\n for i in range(len(self.Database)):\n for j in range(len(self.Database[i])):\n if self.Database[i][j] not in candidate:\n candidate[self.Database[i][j]] = [i]\n else:\n candidate[self.Database[i][j]] += [i]\n self.finalPatterns = {keys: value for keys, value in candidate.items() if len(value) >= self.minSup}\n #print(candidate)","title":""},{"docid":"040beceaed5eaf9953636f961ee2c91d","score":"0.4951346","text":"def set_count(items):\n item_count = {}\n for item in items:\n if not item: continue\n if not item_count.has_key(item): item_count[item] = 0\n item_count[item] += 1\n \n items = [(v, k) for k, v in item_count.iteritems()]\n items.sort()\n items.reverse()\n \n return [(k, v) for v, k in items]","title":""},{"docid":"638c68ccc4591aaa2e1196ce95f7d4a1","score":"0.4945082","text":"def __init__(self):\n \n self.items = [] \n self.ind = defaultdict(set) # item -> index into the items array","title":""},{"docid":"ff689f32092e5d3a998c3112f1318c1b","score":"0.49444813","text":"def add_items_quantity_not_duplicates(request):\n all_items_no_duplicates = []\n\n for loop_index, item in enumerate(all_shopping_items(request)):\n item_dict = {\n 'item': item.item,\n 'quantity': item.quantity,\n 'category': item.category.category,\n 'id': item.id,\n 'user': {\n 'username': item.user.first_name\n }\n }\n\n if loop_index == 0:\n all_items_no_duplicates.append(item_dict)\n else:\n item_is_not_a_copy = True\n for list_item in all_items_no_duplicates:\n if list_item['item'] == item.item:\n item_is_not_a_copy = False\n list_item['quantity'] += item.quantity\n list_item['user']['username'] += ' / ' + item.user.first_name\n if item_is_not_a_copy:\n all_items_no_duplicates.append(item_dict)\n\n return all_items_no_duplicates","title":""},{"docid":"c3a9248edfc9e0f0a3358d588b252bd1","score":"0.4931224","text":"def batchListReNumber(oldList, numberChange, untouchedValues):\n import re\n\n newList = copy.deepcopy(oldList)\n\n ## Append'_batchX' with X the smallest original 'Batch' if none already present\n for i in range(len(newList)):\n if (newList[i] not in untouchedValues) & (newList[i].find('_batch') == -1):\n newList[i] = newList[i] + '_batch' + str(min(numberChange.keys()))\n\n ## Update X in all '_batchX' column names (look for previous batch numbers and replace)\n for batchNum in numberChange.keys():\n # exact match with end of string ($)\n query = '.+?(?=_batch' + str(batchNum) + '$)'\n for j in range(len(newList)):\n if newList[j] not in untouchedValues:\n # string without _batchX\n searchRes = re.search(query, newList[j]) # if no match returns None\n if searchRes:\n newList[j] = searchRes.group() + '_batch' + str(numberChange[batchNum])\n\n return newList","title":""},{"docid":"ce56708f97339c7d4a1da6439468eded","score":"0.4925782","text":"def put(self, key, item):\n if key is None or item is None:\n return\n if key in self.key_tracker.keys():\n self.key_tracker.pop(key)\n if len(self.key_tracker) >= BaseCaching.MAX_ITEMS:\n x = self.most_recent_use_key()\n print(\"DISCARD: {}\".format(x))\n self.key_tracker.pop(x)\n self.cache_data.pop(x)\n self.cache_data.update({key: item})\n self.key_tracker.update({key: self.count})\n self.count += 1","title":""},{"docid":"34dec93b3a8a58d181cae4a79482b051","score":"0.4925122","text":"def transform(self):\n\n transactions = self._get_transactions(self._x_transformed)\n self.frequent_items = [set(item) for item in find_frequent_itemsets(\n transactions, minimum_support=self.support_min) if len(item) > 1]\n return self.frequent_items","title":""},{"docid":"466edc1eb51eb08207a6fda46faf4b81","score":"0.49242643","text":"def test_unsized(self):\n cache = FIFOCache()\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","title":""},{"docid":"218620dd2e34e606cff1fc47df6e4d5f","score":"0.49182576","text":"def recache_matches(self):\n matches = (Match.objects\n .filter(Q(winner = self) | Q(loser = self))\n .order_by('-played_time'))[:CACHED_RATING_LIMIT]\n matches = list(matches)\n matches.reverse()\n\n for match in matches:\n self.add_match(match, include_rank=True)\n\n self.save()","title":""},{"docid":"e2bf8a8a350c7fdef133d9654844f1f4","score":"0.4914266","text":"def dedupe_list(input):\n return list(set(input))","title":""},{"docid":"11131adb29b2611b8a23b0d18fcc2938","score":"0.4905418","text":"def clone(self):\n clone = super(LongObjectHashMap, self).clone()\n clone.clear()\n clone.initialize()\n for key in keySet():\n value = self.get(key)\n clone.put(key, value)\n return clone","title":""},{"docid":"9c5be1e283d19a5418f64bf679f2d77a","score":"0.48961446","text":"def remap_ids(self, id_map: Dict[int, int]) -> None:","title":""},{"docid":"58964a17a6901bdd1d37d5b11ca713d7","score":"0.4895037","text":"def uniq(seq, idfun=None):\n\n if idfun is None:\n def idfun(x): return x\n\n seen = {}\n result = []\n\n for item in seq:\n marker = idfun(item)\n if marker in seen: continue\n seen[marker] = 1\n result.append(item)\n return result","title":""},{"docid":"fa37fb1e9c6b2adb33919384bb1fe233","score":"0.48905498","text":"def removeDups(lst):\n\n return list(dict.fromkeys(lst) )","title":""},{"docid":"575fe653444d834d0a8ff1e8d5032ca0","score":"0.488914","text":"def distinct(self):\n memory = set()\n\n def _distinct(iterator):\n while True:\n item = next(iterator)\n if item in memory:\n continue\n memory.add(item)\n return item\n return self.__class__(self, _distinct)","title":""},{"docid":"da853c2a8fa9a853613cd06bd71021c7","score":"0.48863533","text":"def get_ids(self):\n return [item.id for item in self.items]","title":""},{"docid":"4e18e44efa58bc99dfc299a10a6e15d4","score":"0.4885305","text":"def new(self, name=None):\n if not hasattr(self, 'caches'):\n self.caches = []\n thisCache = deque()\n self.caches.append(thisCache)\n k = len(self.caches) - 1\n if name is None:\n name = str(k)\n self.names.append(name)\n return k","title":""},{"docid":"09da322c4f02ec42b23cd82e968aef0d","score":"0.4883666","text":"def unique(list_: List) -> List:\n return list(collections.OrderedDict.fromkeys(list_))","title":""},{"docid":"d95eb948e044afcfc507c664ed7956e1","score":"0.4881793","text":"def rescan(self):\n self.__artists = {}\n self.__artists_by_name = {}\n self.__albums = {}\n self.__tracks = {}\n self.__playlists = {}\n self.__populate_library()","title":""},{"docid":"872baf49f2d4293229cffd1f8c805ebb","score":"0.48815057","text":"def rehash(self, new_len):\n print(\"!!!!!!!!!Rehash\")\n oldtable = self.table\n self.table = [set() for x in range(new_len)]\n for numberset in oldtable:\n for number in numberset:\n self.insert(number)\n\n print(\"Rehash-table-print\")\n print(self.table)","title":""},{"docid":"09d5dc2021d377a0faa58508ba07dc66","score":"0.48813647","text":"def update(self, items: Mapping[Any, Any]) -> None:\n self.extend(list(items.values()))\n return","title":""}],"string":"[\n {\n \"docid\": \"04f3496398ff04367f08c593ebc8f7c4\",\n \"score\": \"0.71066976\",\n \"text\": \"def _unpack_items(self):\\n\\n # Prevent the unpack operation from occurring more than once.\\n if hasattr(self, '_unpack'):\\n delattr(self, '_unpack')\\n else:\\n return\\n\\n # The list contains identifiers that will be unpacked into real items.\\n # Copy them so they won't be lost when the list values are altered.\\n identifiers = self[:]\\n\\n cache_keys = dict(izip(identifiers, self.make_cache_keys(identifiers)))\\n cached_items = self.cache_backend.get_many(cache_keys.values())\\n\\n items = {}\\n missed = []\\n for identifier, cache_key in cache_keys.items():\\n try:\\n item = cached_items[cache_key]\\n assert item is not None\\n except (AssertionError, KeyError):\\n missed.append(identifier)\\n else:\\n items[identifier] = item\\n\\n if missed:\\n\\n # Rebuild the missing items using their identifiers and\\n # replace the contents of this list with those new items.\\n self[:] = self.rebuild_items(missed)\\n\\n # Use the pack_items method to add them to the cache and also\\n # get back their identifiers. Finally, put the new items into\\n # the items dict to be returned at the end.\\n found_identifiers = self._pack_items()\\n items.update(izip(found_identifiers, self))\\n\\n # Replace the value of this list with the final result.\\n del self[:]\\n for identifier in identifiers:\\n item = items.get(identifier)\\n if item is not None:\\n self.append(item)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fd95c30102e1eb9b54c5b5913727ada8\",\n \"score\": \"0.65366846\",\n \"text\": \"def rebuild_items(self, identifiers):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"89d5610230e58fa085046f10e4c06c5f\",\n \"score\": \"0.6319896\",\n \"text\": \"def UpdateIds(self):\\r\\n removed = set(self.item_itemId.keys()) - set(self.data.keys())\\r\\n for item in removed:\\r\\n itemId = self.item_itemId[item]\\r\\n del self.item_itemId[item]\\r\\n del self.itemId_item[itemId]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8aac78c071b4804a50c8441963bb9100\",\n \"score\": \"0.6208331\",\n \"text\": \"def __reduce__(self):\\n init_args = (\\n self.__class__,\\n self._pack_items(),\\n )\\n if self.cache_timeout:\\n init_kwargs = {'cache_timeout': self.cache_timeout}\\n else:\\n init_kwargs = {}\\n return (_unpickle_cached_list, init_args, init_kwargs)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"719aae5ffbb29c6b379af986fa5e37a5\",\n \"score\": \"0.61230433\",\n \"text\": \"def learn_ids(self, item_list):\\n self._reset_sequence()\\n for item in item_list:\\n key = self.nondup_key_for_item(item)\\n self.ids[key] = item[self.id_key]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"405476beaecdf6d402cdcc71a0f9e9f5\",\n \"score\": \"0.6076083\",\n \"text\": \"def set_ids(self, item_list):\\n self._reset_sequence()\\n for item in item_list:\\n key = self.nondup_key_for_item(item)\\n item[self.id_key] = self.ids.get(key) or self._get_next_id()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"70624459dc155a8c7515bf792e28e123\",\n \"score\": \"0.5991048\",\n \"text\": \"def fillCache(self):\\n items = self.source.getRecent()\\n items.reverse() # make sure the most recent ones are added last to the cache\\n for item in items:\\n self.cache.append(item.title)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0029a129d6ea9529f86fea0bf93e576f\",\n \"score\": \"0.5884281\",\n \"text\": \"def rehash(self):\\n old = list()\\n # use iteration to record existing items\\n for i in range(self.capacity // 2):\\n if self.table[i] is not None:\\n old.append(self.table[i])\\n self.table = self.capacity * [None] # then reset table to desired capacity\\n self.size = 0\\n for i in old:\\n index = self.quadratic_probe(i.key)\\n self.table[index] = i\\n self.size += 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d4a8cd859e3895cb5b72bb40991911e7\",\n \"score\": \"0.58541334\",\n \"text\": \"def testRemovingDuplicates(self):\\n\\n item1 = {KEY: 'one', 'name': 'foo'}\\n item2 = {KEY: 'two', 'name': 'bar'}\\n item3 = {KEY: 'three', 'name': 'baz'}\\n dup_item1 = {KEY: 'one', 'name': 'foo'}\\n dup_item2 = {KEY: 'two', 'name': 'qux'}\\n\\n list_with_duplicates = [item1, item2, item3, dup_item1, dup_item2]\\n # duplicate items should not be present in the cached list\\n expected_list = [item1, item2, item3]\\n\\n cached_list_logic.setCacheItems('test_list', list_with_duplicates)\\n cached_list = cached_list_model.CachedList.get_by_id('test_list')\\n self.assertListEqual(cached_list.list_data, expected_list)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ec79bf68b3cc9ade46e621262956863b\",\n \"score\": \"0.5630425\",\n \"text\": \"def remove_duplicates_in_items(items: list, id_key: str) -> list:\\n ids = {}\\n new_items = []\\n for item in items:\\n item_id = item.get(id_key)\\n if item_id not in ids:\\n ids[item_id] = True\\n new_items.append(item)\\n\\n return new_items\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2cf41babfc15555765cec21ea4efcf47\",\n \"score\": \"0.5608932\",\n \"text\": \"def Deduplicate(items):\\n seen = set()\\n for it in items:\\n if it not in seen:\\n seen.add(it)\\n yield it\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6b3f058576245b08a98c4e29c0dbfd46\",\n \"score\": \"0.5596204\",\n \"text\": \"def _hashed_items(self):\\n return self\",\n \"title\": \"\"\n },\n {\n \"docid\": \"362eebce24f40328b63fa390e70c0c79\",\n \"score\": \"0.55942404\",\n \"text\": \"def _reset_track_lst(self):\\n del self._track_item\\n self._track_item = {key : [] for key in self._track_lst}\\n return self._track_item\",\n \"title\": \"\"\n },\n {\n \"docid\": \"700cb8953104865f413da2221aa61eb3\",\n \"score\": \"0.55431926\",\n \"text\": \"def OldItems(self) -> _n_1_t_7:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9cf9511193f5fcbf4050f362f6a20828\",\n \"score\": \"0.55386627\",\n \"text\": \"def collate(items):\\n # return batch items as a list\\n return items\",\n \"title\": \"\"\n },\n {\n \"docid\": \"981de5cb377c8c0713c7fdd006f2296d\",\n \"score\": \"0.5511309\",\n \"text\": \"def _cache(item_label, item_list):\\n id_label = item_label + '_id'\\n mbid_label = item_label + '_mbid'\\n echonest_id_label = item_label + '_echonest_id'\\n items = {}\\n for item in item_list:\\n key = '/%s/%s' % (item_label, item[id_label])\\n items[key] = item\\n musicbrainz_id = item.get(mbid_label, None)\\n if musicbrainz_id:\\n items['/musicbrainz/%s/%s' % (item_label, musicbrainz_id)] = key\\n # echonest_id = item.get(echonest_id_label, None)\\n # if echonest_id:\\n # items['/echonest/%s/%s' % (item_label, echonest_id)] = key\\n application.config.get('CACHE').set_many(items)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c81a69b566689e9502235bf06ce8ab51\",\n \"score\": \"0.54834604\",\n \"text\": \"def clean_up_map(self):\\n self.items = [i for i in self.items if i.quantity != 0]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"037eb212aeb81bbc51022678d212b6c4\",\n \"score\": \"0.546661\",\n \"text\": \"def cache_all(self):\\n if not self._cached_all:\\n poss = range(len(self))\\n uuids = self.vars['uuid']\\n\\n cls_names = self.variables['cls'][:]\\n samples_idxss = self.variables['samples'][:]\\n subchanges_idxss = self.variables['subchanges'][:]\\n mover_idxs = self.variables['mover'][:]\\n details_idxs = self.variables['details'][:]\\n try:\\n input_samples_vars = self.variables['input_samples']\\n except KeyError:\\n # BACKWARD COMPATIBILITY: REMOVE IN 2.0\\n input_samples_idxss = [[] for _ in samples_idxss]\\n else:\\n input_samples_idxss = input_samples_vars[:]\\n\\n [self._add_empty_to_cache(*v) for v in zip(\\n poss,\\n uuids,\\n cls_names,\\n samples_idxss,\\n input_samples_idxss,\\n mover_idxs,\\n details_idxs)]\\n\\n [self._load_partial_subchanges(c, s) for c, s in zip(\\n self,\\n subchanges_idxss)]\\n\\n self._cached_all = True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"768778ac6290dd31ad58bda94e7f950a\",\n \"score\": \"0.5451933\",\n \"text\": \"def uniquify_list(seq, idfun=None):\\n\\n if idfun is None:\\n\\n def idfun(x):\\n return x\\n\\n seen = {}\\n result = []\\n for item in seq:\\n marker = idfun(item)\\n if marker in seen:\\n continue\\n seen[marker] = 1\\n result.append(item)\\n return result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"27056edd253e5a0fc73c653f8cf72b50\",\n \"score\": \"0.5417399\",\n \"text\": \"def concat_duplicate_ids(self) -> None:\\n # Rebuilt list instead of removing duplicated one at a time at the cost of O(n).\\n self.data.clear()\\n\\n # This implementation takes advantage of the ordering of the duplicated in the __init__ method\\n\\n has_external_ids = set()\\n for ext_id, items in self._external_id_to_item.items():\\n if not isinstance(items, list):\\n self.data.append(items)\\n if items.id is not None:\\n has_external_ids.add(items.id)\\n continue\\n concatenated = DatapointsArray.create_from_arrays(*items)\\n self._external_id_to_item[ext_id] = concatenated\\n if concatenated.id is not None:\\n has_external_ids.add(concatenated.id)\\n self._id_to_item[concatenated.id] = concatenated\\n self.data.append(concatenated)\\n\\n if not (only_ids := set(self._id_to_item) - has_external_ids):\\n return\\n\\n for id_, items in self._id_to_item.items():\\n if id_ not in only_ids:\\n continue\\n if not isinstance(items, list):\\n self.data.append(items)\\n continue\\n concatenated = DatapointsArray.create_from_arrays(*items)\\n self._id_to_item[id_] = concatenated\\n self.data.append(concatenated)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0f465738f7d88199fb3e96d16f08925f\",\n \"score\": \"0.54072\",\n \"text\": \"def unique_residue_ids(self): \\n # Convenience abbreviations.\\n identifiers = self.identifiers\\n res_ids = self.res_ids\\n res_cnt = self.res_cnt \\n # Preparing the list of unique residue identifiers.\\n # In the end it should be: res_cnt == len(res_ids)-1.\\n # The 'elif' line is controlling that only unique\\n # identifiers are collected.\\n for identifier in identifiers:\\n if len(res_ids) == 0:\\n # Require 'deepcopy', otherwise constant change\\n # of 'res_ids[res_cnt]' with 'identifier'.\\n res_ids.append(deepcopy(identifier))\\n elif identifier[1] == res_ids[res_cnt][1]: \\n pass\\n else:\\n res_ids.append(deepcopy(identifier))\\n res_cnt += 1 \\n # Return assignments to object scope.\\n self.res_ids = res_ids\\n self.res_cnt = res_cnt\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7887abe496fd6fd9c547ffe44eb6ee68\",\n \"score\": \"0.5397846\",\n \"text\": \"def _expand_priority_order(self, id_list):\\n res = self.id_priority_list.copy()\\n for key in id_list:\\n if key not in self.id_priority_list:\\n res.append(key)\\n return res\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f9d0ec9d39cfb94b73770923cc6880f8\",\n \"score\": \"0.5388973\",\n \"text\": \"def compactify(self):\\n logger.debug(\\\"rebuilding dictionary, shrinking gaps\\\")\\n\\n # build mapping from old id -> new id\\n idmap = dict(zip(sorted(itervalues(self.token2id)), range(len(self.token2id))))\\n\\n # reassign mappings to new ids\\n self.token2id = {token: idmap[tokenid] for token, tokenid in iteritems(self.token2id)}\\n self.id2token = {}\\n self.dfs = {idmap[tokenid]: freq for tokenid, freq in iteritems(self.dfs)}\",\n \"title\": \"\"\n },\n {\n \"docid\": \"15cd6d40f564fe8f6db34d783ab295c7\",\n \"score\": \"0.5363779\",\n \"text\": \"def _update_unused(self, key):\\n try:\\n item_list = self.parent.dataset[key]\\n max_id = max(item['id'] for item in item_list) if item_list else 0\\n next_id = max(max_id + 1, len(item_list))\\n except KeyError:\\n # The table doesn't exist, so we can use anything\\n next_id = 1\\n self.unused[key] = next_id\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3a081b6d2f5907a4cca610f268f2754f\",\n \"score\": \"0.53463596\",\n \"text\": \"def reset(self):\\n for i in range(self.k):\\n self.list[i] = self.dic[i]\\n return self.list\",\n \"title\": \"\"\n },\n {\n \"docid\": \"52319bc27440f01d24b5f7f7d990c9bc\",\n \"score\": \"0.5338179\",\n \"text\": \"def update(self):\\r\\n self.data = [self.make_item_tuple(i) for i in self.query]\\r\\n self._fetched = True\\r\\n query_cache.set(self.iden, self.data)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4426012ea6e97d7223fbe4ca71c77f83\",\n \"score\": \"0.5335431\",\n \"text\": \"def make_cache_keys(self, identifiers):\\n\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d0455dbf0a4c0f80171edacef755f2b3\",\n \"score\": \"0.5325638\",\n \"text\": \"def _unpickle_cached_list(cls, *args, **kwargs):\\n new_list = cls(*args, **kwargs)\\n new_list._unpack = True\\n return new_list\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3d0878b3d86025381140c859c9f882f7\",\n \"score\": \"0.53181565\",\n \"text\": \"def remove_duplicates(data):\\n already_used_items = {}\\n return_data = []\\n\\n for item in data:\\n # Yes, I know that I can find used items in the return_data,\\n # but HW requires this logic.\\n if not already_used_items.get(item):\\n return_data.append(item)\\n already_used_items[item] = True\\n\\n return return_data\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6da9f8f02ea1dab3c752f7bc1f152e37\",\n \"score\": \"0.52880013\",\n \"text\": \"def _increase_size(self) -> None:\\n keys_vals_to_move = [item for item in self.HashMap if item]\\n self.length = 0\\n self.capacity = self.capacity * 2\\n self.HashMap = [None] * self.capacity\\n for item in keys_vals_to_move:\\n while len(item) > 0:\\n self.add(item[0], item[1])\\n item.pop(0)\\n item.pop(0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"75e5962c6bb6e899a567f9886a797905\",\n \"score\": \"0.5285236\",\n \"text\": \"def GetItemsFromIterablesCached(self):\\n items = []\\n assert len(self.state_id) == len(self.iterables)\\n for iter_num, iter_counter in enumerate(self.state_id):\\n item = self.history_items[iter_num].get(iter_counter+1, \\\"unexplored\\\")\\n if item == \\\"unexplored\\\":\\n try:\\n item = self.iterables[iter_num].next()\\n except StopIteration:\\n item = None\\n self.history_items[iter_num][iter_counter+1] = item\\n items.append(item)\\n return items\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ce8347208ee33e6fd2c938f0509aedf1\",\n \"score\": \"0.52832246\",\n \"text\": \"def clear_cache(self):\\n ida_strlist.clear_strlist()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0a6692985258457ba9a782cf0a6d9198\",\n \"score\": \"0.5281415\",\n \"text\": \"def remove_duplicates_for_fetch(items: list, last_fetched_ids: list) -> list:\\n return [\\n item\\n for item in items\\n if item.get('id') and item.get('id') not in last_fetched_ids\\n ]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"21583c27bcaf64ae76a948825eacbf04\",\n \"score\": \"0.52663577\",\n \"text\": \"def fill_from_cache(self):\\n move_count = min(\\n len(self._replacement_cache),\\n constants.K - len(self._contacts)\\n )\\n\\n for _ in range(move_count):\\n self.add_contact(self._replacement_cache.pop())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9fdcda24368d43c68d039a458ccd6446\",\n \"score\": \"0.52637416\",\n \"text\": \"def large_train_collection(train_items: List[JSONDict]) -> TrainCollection:\\n items = []\\n\\n item = train_items[0]\\n for i in range(3000):\\n copy = item.copy()\\n copy[\\\"url\\\"] = copy[\\\"url\\\"].replace(\\\"post1\\\", f\\\"post{i}\\\")\\n items.append(copy)\\n\\n collection = TrainCollection(items=items)\\n return collection\",\n \"title\": \"\"\n },\n {\n \"docid\": \"990715882cbcb3b4c793a97c0ee772f0\",\n \"score\": \"0.5230081\",\n \"text\": \"def clear_flush_lists(self, keys):\\r\\n cache.delete_many(keys)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a61766dec7c0c946a54fcb5b1631ac45\",\n \"score\": \"0.5229862\",\n \"text\": \"def trim_items(self, items):\\r\\n\\t\\tlogger.debug(\\\"Enter\\\")\\r\\n\\t\\t\\r\\n\\t\\tif self.transactions:\\r\\n\\t\\t\\tall_items = set.union(*[self.transactions[u][-1] for u in self.transactions.keys()])\\r\\n\\t\\telse:\\r\\n\\t\\t\\treturn items\\r\\n\\t\\t\\t\\r\\n\\t\\ttmp = items.copy()\\r\\n\\t\\t\\r\\n\\t\\tfor i in items:\\r\\n\\t\\t\\tif i in all_items:\\r\\n\\t\\t\\t\\tlogger.debug(\\\"Removing %r\\\" % i)\\r\\n\\t\\t\\t\\ttmp.remove(i)\\r\\n\\t\\t\\t\\t\\r\\n\\t\\tlogger.debug(\\\"Exit\\\")\\r\\n\\t\\treturn tmp\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e315ec3a484517b576a5a8b4eb6c6880\",\n \"score\": \"0.52169263\",\n \"text\": \"def evict_or_add (self, item):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c7a06bcf5829018a8e58a369e038a602\",\n \"score\": \"0.521555\",\n \"text\": \"def cache_db_items(self, key, items, item_key='id'):\\n db_items = self._extension_data['db_items'].setdefault(key, {})\\n for item in items:\\n db_items[item[item_key]] = item\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e02d6bcaaa4b546441050e042af93801\",\n \"score\": \"0.52053124\",\n \"text\": \"def untie_everything(self):\\r\\n self.tied_indices = []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"80a4055d21c6dd78745d80ec67cba51e\",\n \"score\": \"0.5204175\",\n \"text\": \"def remove_duplicate_items(cls, items_in, prior_batch_ids):\\n items_out = []\\n item_ids = set(prior_batch_ids)\\n for item in items_in:\\n if item[\\\"id\\\"] not in item_ids:\\n item_ids.add(item[\\\"id\\\"])\\n items_out.append(item)\\n else:\\n continue\\n return items_out\",\n \"title\": \"\"\n },\n {\n \"docid\": \"27b93b9260cc5dce0097053577cd0ac5\",\n \"score\": \"0.51884717\",\n \"text\": \"def delete_duplicate(x):\\n return list(dict.fromkeys(x))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"914725600bf52a10842be4db18e10034\",\n \"score\": \"0.5184313\",\n \"text\": \"def prune(self): # HashMap.prune\\n for hashval, list in self.contentHash.iteritems():\\n newlist=[]\\n for entry in list:\\n if not entry.deleted:\\n newlist.append(entry)\\n self.contentHash[hashval]=newlist\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8489e3ee6eb773ff17078793c717ffd4\",\n \"score\": \"0.51667583\",\n \"text\": \"def _fillcache(self, n: int | None) -> None:\\n if not n:\\n n = 1\\n try:\\n while len(self._cache) < n:\\n self._cache.append(self.modifier(next(self._iterable))) # type: ignore\\n except StopIteration:\\n while len(self._cache) < n:\\n self._cache.append(self.sentinel)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"312868e6563227ce5e3cbfe5a72b841e\",\n \"score\": \"0.5164763\",\n \"text\": \"def remove_duplicates(input_list):\\n return list(dict.fromkeys(input_list))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"681a06ca9b01daaf8a4dd09169de8563\",\n \"score\": \"0.5159341\",\n \"text\": \"def _change_objs_to_IDs(self):\\n if self.location:\\n self.location = self.location.id\\n if self.contents:\\n self.contents = [obj.id for obj in self.contents]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"59ee1707485a948778f73bcfd255ec48\",\n \"score\": \"0.51530373\",\n \"text\": \"def _hash(self, item):\\r\\n pass # TODO\\r\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f012f5379aad31fe74cd1eae0b390801\",\n \"score\": \"0.51485205\",\n \"text\": \"def _shrink(self):\\n self.capacity = round(self.capacity / self.factor)\\n temp = [None] * self.capacity\\n for i in range(self.capacity):\\n temp[i] = self.store[i]\\n self.store = temp\",\n \"title\": \"\"\n },\n {\n \"docid\": \"98a5993a5cee476306e6864df5d4e925\",\n \"score\": \"0.51277685\",\n \"text\": \"def dedupe(items):\\n seen = set()\\n for item in items:\\n if item not in seen:\\n yield item\\n seen.add(item)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"288d9d2a080beb0d9cc12e0cc0d60fbe\",\n \"score\": \"0.5118063\",\n \"text\": \"def remove_duplicates(self):\\n names: Dict[str, int] = dict()\\n for step in self.Sequence:\\n if isinstance(step, Repeater):\\n continue\\n name = step.Name\\n if name != '':\\n if name not in names:\\n names[name] = 1\\n else:\\n names[name] += 1\\n for step in reversed(self.Sequence):\\n if isinstance(step, Repeater):\\n continue\\n name = step.Name\\n if name and (names[name] > 1):\\n names[name] -= 1\\n step.Name = name + \\\"_%i\\\" % names[name]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e42f9fdac48b633a57e1b1ed05b3313e\",\n \"score\": \"0.5107073\",\n \"text\": \"def _update_use(self, key):\\n\\t\\tif (self._replace_pol == Cache.LRU):\\n\\t\\t\\tself.cache[key]= self.hashmap[key]\\n\\t\\tif (self._replace_pol == Cache.LRU_S):\\n\\t\\t\\tself.cache[key] = self.hashmap[key]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"066452b6998349caf8cfe8c6554ca6f7\",\n \"score\": \"0.51054615\",\n \"text\": \"def removeOldItems(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0fbe1bb26e47641f1f92e3af341696b8\",\n \"score\": \"0.51044595\",\n \"text\": \"def shuffled_data_reset(self):\\n self.unique_data = {}\\n for stock in self.stocks:\\n self.unique_data[stock] = []\\n for date in self.dates:\\n self.unique_data[stock] += [date]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1261f1cd1f279cb3ea82516fa1d986fb\",\n \"score\": \"0.5082867\",\n \"text\": \"def hash_fieldlist(cls):\\n for field in cls.fieldlist:\\n cls.fieldhash[field.id] = field\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aa1760328e5c1293629bd24921c1bcbf\",\n \"score\": \"0.5079646\",\n \"text\": \"def mixed_train_items(train_items: List[JSONDict]) -> List[JSONDict]:\\n train_items[1][\\\"categoryid\\\"] = 9107252648\\n return train_items\",\n \"title\": \"\"\n },\n {\n \"docid\": \"707f627a09c9f7f6a0e572774bb508e5\",\n \"score\": \"0.50749475\",\n \"text\": \"def __init__(self):\\n self.items = []\\n self.indexes: Dict[int, Set] = defaultdict(set)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5cce20cbf558401cc8c1d179de3b56b6\",\n \"score\": \"0.5070577\",\n \"text\": \"def deduped(items):\\n \\n return list(set(items))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cfe0fac80127b37b024e0b8dad1328c3\",\n \"score\": \"0.506829\",\n \"text\": \"def reap():\\n\\n # This might be more efficient by paginating manually and do memcache.get_multi\\n for counter in get_all_counters():\\n value = memcache.get(counter.key.string_id(), namespace=NAMESPACE)\\n # if value is None:\\n # continue\\n _increment_db(counter, value)\\n memcache.decr(counter.key.string_id(), value, namespace=NAMESPACE)\\n print 'memcache: %s => %s' % (counter.key.string_id(), memcache.get(counter.key.string_id(), namespace=NAMESPACE))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"64a232a9c4b886445179f8217d1dbe63\",\n \"score\": \"0.5066847\",\n \"text\": \"def __init__(self):\\n self.ids_seen = set()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"37a39cdbeeb3e27bcc1fb4eb342d6fa1\",\n \"score\": \"0.506516\",\n \"text\": \"def potentials(self, potential_list):\\n for item in potential_list:\\n item.store()\\n potential_list_uuids = [item.uuid for item in potential_list]\\n self.set_attribute('potentials', potential_list_uuids)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"105ce627edef9178252460b3bdf9e8c1\",\n \"score\": \"0.5062378\",\n \"text\": \"def map_items(self) -> None:\\n self.__attribute_columns = list(self.__DataFrame.columns)\\n self.__attribute_columns.remove(self.__surv_col_name)\\n self.__attribute_columns.remove(self.__status_col_name)\\n\\n mapped_int = 0\\n\\n for attribute in self.__attribute_columns:\\n for value in self.__DataFrame[attribute].unique():\\n item_reference = (attribute, value)\\n self.__item_map[item_reference] = mapped_int\\n self.items_list.append(item_reference)\\n mapped_int += 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d1358b98e41139369442a74ad2a3db1d\",\n \"score\": \"0.5051759\",\n \"text\": \"def expand_id_map(id_map, all_ids):\\n\\n unmapped_ids = list(set(all_ids).difference(id_map.keys()))\\n\\n for i in unmapped_ids:\\n id_map[i] = i\\n\\n return id_map\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b1668ee6e1df57e8925590d2e042e93e\",\n \"score\": \"0.50455356\",\n \"text\": \"def rehash(self):\\n new_cap = self._get_new_capacity() # Choose not to handle the ValueError thrown by _get_new_capacity()\\n new_table = HashTable(new_cap) # Create a new hash table directly\\n for i in range(self.size):\\n if self.keys[i] is not None: # Only put() when there exists a key (no Nones)\\n new_table[self.keys[i]] = self.values[i] # Rehash and insert into the new table\\n\\n self.keys = new_table.keys # Update instance variables\\n self.values = new_table.values\\n self.size = new_cap # Update N\\n self.count_rehashes += 1 # Increment total rehashes\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e3d60e32e91c980445d6d1e66f08977e\",\n \"score\": \"0.5032233\",\n \"text\": \"def __fillCache(self):\\n assert (not self.__modelCache)\\n\\n # Assemble a list of model IDs to look up\\n numModelIDs = len(self.__modelIDs) if self.__modelIDs else 0\\n\\n if self.__nextIndex >= numModelIDs:\\n return\\n\\n idRange = self.__nextIndex + self.__CACHE_LIMIT\\n if idRange > numModelIDs:\\n idRange = numModelIDs\\n\\n lookupIDs = self.__modelIDs[self.__nextIndex:idRange]\\n\\n self.__nextIndex += (idRange - self.__nextIndex)\\n\\n # Query Nupic for model info of all models in the look-up list\\n # NOTE: the order of results may not be the same as lookupIDs\\n infoList = _clientJobsDB().modelsInfo(lookupIDs)\\n assert len(infoList) == len(lookupIDs), \\\\\\n \\\"modelsInfo returned %s elements; expected %s.\\\" % \\\\\\n (len(infoList), len(lookupIDs))\\n\\n # Create _NupicModelInfo instances and add them to cache\\n for rawInfo in infoList:\\n modelInfo = _NupicModelInfo(rawInfo=rawInfo)\\n self.__modelCache.append(modelInfo)\\n\\n assert len(self.__modelCache) == len(lookupIDs), \\\\\\n \\\"Added %s elements to modelCache; expected %s.\\\" % \\\\\\n (len(self.__modelCache), len(lookupIDs))\\n\\n if self.debug:\\n _emit(Verbosity.DEBUG,\\n \\\"MODELITERATOR: Leaving __fillCache(); modelCacheLen=%s\\\" % \\\\\\n (len(self.__modelCache),))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f774b8e5bed3aa9569453565162825db\",\n \"score\": \"0.50301826\",\n \"text\": \"def _remove_duplicates(input_list):\\n return list(OrderedDict.fromkeys(input_list))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c2b2f4395e0c3820a7e3587e355598ae\",\n \"score\": \"0.50289893\",\n \"text\": \"def mapper_get_items_init(self):\\n if int(self.options.iteration) > 1:\\n with open(self.options.f, 'r') as fh:\\n self.frequent_items = set(fh.read().splitlines())\\n else:\\n self.frequent_items = {}\",\n \"title\": \"\"\n },\n {\n \"docid\": \"867ffc91a746827266f061a3c0ae9897\",\n \"score\": \"0.50242746\",\n \"text\": \"def test_unsized(self):\\n cache = LRUCache()\\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\",\n \"title\": \"\"\n },\n {\n \"docid\": \"89ed3790f153ec8739030c451e4af4c3\",\n \"score\": \"0.50208384\",\n \"text\": \"def _fillcache(self, n: int | None) -> None:\\n if not n:\\n n = 1\\n try:\\n while len(self._cache) < n:\\n self._cache.append(next(self._iterable)) # type: ignore\\n except StopIteration:\\n while len(self._cache) < n:\\n self._cache.append(self.sentinel)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"084dc13ea4b269548970835742e2e48d\",\n \"score\": \"0.501621\",\n \"text\": \"def add(self, item):\\n self.update(set([item]))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"761ac9d24d795bc18846babfe10ea551\",\n \"score\": \"0.50095797\",\n \"text\": \"def removeDuplicatesInList(self, data):\\n newDataList = []\\n for i in data:\\n if newDataList.count(i) == 0:\\n newDataList.append(i)\\n data.clear()\\n data += newDataList\",\n \"title\": \"\"\n },\n {\n \"docid\": \"89e4d0319dfeac13114d90db0bfe8255\",\n \"score\": \"0.5009236\",\n \"text\": \"def duplicate_train_items(train_items: List[JSONDict]) -> List[JSONDict]:\\n train_items[1][\\\"url\\\"] = train_items[0][\\\"url\\\"]\\n return train_items\",\n \"title\": \"\"\n },\n {\n \"docid\": \"66f4c343d416d8f4427b63c0ab29a170\",\n \"score\": \"0.50060844\",\n \"text\": \"def item2id(self):\\n if self._item2id is None:\\n self._item2id = dict(zip(self.item_unique_vals, range(self.n_items)))\\n return self._item2id\",\n \"title\": \"\"\n },\n {\n \"docid\": \"27a87ab4211569e026551ad5c47e9c81\",\n \"score\": \"0.5004679\",\n \"text\": \"def customized_retained_list(self, base_day, day_list=[]):\\n auBitmap = self.make_bitmap(base_day, 'dau')\\n return [(base_day, auBitmap.count())] + \\\\\\n zip(day_list, self._retained_value(base_day, day_list, 'dau'))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f03f7c7b4a76609a03dd5702e72a26b7\",\n \"score\": \"0.4989525\",\n \"text\": \"def evict_purged(self, entity_ids: Iterable[str]) -> None:\\n for entity_id in entity_ids:\\n self._id_map.pop(entity_id, None)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ad5c6f1d98a8bd7ccf01f8feb7706eed\",\n \"score\": \"0.4983754\",\n \"text\": \"def all_reduce(self):\\n return {k: reduce_number(v) for k, v in self.items()}\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f52c5d3224a282b90a85cc7d9a214ff1\",\n \"score\": \"0.49834982\",\n \"text\": \"def purify(l):\\n return set([item.replace('B-', '').replace('I-', '') for item in l])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c8ace0f1a644421dec91924729cb3207\",\n \"score\": \"0.4974587\",\n \"text\": \"def remove_duplicate_urls(seq, id_fun=None):\\n\\n if id_fun is None:\\n def id_fun(x):\\n return x\\n seen = {}\\n result = []\\n for item in seq:\\n marker = id_fun(item)\\n if marker in seen:\\n continue\\n seen[marker] = 1\\n result.append(item)\\n\\n return result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c33aaffbadb012dec2a4c4231ab05208\",\n \"score\": \"0.49692756\",\n \"text\": \"def setA(cls,*items):\\n cls.A = sympy.FiniteSet(*items)\\n cls.id2items= {}\\n num = 0\\n for i in cls.A:\\n cls.id2items[num] = i\\n num = num + 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"264b7a9220432c6e5decdcd8d48cbb3a\",\n \"score\": \"0.4964221\",\n \"text\": \"def dedupe(self):\\n elems = []\\n for x in self.elems:\\n if x not in elems:\\n elems.append(x)\\n return _coconut_tail_call(self.__class__, *elems)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"57508bd0a67b85f81e74c3eeb789319b\",\n \"score\": \"0.49561846\",\n \"text\": \"def frequentOneItem(self):\\n\\n candidate = {}\\n # global finalPatterns, minSup, Database\\n # self.minSup = self.minSup\\n for i in range(len(self.Database)):\\n for j in range(len(self.Database[i])):\\n if self.Database[i][j] not in candidate:\\n candidate[self.Database[i][j]] = [i]\\n else:\\n candidate[self.Database[i][j]] += [i]\\n self.finalPatterns = {keys: value for keys, value in candidate.items() if len(value) >= self.minSup}\\n #print(candidate)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"040beceaed5eaf9953636f961ee2c91d\",\n \"score\": \"0.4951346\",\n \"text\": \"def set_count(items):\\n item_count = {}\\n for item in items:\\n if not item: continue\\n if not item_count.has_key(item): item_count[item] = 0\\n item_count[item] += 1\\n \\n items = [(v, k) for k, v in item_count.iteritems()]\\n items.sort()\\n items.reverse()\\n \\n return [(k, v) for v, k in items]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"638c68ccc4591aaa2e1196ce95f7d4a1\",\n \"score\": \"0.4945082\",\n \"text\": \"def __init__(self):\\n \\n self.items = [] \\n self.ind = defaultdict(set) # item -> index into the items array\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ff689f32092e5d3a998c3112f1318c1b\",\n \"score\": \"0.49444813\",\n \"text\": \"def add_items_quantity_not_duplicates(request):\\n all_items_no_duplicates = []\\n\\n for loop_index, item in enumerate(all_shopping_items(request)):\\n item_dict = {\\n 'item': item.item,\\n 'quantity': item.quantity,\\n 'category': item.category.category,\\n 'id': item.id,\\n 'user': {\\n 'username': item.user.first_name\\n }\\n }\\n\\n if loop_index == 0:\\n all_items_no_duplicates.append(item_dict)\\n else:\\n item_is_not_a_copy = True\\n for list_item in all_items_no_duplicates:\\n if list_item['item'] == item.item:\\n item_is_not_a_copy = False\\n list_item['quantity'] += item.quantity\\n list_item['user']['username'] += ' / ' + item.user.first_name\\n if item_is_not_a_copy:\\n all_items_no_duplicates.append(item_dict)\\n\\n return all_items_no_duplicates\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c3a9248edfc9e0f0a3358d588b252bd1\",\n \"score\": \"0.4931224\",\n \"text\": \"def batchListReNumber(oldList, numberChange, untouchedValues):\\n import re\\n\\n newList = copy.deepcopy(oldList)\\n\\n ## Append'_batchX' with X the smallest original 'Batch' if none already present\\n for i in range(len(newList)):\\n if (newList[i] not in untouchedValues) & (newList[i].find('_batch') == -1):\\n newList[i] = newList[i] + '_batch' + str(min(numberChange.keys()))\\n\\n ## Update X in all '_batchX' column names (look for previous batch numbers and replace)\\n for batchNum in numberChange.keys():\\n # exact match with end of string ($)\\n query = '.+?(?=_batch' + str(batchNum) + '$)'\\n for j in range(len(newList)):\\n if newList[j] not in untouchedValues:\\n # string without _batchX\\n searchRes = re.search(query, newList[j]) # if no match returns None\\n if searchRes:\\n newList[j] = searchRes.group() + '_batch' + str(numberChange[batchNum])\\n\\n return newList\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ce56708f97339c7d4a1da6439468eded\",\n \"score\": \"0.4925782\",\n \"text\": \"def put(self, key, item):\\n if key is None or item is None:\\n return\\n if key in self.key_tracker.keys():\\n self.key_tracker.pop(key)\\n if len(self.key_tracker) >= BaseCaching.MAX_ITEMS:\\n x = self.most_recent_use_key()\\n print(\\\"DISCARD: {}\\\".format(x))\\n self.key_tracker.pop(x)\\n self.cache_data.pop(x)\\n self.cache_data.update({key: item})\\n self.key_tracker.update({key: self.count})\\n self.count += 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"34dec93b3a8a58d181cae4a79482b051\",\n \"score\": \"0.4925122\",\n \"text\": \"def transform(self):\\n\\n transactions = self._get_transactions(self._x_transformed)\\n self.frequent_items = [set(item) for item in find_frequent_itemsets(\\n transactions, minimum_support=self.support_min) if len(item) > 1]\\n return self.frequent_items\",\n \"title\": \"\"\n },\n {\n \"docid\": \"466edc1eb51eb08207a6fda46faf4b81\",\n \"score\": \"0.49242643\",\n \"text\": \"def test_unsized(self):\\n cache = FIFOCache()\\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\",\n \"title\": \"\"\n },\n {\n \"docid\": \"218620dd2e34e606cff1fc47df6e4d5f\",\n \"score\": \"0.49182576\",\n \"text\": \"def recache_matches(self):\\n matches = (Match.objects\\n .filter(Q(winner = self) | Q(loser = self))\\n .order_by('-played_time'))[:CACHED_RATING_LIMIT]\\n matches = list(matches)\\n matches.reverse()\\n\\n for match in matches:\\n self.add_match(match, include_rank=True)\\n\\n self.save()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e2bf8a8a350c7fdef133d9654844f1f4\",\n \"score\": \"0.4914266\",\n \"text\": \"def dedupe_list(input):\\n return list(set(input))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"11131adb29b2611b8a23b0d18fcc2938\",\n \"score\": \"0.4905418\",\n \"text\": \"def clone(self):\\n clone = super(LongObjectHashMap, self).clone()\\n clone.clear()\\n clone.initialize()\\n for key in keySet():\\n value = self.get(key)\\n clone.put(key, value)\\n return clone\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9c5be1e283d19a5418f64bf679f2d77a\",\n \"score\": \"0.48961446\",\n \"text\": \"def remap_ids(self, id_map: Dict[int, int]) -> None:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"58964a17a6901bdd1d37d5b11ca713d7\",\n \"score\": \"0.4895037\",\n \"text\": \"def uniq(seq, idfun=None):\\n\\n if idfun is None:\\n def idfun(x): return x\\n\\n seen = {}\\n result = []\\n\\n for item in seq:\\n marker = idfun(item)\\n if marker in seen: continue\\n seen[marker] = 1\\n result.append(item)\\n return result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fa37fb1e9c6b2adb33919384bb1fe233\",\n \"score\": \"0.48905498\",\n \"text\": \"def removeDups(lst):\\n\\n return list(dict.fromkeys(lst) )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"575fe653444d834d0a8ff1e8d5032ca0\",\n \"score\": \"0.488914\",\n \"text\": \"def distinct(self):\\n memory = set()\\n\\n def _distinct(iterator):\\n while True:\\n item = next(iterator)\\n if item in memory:\\n continue\\n memory.add(item)\\n return item\\n return self.__class__(self, _distinct)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"da853c2a8fa9a853613cd06bd71021c7\",\n \"score\": \"0.48863533\",\n \"text\": \"def get_ids(self):\\n return [item.id for item in self.items]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4e18e44efa58bc99dfc299a10a6e15d4\",\n \"score\": \"0.4885305\",\n \"text\": \"def new(self, name=None):\\n if not hasattr(self, 'caches'):\\n self.caches = []\\n thisCache = deque()\\n self.caches.append(thisCache)\\n k = len(self.caches) - 1\\n if name is None:\\n name = str(k)\\n self.names.append(name)\\n return k\",\n \"title\": \"\"\n },\n {\n \"docid\": \"09da322c4f02ec42b23cd82e968aef0d\",\n \"score\": \"0.4883666\",\n \"text\": \"def unique(list_: List) -> List:\\n return list(collections.OrderedDict.fromkeys(list_))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d95eb948e044afcfc507c664ed7956e1\",\n \"score\": \"0.4881793\",\n \"text\": \"def rescan(self):\\n self.__artists = {}\\n self.__artists_by_name = {}\\n self.__albums = {}\\n self.__tracks = {}\\n self.__playlists = {}\\n self.__populate_library()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"872baf49f2d4293229cffd1f8c805ebb\",\n \"score\": \"0.48815057\",\n \"text\": \"def rehash(self, new_len):\\n print(\\\"!!!!!!!!!Rehash\\\")\\n oldtable = self.table\\n self.table = [set() for x in range(new_len)]\\n for numberset in oldtable:\\n for number in numberset:\\n self.insert(number)\\n\\n print(\\\"Rehash-table-print\\\")\\n print(self.table)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"09d5dc2021d377a0faa58508ba07dc66\",\n \"score\": \"0.48813647\",\n \"text\": \"def update(self, items: Mapping[Any, Any]) -> None:\\n self.extend(list(items.values()))\\n return\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":393,"cells":{"query_id":{"kind":"string","value":"95246c749a7299f7107f201320e37e0a"},"query":{"kind":"string","value":"Updates the World Object Grid"},"positive_passages":{"kind":"list like","value":[{"docid":"e215fbe7a36102b1ca32dcd123523225","score":"0.7229946","text":"def update_world_object(self, Object, x, y):\n self.WOG[x][y] = Object","title":""}],"string":"[\n {\n \"docid\": \"e215fbe7a36102b1ca32dcd123523225\",\n \"score\": \"0.7229946\",\n \"text\": \"def update_world_object(self, Object, x, y):\\n self.WOG[x][y] = Object\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"ccb16c16812bbd50b00fe75b0f0a58a2","score":"0.6663007","text":"def update(self, player, obj_list):\n for obj in obj_list:\n obj.update(obj_list)\n player.update(self.map.tile_boxes)","title":""},{"docid":"4251b18b88419fdcb5c977011fe47ba1","score":"0.6646035","text":"def update_grid_pos(self):\n self.grid_pos = self.get_tile_of_position(self.tank.body.position)","title":""},{"docid":"49b7d14b764471d2f66ecf4b41ebcbb8","score":"0.6583626","text":"def update_grid(self):\r\n\t\tself.get_sim_cells()\r\n\t\t\"\"\"Two loops are used to stop early death or birth of cells.\r\n\t\tThe grid is meant to evolve as a whole each tick,\r\n\t\tand not cell-by-cell.\r\n\t\t\"\"\"\r\n\t\tfor coord in self.sim_cells:\r\n\t\t\tCell.ref_dict[coord].get_new_state()\r\n\t\tfor coord in self.sim_cells:\r\n\t\t\tCell.ref_dict[coord].update_state()\r\n\t\treturn self","title":""},{"docid":"5fc87997f91cb27a844989ed1c7d632d","score":"0.6409022","text":"def update(self):\n if self.winter_tiles:\n for i in range(len(self.winter_tiles)):\n self.winter_tiles[i].show(self.game_display)\n self.grid.show_grid(self.game_display) # Show a grid\n self.show_tile_from_matrix('road')\n\n # Sorting of the objects based on y-coordinates for correct depiction\n tmp_objects = self.sort_objects_by_draw_y()\n if tmp_objects:\n self.draw_objects(tmp_objects)\n\n self.coinMatrix.draw(self.game_display, self.grid_size)\n\n # Snowing\n self.snow.update(self.width, self.height)\n self.snow.show(self.game_display)\n\n # Save and load the game\n if self.game_state == 'Save':\n self.save_json()\n elif self.game_state == 'Load':\n self.load_json()\n self.coinMatrix.updateMatrix(self.road_matrix)\n pygame.display.update() # Update of the screen\n self.clock.tick(60)","title":""},{"docid":"e222f5ab4ad18cba94fed235fcc9199a","score":"0.6276333","text":"def update_grid(self):\n for var in self.model.variables():\n if var.name[0:1] == 'x':\n coor = int(var.name[1:])\n xCoor = (coor - 1) % self.cols\n yCoor = math.floor((coor - 1) / self.cols)\n if self.grid[yCoor][xCoor] == 0:\n self.grid[yCoor][xCoor] = \"0\"\n continue\n if var.value() == 1:\n self.grid[yCoor][xCoor] = \"x\"\n else:\n self.grid[yCoor][xCoor] = \"1\"","title":""},{"docid":"e30e397a1218d02fb472bef3ebb01a3e","score":"0.61028606","text":"def update_grid(self):\n # List of all occupied/visited cells\n all_occupied_cells = [player, grid_goal] + self.myObstacles + self.myRewards + self.visited_cells\n\n # For every coordinate on the board, check whether it is occupied by any one of the above\n # cells by comparing coordinates and x, y indices. If no cell is found, add 0 to that position\n # in the grid indicating an empty cell\n # If a cell is found, add the cell-type to the position in the grid if\n # the cell is not of \"reward\" type. If it is of reward type,\n # add its value with a 'plus' in front of it\n for coords in self.get_cell_coordinates():\n i, j = coords\n required_cell = next((cell for cell in all_occupied_cells if (cell.x, cell.y) == coords), None)\n\n if required_cell:\n self.grid[i][j] = required_cell.type if required_cell.type is not 3 else '+' + str(required_cell.value)\n else:\n self.grid[i][j] = 0","title":""},{"docid":"3244199d97f3394cef022740d39ec56c","score":"0.61010367","text":"def update(self):\n self.update_physics()\n\n for game_object in self.object_pool:\n game_object.update()","title":""},{"docid":"dc0989774ffb37aeeed717137cb5d66f","score":"0.6082684","text":"def update(self, world):\n self.draw(world)\n if self.render:\n pygame.display.update()","title":""},{"docid":"afec1254648b3c31d8c6402468258f13","score":"0.6040232","text":"def update( self):\n#\t\tGame._window.update()\n\t\tself.rect.topleft = self.pos\n\n\t\tself.setGrid(0, self.inactiveGrid())\n\t\tfor row in range( self.numRows - 1):\n\t\t\tfor col in range( self.numCols - 1):\n\t\t\t\tgameState_next = self.check_cellNeighbours(row, col)\n\t\t\t\tself.grids[ self.inactiveGrid()][row][col] = gameState_next\n\n\t\tself.activeGrid = self.inactiveGrid()","title":""},{"docid":"478325dded0df68632170ff1dbd59855","score":"0.60273534","text":"def edit_grid() :\r\n\r\n #Loading a global variable\r\n global obstacle_coords\r\n\r\n #Checking if the tile is an obstacle or a free tile\r\n if(((row, col) in obstacle_coords) == False) :\r\n #Changing background colour of button\r\n gui_elements[\"maze_grid\"][row][col].config(bg=\"red\")\r\n\r\n #Updating the list of obstructions\r\n obstacle_coords.append((row, col))\r\n\r\n else :\r\n #Changing background colour of button\r\n gui_elements[\"maze_grid\"][row][col].config(bg=\"white\")\r\n\r\n #Updating the list of obstructions\r\n obstacle_coords.remove((row, col))","title":""},{"docid":"009fb730578d942234ab8a8919effcfd","score":"0.60224444","text":"def update(self):\n p.setGravity(0, 0, -10.)\n if self.state == 0:\n for envO in self.env_objects:\n c_points = p.getClosestPoints(self.bot.p_id, envO.p_id, 0.001)\n if c_points is not None and len(c_points) > 0:\n self.state = 2\n print(\"CRASH\")\n if self.goal_pos.dist_2d(self.bot.pos) < self.config_.ROB_RADIUS * 1.5:\n print(\"GOAL\")\n self.state = 1\n self.bot.update()\n for o in self.env_objects:\n o.update()","title":""},{"docid":"4826132262c399b4321b97fce27217c0","score":"0.59522325","text":"def Update_World(mech, world):\n for func in Update_World.updaters:\n func(mech, world)\n\n update_func_world(mech, world)\n Update_RATE(mech, world)","title":""},{"docid":"f4f61fab96c39e37c01fda6b509e4a2f","score":"0.5947868","text":"def update_grid(self, grid):\n if torch.is_tensor(grid):\n grid = convert_legacy_grid(grid)\n\n if len(grid) != self.num_dims:\n raise RuntimeError(\"New grid should have the same number of dimensions as before.\")\n\n for i in range(self.num_dims):\n setattr(self, f\"grid_{i}\", grid[i])\n\n if not self.interpolation_mode:\n self.full_grid = create_data_from_grid(self.grid)\n\n self._clear_cache()\n return self","title":""},{"docid":"20856802fff123ea0dbe44d7f29254f4","score":"0.59443927","text":"def update(self):\n for mc in self.monsters:\n mc.update(self)","title":""},{"docid":"3d4ed00f8918f1ca806b65d160ee092e","score":"0.5938704","text":"def update_func_world(mech, world):\n globals().update(world)","title":""},{"docid":"9076acb5b9f1ea0370fa81f1ee58cf74","score":"0.59250045","text":"def test_update_world(self):\n world = World()\n self.assertEqual(world.time, 0)\n\n old_state = []","title":""},{"docid":"95d2971320d743db3ddea25f3cba6342","score":"0.5903083","text":"def update_map(self):\n self.generate_walls_from_markers()\n for (id,cube) in self.robot.world.light_cubes.items():\n self.update_cube(cube)\n for face in self.robot.world._faces.values():\n self.update_face(face)","title":""},{"docid":"d2e7d6494257b3418ec5ecbd454a245c","score":"0.5900022","text":"def update(self, world: World, events):\n\n is_world_updated = self.previous_world_t != world.t\n if is_world_updated:\n self.previous_world_t = world.t\n\n self._handle_events(events)\n\n self.entities = self._get_entities(world)\n\n self.selected_entity_index %= len(self.entities)\n selected_entity = self.entities[self.selected_entity_index]\n reference_entity = self.entities[self.reference_entity_index]\n self.viewer.draw(world, reference_entity, selected_entity)\n\n if is_world_updated: self.plotter.update(self.entities, reference_entity)\n self.plotter.draw(selected_entity, self.entities)\n\n pygame.display.flip()","title":""},{"docid":"9239c99658343d804abbdc9ef0570628","score":"0.588836","text":"def update(self):\n self.dirty_rects, old = [], self.dirty_rects\n self.world.tick()\n self.draw_world()\n\n self.clock.tick(FRAMERATE)\n pygame.display.update(self.dirty_rects + old)\n # print(self.world)\n print(self.world.ticks)","title":""},{"docid":"e8d1fc7dbc63dbd6bb5049043c2d121b","score":"0.58847094","text":"def updateGlobalCoords(self):\r\n self.globalCoords = [ self.localToGlobalCoords(T) for T in self.localCoords ]\r\n #print 'cx,cy,thd are', self.cx, self.cy, math.degrees(self.thr)\r\n #print 'globalCoords are', self.globalCoords\r","title":""},{"docid":"d676fd3eea594b39042ed82764c5522b","score":"0.58839756","text":"def draw_world(self):\n for row in self.world.cells:\n for cell in row:\n if not cell.static:\n self.draw_cell(cell)","title":""},{"docid":"7a3110e49ab2d94bbf724b47267bf193","score":"0.5855152","text":"def update(self):\r\n self.cell.update()\r\n self.receptor_system.update()\r\n self.glucose_system.update()\r\n self.sensor_system.update()\r\n self.protein_system.update()\r\n self.glut_system.update()","title":""},{"docid":"16a9df5df41d9c59d804de27e6a360d1","score":"0.58381873","text":"def update_objects(self):\n # Draw obstacles on the screen\n for obstacle in self._obstacles:\n obstacle.draw(self.screen)\n\n # Draw player on the screen\n self.player.draw(self.screen)\n # Draw score widget on the screen\n self.score_widget.draw(self.screen)","title":""},{"docid":"7ba79b058d64e40a68348deb6c2f8925","score":"0.5811544","text":"def update(self, couple):\n bbox = couple[1]\n if bbox.x is None or bbox.y is None:\n return\n\n new_pos = set()\n x1 = int(bbox.x // self.grid_size)\n y1 = int(bbox.y // self.grid_size)\n x2 = int((bbox.x + bbox.w) // self.grid_size)\n y2 = int((bbox.y + bbox.h) // self.grid_size)\n\n # New population set\n positions = (x1, y1), (x1, y2), (x1, y2), (x2, y2)\n for pos in positions:\n if (0 <= pos[0] <= self.num_columns\n and 0 <= pos[1] <= self.num_rows):\n new_pos.add(pos)\n\n # Remove from previous locations\n for pos in self._population.get(couple, set()) - new_pos:\n self._grid[pos[0]][pos[1]].discard(couple)\n # Add to new locations\n for pos in new_pos - self._population.get(couple, set()):\n self._grid[pos[0]][pos[1]].add(couple)\n\n # Update population\n self._population[couple] = new_pos","title":""},{"docid":"ba6dc86cad96fa6a10cd88c66211ebb6","score":"0.5792867","text":"def Update(*args):\r\n return _pynewton.World_Update(*args)","title":""},{"docid":"84aced866f490d2416d8ee5c333b0b6d","score":"0.577716","text":"def _update(self):\n self._game.update()","title":""},{"docid":"8c81d718a4c72893a0b317b5b9ce67a4","score":"0.5762038","text":"def update_obstacles(self, env_object_info):\n gui_obstacle_name_id = \\\n self.gui_obstacles_idx_to_name.index(env_object_info['name'])\n gui_obstacle_id = self.gui_obstacles_circle_idx[gui_obstacle_name_id]\n new_gui_obstacle_position = self.scale(env_object_info['position'])\n new_gui_obstacle_radius = env_object_info['radius'] * self.draw_scale\n new_gui_obstacle_points = util.get_circle_points(new_gui_obstacle_position,\n new_gui_obstacle_radius)\n self.canvas.coords(gui_obstacle_id, new_gui_obstacle_points)\n\n gui_obstacle_text_id = self.gui_obstacles_texts_idx[gui_obstacle_name_id]\n self.canvas.coords(gui_obstacle_text_id,\n new_gui_obstacle_position[0],\n new_gui_obstacle_position[1])","title":""},{"docid":"ef0934c068db0c31c84e2d3181354575","score":"0.57311904","text":"def update(self):\r\n if len(self.collbox_dict) != 0:\r\n for coll_box in self.collbox_dict.values():\r\n coll_box.x = self.x + (coll_box.width // 2) + coll_box.x_offset\r\n coll_box.y = self.y + (coll_box.height // 2) + coll_box.y_offset\r\n coll_box.left_edge = coll_box.x - (coll_box.width // 2)\r\n coll_box.right_edge = coll_box.x + (coll_box.width // 2)\r\n coll_box.top_edge = coll_box.y - (coll_box.height // 2)\r\n coll_box.bottom_edge = coll_box.y + (coll_box.height // 2)\r\n\r\n if self.sprite_dict != None:\r\n for sprite in self.sprite_dict.values():\r\n sprite.x = self.x\r\n sprite.y = self.y","title":""},{"docid":"8833f9340a225f4bf3820c523e3221ad","score":"0.57147515","text":"def update(self):\n self._coarse_grid = self._config_dict['coarse_grid']\n self._solution = self._config_dict['solution']\n BR_dict = dict()\n RTf_dict = dict()\n self._interface2dof_map = dict()\n self._global_dof_dimension = 0\n\n for problem_id, local_problem in self._local_problems_dict.items():\n BR_int_dict = dict()\n if local_problem.kernel.size == 0:\n for interface, B in local_problem.B.items():\n BR_int_dict[interface] = np.array([])\n else:\n for interface, B in local_problem.B.items():\n BR_int_dict[interface] = B @ local_problem.kernel\n BR_dict[problem_id] = BR_int_dict\n if local_problem.kernel.size == 0:\n RTf_dict[problem_id] = np.array([])\n else:\n RTf_dict[problem_id] = np.asarray(local_problem.kernel.T @ local_problem.f).flatten()\n for interface, B in local_problem.B.items():\n if interface not in self._interface2dof_map:\n new_global_dof_dimension = self._global_dof_dimension + B.shape[0]\n self._interface2dof_map[interface] = np.arange(self._global_dof_dimension, new_global_dof_dimension)\n self._global_dof_dimension = new_global_dof_dimension\n\n self._coarse_grid.update(BR_dict, RTf_dict, self._interfacedict2vector)","title":""},{"docid":"7737ad53c94eaf262fc7531d4dd0bcab","score":"0.5705845","text":"def update_individual_spatial(self, population, row, col):\n\t\tNam = population[1][row][col]\n\t\tNim = population[2][row][col]\n\t\tpopulation[1][row][col], population[2][row][col] = self.mutate_individual(Nam, Nim)\n\t\tpopulation[0][row][col] = self.compute_r(population[1][row][col], population[2][row][col])\n\t\treturn(population)","title":""},{"docid":"c5b490707e9d67dad989d77d605cfca8","score":"0.568819","text":"def update_square(self, location):\n x, y, z = location\n terrainNode = self.grid.get_node_at(location)\n if terrainNode is not None:\n rect = pygame.Rect(x, y, 1, 1)\n terrainNode.contents.render(rect, self.surface)","title":""},{"docid":"f5e0bcbb560c321a9c2c3c06b97242f7","score":"0.56843","text":"def update(self):\n self.OH.update_objects()","title":""},{"docid":"c1b3e677f6173b23b93234a8db829d2d","score":"0.56799513","text":"def do_it(self):\r\n \r\n sql = r\"\"\"UPDATE OR IGNORE obs_points SET east=X(Geometry) WHERE obsid IN \"\"\" + self.sqlpart2\r\n utils.sql_alter_db(sql)\r\n sql = r\"\"\"UPDATE OR IGNORE obs_points SET north=Y(Geometry) WHERE obsid IN \"\"\" + self.sqlpart2\r\n utils.sql_alter_db(sql)","title":""},{"docid":"b3b45a222915f6de5d439614b120d82d","score":"0.5672655","text":"def update(self, window: 'Window'):\n self._cached_points = self.projected(window)","title":""},{"docid":"b3b45a222915f6de5d439614b120d82d","score":"0.5672655","text":"def update(self, window: 'Window'):\n self._cached_points = self.projected(window)","title":""},{"docid":"6e38eed70813e1e19ce2b93dbdfb4816","score":"0.56643426","text":"def workspace_update_data(self, event):\n\n self.GetMDIParent().workspace_modified = True\n\n if self.IsMaximized():\n event.Skip()\n return\n\n position = self.GetPosition()\n size = self.GetSize()\n\n self.workspace_data['x'] = position[0]\n self.workspace_data['y'] = position[1]\n self.workspace_data['width'] = size[0]\n self.workspace_data['height'] = size[1]\n\n event.Skip()","title":""},{"docid":"5636a9689d4bb52d534c505dec324299","score":"0.5657264","text":"def update_grid(self):\n for m in self.messages:\n message = self.load_message(m)\n self.grid[message['position']]['agent'] = message['name']","title":""},{"docid":"c5aee62bcb611d9817ed5abf5792499d","score":"0.56422895","text":"def updateGrid(array, community):\r\n \r\n #shuffle grid along both axes\r\n np.apply_along_axis(np.random.shuffle, 1, array)\r\n np.random.shuffle(array)\r\n \r\n #update locations of individuals\r\n getLoc = lambda x : (x // array.shape[0], x % array.shape[1])\r\n r = array.ravel()\r\n for i in range(array.size):\r\n community.people[r[i]].updateLoc(getLoc(i))\r\n \r\n return array","title":""},{"docid":"cd05cc3bca07284a8666c32569b3ab00","score":"0.5627794","text":"def update(self):\n # This could use a refactor, but it's pointless to refactor before we\n # know what all the controls should be.\n\n if pyxel.btnp(pyxel.KEY_Q):\n pyxel.quit()\n elif pyxel.btnp(pyxel.KEY_W):\n self.player.walk(0)\n elif pyxel.btnp(pyxel.KEY_D):\n self.player.walk(2)\n elif pyxel.btnp(pyxel.KEY_S):\n self.player.walk(4)\n elif pyxel.btnp(pyxel.KEY_A):\n self.player.walk(6)\n\n for objekt in self.things:\n objekt.update()","title":""},{"docid":"73c809aae8ca5b70d30c9a31dede18c3","score":"0.5603339","text":"def add_obj(self, map_obj):\n for i, cell in enumerate(self.grid):\n if map_obj.shape.intersects(cell):\n self.grid_occupancy[i] = 1","title":""},{"docid":"abf70ac58c2b6fb74ac4492dae3e0220","score":"0.55884767","text":"def __init__(self, grid=None, nrow=25, ncol=25, goal_length=1,\n density=0.3, ctrl_error=0.05, episode_length=100, verbose=False):\n super(GridWorldEnv, self).__init__(\n grid, nrow, ncol, goal_length, density, ctrl_error, episode_length, verbose)\n self.nb_states = self.nrow * self.ncol\n self.nb_actions = 4","title":""},{"docid":"a3a0515b0db1a8267f9cd8b09a79de08","score":"0.55829614","text":"def setup(self):\n self.set_cursor(0, 0)\n\n for obj in self.objects.copy():\n obj.destroy()\n\n for y in xrange(self.height):\n for x in xrange(self.width):\n self.map[x][y] = [floor]\n\n self[self.world.player.location].append(self.world.player)\n\n self.regions = []","title":""},{"docid":"6b2716b1a1d3ec3a56232585aa38edf1","score":"0.5582553","text":"def make_world(self, num_obstacles):\r\n for o in range(num_obstacles):\r\n cell = UNDEFINED\r\n while cell != EMPTY:\r\n i = np.random.randint(0, self.grid.shape[0])\r\n j = np.random.randint(0, self.grid.shape[1])\r\n cell = self.grid[i, j]\r\n if cell == EMPTY:\r\n self.grid[i, j] = OBSTACLE","title":""},{"docid":"d179089399b8adf5c25b7e381e08df00","score":"0.5581471","text":"def refresh_and_blit_overworld_viewing(self, display_update=True):\n\n self.overworld_viewing.refresh_and_blit_self()\n\n if display_update:\n pygame.display.update()","title":""},{"docid":"1a27278fa0d332693d29f8a7b665219a","score":"0.5580832","text":"def update(self):\n # update all sprites\n self.all_sprites.update()","title":""},{"docid":"3b0d5bcdfa009169d5cdb1595d82beb2","score":"0.55695754","text":"def update(self):\n for ai in self.ai_entities:\n ai.update()\n for animation in self.display_entities:\n animation.update()\n for physics in self.physics_entities:\n physics.update()","title":""},{"docid":"07e970d206b1518e4d307cc25073789f","score":"0.55520135","text":"def update():","title":""},{"docid":"f669914f20ed7cd28e0fcac380f00f5e","score":"0.55500704","text":"def __update_modelview(self):\n\n glMatrixMode(GL_MODELVIEW)\n glLoadIdentity()\n\n # We move the camera by moving the world in the opposite direction\n # We deduct how to move the world by the camera position\n camera_pose = self.scene.cam.pose\n world_pose = copy.deepcopy(camera_pose)\n # world_pose.yaw = np.pi/2 - camera_pose.yaw\n # world_pose.pitch = np.pi/2 - camera_pose.pitch\n # world_pose.roll = np.pi/2 - camera_pose.roll\n\n M = world_pose.transfmat\n M[:3, :] = -M[:3, :]\n\n # fit to open gl coordinate system\n M[0, :] = -M[0, :]\n M[1, :] = -M[1, :]\n # transpose and flatten to get column order\n M = M.T\n m = M.flatten()\n # replace model view with the new matrix\n glLoadMatrixf(m)","title":""},{"docid":"efb0c6762609000b1050cb7f0fd48e8c","score":"0.5536209","text":"def update(self):\n self.update_agents()\n self.update_workplaces()\n self.update_specialties()\n self.update_adjacency()\n self.update_influence()\n self.update_state()\n #self.build_network_graph()\n #self.build_transition_matrix()\n #self.build_policy()\n self.reset_simulation()","title":""},{"docid":"4bb550f46a2dbe813c81755d9c7b6132","score":"0.5530107","text":"def update(self):\n # Visualize the detected object\n is_world_changed = False\n self._lock.acquire()\n if self.has_objects():\n to_remove = None\n for i in range(len(self._objects)):\n if self._objects[i].is_removed:\n to_remove = i\n if to_remove is not None:\n self._remove_object(to_remove)\n is_world_changed = True\n\n self._lock.release()\n return is_world_changed","title":""},{"docid":"515b6d7cc1b137f279527ceff4eac88f","score":"0.5528818","text":"def update_agent(self, env_object_info):\n gui_agent_name_id = \\\n self.gui_agents_idx_to_name.index(env_object_info['name'])\n gui_agent_id = self.gui_agents_circle_idx[gui_agent_name_id]\n new_gui_agent_position = self.scale(env_object_info['position'])\n new_gui_agent_radius = env_object_info['radius'] * self.draw_scale\n new_gui_agent_points = util.get_circle_points(new_gui_agent_position,\n new_gui_agent_radius)\n self.canvas.coords(gui_agent_id, new_gui_agent_points)\n\n gui_agent_text_id = self.gui_agents_texts_idx[gui_agent_name_id]\n self.canvas.coords(gui_agent_text_id,\n new_gui_agent_position[0],\n new_gui_agent_position[1])","title":""},{"docid":"28ac099bdb85bed66d67520d2217bf71","score":"0.5525303","text":"def update_grid(self):\n old_grid = self._grid.copy()\n N = self._N\n for i in range(N):\n for j in range(N):\n total = (old_grid[i, (j-1) % N] # up\n + old_grid[i, (j+1) % N] # down\n + old_grid[(i-1) % N, j] # left\n + old_grid[(i+1) % N, j] # right\n + old_grid[(i-1) % N, (j-1) % N] # top-left\n + old_grid[(i+1) % N, (j-1) % N] # top-right\n + old_grid[(i-1) % N, (j+1) % N] # bottom-left\n + old_grid[(i+1) % N, (j+1) % N]) # bottom-right\n\n # Apply the rule\n if old_grid[i, j] == type(self).ON:\n if (total < 2) or (total > 3):\n self._grid[i, j] = type(self).OFF\n else:\n if total == 3:\n self._grid[i, j] = type(self).ON","title":""},{"docid":"01e02286ce64e19077c073363d90c0dd","score":"0.55229336","text":"def update(self):\n #Skip this if there is no tileset or map data\n if self.tileset is None:\n Logger.warning(\"TileMap: There is no assigned tileset.\")\n return\n\n if self.map_data is None:\n Logger.warning(\"TileMap: There is no map data.\")\n return\n\n #Update Fbo size\n w, h = self.size\n w = w * 32\n h = h * 32\n self._fbo.size = (w, h)\n self._rect.size = (w, h)\n self._rect.texture = self._fbo.texture\n\n #Draw the new tiles\n self._fbo.clear()\n\n with self._fbo:\n ClearColor(0, 0, 0, 0)\n ClearBuffers()\n\n #Draw each tile\n x = 0\n y = 0\n\n for row in self.map_data:\n for tile in row:\n Rectangle(pos = (x, y), size = (32, 32), \n source = self.tileset[tile])\n x += 32\n\n y += 32\n x = 0\n\n #Force a redraw of the Fbo\n self._fbo.draw()","title":""},{"docid":"f6709b0464ac5533935d999911fcb0cd","score":"0.5517183","text":"def update(self):\n self.game_manager.update()","title":""},{"docid":"26dd1eca1986788cb58cdf69574460fe","score":"0.5516408","text":"def _draw_grid(self, state):\n for pos in state.grid.keys():\n agent_square = False\n if pos == state.player_pos:\n agent_square = True\n canvas_pos = self._square_coord_to_canvas_coord(*pos)\n self._draw_square(state.grid[pos], canvas_pos, agent_square)","title":""},{"docid":"8cfaf14668ae0c3e8a17c226cba4a187","score":"0.5492774","text":"def update(self):\n units = list(self.units)\n shuffle(units)\n for unit in units:\n unit.action()\n self.auto_update_occupied_cells()\n self.kill_units()\n self.auto_update_occupied_cells()","title":""},{"docid":"35bb606c2d05652b4c14087111f45ce7","score":"0.54828745","text":"def _updateGeometry(self):\n pass","title":""},{"docid":"635fb17a8eb974081f6ffef689c0a79c","score":"0.54768187","text":"def _grid_changed(self):\n\n if not self.grid:\n return\n dimensions = self.getDimensions()\n if not self.isMRG():\n # MD layout (1 or 2 dimensions)\n if self.grid[0] != self.index0:\n self.index0 = self.grid[0]\n if self.grid[1] != self.index1:\n self.index1 = self.grid[1]\n else:\n # MRG layout (3 dimensions)\n if self.grid[0] != self.index1:\n self.index1 = self.grid[0]\n if self.grid[1] != self.index2:\n self.index2 = self.grid[1]\n if self.sensor:\n self.drawLocationImages()","title":""},{"docid":"5c8ace147c2fd716eabb25237931d85e","score":"0.5471644","text":"def update(self):\n self.platform_list.update()\n self.enemy_list.update()\n self.zone_list.update()\n self.potion_list.update()","title":""},{"docid":"4cc1b8dc6388e01f9433adf62a8b5fad","score":"0.54702455","text":"def update_model(self):\n self.request = self.model.get_request(self.events)\n self.model.user_request(self.request)\n self.model.call_menu()\n self.model.towers_attack()\n self.model.enemies_advance()\n\n for tw in self.model.towers:\n tw.update()\n for en in self.model.enemies.get():\n en.update()","title":""},{"docid":"9c2f8754627565f6a005fb2efacd7b34","score":"0.54696226","text":"def update_fov(self) -> None:\n self.game_map.visible_tiles[:] = tcod.map.compute_fov(\n self.game_map.tiles[\"transparent\"],\n (self._player.x, self._player.y),\n radius=self._fov_radius,\n )\n # If a tile is 'visible' it should be set to 'explored'.\n self.game_map.explored_tiles |= self.game_map.visible_tiles","title":""},{"docid":"bc303e1cc5b12ba538a724afd52d5d58","score":"0.54618496","text":"def update(self, entities):\n\n # The set of entities that need a corresponding simulation\n # object. We remove entities where we see them, and create\n # simulation objects where necessary.\n to_remove = set(self.__mapping.keys())\n for e in entities:\n if e in to_remove:\n to_remove.remove(e)\n else:\n body = e.get_component(Body)\n assert body\n pymunk_body = Physics.PymunkBody(body)\n self.__mapping[e] = pymunk_body\n self.__space.add(pymunk_body.body, pymunk_body.shape)\n\n # Now, the set contains all of the entities that had simulation\n # bodies but shouldn't any more.\n for e in to_remove:\n pymunk_body = self.__mapping[e]\n self.__space.remove(pymunk_body.body, pymunk_body.shape)\n del self.__mapping[e]","title":""},{"docid":"d9caabb854d8e0c8fa0f512bf7c29f0b","score":"0.5458752","text":"def update_programs_world_matrix(self):\n # upload the model matrix to the gpu\n for p in self.programs.values():\n p.set_world_matrix(self.camera.world_matrix)","title":""},{"docid":"c6c552facb2059bf452552ae488ea90c","score":"0.5453995","text":"def update_objects(self):\n ObjectsDialog.update_objects(self)\n self.__update_datasets()","title":""},{"docid":"31e90d87aba297f6dbd72da2ac316c99","score":"0.54509586","text":"def createhillMovesGrid(currentObject, numpyGrid, dimensions, houseCounter):\n\n YPosition = 300\n waterWidth = int(23040/296)\n\n # Specify drawNumbers\n drawNumber = currentObject.uniqueID\n fADrawNumber = 1\n\n # Define the maximum number of houses that can be placed on one row\n maxHousesOnRow = houseCounter[3]\n\n if currentObject.type == \"eengezinswoning\":\n maxHousesOnNextRows = houseCounter[4]\n\n # Put eengezinswoningen on the first row\n if houseCounter[0] < maxHousesOnRow:\n coordinates = (YPosition, currentObject.freeArea\n + dimensions * houseCounter[0])\n\n # Put eengezinswoningen on the second row\n elif houseCounter[1] < maxHousesOnNextRows:\n coordinates = (YPosition - dimensions, waterWidth +\n currentObject.freeArea + dimensions * houseCounter[1])\n\n # Put eengezinswoningen on the third row\n elif houseCounter[2] < maxHousesOnNextRows:\n coordinates = (YPosition - dimensions * 2, waterWidth +\n currentObject.freeArea + dimensions * houseCounter[2])\n\n else:\n\n # Put bungalows on the first row\n if houseCounter[0] < maxHousesOnRow:\n coordinates = (currentObject.freeArea,\n waterWidth + currentObject.freeArea + dimensions * \\\n houseCounter[0])\n\n # Put bungalows on the second row\n elif houseCounter[1] < maxHousesOnRow:\n coordinates = (currentObject.freeArea + dimensions,\n waterWidth + currentObject.freeArea + dimensions * \\\n houseCounter[1])\n\n # Put bungalows on the third row\n elif houseCounter[2] < maxHousesOnRow:\n coordinates = (currentObject.freeArea + dimensions * 2,\n waterWidth + currentObject.freeArea + dimensions * \\\n houseCounter[2])\n\n # Update coordinats in self\n changeCoordinates(currentObject, coordinates)\n\n # Get coordinate variables\n coord = coordinateVariables(currentObject)\n\n # The area is clear, so we can immediately draw the free area\n visualizeOnGrid(coord[5], coord[6], coord[7], coord[8],\n numpyGrid, fADrawNumber)\n\n # Visualize house on top of free area\n visualizeOnGrid(coord[0], coord[1], coord[2], coord[3],\n numpyGrid, drawNumber)","title":""},{"docid":"c8bfe92e9541b604a9fbbe005d935ecc","score":"0.5445584","text":"def update(self):\n tmpGrid = self.grid.copy()\n for i in range(self.N):\n for j in range(self.N):\n neighbours = self.grid[max(0, i-1):min(i+2,self.N),max(0, j-1):min(j+2,self.N)].sum()\n neighbours -= self.grid[i, j]\n if self.grid[i, j] == 1:\n if neighbours > 3 or neighbours < 2:\n tmpGrid[i, j] = 0\n elif neighbours == 3:\n tmpGrid[i, j] = 1\n self.grid = tmpGrid","title":""},{"docid":"a296e69589282cdcac7d48eaff3fc9b8","score":"0.5431386","text":"def grid(self, grid):\n self._grid = grid","title":""},{"docid":"5c66034202e7afe84c2224949bd089c1","score":"0.5429856","text":"def update_map(self,players,enemies,attacks,items):\n ##Reset map\n objects = players.player_array + enemies.enemy_array + self.tiles \n players = players.player_array\n attacks = attacks.attack_array\n items = items.item_array\n\n for key in self.spatial_map.keys():\n self.spatial_map[key][\"objects\"] = []\n self.spatial_map[key][\"attacks\"] = []\n self.spatial_map[key][\"players\"] = []\n self.spatial_map[key][\"items\"] = []\n\n #For each object place a reference to them inside each tile they overlap\n for obj in objects:\n self.update_single_obj(obj)\n \n for player in players:\n self.update_single_player(player)\n\n for attack in attacks:\n self.update_single_att(attack)\n\n for item in items:\n self.update_single_item(item)","title":""},{"docid":"2b63135918dde00f4bf19df5a21c549b","score":"0.5428709","text":"def update( ):","title":""},{"docid":"ab42acbae32976a01f94a19c2e3dc505","score":"0.54275686","text":"def update_track_data(self):\n if self.interactive_cell is not None:\n print(\"updating the data structure\")\n print(self.trackdata.get_cell_params(self.current_image, self.current_cell_id))\n properties = self.interactive_cell.get_position_props()\n print(properties)\n self.trackdata.set_cell_properties(self.current_image, self.current_cell_id, properties)\n print(self.trackdata.get_cell_params(self.current_image, self.current_cell_id))","title":""},{"docid":"a38e56cca0ea7476dd3d740729a1cb73","score":"0.54199016","text":"def update(self):\n\n if self.states[PROP_VIEW] == STATE_OVERVIEW: # the worldmap\n if self.states[PROP_UPDATE_MAIN]: # if the main view is being updated\n self.main_view.set_img(self.game.overview_map) # set the view to the worldmap\n self.gm_view.set_img(self.game.overview_map_dm) # set the view to the worldmap\n elif self.states[PROP_VIEW] == STATE_MAPVIEW: # view a map\n # calculate zoom and translation parameters for the main_view\n params = {\"fow\": \"tv\"} # the parameters that will be asked for in the image. fow will be a nice rendering\n if self.states[PROP_ZOOM] != 1:\n params[\"zoom\"] = self.states[PROP_ZOOM]\n if self.states[PROP_TRANS_X]:\n params[\"trans_x\"] = self.states[PROP_TRANS_X]\n if self.states[PROP_TRANS_Y]:\n params[\"trans_y\"] = self.states[PROP_TRANS_Y]\n\n if self.states[PROP_SHOW_TOKEN]:\n params[\"tokens\"] = True\n\n # only update main if allowed\n if self.states[PROP_UPDATE_MAIN]:\n self.main_view.set_img(self.game.curr_map().get_img(**params))\n\n # now that the main view is updated start changing the parameters to suit the gm view\n if self.states[PROP_UPDATE_MAIN]:\n params[\"border\"] = True\n if self.states[PROP_GM_VIEW] == STATE_PREVIEW: # preview is almost the image the main map shows + border\n self.gm_view.set_img(self.game.curr_map().get_img(**params))\n elif self.states[PROP_GM_VIEW] == STATE_NORMAL: # normal gm view\n # add fow param for the gm's view\n if self.states[PROP_GRIDLINES]:\n params[\"gridlines\"] = True\n params[\"fow\"] = \"gm\"\n params[\"dm\"] = True\n params[\"tokens\"] = True\n self.gm_view.set_img(self.game.curr_map().get_img(**params)) # get image and set view\n\n # actually show the images created\n self.gm_view.show(\"gm\")\n self.main_view.show(\"main\")","title":""},{"docid":"9878dbf2b0d57bd216906e2ddd16cb82","score":"0.5416527","text":"def update_geometry(self):\r\n \r\n self.__e2p_horz_marg, self.__e2p_vert_marg,\\\r\n self.__p2l_horz_marg, self.__p2p_gap, self.__p2n_gap,\\\r\n self.__port_size, self.__l2n_gap = self.__geo_prop\r\n\r\n self.update_block()\r\n pass","title":""},{"docid":"4e266d338fe2cfb9910cdae67992f45c","score":"0.5414993","text":"def updateGrid(self, shape):\r\n testing = find_max_score_location(self, shape)\r\n location = testing[2]\r\n fits = testing[0]\r\n numRotations = testing[1]\r\n while numRotations:\r\n shape.rotate90()\r\n numRotations -= 1\r\n for row in range(len(shape.squares)):\r\n for col in range(len(shape.squares[0])):\r\n if shape.squares[row][col] == True:\r\n self.squares[location[0] + row][location[1] + col] = True\r\n self.print()\r\n return fits","title":""},{"docid":"72820f98bcdbd7300373cfc703cf6249","score":"0.54123235","text":"def refresh_2D(self, width, height):\n glViewport(0, 0, width, height)\n glMatrixMode(GL_PROJECTION)\n glLoadIdentity()\n glOrtho(0.0, width, height, 0.0, -1.0, 1.0)\n glMatrixMode(GL_MODELVIEW)\n glLoadIdentity()","title":""},{"docid":"292b387c73ce85b26f2b482af1dff071","score":"0.54103035","text":"def run_world_simulation(self, world, generation, one_loc=None):\n draw_path = '{}gen{}/world'.format(self.path, generation)\n if one_loc:\n one_agent = self.world.agents[one_loc]\n draw_path = '{}gen{}/agent-i{}/world'.format(self.path, generation, one_agent.private_id)\n draw_ext = '.png'\n if self.draw:\n self.view.draw(world)\n self.view.save(draw_path+'0'+draw_ext)\n # print('max_time: {}'.format(self.max_time))\n for t in range(1, self.max_time):\n self.update(world)\n if self.draw:\n self.view.save(draw_path+str(t)+draw_ext)\n with open((draw_path+str(t)+'-comm.csv'), 'w') as f:\n f.write('\\n'.join([str(x) for x in world.comms]))\n self.num_comms += len(world.comms)\n world.comms = []","title":""},{"docid":"c5ea5f507d0b9be50788171e887c8995","score":"0.54042923","text":"def update_house(self, house, points):\n pass","title":""},{"docid":"aa51267cc8dcfe6b3eb332e78ec729c0","score":"0.54038113","text":"def __init__(self, lifespan=None): \n Grid_2D_World.__init__(self, lifespan)\n self.name = 'grid_2D_dc'\n self.name_long = 'decoupled two dimensional grid world'\n print \"--decoupled\"\n self.num_sensors = self.world_size * 2\n self.VISUALIZE_PERIOD = 10 ** 3\n self.display_state = False","title":""},{"docid":"7e104119c0f5c4b592a26de9a22b112c","score":"0.54023683","text":"def update_scene(self):\n\n self.update_programs_projection_matrix()\n self.update_programs_view_matrix()\n self.update_programs_world_matrix()\n if self.ctrl:\n self.update_cursor_data()\n self.glDraw()","title":""},{"docid":"aa8b482d13bca78d63790cc20dc94fb9","score":"0.5402059","text":"def tick(self):\n for world_object in self.objects:\n world_object.tick(self.tick_length)\n self.time += self.tick_length","title":""},{"docid":"66403dc28195279d2d3088308df283e7","score":"0.54001397","text":"def update(self, object_):\n raise NotImplementedError()","title":""},{"docid":"1232dc9540edd7787a03a32b67628ce8","score":"0.5397368","text":"def update_window(self):\n # Update robot position\n self.r1.update_window()\n self.r2.update_window()\n self.r3.update_window()\n\n # now update the OpenGL graphics in window\n self.view3D.update()","title":""},{"docid":"df6f23fddcb85ba97dcaeb9ed9a7489d","score":"0.5393906","text":"def update(self):\n self.robot.update()","title":""},{"docid":"0d5cd273b650ad21a37108b8eda17554","score":"0.53879035","text":"def regenerate_surface(self):\n for x in xrange(0, self.gridWidth):\n for y in xrange(0, self.gridHeight):\n self.update_square((x, y, self.view.z))","title":""},{"docid":"eca5925f4dfe86b42b1ab32e44737d6f","score":"0.53785145","text":"def update():\n\n\tglobal START, END\n\n\tfor i in range(ROWS):\n\t\tfor j in range(COLS):\n\n\t\t\tif GRID[i][j].rect.collidepoint(pygame.mouse.get_pos()[0], pygame.mouse.get_pos()[1]):\n\t\t\t\tkeys = pygame.key.get_pressed()\n\n\t\t\t\tif keys[pygame.K_s] and not GRID[i][j].isEnd:\n\t\t\t\t\tsetStart(i, j)\n\n\t\t\t\telif keys[pygame.K_e] and not GRID[i][j].isStart:\n\t\t\t\t\tsetEnd(i, j)\n\n\t\t\tGRID[i][j].update()","title":""},{"docid":"42e1433ce749544a15aa95c21da63a5f","score":"0.5366284","text":"def test_update(self):\n square = Square(5)\n square.update()\n square.update(1, 2, y=3)\n square.update(1, 12, id=4)\n square.update(size=2, y=5)","title":""},{"docid":"e29da65f264ecaa6bf4014a7e51d8354","score":"0.53635085","text":"def _update_state(self, obs_dict):\n self.x = obs_dict['poses_x'][obs_dict['ego_idx']]\n self.y = obs_dict['poses_y'][obs_dict['ego_idx']]\n\n self.theta = obs_dict['poses_theta'][obs_dict['ego_idx']]\n self.in_collision = obs_dict['collisions'][obs_dict['ego_idx']]\n self.collision_angle = obs_dict['collision_angles'][obs_dict['ego_idx']]","title":""},{"docid":"1ece8315b242490ae55390b9e2366a49","score":"0.5356332","text":"def updatePositions(self):\r\n for body in self.smallBodies+self.largeBodies:\r\n body.pos += body.velocity*self.dt","title":""},{"docid":"b6994c9fd53b5c09e7e66dde3832e274","score":"0.53509086","text":"def move_obj(self, move_x, move_y):\r\n self.wall_list.update(move_x, move_y)\r\n self.door_list.update(move_x, move_y)\r\n self.coin_list.update(move_x, move_y)","title":""},{"docid":"cba6d4f75eac09baf930bc0a050738d5","score":"0.53463733","text":"def update(self):\n\t\tself.active_sprite_list.update()\n\t\tfireball.Fireball.all_fireballs.update()\n\t\tself.score_board.update()","title":""},{"docid":"8f0cea03788b385805f747817ce4cd5a","score":"0.53455746","text":"def _update_geos(self):\n # globe\n self._fig.update_geos(\n row=2,\n col=1,\n showland=False,\n showcountries=False,\n showocean=False,\n showcoastlines=False,\n showframe=False,\n showrivers=False,\n showlakes=False,\n showsubunits=False,\n bgcolor=\"rgba(0,0,0,0)\",\n projection=dict(type=self.projection, rotation=dict(lon=0, lat=0, roll=0)),\n lonaxis=dict(showgrid=True, gridcolor=\"rgb(102, 102, 102)\", gridwidth=1),\n lataxis=dict(showgrid=True, gridcolor=\"rgb(102, 102, 102)\", gridwidth=1),\n )","title":""},{"docid":"c0cabb3c24dc1a92eeb199d14a0eaa45","score":"0.53441733","text":"def do_it(self):\r\n # First find EPSG-ID for the CRS\r\n sql = r\"\"\"SELECT srid FROM geometry_columns where f_table_name = 'obs_points'\"\"\"\r\n ConnectionOK, result = utils.sql_load_fr_db(sql)\r\n EPSGID= str(result[0][0])\r\n #Then do the operation\r\n sql = r\"\"\"Update or ignore 'obs_points' SET Geometry=MakePoint(east, north, \"\"\"\r\n sql += EPSGID\r\n sql += \"\"\") WHERE obsid IN \"\"\" + self.sqlpart2\r\n utils.sql_alter_db(sql)","title":""},{"docid":"ab8104a66e11aa40aa274007683334ef","score":"0.5338825","text":"def get_grid_obs(self):\n self.get_map()\n if not self.finalized:\n self.add_objs_to_map()\n self.grid = [''.join(x) for x in self.map]\n\n return self.grid","title":""},{"docid":"494638ef20dbefa8eadf604666927a82","score":"0.5332123","text":"def _write_grid(self, rr_graph):\n\n grid_locs = rr_graph.grid.init('gridLocs', len(self.graph.grid))\n for out_grid_loc, grid_loc in zip(grid_locs, self.graph.grid):\n out_grid_loc.x = grid_loc.x\n out_grid_loc.y = grid_loc.y\n out_grid_loc.blockTypeId = grid_loc.block_type_id\n out_grid_loc.widthOffset = grid_loc.width_offset\n out_grid_loc.heightOffset = grid_loc.height_offset","title":""},{"docid":"f737f468202e354adc13cb16f314c686","score":"0.5331146","text":"def updateWorld(msg):\n global X, V, orientation\n X = np.array([float(msg.pose[1].position.x), float(msg.pose[1].position.y)])\n V = np.array([float(msg.twist[1].linear.x), float(msg.twist[1].linear.y)])\n orientation = np.arctan2(2 * float(msg.pose[1].orientation.w) * float(msg.pose[1].orientation.z), \\\n 1 - 2 * float(msg.pose[1].orientation.z)**2)","title":""},{"docid":"41200d1aea434dd8554b8745d4687109","score":"0.532805","text":"def update(self):\n old_coords = self.coords\n new_coords = (old_coords[0] + self.direction['H'] * self.speed[0],\n old_coords[1] + self.direction['V'] * self.speed[1])\n self.coords = new_coords","title":""},{"docid":"3a8f4c6a40855cdbd0576aafa89ee391","score":"0.53174084","text":"def __init__(self, env, width, height, min_reward, max_reward): \n self.env = env\n self.width = width\n self.height = height\n self.min_reward = min_reward\n self.max_reward = max_reward\n \n self.root_window = Tkinter.Tk()\n self.root_window.title(\"Gridworld Visualisation\")\n self.root_window.geometry(str(width)+\"x\"+str(height)+\"+200+200\")\n self.root_window.resizable(0, 0)\n \n self.canvas = Tkinter.Canvas(self.root_window, width=width, height=height)\n self.canvas.pack(fill=Tkinter.BOTH, expand=1)\n \n self.grid_x_inc = float(self.width) / self.env.width\n self.half_grid_x_inc = self.grid_x_inc / 2.0\n self.grid_y_inc = float(self.height) / self.env.height\n self.half_grid_y_inc = self.grid_y_inc / 2.0\n \n self.h_lines = []\n for l in xrange(self.env.height):\n pos = l * self.grid_y_inc\n self.h_lines.append(self.canvas.create_line(0, pos, self.width, pos,\n fill=LINE_COLOR))\n \n self.v_lines = []\n for l in xrange(self.env.width):\n pos = l * self.grid_x_inc\n self.v_lines.append(self.canvas.create_line(pos, 0, pos, self.height,\n fill=LINE_COLOR))\n \n self.Q_values = {}\n for state in xrange(self.env.num_states):\n x, y = self.state_to_pos(state)\n x_pos = x * self.grid_x_inc\n y_pos = y * self.grid_y_inc\n #up\n self.Q_values[(state, \"up\")] = self.canvas.create_polygon(\\\n x_pos+Q_TRIANGLE_BORDER,\n y_pos+Q_TRIANGLE_BORDER, \n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\n y_pos+Q_TRIANGLE_BORDER,\n x_pos+self.half_grid_x_inc,\n y_pos+Q_TRIANGLE_PERCENT*self.half_grid_y_inc,\n fill=\"blue\")\n #down\n self.Q_values[(state, \"down\")] = self.canvas.create_polygon(\\\n x_pos+Q_TRIANGLE_BORDER,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1, \n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1,\n x_pos+self.half_grid_x_inc,\n y_pos+self.grid_y_inc-Q_TRIANGLE_PERCENT*self.half_grid_y_inc,\n fill=\"blue\")\n #left\n self.Q_values[(state, \"left\")] = self.canvas.create_polygon(\\\n x_pos+Q_TRIANGLE_BORDER,\n y_pos+Q_TRIANGLE_BORDER,\n x_pos+Q_TRIANGLE_BORDER,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1,\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\n y_pos+self.half_grid_y_inc,\n fill=\"blue\")\n #right\n self.Q_values[(state, \"right\")] = self.canvas.create_polygon(\\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\n y_pos+Q_TRIANGLE_BORDER,\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1,\n x_pos+self.grid_x_inc-Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\n y_pos+self.half_grid_y_inc,\n fill=\"blue\")\n \n self.greedy_policy = {}\n for state in xrange(self.env.num_states):\n x, y = self.state_to_pos(state)\n x_pos = x * self.grid_x_inc\n y_pos = y * self.grid_y_inc\n #up\n self.greedy_policy[(state, \"up\")] = self.canvas.create_polygon(\\\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*G_OUTER_PERCENT,\n y_pos+Q_TRIANGLE_BORDER, \n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*G_OUTER_PERCENT,\n y_pos+Q_TRIANGLE_BORDER,\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*G_INNER_PERCENT,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*G_INNER_PERCENT,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\n fill=G_COLOR, state=Tkinter.HIDDEN)\n #down\n self.greedy_policy[(state, \"down\")] = self.canvas.create_polygon(\\\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*G_OUTER_PERCENT,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1, \n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*G_OUTER_PERCENT,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1,\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*G_INNER_PERCENT,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*G_INNER_PERCENT,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\n fill=G_COLOR, state=Tkinter.HIDDEN)\n #left\n self.greedy_policy[(state, \"left\")] = self.canvas.create_polygon(\\\n x_pos+Q_TRIANGLE_BORDER,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*G_OUTER_PERCENT,\n x_pos+Q_TRIANGLE_BORDER,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*G_OUTER_PERCENT,\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*G_INNER_PERCENT,\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*G_INNER_PERCENT,\n fill=G_COLOR, state=Tkinter.HIDDEN)\n #right\n self.greedy_policy[(state, \"right\")] = self.canvas.create_polygon(\\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*G_OUTER_PERCENT,\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*G_OUTER_PERCENT,\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*G_INNER_PERCENT,\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*G_INNER_PERCENT,\n fill=G_COLOR, state=Tkinter.HIDDEN)\n \n self.actions_taken = {}\n for state in xrange(self.env.num_states):\n x, y = self.state_to_pos(state)\n x_pos = x * self.grid_x_inc\n y_pos = y * self.grid_y_inc\n #up\n self.actions_taken[(state, \"up\")] = self.canvas.create_polygon(\\\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*T_OUTER_PERCENT,\n y_pos+Q_TRIANGLE_BORDER, \n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*T_OUTER_PERCENT,\n y_pos+Q_TRIANGLE_BORDER,\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*T_INNER_PERCENT,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*T_INNER_PERCENT,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\n fill=T_TRIANGLE_COLOR, state=Tkinter.HIDDEN)\n #down\n self.actions_taken[(state, \"down\")] = self.canvas.create_polygon(\\\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*T_OUTER_PERCENT,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1, \n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*T_OUTER_PERCENT,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1,\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*T_INNER_PERCENT,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*T_INNER_PERCENT,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\n fill=T_TRIANGLE_COLOR, state=Tkinter.HIDDEN)\n #left\n self.actions_taken[(state, \"left\")] = self.canvas.create_polygon(\\\n x_pos+Q_TRIANGLE_BORDER,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*T_OUTER_PERCENT,\n x_pos+Q_TRIANGLE_BORDER,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*T_OUTER_PERCENT,\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*T_INNER_PERCENT,\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*T_INNER_PERCENT,\n fill=T_TRIANGLE_COLOR, state=Tkinter.HIDDEN)\n #right\n self.actions_taken[(state, \"right\")] = self.canvas.create_polygon(\\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*T_OUTER_PERCENT,\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*T_OUTER_PERCENT,\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*T_INNER_PERCENT,\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*T_INNER_PERCENT,\n fill=T_TRIANGLE_COLOR, state=Tkinter.HIDDEN)","title":""},{"docid":"81199972fa288a30be57e9729209e64d","score":"0.531061","text":"def update_plants(self,surface):\n for plant in self.plants:\n plant.update(surface,self.current_time)","title":""},{"docid":"fee6404df206f5541c3e32c0ad1f55d2","score":"0.5310382","text":"def update_map(self, grid_map, pose, scan):\n\n # Current yaw of the robot\n robot_yaw = self.get_yaw(pose.pose.orientation)\n # The origin of the map [m, m, rad]. This is the real-world pose of the\n # cell (0,0) in the map.\n origin = grid_map.get_origin()\n # The map resolution [m/cell]\n resolution = grid_map.get_resolution()\n \n \n \"\"\"\n print(\"das sind die Pose- Werte: \" +str(pose))\n \n a = True\n if a == True:\n print(\"das sind die grid- Werte: \" +str(grid_map)) \n a = False\n \"\"\"\n x_list = []\n y_list = []\n #x_y_list = []\n occupied_cells = []\n \n \n for i in range(len(scan.ranges)):\n \n if scan.ranges[i] > scan.range_min and scan.ranges[i] < scan.range_max:\n \n x = (scan.ranges[i] * cos(robot_yaw + (scan.angle_min + scan.angle_increment * i))) + pose.pose.position.x - origin.position.x\n \n y = (scan.ranges[i] * sin(robot_yaw + (scan.angle_min + scan.angle_increment * i))) + pose.pose.position.y - origin.position.y\n \n #x and y end index\n \n x = int(x / resolution) \n y = int(y / resolution)\n \n occupied_cells.append([x,y])\n \n \n #mark as free\n \n starting_x = int((pose.pose.position.x - origin.position.x) / resolution)\n \n starting_y = int((pose.pose.position.y - origin.position.y) / resolution) \n \n start = [starting_x, starting_y]\n \n end = [x,y] \n \n traversed = self.raytrace(start, end)\n \n \n for i in traversed:\n \n self.add_to_map(grid_map, i [0], i [1],self.free_space)\n \n if self.is_in_bounds(grid_map, i[0], i[1]):\n \n x_list.append(i[0])\n \n y_list.append(i[1])\n \n #x_y_list.append([i[0],i[1],self.free_space]) \n \n \n #x and y end index add to list\n #x_list.append(x)\n \n \n #mark as occupied\n \n for i in range(len(occupied_cells)):\n \n self.add_to_map(grid_map,occupied_cells [i][0], occupied_cells [i] [1],self.occupied_space) \n \n #if self.is_in_bounds(grid_map,occupied_cells [i][0], occupied_cells [i][1]):\n \n #x_list.append(occupied_cells [i][0])\n \n #y_list.append(occupied_cells [i][1])\n \n #x_y_list.append([occupied_cells [i][0],occupied_cells [i][1],self.occupied_space])\n \n \n #x_y_list.sort()\n \n data = []\n \n # Only get the part that has been updated\n update = OccupancyGridUpdate()\n \n # The minimum x index in 'grid_map' that has been updated\n update.x = min(x_list)\n \n # The minimum y index in 'grid_map' that has been updated\n update.y = min(y_list)\n \n # Maximum x index - minimum x index + 1\n update.width = max(x_list) - min(x_list) + 1\n #print(\"Breite des Rechtecks: \" +str(update.width))\n \n # Maximum y index _map- minimum y index + 1\n update.height = max(y_list) - min(y_list) + 1\n \n #print(\"Hoehe des Rechtecks: \" +str(update.height))\n # The map data inside the rectangle, in row-major order.\n \n for h in range(update.height):\n \n for i in range(update.width):\n \n data.append(grid_map[update.x + i, update.y + h])\n \n update.data = data\n #print(\"das sind die Daten: \" +str(data))\n \n return grid_map, update","title":""},{"docid":"a03074f42a860d470e4816b8ac49a385","score":"0.53102237","text":"def updateVS(db):\n# graph = get_graph(db)\n mesh = get_mesh(db)\n pos = db.get_property('position')\n wall = db.get_property('wall')\n scale = db.get_property('scale_px_to_micron')\n\n if mesh.degree()==3:\n\t # Area of each cell\n\t V = refresh_property(db, 'V')\n\t for cid in mesh.wisps(3):\n\t\tV[cid]=scale[0]*scale[0]*scale[0]*cell_volume(mesh, pos, cid)\n \n\t # Lengths of each wall\n\t S = refresh_property(db, 'S')\n\t for wid in mesh.wisps(2):\n\t\tS[wid] = scale[0]*scale[0]*face_surface_3D(mesh, pos, wid)\n\n if mesh.degree()==2:\n\t # Area of each cell\n\t V = refresh_property(db, 'V')\n\t for cid in mesh.wisps(2):\n\t\tV[cid]=scale[0]*scale[0]*face_surface_2D(mesh, pos, cid)\n\n\t \n\t # Lengths of each wall\n\t S = refresh_property(db, 'S')\n\t for wid in mesh.wisps(1):\n\t\tS[wid] = scale[0]*edge_length(mesh, pos, wid)","title":""},{"docid":"13bc3a224e18c196b6ad30e173f22528","score":"0.53061366","text":"def updatePixelCoords( self ):\r\n print 'in Movable\\'s updatePixelCoords'","title":""}],"string":"[\n {\n \"docid\": \"ccb16c16812bbd50b00fe75b0f0a58a2\",\n \"score\": \"0.6663007\",\n \"text\": \"def update(self, player, obj_list):\\n for obj in obj_list:\\n obj.update(obj_list)\\n player.update(self.map.tile_boxes)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4251b18b88419fdcb5c977011fe47ba1\",\n \"score\": \"0.6646035\",\n \"text\": \"def update_grid_pos(self):\\n self.grid_pos = self.get_tile_of_position(self.tank.body.position)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"49b7d14b764471d2f66ecf4b41ebcbb8\",\n \"score\": \"0.6583626\",\n \"text\": \"def update_grid(self):\\r\\n\\t\\tself.get_sim_cells()\\r\\n\\t\\t\\\"\\\"\\\"Two loops are used to stop early death or birth of cells.\\r\\n\\t\\tThe grid is meant to evolve as a whole each tick,\\r\\n\\t\\tand not cell-by-cell.\\r\\n\\t\\t\\\"\\\"\\\"\\r\\n\\t\\tfor coord in self.sim_cells:\\r\\n\\t\\t\\tCell.ref_dict[coord].get_new_state()\\r\\n\\t\\tfor coord in self.sim_cells:\\r\\n\\t\\t\\tCell.ref_dict[coord].update_state()\\r\\n\\t\\treturn self\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5fc87997f91cb27a844989ed1c7d632d\",\n \"score\": \"0.6409022\",\n \"text\": \"def update(self):\\n if self.winter_tiles:\\n for i in range(len(self.winter_tiles)):\\n self.winter_tiles[i].show(self.game_display)\\n self.grid.show_grid(self.game_display) # Show a grid\\n self.show_tile_from_matrix('road')\\n\\n # Sorting of the objects based on y-coordinates for correct depiction\\n tmp_objects = self.sort_objects_by_draw_y()\\n if tmp_objects:\\n self.draw_objects(tmp_objects)\\n\\n self.coinMatrix.draw(self.game_display, self.grid_size)\\n\\n # Snowing\\n self.snow.update(self.width, self.height)\\n self.snow.show(self.game_display)\\n\\n # Save and load the game\\n if self.game_state == 'Save':\\n self.save_json()\\n elif self.game_state == 'Load':\\n self.load_json()\\n self.coinMatrix.updateMatrix(self.road_matrix)\\n pygame.display.update() # Update of the screen\\n self.clock.tick(60)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e222f5ab4ad18cba94fed235fcc9199a\",\n \"score\": \"0.6276333\",\n \"text\": \"def update_grid(self):\\n for var in self.model.variables():\\n if var.name[0:1] == 'x':\\n coor = int(var.name[1:])\\n xCoor = (coor - 1) % self.cols\\n yCoor = math.floor((coor - 1) / self.cols)\\n if self.grid[yCoor][xCoor] == 0:\\n self.grid[yCoor][xCoor] = \\\"0\\\"\\n continue\\n if var.value() == 1:\\n self.grid[yCoor][xCoor] = \\\"x\\\"\\n else:\\n self.grid[yCoor][xCoor] = \\\"1\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e30e397a1218d02fb472bef3ebb01a3e\",\n \"score\": \"0.61028606\",\n \"text\": \"def update_grid(self):\\n # List of all occupied/visited cells\\n all_occupied_cells = [player, grid_goal] + self.myObstacles + self.myRewards + self.visited_cells\\n\\n # For every coordinate on the board, check whether it is occupied by any one of the above\\n # cells by comparing coordinates and x, y indices. If no cell is found, add 0 to that position\\n # in the grid indicating an empty cell\\n # If a cell is found, add the cell-type to the position in the grid if\\n # the cell is not of \\\"reward\\\" type. If it is of reward type,\\n # add its value with a 'plus' in front of it\\n for coords in self.get_cell_coordinates():\\n i, j = coords\\n required_cell = next((cell for cell in all_occupied_cells if (cell.x, cell.y) == coords), None)\\n\\n if required_cell:\\n self.grid[i][j] = required_cell.type if required_cell.type is not 3 else '+' + str(required_cell.value)\\n else:\\n self.grid[i][j] = 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3244199d97f3394cef022740d39ec56c\",\n \"score\": \"0.61010367\",\n \"text\": \"def update(self):\\n self.update_physics()\\n\\n for game_object in self.object_pool:\\n game_object.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dc0989774ffb37aeeed717137cb5d66f\",\n \"score\": \"0.6082684\",\n \"text\": \"def update(self, world):\\n self.draw(world)\\n if self.render:\\n pygame.display.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"afec1254648b3c31d8c6402468258f13\",\n \"score\": \"0.6040232\",\n \"text\": \"def update( self):\\n#\\t\\tGame._window.update()\\n\\t\\tself.rect.topleft = self.pos\\n\\n\\t\\tself.setGrid(0, self.inactiveGrid())\\n\\t\\tfor row in range( self.numRows - 1):\\n\\t\\t\\tfor col in range( self.numCols - 1):\\n\\t\\t\\t\\tgameState_next = self.check_cellNeighbours(row, col)\\n\\t\\t\\t\\tself.grids[ self.inactiveGrid()][row][col] = gameState_next\\n\\n\\t\\tself.activeGrid = self.inactiveGrid()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"478325dded0df68632170ff1dbd59855\",\n \"score\": \"0.60273534\",\n \"text\": \"def edit_grid() :\\r\\n\\r\\n #Loading a global variable\\r\\n global obstacle_coords\\r\\n\\r\\n #Checking if the tile is an obstacle or a free tile\\r\\n if(((row, col) in obstacle_coords) == False) :\\r\\n #Changing background colour of button\\r\\n gui_elements[\\\"maze_grid\\\"][row][col].config(bg=\\\"red\\\")\\r\\n\\r\\n #Updating the list of obstructions\\r\\n obstacle_coords.append((row, col))\\r\\n\\r\\n else :\\r\\n #Changing background colour of button\\r\\n gui_elements[\\\"maze_grid\\\"][row][col].config(bg=\\\"white\\\")\\r\\n\\r\\n #Updating the list of obstructions\\r\\n obstacle_coords.remove((row, col))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"009fb730578d942234ab8a8919effcfd\",\n \"score\": \"0.60224444\",\n \"text\": \"def update(self):\\n p.setGravity(0, 0, -10.)\\n if self.state == 0:\\n for envO in self.env_objects:\\n c_points = p.getClosestPoints(self.bot.p_id, envO.p_id, 0.001)\\n if c_points is not None and len(c_points) > 0:\\n self.state = 2\\n print(\\\"CRASH\\\")\\n if self.goal_pos.dist_2d(self.bot.pos) < self.config_.ROB_RADIUS * 1.5:\\n print(\\\"GOAL\\\")\\n self.state = 1\\n self.bot.update()\\n for o in self.env_objects:\\n o.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4826132262c399b4321b97fce27217c0\",\n \"score\": \"0.59522325\",\n \"text\": \"def Update_World(mech, world):\\n for func in Update_World.updaters:\\n func(mech, world)\\n\\n update_func_world(mech, world)\\n Update_RATE(mech, world)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f4f61fab96c39e37c01fda6b509e4a2f\",\n \"score\": \"0.5947868\",\n \"text\": \"def update_grid(self, grid):\\n if torch.is_tensor(grid):\\n grid = convert_legacy_grid(grid)\\n\\n if len(grid) != self.num_dims:\\n raise RuntimeError(\\\"New grid should have the same number of dimensions as before.\\\")\\n\\n for i in range(self.num_dims):\\n setattr(self, f\\\"grid_{i}\\\", grid[i])\\n\\n if not self.interpolation_mode:\\n self.full_grid = create_data_from_grid(self.grid)\\n\\n self._clear_cache()\\n return self\",\n \"title\": \"\"\n },\n {\n \"docid\": \"20856802fff123ea0dbe44d7f29254f4\",\n \"score\": \"0.59443927\",\n \"text\": \"def update(self):\\n for mc in self.monsters:\\n mc.update(self)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3d4ed00f8918f1ca806b65d160ee092e\",\n \"score\": \"0.5938704\",\n \"text\": \"def update_func_world(mech, world):\\n globals().update(world)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9076acb5b9f1ea0370fa81f1ee58cf74\",\n \"score\": \"0.59250045\",\n \"text\": \"def test_update_world(self):\\n world = World()\\n self.assertEqual(world.time, 0)\\n\\n old_state = []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"95d2971320d743db3ddea25f3cba6342\",\n \"score\": \"0.5903083\",\n \"text\": \"def update_map(self):\\n self.generate_walls_from_markers()\\n for (id,cube) in self.robot.world.light_cubes.items():\\n self.update_cube(cube)\\n for face in self.robot.world._faces.values():\\n self.update_face(face)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d2e7d6494257b3418ec5ecbd454a245c\",\n \"score\": \"0.5900022\",\n \"text\": \"def update(self, world: World, events):\\n\\n is_world_updated = self.previous_world_t != world.t\\n if is_world_updated:\\n self.previous_world_t = world.t\\n\\n self._handle_events(events)\\n\\n self.entities = self._get_entities(world)\\n\\n self.selected_entity_index %= len(self.entities)\\n selected_entity = self.entities[self.selected_entity_index]\\n reference_entity = self.entities[self.reference_entity_index]\\n self.viewer.draw(world, reference_entity, selected_entity)\\n\\n if is_world_updated: self.plotter.update(self.entities, reference_entity)\\n self.plotter.draw(selected_entity, self.entities)\\n\\n pygame.display.flip()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9239c99658343d804abbdc9ef0570628\",\n \"score\": \"0.588836\",\n \"text\": \"def update(self):\\n self.dirty_rects, old = [], self.dirty_rects\\n self.world.tick()\\n self.draw_world()\\n\\n self.clock.tick(FRAMERATE)\\n pygame.display.update(self.dirty_rects + old)\\n # print(self.world)\\n print(self.world.ticks)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e8d1fc7dbc63dbd6bb5049043c2d121b\",\n \"score\": \"0.58847094\",\n \"text\": \"def updateGlobalCoords(self):\\r\\n self.globalCoords = [ self.localToGlobalCoords(T) for T in self.localCoords ]\\r\\n #print 'cx,cy,thd are', self.cx, self.cy, math.degrees(self.thr)\\r\\n #print 'globalCoords are', self.globalCoords\\r\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d676fd3eea594b39042ed82764c5522b\",\n \"score\": \"0.58839756\",\n \"text\": \"def draw_world(self):\\n for row in self.world.cells:\\n for cell in row:\\n if not cell.static:\\n self.draw_cell(cell)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7a3110e49ab2d94bbf724b47267bf193\",\n \"score\": \"0.5855152\",\n \"text\": \"def update(self):\\r\\n self.cell.update()\\r\\n self.receptor_system.update()\\r\\n self.glucose_system.update()\\r\\n self.sensor_system.update()\\r\\n self.protein_system.update()\\r\\n self.glut_system.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"16a9df5df41d9c59d804de27e6a360d1\",\n \"score\": \"0.58381873\",\n \"text\": \"def update_objects(self):\\n # Draw obstacles on the screen\\n for obstacle in self._obstacles:\\n obstacle.draw(self.screen)\\n\\n # Draw player on the screen\\n self.player.draw(self.screen)\\n # Draw score widget on the screen\\n self.score_widget.draw(self.screen)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7ba79b058d64e40a68348deb6c2f8925\",\n \"score\": \"0.5811544\",\n \"text\": \"def update(self, couple):\\n bbox = couple[1]\\n if bbox.x is None or bbox.y is None:\\n return\\n\\n new_pos = set()\\n x1 = int(bbox.x // self.grid_size)\\n y1 = int(bbox.y // self.grid_size)\\n x2 = int((bbox.x + bbox.w) // self.grid_size)\\n y2 = int((bbox.y + bbox.h) // self.grid_size)\\n\\n # New population set\\n positions = (x1, y1), (x1, y2), (x1, y2), (x2, y2)\\n for pos in positions:\\n if (0 <= pos[0] <= self.num_columns\\n and 0 <= pos[1] <= self.num_rows):\\n new_pos.add(pos)\\n\\n # Remove from previous locations\\n for pos in self._population.get(couple, set()) - new_pos:\\n self._grid[pos[0]][pos[1]].discard(couple)\\n # Add to new locations\\n for pos in new_pos - self._population.get(couple, set()):\\n self._grid[pos[0]][pos[1]].add(couple)\\n\\n # Update population\\n self._population[couple] = new_pos\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ba6dc86cad96fa6a10cd88c66211ebb6\",\n \"score\": \"0.5792867\",\n \"text\": \"def Update(*args):\\r\\n return _pynewton.World_Update(*args)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"84aced866f490d2416d8ee5c333b0b6d\",\n \"score\": \"0.577716\",\n \"text\": \"def _update(self):\\n self._game.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8c81d718a4c72893a0b317b5b9ce67a4\",\n \"score\": \"0.5762038\",\n \"text\": \"def update_obstacles(self, env_object_info):\\n gui_obstacle_name_id = \\\\\\n self.gui_obstacles_idx_to_name.index(env_object_info['name'])\\n gui_obstacle_id = self.gui_obstacles_circle_idx[gui_obstacle_name_id]\\n new_gui_obstacle_position = self.scale(env_object_info['position'])\\n new_gui_obstacle_radius = env_object_info['radius'] * self.draw_scale\\n new_gui_obstacle_points = util.get_circle_points(new_gui_obstacle_position,\\n new_gui_obstacle_radius)\\n self.canvas.coords(gui_obstacle_id, new_gui_obstacle_points)\\n\\n gui_obstacle_text_id = self.gui_obstacles_texts_idx[gui_obstacle_name_id]\\n self.canvas.coords(gui_obstacle_text_id,\\n new_gui_obstacle_position[0],\\n new_gui_obstacle_position[1])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ef0934c068db0c31c84e2d3181354575\",\n \"score\": \"0.57311904\",\n \"text\": \"def update(self):\\r\\n if len(self.collbox_dict) != 0:\\r\\n for coll_box in self.collbox_dict.values():\\r\\n coll_box.x = self.x + (coll_box.width // 2) + coll_box.x_offset\\r\\n coll_box.y = self.y + (coll_box.height // 2) + coll_box.y_offset\\r\\n coll_box.left_edge = coll_box.x - (coll_box.width // 2)\\r\\n coll_box.right_edge = coll_box.x + (coll_box.width // 2)\\r\\n coll_box.top_edge = coll_box.y - (coll_box.height // 2)\\r\\n coll_box.bottom_edge = coll_box.y + (coll_box.height // 2)\\r\\n\\r\\n if self.sprite_dict != None:\\r\\n for sprite in self.sprite_dict.values():\\r\\n sprite.x = self.x\\r\\n sprite.y = self.y\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8833f9340a225f4bf3820c523e3221ad\",\n \"score\": \"0.57147515\",\n \"text\": \"def update(self):\\n self._coarse_grid = self._config_dict['coarse_grid']\\n self._solution = self._config_dict['solution']\\n BR_dict = dict()\\n RTf_dict = dict()\\n self._interface2dof_map = dict()\\n self._global_dof_dimension = 0\\n\\n for problem_id, local_problem in self._local_problems_dict.items():\\n BR_int_dict = dict()\\n if local_problem.kernel.size == 0:\\n for interface, B in local_problem.B.items():\\n BR_int_dict[interface] = np.array([])\\n else:\\n for interface, B in local_problem.B.items():\\n BR_int_dict[interface] = B @ local_problem.kernel\\n BR_dict[problem_id] = BR_int_dict\\n if local_problem.kernel.size == 0:\\n RTf_dict[problem_id] = np.array([])\\n else:\\n RTf_dict[problem_id] = np.asarray(local_problem.kernel.T @ local_problem.f).flatten()\\n for interface, B in local_problem.B.items():\\n if interface not in self._interface2dof_map:\\n new_global_dof_dimension = self._global_dof_dimension + B.shape[0]\\n self._interface2dof_map[interface] = np.arange(self._global_dof_dimension, new_global_dof_dimension)\\n self._global_dof_dimension = new_global_dof_dimension\\n\\n self._coarse_grid.update(BR_dict, RTf_dict, self._interfacedict2vector)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7737ad53c94eaf262fc7531d4dd0bcab\",\n \"score\": \"0.5705845\",\n \"text\": \"def update_individual_spatial(self, population, row, col):\\n\\t\\tNam = population[1][row][col]\\n\\t\\tNim = population[2][row][col]\\n\\t\\tpopulation[1][row][col], population[2][row][col] = self.mutate_individual(Nam, Nim)\\n\\t\\tpopulation[0][row][col] = self.compute_r(population[1][row][col], population[2][row][col])\\n\\t\\treturn(population)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c5b490707e9d67dad989d77d605cfca8\",\n \"score\": \"0.568819\",\n \"text\": \"def update_square(self, location):\\n x, y, z = location\\n terrainNode = self.grid.get_node_at(location)\\n if terrainNode is not None:\\n rect = pygame.Rect(x, y, 1, 1)\\n terrainNode.contents.render(rect, self.surface)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f5e0bcbb560c321a9c2c3c06b97242f7\",\n \"score\": \"0.56843\",\n \"text\": \"def update(self):\\n self.OH.update_objects()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c1b3e677f6173b23b93234a8db829d2d\",\n \"score\": \"0.56799513\",\n \"text\": \"def do_it(self):\\r\\n \\r\\n sql = r\\\"\\\"\\\"UPDATE OR IGNORE obs_points SET east=X(Geometry) WHERE obsid IN \\\"\\\"\\\" + self.sqlpart2\\r\\n utils.sql_alter_db(sql)\\r\\n sql = r\\\"\\\"\\\"UPDATE OR IGNORE obs_points SET north=Y(Geometry) WHERE obsid IN \\\"\\\"\\\" + self.sqlpart2\\r\\n utils.sql_alter_db(sql)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b3b45a222915f6de5d439614b120d82d\",\n \"score\": \"0.5672655\",\n \"text\": \"def update(self, window: 'Window'):\\n self._cached_points = self.projected(window)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b3b45a222915f6de5d439614b120d82d\",\n \"score\": \"0.5672655\",\n \"text\": \"def update(self, window: 'Window'):\\n self._cached_points = self.projected(window)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6e38eed70813e1e19ce2b93dbdfb4816\",\n \"score\": \"0.56643426\",\n \"text\": \"def workspace_update_data(self, event):\\n\\n self.GetMDIParent().workspace_modified = True\\n\\n if self.IsMaximized():\\n event.Skip()\\n return\\n\\n position = self.GetPosition()\\n size = self.GetSize()\\n\\n self.workspace_data['x'] = position[0]\\n self.workspace_data['y'] = position[1]\\n self.workspace_data['width'] = size[0]\\n self.workspace_data['height'] = size[1]\\n\\n event.Skip()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5636a9689d4bb52d534c505dec324299\",\n \"score\": \"0.5657264\",\n \"text\": \"def update_grid(self):\\n for m in self.messages:\\n message = self.load_message(m)\\n self.grid[message['position']]['agent'] = message['name']\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c5aee62bcb611d9817ed5abf5792499d\",\n \"score\": \"0.56422895\",\n \"text\": \"def updateGrid(array, community):\\r\\n \\r\\n #shuffle grid along both axes\\r\\n np.apply_along_axis(np.random.shuffle, 1, array)\\r\\n np.random.shuffle(array)\\r\\n \\r\\n #update locations of individuals\\r\\n getLoc = lambda x : (x // array.shape[0], x % array.shape[1])\\r\\n r = array.ravel()\\r\\n for i in range(array.size):\\r\\n community.people[r[i]].updateLoc(getLoc(i))\\r\\n \\r\\n return array\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cd05cc3bca07284a8666c32569b3ab00\",\n \"score\": \"0.5627794\",\n \"text\": \"def update(self):\\n # This could use a refactor, but it's pointless to refactor before we\\n # know what all the controls should be.\\n\\n if pyxel.btnp(pyxel.KEY_Q):\\n pyxel.quit()\\n elif pyxel.btnp(pyxel.KEY_W):\\n self.player.walk(0)\\n elif pyxel.btnp(pyxel.KEY_D):\\n self.player.walk(2)\\n elif pyxel.btnp(pyxel.KEY_S):\\n self.player.walk(4)\\n elif pyxel.btnp(pyxel.KEY_A):\\n self.player.walk(6)\\n\\n for objekt in self.things:\\n objekt.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"73c809aae8ca5b70d30c9a31dede18c3\",\n \"score\": \"0.5603339\",\n \"text\": \"def add_obj(self, map_obj):\\n for i, cell in enumerate(self.grid):\\n if map_obj.shape.intersects(cell):\\n self.grid_occupancy[i] = 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"abf70ac58c2b6fb74ac4492dae3e0220\",\n \"score\": \"0.55884767\",\n \"text\": \"def __init__(self, grid=None, nrow=25, ncol=25, goal_length=1,\\n density=0.3, ctrl_error=0.05, episode_length=100, verbose=False):\\n super(GridWorldEnv, self).__init__(\\n grid, nrow, ncol, goal_length, density, ctrl_error, episode_length, verbose)\\n self.nb_states = self.nrow * self.ncol\\n self.nb_actions = 4\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a3a0515b0db1a8267f9cd8b09a79de08\",\n \"score\": \"0.55829614\",\n \"text\": \"def setup(self):\\n self.set_cursor(0, 0)\\n\\n for obj in self.objects.copy():\\n obj.destroy()\\n\\n for y in xrange(self.height):\\n for x in xrange(self.width):\\n self.map[x][y] = [floor]\\n\\n self[self.world.player.location].append(self.world.player)\\n\\n self.regions = []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6b2716b1a1d3ec3a56232585aa38edf1\",\n \"score\": \"0.5582553\",\n \"text\": \"def make_world(self, num_obstacles):\\r\\n for o in range(num_obstacles):\\r\\n cell = UNDEFINED\\r\\n while cell != EMPTY:\\r\\n i = np.random.randint(0, self.grid.shape[0])\\r\\n j = np.random.randint(0, self.grid.shape[1])\\r\\n cell = self.grid[i, j]\\r\\n if cell == EMPTY:\\r\\n self.grid[i, j] = OBSTACLE\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d179089399b8adf5c25b7e381e08df00\",\n \"score\": \"0.5581471\",\n \"text\": \"def refresh_and_blit_overworld_viewing(self, display_update=True):\\n\\n self.overworld_viewing.refresh_and_blit_self()\\n\\n if display_update:\\n pygame.display.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1a27278fa0d332693d29f8a7b665219a\",\n \"score\": \"0.5580832\",\n \"text\": \"def update(self):\\n # update all sprites\\n self.all_sprites.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3b0d5bcdfa009169d5cdb1595d82beb2\",\n \"score\": \"0.55695754\",\n \"text\": \"def update(self):\\n for ai in self.ai_entities:\\n ai.update()\\n for animation in self.display_entities:\\n animation.update()\\n for physics in self.physics_entities:\\n physics.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"07e970d206b1518e4d307cc25073789f\",\n \"score\": \"0.55520135\",\n \"text\": \"def update():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f669914f20ed7cd28e0fcac380f00f5e\",\n \"score\": \"0.55500704\",\n \"text\": \"def __update_modelview(self):\\n\\n glMatrixMode(GL_MODELVIEW)\\n glLoadIdentity()\\n\\n # We move the camera by moving the world in the opposite direction\\n # We deduct how to move the world by the camera position\\n camera_pose = self.scene.cam.pose\\n world_pose = copy.deepcopy(camera_pose)\\n # world_pose.yaw = np.pi/2 - camera_pose.yaw\\n # world_pose.pitch = np.pi/2 - camera_pose.pitch\\n # world_pose.roll = np.pi/2 - camera_pose.roll\\n\\n M = world_pose.transfmat\\n M[:3, :] = -M[:3, :]\\n\\n # fit to open gl coordinate system\\n M[0, :] = -M[0, :]\\n M[1, :] = -M[1, :]\\n # transpose and flatten to get column order\\n M = M.T\\n m = M.flatten()\\n # replace model view with the new matrix\\n glLoadMatrixf(m)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"efb0c6762609000b1050cb7f0fd48e8c\",\n \"score\": \"0.5536209\",\n \"text\": \"def update(self):\\n self.update_agents()\\n self.update_workplaces()\\n self.update_specialties()\\n self.update_adjacency()\\n self.update_influence()\\n self.update_state()\\n #self.build_network_graph()\\n #self.build_transition_matrix()\\n #self.build_policy()\\n self.reset_simulation()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4bb550f46a2dbe813c81755d9c7b6132\",\n \"score\": \"0.5530107\",\n \"text\": \"def update(self):\\n # Visualize the detected object\\n is_world_changed = False\\n self._lock.acquire()\\n if self.has_objects():\\n to_remove = None\\n for i in range(len(self._objects)):\\n if self._objects[i].is_removed:\\n to_remove = i\\n if to_remove is not None:\\n self._remove_object(to_remove)\\n is_world_changed = True\\n\\n self._lock.release()\\n return is_world_changed\",\n \"title\": \"\"\n },\n {\n \"docid\": \"515b6d7cc1b137f279527ceff4eac88f\",\n \"score\": \"0.5528818\",\n \"text\": \"def update_agent(self, env_object_info):\\n gui_agent_name_id = \\\\\\n self.gui_agents_idx_to_name.index(env_object_info['name'])\\n gui_agent_id = self.gui_agents_circle_idx[gui_agent_name_id]\\n new_gui_agent_position = self.scale(env_object_info['position'])\\n new_gui_agent_radius = env_object_info['radius'] * self.draw_scale\\n new_gui_agent_points = util.get_circle_points(new_gui_agent_position,\\n new_gui_agent_radius)\\n self.canvas.coords(gui_agent_id, new_gui_agent_points)\\n\\n gui_agent_text_id = self.gui_agents_texts_idx[gui_agent_name_id]\\n self.canvas.coords(gui_agent_text_id,\\n new_gui_agent_position[0],\\n new_gui_agent_position[1])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"28ac099bdb85bed66d67520d2217bf71\",\n \"score\": \"0.5525303\",\n \"text\": \"def update_grid(self):\\n old_grid = self._grid.copy()\\n N = self._N\\n for i in range(N):\\n for j in range(N):\\n total = (old_grid[i, (j-1) % N] # up\\n + old_grid[i, (j+1) % N] # down\\n + old_grid[(i-1) % N, j] # left\\n + old_grid[(i+1) % N, j] # right\\n + old_grid[(i-1) % N, (j-1) % N] # top-left\\n + old_grid[(i+1) % N, (j-1) % N] # top-right\\n + old_grid[(i-1) % N, (j+1) % N] # bottom-left\\n + old_grid[(i+1) % N, (j+1) % N]) # bottom-right\\n\\n # Apply the rule\\n if old_grid[i, j] == type(self).ON:\\n if (total < 2) or (total > 3):\\n self._grid[i, j] = type(self).OFF\\n else:\\n if total == 3:\\n self._grid[i, j] = type(self).ON\",\n \"title\": \"\"\n },\n {\n \"docid\": \"01e02286ce64e19077c073363d90c0dd\",\n \"score\": \"0.55229336\",\n \"text\": \"def update(self):\\n #Skip this if there is no tileset or map data\\n if self.tileset is None:\\n Logger.warning(\\\"TileMap: There is no assigned tileset.\\\")\\n return\\n\\n if self.map_data is None:\\n Logger.warning(\\\"TileMap: There is no map data.\\\")\\n return\\n\\n #Update Fbo size\\n w, h = self.size\\n w = w * 32\\n h = h * 32\\n self._fbo.size = (w, h)\\n self._rect.size = (w, h)\\n self._rect.texture = self._fbo.texture\\n\\n #Draw the new tiles\\n self._fbo.clear()\\n\\n with self._fbo:\\n ClearColor(0, 0, 0, 0)\\n ClearBuffers()\\n\\n #Draw each tile\\n x = 0\\n y = 0\\n\\n for row in self.map_data:\\n for tile in row:\\n Rectangle(pos = (x, y), size = (32, 32), \\n source = self.tileset[tile])\\n x += 32\\n\\n y += 32\\n x = 0\\n\\n #Force a redraw of the Fbo\\n self._fbo.draw()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f6709b0464ac5533935d999911fcb0cd\",\n \"score\": \"0.5517183\",\n \"text\": \"def update(self):\\n self.game_manager.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"26dd1eca1986788cb58cdf69574460fe\",\n \"score\": \"0.5516408\",\n \"text\": \"def _draw_grid(self, state):\\n for pos in state.grid.keys():\\n agent_square = False\\n if pos == state.player_pos:\\n agent_square = True\\n canvas_pos = self._square_coord_to_canvas_coord(*pos)\\n self._draw_square(state.grid[pos], canvas_pos, agent_square)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8cfaf14668ae0c3e8a17c226cba4a187\",\n \"score\": \"0.5492774\",\n \"text\": \"def update(self):\\n units = list(self.units)\\n shuffle(units)\\n for unit in units:\\n unit.action()\\n self.auto_update_occupied_cells()\\n self.kill_units()\\n self.auto_update_occupied_cells()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"35bb606c2d05652b4c14087111f45ce7\",\n \"score\": \"0.54828745\",\n \"text\": \"def _updateGeometry(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"635fb17a8eb974081f6ffef689c0a79c\",\n \"score\": \"0.54768187\",\n \"text\": \"def _grid_changed(self):\\n\\n if not self.grid:\\n return\\n dimensions = self.getDimensions()\\n if not self.isMRG():\\n # MD layout (1 or 2 dimensions)\\n if self.grid[0] != self.index0:\\n self.index0 = self.grid[0]\\n if self.grid[1] != self.index1:\\n self.index1 = self.grid[1]\\n else:\\n # MRG layout (3 dimensions)\\n if self.grid[0] != self.index1:\\n self.index1 = self.grid[0]\\n if self.grid[1] != self.index2:\\n self.index2 = self.grid[1]\\n if self.sensor:\\n self.drawLocationImages()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5c8ace147c2fd716eabb25237931d85e\",\n \"score\": \"0.5471644\",\n \"text\": \"def update(self):\\n self.platform_list.update()\\n self.enemy_list.update()\\n self.zone_list.update()\\n self.potion_list.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4cc1b8dc6388e01f9433adf62a8b5fad\",\n \"score\": \"0.54702455\",\n \"text\": \"def update_model(self):\\n self.request = self.model.get_request(self.events)\\n self.model.user_request(self.request)\\n self.model.call_menu()\\n self.model.towers_attack()\\n self.model.enemies_advance()\\n\\n for tw in self.model.towers:\\n tw.update()\\n for en in self.model.enemies.get():\\n en.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9c2f8754627565f6a005fb2efacd7b34\",\n \"score\": \"0.54696226\",\n \"text\": \"def update_fov(self) -> None:\\n self.game_map.visible_tiles[:] = tcod.map.compute_fov(\\n self.game_map.tiles[\\\"transparent\\\"],\\n (self._player.x, self._player.y),\\n radius=self._fov_radius,\\n )\\n # If a tile is 'visible' it should be set to 'explored'.\\n self.game_map.explored_tiles |= self.game_map.visible_tiles\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bc303e1cc5b12ba538a724afd52d5d58\",\n \"score\": \"0.54618496\",\n \"text\": \"def update(self, entities):\\n\\n # The set of entities that need a corresponding simulation\\n # object. We remove entities where we see them, and create\\n # simulation objects where necessary.\\n to_remove = set(self.__mapping.keys())\\n for e in entities:\\n if e in to_remove:\\n to_remove.remove(e)\\n else:\\n body = e.get_component(Body)\\n assert body\\n pymunk_body = Physics.PymunkBody(body)\\n self.__mapping[e] = pymunk_body\\n self.__space.add(pymunk_body.body, pymunk_body.shape)\\n\\n # Now, the set contains all of the entities that had simulation\\n # bodies but shouldn't any more.\\n for e in to_remove:\\n pymunk_body = self.__mapping[e]\\n self.__space.remove(pymunk_body.body, pymunk_body.shape)\\n del self.__mapping[e]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d9caabb854d8e0c8fa0f512bf7c29f0b\",\n \"score\": \"0.5458752\",\n \"text\": \"def update_programs_world_matrix(self):\\n # upload the model matrix to the gpu\\n for p in self.programs.values():\\n p.set_world_matrix(self.camera.world_matrix)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c6c552facb2059bf452552ae488ea90c\",\n \"score\": \"0.5453995\",\n \"text\": \"def update_objects(self):\\n ObjectsDialog.update_objects(self)\\n self.__update_datasets()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"31e90d87aba297f6dbd72da2ac316c99\",\n \"score\": \"0.54509586\",\n \"text\": \"def createhillMovesGrid(currentObject, numpyGrid, dimensions, houseCounter):\\n\\n YPosition = 300\\n waterWidth = int(23040/296)\\n\\n # Specify drawNumbers\\n drawNumber = currentObject.uniqueID\\n fADrawNumber = 1\\n\\n # Define the maximum number of houses that can be placed on one row\\n maxHousesOnRow = houseCounter[3]\\n\\n if currentObject.type == \\\"eengezinswoning\\\":\\n maxHousesOnNextRows = houseCounter[4]\\n\\n # Put eengezinswoningen on the first row\\n if houseCounter[0] < maxHousesOnRow:\\n coordinates = (YPosition, currentObject.freeArea\\n + dimensions * houseCounter[0])\\n\\n # Put eengezinswoningen on the second row\\n elif houseCounter[1] < maxHousesOnNextRows:\\n coordinates = (YPosition - dimensions, waterWidth +\\n currentObject.freeArea + dimensions * houseCounter[1])\\n\\n # Put eengezinswoningen on the third row\\n elif houseCounter[2] < maxHousesOnNextRows:\\n coordinates = (YPosition - dimensions * 2, waterWidth +\\n currentObject.freeArea + dimensions * houseCounter[2])\\n\\n else:\\n\\n # Put bungalows on the first row\\n if houseCounter[0] < maxHousesOnRow:\\n coordinates = (currentObject.freeArea,\\n waterWidth + currentObject.freeArea + dimensions * \\\\\\n houseCounter[0])\\n\\n # Put bungalows on the second row\\n elif houseCounter[1] < maxHousesOnRow:\\n coordinates = (currentObject.freeArea + dimensions,\\n waterWidth + currentObject.freeArea + dimensions * \\\\\\n houseCounter[1])\\n\\n # Put bungalows on the third row\\n elif houseCounter[2] < maxHousesOnRow:\\n coordinates = (currentObject.freeArea + dimensions * 2,\\n waterWidth + currentObject.freeArea + dimensions * \\\\\\n houseCounter[2])\\n\\n # Update coordinats in self\\n changeCoordinates(currentObject, coordinates)\\n\\n # Get coordinate variables\\n coord = coordinateVariables(currentObject)\\n\\n # The area is clear, so we can immediately draw the free area\\n visualizeOnGrid(coord[5], coord[6], coord[7], coord[8],\\n numpyGrid, fADrawNumber)\\n\\n # Visualize house on top of free area\\n visualizeOnGrid(coord[0], coord[1], coord[2], coord[3],\\n numpyGrid, drawNumber)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c8bfe92e9541b604a9fbbe005d935ecc\",\n \"score\": \"0.5445584\",\n \"text\": \"def update(self):\\n tmpGrid = self.grid.copy()\\n for i in range(self.N):\\n for j in range(self.N):\\n neighbours = self.grid[max(0, i-1):min(i+2,self.N),max(0, j-1):min(j+2,self.N)].sum()\\n neighbours -= self.grid[i, j]\\n if self.grid[i, j] == 1:\\n if neighbours > 3 or neighbours < 2:\\n tmpGrid[i, j] = 0\\n elif neighbours == 3:\\n tmpGrid[i, j] = 1\\n self.grid = tmpGrid\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a296e69589282cdcac7d48eaff3fc9b8\",\n \"score\": \"0.5431386\",\n \"text\": \"def grid(self, grid):\\n self._grid = grid\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5c66034202e7afe84c2224949bd089c1\",\n \"score\": \"0.5429856\",\n \"text\": \"def update_map(self,players,enemies,attacks,items):\\n ##Reset map\\n objects = players.player_array + enemies.enemy_array + self.tiles \\n players = players.player_array\\n attacks = attacks.attack_array\\n items = items.item_array\\n\\n for key in self.spatial_map.keys():\\n self.spatial_map[key][\\\"objects\\\"] = []\\n self.spatial_map[key][\\\"attacks\\\"] = []\\n self.spatial_map[key][\\\"players\\\"] = []\\n self.spatial_map[key][\\\"items\\\"] = []\\n\\n #For each object place a reference to them inside each tile they overlap\\n for obj in objects:\\n self.update_single_obj(obj)\\n \\n for player in players:\\n self.update_single_player(player)\\n\\n for attack in attacks:\\n self.update_single_att(attack)\\n\\n for item in items:\\n self.update_single_item(item)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2b63135918dde00f4bf19df5a21c549b\",\n \"score\": \"0.5428709\",\n \"text\": \"def update( ):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ab42acbae32976a01f94a19c2e3dc505\",\n \"score\": \"0.54275686\",\n \"text\": \"def update_track_data(self):\\n if self.interactive_cell is not None:\\n print(\\\"updating the data structure\\\")\\n print(self.trackdata.get_cell_params(self.current_image, self.current_cell_id))\\n properties = self.interactive_cell.get_position_props()\\n print(properties)\\n self.trackdata.set_cell_properties(self.current_image, self.current_cell_id, properties)\\n print(self.trackdata.get_cell_params(self.current_image, self.current_cell_id))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a38e56cca0ea7476dd3d740729a1cb73\",\n \"score\": \"0.54199016\",\n \"text\": \"def update(self):\\n\\n if self.states[PROP_VIEW] == STATE_OVERVIEW: # the worldmap\\n if self.states[PROP_UPDATE_MAIN]: # if the main view is being updated\\n self.main_view.set_img(self.game.overview_map) # set the view to the worldmap\\n self.gm_view.set_img(self.game.overview_map_dm) # set the view to the worldmap\\n elif self.states[PROP_VIEW] == STATE_MAPVIEW: # view a map\\n # calculate zoom and translation parameters for the main_view\\n params = {\\\"fow\\\": \\\"tv\\\"} # the parameters that will be asked for in the image. fow will be a nice rendering\\n if self.states[PROP_ZOOM] != 1:\\n params[\\\"zoom\\\"] = self.states[PROP_ZOOM]\\n if self.states[PROP_TRANS_X]:\\n params[\\\"trans_x\\\"] = self.states[PROP_TRANS_X]\\n if self.states[PROP_TRANS_Y]:\\n params[\\\"trans_y\\\"] = self.states[PROP_TRANS_Y]\\n\\n if self.states[PROP_SHOW_TOKEN]:\\n params[\\\"tokens\\\"] = True\\n\\n # only update main if allowed\\n if self.states[PROP_UPDATE_MAIN]:\\n self.main_view.set_img(self.game.curr_map().get_img(**params))\\n\\n # now that the main view is updated start changing the parameters to suit the gm view\\n if self.states[PROP_UPDATE_MAIN]:\\n params[\\\"border\\\"] = True\\n if self.states[PROP_GM_VIEW] == STATE_PREVIEW: # preview is almost the image the main map shows + border\\n self.gm_view.set_img(self.game.curr_map().get_img(**params))\\n elif self.states[PROP_GM_VIEW] == STATE_NORMAL: # normal gm view\\n # add fow param for the gm's view\\n if self.states[PROP_GRIDLINES]:\\n params[\\\"gridlines\\\"] = True\\n params[\\\"fow\\\"] = \\\"gm\\\"\\n params[\\\"dm\\\"] = True\\n params[\\\"tokens\\\"] = True\\n self.gm_view.set_img(self.game.curr_map().get_img(**params)) # get image and set view\\n\\n # actually show the images created\\n self.gm_view.show(\\\"gm\\\")\\n self.main_view.show(\\\"main\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9878dbf2b0d57bd216906e2ddd16cb82\",\n \"score\": \"0.5416527\",\n \"text\": \"def update_geometry(self):\\r\\n \\r\\n self.__e2p_horz_marg, self.__e2p_vert_marg,\\\\\\r\\n self.__p2l_horz_marg, self.__p2p_gap, self.__p2n_gap,\\\\\\r\\n self.__port_size, self.__l2n_gap = self.__geo_prop\\r\\n\\r\\n self.update_block()\\r\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4e266d338fe2cfb9910cdae67992f45c\",\n \"score\": \"0.5414993\",\n \"text\": \"def updateGrid(self, shape):\\r\\n testing = find_max_score_location(self, shape)\\r\\n location = testing[2]\\r\\n fits = testing[0]\\r\\n numRotations = testing[1]\\r\\n while numRotations:\\r\\n shape.rotate90()\\r\\n numRotations -= 1\\r\\n for row in range(len(shape.squares)):\\r\\n for col in range(len(shape.squares[0])):\\r\\n if shape.squares[row][col] == True:\\r\\n self.squares[location[0] + row][location[1] + col] = True\\r\\n self.print()\\r\\n return fits\",\n \"title\": \"\"\n },\n {\n \"docid\": \"72820f98bcdbd7300373cfc703cf6249\",\n \"score\": \"0.54123235\",\n \"text\": \"def refresh_2D(self, width, height):\\n glViewport(0, 0, width, height)\\n glMatrixMode(GL_PROJECTION)\\n glLoadIdentity()\\n glOrtho(0.0, width, height, 0.0, -1.0, 1.0)\\n glMatrixMode(GL_MODELVIEW)\\n glLoadIdentity()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"292b387c73ce85b26f2b482af1dff071\",\n \"score\": \"0.54103035\",\n \"text\": \"def run_world_simulation(self, world, generation, one_loc=None):\\n draw_path = '{}gen{}/world'.format(self.path, generation)\\n if one_loc:\\n one_agent = self.world.agents[one_loc]\\n draw_path = '{}gen{}/agent-i{}/world'.format(self.path, generation, one_agent.private_id)\\n draw_ext = '.png'\\n if self.draw:\\n self.view.draw(world)\\n self.view.save(draw_path+'0'+draw_ext)\\n # print('max_time: {}'.format(self.max_time))\\n for t in range(1, self.max_time):\\n self.update(world)\\n if self.draw:\\n self.view.save(draw_path+str(t)+draw_ext)\\n with open((draw_path+str(t)+'-comm.csv'), 'w') as f:\\n f.write('\\\\n'.join([str(x) for x in world.comms]))\\n self.num_comms += len(world.comms)\\n world.comms = []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c5ea5f507d0b9be50788171e887c8995\",\n \"score\": \"0.54042923\",\n \"text\": \"def update_house(self, house, points):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aa51267cc8dcfe6b3eb332e78ec729c0\",\n \"score\": \"0.54038113\",\n \"text\": \"def __init__(self, lifespan=None): \\n Grid_2D_World.__init__(self, lifespan)\\n self.name = 'grid_2D_dc'\\n self.name_long = 'decoupled two dimensional grid world'\\n print \\\"--decoupled\\\"\\n self.num_sensors = self.world_size * 2\\n self.VISUALIZE_PERIOD = 10 ** 3\\n self.display_state = False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7e104119c0f5c4b592a26de9a22b112c\",\n \"score\": \"0.54023683\",\n \"text\": \"def update_scene(self):\\n\\n self.update_programs_projection_matrix()\\n self.update_programs_view_matrix()\\n self.update_programs_world_matrix()\\n if self.ctrl:\\n self.update_cursor_data()\\n self.glDraw()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aa8b482d13bca78d63790cc20dc94fb9\",\n \"score\": \"0.5402059\",\n \"text\": \"def tick(self):\\n for world_object in self.objects:\\n world_object.tick(self.tick_length)\\n self.time += self.tick_length\",\n \"title\": \"\"\n },\n {\n \"docid\": \"66403dc28195279d2d3088308df283e7\",\n \"score\": \"0.54001397\",\n \"text\": \"def update(self, object_):\\n raise NotImplementedError()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1232dc9540edd7787a03a32b67628ce8\",\n \"score\": \"0.5397368\",\n \"text\": \"def update_window(self):\\n # Update robot position\\n self.r1.update_window()\\n self.r2.update_window()\\n self.r3.update_window()\\n\\n # now update the OpenGL graphics in window\\n self.view3D.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"df6f23fddcb85ba97dcaeb9ed9a7489d\",\n \"score\": \"0.5393906\",\n \"text\": \"def update(self):\\n self.robot.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0d5cd273b650ad21a37108b8eda17554\",\n \"score\": \"0.53879035\",\n \"text\": \"def regenerate_surface(self):\\n for x in xrange(0, self.gridWidth):\\n for y in xrange(0, self.gridHeight):\\n self.update_square((x, y, self.view.z))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"eca5925f4dfe86b42b1ab32e44737d6f\",\n \"score\": \"0.53785145\",\n \"text\": \"def update():\\n\\n\\tglobal START, END\\n\\n\\tfor i in range(ROWS):\\n\\t\\tfor j in range(COLS):\\n\\n\\t\\t\\tif GRID[i][j].rect.collidepoint(pygame.mouse.get_pos()[0], pygame.mouse.get_pos()[1]):\\n\\t\\t\\t\\tkeys = pygame.key.get_pressed()\\n\\n\\t\\t\\t\\tif keys[pygame.K_s] and not GRID[i][j].isEnd:\\n\\t\\t\\t\\t\\tsetStart(i, j)\\n\\n\\t\\t\\t\\telif keys[pygame.K_e] and not GRID[i][j].isStart:\\n\\t\\t\\t\\t\\tsetEnd(i, j)\\n\\n\\t\\t\\tGRID[i][j].update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"42e1433ce749544a15aa95c21da63a5f\",\n \"score\": \"0.5366284\",\n \"text\": \"def test_update(self):\\n square = Square(5)\\n square.update()\\n square.update(1, 2, y=3)\\n square.update(1, 12, id=4)\\n square.update(size=2, y=5)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e29da65f264ecaa6bf4014a7e51d8354\",\n \"score\": \"0.53635085\",\n \"text\": \"def _update_state(self, obs_dict):\\n self.x = obs_dict['poses_x'][obs_dict['ego_idx']]\\n self.y = obs_dict['poses_y'][obs_dict['ego_idx']]\\n\\n self.theta = obs_dict['poses_theta'][obs_dict['ego_idx']]\\n self.in_collision = obs_dict['collisions'][obs_dict['ego_idx']]\\n self.collision_angle = obs_dict['collision_angles'][obs_dict['ego_idx']]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1ece8315b242490ae55390b9e2366a49\",\n \"score\": \"0.5356332\",\n \"text\": \"def updatePositions(self):\\r\\n for body in self.smallBodies+self.largeBodies:\\r\\n body.pos += body.velocity*self.dt\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b6994c9fd53b5c09e7e66dde3832e274\",\n \"score\": \"0.53509086\",\n \"text\": \"def move_obj(self, move_x, move_y):\\r\\n self.wall_list.update(move_x, move_y)\\r\\n self.door_list.update(move_x, move_y)\\r\\n self.coin_list.update(move_x, move_y)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cba6d4f75eac09baf930bc0a050738d5\",\n \"score\": \"0.53463733\",\n \"text\": \"def update(self):\\n\\t\\tself.active_sprite_list.update()\\n\\t\\tfireball.Fireball.all_fireballs.update()\\n\\t\\tself.score_board.update()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8f0cea03788b385805f747817ce4cd5a\",\n \"score\": \"0.53455746\",\n \"text\": \"def _update_geos(self):\\n # globe\\n self._fig.update_geos(\\n row=2,\\n col=1,\\n showland=False,\\n showcountries=False,\\n showocean=False,\\n showcoastlines=False,\\n showframe=False,\\n showrivers=False,\\n showlakes=False,\\n showsubunits=False,\\n bgcolor=\\\"rgba(0,0,0,0)\\\",\\n projection=dict(type=self.projection, rotation=dict(lon=0, lat=0, roll=0)),\\n lonaxis=dict(showgrid=True, gridcolor=\\\"rgb(102, 102, 102)\\\", gridwidth=1),\\n lataxis=dict(showgrid=True, gridcolor=\\\"rgb(102, 102, 102)\\\", gridwidth=1),\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c0cabb3c24dc1a92eeb199d14a0eaa45\",\n \"score\": \"0.53441733\",\n \"text\": \"def do_it(self):\\r\\n # First find EPSG-ID for the CRS\\r\\n sql = r\\\"\\\"\\\"SELECT srid FROM geometry_columns where f_table_name = 'obs_points'\\\"\\\"\\\"\\r\\n ConnectionOK, result = utils.sql_load_fr_db(sql)\\r\\n EPSGID= str(result[0][0])\\r\\n #Then do the operation\\r\\n sql = r\\\"\\\"\\\"Update or ignore 'obs_points' SET Geometry=MakePoint(east, north, \\\"\\\"\\\"\\r\\n sql += EPSGID\\r\\n sql += \\\"\\\"\\\") WHERE obsid IN \\\"\\\"\\\" + self.sqlpart2\\r\\n utils.sql_alter_db(sql)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ab8104a66e11aa40aa274007683334ef\",\n \"score\": \"0.5338825\",\n \"text\": \"def get_grid_obs(self):\\n self.get_map()\\n if not self.finalized:\\n self.add_objs_to_map()\\n self.grid = [''.join(x) for x in self.map]\\n\\n return self.grid\",\n \"title\": \"\"\n },\n {\n \"docid\": \"494638ef20dbefa8eadf604666927a82\",\n \"score\": \"0.5332123\",\n \"text\": \"def _write_grid(self, rr_graph):\\n\\n grid_locs = rr_graph.grid.init('gridLocs', len(self.graph.grid))\\n for out_grid_loc, grid_loc in zip(grid_locs, self.graph.grid):\\n out_grid_loc.x = grid_loc.x\\n out_grid_loc.y = grid_loc.y\\n out_grid_loc.blockTypeId = grid_loc.block_type_id\\n out_grid_loc.widthOffset = grid_loc.width_offset\\n out_grid_loc.heightOffset = grid_loc.height_offset\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f737f468202e354adc13cb16f314c686\",\n \"score\": \"0.5331146\",\n \"text\": \"def updateWorld(msg):\\n global X, V, orientation\\n X = np.array([float(msg.pose[1].position.x), float(msg.pose[1].position.y)])\\n V = np.array([float(msg.twist[1].linear.x), float(msg.twist[1].linear.y)])\\n orientation = np.arctan2(2 * float(msg.pose[1].orientation.w) * float(msg.pose[1].orientation.z), \\\\\\n 1 - 2 * float(msg.pose[1].orientation.z)**2)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"41200d1aea434dd8554b8745d4687109\",\n \"score\": \"0.532805\",\n \"text\": \"def update(self):\\n old_coords = self.coords\\n new_coords = (old_coords[0] + self.direction['H'] * self.speed[0],\\n old_coords[1] + self.direction['V'] * self.speed[1])\\n self.coords = new_coords\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3a8f4c6a40855cdbd0576aafa89ee391\",\n \"score\": \"0.53174084\",\n \"text\": \"def __init__(self, env, width, height, min_reward, max_reward): \\n self.env = env\\n self.width = width\\n self.height = height\\n self.min_reward = min_reward\\n self.max_reward = max_reward\\n \\n self.root_window = Tkinter.Tk()\\n self.root_window.title(\\\"Gridworld Visualisation\\\")\\n self.root_window.geometry(str(width)+\\\"x\\\"+str(height)+\\\"+200+200\\\")\\n self.root_window.resizable(0, 0)\\n \\n self.canvas = Tkinter.Canvas(self.root_window, width=width, height=height)\\n self.canvas.pack(fill=Tkinter.BOTH, expand=1)\\n \\n self.grid_x_inc = float(self.width) / self.env.width\\n self.half_grid_x_inc = self.grid_x_inc / 2.0\\n self.grid_y_inc = float(self.height) / self.env.height\\n self.half_grid_y_inc = self.grid_y_inc / 2.0\\n \\n self.h_lines = []\\n for l in xrange(self.env.height):\\n pos = l * self.grid_y_inc\\n self.h_lines.append(self.canvas.create_line(0, pos, self.width, pos,\\n fill=LINE_COLOR))\\n \\n self.v_lines = []\\n for l in xrange(self.env.width):\\n pos = l * self.grid_x_inc\\n self.v_lines.append(self.canvas.create_line(pos, 0, pos, self.height,\\n fill=LINE_COLOR))\\n \\n self.Q_values = {}\\n for state in xrange(self.env.num_states):\\n x, y = self.state_to_pos(state)\\n x_pos = x * self.grid_x_inc\\n y_pos = y * self.grid_y_inc\\n #up\\n self.Q_values[(state, \\\"up\\\")] = self.canvas.create_polygon(\\\\\\n x_pos+Q_TRIANGLE_BORDER,\\n y_pos+Q_TRIANGLE_BORDER, \\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\\n y_pos+Q_TRIANGLE_BORDER,\\n x_pos+self.half_grid_x_inc,\\n y_pos+Q_TRIANGLE_PERCENT*self.half_grid_y_inc,\\n fill=\\\"blue\\\")\\n #down\\n self.Q_values[(state, \\\"down\\\")] = self.canvas.create_polygon(\\\\\\n x_pos+Q_TRIANGLE_BORDER,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1, \\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1,\\n x_pos+self.half_grid_x_inc,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_PERCENT*self.half_grid_y_inc,\\n fill=\\\"blue\\\")\\n #left\\n self.Q_values[(state, \\\"left\\\")] = self.canvas.create_polygon(\\\\\\n x_pos+Q_TRIANGLE_BORDER,\\n y_pos+Q_TRIANGLE_BORDER,\\n x_pos+Q_TRIANGLE_BORDER,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1,\\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\\n y_pos+self.half_grid_y_inc,\\n fill=\\\"blue\\\")\\n #right\\n self.Q_values[(state, \\\"right\\\")] = self.canvas.create_polygon(\\\\\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\\n y_pos+Q_TRIANGLE_BORDER,\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1,\\n x_pos+self.grid_x_inc-Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\\n y_pos+self.half_grid_y_inc,\\n fill=\\\"blue\\\")\\n \\n self.greedy_policy = {}\\n for state in xrange(self.env.num_states):\\n x, y = self.state_to_pos(state)\\n x_pos = x * self.grid_x_inc\\n y_pos = y * self.grid_y_inc\\n #up\\n self.greedy_policy[(state, \\\"up\\\")] = self.canvas.create_polygon(\\\\\\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*G_OUTER_PERCENT,\\n y_pos+Q_TRIANGLE_BORDER, \\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*G_OUTER_PERCENT,\\n y_pos+Q_TRIANGLE_BORDER,\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*G_INNER_PERCENT,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*G_INNER_PERCENT,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\\n fill=G_COLOR, state=Tkinter.HIDDEN)\\n #down\\n self.greedy_policy[(state, \\\"down\\\")] = self.canvas.create_polygon(\\\\\\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*G_OUTER_PERCENT,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1, \\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*G_OUTER_PERCENT,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1,\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*G_INNER_PERCENT,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*G_INNER_PERCENT,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\\n fill=G_COLOR, state=Tkinter.HIDDEN)\\n #left\\n self.greedy_policy[(state, \\\"left\\\")] = self.canvas.create_polygon(\\\\\\n x_pos+Q_TRIANGLE_BORDER,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*G_OUTER_PERCENT,\\n x_pos+Q_TRIANGLE_BORDER,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*G_OUTER_PERCENT,\\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*G_INNER_PERCENT,\\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*G_INNER_PERCENT,\\n fill=G_COLOR, state=Tkinter.HIDDEN)\\n #right\\n self.greedy_policy[(state, \\\"right\\\")] = self.canvas.create_polygon(\\\\\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*G_OUTER_PERCENT,\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*G_OUTER_PERCENT,\\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*G_INNER_PERCENT,\\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*G_INNER_PERCENT,\\n fill=G_COLOR, state=Tkinter.HIDDEN)\\n \\n self.actions_taken = {}\\n for state in xrange(self.env.num_states):\\n x, y = self.state_to_pos(state)\\n x_pos = x * self.grid_x_inc\\n y_pos = y * self.grid_y_inc\\n #up\\n self.actions_taken[(state, \\\"up\\\")] = self.canvas.create_polygon(\\\\\\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*T_OUTER_PERCENT,\\n y_pos+Q_TRIANGLE_BORDER, \\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*T_OUTER_PERCENT,\\n y_pos+Q_TRIANGLE_BORDER,\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*T_INNER_PERCENT,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*T_INNER_PERCENT,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\\n fill=T_TRIANGLE_COLOR, state=Tkinter.HIDDEN)\\n #down\\n self.actions_taken[(state, \\\"down\\\")] = self.canvas.create_polygon(\\\\\\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*T_OUTER_PERCENT,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1, \\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*T_OUTER_PERCENT,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1,\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1-self.half_grid_x_inc*T_INNER_PERCENT,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\\n x_pos+Q_TRIANGLE_BORDER+self.half_grid_x_inc*T_INNER_PERCENT,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc,\\n fill=T_TRIANGLE_COLOR, state=Tkinter.HIDDEN)\\n #left\\n self.actions_taken[(state, \\\"left\\\")] = self.canvas.create_polygon(\\\\\\n x_pos+Q_TRIANGLE_BORDER,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*T_OUTER_PERCENT,\\n x_pos+Q_TRIANGLE_BORDER,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*T_OUTER_PERCENT,\\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*T_INNER_PERCENT,\\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*T_INNER_PERCENT,\\n fill=T_TRIANGLE_COLOR, state=Tkinter.HIDDEN)\\n #right\\n self.actions_taken[(state, \\\"right\\\")] = self.canvas.create_polygon(\\\\\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*T_OUTER_PERCENT,\\n x_pos+self.grid_x_inc-Q_TRIANGLE_BORDER+1,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*T_OUTER_PERCENT,\\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\\n y_pos+self.grid_y_inc-Q_TRIANGLE_BORDER+1-self.half_grid_y_inc*T_INNER_PERCENT,\\n x_pos+Q_TRIANGLE_PERCENT*self.half_grid_x_inc,\\n y_pos+Q_TRIANGLE_BORDER+self.half_grid_y_inc*T_INNER_PERCENT,\\n fill=T_TRIANGLE_COLOR, state=Tkinter.HIDDEN)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"81199972fa288a30be57e9729209e64d\",\n \"score\": \"0.531061\",\n \"text\": \"def update_plants(self,surface):\\n for plant in self.plants:\\n plant.update(surface,self.current_time)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fee6404df206f5541c3e32c0ad1f55d2\",\n \"score\": \"0.5310382\",\n \"text\": \"def update_map(self, grid_map, pose, scan):\\n\\n # Current yaw of the robot\\n robot_yaw = self.get_yaw(pose.pose.orientation)\\n # The origin of the map [m, m, rad]. This is the real-world pose of the\\n # cell (0,0) in the map.\\n origin = grid_map.get_origin()\\n # The map resolution [m/cell]\\n resolution = grid_map.get_resolution()\\n \\n \\n \\\"\\\"\\\"\\n print(\\\"das sind die Pose- Werte: \\\" +str(pose))\\n \\n a = True\\n if a == True:\\n print(\\\"das sind die grid- Werte: \\\" +str(grid_map)) \\n a = False\\n \\\"\\\"\\\"\\n x_list = []\\n y_list = []\\n #x_y_list = []\\n occupied_cells = []\\n \\n \\n for i in range(len(scan.ranges)):\\n \\n if scan.ranges[i] > scan.range_min and scan.ranges[i] < scan.range_max:\\n \\n x = (scan.ranges[i] * cos(robot_yaw + (scan.angle_min + scan.angle_increment * i))) + pose.pose.position.x - origin.position.x\\n \\n y = (scan.ranges[i] * sin(robot_yaw + (scan.angle_min + scan.angle_increment * i))) + pose.pose.position.y - origin.position.y\\n \\n #x and y end index\\n \\n x = int(x / resolution) \\n y = int(y / resolution)\\n \\n occupied_cells.append([x,y])\\n \\n \\n #mark as free\\n \\n starting_x = int((pose.pose.position.x - origin.position.x) / resolution)\\n \\n starting_y = int((pose.pose.position.y - origin.position.y) / resolution) \\n \\n start = [starting_x, starting_y]\\n \\n end = [x,y] \\n \\n traversed = self.raytrace(start, end)\\n \\n \\n for i in traversed:\\n \\n self.add_to_map(grid_map, i [0], i [1],self.free_space)\\n \\n if self.is_in_bounds(grid_map, i[0], i[1]):\\n \\n x_list.append(i[0])\\n \\n y_list.append(i[1])\\n \\n #x_y_list.append([i[0],i[1],self.free_space]) \\n \\n \\n #x and y end index add to list\\n #x_list.append(x)\\n \\n \\n #mark as occupied\\n \\n for i in range(len(occupied_cells)):\\n \\n self.add_to_map(grid_map,occupied_cells [i][0], occupied_cells [i] [1],self.occupied_space) \\n \\n #if self.is_in_bounds(grid_map,occupied_cells [i][0], occupied_cells [i][1]):\\n \\n #x_list.append(occupied_cells [i][0])\\n \\n #y_list.append(occupied_cells [i][1])\\n \\n #x_y_list.append([occupied_cells [i][0],occupied_cells [i][1],self.occupied_space])\\n \\n \\n #x_y_list.sort()\\n \\n data = []\\n \\n # Only get the part that has been updated\\n update = OccupancyGridUpdate()\\n \\n # The minimum x index in 'grid_map' that has been updated\\n update.x = min(x_list)\\n \\n # The minimum y index in 'grid_map' that has been updated\\n update.y = min(y_list)\\n \\n # Maximum x index - minimum x index + 1\\n update.width = max(x_list) - min(x_list) + 1\\n #print(\\\"Breite des Rechtecks: \\\" +str(update.width))\\n \\n # Maximum y index _map- minimum y index + 1\\n update.height = max(y_list) - min(y_list) + 1\\n \\n #print(\\\"Hoehe des Rechtecks: \\\" +str(update.height))\\n # The map data inside the rectangle, in row-major order.\\n \\n for h in range(update.height):\\n \\n for i in range(update.width):\\n \\n data.append(grid_map[update.x + i, update.y + h])\\n \\n update.data = data\\n #print(\\\"das sind die Daten: \\\" +str(data))\\n \\n return grid_map, update\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a03074f42a860d470e4816b8ac49a385\",\n \"score\": \"0.53102237\",\n \"text\": \"def updateVS(db):\\n# graph = get_graph(db)\\n mesh = get_mesh(db)\\n pos = db.get_property('position')\\n wall = db.get_property('wall')\\n scale = db.get_property('scale_px_to_micron')\\n\\n if mesh.degree()==3:\\n\\t # Area of each cell\\n\\t V = refresh_property(db, 'V')\\n\\t for cid in mesh.wisps(3):\\n\\t\\tV[cid]=scale[0]*scale[0]*scale[0]*cell_volume(mesh, pos, cid)\\n \\n\\t # Lengths of each wall\\n\\t S = refresh_property(db, 'S')\\n\\t for wid in mesh.wisps(2):\\n\\t\\tS[wid] = scale[0]*scale[0]*face_surface_3D(mesh, pos, wid)\\n\\n if mesh.degree()==2:\\n\\t # Area of each cell\\n\\t V = refresh_property(db, 'V')\\n\\t for cid in mesh.wisps(2):\\n\\t\\tV[cid]=scale[0]*scale[0]*face_surface_2D(mesh, pos, cid)\\n\\n\\t \\n\\t # Lengths of each wall\\n\\t S = refresh_property(db, 'S')\\n\\t for wid in mesh.wisps(1):\\n\\t\\tS[wid] = scale[0]*edge_length(mesh, pos, wid)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"13bc3a224e18c196b6ad30e173f22528\",\n \"score\": \"0.53061366\",\n \"text\": \"def updatePixelCoords( self ):\\r\\n print 'in Movable\\\\'s updatePixelCoords'\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":394,"cells":{"query_id":{"kind":"string","value":"fe15a1a597b13a43456fd8bdf2a252fd"},"query":{"kind":"string","value":"rejects a nonnumeric input of \"foo\""},"positive_passages":{"kind":"list like","value":[{"docid":"1232bc5326ddca1da44076edffbc92a9","score":"0.0","text":"def test_reject_foo():\n check50.run(\"python3 cash.py\").stdin(\"foo\").reject()","title":""}],"string":"[\n {\n \"docid\": \"1232bc5326ddca1da44076edffbc92a9\",\n \"score\": \"0.0\",\n \"text\": \"def test_reject_foo():\\n check50.run(\\\"python3 cash.py\\\").stdin(\\\"foo\\\").reject()\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"eb8de4b095347f3422d0d8ab42c05c67","score":"0.6866605","text":"def check(param):\n try:\n param = float(param)\n\n except ValueError:\n print(\"Incorrect input \\\"%s\\\". Must be number.\" % param)","title":""},{"docid":"a6ba2276e2f4248e8994b8cae14a2c63","score":"0.6722084","text":"def is_numeric(form, field):\n data = str(field.data)\n if data.isalpha():\n raise ValidationError(message_is_numeric)","title":""},{"docid":"c8fc4d6d231bb1139f1bf85d09b3d578","score":"0.667467","text":"def check_numeric(arg):\n while True:\n try:\n entry = float(input(arg))\n if entry < 0:\n raise ValueError\n else:\n return entry\n\n except ValueError:\n print(\"Entries must be positive and numeric\")","title":""},{"docid":"79c55c128ca5194b60f902f99d0295eb","score":"0.66200054","text":"def number_or_exit(s, msg):\n isNumber = r'^[1-9][0-9]*\\.?[0-9]*([Ee][+-]?[0-9]+)?$';\n\n if not re.search(isNumber, s):\n print(\"Error: the {} argument must be a number\".format(msg))\n exit_with_usage()","title":""},{"docid":"a980ed468489ba0d4901ce4ee2656340","score":"0.6596289","text":"def _validate(number):\n # Validate Input\n if type(number) == str: # If it is a string, make sure it is digits \n if isdigit(number): number\n else:\n print(\"Verify that your imput consists of the digits 0 thru 9. Your input: \", number)\n return -1 #Bad Input\n elif type(number) == int: # It is an integer value, convert to string\n number = str(number)\n return number","title":""},{"docid":"c99873a99c3fd87e380a2a66255007a7","score":"0.6582099","text":"def validate_number(input_data):\n if input_data.startswith('-'):\n return input_data[1:].isdigit()\n return input_data.isdigit()","title":""},{"docid":"8af4ea160899d993701c988a55ee70a5","score":"0.6551377","text":"def numeric_validation(entry):\n while True:\n try:\n entry = int(entry)\n break\n except ValueError:\n entry = input(\"Please enter a valid integer: \")\n return entry","title":""},{"docid":"66f277376594f176feb9d7b76047ed4d","score":"0.64648896","text":"def validate_amount(amount):\n\n try:\n amount = float(amount)\n\n if amount < 0:\n raise argparse.ArgumentTypeError(\"Amount value should be a non-negative value.\")\n\n if math.isnan(amount) or math.isinf(amount):\n raise argparse.ArgumentTypeError(\"Amount value is not a number.\")\n\n except ValueError:\n raise\n\n return amount","title":""},{"docid":"517ed8a6bd6069985c38912f743da2a0","score":"0.6449597","text":"def validate_float(user_input): \r\n try:\r\n return float(user_input)\r\n except:\r\n print(\"\\nPlease enter a real number.\")\r\n return \"invalid_input\"","title":""},{"docid":"f972af5a797c3e414fadedf5ad628bf3","score":"0.64454305","text":"def test_wrong_type_integer_input(self):\n\n number = get_integer_input(\"Integer Number\")\n self.assertNotEqual(type(number), str)","title":""},{"docid":"f731f9c460e778127dca9278eb407034","score":"0.644076","text":"def test_convert_nonnumeric_value(self):\n with pytest.raises(TypeError):\n pressure_util.convert('a', PRESSURE_HPA, PRESSURE_INHG)","title":""},{"docid":"08415286648c0f8b4fd7378180d1022c","score":"0.6374627","text":"def isnumeric(input):\n # 2016-01-20 11:48 IJMC: Created\n try:\n junk = float(input) + 0.\n ret = True\n except:\n ret = False\n return ret","title":""},{"docid":"f4d68c992af47b38e44ca5f87e11dd4c","score":"0.63367385","text":"def raise_not_number(x):\n try:\n float(x)\n except ValueError:\n raise SizeError('Must pass a number, received {}'.format(x))","title":""},{"docid":"c9a902cb7cb025889c5c1206d35dfcec","score":"0.63094205","text":"def validate_num(\r\n num: Union[int, float, Int, Number]) -> None:\r\n from apysc.type.number_value_interface import NumberValueInterface\r\n if isinstance(\r\n num,\r\n (int, float, NumberValueInterface)):\r\n return\r\n raise ValueError(\r\n f'Specified value is not iteger or float type: {num}'\r\n f'({type(num)})')","title":""},{"docid":"207bcec40f3cdc3d1569bac10afc1e9c","score":"0.6236718","text":"def opcion_valida(opcion: str) -> int:\n while not opcion.isnumeric() or int(opcion) < 1 or int(opcion) > 8:\n opcion = input(\"Ingrese una opcion correcta: \")\n opcion = int(opcion)\n return opcion","title":""},{"docid":"fcd0eb6c674273e8e9284f93193ea558","score":"0.6201344","text":"def is_numeric(input_str):\n\n try:\n float(input_str)\n return True\n except ValueError:\n return False","title":""},{"docid":"06a32c66bfcb03036a23a34f571bf94e","score":"0.61735827","text":"def ask(question, valueType):\n while True:\n try:\n answer = valueType(raw_input(question))\n if answer < 0:\n raise ValueError\n return answer\n except ValueError:\n if valueType == int:\n print \" ^ Enter a positive whole number...\"\n else:\n print \" ^ Enter a positive number...\"","title":""},{"docid":"0d594095e6f520a42448be4069e66e01","score":"0.6124916","text":"def test_if_it_accepts_float_numbers_are_accepted(self):\n with self.assertRaises(TypeError):\n primenum(56.58)","title":""},{"docid":"f789770989c157819bc10916e71cd027","score":"0.61225647","text":"def check_input(valid_number): # function which checks all user input, whether it is valid (whole positive numbers) or invalid\n value = None\n while not value: # creates a loop so it will keep going till user input is valid \n value = input(valid_number)\n if not value.isnumeric(): # if input is not a number\n print(\"Please enter a valid number\")\n print(\"\\n\")\n value = None\n else:\n return int(value) # once a correct number is entered the number is returned and program contiues","title":""},{"docid":"0b28f9f30b6419dace166792ce48baad","score":"0.6111065","text":"def test_phone_parser_wrong_input(self):\r\n invalid = ('66867867', '', 668678678)\r\n for num in invalid:\r\n self.assertRaises(WrongInput, phone_parser, num)","title":""},{"docid":"7ee45eeda94b9d8da93bfdc5770097a7","score":"0.6106006","text":"def validate_numeric_scalar(var: Any) -> bool:\n assert isinstance(var, (int, float)), \"Argument must be single numeric value\"\n return var","title":""},{"docid":"952e4bda8e3e4f0002b89bf61c64789d","score":"0.6091906","text":"def is_number(num):\n try:\n int(num)\n except:\n print('Only enter numbers')\n return False\n return True","title":""},{"docid":"6146a4fc89cbad85b94fc25599723c26","score":"0.60882956","text":"def test_input_with_other_char_than_numbers(self):\n input_with_letter = \"12A456789\"\n input_with_special_char = \"1234567+9\"\n self.assertEqual(input_is_valid(input_with_letter), False)\n self.assertEqual(input_is_valid(input_with_special_char), False)","title":""},{"docid":"56ac19df2aa65ded6074ee395cad9ca0","score":"0.6079081","text":"def validate_input(input, opts):\n if not input.isnumeric():\n return False\n n = int(input)\n # Valid indices start at 1.\n if 0 >= n or len(opts) < n:\n return False\n return True","title":""},{"docid":"5d8d4673526ee08d47a7128dde99336f","score":"0.6073587","text":"def test_bad_numeric(self):\n with pytest.raises(UnwrapFailedError):\n assert self._get(123).unwrap() # noqa: Z432","title":""},{"docid":"5d8d4673526ee08d47a7128dde99336f","score":"0.6073587","text":"def test_bad_numeric(self):\n with pytest.raises(UnwrapFailedError):\n assert self._get(123).unwrap() # noqa: Z432","title":""},{"docid":"007c7331fbe2f3cd681e1816b05474ec","score":"0.60536397","text":"def valid_number(data_in):\n\n try:\n data_out = float(data_in)\n except ValueError:\n data_out = np.nan\n return data_out","title":""},{"docid":"c98c9aa97a845f00394863b636045a4d","score":"0.6045029","text":"def clean_price(price_str):\n try:\n try:\n price_float = float(price_str)\n except ValueError:\n price_float = float(price_str[1:])\n\n except ValueError:\n input('''\n \\n***** PRICE ERROR *****\n \\rThe Price should be a number without a currency label.\n \\rEx: 5.99\n \\rPress enter to try again.\n \\r**********************''')\n return\n else:\n return int(price_float * 100)","title":""},{"docid":"14fdc92dd81e78350604bad01db769a1","score":"0.6037946","text":"def number_check(num_, len_, name):\r\n valid = True\r\n error_message = \"\"\r\n if not isinstance(num_, str):\r\n valid = False\r\n error_message = f\"Input for {name} should be string\"\r\n elif len(num_) > len_:\r\n error_message = f\"Max len of {name} is 5 char\"\r\n valid = False\r\n elif num_ == \"\":\r\n valid = True\r\n error_message = \"\"\r\n elif not re.search(r\"[\\d]+[-\\/.]*[a-zA-Z]*\", num_):\r\n error_message = f\"{name} should be: [0-9][ - . /][ a-zA-Z]\"\r\n valid = False\r\n return (valid, error_message, num_)","title":""},{"docid":"c50f225ce7a6c2c0bbb43d961d11a695","score":"0.6022796","text":"def safeIntegerInput(prompt):\n inputString = input(prompt)\n try:\n number = int(inputString)\n return number\n except ValueError:\n print(\"Error in number format:\", inputString)\n return safeIntegerInput(prompt)","title":""},{"docid":"a74a3a2ef82c494c9641d148a4982235","score":"0.60155165","text":"def num_in(prompt):\n while True:\n try:\n return float(input(prompt))\n except ValueError:\n print(\"Please enter a number!\")","title":""},{"docid":"4fa113da113c983fc76d9e223a5e8bbc","score":"0.5977137","text":"def is_numeric(val):\n return isinstance(val, (int, float))","title":""},{"docid":"d6ed4019bbc35fd0532d27a0bb85c331","score":"0.59757483","text":"def _control_input_type(token: Any) -> None:\n\n if not isinstance(token, str):\n raise TypeError(f\"Wrong input type, expected string, got {type(token)}\")\n if token == \"\":\n raise ValueError(\"Wrong input type: empty string\")","title":""},{"docid":"b4b1c36b7ab629c340833b71e4c2a429","score":"0.59514385","text":"def valid_input(data_input):\n\n is_valid = False\n try:\n data_input = int(data_input)\n except ValueError:\n print(\"\"\"Vous n'avez pas saisi un nombre. Veuillez recommencer...\"\"\")\n else:\n is_valid = True\n\n return is_valid","title":""},{"docid":"244a938499385171cf96d9abd510b47b","score":"0.5948644","text":"def is_valid(candidate):\n if candidate.isalnum():\n if candidate.isalpha():\n retval = True, 'letter'\n else:\n retval = True, 'number'\n else:\n try:\n val = float(candidate)\n retval = True, 'number'\n except ValueError:\n retval = False, 'neither'\n return retval","title":""},{"docid":"7d7fd11c60fe458920c91fc3acfbceb6","score":"0.5946673","text":"def validate_input(input_val):\n try:\n float_input = float(input_val)\n return float_input\n except ValueError:\n return None","title":""},{"docid":"086eb11cb087707c1fe32284d9f874ee","score":"0.5944595","text":"def isNum(x):\n\treturn isfloat(x) or isint(x)","title":""},{"docid":"6c38583bc6449528fdbc08c7b8274a05","score":"0.59426284","text":"def is_numeric(value):\n return isinstance(value, int) or isinstance(value, float)","title":""},{"docid":"6c38583bc6449528fdbc08c7b8274a05","score":"0.59426284","text":"def is_numeric(value):\n return isinstance(value, int) or isinstance(value, float)","title":""},{"docid":"32f4f06874d843f6cf43c14f9d947e84","score":"0.59352654","text":"def test_with_non_numeric_nomor(self):\n form = self.form_data(\"ini non numeric\", 'p')\n self.assertFalse(form.is_valid())\n #get first form, and get nomor field.\n #then get it data with .as_data() method\n error = form[0]['nomor'].errors.as_data()[0]\n self.assertEqual(error.code, 'invalid input')","title":""},{"docid":"3d228631096be14c2a4b580eb8423272","score":"0.5913183","text":"def check_int_type(rep):\n try:\n rep = int(rep)\n except ValueError:\n print(\"Be carefull, a number is expected!\")\n sys.exit(2)\n if rep < 0:\n print(\"The number must be positive!\")\n sys.exit(2)\n return rep","title":""},{"docid":"7c068c3d073b28b614ee6b698c586cd4","score":"0.5906656","text":"def bad_input():\r\n print(\"Bad input, please try again\")","title":""},{"docid":"82a6dae82c98970ee01eeac8f5de7cbf","score":"0.5901525","text":"def validate_int_or_basestring(option, value):\r\n if isinstance(value, (int, long)):\r\n return value\r\n elif isinstance(value, basestring):\r\n if value.isdigit():\r\n return int(value)\r\n return value\r\n raise TypeError(\"Wrong type for %s, value must be an \"\r\n \"integer or a string\" % (option,))","title":""},{"docid":"1e69bfa53544896a15e4433b45768c98","score":"0.5899116","text":"def test_strip_nonnumeric(self):\n Valid = self.create_ValidIDs_class()\n Valid.strip_nonnumeric(keycol)\n assert False not in [\n isinstance(val.item(), int) for val\n in Valid.df[keycol].dropna().astype(int).values\n ]","title":""},{"docid":"b49e2a308c7622e07d6f1c1014cee935","score":"0.58989674","text":"def is_number_tryexcept(s):\n try:\n if s == 'nan':\n return False\n float(s)\n return True\n except ValueError:\n return False","title":""},{"docid":"b2b6a2303c6a7d7ab7fb619588d1e580","score":"0.58912516","text":"def valid(f):\n try: \n return not re.search(r'\\b0[0-9]', f) and eval(f) is True\n except ArithmeticError:\n return False","title":""},{"docid":"8862188df7f1d1ddce612604ae1542e3","score":"0.5882695","text":"def get_valid_number(question):\n value = input(question)\n valid = False\n while valid == False:\n try:\n while int(value) <= 0: # Reject values less than 0\n print('Number must be > 0')\n value = input(question)\n valid = True\n except ValueError: # Reject invalid values\n print('Invalid input; enter a valid number')\n value = input(question)\n return value","title":""},{"docid":"905eec86a710c1304b90a2cc01c7d6e7","score":"0.58655685","text":"def is_numeric(self, val):\n val = str(val)\n if val.isnumeric():\n print(\"Numeric\")\n return True\n else:\n print(\"Not numeric\")\n return False","title":""},{"docid":"ea11ed966a078ecd3aa1ed335d3c0c67","score":"0.5863097","text":"def test_validate_amount(self):\n\n self.assertEqual(util.validate_amount('1'), '1.00')\n self.assertEqual(util.validate_amount('10'), '10.00')\n self.assertEqual(util.validate_amount('10.'), '10.00')\n self.assertEqual(util.validate_amount('10.0'), '10.00')\n self.assertEqual(util.validate_amount('10.00'), '10.00')\n\n with self.assertRaises(ValueError):\n util.validate_amount('-')\n util.validate_amount('f')\n util.validate_amount('1f')\n util.validate_amount('10.f')\n util.validate_amount('10.0f')","title":""},{"docid":"cf3328ad448ad953a3e4b1d3ceaed1d7","score":"0.5861212","text":"def get_integer_input(message):\n\n value_as_string = input(message)\n while not value_as_string.isdecimal() and value_as_string.isnumeric():\n print('The Input must be an integer')\n value_as_string = input(message)\n\n return float(value_as_string)","title":""},{"docid":"4a781ea0eab1ed8d15d371a815601cc9","score":"0.5852245","text":"def enforce_some_alnum(value):\n \n if value:\n for c in value:\n x = ord(c)\n if lower_start <= x <= lower_end:\n return value\n elif upper_start <= x <= upper_end:\n return value\n elif digit_start <= x <= digit_end:\n return value\n \n msg = _('There must be at least one letter or digit.')\n raise forms.ValidationError(msg)","title":""},{"docid":"254de535a7d13248483ac8003bd1c840","score":"0.58470005","text":"def _isint(word):\n return match('^[-+]?[0-9]+$',word)","title":""},{"docid":"e2faf187d42b968c46984d1b9bcd654a","score":"0.58445674","text":"def _validate(value):\n\n try:\n return float(value)\n except ValueError as e:\n e.args = (e.args[0],'Value entered can not be convert to float')\n raise","title":""},{"docid":"7118996b6c317ffcb8f19950f81f5315","score":"0.58423126","text":"def is_numeric(str, func=float):\n try:\n i = func(str)\n except:\n return False\n return True","title":""},{"docid":"9b7cf775ad70be2dc5a918d7b559f974","score":"0.5841039","text":"def _replace_invalid(value):\n if isinstance(value, str):\n if 's' or '*' in value:\n value = np.nan\n return float(value)","title":""},{"docid":"aa05f720b7ccdd6827c3aa8c1ffd92ac","score":"0.58398867","text":"def valid(f):\r\n try: \r\n return not re.search(r'\\b0[0-9]', f) and eval(f) is True\r\n except ArithmeticError:\r\n return False","title":""},{"docid":"0741b12a6b2626793ab95e7d88625a84","score":"0.5838307","text":"def validate_integer(user_input): \r\n try:\r\n return int(user_input)\r\n except ValueError:\r\n print(\"\\nInvalid input, please enter an integer.\")\r\n return \"invalid_input\"","title":""},{"docid":"7a1eb50a845310f17a5b4b39db6aa2c5","score":"0.5822806","text":"def ensure_int(param):\n try:\n param = re.sub(\"\\W\", \"\", param)\n return int(param)\n except ValueError:\n return None","title":""},{"docid":"62bfe77285aa05c0cab1dab4a50aea20","score":"0.582152","text":"def _force_number(func):\n def validation_decorator(*args, **kwargs):\n params = list(args)\n for i, n in enumerate(params):\n\n if type(n) == list or type(n) == tuple:\n if len(n) == 0:\n params[i] = n = 0\n elif len(n) == 1:\n params[i] = n = n[0]\n\n if type(n) == str:\n if n == \"\":\n params[i] = n = 0\n continue\n\n if n is None:\n params[i] = 0\n continue\n\n if type(n) != float and type(n) != int:\n try:\n if '.' in n:\n params[i] = float(n)\n else:\n params[i] = int(n)\n except Exception:\n # raise ValueError(\"\")\n # js returns None instead\n pass\n\n args = tuple(params)\n try:\n return func(*args)\n except Exception:\n return None\n\n return validation_decorator","title":""},{"docid":"8a5c7c81bbf800b02b81fc24144ffcf3","score":"0.5821398","text":"def is_number_tryexcept(s):\n try:\n float(s)\n return True\n except ValueError:\n return False","title":""},{"docid":"ba71e4dc2c51cd441a00e9b06cef9b71","score":"0.57937133","text":"def is_num(text):\n try:\n float(text)\n except:\n return False\n else:\n return True","title":""},{"docid":"4d78e8957212dfcd9afdb9630e4907b1","score":"0.57752436","text":"def tests_api_returns_error_when_user_posts_non_numeric_data(self):\n url = reverse('fibonacci_api')\n data = {\"number\": \"not a numeric value\"}\n response = self.client.post(url, data, format='json')\n self.assertIn(403, response.data)","title":""},{"docid":"9427c05561710ea2755a1eadaea25df9","score":"0.5769555","text":"def valid_rating(number_string):\n\n try:\n if int(number_string) >= 0:\n return True\n else:\n return False\n\n except ValueError:\n print(\"\\n It has to be a 0 or positive number!\")\n return False","title":""},{"docid":"846615941ff04b31e13a84aa37ae18eb","score":"0.5766522","text":"def test_parsing_fails_alpha_utilization(self):\n with self.assertRaises(ValueError):\n self.alert_service._parse(\"(1234,a,1,1)\")","title":""},{"docid":"ba091bbff0755c94c2887f75f58e9f60","score":"0.57642835","text":"def get_user_number_input() -> int:\n try:\n user_number = int(input())\n except ValueError as e:\n print(e.args)\n throw_error(\"Invalid input - must be natural number\")\n return user_number","title":""},{"docid":"eb72567cd8a32810cc6bd8ca090593dc","score":"0.5763005","text":"def valid(f):\n try:\n return not re.search(r'\\b0[0-9]', f) and eval(f) is True\n except ArithmeticError:\n return False","title":""},{"docid":"eb72567cd8a32810cc6bd8ca090593dc","score":"0.5763005","text":"def valid(f):\n try:\n return not re.search(r'\\b0[0-9]', f) and eval(f) is True\n except ArithmeticError:\n return False","title":""},{"docid":"1b3d5640969014f9f2b4d1e2422c0ab9","score":"0.57540035","text":"def _check_angka(cls, indo):\n if not (isinstance(indo, int) or indo.isdigit()):\n raise ValueError((\"Angka harus berupa int, \"\n \"atau string berisi digit\"))\n return indo","title":""},{"docid":"7aafc5a33b6985ba123c35b5e4eb43d6","score":"0.5748548","text":"def validate_int(question):\n while True:\n try:\n ans = int(input(question))\n return ans\n except ValueError: print(\"You must input an integer!\")","title":""},{"docid":"2951267509945c6ebbd967629b88000c","score":"0.57440245","text":"def input_number():\n while True:\n number = input('Enter number:\\n')\n if number.isdigit():\n return number\n elif number.lower() == 'quit':\n return 0\n else:\n print (\"Invalid input, not number!\")","title":""},{"docid":"93a137b204dca68cb85c813b4c08f5ba","score":"0.57411116","text":"def check_input(input):\n check = True\n \n if len(input) == 0:\n check = False\n else:\n for i in range(len(input)):\n if (input[i] < '0') or (input[i] > '9'):\n check = False\n\n return check","title":""},{"docid":"fd5199c8319f17c89f427694273d1ca9","score":"0.5732932","text":"def isnumerical(x):\n try:\n xx = float(x)\n except TypeError:\n return False\n except ValueError:\n return False\n except Exception:\n return False\n else:\n return True","title":""},{"docid":"6bc5fa366eefd68e6804331576d431fd","score":"0.5728857","text":"def test__validate_inputs_scalar_unknown(self):\n # Run / Assert\n with pytest.raises(ValueError):\n GreaterThan._validate_inputs(low='a', high='b', scalar='unknown', drop=None)","title":""},{"docid":"5bb2787f0186a3ea32c739287c521b60","score":"0.57250357","text":"def get_positive_float(question):\n while True:\n try:\n answer = float(input(question))\n if not answer or answer < 0:\n message(\"Please use positive decimal values for the price\")\n answer = float(input(question))\n else:\n return answer\n except ValueError:\n message(\"Please enter a number\")","title":""},{"docid":"e2f6309c2b141473df41489928cb7117","score":"0.5724969","text":"def test_input_not_valid(set_cli_sys_argv, capsys):\n sys.argv.append(\"101\")\n with pytest.raises(\n ValueError, match=\"favorite_number_less_than_100 has to be smaller than 100!\"\n ):\n main()","title":""},{"docid":"bdb92c0ead8dc24ec1d1686ce70d504a","score":"0.57186574","text":"def validate_positive_integer(user_input):\r\n try:\r\n user_input = int(user_input)\r\n if user_input < 0:\r\n print(\"\\nPlease enter a non-negative integer.\")\r\n return \"invalid_input\"\r\n else:\r\n return user_input\r\n except ValueError:\r\n print(\"\\nInvalid input, please enter an integer.\")\r\n return \"invalid_input\"","title":""},{"docid":"e33fe76ccc9500ad5b04bdce7a4676aa","score":"0.5708761","text":"def is_numeric(value, value_label):\n if not isinstance(value, numbers.Number):\n raise ValueError(\"`\" + value_label + \"` must be a number\")","title":""},{"docid":"272c7bb13ae63bad0bfa8825783aecac","score":"0.57053864","text":"def _is_number(s):\n if len(s) > 0 and s[0] in ('-', '+'):\n return s[1:].isdigit()\n return s.isdigit()","title":""},{"docid":"6d4ed990ee4d5984842c4705c9eed2cb","score":"0.56966096","text":"def validateFloat(number):\n try:\n float(number)\n except ValueError:\n print(\"You must input a number.\")\n return False\n finally: pass","title":""},{"docid":"0c29741ef5d9b87282a32f0c2149b6c0","score":"0.5689624","text":"def _isNumeric(n):\n try:\n b = float(n)\n return True\n except:\n pass\n return False","title":""},{"docid":"d5f478200fa7214b8af4ecde08d2dfb6","score":"0.5689393","text":"def chkNumeric(elm):\n \n try:\n test = float(elm)\n except:\n return False\n else:\n return True","title":""},{"docid":"6584aed1609cb72fd4e120c3841fad40","score":"0.5688048","text":"def invalid_query(query):\n if isinstance(query, str):\n if re.search(r\"[0-9]\", query, re.UNICODE):\n return {'error': 'City name must not contain numbers!'}\n else:\n return False\n else:\n return {'error': 'City name must be a string!'}","title":""},{"docid":"bfca7f290757bda402af33d9ca3f5839","score":"0.5680651","text":"def _ValidateASNum(self, asnum):\n try:\n asnumber = int(asnum)\n if asnumber <= 0:\n raise errors.ApilityioValueError(\n 'Not a valid ASNUM. Negative number.')\n return True\n except Exception:\n raise errors.ApilityioValueError(\n 'Not a valid ASNUM. It is a string.')","title":""},{"docid":"ec5e117048f8c5379ca1e6f0f8b6a075","score":"0.5671852","text":"def numeric(input):\n try:\n junk = input + 0\n ret = True\n except:\n ret = False\n return ret","title":""},{"docid":"6f0b56b6ea870e9ecc8af86a8b5188e8","score":"0.56701636","text":"def isNumPosStrValue(value):\r\n\r\n return (value and isinstance(value, basestring) and value.isdigit() and int(value) > 0) or (isinstance(value, int) and value > 0)","title":""},{"docid":"6cf56f4950984eb46ebf58a55b392019","score":"0.56622547","text":"def ttest_typeerror2():\n with pytest.raises(TypeError, match=\"only numbers are allowed\"):\n add('a', 'b')","title":""},{"docid":"c7585b7abc935a169e4241658298dfb3","score":"0.5659002","text":"def get_good_input():\r\n got_good_input = False\r\n while got_good_input == False:\r\n try:\r\n (input(\"Please enter a whole number: \"))\r\n got_good_input = True\r\n except ValueError:\r\n print(\"That was not a a whole number. Please try again.\")\r\n good = \"Valid\"\r\n return good","title":""},{"docid":"0c4277b7fcabe93a2a5a0ff9f3c57b87","score":"0.5651511","text":"def invalid_number_error_message(context):\n assert_in(\"next-action: error: argument -n/--number: invalid number:\", context.next_action())","title":""},{"docid":"0d7335d00c7a1ab679edb05aa9c27db3","score":"0.5648884","text":"def is_number(s): \n try:\n float(s)\n return True\n except ValueError:\n return False","title":""},{"docid":"0d7335d00c7a1ab679edb05aa9c27db3","score":"0.5648884","text":"def is_number(s): \n try:\n float(s)\n return True\n except ValueError:\n return False","title":""},{"docid":"ade3ddacfcc42a7e0fa04c2523dbb92f","score":"0.56452686","text":"def validateNumberGreaterThanZero(message):\n\n badInput = True\n while badInput:\n try:\n response = int(input(message))\n\n while response <= 0:\n response = int(input(\"Only positive amounts greater than 0 allowed. Try again: \"))\n badInput = False\n except ValueError:\n print(\"Only numbers allowed\")\n return response","title":""},{"docid":"7d74fb7aa5c76cf04b3f127cde7b7f12","score":"0.56437224","text":"def parse_input(input_string):\n if input_string.strip() in {\"1\", \"2\", \"3\", \"4\", \"5\", \"6\"}:\n return int(input_string)\n else:\n print(\"Please enter a number from 1 to 6.\")\n raise SystemExit(1)","title":""},{"docid":"dc038012329800ee77b7cb3b34695cdd","score":"0.5638011","text":"def isvalid(number):\n if (number is None) or isinstance(number, str) or not np.isfinite(number):\n return False\n else:\n return True","title":""},{"docid":"25d94a0b284fb14650ca36d8676087bc","score":"0.56313074","text":"def inputValid(userInput):\r\n regex = \"\\d+[d,D]+\\d+[+,-]\\d+\"\r\n if re.search(regex, userInput):\r\n return True\r\n else:\r\n return False","title":""},{"docid":"7a781cd4137842820a863e1637af7ca4","score":"0.5630836","text":"def alpha_numeric(alpha_numeric_string: str) -> str:\n if alpha_numeric_string and re.match(\"^[a-zA-Z0-9\\-_]+$\",\n alpha_numeric_string):\n return alpha_numeric_string\n else:\n raise argparse.ArgumentTypeError(\"invalid alphaNumeric string\")","title":""},{"docid":"e29670158462d4efee0d470ea51fe480","score":"0.56270325","text":"def test_passing_and_invalid_input_type(self, mock_input):\n invalid_input_type = 'not_int_nor_float'\n with self.assertRaises(InvalidInputType) as e:\n self.inputy.format_input(type=invalid_input_type)\n self.assertEqual(e.exception.input_type, invalid_input_type)","title":""},{"docid":"c4a300d92395302fd694f58140d5c6b1","score":"0.5624863","text":"def type_checker(val):\n try:\n return int(val)\n except ValueError:\n pass\n try:\n return float(val)\n except ValueError:\n pass\n return bool_filter(val)","title":""},{"docid":"f898146e15270bef31adecc3af80f434","score":"0.56119406","text":"def is_number(word):\n try:\n n = float(word)\n return True\n except:\n return False","title":""},{"docid":"6b2b43484161931967aa63168a505b93","score":"0.56117135","text":"def isNumber(s):\n try:\n float(s)\n return True\n except ValueError:\n return False","title":""},{"docid":"de46893c8497dc7ef7383b84cd7ab349","score":"0.56103134","text":"def isnumeric(x):\n return isinstance(x, NUMERIC_TYPES)","title":""},{"docid":"57c7dde702f7a5d6e65039a594537f38","score":"0.5609447","text":"def _numeric_type(param):\n return isinstance(param, (float, int)) or param is None","title":""}],"string":"[\n {\n \"docid\": \"eb8de4b095347f3422d0d8ab42c05c67\",\n \"score\": \"0.6866605\",\n \"text\": \"def check(param):\\n try:\\n param = float(param)\\n\\n except ValueError:\\n print(\\\"Incorrect input \\\\\\\"%s\\\\\\\". Must be number.\\\" % param)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a6ba2276e2f4248e8994b8cae14a2c63\",\n \"score\": \"0.6722084\",\n \"text\": \"def is_numeric(form, field):\\n data = str(field.data)\\n if data.isalpha():\\n raise ValidationError(message_is_numeric)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c8fc4d6d231bb1139f1bf85d09b3d578\",\n \"score\": \"0.667467\",\n \"text\": \"def check_numeric(arg):\\n while True:\\n try:\\n entry = float(input(arg))\\n if entry < 0:\\n raise ValueError\\n else:\\n return entry\\n\\n except ValueError:\\n print(\\\"Entries must be positive and numeric\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"79c55c128ca5194b60f902f99d0295eb\",\n \"score\": \"0.66200054\",\n \"text\": \"def number_or_exit(s, msg):\\n isNumber = r'^[1-9][0-9]*\\\\.?[0-9]*([Ee][+-]?[0-9]+)?$';\\n\\n if not re.search(isNumber, s):\\n print(\\\"Error: the {} argument must be a number\\\".format(msg))\\n exit_with_usage()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a980ed468489ba0d4901ce4ee2656340\",\n \"score\": \"0.6596289\",\n \"text\": \"def _validate(number):\\n # Validate Input\\n if type(number) == str: # If it is a string, make sure it is digits \\n if isdigit(number): number\\n else:\\n print(\\\"Verify that your imput consists of the digits 0 thru 9. Your input: \\\", number)\\n return -1 #Bad Input\\n elif type(number) == int: # It is an integer value, convert to string\\n number = str(number)\\n return number\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c99873a99c3fd87e380a2a66255007a7\",\n \"score\": \"0.6582099\",\n \"text\": \"def validate_number(input_data):\\n if input_data.startswith('-'):\\n return input_data[1:].isdigit()\\n return input_data.isdigit()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8af4ea160899d993701c988a55ee70a5\",\n \"score\": \"0.6551377\",\n \"text\": \"def numeric_validation(entry):\\n while True:\\n try:\\n entry = int(entry)\\n break\\n except ValueError:\\n entry = input(\\\"Please enter a valid integer: \\\")\\n return entry\",\n \"title\": \"\"\n },\n {\n \"docid\": \"66f277376594f176feb9d7b76047ed4d\",\n \"score\": \"0.64648896\",\n \"text\": \"def validate_amount(amount):\\n\\n try:\\n amount = float(amount)\\n\\n if amount < 0:\\n raise argparse.ArgumentTypeError(\\\"Amount value should be a non-negative value.\\\")\\n\\n if math.isnan(amount) or math.isinf(amount):\\n raise argparse.ArgumentTypeError(\\\"Amount value is not a number.\\\")\\n\\n except ValueError:\\n raise\\n\\n return amount\",\n \"title\": \"\"\n },\n {\n \"docid\": \"517ed8a6bd6069985c38912f743da2a0\",\n \"score\": \"0.6449597\",\n \"text\": \"def validate_float(user_input): \\r\\n try:\\r\\n return float(user_input)\\r\\n except:\\r\\n print(\\\"\\\\nPlease enter a real number.\\\")\\r\\n return \\\"invalid_input\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f972af5a797c3e414fadedf5ad628bf3\",\n \"score\": \"0.64454305\",\n \"text\": \"def test_wrong_type_integer_input(self):\\n\\n number = get_integer_input(\\\"Integer Number\\\")\\n self.assertNotEqual(type(number), str)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f731f9c460e778127dca9278eb407034\",\n \"score\": \"0.644076\",\n \"text\": \"def test_convert_nonnumeric_value(self):\\n with pytest.raises(TypeError):\\n pressure_util.convert('a', PRESSURE_HPA, PRESSURE_INHG)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"08415286648c0f8b4fd7378180d1022c\",\n \"score\": \"0.6374627\",\n \"text\": \"def isnumeric(input):\\n # 2016-01-20 11:48 IJMC: Created\\n try:\\n junk = float(input) + 0.\\n ret = True\\n except:\\n ret = False\\n return ret\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f4d68c992af47b38e44ca5f87e11dd4c\",\n \"score\": \"0.63367385\",\n \"text\": \"def raise_not_number(x):\\n try:\\n float(x)\\n except ValueError:\\n raise SizeError('Must pass a number, received {}'.format(x))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c9a902cb7cb025889c5c1206d35dfcec\",\n \"score\": \"0.63094205\",\n \"text\": \"def validate_num(\\r\\n num: Union[int, float, Int, Number]) -> None:\\r\\n from apysc.type.number_value_interface import NumberValueInterface\\r\\n if isinstance(\\r\\n num,\\r\\n (int, float, NumberValueInterface)):\\r\\n return\\r\\n raise ValueError(\\r\\n f'Specified value is not iteger or float type: {num}'\\r\\n f'({type(num)})')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"207bcec40f3cdc3d1569bac10afc1e9c\",\n \"score\": \"0.6236718\",\n \"text\": \"def opcion_valida(opcion: str) -> int:\\n while not opcion.isnumeric() or int(opcion) < 1 or int(opcion) > 8:\\n opcion = input(\\\"Ingrese una opcion correcta: \\\")\\n opcion = int(opcion)\\n return opcion\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fcd0eb6c674273e8e9284f93193ea558\",\n \"score\": \"0.6201344\",\n \"text\": \"def is_numeric(input_str):\\n\\n try:\\n float(input_str)\\n return True\\n except ValueError:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"06a32c66bfcb03036a23a34f571bf94e\",\n \"score\": \"0.61735827\",\n \"text\": \"def ask(question, valueType):\\n while True:\\n try:\\n answer = valueType(raw_input(question))\\n if answer < 0:\\n raise ValueError\\n return answer\\n except ValueError:\\n if valueType == int:\\n print \\\" ^ Enter a positive whole number...\\\"\\n else:\\n print \\\" ^ Enter a positive number...\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0d594095e6f520a42448be4069e66e01\",\n \"score\": \"0.6124916\",\n \"text\": \"def test_if_it_accepts_float_numbers_are_accepted(self):\\n with self.assertRaises(TypeError):\\n primenum(56.58)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f789770989c157819bc10916e71cd027\",\n \"score\": \"0.61225647\",\n \"text\": \"def check_input(valid_number): # function which checks all user input, whether it is valid (whole positive numbers) or invalid\\n value = None\\n while not value: # creates a loop so it will keep going till user input is valid \\n value = input(valid_number)\\n if not value.isnumeric(): # if input is not a number\\n print(\\\"Please enter a valid number\\\")\\n print(\\\"\\\\n\\\")\\n value = None\\n else:\\n return int(value) # once a correct number is entered the number is returned and program contiues\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0b28f9f30b6419dace166792ce48baad\",\n \"score\": \"0.6111065\",\n \"text\": \"def test_phone_parser_wrong_input(self):\\r\\n invalid = ('66867867', '', 668678678)\\r\\n for num in invalid:\\r\\n self.assertRaises(WrongInput, phone_parser, num)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7ee45eeda94b9d8da93bfdc5770097a7\",\n \"score\": \"0.6106006\",\n \"text\": \"def validate_numeric_scalar(var: Any) -> bool:\\n assert isinstance(var, (int, float)), \\\"Argument must be single numeric value\\\"\\n return var\",\n \"title\": \"\"\n },\n {\n \"docid\": \"952e4bda8e3e4f0002b89bf61c64789d\",\n \"score\": \"0.6091906\",\n \"text\": \"def is_number(num):\\n try:\\n int(num)\\n except:\\n print('Only enter numbers')\\n return False\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6146a4fc89cbad85b94fc25599723c26\",\n \"score\": \"0.60882956\",\n \"text\": \"def test_input_with_other_char_than_numbers(self):\\n input_with_letter = \\\"12A456789\\\"\\n input_with_special_char = \\\"1234567+9\\\"\\n self.assertEqual(input_is_valid(input_with_letter), False)\\n self.assertEqual(input_is_valid(input_with_special_char), False)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"56ac19df2aa65ded6074ee395cad9ca0\",\n \"score\": \"0.6079081\",\n \"text\": \"def validate_input(input, opts):\\n if not input.isnumeric():\\n return False\\n n = int(input)\\n # Valid indices start at 1.\\n if 0 >= n or len(opts) < n:\\n return False\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5d8d4673526ee08d47a7128dde99336f\",\n \"score\": \"0.6073587\",\n \"text\": \"def test_bad_numeric(self):\\n with pytest.raises(UnwrapFailedError):\\n assert self._get(123).unwrap() # noqa: Z432\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5d8d4673526ee08d47a7128dde99336f\",\n \"score\": \"0.6073587\",\n \"text\": \"def test_bad_numeric(self):\\n with pytest.raises(UnwrapFailedError):\\n assert self._get(123).unwrap() # noqa: Z432\",\n \"title\": \"\"\n },\n {\n \"docid\": \"007c7331fbe2f3cd681e1816b05474ec\",\n \"score\": \"0.60536397\",\n \"text\": \"def valid_number(data_in):\\n\\n try:\\n data_out = float(data_in)\\n except ValueError:\\n data_out = np.nan\\n return data_out\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c98c9aa97a845f00394863b636045a4d\",\n \"score\": \"0.6045029\",\n \"text\": \"def clean_price(price_str):\\n try:\\n try:\\n price_float = float(price_str)\\n except ValueError:\\n price_float = float(price_str[1:])\\n\\n except ValueError:\\n input('''\\n \\\\n***** PRICE ERROR *****\\n \\\\rThe Price should be a number without a currency label.\\n \\\\rEx: 5.99\\n \\\\rPress enter to try again.\\n \\\\r**********************''')\\n return\\n else:\\n return int(price_float * 100)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"14fdc92dd81e78350604bad01db769a1\",\n \"score\": \"0.6037946\",\n \"text\": \"def number_check(num_, len_, name):\\r\\n valid = True\\r\\n error_message = \\\"\\\"\\r\\n if not isinstance(num_, str):\\r\\n valid = False\\r\\n error_message = f\\\"Input for {name} should be string\\\"\\r\\n elif len(num_) > len_:\\r\\n error_message = f\\\"Max len of {name} is 5 char\\\"\\r\\n valid = False\\r\\n elif num_ == \\\"\\\":\\r\\n valid = True\\r\\n error_message = \\\"\\\"\\r\\n elif not re.search(r\\\"[\\\\d]+[-\\\\/.]*[a-zA-Z]*\\\", num_):\\r\\n error_message = f\\\"{name} should be: [0-9][ - . /][ a-zA-Z]\\\"\\r\\n valid = False\\r\\n return (valid, error_message, num_)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c50f225ce7a6c2c0bbb43d961d11a695\",\n \"score\": \"0.6022796\",\n \"text\": \"def safeIntegerInput(prompt):\\n inputString = input(prompt)\\n try:\\n number = int(inputString)\\n return number\\n except ValueError:\\n print(\\\"Error in number format:\\\", inputString)\\n return safeIntegerInput(prompt)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a74a3a2ef82c494c9641d148a4982235\",\n \"score\": \"0.60155165\",\n \"text\": \"def num_in(prompt):\\n while True:\\n try:\\n return float(input(prompt))\\n except ValueError:\\n print(\\\"Please enter a number!\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4fa113da113c983fc76d9e223a5e8bbc\",\n \"score\": \"0.5977137\",\n \"text\": \"def is_numeric(val):\\n return isinstance(val, (int, float))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d6ed4019bbc35fd0532d27a0bb85c331\",\n \"score\": \"0.59757483\",\n \"text\": \"def _control_input_type(token: Any) -> None:\\n\\n if not isinstance(token, str):\\n raise TypeError(f\\\"Wrong input type, expected string, got {type(token)}\\\")\\n if token == \\\"\\\":\\n raise ValueError(\\\"Wrong input type: empty string\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b4b1c36b7ab629c340833b71e4c2a429\",\n \"score\": \"0.59514385\",\n \"text\": \"def valid_input(data_input):\\n\\n is_valid = False\\n try:\\n data_input = int(data_input)\\n except ValueError:\\n print(\\\"\\\"\\\"Vous n'avez pas saisi un nombre. Veuillez recommencer...\\\"\\\"\\\")\\n else:\\n is_valid = True\\n\\n return is_valid\",\n \"title\": \"\"\n },\n {\n \"docid\": \"244a938499385171cf96d9abd510b47b\",\n \"score\": \"0.5948644\",\n \"text\": \"def is_valid(candidate):\\n if candidate.isalnum():\\n if candidate.isalpha():\\n retval = True, 'letter'\\n else:\\n retval = True, 'number'\\n else:\\n try:\\n val = float(candidate)\\n retval = True, 'number'\\n except ValueError:\\n retval = False, 'neither'\\n return retval\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7d7fd11c60fe458920c91fc3acfbceb6\",\n \"score\": \"0.5946673\",\n \"text\": \"def validate_input(input_val):\\n try:\\n float_input = float(input_val)\\n return float_input\\n except ValueError:\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"086eb11cb087707c1fe32284d9f874ee\",\n \"score\": \"0.5944595\",\n \"text\": \"def isNum(x):\\n\\treturn isfloat(x) or isint(x)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6c38583bc6449528fdbc08c7b8274a05\",\n \"score\": \"0.59426284\",\n \"text\": \"def is_numeric(value):\\n return isinstance(value, int) or isinstance(value, float)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6c38583bc6449528fdbc08c7b8274a05\",\n \"score\": \"0.59426284\",\n \"text\": \"def is_numeric(value):\\n return isinstance(value, int) or isinstance(value, float)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"32f4f06874d843f6cf43c14f9d947e84\",\n \"score\": \"0.59352654\",\n \"text\": \"def test_with_non_numeric_nomor(self):\\n form = self.form_data(\\\"ini non numeric\\\", 'p')\\n self.assertFalse(form.is_valid())\\n #get first form, and get nomor field.\\n #then get it data with .as_data() method\\n error = form[0]['nomor'].errors.as_data()[0]\\n self.assertEqual(error.code, 'invalid input')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3d228631096be14c2a4b580eb8423272\",\n \"score\": \"0.5913183\",\n \"text\": \"def check_int_type(rep):\\n try:\\n rep = int(rep)\\n except ValueError:\\n print(\\\"Be carefull, a number is expected!\\\")\\n sys.exit(2)\\n if rep < 0:\\n print(\\\"The number must be positive!\\\")\\n sys.exit(2)\\n return rep\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7c068c3d073b28b614ee6b698c586cd4\",\n \"score\": \"0.5906656\",\n \"text\": \"def bad_input():\\r\\n print(\\\"Bad input, please try again\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"82a6dae82c98970ee01eeac8f5de7cbf\",\n \"score\": \"0.5901525\",\n \"text\": \"def validate_int_or_basestring(option, value):\\r\\n if isinstance(value, (int, long)):\\r\\n return value\\r\\n elif isinstance(value, basestring):\\r\\n if value.isdigit():\\r\\n return int(value)\\r\\n return value\\r\\n raise TypeError(\\\"Wrong type for %s, value must be an \\\"\\r\\n \\\"integer or a string\\\" % (option,))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1e69bfa53544896a15e4433b45768c98\",\n \"score\": \"0.5899116\",\n \"text\": \"def test_strip_nonnumeric(self):\\n Valid = self.create_ValidIDs_class()\\n Valid.strip_nonnumeric(keycol)\\n assert False not in [\\n isinstance(val.item(), int) for val\\n in Valid.df[keycol].dropna().astype(int).values\\n ]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b49e2a308c7622e07d6f1c1014cee935\",\n \"score\": \"0.58989674\",\n \"text\": \"def is_number_tryexcept(s):\\n try:\\n if s == 'nan':\\n return False\\n float(s)\\n return True\\n except ValueError:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b2b6a2303c6a7d7ab7fb619588d1e580\",\n \"score\": \"0.58912516\",\n \"text\": \"def valid(f):\\n try: \\n return not re.search(r'\\\\b0[0-9]', f) and eval(f) is True\\n except ArithmeticError:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8862188df7f1d1ddce612604ae1542e3\",\n \"score\": \"0.5882695\",\n \"text\": \"def get_valid_number(question):\\n value = input(question)\\n valid = False\\n while valid == False:\\n try:\\n while int(value) <= 0: # Reject values less than 0\\n print('Number must be > 0')\\n value = input(question)\\n valid = True\\n except ValueError: # Reject invalid values\\n print('Invalid input; enter a valid number')\\n value = input(question)\\n return value\",\n \"title\": \"\"\n },\n {\n \"docid\": \"905eec86a710c1304b90a2cc01c7d6e7\",\n \"score\": \"0.58655685\",\n \"text\": \"def is_numeric(self, val):\\n val = str(val)\\n if val.isnumeric():\\n print(\\\"Numeric\\\")\\n return True\\n else:\\n print(\\\"Not numeric\\\")\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ea11ed966a078ecd3aa1ed335d3c0c67\",\n \"score\": \"0.5863097\",\n \"text\": \"def test_validate_amount(self):\\n\\n self.assertEqual(util.validate_amount('1'), '1.00')\\n self.assertEqual(util.validate_amount('10'), '10.00')\\n self.assertEqual(util.validate_amount('10.'), '10.00')\\n self.assertEqual(util.validate_amount('10.0'), '10.00')\\n self.assertEqual(util.validate_amount('10.00'), '10.00')\\n\\n with self.assertRaises(ValueError):\\n util.validate_amount('-')\\n util.validate_amount('f')\\n util.validate_amount('1f')\\n util.validate_amount('10.f')\\n util.validate_amount('10.0f')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cf3328ad448ad953a3e4b1d3ceaed1d7\",\n \"score\": \"0.5861212\",\n \"text\": \"def get_integer_input(message):\\n\\n value_as_string = input(message)\\n while not value_as_string.isdecimal() and value_as_string.isnumeric():\\n print('The Input must be an integer')\\n value_as_string = input(message)\\n\\n return float(value_as_string)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4a781ea0eab1ed8d15d371a815601cc9\",\n \"score\": \"0.5852245\",\n \"text\": \"def enforce_some_alnum(value):\\n \\n if value:\\n for c in value:\\n x = ord(c)\\n if lower_start <= x <= lower_end:\\n return value\\n elif upper_start <= x <= upper_end:\\n return value\\n elif digit_start <= x <= digit_end:\\n return value\\n \\n msg = _('There must be at least one letter or digit.')\\n raise forms.ValidationError(msg)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"254de535a7d13248483ac8003bd1c840\",\n \"score\": \"0.58470005\",\n \"text\": \"def _isint(word):\\n return match('^[-+]?[0-9]+$',word)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e2faf187d42b968c46984d1b9bcd654a\",\n \"score\": \"0.58445674\",\n \"text\": \"def _validate(value):\\n\\n try:\\n return float(value)\\n except ValueError as e:\\n e.args = (e.args[0],'Value entered can not be convert to float')\\n raise\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7118996b6c317ffcb8f19950f81f5315\",\n \"score\": \"0.58423126\",\n \"text\": \"def is_numeric(str, func=float):\\n try:\\n i = func(str)\\n except:\\n return False\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9b7cf775ad70be2dc5a918d7b559f974\",\n \"score\": \"0.5841039\",\n \"text\": \"def _replace_invalid(value):\\n if isinstance(value, str):\\n if 's' or '*' in value:\\n value = np.nan\\n return float(value)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aa05f720b7ccdd6827c3aa8c1ffd92ac\",\n \"score\": \"0.58398867\",\n \"text\": \"def valid(f):\\r\\n try: \\r\\n return not re.search(r'\\\\b0[0-9]', f) and eval(f) is True\\r\\n except ArithmeticError:\\r\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0741b12a6b2626793ab95e7d88625a84\",\n \"score\": \"0.5838307\",\n \"text\": \"def validate_integer(user_input): \\r\\n try:\\r\\n return int(user_input)\\r\\n except ValueError:\\r\\n print(\\\"\\\\nInvalid input, please enter an integer.\\\")\\r\\n return \\\"invalid_input\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7a1eb50a845310f17a5b4b39db6aa2c5\",\n \"score\": \"0.5822806\",\n \"text\": \"def ensure_int(param):\\n try:\\n param = re.sub(\\\"\\\\W\\\", \\\"\\\", param)\\n return int(param)\\n except ValueError:\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"62bfe77285aa05c0cab1dab4a50aea20\",\n \"score\": \"0.582152\",\n \"text\": \"def _force_number(func):\\n def validation_decorator(*args, **kwargs):\\n params = list(args)\\n for i, n in enumerate(params):\\n\\n if type(n) == list or type(n) == tuple:\\n if len(n) == 0:\\n params[i] = n = 0\\n elif len(n) == 1:\\n params[i] = n = n[0]\\n\\n if type(n) == str:\\n if n == \\\"\\\":\\n params[i] = n = 0\\n continue\\n\\n if n is None:\\n params[i] = 0\\n continue\\n\\n if type(n) != float and type(n) != int:\\n try:\\n if '.' in n:\\n params[i] = float(n)\\n else:\\n params[i] = int(n)\\n except Exception:\\n # raise ValueError(\\\"\\\")\\n # js returns None instead\\n pass\\n\\n args = tuple(params)\\n try:\\n return func(*args)\\n except Exception:\\n return None\\n\\n return validation_decorator\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8a5c7c81bbf800b02b81fc24144ffcf3\",\n \"score\": \"0.5821398\",\n \"text\": \"def is_number_tryexcept(s):\\n try:\\n float(s)\\n return True\\n except ValueError:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ba71e4dc2c51cd441a00e9b06cef9b71\",\n \"score\": \"0.57937133\",\n \"text\": \"def is_num(text):\\n try:\\n float(text)\\n except:\\n return False\\n else:\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4d78e8957212dfcd9afdb9630e4907b1\",\n \"score\": \"0.57752436\",\n \"text\": \"def tests_api_returns_error_when_user_posts_non_numeric_data(self):\\n url = reverse('fibonacci_api')\\n data = {\\\"number\\\": \\\"not a numeric value\\\"}\\n response = self.client.post(url, data, format='json')\\n self.assertIn(403, response.data)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9427c05561710ea2755a1eadaea25df9\",\n \"score\": \"0.5769555\",\n \"text\": \"def valid_rating(number_string):\\n\\n try:\\n if int(number_string) >= 0:\\n return True\\n else:\\n return False\\n\\n except ValueError:\\n print(\\\"\\\\n It has to be a 0 or positive number!\\\")\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"846615941ff04b31e13a84aa37ae18eb\",\n \"score\": \"0.5766522\",\n \"text\": \"def test_parsing_fails_alpha_utilization(self):\\n with self.assertRaises(ValueError):\\n self.alert_service._parse(\\\"(1234,a,1,1)\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ba091bbff0755c94c2887f75f58e9f60\",\n \"score\": \"0.57642835\",\n \"text\": \"def get_user_number_input() -> int:\\n try:\\n user_number = int(input())\\n except ValueError as e:\\n print(e.args)\\n throw_error(\\\"Invalid input - must be natural number\\\")\\n return user_number\",\n \"title\": \"\"\n },\n {\n \"docid\": \"eb72567cd8a32810cc6bd8ca090593dc\",\n \"score\": \"0.5763005\",\n \"text\": \"def valid(f):\\n try:\\n return not re.search(r'\\\\b0[0-9]', f) and eval(f) is True\\n except ArithmeticError:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"eb72567cd8a32810cc6bd8ca090593dc\",\n \"score\": \"0.5763005\",\n \"text\": \"def valid(f):\\n try:\\n return not re.search(r'\\\\b0[0-9]', f) and eval(f) is True\\n except ArithmeticError:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1b3d5640969014f9f2b4d1e2422c0ab9\",\n \"score\": \"0.57540035\",\n \"text\": \"def _check_angka(cls, indo):\\n if not (isinstance(indo, int) or indo.isdigit()):\\n raise ValueError((\\\"Angka harus berupa int, \\\"\\n \\\"atau string berisi digit\\\"))\\n return indo\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7aafc5a33b6985ba123c35b5e4eb43d6\",\n \"score\": \"0.5748548\",\n \"text\": \"def validate_int(question):\\n while True:\\n try:\\n ans = int(input(question))\\n return ans\\n except ValueError: print(\\\"You must input an integer!\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2951267509945c6ebbd967629b88000c\",\n \"score\": \"0.57440245\",\n \"text\": \"def input_number():\\n while True:\\n number = input('Enter number:\\\\n')\\n if number.isdigit():\\n return number\\n elif number.lower() == 'quit':\\n return 0\\n else:\\n print (\\\"Invalid input, not number!\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"93a137b204dca68cb85c813b4c08f5ba\",\n \"score\": \"0.57411116\",\n \"text\": \"def check_input(input):\\n check = True\\n \\n if len(input) == 0:\\n check = False\\n else:\\n for i in range(len(input)):\\n if (input[i] < '0') or (input[i] > '9'):\\n check = False\\n\\n return check\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fd5199c8319f17c89f427694273d1ca9\",\n \"score\": \"0.5732932\",\n \"text\": \"def isnumerical(x):\\n try:\\n xx = float(x)\\n except TypeError:\\n return False\\n except ValueError:\\n return False\\n except Exception:\\n return False\\n else:\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6bc5fa366eefd68e6804331576d431fd\",\n \"score\": \"0.5728857\",\n \"text\": \"def test__validate_inputs_scalar_unknown(self):\\n # Run / Assert\\n with pytest.raises(ValueError):\\n GreaterThan._validate_inputs(low='a', high='b', scalar='unknown', drop=None)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5bb2787f0186a3ea32c739287c521b60\",\n \"score\": \"0.57250357\",\n \"text\": \"def get_positive_float(question):\\n while True:\\n try:\\n answer = float(input(question))\\n if not answer or answer < 0:\\n message(\\\"Please use positive decimal values for the price\\\")\\n answer = float(input(question))\\n else:\\n return answer\\n except ValueError:\\n message(\\\"Please enter a number\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e2f6309c2b141473df41489928cb7117\",\n \"score\": \"0.5724969\",\n \"text\": \"def test_input_not_valid(set_cli_sys_argv, capsys):\\n sys.argv.append(\\\"101\\\")\\n with pytest.raises(\\n ValueError, match=\\\"favorite_number_less_than_100 has to be smaller than 100!\\\"\\n ):\\n main()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bdb92c0ead8dc24ec1d1686ce70d504a\",\n \"score\": \"0.57186574\",\n \"text\": \"def validate_positive_integer(user_input):\\r\\n try:\\r\\n user_input = int(user_input)\\r\\n if user_input < 0:\\r\\n print(\\\"\\\\nPlease enter a non-negative integer.\\\")\\r\\n return \\\"invalid_input\\\"\\r\\n else:\\r\\n return user_input\\r\\n except ValueError:\\r\\n print(\\\"\\\\nInvalid input, please enter an integer.\\\")\\r\\n return \\\"invalid_input\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e33fe76ccc9500ad5b04bdce7a4676aa\",\n \"score\": \"0.5708761\",\n \"text\": \"def is_numeric(value, value_label):\\n if not isinstance(value, numbers.Number):\\n raise ValueError(\\\"`\\\" + value_label + \\\"` must be a number\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"272c7bb13ae63bad0bfa8825783aecac\",\n \"score\": \"0.57053864\",\n \"text\": \"def _is_number(s):\\n if len(s) > 0 and s[0] in ('-', '+'):\\n return s[1:].isdigit()\\n return s.isdigit()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6d4ed990ee4d5984842c4705c9eed2cb\",\n \"score\": \"0.56966096\",\n \"text\": \"def validateFloat(number):\\n try:\\n float(number)\\n except ValueError:\\n print(\\\"You must input a number.\\\")\\n return False\\n finally: pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0c29741ef5d9b87282a32f0c2149b6c0\",\n \"score\": \"0.5689624\",\n \"text\": \"def _isNumeric(n):\\n try:\\n b = float(n)\\n return True\\n except:\\n pass\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d5f478200fa7214b8af4ecde08d2dfb6\",\n \"score\": \"0.5689393\",\n \"text\": \"def chkNumeric(elm):\\n \\n try:\\n test = float(elm)\\n except:\\n return False\\n else:\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6584aed1609cb72fd4e120c3841fad40\",\n \"score\": \"0.5688048\",\n \"text\": \"def invalid_query(query):\\n if isinstance(query, str):\\n if re.search(r\\\"[0-9]\\\", query, re.UNICODE):\\n return {'error': 'City name must not contain numbers!'}\\n else:\\n return False\\n else:\\n return {'error': 'City name must be a string!'}\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bfca7f290757bda402af33d9ca3f5839\",\n \"score\": \"0.5680651\",\n \"text\": \"def _ValidateASNum(self, asnum):\\n try:\\n asnumber = int(asnum)\\n if asnumber <= 0:\\n raise errors.ApilityioValueError(\\n 'Not a valid ASNUM. Negative number.')\\n return True\\n except Exception:\\n raise errors.ApilityioValueError(\\n 'Not a valid ASNUM. It is a string.')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ec5e117048f8c5379ca1e6f0f8b6a075\",\n \"score\": \"0.5671852\",\n \"text\": \"def numeric(input):\\n try:\\n junk = input + 0\\n ret = True\\n except:\\n ret = False\\n return ret\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6f0b56b6ea870e9ecc8af86a8b5188e8\",\n \"score\": \"0.56701636\",\n \"text\": \"def isNumPosStrValue(value):\\r\\n\\r\\n return (value and isinstance(value, basestring) and value.isdigit() and int(value) > 0) or (isinstance(value, int) and value > 0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6cf56f4950984eb46ebf58a55b392019\",\n \"score\": \"0.56622547\",\n \"text\": \"def ttest_typeerror2():\\n with pytest.raises(TypeError, match=\\\"only numbers are allowed\\\"):\\n add('a', 'b')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c7585b7abc935a169e4241658298dfb3\",\n \"score\": \"0.5659002\",\n \"text\": \"def get_good_input():\\r\\n got_good_input = False\\r\\n while got_good_input == False:\\r\\n try:\\r\\n (input(\\\"Please enter a whole number: \\\"))\\r\\n got_good_input = True\\r\\n except ValueError:\\r\\n print(\\\"That was not a a whole number. Please try again.\\\")\\r\\n good = \\\"Valid\\\"\\r\\n return good\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0c4277b7fcabe93a2a5a0ff9f3c57b87\",\n \"score\": \"0.5651511\",\n \"text\": \"def invalid_number_error_message(context):\\n assert_in(\\\"next-action: error: argument -n/--number: invalid number:\\\", context.next_action())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0d7335d00c7a1ab679edb05aa9c27db3\",\n \"score\": \"0.5648884\",\n \"text\": \"def is_number(s): \\n try:\\n float(s)\\n return True\\n except ValueError:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0d7335d00c7a1ab679edb05aa9c27db3\",\n \"score\": \"0.5648884\",\n \"text\": \"def is_number(s): \\n try:\\n float(s)\\n return True\\n except ValueError:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ade3ddacfcc42a7e0fa04c2523dbb92f\",\n \"score\": \"0.56452686\",\n \"text\": \"def validateNumberGreaterThanZero(message):\\n\\n badInput = True\\n while badInput:\\n try:\\n response = int(input(message))\\n\\n while response <= 0:\\n response = int(input(\\\"Only positive amounts greater than 0 allowed. Try again: \\\"))\\n badInput = False\\n except ValueError:\\n print(\\\"Only numbers allowed\\\")\\n return response\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7d74fb7aa5c76cf04b3f127cde7b7f12\",\n \"score\": \"0.56437224\",\n \"text\": \"def parse_input(input_string):\\n if input_string.strip() in {\\\"1\\\", \\\"2\\\", \\\"3\\\", \\\"4\\\", \\\"5\\\", \\\"6\\\"}:\\n return int(input_string)\\n else:\\n print(\\\"Please enter a number from 1 to 6.\\\")\\n raise SystemExit(1)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dc038012329800ee77b7cb3b34695cdd\",\n \"score\": \"0.5638011\",\n \"text\": \"def isvalid(number):\\n if (number is None) or isinstance(number, str) or not np.isfinite(number):\\n return False\\n else:\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"25d94a0b284fb14650ca36d8676087bc\",\n \"score\": \"0.56313074\",\n \"text\": \"def inputValid(userInput):\\r\\n regex = \\\"\\\\d+[d,D]+\\\\d+[+,-]\\\\d+\\\"\\r\\n if re.search(regex, userInput):\\r\\n return True\\r\\n else:\\r\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7a781cd4137842820a863e1637af7ca4\",\n \"score\": \"0.5630836\",\n \"text\": \"def alpha_numeric(alpha_numeric_string: str) -> str:\\n if alpha_numeric_string and re.match(\\\"^[a-zA-Z0-9\\\\-_]+$\\\",\\n alpha_numeric_string):\\n return alpha_numeric_string\\n else:\\n raise argparse.ArgumentTypeError(\\\"invalid alphaNumeric string\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e29670158462d4efee0d470ea51fe480\",\n \"score\": \"0.56270325\",\n \"text\": \"def test_passing_and_invalid_input_type(self, mock_input):\\n invalid_input_type = 'not_int_nor_float'\\n with self.assertRaises(InvalidInputType) as e:\\n self.inputy.format_input(type=invalid_input_type)\\n self.assertEqual(e.exception.input_type, invalid_input_type)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c4a300d92395302fd694f58140d5c6b1\",\n \"score\": \"0.5624863\",\n \"text\": \"def type_checker(val):\\n try:\\n return int(val)\\n except ValueError:\\n pass\\n try:\\n return float(val)\\n except ValueError:\\n pass\\n return bool_filter(val)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f898146e15270bef31adecc3af80f434\",\n \"score\": \"0.56119406\",\n \"text\": \"def is_number(word):\\n try:\\n n = float(word)\\n return True\\n except:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6b2b43484161931967aa63168a505b93\",\n \"score\": \"0.56117135\",\n \"text\": \"def isNumber(s):\\n try:\\n float(s)\\n return True\\n except ValueError:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"de46893c8497dc7ef7383b84cd7ab349\",\n \"score\": \"0.56103134\",\n \"text\": \"def isnumeric(x):\\n return isinstance(x, NUMERIC_TYPES)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"57c7dde702f7a5d6e65039a594537f38\",\n \"score\": \"0.5609447\",\n \"text\": \"def _numeric_type(param):\\n return isinstance(param, (float, int)) or param is None\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":395,"cells":{"query_id":{"kind":"string","value":"684d4bb24cc2591d34e2cb4b07a3c8d5"},"query":{"kind":"string","value":"where should we go next tick?"},"positive_passages":{"kind":"list like","value":[{"docid":"50f191c660eb379fbac6e791db39402f","score":"0.0","text":"def nextStep(self):\n options = self.surroundingValues()\n\n a = [self.expandTile(tile, tile.explored) for tile in options]\n\n m = min(a)\n maxIndexes = [i for i, j in enumerate(a) if j == m]\n\n\tprint a\t\n\tprint maxIndexes\n\tprint \n\n direction = random.choice(maxIndexes)\n\n # go from index in the array to an actual direction\n if direction == 0:\n return [0,1]\n elif direction == 1:\n return [1,0]\n elif direction == 2:\n return [0,-1]\n elif direction == 3:\n return [-1,0]\n\n raise ValueError('wat')\n return","title":""}],"string":"[\n {\n \"docid\": \"50f191c660eb379fbac6e791db39402f\",\n \"score\": \"0.0\",\n \"text\": \"def nextStep(self):\\n options = self.surroundingValues()\\n\\n a = [self.expandTile(tile, tile.explored) for tile in options]\\n\\n m = min(a)\\n maxIndexes = [i for i, j in enumerate(a) if j == m]\\n\\n\\tprint a\\t\\n\\tprint maxIndexes\\n\\tprint \\n\\n direction = random.choice(maxIndexes)\\n\\n # go from index in the array to an actual direction\\n if direction == 0:\\n return [0,1]\\n elif direction == 1:\\n return [1,0]\\n elif direction == 2:\\n return [0,-1]\\n elif direction == 3:\\n return [-1,0]\\n\\n raise ValueError('wat')\\n return\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"47e4d0cbcb6e027f154a33d964fd0780","score":"0.76231015","text":"def tick(self):","title":""},{"docid":"47e4d0cbcb6e027f154a33d964fd0780","score":"0.76231015","text":"def tick(self):","title":""},{"docid":"c6895c04d064960b1ae0bf4a4da83d20","score":"0.75546896","text":"def tick(self):\n pass","title":""},{"docid":"c6895c04d064960b1ae0bf4a4da83d20","score":"0.75546896","text":"def tick(self):\n pass","title":""},{"docid":"fa5b9e7cb1da1b9aaba893abc7f61a3e","score":"0.71828836","text":"def tick(self):\n\t\tprint('Must implement tick method')","title":""},{"docid":"21052662d26063a1de0e4df86f5cc5b8","score":"0.70880234","text":"def tick_handler(self):","title":""},{"docid":"cedc0f1436ad90cd3e7334501714b7db","score":"0.6972772","text":"def play_tick(self):\n pass","title":""},{"docid":"9db75ec327a0b6e4adee278c6bea2aad","score":"0.69448376","text":"def Tick1S():\n#---------------------------------------------------------------\n pass","title":""},{"docid":"f6b05c9c18c04aba7eb58245b11add60","score":"0.6774041","text":"def on_event_new_tick(self):","title":""},{"docid":"1f9bb8d4246d809321fa4bf354427e6c","score":"0.66825753","text":"def tick(self, gamestate):","title":""},{"docid":"6d7ea7315bd8ac95ba29105ee17c9b12","score":"0.66772","text":"def Tick100MS():\n#---------------------------------------------------------------\n pass","title":""},{"docid":"7182d0ac848260612b814a633a7d7be2","score":"0.66086775","text":"def tick(self, sim):\n pass","title":""},{"docid":"56326e14c9c27b9d96388c6abd44917c","score":"0.65953845","text":"def tick(self):\n raise NotImplementedError('You must implement this.')","title":""},{"docid":"c06fea3f96b163280f0a338958457004","score":"0.655352","text":"def new_tick(self, msg):\n pass","title":""},{"docid":"2c5f4fa64dc17db4472fbce28743b03f","score":"0.65278935","text":"def ticking(self):\n self.ready()","title":""},{"docid":"b5c2edbd87a66dadfd9eebf02006e48a","score":"0.6331","text":"def on_tick() -> None:\n raise NotImplementedError","title":""},{"docid":"95f2cdfeb1fe90c4ab87164d1e5ecccc","score":"0.6325778","text":"def advance_time():","title":""},{"docid":"7e279f82fd8010fb5a69d595e2367ba6","score":"0.6290593","text":"def _tick(self):\n self._update_agent_stats()\n\n self.handle_call_events()\n\n if not self._shift_over:\n self.calculate()\n\n if self._current_time % self.REPORTING_INTERVAL == 0:\n self.print_report()\n\n self._create_checkpoint()","title":""},{"docid":"7c8a8117e379e5f45abdbc2451cc30c0","score":"0.6217834","text":"def next_event(self):\n pass","title":""},{"docid":"3808952aa046cafd9993d295316ead3a","score":"0.6190031","text":"def tick(self):\r\n self.times.append(timeit.default_timer())","title":""},{"docid":"59b0fa88992b8fb1612d1356149a7082","score":"0.6173794","text":"def tick(self) -> bool:\n return False","title":""},{"docid":"7fa46544c2dfee7177f828ed7d3ab244","score":"0.6170556","text":"def _ticktock2(self):\n ui = self._ui\n \n now = dt.utcnow()\n self._ui['tick_ends'].appendleft(now)\n \n counter = ui['counter']\n ui['counter'] = counter +1\n \n if ui['sync'] is not None:\n return\n \n \n self._ui['entries'].appendleft(now)\n \n if not counter:\n ui['epoch'] = now\n ui['first'] = now","title":""},{"docid":"0438e92ffc4a6d87d73cfa42d3aa0055","score":"0.614751","text":"def tick():\r\n global tenths\r\n tenths = tenths + 1\r\n format(tenths)","title":""},{"docid":"4d8b0c207c4f4419126c23b03b12f48f","score":"0.60896516","text":"def tickle_me():\n\tload_til(500.0)\n\treturn \"Tickling you. (half-second)\"","title":""},{"docid":"b4519cdf915e87d087aa394273ccc251","score":"0.60748243","text":"def tick(self, amount):\n pass","title":""},{"docid":"0df62d77e1b3e3def45dcdc4eadd07d9","score":"0.6068059","text":"def performGameCycle(self):","title":""},{"docid":"ce4ea50f299f888de2b575b8fcff76dd","score":"0.6025078","text":"def update(self) -> None:\n time_elapsed = min(self.time_to_tick, self.time_to_weave)\n self.time += time_elapsed\n\n # Handle DoTs\n if self.song_began and self.time % 3000 == self.tick_offset:\n for _ in range(DOTS_UP):\n self.on_tick()\n\n # Natural BL regeneration\n if self.bl_stacks < MAX_BL_STACKS:\n if self.bl_cd - time_elapsed <= 0:\n self.bl_stacks += 1\n\n # If we're still not at max stacks, lower the CD\n if self.bl_stacks < MAX_BL_STACKS:\n self.bl_cd = (self.bl_cd - time_elapsed) % 15000\n else:\n self.bl_cd = 15000 \n else:\n self.bl_cd -= time_elapsed\n\n # EA regeneration\n if self.ea_cd > 0:\n self.ea_cd = max(0, self.ea_cd - time_elapsed)","title":""},{"docid":"4c1a43e5f913bd740df6d94ab87221b9","score":"0.60147256","text":"def called_every_second(self):","title":""},{"docid":"3de663b1de6663b09b0ea6b0d7e17866","score":"0.6002003","text":"def tick(self):\n\n previous_hour = self.__hours\n Clock.tick(self)\n if (self.__hours < previous_hour):\n self.advance()","title":""},{"docid":"03c71c964933df3c6b5d4c6bc2433e13","score":"0.59970266","text":"def periodic():","title":""},{"docid":"94799c5ab462aca47cf0ef4b05f3014e","score":"0.5991244","text":"def start_tick(self):\n if self.iactive is not None and self.scenes:\n self.scenes[self.iactive].start_tick()","title":""},{"docid":"2319c8a53be6def32ed9589ca70780fe","score":"0.5975583","text":"def step(self):\n self.incendio()","title":""},{"docid":"e036c2d95a166ac7d43296b88b699573","score":"0.5962916","text":"def pause_tick(self):\n pass","title":""},{"docid":"76e811b4cb6512f0e6d2d6f9233d648e","score":"0.5962218","text":"def start(self):\n self.stop()\n self.ticking = 1\n self.step()\n self.tickId = self.parent.after(self.tickDelay, self.start)","title":""},{"docid":"24deef73ebf7990d05e975d50d7a5918","score":"0.59597754","text":"def step(self):\n self.schedule.step()","title":""},{"docid":"24deef73ebf7990d05e975d50d7a5918","score":"0.59597754","text":"def step(self):\n self.schedule.step()","title":""},{"docid":"54ae33ddbb2ab5a1b55c19d855444a19","score":"0.5947314","text":"def __calculate_next_tick(self, ref_time_stamp):\n # The remaining time is calculated as follows\n # The ref time marks the start of job execution\n # time consumed by job is current time minus the ref time\n # Thus the remaining time is the difference between the consumed time and the frequency time\n # If the job consumes more time than the frequency allows, the calculated time will be negative\n # In that case, the next_tick shall be set to zero forcing zero sleep and immediate execution of next iteration\n next_tick = self.__clock_tick_duration_seconds - (time.time() - ref_time_stamp)\n self.__next_tick = 0 if next_tick < 0 else next_tick","title":""},{"docid":"bd98cdd2868727f877e1e9019a9d31a9","score":"0.59169257","text":"def tick():\n global t\n t = t + 1\n #print \"test\"+ str(t)\n format(t)","title":""},{"docid":"8b92c543267613037f0e9b3fb23d1f70","score":"0.59071636","text":"def next_track(self):\r\n if self.is_active:\r\n self.sp.next_track()","title":""},{"docid":"27118093759e678b4d56e476e035fa64","score":"0.58784366","text":"def tick(self, now=None):\r\n if now is None:\r\n # now won't be None in unit tests\r\n now = time.time()\r\n for event in events.TICK_EVENTS:\r\n period = event.period\r\n last_tick = self.ticks.get(period)\r\n if last_tick is None:\r\n # we just started up\r\n last_tick = self.ticks[period] = timeslice(period, now)\r\n this_tick = timeslice(period, now)\r\n if this_tick != last_tick:\r\n self.ticks[period] = this_tick\r\n events.notify(event(this_tick, self))","title":""},{"docid":"c2dbd678720b9ab300afd2d7550eed53","score":"0.58740884","text":"def tick():\n global countdown\n countdown -= 1","title":""},{"docid":"a03905a89dd14f70ca777ad674589f7a","score":"0.58666366","text":"def tick(self, ticktime_ms):\n\n self.next_locations = self.request_next_locations(ticktime_ms)\n\n return","title":""},{"docid":"e98f5fbb08a37fc090fd1042582ecb75","score":"0.5860322","text":"def step(self):","title":""},{"docid":"e98f5fbb08a37fc090fd1042582ecb75","score":"0.5860322","text":"def step(self):","title":""},{"docid":"e98f5fbb08a37fc090fd1042582ecb75","score":"0.5860322","text":"def step(self):","title":""},{"docid":"e98f5fbb08a37fc090fd1042582ecb75","score":"0.5860322","text":"def step(self):","title":""},{"docid":"d0067d3090d07677b31084c970512d39","score":"0.58435094","text":"def next(self):\n for d in self.getdatanames(): # Looping through all symbols\n pos = self.getpositionbyname(d).size or 0\n if pos == 0: # Are we out of the market?\n # Consider the possibility of entrance\n # Notice the indexing; [0] always means the present bar, and [-1] the bar immediately preceding\n # Thus, the condition below translates to: \"If today the regime is bullish (greater than\n # 0) and yesterday the regime was not bullish\"\n if self.regime[d][0] > 0 and self.regime[d][-1] <= 0: # A buy signal\n self.buy(data=self.getdatabyname(d))\n\n else: # We have an open position\n if self.regime[d][0] <= 0 and self.regime[d][-1] > 0: # A sell signal\n self.sell(data=self.getdatabyname(d))","title":""},{"docid":"80563f63bb74366790fe901deb7809c9","score":"0.58254075","text":"def lasttick(self):\n if self.__lasttick:\n return self.__lasttick\n else:\n return 0","title":""},{"docid":"f88dc84e558db338cab6d32a89b41386","score":"0.58142823","text":"def nxt_followed(self, handle, nxt_handle, x_axis, y_axis):\n print \"moving nxt to next point of the path\"\n return {'ack': 'got followed'}","title":""},{"docid":"70d8a735611647b0debb6be4f385b9a0","score":"0.58093745","text":"def on_tick(self, tick: TickData):\n if not tick.last_price:\n return\n\n # update tick\n self.last_tick = tick\n\n # update vline for different pairs\n #self.vg[tick.vt_symbol].update_tick(tick=tick)\n #print(tick)\n #print(self.vg[tick.vt_symbol].vline)\n\n #self.last_vline = self.vg[self.vt_symbol].vline\n\n #for v in self.vg.vline_buf:\n # if self.vg.vline_buf[v].volume < 0.9*v:\n # return\n\n \"\"\"\"\"\"\n #self.last_tick = tick\n #self.write_log(f\"Tick: {tick.last_price} TS: {tick.datetime}\")","title":""},{"docid":"177287ab7295d082e24b131a86bcfeae","score":"0.58038265","text":"def tick(self):\n if self.stopped:\n return\n \n last_time = self.current_time\n last_clock = self.last_clock_time\n \n # first, determine new time\n clock_time = time()\n if last_clock is None:\n last_clock = clock_time\n diff = clock_time - last_clock\n new_time = (self.direction * self.rate * diff) + last_time\n \n # update the time\n self.last_clock_time = clock_time\n self.current_time = new_time\n \n # now we make sure we're in bounds (we don't do this before, since it\n # can cause us to skip events that are at boundaries.\n self.current_time = max(self.current_time, 0)\n self.current_time = min(self.current_time, self.length())","title":""},{"docid":"836e368944edb41f943f5ffde76ee6a9","score":"0.57948995","text":"def tick(self):\n self.time += 1\n self.calculate_weights()\n if not self.time % self.rotation_time:\n self.rotate()","title":""},{"docid":"6123eadcf90a2a9bf107ccb4c90c8243","score":"0.5779648","text":"def increment_time(self):","title":""},{"docid":"306a240143120063ccbcf19a543936df","score":"0.577839","text":"def on_tick(self, tick: TickData):\n if (\n self.last_tick_time\n and self.last_tick_time.minute != tick.datetime.minute\n ):\n bars = {}\n for vt_symbol, bg in self.bgs.items():\n bars[vt_symbol] = bg.generate()\n self.on_bars(bars)\n\n bg: BarGenerator = self.bgs[tick.vt_symbol]\n bg.update_tick(tick)\n\n self.last_tick_time = tick.datetime","title":""},{"docid":"bef3c65d982c6ee104b14f79694ed1ff","score":"0.5773426","text":"def tick(self):\n self._wrap_lock(self._tick)","title":""},{"docid":"c457d216db7375602c3d350accf3248f","score":"0.5770214","text":"def tick(self):\n t = self.time()\n self._dt = t - self._t\n self._t = t\n self._frame_times.append(self._dt)","title":""},{"docid":"befbaa99edbe8f05a04b4a98d7bdb66e","score":"0.5769967","text":"def run_now(self):\n self.last_check = 0","title":""},{"docid":"abdf57dc2a7f86e7343cf784cb263754","score":"0.5767029","text":"def next(self):\n if not self.position:\n if self.close[0] > self.ketler.upper[0]:\n self.order = self.order_target_percent(target=0.95)\n else:\n if self.close[0] < self.ketler.expo[0]:\n self.order = self.sell()","title":""},{"docid":"3b73c601130a0080df06a82800d61ec2","score":"0.5761602","text":"def next(self):\n for d in self.getdatanames(): # Looping through all symbols\n pos = self.getpositionbyname(d).size or 0\n if pos == 0: # Are we out of the market?\n # Consider the possibility of entrance\n # Notice the indexing; [0] always means the present bar, and [-1] the bar immediately preceding\n # Thus, the condition below translates to: \"If today the regime is bullish (greater than\n # 0) and yesterday the regime was not bullish\"\n if self.sma[d][0] * self.params.var1 > self.getdatabyname(d).high[0]: # A buy signal\n self.order_target_percent(data=self.getdatabyname(d), target=0.98)\n\n else: # We have an open position\n if self.getdatabyname(d).close[-1] * self.params.var2 <= self.getdatabyname(d).high[0]: # A sell signal\n self.order_target_percent(data=self.getdatabyname(d), target=0)","title":""},{"docid":"bfedda1685cc4fe553c253b697ca3794","score":"0.57515013","text":"def do_timestep(self, ticks) -> None:\n if ticks == 0:\n return\n\n timeplus = float(ticks) / float(self.ticks_per_beat)\n if not self._pos_feed:\n self._acumulated_time += ticks\n if self._acumulated_time >= self._min_time_division and not self._pos_feed:\n self.position += 1\n self._acumulated_time = 0\n self._pos_feed = True\n\n if self._last_note_on:\n self.distance = timeplus\n else:\n self.distance += timeplus\n self._last_note_on = False\n\n for note in self.active_notes:\n note.length += timeplus","title":""},{"docid":"f26b04ba0299607b110f6af8bf9f2017","score":"0.57501334","text":"def next(self):\n\n # Determine which set of moving averages to use\n curdate = self.datetime.date(0)\n dtidx = None # Will be index\n # Determine which period (if any) we are in\n for sd, ed in self.date_combos:\n # Debug output\n # print('{}: {} < {}: {}, {} < {}: {}'.format(\n # len(self), sd, curdate, (sd <= curdate), curdate, ed, (curdate <= ed)))\n if sd <= curdate and curdate <= ed:\n dtidx = (sd, ed)\n # Debug output\n # print('{}: the dtixdx is {}, and curdate is {};'.format(len(self), dtidx, curdate))\n for d in self.getdatanames(): # Looping through all symbols\n pos = self.getpositionbyname(d).size or 0\n if dtidx is None: # Not in any window\n break # Don't engage in trades\n if pos == 0: # Are we out of the market?\n # Consider the possibility of entrance\n # Notice the indexing; [0] always mens the present bar, and [-1] the bar immediately preceding\n # Thus, the condition below translates to: \"If today the regime is bullish (greater than\n # 0) and yesterday the regime was not bullish\"\n '''if self.slowma[d][dtidx][0] > self.getdatabyname(d).close[0]: # A buy signal\n self.sell(data=self.getdatabyname(d), size=1000)\n\n else: # We have an open position\n if self.fastma[d][dtidx][0] < self.getdatabyname(d).close[0]: # A sell signal\n self.close(data=self.getdatabyname(d), size=1000)\n '''\n if self.sma[d][dtidx][0] * self.var1[d][dtidx] > self.getdatabyname(d).high[0]: # A buy signal\n self.order_target_percent(data=self.getdatabyname(d), target=0.98)\n\n else: # We have an open position\n if self.getdatabyname(d).close[-1] * self.var2[d][dtidx] <= self.getdatabyname(d).high[0]: # A sell signal\n self.order_target_percent(data=self.getdatabyname(d), target=0)","title":""},{"docid":"65b0875fe77e17a3b8d75adf58219632","score":"0.57475924","text":"def tick(self):\n\n # next historical order to be sent\n\n oborder = self.hist_orders[self.ob_idx]\n\n # if I have queued orders\n if self.my_queue:\n # if my order reaches the orderbook before the next historical order\n if self.my_queue[0].timestamp < oborder[self.col_idx['timestamp']]:\n my_order = self.my_queue.popleft()\n self._send_to_orderbook(my_order, is_mine=True)\n self.remove_vol_in_queue(my_order[self.col_idx['uid']])\n return\n\n # otherwise sent next historical order\n self._send_historical_order(oborder)","title":""},{"docid":"f6d140c7056e7f3f75b4a69e04f6b25d","score":"0.5744944","text":"def _on_tick(self, args: Tuple, kwargs: Dict) -> None:\n pass","title":""},{"docid":"6db101e376fc8c48eab7fbaace6103a5","score":"0.5743131","text":"def tick(self):\n while self.active:\n for coil in self.ball_search_coils:\n self.pop_coil(coil)\n yield Timing.secs(self.machine.config['ball_search']\\\n ['secs between ball search coils'])\n yield Timing.secs(self.machine.config['ball_search']\\\n ['secs between ball search rounds'])\n # todo do we have to deal with switches that might be hit due to these\n # coils firing?\n # todo should the above code also look for self.active?","title":""},{"docid":"9350ee10aabc339a2aa5e3462385fcb8","score":"0.5741916","text":"def _ticktock(self):\n \n ui = self._ui\n now = dt.utcnow() \n ui['ticks'].appendleft(now)\n \n if ui['sync'] is None:\n return\n \n \n counter = ui['counter']\n if not counter:\n self._ticktock_1st(now)\n \n \n entry = self._synced(now)\n ui['entries'].appendleft(entry)\n \n if not counter:\n ui['first'] = entry","title":""},{"docid":"78689bed249ecaf6cf004b3f48055669","score":"0.5733522","text":"def on_tick(self, tick: TickData):\n self.bg5.update_tick(tick)","title":""},{"docid":"d994dae4eef2b1336265ae6a2f02b241","score":"0.5730125","text":"def step(self):\r\n ...","title":""},{"docid":"c0cd4dca1c2f1b00a602b29bb1107f20","score":"0.5726646","text":"def do_tick(self):\n for member in self.members:\n member.tick(self.tick_count * swimprotocol.SWIM.T)\n self.tick_count = self.tick_count + 1","title":""},{"docid":"17715d50d4aba1afe1b7be37b19195d5","score":"0.57241493","text":"def running():","title":""},{"docid":"67d1fd75b3152adee56252abf0c94f95","score":"0.57208514","text":"def __tick(self):\n def set_current_time():\n now = datetime.datetime.now()\n self.__hour = now.hour\n self.__minute = now.minute\n self.__second = now.second\n self.notifyAll()\n\n self.__interval = Interval(set_current_time, 3)","title":""},{"docid":"1dc3ca2a84edb0bea255cf1365c4eea3","score":"0.57200813","text":"def tick(cls):\n cls.instance_.finishActive()","title":""},{"docid":"9bd74a9679855c9b70878c353cce289a","score":"0.5699552","text":"def timer():","title":""},{"docid":"16fee983405830fbcdc81e6215b804d8","score":"0.56920654","text":"def run_logic(self):\n\n self._clock.tick(60)","title":""},{"docid":"2b5edd0393607d05f14af1131611718e","score":"0.5676555","text":"def _schedule_next_flush(self):\n #time until the hour rolls over:\n vals = time.localtime()\n timeLeft = 60*(60-vals[4]) - vals[5]\n timeLeft += 30\n ##DEBUG:\n #timeLeft = 30\n self._next_flush_event = reactor.callLater(timeLeft, self._flush_event_logs)","title":""},{"docid":"8ed86ba25084a59523d90cb5630967a9","score":"0.56755614","text":"def advance(self):\n None","title":""},{"docid":"38c78989fdeeec4265bac4b2258dbb5c","score":"0.5666694","text":"def tick(self):\n if self.currentTask is not None:\n self.timeRemaining -= 1\n if(self.timeRemaining <= 0):\n self.currentTask = None\n self.timeRemaining = 0 # just in case it goes negative","title":""},{"docid":"0e43b0f7b0d518551bfcc7bfbfe27a7c","score":"0.56557053","text":"def tick(self):\r\n if self.seconds == 59:\r\n self.seconds = 0\r\n if (self.minutes == 59):\r\n self.minutes = 0\r\n self.hours = 0 if self.hours==23 else self.hours + 1\r\n else:\r\n self.minutes += 1;\r\n else:\r\n self.seconds += 1;","title":""},{"docid":"681682eaa53da71329813e7f88ce4fd5","score":"0.56551063","text":"def loop():","title":""},{"docid":"3e5df73a786e2c9fc2c6adebc1e083bd","score":"0.5647457","text":"def on_epoch_end(self):\n # TODO: Some sort of shuffling?\n return","title":""},{"docid":"7b7afbfb0e0595e84e127c27b9706c8f","score":"0.56371874","text":"def start_epoch(self):\r\n pass # for this type of con. method we don't do anything\r","title":""},{"docid":"ef8176ebb5b0e3b557bf09a6d76dc29f","score":"0.5635328","text":"def timer_tick(self, *args):\n # Generate a new number and increment the tick count\n new_val = self._generator()\n self.num_ticks += len(new_val)\n\n # grab the existing data, truncate it, and append the new point.\n # This isn't the most efficient thing in the world but it works.\n cur_data = self.viewer.data\n # new_data = np.hstack((cur_data[-self.max_num_points+1:], [new_val]))\n new_data = np.r_[cur_data[-self.max_num_points+1:], new_val]\n new_index = np.arange(self.num_ticks - len(new_data) + 1,\n self.num_ticks + 0.01)\n\n self.viewer.index = new_index\n self.viewer.data = new_data\n return","title":""},{"docid":"ccc7a219d5e41f50ea4f1837f24a6667","score":"0.5634773","text":"def step(self):\n pass","title":""},{"docid":"ccc7a219d5e41f50ea4f1837f24a6667","score":"0.5634773","text":"def step(self):\n pass","title":""},{"docid":"79cfbcb7e32fbf9fa1d3aa530ba59a00","score":"0.5633921","text":"def step(self):\n info = self.r.tolist()+self.v.tolist()\n self.v += (self.brain.feedForward(info)[-1]-np.array([.5,.5]))*dt\n self.r += self.v*dt","title":""},{"docid":"03be9d8492481dd1a8d37c35b4fd9a5b","score":"0.5627474","text":"def Schedule_Next(self,Now):\n tf = max([self.orig.travel_factor, self.dest.travel_factor])\n #delta_t = int(abs(round(RNG.Normal(self.T*tf, self.T_std), 0)))\n delta_t = np.random.poisson(self.T*tf)\n Flight_Generator.Schedule_Flight(Now+delta_t, self)","title":""},{"docid":"f5419b268d48246c4068563aed7dc572","score":"0.56225395","text":"def tick_tock():\n text = \"Tock\"\n if time.localtime()[5] % 2 == 0:\n text = \"Tick\"\n print(text)","title":""},{"docid":"aa19df868a4272c7dc8bd6f7423164f0","score":"0.56224823","text":"def step(self, dt):\n pass","title":""},{"docid":"96f9e3e7219c2872b4f978aaf1814982","score":"0.5615514","text":"def timer_tick(self, *args):\r\n # Generate a new number and increment the tick count\r\n new_val = self._generator(self.mean, self.stddev)\r\n self.num_ticks += 1\r\n\r\n # grab the existing data, truncate it, and append the new point.\r\n # This isn't the most efficient thing in the world but it works.\r\n cur_data = self.viewer.data\r\n new_data = np.hstack((cur_data[-self.max_num_points+1:], [new_val]))\r\n new_index = np.arange(self.num_ticks - len(new_data) + 1,\r\n self.num_ticks + 0.01)\r\n\r\n self.viewer.index = new_index\r\n self.viewer.data = new_data\r\n return","title":""},{"docid":"bd906130705ddfdbea59e2491536b644","score":"0.56114537","text":"def redoNext():","title":""},{"docid":"d418af1fd1523b5fe28559bce750a109","score":"0.56098574","text":"def get_on_next(self):","title":""},{"docid":"18df9770ccd94aae29d3caf35c637a1a","score":"0.5608524","text":"def running(self):","title":""},{"docid":"9d03589020a362406d0968edcc4f34ed","score":"0.5605621","text":"def tick(self):\n if self._current_run is None:\n self._current_run = asyncio.ensure_future(self.run_once())\n asyncio.get_event_loop().run_until_complete(self._current_run)","title":""},{"docid":"999ba46dcb5f3c5346796cba77c004ca","score":"0.5600143","text":"def _next_iteration(self):\n pass","title":""},{"docid":"e315f73351409b3a6e3f9ecbfd239c1c","score":"0.5595848","text":"def test_stream_all_ticks(self):\n # Stream to Tick #1 (GOOG)\n self.price_handler.stream_next_tick()\n self.assertEqual(\n self.price_handler.tickers[\"GOOG\"][\"timestamp\"].strftime(\n \"%d-%m-%Y %H:%M:%S.%f\"\n ), \n \"01-02-2016 00:00:01.358000\"\n )\n self.assertEqual(\n self.price_handler.tickers[\"GOOG\"][\"bid\"], \n Decimal(\"683.56000\")\n )\n self.assertEqual(\n self.price_handler.tickers[\"GOOG\"][\"ask\"], \n Decimal(\"683.58000\")\n )\n\n # Stream to Tick #2 (AMZN)\n self.price_handler.stream_next_tick()\n self.assertEqual(\n self.price_handler.tickers[\"AMZN\"][\"timestamp\"].strftime(\n \"%d-%m-%Y %H:%M:%S.%f\"\n ), \n \"01-02-2016 00:00:01.562000\"\n )\n self.assertEqual(\n self.price_handler.tickers[\"AMZN\"][\"bid\"], \n Decimal(\"502.10001\")\n )\n self.assertEqual(\n self.price_handler.tickers[\"AMZN\"][\"ask\"], \n Decimal(\"502.11999\")\n )\n\n # Stream to Tick #3 (MSFT)\n self.price_handler.stream_next_tick()\n self.assertEqual(\n self.price_handler.tickers[\"MSFT\"][\"timestamp\"].strftime(\n \"%d-%m-%Y %H:%M:%S.%f\"\n ), \n \"01-02-2016 00:00:01.578000\"\n )\n self.assertEqual(\n self.price_handler.tickers[\"MSFT\"][\"bid\"], \n Decimal(\"50.14999\")\n )\n self.assertEqual(\n self.price_handler.tickers[\"MSFT\"][\"ask\"], \n Decimal(\"50.17001\")\n )\n\n # Stream to Tick #10 (GOOG)\n for i in range(4, 11):\n self.price_handler.stream_next_tick()\n self.assertEqual(\n self.price_handler.tickers[\"GOOG\"][\"timestamp\"].strftime(\n \"%d-%m-%Y %H:%M:%S.%f\"\n ), \n \"01-02-2016 00:00:05.215000\"\n )\n self.assertEqual(\n self.price_handler.tickers[\"GOOG\"][\"bid\"], \n Decimal(\"683.56001\")\n )\n self.assertEqual(\n self.price_handler.tickers[\"GOOG\"][\"ask\"], \n Decimal(\"683.57999\")\n )\n\n # Stream to Tick #20 (GOOG)\n for i in range(11, 21):\n self.price_handler.stream_next_tick()\n self.assertEqual(\n self.price_handler.tickers[\"MSFT\"][\"timestamp\"].strftime(\n \"%d-%m-%Y %H:%M:%S.%f\"\n ), \n \"01-02-2016 00:00:09.904000\"\n )\n self.assertEqual(\n self.price_handler.tickers[\"MSFT\"][\"bid\"], \n Decimal(\"50.15000\")\n )\n self.assertEqual(\n self.price_handler.tickers[\"MSFT\"][\"ask\"], \n Decimal(\"50.17000\")\n )\n\n # Stream to Tick #30 (final tick, AMZN)\n for i in range(21, 31):\n self.price_handler.stream_next_tick()\n self.assertEqual(\n self.price_handler.tickers[\"AMZN\"][\"timestamp\"].strftime(\n \"%d-%m-%Y %H:%M:%S.%f\"\n ), \n \"01-02-2016 00:00:14.616000\"\n )\n self.assertEqual(\n self.price_handler.tickers[\"AMZN\"][\"bid\"], \n Decimal(\"502.10015\")\n )\n self.assertEqual(\n self.price_handler.tickers[\"AMZN\"][\"ask\"], \n Decimal(\"502.11985\")\n )","title":""},{"docid":"7ce1beb83e693ec8647857b8f4847843","score":"0.5594893","text":"def tick(self, now, elapsed):\n raise NotImplementedError","title":""},{"docid":"bb3ac77e3758dfd85ca82d901cf43327","score":"0.55913913","text":"def timestep(self, simsystem, osc, obs):\n pass","title":""},{"docid":"436b9f1e19b0555a53a94e5f1958a500","score":"0.5589302","text":"def on_tick(self, tick: TrainingTickPacket) -> Optional[Grade]:\n pass # Continue by default","title":""},{"docid":"c5313eced743ca08b3b75da340cf157e","score":"0.5583983","text":"def tick(self):\n self.push_orders_from_queue_to_env()\n self.remove_orders_from_env()","title":""},{"docid":"6b6dad85ce05249c116881412581c003","score":"0.5583846","text":"def position(self, time):","title":""},{"docid":"fb60a891cf2bb559f91eb210c9d05282","score":"0.55787194","text":"def test_Tickable_tickAccumGetsProperValueAfter1Second( self ):\n\t\timport time\n\t\tself.t.tick()\n\t\tself.assertEqual( self.t.tickAccum.seconds, 0, \"Should be 0\" )\n\t\ttime.sleep(1)\n\t\tself.t.tick()\n\t\tself.assertEqual( self.t.tickAccum.seconds, 1, \"Should be about 1\" )","title":""},{"docid":"c41626095a41ac5684951f26cffbd8d5","score":"0.5573586","text":"def end_tick(self):\n if self.iactive is not None and self.scenes:\n self.scenes[self.iactive].end_tick()","title":""}],"string":"[\n {\n \"docid\": \"47e4d0cbcb6e027f154a33d964fd0780\",\n \"score\": \"0.76231015\",\n \"text\": \"def tick(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"47e4d0cbcb6e027f154a33d964fd0780\",\n \"score\": \"0.76231015\",\n \"text\": \"def tick(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c6895c04d064960b1ae0bf4a4da83d20\",\n \"score\": \"0.75546896\",\n \"text\": \"def tick(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c6895c04d064960b1ae0bf4a4da83d20\",\n \"score\": \"0.75546896\",\n \"text\": \"def tick(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fa5b9e7cb1da1b9aaba893abc7f61a3e\",\n \"score\": \"0.71828836\",\n \"text\": \"def tick(self):\\n\\t\\tprint('Must implement tick method')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"21052662d26063a1de0e4df86f5cc5b8\",\n \"score\": \"0.70880234\",\n \"text\": \"def tick_handler(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cedc0f1436ad90cd3e7334501714b7db\",\n \"score\": \"0.6972772\",\n \"text\": \"def play_tick(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9db75ec327a0b6e4adee278c6bea2aad\",\n \"score\": \"0.69448376\",\n \"text\": \"def Tick1S():\\n#---------------------------------------------------------------\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f6b05c9c18c04aba7eb58245b11add60\",\n \"score\": \"0.6774041\",\n \"text\": \"def on_event_new_tick(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1f9bb8d4246d809321fa4bf354427e6c\",\n \"score\": \"0.66825753\",\n \"text\": \"def tick(self, gamestate):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6d7ea7315bd8ac95ba29105ee17c9b12\",\n \"score\": \"0.66772\",\n \"text\": \"def Tick100MS():\\n#---------------------------------------------------------------\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7182d0ac848260612b814a633a7d7be2\",\n \"score\": \"0.66086775\",\n \"text\": \"def tick(self, sim):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"56326e14c9c27b9d96388c6abd44917c\",\n \"score\": \"0.65953845\",\n \"text\": \"def tick(self):\\n raise NotImplementedError('You must implement this.')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c06fea3f96b163280f0a338958457004\",\n \"score\": \"0.655352\",\n \"text\": \"def new_tick(self, msg):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2c5f4fa64dc17db4472fbce28743b03f\",\n \"score\": \"0.65278935\",\n \"text\": \"def ticking(self):\\n self.ready()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b5c2edbd87a66dadfd9eebf02006e48a\",\n \"score\": \"0.6331\",\n \"text\": \"def on_tick() -> None:\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"95f2cdfeb1fe90c4ab87164d1e5ecccc\",\n \"score\": \"0.6325778\",\n \"text\": \"def advance_time():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7e279f82fd8010fb5a69d595e2367ba6\",\n \"score\": \"0.6290593\",\n \"text\": \"def _tick(self):\\n self._update_agent_stats()\\n\\n self.handle_call_events()\\n\\n if not self._shift_over:\\n self.calculate()\\n\\n if self._current_time % self.REPORTING_INTERVAL == 0:\\n self.print_report()\\n\\n self._create_checkpoint()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7c8a8117e379e5f45abdbc2451cc30c0\",\n \"score\": \"0.6217834\",\n \"text\": \"def next_event(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3808952aa046cafd9993d295316ead3a\",\n \"score\": \"0.6190031\",\n \"text\": \"def tick(self):\\r\\n self.times.append(timeit.default_timer())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"59b0fa88992b8fb1612d1356149a7082\",\n \"score\": \"0.6173794\",\n \"text\": \"def tick(self) -> bool:\\n return False\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7fa46544c2dfee7177f828ed7d3ab244\",\n \"score\": \"0.6170556\",\n \"text\": \"def _ticktock2(self):\\n ui = self._ui\\n \\n now = dt.utcnow()\\n self._ui['tick_ends'].appendleft(now)\\n \\n counter = ui['counter']\\n ui['counter'] = counter +1\\n \\n if ui['sync'] is not None:\\n return\\n \\n \\n self._ui['entries'].appendleft(now)\\n \\n if not counter:\\n ui['epoch'] = now\\n ui['first'] = now\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0438e92ffc4a6d87d73cfa42d3aa0055\",\n \"score\": \"0.614751\",\n \"text\": \"def tick():\\r\\n global tenths\\r\\n tenths = tenths + 1\\r\\n format(tenths)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4d8b0c207c4f4419126c23b03b12f48f\",\n \"score\": \"0.60896516\",\n \"text\": \"def tickle_me():\\n\\tload_til(500.0)\\n\\treturn \\\"Tickling you. (half-second)\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b4519cdf915e87d087aa394273ccc251\",\n \"score\": \"0.60748243\",\n \"text\": \"def tick(self, amount):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0df62d77e1b3e3def45dcdc4eadd07d9\",\n \"score\": \"0.6068059\",\n \"text\": \"def performGameCycle(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ce4ea50f299f888de2b575b8fcff76dd\",\n \"score\": \"0.6025078\",\n \"text\": \"def update(self) -> None:\\n time_elapsed = min(self.time_to_tick, self.time_to_weave)\\n self.time += time_elapsed\\n\\n # Handle DoTs\\n if self.song_began and self.time % 3000 == self.tick_offset:\\n for _ in range(DOTS_UP):\\n self.on_tick()\\n\\n # Natural BL regeneration\\n if self.bl_stacks < MAX_BL_STACKS:\\n if self.bl_cd - time_elapsed <= 0:\\n self.bl_stacks += 1\\n\\n # If we're still not at max stacks, lower the CD\\n if self.bl_stacks < MAX_BL_STACKS:\\n self.bl_cd = (self.bl_cd - time_elapsed) % 15000\\n else:\\n self.bl_cd = 15000 \\n else:\\n self.bl_cd -= time_elapsed\\n\\n # EA regeneration\\n if self.ea_cd > 0:\\n self.ea_cd = max(0, self.ea_cd - time_elapsed)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4c1a43e5f913bd740df6d94ab87221b9\",\n \"score\": \"0.60147256\",\n \"text\": \"def called_every_second(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3de663b1de6663b09b0ea6b0d7e17866\",\n \"score\": \"0.6002003\",\n \"text\": \"def tick(self):\\n\\n previous_hour = self.__hours\\n Clock.tick(self)\\n if (self.__hours < previous_hour):\\n self.advance()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"03c71c964933df3c6b5d4c6bc2433e13\",\n \"score\": \"0.59970266\",\n \"text\": \"def periodic():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"94799c5ab462aca47cf0ef4b05f3014e\",\n \"score\": \"0.5991244\",\n \"text\": \"def start_tick(self):\\n if self.iactive is not None and self.scenes:\\n self.scenes[self.iactive].start_tick()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2319c8a53be6def32ed9589ca70780fe\",\n \"score\": \"0.5975583\",\n \"text\": \"def step(self):\\n self.incendio()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e036c2d95a166ac7d43296b88b699573\",\n \"score\": \"0.5962916\",\n \"text\": \"def pause_tick(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"76e811b4cb6512f0e6d2d6f9233d648e\",\n \"score\": \"0.5962218\",\n \"text\": \"def start(self):\\n self.stop()\\n self.ticking = 1\\n self.step()\\n self.tickId = self.parent.after(self.tickDelay, self.start)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"24deef73ebf7990d05e975d50d7a5918\",\n \"score\": \"0.59597754\",\n \"text\": \"def step(self):\\n self.schedule.step()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"24deef73ebf7990d05e975d50d7a5918\",\n \"score\": \"0.59597754\",\n \"text\": \"def step(self):\\n self.schedule.step()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"54ae33ddbb2ab5a1b55c19d855444a19\",\n \"score\": \"0.5947314\",\n \"text\": \"def __calculate_next_tick(self, ref_time_stamp):\\n # The remaining time is calculated as follows\\n # The ref time marks the start of job execution\\n # time consumed by job is current time minus the ref time\\n # Thus the remaining time is the difference between the consumed time and the frequency time\\n # If the job consumes more time than the frequency allows, the calculated time will be negative\\n # In that case, the next_tick shall be set to zero forcing zero sleep and immediate execution of next iteration\\n next_tick = self.__clock_tick_duration_seconds - (time.time() - ref_time_stamp)\\n self.__next_tick = 0 if next_tick < 0 else next_tick\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bd98cdd2868727f877e1e9019a9d31a9\",\n \"score\": \"0.59169257\",\n \"text\": \"def tick():\\n global t\\n t = t + 1\\n #print \\\"test\\\"+ str(t)\\n format(t)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8b92c543267613037f0e9b3fb23d1f70\",\n \"score\": \"0.59071636\",\n \"text\": \"def next_track(self):\\r\\n if self.is_active:\\r\\n self.sp.next_track()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"27118093759e678b4d56e476e035fa64\",\n \"score\": \"0.58784366\",\n \"text\": \"def tick(self, now=None):\\r\\n if now is None:\\r\\n # now won't be None in unit tests\\r\\n now = time.time()\\r\\n for event in events.TICK_EVENTS:\\r\\n period = event.period\\r\\n last_tick = self.ticks.get(period)\\r\\n if last_tick is None:\\r\\n # we just started up\\r\\n last_tick = self.ticks[period] = timeslice(period, now)\\r\\n this_tick = timeslice(period, now)\\r\\n if this_tick != last_tick:\\r\\n self.ticks[period] = this_tick\\r\\n events.notify(event(this_tick, self))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c2dbd678720b9ab300afd2d7550eed53\",\n \"score\": \"0.58740884\",\n \"text\": \"def tick():\\n global countdown\\n countdown -= 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a03905a89dd14f70ca777ad674589f7a\",\n \"score\": \"0.58666366\",\n \"text\": \"def tick(self, ticktime_ms):\\n\\n self.next_locations = self.request_next_locations(ticktime_ms)\\n\\n return\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e98f5fbb08a37fc090fd1042582ecb75\",\n \"score\": \"0.5860322\",\n \"text\": \"def step(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e98f5fbb08a37fc090fd1042582ecb75\",\n \"score\": \"0.5860322\",\n \"text\": \"def step(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e98f5fbb08a37fc090fd1042582ecb75\",\n \"score\": \"0.5860322\",\n \"text\": \"def step(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e98f5fbb08a37fc090fd1042582ecb75\",\n \"score\": \"0.5860322\",\n \"text\": \"def step(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d0067d3090d07677b31084c970512d39\",\n \"score\": \"0.58435094\",\n \"text\": \"def next(self):\\n for d in self.getdatanames(): # Looping through all symbols\\n pos = self.getpositionbyname(d).size or 0\\n if pos == 0: # Are we out of the market?\\n # Consider the possibility of entrance\\n # Notice the indexing; [0] always means the present bar, and [-1] the bar immediately preceding\\n # Thus, the condition below translates to: \\\"If today the regime is bullish (greater than\\n # 0) and yesterday the regime was not bullish\\\"\\n if self.regime[d][0] > 0 and self.regime[d][-1] <= 0: # A buy signal\\n self.buy(data=self.getdatabyname(d))\\n\\n else: # We have an open position\\n if self.regime[d][0] <= 0 and self.regime[d][-1] > 0: # A sell signal\\n self.sell(data=self.getdatabyname(d))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"80563f63bb74366790fe901deb7809c9\",\n \"score\": \"0.58254075\",\n \"text\": \"def lasttick(self):\\n if self.__lasttick:\\n return self.__lasttick\\n else:\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f88dc84e558db338cab6d32a89b41386\",\n \"score\": \"0.58142823\",\n \"text\": \"def nxt_followed(self, handle, nxt_handle, x_axis, y_axis):\\n print \\\"moving nxt to next point of the path\\\"\\n return {'ack': 'got followed'}\",\n \"title\": \"\"\n },\n {\n \"docid\": \"70d8a735611647b0debb6be4f385b9a0\",\n \"score\": \"0.58093745\",\n \"text\": \"def on_tick(self, tick: TickData):\\n if not tick.last_price:\\n return\\n\\n # update tick\\n self.last_tick = tick\\n\\n # update vline for different pairs\\n #self.vg[tick.vt_symbol].update_tick(tick=tick)\\n #print(tick)\\n #print(self.vg[tick.vt_symbol].vline)\\n\\n #self.last_vline = self.vg[self.vt_symbol].vline\\n\\n #for v in self.vg.vline_buf:\\n # if self.vg.vline_buf[v].volume < 0.9*v:\\n # return\\n\\n \\\"\\\"\\\"\\\"\\\"\\\"\\n #self.last_tick = tick\\n #self.write_log(f\\\"Tick: {tick.last_price} TS: {tick.datetime}\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"177287ab7295d082e24b131a86bcfeae\",\n \"score\": \"0.58038265\",\n \"text\": \"def tick(self):\\n if self.stopped:\\n return\\n \\n last_time = self.current_time\\n last_clock = self.last_clock_time\\n \\n # first, determine new time\\n clock_time = time()\\n if last_clock is None:\\n last_clock = clock_time\\n diff = clock_time - last_clock\\n new_time = (self.direction * self.rate * diff) + last_time\\n \\n # update the time\\n self.last_clock_time = clock_time\\n self.current_time = new_time\\n \\n # now we make sure we're in bounds (we don't do this before, since it\\n # can cause us to skip events that are at boundaries.\\n self.current_time = max(self.current_time, 0)\\n self.current_time = min(self.current_time, self.length())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"836e368944edb41f943f5ffde76ee6a9\",\n \"score\": \"0.57948995\",\n \"text\": \"def tick(self):\\n self.time += 1\\n self.calculate_weights()\\n if not self.time % self.rotation_time:\\n self.rotate()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6123eadcf90a2a9bf107ccb4c90c8243\",\n \"score\": \"0.5779648\",\n \"text\": \"def increment_time(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"306a240143120063ccbcf19a543936df\",\n \"score\": \"0.577839\",\n \"text\": \"def on_tick(self, tick: TickData):\\n if (\\n self.last_tick_time\\n and self.last_tick_time.minute != tick.datetime.minute\\n ):\\n bars = {}\\n for vt_symbol, bg in self.bgs.items():\\n bars[vt_symbol] = bg.generate()\\n self.on_bars(bars)\\n\\n bg: BarGenerator = self.bgs[tick.vt_symbol]\\n bg.update_tick(tick)\\n\\n self.last_tick_time = tick.datetime\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bef3c65d982c6ee104b14f79694ed1ff\",\n \"score\": \"0.5773426\",\n \"text\": \"def tick(self):\\n self._wrap_lock(self._tick)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c457d216db7375602c3d350accf3248f\",\n \"score\": \"0.5770214\",\n \"text\": \"def tick(self):\\n t = self.time()\\n self._dt = t - self._t\\n self._t = t\\n self._frame_times.append(self._dt)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"befbaa99edbe8f05a04b4a98d7bdb66e\",\n \"score\": \"0.5769967\",\n \"text\": \"def run_now(self):\\n self.last_check = 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"abdf57dc2a7f86e7343cf784cb263754\",\n \"score\": \"0.5767029\",\n \"text\": \"def next(self):\\n if not self.position:\\n if self.close[0] > self.ketler.upper[0]:\\n self.order = self.order_target_percent(target=0.95)\\n else:\\n if self.close[0] < self.ketler.expo[0]:\\n self.order = self.sell()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3b73c601130a0080df06a82800d61ec2\",\n \"score\": \"0.5761602\",\n \"text\": \"def next(self):\\n for d in self.getdatanames(): # Looping through all symbols\\n pos = self.getpositionbyname(d).size or 0\\n if pos == 0: # Are we out of the market?\\n # Consider the possibility of entrance\\n # Notice the indexing; [0] always means the present bar, and [-1] the bar immediately preceding\\n # Thus, the condition below translates to: \\\"If today the regime is bullish (greater than\\n # 0) and yesterday the regime was not bullish\\\"\\n if self.sma[d][0] * self.params.var1 > self.getdatabyname(d).high[0]: # A buy signal\\n self.order_target_percent(data=self.getdatabyname(d), target=0.98)\\n\\n else: # We have an open position\\n if self.getdatabyname(d).close[-1] * self.params.var2 <= self.getdatabyname(d).high[0]: # A sell signal\\n self.order_target_percent(data=self.getdatabyname(d), target=0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bfedda1685cc4fe553c253b697ca3794\",\n \"score\": \"0.57515013\",\n \"text\": \"def do_timestep(self, ticks) -> None:\\n if ticks == 0:\\n return\\n\\n timeplus = float(ticks) / float(self.ticks_per_beat)\\n if not self._pos_feed:\\n self._acumulated_time += ticks\\n if self._acumulated_time >= self._min_time_division and not self._pos_feed:\\n self.position += 1\\n self._acumulated_time = 0\\n self._pos_feed = True\\n\\n if self._last_note_on:\\n self.distance = timeplus\\n else:\\n self.distance += timeplus\\n self._last_note_on = False\\n\\n for note in self.active_notes:\\n note.length += timeplus\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f26b04ba0299607b110f6af8bf9f2017\",\n \"score\": \"0.57501334\",\n \"text\": \"def next(self):\\n\\n # Determine which set of moving averages to use\\n curdate = self.datetime.date(0)\\n dtidx = None # Will be index\\n # Determine which period (if any) we are in\\n for sd, ed in self.date_combos:\\n # Debug output\\n # print('{}: {} < {}: {}, {} < {}: {}'.format(\\n # len(self), sd, curdate, (sd <= curdate), curdate, ed, (curdate <= ed)))\\n if sd <= curdate and curdate <= ed:\\n dtidx = (sd, ed)\\n # Debug output\\n # print('{}: the dtixdx is {}, and curdate is {};'.format(len(self), dtidx, curdate))\\n for d in self.getdatanames(): # Looping through all symbols\\n pos = self.getpositionbyname(d).size or 0\\n if dtidx is None: # Not in any window\\n break # Don't engage in trades\\n if pos == 0: # Are we out of the market?\\n # Consider the possibility of entrance\\n # Notice the indexing; [0] always mens the present bar, and [-1] the bar immediately preceding\\n # Thus, the condition below translates to: \\\"If today the regime is bullish (greater than\\n # 0) and yesterday the regime was not bullish\\\"\\n '''if self.slowma[d][dtidx][0] > self.getdatabyname(d).close[0]: # A buy signal\\n self.sell(data=self.getdatabyname(d), size=1000)\\n\\n else: # We have an open position\\n if self.fastma[d][dtidx][0] < self.getdatabyname(d).close[0]: # A sell signal\\n self.close(data=self.getdatabyname(d), size=1000)\\n '''\\n if self.sma[d][dtidx][0] * self.var1[d][dtidx] > self.getdatabyname(d).high[0]: # A buy signal\\n self.order_target_percent(data=self.getdatabyname(d), target=0.98)\\n\\n else: # We have an open position\\n if self.getdatabyname(d).close[-1] * self.var2[d][dtidx] <= self.getdatabyname(d).high[0]: # A sell signal\\n self.order_target_percent(data=self.getdatabyname(d), target=0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"65b0875fe77e17a3b8d75adf58219632\",\n \"score\": \"0.57475924\",\n \"text\": \"def tick(self):\\n\\n # next historical order to be sent\\n\\n oborder = self.hist_orders[self.ob_idx]\\n\\n # if I have queued orders\\n if self.my_queue:\\n # if my order reaches the orderbook before the next historical order\\n if self.my_queue[0].timestamp < oborder[self.col_idx['timestamp']]:\\n my_order = self.my_queue.popleft()\\n self._send_to_orderbook(my_order, is_mine=True)\\n self.remove_vol_in_queue(my_order[self.col_idx['uid']])\\n return\\n\\n # otherwise sent next historical order\\n self._send_historical_order(oborder)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f6d140c7056e7f3f75b4a69e04f6b25d\",\n \"score\": \"0.5744944\",\n \"text\": \"def _on_tick(self, args: Tuple, kwargs: Dict) -> None:\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6db101e376fc8c48eab7fbaace6103a5\",\n \"score\": \"0.5743131\",\n \"text\": \"def tick(self):\\n while self.active:\\n for coil in self.ball_search_coils:\\n self.pop_coil(coil)\\n yield Timing.secs(self.machine.config['ball_search']\\\\\\n ['secs between ball search coils'])\\n yield Timing.secs(self.machine.config['ball_search']\\\\\\n ['secs between ball search rounds'])\\n # todo do we have to deal with switches that might be hit due to these\\n # coils firing?\\n # todo should the above code also look for self.active?\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9350ee10aabc339a2aa5e3462385fcb8\",\n \"score\": \"0.5741916\",\n \"text\": \"def _ticktock(self):\\n \\n ui = self._ui\\n now = dt.utcnow() \\n ui['ticks'].appendleft(now)\\n \\n if ui['sync'] is None:\\n return\\n \\n \\n counter = ui['counter']\\n if not counter:\\n self._ticktock_1st(now)\\n \\n \\n entry = self._synced(now)\\n ui['entries'].appendleft(entry)\\n \\n if not counter:\\n ui['first'] = entry\",\n \"title\": \"\"\n },\n {\n \"docid\": \"78689bed249ecaf6cf004b3f48055669\",\n \"score\": \"0.5733522\",\n \"text\": \"def on_tick(self, tick: TickData):\\n self.bg5.update_tick(tick)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d994dae4eef2b1336265ae6a2f02b241\",\n \"score\": \"0.5730125\",\n \"text\": \"def step(self):\\r\\n ...\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c0cd4dca1c2f1b00a602b29bb1107f20\",\n \"score\": \"0.5726646\",\n \"text\": \"def do_tick(self):\\n for member in self.members:\\n member.tick(self.tick_count * swimprotocol.SWIM.T)\\n self.tick_count = self.tick_count + 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"17715d50d4aba1afe1b7be37b19195d5\",\n \"score\": \"0.57241493\",\n \"text\": \"def running():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"67d1fd75b3152adee56252abf0c94f95\",\n \"score\": \"0.57208514\",\n \"text\": \"def __tick(self):\\n def set_current_time():\\n now = datetime.datetime.now()\\n self.__hour = now.hour\\n self.__minute = now.minute\\n self.__second = now.second\\n self.notifyAll()\\n\\n self.__interval = Interval(set_current_time, 3)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1dc3ca2a84edb0bea255cf1365c4eea3\",\n \"score\": \"0.57200813\",\n \"text\": \"def tick(cls):\\n cls.instance_.finishActive()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9bd74a9679855c9b70878c353cce289a\",\n \"score\": \"0.5699552\",\n \"text\": \"def timer():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"16fee983405830fbcdc81e6215b804d8\",\n \"score\": \"0.56920654\",\n \"text\": \"def run_logic(self):\\n\\n self._clock.tick(60)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2b5edd0393607d05f14af1131611718e\",\n \"score\": \"0.5676555\",\n \"text\": \"def _schedule_next_flush(self):\\n #time until the hour rolls over:\\n vals = time.localtime()\\n timeLeft = 60*(60-vals[4]) - vals[5]\\n timeLeft += 30\\n ##DEBUG:\\n #timeLeft = 30\\n self._next_flush_event = reactor.callLater(timeLeft, self._flush_event_logs)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8ed86ba25084a59523d90cb5630967a9\",\n \"score\": \"0.56755614\",\n \"text\": \"def advance(self):\\n None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"38c78989fdeeec4265bac4b2258dbb5c\",\n \"score\": \"0.5666694\",\n \"text\": \"def tick(self):\\n if self.currentTask is not None:\\n self.timeRemaining -= 1\\n if(self.timeRemaining <= 0):\\n self.currentTask = None\\n self.timeRemaining = 0 # just in case it goes negative\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0e43b0f7b0d518551bfcc7bfbfe27a7c\",\n \"score\": \"0.56557053\",\n \"text\": \"def tick(self):\\r\\n if self.seconds == 59:\\r\\n self.seconds = 0\\r\\n if (self.minutes == 59):\\r\\n self.minutes = 0\\r\\n self.hours = 0 if self.hours==23 else self.hours + 1\\r\\n else:\\r\\n self.minutes += 1;\\r\\n else:\\r\\n self.seconds += 1;\",\n \"title\": \"\"\n },\n {\n \"docid\": \"681682eaa53da71329813e7f88ce4fd5\",\n \"score\": \"0.56551063\",\n \"text\": \"def loop():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3e5df73a786e2c9fc2c6adebc1e083bd\",\n \"score\": \"0.5647457\",\n \"text\": \"def on_epoch_end(self):\\n # TODO: Some sort of shuffling?\\n return\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7b7afbfb0e0595e84e127c27b9706c8f\",\n \"score\": \"0.56371874\",\n \"text\": \"def start_epoch(self):\\r\\n pass # for this type of con. method we don't do anything\\r\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ef8176ebb5b0e3b557bf09a6d76dc29f\",\n \"score\": \"0.5635328\",\n \"text\": \"def timer_tick(self, *args):\\n # Generate a new number and increment the tick count\\n new_val = self._generator()\\n self.num_ticks += len(new_val)\\n\\n # grab the existing data, truncate it, and append the new point.\\n # This isn't the most efficient thing in the world but it works.\\n cur_data = self.viewer.data\\n # new_data = np.hstack((cur_data[-self.max_num_points+1:], [new_val]))\\n new_data = np.r_[cur_data[-self.max_num_points+1:], new_val]\\n new_index = np.arange(self.num_ticks - len(new_data) + 1,\\n self.num_ticks + 0.01)\\n\\n self.viewer.index = new_index\\n self.viewer.data = new_data\\n return\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ccc7a219d5e41f50ea4f1837f24a6667\",\n \"score\": \"0.5634773\",\n \"text\": \"def step(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ccc7a219d5e41f50ea4f1837f24a6667\",\n \"score\": \"0.5634773\",\n \"text\": \"def step(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"79cfbcb7e32fbf9fa1d3aa530ba59a00\",\n \"score\": \"0.5633921\",\n \"text\": \"def step(self):\\n info = self.r.tolist()+self.v.tolist()\\n self.v += (self.brain.feedForward(info)[-1]-np.array([.5,.5]))*dt\\n self.r += self.v*dt\",\n \"title\": \"\"\n },\n {\n \"docid\": \"03be9d8492481dd1a8d37c35b4fd9a5b\",\n \"score\": \"0.5627474\",\n \"text\": \"def Schedule_Next(self,Now):\\n tf = max([self.orig.travel_factor, self.dest.travel_factor])\\n #delta_t = int(abs(round(RNG.Normal(self.T*tf, self.T_std), 0)))\\n delta_t = np.random.poisson(self.T*tf)\\n Flight_Generator.Schedule_Flight(Now+delta_t, self)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f5419b268d48246c4068563aed7dc572\",\n \"score\": \"0.56225395\",\n \"text\": \"def tick_tock():\\n text = \\\"Tock\\\"\\n if time.localtime()[5] % 2 == 0:\\n text = \\\"Tick\\\"\\n print(text)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aa19df868a4272c7dc8bd6f7423164f0\",\n \"score\": \"0.56224823\",\n \"text\": \"def step(self, dt):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"96f9e3e7219c2872b4f978aaf1814982\",\n \"score\": \"0.5615514\",\n \"text\": \"def timer_tick(self, *args):\\r\\n # Generate a new number and increment the tick count\\r\\n new_val = self._generator(self.mean, self.stddev)\\r\\n self.num_ticks += 1\\r\\n\\r\\n # grab the existing data, truncate it, and append the new point.\\r\\n # This isn't the most efficient thing in the world but it works.\\r\\n cur_data = self.viewer.data\\r\\n new_data = np.hstack((cur_data[-self.max_num_points+1:], [new_val]))\\r\\n new_index = np.arange(self.num_ticks - len(new_data) + 1,\\r\\n self.num_ticks + 0.01)\\r\\n\\r\\n self.viewer.index = new_index\\r\\n self.viewer.data = new_data\\r\\n return\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bd906130705ddfdbea59e2491536b644\",\n \"score\": \"0.56114537\",\n \"text\": \"def redoNext():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d418af1fd1523b5fe28559bce750a109\",\n \"score\": \"0.56098574\",\n \"text\": \"def get_on_next(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"18df9770ccd94aae29d3caf35c637a1a\",\n \"score\": \"0.5608524\",\n \"text\": \"def running(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9d03589020a362406d0968edcc4f34ed\",\n \"score\": \"0.5605621\",\n \"text\": \"def tick(self):\\n if self._current_run is None:\\n self._current_run = asyncio.ensure_future(self.run_once())\\n asyncio.get_event_loop().run_until_complete(self._current_run)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"999ba46dcb5f3c5346796cba77c004ca\",\n \"score\": \"0.5600143\",\n \"text\": \"def _next_iteration(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e315f73351409b3a6e3f9ecbfd239c1c\",\n \"score\": \"0.5595848\",\n \"text\": \"def test_stream_all_ticks(self):\\n # Stream to Tick #1 (GOOG)\\n self.price_handler.stream_next_tick()\\n self.assertEqual(\\n self.price_handler.tickers[\\\"GOOG\\\"][\\\"timestamp\\\"].strftime(\\n \\\"%d-%m-%Y %H:%M:%S.%f\\\"\\n ), \\n \\\"01-02-2016 00:00:01.358000\\\"\\n )\\n self.assertEqual(\\n self.price_handler.tickers[\\\"GOOG\\\"][\\\"bid\\\"], \\n Decimal(\\\"683.56000\\\")\\n )\\n self.assertEqual(\\n self.price_handler.tickers[\\\"GOOG\\\"][\\\"ask\\\"], \\n Decimal(\\\"683.58000\\\")\\n )\\n\\n # Stream to Tick #2 (AMZN)\\n self.price_handler.stream_next_tick()\\n self.assertEqual(\\n self.price_handler.tickers[\\\"AMZN\\\"][\\\"timestamp\\\"].strftime(\\n \\\"%d-%m-%Y %H:%M:%S.%f\\\"\\n ), \\n \\\"01-02-2016 00:00:01.562000\\\"\\n )\\n self.assertEqual(\\n self.price_handler.tickers[\\\"AMZN\\\"][\\\"bid\\\"], \\n Decimal(\\\"502.10001\\\")\\n )\\n self.assertEqual(\\n self.price_handler.tickers[\\\"AMZN\\\"][\\\"ask\\\"], \\n Decimal(\\\"502.11999\\\")\\n )\\n\\n # Stream to Tick #3 (MSFT)\\n self.price_handler.stream_next_tick()\\n self.assertEqual(\\n self.price_handler.tickers[\\\"MSFT\\\"][\\\"timestamp\\\"].strftime(\\n \\\"%d-%m-%Y %H:%M:%S.%f\\\"\\n ), \\n \\\"01-02-2016 00:00:01.578000\\\"\\n )\\n self.assertEqual(\\n self.price_handler.tickers[\\\"MSFT\\\"][\\\"bid\\\"], \\n Decimal(\\\"50.14999\\\")\\n )\\n self.assertEqual(\\n self.price_handler.tickers[\\\"MSFT\\\"][\\\"ask\\\"], \\n Decimal(\\\"50.17001\\\")\\n )\\n\\n # Stream to Tick #10 (GOOG)\\n for i in range(4, 11):\\n self.price_handler.stream_next_tick()\\n self.assertEqual(\\n self.price_handler.tickers[\\\"GOOG\\\"][\\\"timestamp\\\"].strftime(\\n \\\"%d-%m-%Y %H:%M:%S.%f\\\"\\n ), \\n \\\"01-02-2016 00:00:05.215000\\\"\\n )\\n self.assertEqual(\\n self.price_handler.tickers[\\\"GOOG\\\"][\\\"bid\\\"], \\n Decimal(\\\"683.56001\\\")\\n )\\n self.assertEqual(\\n self.price_handler.tickers[\\\"GOOG\\\"][\\\"ask\\\"], \\n Decimal(\\\"683.57999\\\")\\n )\\n\\n # Stream to Tick #20 (GOOG)\\n for i in range(11, 21):\\n self.price_handler.stream_next_tick()\\n self.assertEqual(\\n self.price_handler.tickers[\\\"MSFT\\\"][\\\"timestamp\\\"].strftime(\\n \\\"%d-%m-%Y %H:%M:%S.%f\\\"\\n ), \\n \\\"01-02-2016 00:00:09.904000\\\"\\n )\\n self.assertEqual(\\n self.price_handler.tickers[\\\"MSFT\\\"][\\\"bid\\\"], \\n Decimal(\\\"50.15000\\\")\\n )\\n self.assertEqual(\\n self.price_handler.tickers[\\\"MSFT\\\"][\\\"ask\\\"], \\n Decimal(\\\"50.17000\\\")\\n )\\n\\n # Stream to Tick #30 (final tick, AMZN)\\n for i in range(21, 31):\\n self.price_handler.stream_next_tick()\\n self.assertEqual(\\n self.price_handler.tickers[\\\"AMZN\\\"][\\\"timestamp\\\"].strftime(\\n \\\"%d-%m-%Y %H:%M:%S.%f\\\"\\n ), \\n \\\"01-02-2016 00:00:14.616000\\\"\\n )\\n self.assertEqual(\\n self.price_handler.tickers[\\\"AMZN\\\"][\\\"bid\\\"], \\n Decimal(\\\"502.10015\\\")\\n )\\n self.assertEqual(\\n self.price_handler.tickers[\\\"AMZN\\\"][\\\"ask\\\"], \\n Decimal(\\\"502.11985\\\")\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7ce1beb83e693ec8647857b8f4847843\",\n \"score\": \"0.5594893\",\n \"text\": \"def tick(self, now, elapsed):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bb3ac77e3758dfd85ca82d901cf43327\",\n \"score\": \"0.55913913\",\n \"text\": \"def timestep(self, simsystem, osc, obs):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"436b9f1e19b0555a53a94e5f1958a500\",\n \"score\": \"0.5589302\",\n \"text\": \"def on_tick(self, tick: TrainingTickPacket) -> Optional[Grade]:\\n pass # Continue by default\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c5313eced743ca08b3b75da340cf157e\",\n \"score\": \"0.5583983\",\n \"text\": \"def tick(self):\\n self.push_orders_from_queue_to_env()\\n self.remove_orders_from_env()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6b6dad85ce05249c116881412581c003\",\n \"score\": \"0.5583846\",\n \"text\": \"def position(self, time):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fb60a891cf2bb559f91eb210c9d05282\",\n \"score\": \"0.55787194\",\n \"text\": \"def test_Tickable_tickAccumGetsProperValueAfter1Second( self ):\\n\\t\\timport time\\n\\t\\tself.t.tick()\\n\\t\\tself.assertEqual( self.t.tickAccum.seconds, 0, \\\"Should be 0\\\" )\\n\\t\\ttime.sleep(1)\\n\\t\\tself.t.tick()\\n\\t\\tself.assertEqual( self.t.tickAccum.seconds, 1, \\\"Should be about 1\\\" )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c41626095a41ac5684951f26cffbd8d5\",\n \"score\": \"0.5573586\",\n \"text\": \"def end_tick(self):\\n if self.iactive is not None and self.scenes:\\n self.scenes[self.iactive].end_tick()\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":396,"cells":{"query_id":{"kind":"string","value":"ba9bf18738bbfb8d5804a416357f11d0"},"query":{"kind":"string","value":"Read in a schema definition for our part of the config and hook it"},"positive_passages":{"kind":"list like","value":[{"docid":"4a9c2e5bea03e0bb0804ad72647ec2bf","score":"0.0","text":"def extend_schema(self, parent_schema):\n schema_path = os.path.join(self.dogen.pwd, \"schema\", \"cct_schema.yaml\")\n schema = {}\n with open(schema_path, 'r') as fh:\n schema = yaml.safe_load(fh)\n\n parent_schema['map']['cct'] = schema","title":""}],"string":"[\n {\n \"docid\": \"4a9c2e5bea03e0bb0804ad72647ec2bf\",\n \"score\": \"0.0\",\n \"text\": \"def extend_schema(self, parent_schema):\\n schema_path = os.path.join(self.dogen.pwd, \\\"schema\\\", \\\"cct_schema.yaml\\\")\\n schema = {}\\n with open(schema_path, 'r') as fh:\\n schema = yaml.safe_load(fh)\\n\\n parent_schema['map']['cct'] = schema\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"20a2e7a8484156b260fdb229de1e1660","score":"0.7257588","text":"def load_schema(self):\n raise NotImplementedError","title":""},{"docid":"a12bfee9e3094a2afc066b5de193e7d9","score":"0.72208834","text":"def input_config_schema(self) -> IDefinitionConfigSchema:","title":""},{"docid":"1aaa12eeb8fcd2e69a5b255fd82fc935","score":"0.6990748","text":"def getSchema():","title":""},{"docid":"86c202456a8db932152b710cb124848e","score":"0.69262326","text":"def define_schema(self) -> None:\n pass","title":""},{"docid":"bdbb3cb8831476d260a1fca630f0fdef","score":"0.64331645","text":"def load_schema(self, path):\n raise NotImplementedError","title":""},{"docid":"1a97a353a946c17db1836d1bb14601e4","score":"0.642445","text":"def load_schema(self):\n query = self.config.get_schemas\n self.cursor.execute(query)\n return self._get_result()","title":""},{"docid":"fdf8cfc9fcfff47bebae3f926f2c607d","score":"0.6417863","text":"def test_read_schema(self):\n assert set(self.s.fields.keys()) \\\n == set(['boolean_field',\n 'int_field',\n 'text_field',\n 'location_field'])\n assert self.s.default_field_name == 'text_field'\n assert self.s.unique_key == 'int_field'","title":""},{"docid":"455d15d2395d68c8573c2b9f5e132008","score":"0.6404794","text":"def _load_schema(schema_name: str) -> dict:\n with open(os.path.join(os.path.dirname(__file__), 'schemas', schema_name)) as f:\n return json.load(f)","title":""},{"docid":"f690c0537ef0a9442abab440818ed322","score":"0.6356305","text":"def get_schema(self, walk, schema, **kwargs):\n raise NotImplemented","title":""},{"docid":"d20eb5b3c38602a6e5ca0948f66be72d","score":"0.63054293","text":"def config_schema(self) -> Optional[JsonObjectSchema]:","title":""},{"docid":"607309fde1470a9863f3b74f96f77421","score":"0.6304943","text":"def get_schema():\n global FULL_SCHEMA\n if FULL_SCHEMA:\n return FULL_SCHEMA\n full_schema = {\n '$schema': 'http://json-schema.org/draft-04/schema#',\n 'id': 'cloud-config-schema', 'allOf': []}\n\n configs_dir = os.path.dirname(os.path.abspath(__file__))\n potential_handlers = find_modules(configs_dir)\n for (_fname, mod_name) in potential_handlers.items():\n mod_locs, _looked_locs = importer.find_module(\n mod_name, ['cloudinit.config'], ['schema'])\n if mod_locs:\n mod = importer.import_module(mod_locs[0])\n full_schema['allOf'].append(mod.schema)\n FULL_SCHEMA = full_schema\n return full_schema","title":""},{"docid":"204df02430bd730be21dcc3c16ad8018","score":"0.6289603","text":"def my_schema_callback(schema):\n for k in [k for k in schema['properties'] if k.startswith('_')]:\n del schema['properties'][k]\n for k in [k for k in schema['properties'] if '/' in k]:\n schema['properties'][k.split('/')[1]] = schema['properties'][k]\n del schema['properties'][k]\n for k in [k for k in schema['properties'] if k.endswith('_id')]:\n if k in schema['required'] or k in schema['systemProperties']:\n continue\n schema['properties'][k.replace('_id', '')] = {'type': ['string', 'null']} # schema['properties'][k]\n del schema['properties'][k]\n # adds extra properties not found in\n schema['category'] = 'bcc extention'\n if 'sizeaxis1' in schema['properties']:\n schema['properties']['lesion'] = {'$ref': '_definitions.yaml#/to_one'}\n return schema","title":""},{"docid":"c49bc1f8afff893a0c9c2bf4eea9fe2d","score":"0.6245679","text":"def loadDBSchema(self):\n\n\t\tprint 'loading database schema: ', self.schemaFile\n\t\twith open(self.schemaFile) as json_file:\n\t\t\tself.schema = json.load(json_file)\n\t\tjson_file.close()\n\t\tassert(self.schema['nTables'] == len(self.schema['tablenames']))\n\t\t# print(self.schema)","title":""},{"docid":"ec5600af127a9a762748b0562e7bfb6e","score":"0.6215938","text":"def _setSchema(self):\n try:\n data = self.request(\"admin/luke\", parameters={'show': \"schema\"})\n\n self._setTypes(data['schema']['types'])\n self.fields = {}\n self._setFields(data['schema']['fields'], self.fields)\n self.dynamicFields = {}\n self._setFields(data['schema']['dynamicFields'], self.dynamicFields)\n\n #Set copySources\n for (fieldname, fieldspecs) in data['schema']['fields'].iteritems():\n for copyfieldname in fieldspecs['copySources']:\n self.fields[fieldname].copySources.append(self.fields[copyfieldname])\n\n #Could we have copyfield for dynamic fields? #FIXME\n\n self.id_field = data['schema']['uniqueKeyField']\n except KeyError, e:\n raise SOLRResponseFormatError, \"Wrong response format: %s %s - %s\" % (KeyError, e, data)","title":""},{"docid":"bafb90925181f38ae9747a47b64098c0","score":"0.62053746","text":"def __init__(self, schema: str):\n if os.path.isfile(schema):\n self._schema = open(schema, 'r').read()\n else:\n self._schema = schema","title":""},{"docid":"440e074d4611c4d29ae4aa82d79a102e","score":"0.6199084","text":"def _schema(self, path, obj, app):\n if path.startswith('#/definitions'):\n last_token = jp_split(path)[-1]\n if app.version == '1.2':\n obj.update_field('name', scope_split(last_token)[-1])\n else:\n obj.update_field('name', last_token)","title":""},{"docid":"87b220f693360af13cb2b927af1ddf4d","score":"0.61490417","text":"def visit_schema(self, schema):\n pass","title":""},{"docid":"b641de252de8d1fdd5216b3e56923568","score":"0.6137045","text":"def load_schema(self, schema):\n self.schema = load_json(schema)\n validate_schema(self.schema)\n self.schema_nx = load_schema_into_networkx(self.schema)","title":""},{"docid":"e88acdb65caf3733d682ebe59491eb94","score":"0.6128808","text":"def _get_schema(self, data):\n return self.schema()","title":""},{"docid":"c0903ca2e5df6a32c23a6cf545428dca","score":"0.60882545","text":"def read_schema_section(self):\n\n # The next tag must be 'SCHEMA'\n tag_line = self.read_line()\n if tag_line is None:\n raise Exception(\"Unexpected EOF, should be SCHEMA tag\")\n (tag, _) = self.parse_tag_line(tag_line)\n if tag != 'SCHEMA':\n raise Exception(\n f\"Unrecoginized tag line_number '{tag_line}', should be SCHEMA\"\n )\n\n # Read the SCHEMA records until the next TAG_TOKEN\n schema_lines = []\n while True:\n line = self.read_line()\n if line is None:\n break\n (tag, _) = self.parse_tag_line(line)\n if tag in self.TAG_TOKENS:\n if tag in ('DATA', 'ERRORS', 'EXISTING_SCHEMA', 'SCHEMA'):\n raise Exception(f\"Unexpected {tag} tag\")\n self.push_back(line)\n break\n schema_lines.append(line)\n\n return ''.join(schema_lines)","title":""},{"docid":"200ae8776af4253ec8ecb5171e6d7ea2","score":"0.6078499","text":"def _read_schema(self):\n cache_filename = os.path.join(\n CACHE_ROOT, \"%s.smt\" % self._representation)\n log.info(\"Attempting to read local schema at %s\" % cache_filename)\n try:\n if time.time() - os.stat(cache_filename).st_mtime > CACHE_EXPIRY:\n log.warning(\"Cache expired, re-pulling\")\n self._pull_schema_definition(cache_filename)\n except OSError:\n log.warning(\"Local schema not found. Pulling from web.\")\n self._pull_schema_definition(cache_filename)\n else:\n log.info(\"Success\")\n\n return cache_filename","title":""},{"docid":"975bc86a280809493d86c0329bf34dbd","score":"0.60747033","text":"def schema(self):\n return _parse_schema_resource(self._properties.get('schema', {}))","title":""},{"docid":"cce4eb26e8258b71145b12a933cb50d2","score":"0.6001636","text":"def SCHEMA(self):\n pass","title":""},{"docid":"cce4eb26e8258b71145b12a933cb50d2","score":"0.6001636","text":"def SCHEMA(self):\n pass","title":""},{"docid":"cce4eb26e8258b71145b12a933cb50d2","score":"0.6001636","text":"def SCHEMA(self):\n pass","title":""},{"docid":"60a65ef4574d42fd7dc9f0c36bb9286b","score":"0.59796387","text":"def __init__(self, definition=None):\n super(Schema, self).__init__()\n self._map = {}\n self._bq_schema = definition\n self._populate_fields(definition)","title":""},{"docid":"75d02d1dab28c87ca8b43ee8a8328657","score":"0.5960625","text":"def main():\n parser = get_parser()\n handle_schema_args('cloudconfig-schema', parser.parse_args())\n return 0","title":""},{"docid":"8b821d6db3a46d7cf7d02d19fb61bd8c","score":"0.5945147","text":"def new_schema():\n generate_new_schema()","title":""},{"docid":"083a001fc0b2c3122ccdc15cfee33ed3","score":"0.59255975","text":"def get_schema(self) -> dict:\n if not os.path.isfile(self.path):\n logger.error('Path `%s` does not resolve as a valid file.', self.path)\n raise ImproperlyConfigured(\n f'The path `{self.path}` does not point to a valid file. Make sure to point to the specification file.'\n )\n try:\n logger.debug('Fetching static schema from %s', self.path)\n with open(self.path, 'r') as f:\n content = f.read()\n except Exception as e:\n logger.exception('Exception raised when fetching OpenAPI schema from %s. Error: %s', self.path, e)\n raise ImproperlyConfigured(\n f'Unable to read the schema file. Please make sure the path setting is correct.\\n\\nError: {e}'\n )\n if '.json' in self.path:\n return json.loads(content)\n elif '.yaml' in self.path or '.yml' in self.path:\n return yaml.load(content, Loader=yaml.FullLoader)\n else:\n raise ImproperlyConfigured('The specified file path does not seem to point to a JSON or YAML file.')","title":""},{"docid":"f7693fe798fd0f30e90a47f25a1c1fbb","score":"0.5916935","text":"def set_schema(obj, eng):\n if '$schema' not in obj.data:\n obj.data['$schema'] = \"{data_type}.json\".format(\n data_type=obj.data_type or eng.workflow_definition.data_type\n )\n\n if not obj.data['$schema'].startswith('http'):\n obj.data['$schema'] = url_for(\n 'invenio_jsonschemas.get_schema',\n schema_path=\"records/{0}\".format(obj.data['$schema'])\n )","title":""},{"docid":"485ee6f1c6dbec358f4df75ecb17b89b","score":"0.5913141","text":"def metadatablock_json_schema():\n\n return open(\"./tests/fixtures/dataversebase/toydataset.schema.json\").read()","title":""},{"docid":"a15a98e8ba3f81903ffbe3a9c145f618","score":"0.5878806","text":"def validate(self):\n logger.info('Reading plugin schema file %s', self.__schema_file)\n\n if self.__plugin_schemas is None:\n self.__plugin_schemas = self.__read_schema_file()\n\n logger.debug('Validating plugin schema file content : %s',\n self.__plugin_schemas)\n self.__validate_schemas()","title":""},{"docid":"e60d2153351382599d56a15394fbc213","score":"0.58765936","text":"def jsonschema_definition(self) -> Dict[str, Any]:\n pass","title":""},{"docid":"a291c5e4428e987bf6cd472cd3cd6124","score":"0.5869546","text":"def cache_schema():\n # Calling load_schema() will generate the schema as a side effect\n load_schema()","title":""},{"docid":"b2327968a1768478ec2a286d7c03dabb","score":"0.5856529","text":"def __register_schema(self,\n config,\n schema):\n\n if not os.path.exists(schema):\n raise IOError(u'Schema does not exists: {s}'.format(s=schema))\n\n # Place a copy of the schema in self.schema_path\n ensure_path_exists(self.schema_path)\n schema_copy_fn = u'{cfg}.schema.{ext}'.format(cfg=config,\n ext=CONST.json)\n schema_copy = os.path.join(self.schema_path, schema_copy_fn)\n shutil.copyfile(schema, schema_copy)\n\n # Register the schema\n self.__registered_cfg[config][CONST.cfg_schema] = schema_copy_fn","title":""},{"docid":"63b407b09cff9d5c2e654bb3204b8067","score":"0.5853047","text":"def get_schema(self):\n return self.schema","title":""},{"docid":"2de2f068964dc7e016d9d22829df3ce9","score":"0.58503586","text":"def handle_schema_args(name, args):\n exclusive_args = [args.config_file, args.docs]\n if not any(exclusive_args) or all(exclusive_args):\n error('Expected either --config-file argument or --docs')\n full_schema = get_schema()\n if args.config_file:\n try:\n validate_cloudconfig_file(\n args.config_file, full_schema, args.annotate)\n except SchemaValidationError as e:\n if not args.annotate:\n error(str(e))\n except RuntimeError as e:\n error(str(e))\n else:\n print(\"Valid cloud-config file {0}\".format(args.config_file))\n elif args.docs:\n schema_ids = [subschema['id'] for subschema in full_schema['allOf']]\n schema_ids += ['all']\n invalid_docs = set(args.docs).difference(set(schema_ids))\n if invalid_docs:\n error('Invalid --docs value {0}. Must be one of: {1}'.format(\n list(invalid_docs), ', '.join(schema_ids)))\n for subschema in full_schema['allOf']:\n if 'all' in args.docs or subschema['id'] in args.docs:\n print(get_schema_doc(subschema))","title":""},{"docid":"af03ba52442219570687a1a4187ab5b6","score":"0.5816239","text":"def load(self, definition, schema_file, context):\n try:\n validate(definition, self._get_schema_from_file(schema_file))\n except ValidationError:\n raise ConfigException(\n 'Failed to validate interface with schema: {}'.format(\n traceback.format_exc()))\n\n try:\n global_settings = self._load_global_setting(\n definition.get('global_settings'), context\n )\n\n requests = [self._load_request(item) for item in definition['requests']]\n\n return munchify({\n 'meta': munchify(definition['meta']),\n 'tokens': definition['tokens'],\n 'global_settings': global_settings,\n 'requests': requests,\n })\n except Exception as ex:\n error = 'Unable to load configuration: %s' % str(ex)\n _logger.exception(error)\n raise ConfigException(error)","title":""},{"docid":"2ec120889092ad5b8ec8eb2159b54978","score":"0.58096194","text":"def schema(self) -> \"Schema\":\n raise NotImplementedError","title":""},{"docid":"b59d3e184492921c228ee929b2b5bb61","score":"0.5780726","text":"def read_schema(self):\n if self.db.has_collection(self.coll_name) and self.state_coll.has('schema'):\n state = self.state_coll.get('schema')\n else:\n state = {'schema': {}}\n\n return state.get('schema')","title":""},{"docid":"79b9a811772cac241c0f0443de1dfd96","score":"0.57753044","text":"def setupSchema(app,\r\n conn,\r\n grantedusers = ['public'],\r\n publicsyn = True):\r\n r = dbschema.getSchemaVersion(conn, oraschema.LATESTVERSIONS)\r\n\r\n if r['schema-version'] is not None:\r\n raise Exception(\"crossbar.io Repository already installed\")\r\n\r\n return _setupSchema(conn, grantedusers, publicsyn)","title":""},{"docid":"c7417c2d0df3bfa9d3573002a79ea6cc","score":"0.5771426","text":"def db_init( self, schema ):\n #TODO: initialize the database schema\n try: \n pass\n except:\n raise Exceptions.ConfigFault(\"Couldn't initialize database\")","title":""},{"docid":"abee92d108e29d2c2aa7588c3117b4db","score":"0.5769642","text":"def schema(self):\n return self.reader.schema()","title":""},{"docid":"e3551ef3e2b9db4d643d8cb0ad216244","score":"0.576468","text":"def schemas_config(self, configs):\n self.__schemas_config = configs","title":""},{"docid":"fc8ed43719decf60a577ce127c8396ba","score":"0.57510227","text":"def load_schema(self, path):\n f = open(path, \"r\")\n return f.read()","title":""},{"docid":"bae3f86858276df1f2463c3e8b62d516","score":"0.5748631","text":"def schema(self, schema):\n \n self._schema = schema","title":""},{"docid":"30468bd01592082a26d906fb98d18ebb","score":"0.5743769","text":"def schema(self):\n try:\n return self._get_schema()\n except SchemaNotFoundError as error:\n logging.getLogger(__name__).warning(str(error))","title":""},{"docid":"30611bbcdd235a8473f17f25934164e5","score":"0.57144326","text":"def start_schema_creation(self, apiId: str, definition: bytes) -> Dict:\n pass","title":""},{"docid":"be8fba408bea9959911084e8b240b666","score":"0.57089764","text":"def schema(self):\n return self.__schema","title":""},{"docid":"be8fba408bea9959911084e8b240b666","score":"0.57089764","text":"def schema(self):\n return self.__schema","title":""},{"docid":"88053be6879d2b3b66af29c6c8eeece9","score":"0.5685297","text":"def config_schema(self) -> vol.Schema:\n return vol.Schema(\n {\n vol.Required(CONF_API_KEY): str,\n vol.Inclusive(\n CONF_LATITUDE, \"coords\", default=self.hass.config.latitude\n ): cv.latitude,\n vol.Inclusive(\n CONF_LONGITUDE, \"coords\", default=self.hass.config.longitude\n ): cv.longitude,\n vol.Optional(\n CONF_ELEVATION, default=self.hass.config.elevation\n ): vol.Coerce(float),\n }\n )","title":""},{"docid":"217e9646acdc42513a0a14e7fd517f16","score":"0.5679437","text":"def get_gedl_schema(schema_location):\n basepath = \"\"\n #get the module paths to help find the schema in a relitive to ourself\n if(len(sys.path) > 1):\n basepath = sys.path[0]\n path = os.path.join(basepath,schema_location)\n \n if(not os.path.exists(path)):\n #schema not found relitive to the python enviroment, check a local path\n path = schema_location\n if(not os.path.exists(path)):\n #Unable to get python schema\n raise(IOError(\"Unable to fild cle schema (expected at): \" + path))\n \n #we found the schema load it into ram\n print(\"Using GEDL schema: \" + path)\n with open(path,\"r\",encoding=\"UTF-8\") as schemafile:\n return(json.loads(schemafile.read()))","title":""},{"docid":"6836ae553860c0c9ee69e1f31556c20d","score":"0.5676","text":"def retrieveSchemas(self)->None:\n aepp.importConfigFile(\n self.CONFIG['original']['config_file_location'])\n schema_instance = aep_schema.Schema()\n tenant_id = schema_instance.getTenantId()\n schemas = schema_instance.getSchemas()\n obj_schema = {schema['title']: schema['meta:altId']\n for schema in schemas if schema['title'].startswith(\"Adhoc\") == False}\n for schema in obj_schema.values():\n schema = schema_instance.getSchema(schema, full=False, save=True)\n allOf = schema['allOf']\n allOf = [element for element in allOf if '$ref' in element.keys()]\n for element in allOf:\n if 'classes' in element['$ref']:\n myClass = schema_instance.getClass(\n element['$ref'], save=True)\n if 'mixins' in element['$ref']:\n myMixin = schema_instance.getMixin(\n element['$ref'], save=True)","title":""},{"docid":"f37e1b5085f50e6f43ea445681f4915d","score":"0.56728673","text":"def __validate_config(self,\n schema_path,\n obj):\n\n # Load schema\n schema_obj = self.__get_schema_obj(schema_path)\n\n if u'properties' in schema_obj:\n # Make sure schema has reference to TEMPLATE_DEFAULTS_ITEM!\n if TEMPLATE_DEFAULTS_ITEM not in schema_obj[u'properties']:\n schema_obj[u'properties'][TEMPLATE_DEFAULTS_ITEM] = {u'type': u'object'}\n\n # Ensure loaded config is still valid (i.e any external modification hasn't corrupted it)\n validator = Draft4Validator(schema_obj.cfg)\n validator.validate(obj.cfg)","title":""},{"docid":"c1d03056954aec670a4f285b7383b8c3","score":"0.5661043","text":"def test_get_schema_from_api():\n connection = DatabaseSchemaConnection(POSTGREST_URL)\n resp = connection.get_by_id(\"marple-dataset.json\")\n assert resp['$schema'] == 'http://json-schema.org/draft-04/schema#'\n assert isinstance(resp,dict)","title":""},{"docid":"2e81759942d12b9229484596160a4eff","score":"0.56599015","text":"def validate_config(self):\n # with self.spinner.reenter('Validating Config') as grandchild:\n super(Instattack, self).validate_config()\n data = self.config.get_dict()\n\n # This is where we would configure the system settings with the user\n # defined settings.\n # config(data)\n\n # grandchild.warning('Not Currently Validating Schema', fatal=False, options={\n # 'label': True,\n # })","title":""},{"docid":"10ed53159fe945a9a12f51f6fdc28aba","score":"0.5644752","text":"def __init__(self):\n if self.schema is None:\n _cls_name = f\"{self.model.__name__}Schema\"\n self.schema = globals()[_cls_name]","title":""},{"docid":"fd30c838971eabbca690bde0abc9055c","score":"0.56210756","text":"def read_json_schema(schemafile):\r\n with open(schemafile, 'r') as jsonschemafile:\r\n data=jsonschemafile.read() \r\n \r\n json_dict = json.loads(data)\r\n colnames = json_dict['ColumnNames']\r\n offsets = json_dict['Offsets']\r\n includeheader = json_dict['IncludeHeader']\r\n fixedwidthencoding = json_dict['FixedWidthEncoding']\r\n delimitedencoding = json_dict['DelimitedEncoding']\r\n return colnames,offsets,includeheader","title":""},{"docid":"b9628d41b08359b69aabf2fcd64f92b9","score":"0.5620795","text":"def create_schema(self, config_path: str, arg_replacements: Dict) -> Schema:\n return self._create_aepobject(Schema, config_path, arg_replacements)","title":""},{"docid":"5d10b2bc62522850570cfce78e7ba920","score":"0.5619358","text":"def read_existing_schema_section(self):\n\n # The next tag must be 'EXISTING_SCHEMA'\n tag_line = self.read_line()\n if tag_line is None:\n raise Exception(\"Unexpected EOF, should be EXISTING_SCHEMA tag\")\n (tag, _) = self.parse_tag_line(tag_line)\n if tag == 'EXISTING_SCHEMA':\n # Read the EXISTING_SCHEMA records until the next TAG_TOKEN\n schema_lines = []\n while True:\n line = self.read_line()\n if line is None:\n break\n (tag, _) = self.parse_tag_line(line)\n if tag in self.TAG_TOKENS:\n if tag in ('DATA', 'EXISTING_SCHEMA'):\n raise Exception(f\"Unexpected {tag} tag\")\n self.push_back(line)\n break\n schema_lines.append(line)\n return ''.join(schema_lines)\n else:\n self.push_back(tag_line)\n return []","title":""},{"docid":"2e95e4b18a86e7a79b02a4b890a65d5a","score":"0.56126887","text":"def _get_schema(self):\n if not self._schema:\n self._schema = XSDSchema(self.filetype, self.version)\n return self._schema","title":""},{"docid":"cd6970bc9033144b09eac1029c53c4ff","score":"0.5612554","text":"def test_schema(self):\n fti = queryUtility(IDexterityFTI, name=CT)\n schema = fti.lookupSchema()\n self.assertEqual(IFeaturedListings, schema)","title":""},{"docid":"793da77f74b8666b14ab78d098726ff1","score":"0.5611442","text":"def Read(self, *args):\n return _Storage.Storage_Schema_Read(self, *args)","title":""},{"docid":"2dce402a8c5394192518f0d55246b0cc","score":"0.5606407","text":"def _get_config_schema(input_dict: dict[str, Any] | None = None) -> vol.Schema:\n if input_dict is None:\n input_dict = {}\n\n return vol.Schema(\n {\n vol.Required(\n CONF_NAME, default=input_dict.get(CONF_NAME, DEFAULT_NAME)\n ): str,\n vol.Required(CONF_HOST, default=input_dict.get(CONF_HOST)): str,\n vol.Required(\n CONF_DEVICE_CLASS,\n default=input_dict.get(CONF_DEVICE_CLASS, DEFAULT_DEVICE_CLASS),\n ): vol.All(\n str,\n vol.Lower,\n vol.In([MediaPlayerDeviceClass.TV, MediaPlayerDeviceClass.SPEAKER]),\n ),\n vol.Optional(\n CONF_ACCESS_TOKEN, default=input_dict.get(CONF_ACCESS_TOKEN, \"\")\n ): str,\n },\n extra=vol.REMOVE_EXTRA,\n )","title":""},{"docid":"74e145096f96f1d3874ecf7cef0539a7","score":"0.56050754","text":"def _get_schema(self, user_input):\n schema = vol.Schema(\n {vol.Required(CONF_HOST, default=user_input.get(CONF_HOST, \"\")): cv.string}\n )\n return schema","title":""},{"docid":"b945c2c96c29ece6dfe827a69eb8b60d","score":"0.559489","text":"def schema(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"schema\")","title":""},{"docid":"b945c2c96c29ece6dfe827a69eb8b60d","score":"0.559489","text":"def schema(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"schema\")","title":""},{"docid":"b945c2c96c29ece6dfe827a69eb8b60d","score":"0.559489","text":"def schema(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"schema\")","title":""},{"docid":"b945c2c96c29ece6dfe827a69eb8b60d","score":"0.559489","text":"def schema(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"schema\")","title":""},{"docid":"b945c2c96c29ece6dfe827a69eb8b60d","score":"0.559489","text":"def schema(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"schema\")","title":""},{"docid":"5786739e86ce1be5c17164295e4e5fd3","score":"0.55935436","text":"def refresh_definition(self):\n encoded_id = urllib.parse.quote_plus(self.id)\n result = self._aep.get(path='schemaregistry.schema',\n body={},\n params={},\n url_suffix='/'+encoded_id)\n self.definition = result","title":""},{"docid":"40bf1c0880ce78c3712f19efbc2583a8","score":"0.558595","text":"def __init__(self, config_path: Optional[str]):\n self.config_path = config_path\n if self.config_path is None:\n if not self.strict:\n self.config = {}\n self.schema = {}\n return\n raise FileNotFoundError(\"Config file was not found\")\n if not os.path.exists(self.config_path):\n raise FileNotFoundError(f\"Configuration file not found in {self.config_path}\")\n main_dirname = os.path.abspath(os.path.dirname(__file__))\n schema_path = os.path.join(main_dirname, \"config.schema.json\")\n with open(self.config_path, \"r\", encoding=\"utf-8\") as fid:\n self.config: dict = json.load(fid)\n if not os.path.exists(schema_path):\n logger.warning(\"Configuration schema was not found in %s. Continuing without schema.\", schema_path)\n self.schema = {}\n return\n with open(schema_path, \"r\", encoding=\"utf-8\") as fid:\n self.schema = json.load(fid)\n jsonschema.validate(self.config, self.schema)","title":""},{"docid":"d69bef2e0c94c2580ba8972b64a5ed60","score":"0.55855185","text":"def schema(self):\n return self._schema","title":""},{"docid":"5aa9a3c4694118b21358e06c875c3fe2","score":"0.557486","text":"def read(self):\n self.schema_class = 'service_instances_schema.ServiceInstancesSchema'\n schema_object = super(ServiceInstance, self).read()\n self.schema_class = 'service_instance_schema.ServiceInstanceSchema'\n return schema_object","title":""},{"docid":"874292ddbb59dfb3062fa8a0ec8b6629","score":"0.557452","text":"def fetch_schema(data_args, schema_inferred):\n if not data_args.schema_file:\n if not data_args.input_bq_table:\n # Both schema and input_bq_table are unset.\n # Use gcs schema file because safer than assuming this user has\n # created the lineorders table.\n data_args.schema_file = \\\n 'gs://python-dataflow-example/schemas/lineorder-schema.json'\n else:\n # Need to fetch schema from existing BQ table.\n bq_cli = bq.Client()\n dataset_name, table_name = data_args.input_bq_table.split('.', 1)\n bq_dataset = bq_cli.dataset(dataset_name)\n # This forms a TableReference object.\n bq_table_ref = bq_dataset.table(table_name)\n # Errors out if table doesn't exist.\n bq_table = bq_cli.get_table(bq_table_ref)\n\n # Quickly parse TableSchema object to list of dictionaries.\n data_args.schema = {\n 'fields': [{\n 'name': field.name,\n 'type': field.field_type,\n 'mode': field.mode,\n 'fields': field.fields\n } for field in bq_table.schema]\n }\n if data_args.output_bq_table:\n # We need to check if this output table already exists.\n dataset_name, table_name = data_args.output_bq_table.split(\n '.', 1)\n bq_dataset = bq_cli.dataset(dataset_name)\n # This forms a TableReference object.\n bq_table_ref = bq_dataset.table(table_name)\n try:\n bq_cli.get_table(bq_table_ref)\n schema_inferred = True\n except NotFound:\n schema_inferred = False\n\n if data_args.schema_file and data_args.input_bq_table:\n logging.error('Error: pipeline was passed both schema_file and '\n 'input_bq_table. '\n 'Please enter only one of these arguments')\n raise ValueError('Error: pipeline was passed both schema_file and '\n 'input_bq_table. '\n 'Please enter only one of these arguments')\n\n return data_args, schema_inferred","title":""},{"docid":"7ba60ebe94793b17791b80605b18118c","score":"0.5570819","text":"def jsonschema_ref_schema(self) -> Dict[str, Any]:\n if self.schema_ref_name:\n return {\"$ref\": f\"#/definitions/{self.schema_ref_name}\"}\n else:\n return self.jsonschema_definition","title":""},{"docid":"5c8ce52652f4f3114e4a85b1e3e92d20","score":"0.55592275","text":"def init(\n new_schema: SortedDict,\n schema_filepath: str,\n overwrite: bool = False,\n verbose: bool = False,\n):\n from syphon import schema\n\n schema.save(new_schema, schema_filepath, overwrite)\n\n if verbose:\n print(f\"Init: wrote {schema_filepath}\")","title":""},{"docid":"0f9f0b9d264149f33dcc4a617b0f31cb","score":"0.55577475","text":"def find_ref_data(self, ref):\n\n if '#' not in ref:\n return None\n schema_ref, path = self.get_schema_ref_and_path(ref)\n if self.ref_to_own_schema(ref):\n schema = self.schemas.get(schema_ref, None)\n if not schema:\n return None\n\n else:\n schema = self.get_remote_schema(ref)\n if not schema:\n return None\n\n elements = [x for x in path.split('/') if x]\n element = ''\n for element in elements:\n if element in schema:\n schema = schema[element]\n else:\n return None\n\n schema = dict(schema)\n schema['_from_schema_ref'] = schema_ref\n if '_schema_name' not in schema:\n schema['_schema_name'] = self.get_schema_name(schema_ref)\n schema['_prop_name'] = element\n schema['_ref_uri'] = ref\n return schema","title":""},{"docid":"c4417464d0ec2ceb4cd5d0d981b11049","score":"0.55544174","text":"def schemas_config(self):\n return self.__schemas_config","title":""},{"docid":"c822837f28a369dce83495dbc291ad28","score":"0.55474746","text":"def schema_definition(self) -> pulumi.Input['TableSchemaDefinitionArgs']:\n return pulumi.get(self, \"schema_definition\")","title":""},{"docid":"cfc89350ddce6cc3489e4b953fbef05d","score":"0.55418557","text":"def _get_create_schema(self, data):\n if getattr(self, 'create_schema', None):\n return self.create_schema()\n else:\n return self._get_schema(data)","title":""},{"docid":"517f5aa53421921a0617b3b17aa8aed0","score":"0.5536574","text":"def __validate_registered_config(self,\n config,\n obj):\n\n cfg = self.__registered_cfg.get(config)\n schema = cfg.get(CONST.cfg_schema)\n\n if schema is not None:\n # Load schema\n schema_path = os.path.join(self.schema_path, schema)\n self.__validate_config(schema_path, obj)","title":""},{"docid":"06c605488c395fcca05bf4743cb2df10","score":"0.5529778","text":"def read_previous_schema(self) -> List[dict]:\n\n self.check_for_existing_schema()\n\n with open(self.schema_dir) as schema:\n data = json.load(schema)\n\n return data","title":""},{"docid":"f72f363b71c88692c90897d38e58fb8f","score":"0.5527214","text":"def read_schema_from_file() -> dict:\n logger.info(f'Reading schema from: {SCHEMA_FILE}')\n try:\n with open(SCHEMA_FILE) as input_file:\n return json.load(input_file)\n except FileNotFoundError:\n raise ZenodoMetadataException(f'Schema file: {SCHEMA_FILE} not found.')","title":""},{"docid":"57cdf079f69d20f92d720723c7110103","score":"0.55207723","text":"def fake_data_schema():\n return FakeDataSchema()","title":""},{"docid":"8dd08e8786a8ba6b7d4d4ae3d8df15ec","score":"0.5520027","text":"def __init__(self):\n self.data_schema = vol.Schema(\n {\n vol.Required(CONF_USERNAME): str,\n vol.Required(CONF_PASSWORD): str,\n vol.Optional(CONF_CODE): str,\n }\n )","title":""},{"docid":"00cb27c88dcbcfd1e1ffbf7fdd4dfdee","score":"0.5514165","text":"def _schema_def(self, resource: Type[ResourceBase]) -> Dict[str, str]:\n meta = getmeta(resource)\n ref = meta.resource_name\n if ref not in self.defs:\n self.defs[ref] = None # Placeholder to prevent recursion\n self.defs[ref] = self._resource_to_schema(meta)\n return {\"$ref\": f\"#/$defs/{ref}\"}","title":""},{"docid":"9ae7bad8c28802a5ec685660f0c8ad3e","score":"0.5506005","text":"def __init__(self, name, schema):\n self.name = name\n self.schema = schema","title":""},{"docid":"478ed98ec167e968643f21f4c1c29c55","score":"0.5498467","text":"def schema(self, schema):\n\n self._schema = schema","title":""},{"docid":"ee2d716cf61a72e64dcd03a60345a487","score":"0.5497979","text":"def get_schema(cls) -> Dict[str, Any]:\n schema = super().get_schema()\n schema[\"uihints\"].update({\"canRefresh\": True})\n return schema","title":""},{"docid":"f286ea442c15596513ad704ee381587e","score":"0.5493095","text":"def _get_schema_from_file(schema_file):\n try:\n return load_json_file(schema_file)\n except:\n raise ConfigException(\n 'Cannot load schema from file {}: {}'.format(\n schema_file, traceback.format_exc())\n )","title":""},{"docid":"70978278f69bcd0b1d2f6eb4a47c8612","score":"0.54918206","text":"def get_standard_json_schema():\n return standard_json_schema","title":""},{"docid":"d912056dc4c4aaf55431cfdf00cce0d9","score":"0.54900414","text":"def getschema(self, schemaname):\n if not self.registry.has_key(schemaname):\n self.convert_schema(schemaname=schemaname)\n outschema = self.registry.get(schemaname)\n return outschema","title":""},{"docid":"8fec341de54cccbdf06e4278b224c7dd","score":"0.54724944","text":"def getSchema(schema):\n \n rip = _schema[schema]\n \n s = Schema.Schema(open(rip.path))\n \n assert s.id == schema, _('schema %s has not the same id %s as in the RIP files') % (\n rip.path, schema)\n return s","title":""},{"docid":"60ba4845e64be76aeba0dbed09feca26","score":"0.5470302","text":"def get_introspection_schema(self, apiId: str, format: str) -> Dict:\n pass","title":""},{"docid":"508b4e1b2739b7428e0976a821059255","score":"0.5469957","text":"def schema(self):\n schema = super().schema\n schema['properties'].update(\n {\n 'artist': {'type': 'string'},\n 'album': {'type': 'string'},\n 'year': {'type': ['string', 'integer']},\n 'tags': one_or_more({'type': 'string'}),\n 'tag_type': {'type': 'string', 'enum': list(self._opts('tag_type').keys())},\n 'encoding': {'type': 'string', 'enum': self._opts('encoding')},\n 'format': {'type': 'string', 'enum': self._opts('format')},\n 'media': {'type': 'string', 'enum': self._opts('media')},\n 'release_type': {\n 'type': 'string',\n 'enum': list(self._opts('release_type').keys()),\n },\n 'log': {\n 'oneOf': [\n {'type': 'string', 'enum': list(self._opts('log').keys())},\n {'type': 'boolean'},\n ]\n },\n 'leech_type': {'type': 'string', 'enum': list(self._opts('leech_type').keys())},\n 'hascue': {'type': 'boolean'},\n 'scene': {'type': 'boolean'},\n 'vanityhouse': {'type': 'boolean'},\n }\n )\n return schema","title":""},{"docid":"b0c25fdf6f6f2d1de92730eeaa36d0a2","score":"0.54668695","text":"def schema_database_read():\n return {0: (\"titleb\", str),\n 1: (\"type\", str),\n 2: (\"xmlUrl\", str),\n 3: (\"htmlUrl\", str),\n 4: (\"keywordsb\", str),\n 5: (\"id\", int, \"PRIMARYKEY\", \"AUTOINCREMENT\")}","title":""},{"docid":"30b70c118a4730f09794c7615ca5424b","score":"0.5466642","text":"def need_schema_upgrade(self):\n raise NotImplementedError","title":""},{"docid":"f0227b515313d3f4a501081a62ebaeaf","score":"0.54564106","text":"def add_schema(schema, connection):\n create_schemas_meta_table(connection)\n\n file_pattern = schema['meta']['files']\n time = schema['meta']['version']\n description = schema['meta']['description']\n processing_schema = json.dumps(schema['processing'])\n\n cur = connection.cursor()\n cur.execute(\n f\"INSERT INTO {xml_schemas_table} \"\n f\"({file_pattern_field}, {schema_time_field}, {schema_desc_field}, {proc_schema_field}) \"\n \n \"VALUES \"\n f\"('{file_pattern}', '{time}', '{description}', '{processing_schema}'::json) \"\n \n f\"ON CONFLICT DO NOTHING;\")\n connection.commit()","title":""},{"docid":"15d517c411da1cce436813b4bbdb5ab6","score":"0.5456108","text":"def __fetch__definition(self):\r\n dom = xml.dom.minidom.parseString(self.input_xml)\r\n self.logger.debug('Loading parameters: %s' % (dom.toprettyxml()))\r\n setattr(self, 'thoughtspot_host_name', Et.fromstring(self.input_xml).find('DestinationServer').text\r\n if 'DestinationServer' in self.input_xml else None)\r\n if self.thoughtspot_host_name is None:\r\n self.error = \"Please Enter a ThoughtSpot Server\"\r\n return\r\n\r\n setattr(self,'thoughtspot_database_name', Et.fromstring(self.input_xml).find('TargetDatabase').text\r\n if 'TargetDatabase' in self.input_xml else None)\r\n if self.thoughtspot_database_name is None:\r\n self.error = \"Please Enter a Database Name\"\r\n return\r\n\r\n setattr(self, 'thoughtspot_schema', Et.fromstring(self.input_xml).find('TargetSchema').text\r\n if 'TargetSchema' in self.input_xml else 'falcon_default_schema')\r\n\r\n setattr(self, 'thoughtspot_user_name', Et.fromstring(self.input_xml).find('UserName').text\r\n if 'UserName' in self.input_xml else None)\r\n if self.thoughtspot_user_name is None:\r\n self.error = \"Please Enter a ThoughtSpot User Name\"\r\n return\r\n\r\n password = Et.fromstring(self.input_xml).find('Password').text if 'Password' in self.input_xml else None\r\n setattr(self, 'thoughtspot_rsa_file_path', Et.fromstring(self.input_xml).find('rsaFilePath').text\r\n if 'rsaFilePath' in self.input_xml else None)\r\n if self.thoughtspot_rsa_file_path is not None:\r\n setattr(self, 'use_key_file', True)\r\n setattr(self, 'thoughtspot_password', None)\r\n else:\r\n if password is None:\r\n self.error = \"A Password or Key file Must be Entered\"\r\n return\r\n else:\r\n # Can be used for unencrypted passwords. remove # on line 95 and place a # on lines 97 and 98\r\n # setattr(self, 'thoughtspot_password', password)\r\n setattr(self, 'use_key_file', False)\r\n setattr(self, 'thoughtspot_password', self.alteryx_engine.decrypt_password(\r\n Et.fromstring(self.input_xml).find('Password').text, 0))\r\n\r\n setattr(self, 'thoughtspot_table_name', Et.fromstring(self.input_xml).find('TableName').text\r\n if 'TableName' in self.input_xml else None)\r\n if self.thoughtspot_table_name is None:\r\n self.error = \"Please Enter a ThoughtSpot Table Name\"\r\n return\r\n\r\n port_test = Et.fromstring(self.input_xml).find('DestinationPort').text\r\n self.logger.info(port_test)\r\n if port_test is None:\r\n setattr(self, 'thoughtspot_port', 22)\r\n else:\r\n setattr(self, 'thoughtspot_port', int(port_test))\r\n\r\n setattr(self, 'buffer_size', int(Et.fromstring(self.input_xml).find('BufferSize').text)\r\n if 'BufferSize' in self.input_xml else None)\r\n if self.buffer_size is None:\r\n self.error = \"Please Enter the row buffer size (Default: 1000)\"\r\n return\r\n\r\n setattr(self, 'verbosity', Et.fromstring(self.input_xml).find('Verbosity').text\r\n if 'Verbosity' in self.input_xml else 0)\r\n setattr(self, 'maxingoredrows', Et.fromstring(self.input_xml).find('MaxIgnoredRows').text\r\n if 'MaxIgnoredRows' in self.input_xml else 0)\r\n setattr(self, 'truncate', Et.fromstring(self.input_xml).find('Truncate').text\r\n if 'Truncate' in self.input_xml else False)\r\n setattr(self, 'ts_create_database', Et.fromstring(self.input_xml).find('CreateDatabase').text\r\n if 'CreateDatabase' in self.input_xml else False)\r\n setattr(self, 'booleanstring', Et.fromstring(self.input_xml).find('BooleanString').text\r\n if 'BooleanString' in self.input_xml else 'T_F')\r\n setattr(self, 'ts_create_table', Et.fromstring(self.input_xml).find('CreateTable').text\r\n if 'CreateTable' in self.input_xml else False)\r\n\r\n primary_keys = Et.fromstring(self.input_xml).find('PrimaryKey').text \\\r\n if 'PrimaryKey' in self.input_xml else None\r\n if primary_keys is not None:\r\n setattr(self, 'primary_keys', '\",\"'.join(primary_keys.split(\",\")))\r\n else:\r\n setattr(self, 'primary_keys', None)\r\n\r\n hash_test = Et.fromstring(self.input_xml).find('HashValue').text\r\n self.logger.info(hash_test)\r\n if hash_test is None:\r\n setattr(self, 'hash_number', 0)\r\n setattr(self, 'partition_keys', None)\r\n else:\r\n setattr(self, 'hash_number', int(hash_test))\r\n partition_keys = Et.fromstring(self.input_xml).find('PartitionKey').text \\\r\n if 'PartitionKey' in self.input_xml else None\r\n if partition_keys is not None:\r\n setattr(self, 'partition_keys', '\",\"'.join(partition_keys.split(\",\")))\r\n else:\r\n setattr(self, 'partition_keys', None)","title":""},{"docid":"6f1ce7d7d3f58fb96f924949d0c220e8","score":"0.5454911","text":"def __init__(self):\n\n self.database = \"shsmd.db\"\n self.debug = False\n self.schema = \"../schema.sql\"","title":""}],"string":"[\n {\n \"docid\": \"20a2e7a8484156b260fdb229de1e1660\",\n \"score\": \"0.7257588\",\n \"text\": \"def load_schema(self):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a12bfee9e3094a2afc066b5de193e7d9\",\n \"score\": \"0.72208834\",\n \"text\": \"def input_config_schema(self) -> IDefinitionConfigSchema:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1aaa12eeb8fcd2e69a5b255fd82fc935\",\n \"score\": \"0.6990748\",\n \"text\": \"def getSchema():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"86c202456a8db932152b710cb124848e\",\n \"score\": \"0.69262326\",\n \"text\": \"def define_schema(self) -> None:\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bdbb3cb8831476d260a1fca630f0fdef\",\n \"score\": \"0.64331645\",\n \"text\": \"def load_schema(self, path):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1a97a353a946c17db1836d1bb14601e4\",\n \"score\": \"0.642445\",\n \"text\": \"def load_schema(self):\\n query = self.config.get_schemas\\n self.cursor.execute(query)\\n return self._get_result()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fdf8cfc9fcfff47bebae3f926f2c607d\",\n \"score\": \"0.6417863\",\n \"text\": \"def test_read_schema(self):\\n assert set(self.s.fields.keys()) \\\\\\n == set(['boolean_field',\\n 'int_field',\\n 'text_field',\\n 'location_field'])\\n assert self.s.default_field_name == 'text_field'\\n assert self.s.unique_key == 'int_field'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"455d15d2395d68c8573c2b9f5e132008\",\n \"score\": \"0.6404794\",\n \"text\": \"def _load_schema(schema_name: str) -> dict:\\n with open(os.path.join(os.path.dirname(__file__), 'schemas', schema_name)) as f:\\n return json.load(f)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f690c0537ef0a9442abab440818ed322\",\n \"score\": \"0.6356305\",\n \"text\": \"def get_schema(self, walk, schema, **kwargs):\\n raise NotImplemented\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d20eb5b3c38602a6e5ca0948f66be72d\",\n \"score\": \"0.63054293\",\n \"text\": \"def config_schema(self) -> Optional[JsonObjectSchema]:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"607309fde1470a9863f3b74f96f77421\",\n \"score\": \"0.6304943\",\n \"text\": \"def get_schema():\\n global FULL_SCHEMA\\n if FULL_SCHEMA:\\n return FULL_SCHEMA\\n full_schema = {\\n '$schema': 'http://json-schema.org/draft-04/schema#',\\n 'id': 'cloud-config-schema', 'allOf': []}\\n\\n configs_dir = os.path.dirname(os.path.abspath(__file__))\\n potential_handlers = find_modules(configs_dir)\\n for (_fname, mod_name) in potential_handlers.items():\\n mod_locs, _looked_locs = importer.find_module(\\n mod_name, ['cloudinit.config'], ['schema'])\\n if mod_locs:\\n mod = importer.import_module(mod_locs[0])\\n full_schema['allOf'].append(mod.schema)\\n FULL_SCHEMA = full_schema\\n return full_schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"204df02430bd730be21dcc3c16ad8018\",\n \"score\": \"0.6289603\",\n \"text\": \"def my_schema_callback(schema):\\n for k in [k for k in schema['properties'] if k.startswith('_')]:\\n del schema['properties'][k]\\n for k in [k for k in schema['properties'] if '/' in k]:\\n schema['properties'][k.split('/')[1]] = schema['properties'][k]\\n del schema['properties'][k]\\n for k in [k for k in schema['properties'] if k.endswith('_id')]:\\n if k in schema['required'] or k in schema['systemProperties']:\\n continue\\n schema['properties'][k.replace('_id', '')] = {'type': ['string', 'null']} # schema['properties'][k]\\n del schema['properties'][k]\\n # adds extra properties not found in\\n schema['category'] = 'bcc extention'\\n if 'sizeaxis1' in schema['properties']:\\n schema['properties']['lesion'] = {'$ref': '_definitions.yaml#/to_one'}\\n return schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c49bc1f8afff893a0c9c2bf4eea9fe2d\",\n \"score\": \"0.6245679\",\n \"text\": \"def loadDBSchema(self):\\n\\n\\t\\tprint 'loading database schema: ', self.schemaFile\\n\\t\\twith open(self.schemaFile) as json_file:\\n\\t\\t\\tself.schema = json.load(json_file)\\n\\t\\tjson_file.close()\\n\\t\\tassert(self.schema['nTables'] == len(self.schema['tablenames']))\\n\\t\\t# print(self.schema)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ec5600af127a9a762748b0562e7bfb6e\",\n \"score\": \"0.6215938\",\n \"text\": \"def _setSchema(self):\\n try:\\n data = self.request(\\\"admin/luke\\\", parameters={'show': \\\"schema\\\"})\\n\\n self._setTypes(data['schema']['types'])\\n self.fields = {}\\n self._setFields(data['schema']['fields'], self.fields)\\n self.dynamicFields = {}\\n self._setFields(data['schema']['dynamicFields'], self.dynamicFields)\\n\\n #Set copySources\\n for (fieldname, fieldspecs) in data['schema']['fields'].iteritems():\\n for copyfieldname in fieldspecs['copySources']:\\n self.fields[fieldname].copySources.append(self.fields[copyfieldname])\\n\\n #Could we have copyfield for dynamic fields? #FIXME\\n\\n self.id_field = data['schema']['uniqueKeyField']\\n except KeyError, e:\\n raise SOLRResponseFormatError, \\\"Wrong response format: %s %s - %s\\\" % (KeyError, e, data)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bafb90925181f38ae9747a47b64098c0\",\n \"score\": \"0.62053746\",\n \"text\": \"def __init__(self, schema: str):\\n if os.path.isfile(schema):\\n self._schema = open(schema, 'r').read()\\n else:\\n self._schema = schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"440e074d4611c4d29ae4aa82d79a102e\",\n \"score\": \"0.6199084\",\n \"text\": \"def _schema(self, path, obj, app):\\n if path.startswith('#/definitions'):\\n last_token = jp_split(path)[-1]\\n if app.version == '1.2':\\n obj.update_field('name', scope_split(last_token)[-1])\\n else:\\n obj.update_field('name', last_token)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"87b220f693360af13cb2b927af1ddf4d\",\n \"score\": \"0.61490417\",\n \"text\": \"def visit_schema(self, schema):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b641de252de8d1fdd5216b3e56923568\",\n \"score\": \"0.6137045\",\n \"text\": \"def load_schema(self, schema):\\n self.schema = load_json(schema)\\n validate_schema(self.schema)\\n self.schema_nx = load_schema_into_networkx(self.schema)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e88acdb65caf3733d682ebe59491eb94\",\n \"score\": \"0.6128808\",\n \"text\": \"def _get_schema(self, data):\\n return self.schema()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c0903ca2e5df6a32c23a6cf545428dca\",\n \"score\": \"0.60882545\",\n \"text\": \"def read_schema_section(self):\\n\\n # The next tag must be 'SCHEMA'\\n tag_line = self.read_line()\\n if tag_line is None:\\n raise Exception(\\\"Unexpected EOF, should be SCHEMA tag\\\")\\n (tag, _) = self.parse_tag_line(tag_line)\\n if tag != 'SCHEMA':\\n raise Exception(\\n f\\\"Unrecoginized tag line_number '{tag_line}', should be SCHEMA\\\"\\n )\\n\\n # Read the SCHEMA records until the next TAG_TOKEN\\n schema_lines = []\\n while True:\\n line = self.read_line()\\n if line is None:\\n break\\n (tag, _) = self.parse_tag_line(line)\\n if tag in self.TAG_TOKENS:\\n if tag in ('DATA', 'ERRORS', 'EXISTING_SCHEMA', 'SCHEMA'):\\n raise Exception(f\\\"Unexpected {tag} tag\\\")\\n self.push_back(line)\\n break\\n schema_lines.append(line)\\n\\n return ''.join(schema_lines)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"200ae8776af4253ec8ecb5171e6d7ea2\",\n \"score\": \"0.6078499\",\n \"text\": \"def _read_schema(self):\\n cache_filename = os.path.join(\\n CACHE_ROOT, \\\"%s.smt\\\" % self._representation)\\n log.info(\\\"Attempting to read local schema at %s\\\" % cache_filename)\\n try:\\n if time.time() - os.stat(cache_filename).st_mtime > CACHE_EXPIRY:\\n log.warning(\\\"Cache expired, re-pulling\\\")\\n self._pull_schema_definition(cache_filename)\\n except OSError:\\n log.warning(\\\"Local schema not found. Pulling from web.\\\")\\n self._pull_schema_definition(cache_filename)\\n else:\\n log.info(\\\"Success\\\")\\n\\n return cache_filename\",\n \"title\": \"\"\n },\n {\n \"docid\": \"975bc86a280809493d86c0329bf34dbd\",\n \"score\": \"0.60747033\",\n \"text\": \"def schema(self):\\n return _parse_schema_resource(self._properties.get('schema', {}))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cce4eb26e8258b71145b12a933cb50d2\",\n \"score\": \"0.6001636\",\n \"text\": \"def SCHEMA(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cce4eb26e8258b71145b12a933cb50d2\",\n \"score\": \"0.6001636\",\n \"text\": \"def SCHEMA(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cce4eb26e8258b71145b12a933cb50d2\",\n \"score\": \"0.6001636\",\n \"text\": \"def SCHEMA(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"60a65ef4574d42fd7dc9f0c36bb9286b\",\n \"score\": \"0.59796387\",\n \"text\": \"def __init__(self, definition=None):\\n super(Schema, self).__init__()\\n self._map = {}\\n self._bq_schema = definition\\n self._populate_fields(definition)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"75d02d1dab28c87ca8b43ee8a8328657\",\n \"score\": \"0.5960625\",\n \"text\": \"def main():\\n parser = get_parser()\\n handle_schema_args('cloudconfig-schema', parser.parse_args())\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8b821d6db3a46d7cf7d02d19fb61bd8c\",\n \"score\": \"0.5945147\",\n \"text\": \"def new_schema():\\n generate_new_schema()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"083a001fc0b2c3122ccdc15cfee33ed3\",\n \"score\": \"0.59255975\",\n \"text\": \"def get_schema(self) -> dict:\\n if not os.path.isfile(self.path):\\n logger.error('Path `%s` does not resolve as a valid file.', self.path)\\n raise ImproperlyConfigured(\\n f'The path `{self.path}` does not point to a valid file. Make sure to point to the specification file.'\\n )\\n try:\\n logger.debug('Fetching static schema from %s', self.path)\\n with open(self.path, 'r') as f:\\n content = f.read()\\n except Exception as e:\\n logger.exception('Exception raised when fetching OpenAPI schema from %s. Error: %s', self.path, e)\\n raise ImproperlyConfigured(\\n f'Unable to read the schema file. Please make sure the path setting is correct.\\\\n\\\\nError: {e}'\\n )\\n if '.json' in self.path:\\n return json.loads(content)\\n elif '.yaml' in self.path or '.yml' in self.path:\\n return yaml.load(content, Loader=yaml.FullLoader)\\n else:\\n raise ImproperlyConfigured('The specified file path does not seem to point to a JSON or YAML file.')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f7693fe798fd0f30e90a47f25a1c1fbb\",\n \"score\": \"0.5916935\",\n \"text\": \"def set_schema(obj, eng):\\n if '$schema' not in obj.data:\\n obj.data['$schema'] = \\\"{data_type}.json\\\".format(\\n data_type=obj.data_type or eng.workflow_definition.data_type\\n )\\n\\n if not obj.data['$schema'].startswith('http'):\\n obj.data['$schema'] = url_for(\\n 'invenio_jsonschemas.get_schema',\\n schema_path=\\\"records/{0}\\\".format(obj.data['$schema'])\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"485ee6f1c6dbec358f4df75ecb17b89b\",\n \"score\": \"0.5913141\",\n \"text\": \"def metadatablock_json_schema():\\n\\n return open(\\\"./tests/fixtures/dataversebase/toydataset.schema.json\\\").read()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a15a98e8ba3f81903ffbe3a9c145f618\",\n \"score\": \"0.5878806\",\n \"text\": \"def validate(self):\\n logger.info('Reading plugin schema file %s', self.__schema_file)\\n\\n if self.__plugin_schemas is None:\\n self.__plugin_schemas = self.__read_schema_file()\\n\\n logger.debug('Validating plugin schema file content : %s',\\n self.__plugin_schemas)\\n self.__validate_schemas()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e60d2153351382599d56a15394fbc213\",\n \"score\": \"0.58765936\",\n \"text\": \"def jsonschema_definition(self) -> Dict[str, Any]:\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a291c5e4428e987bf6cd472cd3cd6124\",\n \"score\": \"0.5869546\",\n \"text\": \"def cache_schema():\\n # Calling load_schema() will generate the schema as a side effect\\n load_schema()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b2327968a1768478ec2a286d7c03dabb\",\n \"score\": \"0.5856529\",\n \"text\": \"def __register_schema(self,\\n config,\\n schema):\\n\\n if not os.path.exists(schema):\\n raise IOError(u'Schema does not exists: {s}'.format(s=schema))\\n\\n # Place a copy of the schema in self.schema_path\\n ensure_path_exists(self.schema_path)\\n schema_copy_fn = u'{cfg}.schema.{ext}'.format(cfg=config,\\n ext=CONST.json)\\n schema_copy = os.path.join(self.schema_path, schema_copy_fn)\\n shutil.copyfile(schema, schema_copy)\\n\\n # Register the schema\\n self.__registered_cfg[config][CONST.cfg_schema] = schema_copy_fn\",\n \"title\": \"\"\n },\n {\n \"docid\": \"63b407b09cff9d5c2e654bb3204b8067\",\n \"score\": \"0.5853047\",\n \"text\": \"def get_schema(self):\\n return self.schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2de2f068964dc7e016d9d22829df3ce9\",\n \"score\": \"0.58503586\",\n \"text\": \"def handle_schema_args(name, args):\\n exclusive_args = [args.config_file, args.docs]\\n if not any(exclusive_args) or all(exclusive_args):\\n error('Expected either --config-file argument or --docs')\\n full_schema = get_schema()\\n if args.config_file:\\n try:\\n validate_cloudconfig_file(\\n args.config_file, full_schema, args.annotate)\\n except SchemaValidationError as e:\\n if not args.annotate:\\n error(str(e))\\n except RuntimeError as e:\\n error(str(e))\\n else:\\n print(\\\"Valid cloud-config file {0}\\\".format(args.config_file))\\n elif args.docs:\\n schema_ids = [subschema['id'] for subschema in full_schema['allOf']]\\n schema_ids += ['all']\\n invalid_docs = set(args.docs).difference(set(schema_ids))\\n if invalid_docs:\\n error('Invalid --docs value {0}. Must be one of: {1}'.format(\\n list(invalid_docs), ', '.join(schema_ids)))\\n for subschema in full_schema['allOf']:\\n if 'all' in args.docs or subschema['id'] in args.docs:\\n print(get_schema_doc(subschema))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"af03ba52442219570687a1a4187ab5b6\",\n \"score\": \"0.5816239\",\n \"text\": \"def load(self, definition, schema_file, context):\\n try:\\n validate(definition, self._get_schema_from_file(schema_file))\\n except ValidationError:\\n raise ConfigException(\\n 'Failed to validate interface with schema: {}'.format(\\n traceback.format_exc()))\\n\\n try:\\n global_settings = self._load_global_setting(\\n definition.get('global_settings'), context\\n )\\n\\n requests = [self._load_request(item) for item in definition['requests']]\\n\\n return munchify({\\n 'meta': munchify(definition['meta']),\\n 'tokens': definition['tokens'],\\n 'global_settings': global_settings,\\n 'requests': requests,\\n })\\n except Exception as ex:\\n error = 'Unable to load configuration: %s' % str(ex)\\n _logger.exception(error)\\n raise ConfigException(error)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2ec120889092ad5b8ec8eb2159b54978\",\n \"score\": \"0.58096194\",\n \"text\": \"def schema(self) -> \\\"Schema\\\":\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b59d3e184492921c228ee929b2b5bb61\",\n \"score\": \"0.5780726\",\n \"text\": \"def read_schema(self):\\n if self.db.has_collection(self.coll_name) and self.state_coll.has('schema'):\\n state = self.state_coll.get('schema')\\n else:\\n state = {'schema': {}}\\n\\n return state.get('schema')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"79b9a811772cac241c0f0443de1dfd96\",\n \"score\": \"0.57753044\",\n \"text\": \"def setupSchema(app,\\r\\n conn,\\r\\n grantedusers = ['public'],\\r\\n publicsyn = True):\\r\\n r = dbschema.getSchemaVersion(conn, oraschema.LATESTVERSIONS)\\r\\n\\r\\n if r['schema-version'] is not None:\\r\\n raise Exception(\\\"crossbar.io Repository already installed\\\")\\r\\n\\r\\n return _setupSchema(conn, grantedusers, publicsyn)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c7417c2d0df3bfa9d3573002a79ea6cc\",\n \"score\": \"0.5771426\",\n \"text\": \"def db_init( self, schema ):\\n #TODO: initialize the database schema\\n try: \\n pass\\n except:\\n raise Exceptions.ConfigFault(\\\"Couldn't initialize database\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"abee92d108e29d2c2aa7588c3117b4db\",\n \"score\": \"0.5769642\",\n \"text\": \"def schema(self):\\n return self.reader.schema()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e3551ef3e2b9db4d643d8cb0ad216244\",\n \"score\": \"0.576468\",\n \"text\": \"def schemas_config(self, configs):\\n self.__schemas_config = configs\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fc8ed43719decf60a577ce127c8396ba\",\n \"score\": \"0.57510227\",\n \"text\": \"def load_schema(self, path):\\n f = open(path, \\\"r\\\")\\n return f.read()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bae3f86858276df1f2463c3e8b62d516\",\n \"score\": \"0.5748631\",\n \"text\": \"def schema(self, schema):\\n \\n self._schema = schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"30468bd01592082a26d906fb98d18ebb\",\n \"score\": \"0.5743769\",\n \"text\": \"def schema(self):\\n try:\\n return self._get_schema()\\n except SchemaNotFoundError as error:\\n logging.getLogger(__name__).warning(str(error))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"30611bbcdd235a8473f17f25934164e5\",\n \"score\": \"0.57144326\",\n \"text\": \"def start_schema_creation(self, apiId: str, definition: bytes) -> Dict:\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"be8fba408bea9959911084e8b240b666\",\n \"score\": \"0.57089764\",\n \"text\": \"def schema(self):\\n return self.__schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"be8fba408bea9959911084e8b240b666\",\n \"score\": \"0.57089764\",\n \"text\": \"def schema(self):\\n return self.__schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"88053be6879d2b3b66af29c6c8eeece9\",\n \"score\": \"0.5685297\",\n \"text\": \"def config_schema(self) -> vol.Schema:\\n return vol.Schema(\\n {\\n vol.Required(CONF_API_KEY): str,\\n vol.Inclusive(\\n CONF_LATITUDE, \\\"coords\\\", default=self.hass.config.latitude\\n ): cv.latitude,\\n vol.Inclusive(\\n CONF_LONGITUDE, \\\"coords\\\", default=self.hass.config.longitude\\n ): cv.longitude,\\n vol.Optional(\\n CONF_ELEVATION, default=self.hass.config.elevation\\n ): vol.Coerce(float),\\n }\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"217e9646acdc42513a0a14e7fd517f16\",\n \"score\": \"0.5679437\",\n \"text\": \"def get_gedl_schema(schema_location):\\n basepath = \\\"\\\"\\n #get the module paths to help find the schema in a relitive to ourself\\n if(len(sys.path) > 1):\\n basepath = sys.path[0]\\n path = os.path.join(basepath,schema_location)\\n \\n if(not os.path.exists(path)):\\n #schema not found relitive to the python enviroment, check a local path\\n path = schema_location\\n if(not os.path.exists(path)):\\n #Unable to get python schema\\n raise(IOError(\\\"Unable to fild cle schema (expected at): \\\" + path))\\n \\n #we found the schema load it into ram\\n print(\\\"Using GEDL schema: \\\" + path)\\n with open(path,\\\"r\\\",encoding=\\\"UTF-8\\\") as schemafile:\\n return(json.loads(schemafile.read()))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6836ae553860c0c9ee69e1f31556c20d\",\n \"score\": \"0.5676\",\n \"text\": \"def retrieveSchemas(self)->None:\\n aepp.importConfigFile(\\n self.CONFIG['original']['config_file_location'])\\n schema_instance = aep_schema.Schema()\\n tenant_id = schema_instance.getTenantId()\\n schemas = schema_instance.getSchemas()\\n obj_schema = {schema['title']: schema['meta:altId']\\n for schema in schemas if schema['title'].startswith(\\\"Adhoc\\\") == False}\\n for schema in obj_schema.values():\\n schema = schema_instance.getSchema(schema, full=False, save=True)\\n allOf = schema['allOf']\\n allOf = [element for element in allOf if '$ref' in element.keys()]\\n for element in allOf:\\n if 'classes' in element['$ref']:\\n myClass = schema_instance.getClass(\\n element['$ref'], save=True)\\n if 'mixins' in element['$ref']:\\n myMixin = schema_instance.getMixin(\\n element['$ref'], save=True)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f37e1b5085f50e6f43ea445681f4915d\",\n \"score\": \"0.56728673\",\n \"text\": \"def __validate_config(self,\\n schema_path,\\n obj):\\n\\n # Load schema\\n schema_obj = self.__get_schema_obj(schema_path)\\n\\n if u'properties' in schema_obj:\\n # Make sure schema has reference to TEMPLATE_DEFAULTS_ITEM!\\n if TEMPLATE_DEFAULTS_ITEM not in schema_obj[u'properties']:\\n schema_obj[u'properties'][TEMPLATE_DEFAULTS_ITEM] = {u'type': u'object'}\\n\\n # Ensure loaded config is still valid (i.e any external modification hasn't corrupted it)\\n validator = Draft4Validator(schema_obj.cfg)\\n validator.validate(obj.cfg)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c1d03056954aec670a4f285b7383b8c3\",\n \"score\": \"0.5661043\",\n \"text\": \"def test_get_schema_from_api():\\n connection = DatabaseSchemaConnection(POSTGREST_URL)\\n resp = connection.get_by_id(\\\"marple-dataset.json\\\")\\n assert resp['$schema'] == 'http://json-schema.org/draft-04/schema#'\\n assert isinstance(resp,dict)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2e81759942d12b9229484596160a4eff\",\n \"score\": \"0.56599015\",\n \"text\": \"def validate_config(self):\\n # with self.spinner.reenter('Validating Config') as grandchild:\\n super(Instattack, self).validate_config()\\n data = self.config.get_dict()\\n\\n # This is where we would configure the system settings with the user\\n # defined settings.\\n # config(data)\\n\\n # grandchild.warning('Not Currently Validating Schema', fatal=False, options={\\n # 'label': True,\\n # })\",\n \"title\": \"\"\n },\n {\n \"docid\": \"10ed53159fe945a9a12f51f6fdc28aba\",\n \"score\": \"0.5644752\",\n \"text\": \"def __init__(self):\\n if self.schema is None:\\n _cls_name = f\\\"{self.model.__name__}Schema\\\"\\n self.schema = globals()[_cls_name]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fd30c838971eabbca690bde0abc9055c\",\n \"score\": \"0.56210756\",\n \"text\": \"def read_json_schema(schemafile):\\r\\n with open(schemafile, 'r') as jsonschemafile:\\r\\n data=jsonschemafile.read() \\r\\n \\r\\n json_dict = json.loads(data)\\r\\n colnames = json_dict['ColumnNames']\\r\\n offsets = json_dict['Offsets']\\r\\n includeheader = json_dict['IncludeHeader']\\r\\n fixedwidthencoding = json_dict['FixedWidthEncoding']\\r\\n delimitedencoding = json_dict['DelimitedEncoding']\\r\\n return colnames,offsets,includeheader\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b9628d41b08359b69aabf2fcd64f92b9\",\n \"score\": \"0.5620795\",\n \"text\": \"def create_schema(self, config_path: str, arg_replacements: Dict) -> Schema:\\n return self._create_aepobject(Schema, config_path, arg_replacements)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5d10b2bc62522850570cfce78e7ba920\",\n \"score\": \"0.5619358\",\n \"text\": \"def read_existing_schema_section(self):\\n\\n # The next tag must be 'EXISTING_SCHEMA'\\n tag_line = self.read_line()\\n if tag_line is None:\\n raise Exception(\\\"Unexpected EOF, should be EXISTING_SCHEMA tag\\\")\\n (tag, _) = self.parse_tag_line(tag_line)\\n if tag == 'EXISTING_SCHEMA':\\n # Read the EXISTING_SCHEMA records until the next TAG_TOKEN\\n schema_lines = []\\n while True:\\n line = self.read_line()\\n if line is None:\\n break\\n (tag, _) = self.parse_tag_line(line)\\n if tag in self.TAG_TOKENS:\\n if tag in ('DATA', 'EXISTING_SCHEMA'):\\n raise Exception(f\\\"Unexpected {tag} tag\\\")\\n self.push_back(line)\\n break\\n schema_lines.append(line)\\n return ''.join(schema_lines)\\n else:\\n self.push_back(tag_line)\\n return []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2e95e4b18a86e7a79b02a4b890a65d5a\",\n \"score\": \"0.56126887\",\n \"text\": \"def _get_schema(self):\\n if not self._schema:\\n self._schema = XSDSchema(self.filetype, self.version)\\n return self._schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cd6970bc9033144b09eac1029c53c4ff\",\n \"score\": \"0.5612554\",\n \"text\": \"def test_schema(self):\\n fti = queryUtility(IDexterityFTI, name=CT)\\n schema = fti.lookupSchema()\\n self.assertEqual(IFeaturedListings, schema)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"793da77f74b8666b14ab78d098726ff1\",\n \"score\": \"0.5611442\",\n \"text\": \"def Read(self, *args):\\n return _Storage.Storage_Schema_Read(self, *args)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2dce402a8c5394192518f0d55246b0cc\",\n \"score\": \"0.5606407\",\n \"text\": \"def _get_config_schema(input_dict: dict[str, Any] | None = None) -> vol.Schema:\\n if input_dict is None:\\n input_dict = {}\\n\\n return vol.Schema(\\n {\\n vol.Required(\\n CONF_NAME, default=input_dict.get(CONF_NAME, DEFAULT_NAME)\\n ): str,\\n vol.Required(CONF_HOST, default=input_dict.get(CONF_HOST)): str,\\n vol.Required(\\n CONF_DEVICE_CLASS,\\n default=input_dict.get(CONF_DEVICE_CLASS, DEFAULT_DEVICE_CLASS),\\n ): vol.All(\\n str,\\n vol.Lower,\\n vol.In([MediaPlayerDeviceClass.TV, MediaPlayerDeviceClass.SPEAKER]),\\n ),\\n vol.Optional(\\n CONF_ACCESS_TOKEN, default=input_dict.get(CONF_ACCESS_TOKEN, \\\"\\\")\\n ): str,\\n },\\n extra=vol.REMOVE_EXTRA,\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"74e145096f96f1d3874ecf7cef0539a7\",\n \"score\": \"0.56050754\",\n \"text\": \"def _get_schema(self, user_input):\\n schema = vol.Schema(\\n {vol.Required(CONF_HOST, default=user_input.get(CONF_HOST, \\\"\\\")): cv.string}\\n )\\n return schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b945c2c96c29ece6dfe827a69eb8b60d\",\n \"score\": \"0.559489\",\n \"text\": \"def schema(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"schema\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b945c2c96c29ece6dfe827a69eb8b60d\",\n \"score\": \"0.559489\",\n \"text\": \"def schema(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"schema\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b945c2c96c29ece6dfe827a69eb8b60d\",\n \"score\": \"0.559489\",\n \"text\": \"def schema(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"schema\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b945c2c96c29ece6dfe827a69eb8b60d\",\n \"score\": \"0.559489\",\n \"text\": \"def schema(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"schema\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b945c2c96c29ece6dfe827a69eb8b60d\",\n \"score\": \"0.559489\",\n \"text\": \"def schema(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"schema\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5786739e86ce1be5c17164295e4e5fd3\",\n \"score\": \"0.55935436\",\n \"text\": \"def refresh_definition(self):\\n encoded_id = urllib.parse.quote_plus(self.id)\\n result = self._aep.get(path='schemaregistry.schema',\\n body={},\\n params={},\\n url_suffix='/'+encoded_id)\\n self.definition = result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"40bf1c0880ce78c3712f19efbc2583a8\",\n \"score\": \"0.558595\",\n \"text\": \"def __init__(self, config_path: Optional[str]):\\n self.config_path = config_path\\n if self.config_path is None:\\n if not self.strict:\\n self.config = {}\\n self.schema = {}\\n return\\n raise FileNotFoundError(\\\"Config file was not found\\\")\\n if not os.path.exists(self.config_path):\\n raise FileNotFoundError(f\\\"Configuration file not found in {self.config_path}\\\")\\n main_dirname = os.path.abspath(os.path.dirname(__file__))\\n schema_path = os.path.join(main_dirname, \\\"config.schema.json\\\")\\n with open(self.config_path, \\\"r\\\", encoding=\\\"utf-8\\\") as fid:\\n self.config: dict = json.load(fid)\\n if not os.path.exists(schema_path):\\n logger.warning(\\\"Configuration schema was not found in %s. Continuing without schema.\\\", schema_path)\\n self.schema = {}\\n return\\n with open(schema_path, \\\"r\\\", encoding=\\\"utf-8\\\") as fid:\\n self.schema = json.load(fid)\\n jsonschema.validate(self.config, self.schema)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d69bef2e0c94c2580ba8972b64a5ed60\",\n \"score\": \"0.55855185\",\n \"text\": \"def schema(self):\\n return self._schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5aa9a3c4694118b21358e06c875c3fe2\",\n \"score\": \"0.557486\",\n \"text\": \"def read(self):\\n self.schema_class = 'service_instances_schema.ServiceInstancesSchema'\\n schema_object = super(ServiceInstance, self).read()\\n self.schema_class = 'service_instance_schema.ServiceInstanceSchema'\\n return schema_object\",\n \"title\": \"\"\n },\n {\n \"docid\": \"874292ddbb59dfb3062fa8a0ec8b6629\",\n \"score\": \"0.557452\",\n \"text\": \"def fetch_schema(data_args, schema_inferred):\\n if not data_args.schema_file:\\n if not data_args.input_bq_table:\\n # Both schema and input_bq_table are unset.\\n # Use gcs schema file because safer than assuming this user has\\n # created the lineorders table.\\n data_args.schema_file = \\\\\\n 'gs://python-dataflow-example/schemas/lineorder-schema.json'\\n else:\\n # Need to fetch schema from existing BQ table.\\n bq_cli = bq.Client()\\n dataset_name, table_name = data_args.input_bq_table.split('.', 1)\\n bq_dataset = bq_cli.dataset(dataset_name)\\n # This forms a TableReference object.\\n bq_table_ref = bq_dataset.table(table_name)\\n # Errors out if table doesn't exist.\\n bq_table = bq_cli.get_table(bq_table_ref)\\n\\n # Quickly parse TableSchema object to list of dictionaries.\\n data_args.schema = {\\n 'fields': [{\\n 'name': field.name,\\n 'type': field.field_type,\\n 'mode': field.mode,\\n 'fields': field.fields\\n } for field in bq_table.schema]\\n }\\n if data_args.output_bq_table:\\n # We need to check if this output table already exists.\\n dataset_name, table_name = data_args.output_bq_table.split(\\n '.', 1)\\n bq_dataset = bq_cli.dataset(dataset_name)\\n # This forms a TableReference object.\\n bq_table_ref = bq_dataset.table(table_name)\\n try:\\n bq_cli.get_table(bq_table_ref)\\n schema_inferred = True\\n except NotFound:\\n schema_inferred = False\\n\\n if data_args.schema_file and data_args.input_bq_table:\\n logging.error('Error: pipeline was passed both schema_file and '\\n 'input_bq_table. '\\n 'Please enter only one of these arguments')\\n raise ValueError('Error: pipeline was passed both schema_file and '\\n 'input_bq_table. '\\n 'Please enter only one of these arguments')\\n\\n return data_args, schema_inferred\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7ba60ebe94793b17791b80605b18118c\",\n \"score\": \"0.5570819\",\n \"text\": \"def jsonschema_ref_schema(self) -> Dict[str, Any]:\\n if self.schema_ref_name:\\n return {\\\"$ref\\\": f\\\"#/definitions/{self.schema_ref_name}\\\"}\\n else:\\n return self.jsonschema_definition\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5c8ce52652f4f3114e4a85b1e3e92d20\",\n \"score\": \"0.55592275\",\n \"text\": \"def init(\\n new_schema: SortedDict,\\n schema_filepath: str,\\n overwrite: bool = False,\\n verbose: bool = False,\\n):\\n from syphon import schema\\n\\n schema.save(new_schema, schema_filepath, overwrite)\\n\\n if verbose:\\n print(f\\\"Init: wrote {schema_filepath}\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0f9f0b9d264149f33dcc4a617b0f31cb\",\n \"score\": \"0.55577475\",\n \"text\": \"def find_ref_data(self, ref):\\n\\n if '#' not in ref:\\n return None\\n schema_ref, path = self.get_schema_ref_and_path(ref)\\n if self.ref_to_own_schema(ref):\\n schema = self.schemas.get(schema_ref, None)\\n if not schema:\\n return None\\n\\n else:\\n schema = self.get_remote_schema(ref)\\n if not schema:\\n return None\\n\\n elements = [x for x in path.split('/') if x]\\n element = ''\\n for element in elements:\\n if element in schema:\\n schema = schema[element]\\n else:\\n return None\\n\\n schema = dict(schema)\\n schema['_from_schema_ref'] = schema_ref\\n if '_schema_name' not in schema:\\n schema['_schema_name'] = self.get_schema_name(schema_ref)\\n schema['_prop_name'] = element\\n schema['_ref_uri'] = ref\\n return schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c4417464d0ec2ceb4cd5d0d981b11049\",\n \"score\": \"0.55544174\",\n \"text\": \"def schemas_config(self):\\n return self.__schemas_config\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c822837f28a369dce83495dbc291ad28\",\n \"score\": \"0.55474746\",\n \"text\": \"def schema_definition(self) -> pulumi.Input['TableSchemaDefinitionArgs']:\\n return pulumi.get(self, \\\"schema_definition\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cfc89350ddce6cc3489e4b953fbef05d\",\n \"score\": \"0.55418557\",\n \"text\": \"def _get_create_schema(self, data):\\n if getattr(self, 'create_schema', None):\\n return self.create_schema()\\n else:\\n return self._get_schema(data)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"517f5aa53421921a0617b3b17aa8aed0\",\n \"score\": \"0.5536574\",\n \"text\": \"def __validate_registered_config(self,\\n config,\\n obj):\\n\\n cfg = self.__registered_cfg.get(config)\\n schema = cfg.get(CONST.cfg_schema)\\n\\n if schema is not None:\\n # Load schema\\n schema_path = os.path.join(self.schema_path, schema)\\n self.__validate_config(schema_path, obj)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"06c605488c395fcca05bf4743cb2df10\",\n \"score\": \"0.5529778\",\n \"text\": \"def read_previous_schema(self) -> List[dict]:\\n\\n self.check_for_existing_schema()\\n\\n with open(self.schema_dir) as schema:\\n data = json.load(schema)\\n\\n return data\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f72f363b71c88692c90897d38e58fb8f\",\n \"score\": \"0.5527214\",\n \"text\": \"def read_schema_from_file() -> dict:\\n logger.info(f'Reading schema from: {SCHEMA_FILE}')\\n try:\\n with open(SCHEMA_FILE) as input_file:\\n return json.load(input_file)\\n except FileNotFoundError:\\n raise ZenodoMetadataException(f'Schema file: {SCHEMA_FILE} not found.')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"57cdf079f69d20f92d720723c7110103\",\n \"score\": \"0.55207723\",\n \"text\": \"def fake_data_schema():\\n return FakeDataSchema()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8dd08e8786a8ba6b7d4d4ae3d8df15ec\",\n \"score\": \"0.5520027\",\n \"text\": \"def __init__(self):\\n self.data_schema = vol.Schema(\\n {\\n vol.Required(CONF_USERNAME): str,\\n vol.Required(CONF_PASSWORD): str,\\n vol.Optional(CONF_CODE): str,\\n }\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"00cb27c88dcbcfd1e1ffbf7fdd4dfdee\",\n \"score\": \"0.5514165\",\n \"text\": \"def _schema_def(self, resource: Type[ResourceBase]) -> Dict[str, str]:\\n meta = getmeta(resource)\\n ref = meta.resource_name\\n if ref not in self.defs:\\n self.defs[ref] = None # Placeholder to prevent recursion\\n self.defs[ref] = self._resource_to_schema(meta)\\n return {\\\"$ref\\\": f\\\"#/$defs/{ref}\\\"}\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9ae7bad8c28802a5ec685660f0c8ad3e\",\n \"score\": \"0.5506005\",\n \"text\": \"def __init__(self, name, schema):\\n self.name = name\\n self.schema = schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"478ed98ec167e968643f21f4c1c29c55\",\n \"score\": \"0.5498467\",\n \"text\": \"def schema(self, schema):\\n\\n self._schema = schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ee2d716cf61a72e64dcd03a60345a487\",\n \"score\": \"0.5497979\",\n \"text\": \"def get_schema(cls) -> Dict[str, Any]:\\n schema = super().get_schema()\\n schema[\\\"uihints\\\"].update({\\\"canRefresh\\\": True})\\n return schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f286ea442c15596513ad704ee381587e\",\n \"score\": \"0.5493095\",\n \"text\": \"def _get_schema_from_file(schema_file):\\n try:\\n return load_json_file(schema_file)\\n except:\\n raise ConfigException(\\n 'Cannot load schema from file {}: {}'.format(\\n schema_file, traceback.format_exc())\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"70978278f69bcd0b1d2f6eb4a47c8612\",\n \"score\": \"0.54918206\",\n \"text\": \"def get_standard_json_schema():\\n return standard_json_schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d912056dc4c4aaf55431cfdf00cce0d9\",\n \"score\": \"0.54900414\",\n \"text\": \"def getschema(self, schemaname):\\n if not self.registry.has_key(schemaname):\\n self.convert_schema(schemaname=schemaname)\\n outschema = self.registry.get(schemaname)\\n return outschema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8fec341de54cccbdf06e4278b224c7dd\",\n \"score\": \"0.54724944\",\n \"text\": \"def getSchema(schema):\\n \\n rip = _schema[schema]\\n \\n s = Schema.Schema(open(rip.path))\\n \\n assert s.id == schema, _('schema %s has not the same id %s as in the RIP files') % (\\n rip.path, schema)\\n return s\",\n \"title\": \"\"\n },\n {\n \"docid\": \"60ba4845e64be76aeba0dbed09feca26\",\n \"score\": \"0.5470302\",\n \"text\": \"def get_introspection_schema(self, apiId: str, format: str) -> Dict:\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"508b4e1b2739b7428e0976a821059255\",\n \"score\": \"0.5469957\",\n \"text\": \"def schema(self):\\n schema = super().schema\\n schema['properties'].update(\\n {\\n 'artist': {'type': 'string'},\\n 'album': {'type': 'string'},\\n 'year': {'type': ['string', 'integer']},\\n 'tags': one_or_more({'type': 'string'}),\\n 'tag_type': {'type': 'string', 'enum': list(self._opts('tag_type').keys())},\\n 'encoding': {'type': 'string', 'enum': self._opts('encoding')},\\n 'format': {'type': 'string', 'enum': self._opts('format')},\\n 'media': {'type': 'string', 'enum': self._opts('media')},\\n 'release_type': {\\n 'type': 'string',\\n 'enum': list(self._opts('release_type').keys()),\\n },\\n 'log': {\\n 'oneOf': [\\n {'type': 'string', 'enum': list(self._opts('log').keys())},\\n {'type': 'boolean'},\\n ]\\n },\\n 'leech_type': {'type': 'string', 'enum': list(self._opts('leech_type').keys())},\\n 'hascue': {'type': 'boolean'},\\n 'scene': {'type': 'boolean'},\\n 'vanityhouse': {'type': 'boolean'},\\n }\\n )\\n return schema\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b0c25fdf6f6f2d1de92730eeaa36d0a2\",\n \"score\": \"0.54668695\",\n \"text\": \"def schema_database_read():\\n return {0: (\\\"titleb\\\", str),\\n 1: (\\\"type\\\", str),\\n 2: (\\\"xmlUrl\\\", str),\\n 3: (\\\"htmlUrl\\\", str),\\n 4: (\\\"keywordsb\\\", str),\\n 5: (\\\"id\\\", int, \\\"PRIMARYKEY\\\", \\\"AUTOINCREMENT\\\")}\",\n \"title\": \"\"\n },\n {\n \"docid\": \"30b70c118a4730f09794c7615ca5424b\",\n \"score\": \"0.5466642\",\n \"text\": \"def need_schema_upgrade(self):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f0227b515313d3f4a501081a62ebaeaf\",\n \"score\": \"0.54564106\",\n \"text\": \"def add_schema(schema, connection):\\n create_schemas_meta_table(connection)\\n\\n file_pattern = schema['meta']['files']\\n time = schema['meta']['version']\\n description = schema['meta']['description']\\n processing_schema = json.dumps(schema['processing'])\\n\\n cur = connection.cursor()\\n cur.execute(\\n f\\\"INSERT INTO {xml_schemas_table} \\\"\\n f\\\"({file_pattern_field}, {schema_time_field}, {schema_desc_field}, {proc_schema_field}) \\\"\\n \\n \\\"VALUES \\\"\\n f\\\"('{file_pattern}', '{time}', '{description}', '{processing_schema}'::json) \\\"\\n \\n f\\\"ON CONFLICT DO NOTHING;\\\")\\n connection.commit()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"15d517c411da1cce436813b4bbdb5ab6\",\n \"score\": \"0.5456108\",\n \"text\": \"def __fetch__definition(self):\\r\\n dom = xml.dom.minidom.parseString(self.input_xml)\\r\\n self.logger.debug('Loading parameters: %s' % (dom.toprettyxml()))\\r\\n setattr(self, 'thoughtspot_host_name', Et.fromstring(self.input_xml).find('DestinationServer').text\\r\\n if 'DestinationServer' in self.input_xml else None)\\r\\n if self.thoughtspot_host_name is None:\\r\\n self.error = \\\"Please Enter a ThoughtSpot Server\\\"\\r\\n return\\r\\n\\r\\n setattr(self,'thoughtspot_database_name', Et.fromstring(self.input_xml).find('TargetDatabase').text\\r\\n if 'TargetDatabase' in self.input_xml else None)\\r\\n if self.thoughtspot_database_name is None:\\r\\n self.error = \\\"Please Enter a Database Name\\\"\\r\\n return\\r\\n\\r\\n setattr(self, 'thoughtspot_schema', Et.fromstring(self.input_xml).find('TargetSchema').text\\r\\n if 'TargetSchema' in self.input_xml else 'falcon_default_schema')\\r\\n\\r\\n setattr(self, 'thoughtspot_user_name', Et.fromstring(self.input_xml).find('UserName').text\\r\\n if 'UserName' in self.input_xml else None)\\r\\n if self.thoughtspot_user_name is None:\\r\\n self.error = \\\"Please Enter a ThoughtSpot User Name\\\"\\r\\n return\\r\\n\\r\\n password = Et.fromstring(self.input_xml).find('Password').text if 'Password' in self.input_xml else None\\r\\n setattr(self, 'thoughtspot_rsa_file_path', Et.fromstring(self.input_xml).find('rsaFilePath').text\\r\\n if 'rsaFilePath' in self.input_xml else None)\\r\\n if self.thoughtspot_rsa_file_path is not None:\\r\\n setattr(self, 'use_key_file', True)\\r\\n setattr(self, 'thoughtspot_password', None)\\r\\n else:\\r\\n if password is None:\\r\\n self.error = \\\"A Password or Key file Must be Entered\\\"\\r\\n return\\r\\n else:\\r\\n # Can be used for unencrypted passwords. remove # on line 95 and place a # on lines 97 and 98\\r\\n # setattr(self, 'thoughtspot_password', password)\\r\\n setattr(self, 'use_key_file', False)\\r\\n setattr(self, 'thoughtspot_password', self.alteryx_engine.decrypt_password(\\r\\n Et.fromstring(self.input_xml).find('Password').text, 0))\\r\\n\\r\\n setattr(self, 'thoughtspot_table_name', Et.fromstring(self.input_xml).find('TableName').text\\r\\n if 'TableName' in self.input_xml else None)\\r\\n if self.thoughtspot_table_name is None:\\r\\n self.error = \\\"Please Enter a ThoughtSpot Table Name\\\"\\r\\n return\\r\\n\\r\\n port_test = Et.fromstring(self.input_xml).find('DestinationPort').text\\r\\n self.logger.info(port_test)\\r\\n if port_test is None:\\r\\n setattr(self, 'thoughtspot_port', 22)\\r\\n else:\\r\\n setattr(self, 'thoughtspot_port', int(port_test))\\r\\n\\r\\n setattr(self, 'buffer_size', int(Et.fromstring(self.input_xml).find('BufferSize').text)\\r\\n if 'BufferSize' in self.input_xml else None)\\r\\n if self.buffer_size is None:\\r\\n self.error = \\\"Please Enter the row buffer size (Default: 1000)\\\"\\r\\n return\\r\\n\\r\\n setattr(self, 'verbosity', Et.fromstring(self.input_xml).find('Verbosity').text\\r\\n if 'Verbosity' in self.input_xml else 0)\\r\\n setattr(self, 'maxingoredrows', Et.fromstring(self.input_xml).find('MaxIgnoredRows').text\\r\\n if 'MaxIgnoredRows' in self.input_xml else 0)\\r\\n setattr(self, 'truncate', Et.fromstring(self.input_xml).find('Truncate').text\\r\\n if 'Truncate' in self.input_xml else False)\\r\\n setattr(self, 'ts_create_database', Et.fromstring(self.input_xml).find('CreateDatabase').text\\r\\n if 'CreateDatabase' in self.input_xml else False)\\r\\n setattr(self, 'booleanstring', Et.fromstring(self.input_xml).find('BooleanString').text\\r\\n if 'BooleanString' in self.input_xml else 'T_F')\\r\\n setattr(self, 'ts_create_table', Et.fromstring(self.input_xml).find('CreateTable').text\\r\\n if 'CreateTable' in self.input_xml else False)\\r\\n\\r\\n primary_keys = Et.fromstring(self.input_xml).find('PrimaryKey').text \\\\\\r\\n if 'PrimaryKey' in self.input_xml else None\\r\\n if primary_keys is not None:\\r\\n setattr(self, 'primary_keys', '\\\",\\\"'.join(primary_keys.split(\\\",\\\")))\\r\\n else:\\r\\n setattr(self, 'primary_keys', None)\\r\\n\\r\\n hash_test = Et.fromstring(self.input_xml).find('HashValue').text\\r\\n self.logger.info(hash_test)\\r\\n if hash_test is None:\\r\\n setattr(self, 'hash_number', 0)\\r\\n setattr(self, 'partition_keys', None)\\r\\n else:\\r\\n setattr(self, 'hash_number', int(hash_test))\\r\\n partition_keys = Et.fromstring(self.input_xml).find('PartitionKey').text \\\\\\r\\n if 'PartitionKey' in self.input_xml else None\\r\\n if partition_keys is not None:\\r\\n setattr(self, 'partition_keys', '\\\",\\\"'.join(partition_keys.split(\\\",\\\")))\\r\\n else:\\r\\n setattr(self, 'partition_keys', None)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6f1ce7d7d3f58fb96f924949d0c220e8\",\n \"score\": \"0.5454911\",\n \"text\": \"def __init__(self):\\n\\n self.database = \\\"shsmd.db\\\"\\n self.debug = False\\n self.schema = \\\"../schema.sql\\\"\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":397,"cells":{"query_id":{"kind":"string","value":"ba2f90b28966006b3764a6a8cadb2c84"},"query":{"kind":"string","value":"Returns the importance of term in document id. If the term isn't in the document, then return 0."},"positive_passages":{"kind":"list like","value":[{"docid":"40550b3d44025bcbb8fdf4c3d7ea859c","score":"0.718705","text":"def imp(term,id):\r\n if id in postings[term]:\r\n return postings[term][id]*inverse_document_frequency(term)\r\n else:\r\n return 0.0","title":""}],"string":"[\n {\n \"docid\": \"40550b3d44025bcbb8fdf4c3d7ea859c\",\n \"score\": \"0.718705\",\n \"text\": \"def imp(term,id):\\r\\n if id in postings[term]:\\r\\n return postings[term][id]*inverse_document_frequency(term)\\r\\n else:\\r\\n return 0.0\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"1ab6cc16ab1cfd758823ca6ce6adb0c8","score":"0.73194516","text":"def get_tfidf_scores(self, term, document):\n if term in self.tf[document]:\n return self.tf[document][term] * self.idf[term]\n else:\n return 0","title":""},{"docid":"a5322e56d406d8222b4591b5dc78afe3","score":"0.7267702","text":"def imp(self, term, id):\n if id in self.frequency[term]:\n return self.frequency[term][id] * self.inverse_document_frequency(term)\n else:\n return 0.0","title":""},{"docid":"4c2be31df7ae39a53804ef7839af5709","score":"0.7203408","text":"def compute_term_frequency_in_collection(self, term, id_document):\n try:\n tf = self.inverted_index[term][id_document]\n return tf\n except KeyError:\n return 0","title":""},{"docid":"b76922a897681b8201269db22bb15b46","score":"0.6974998","text":"def get_idf(self, term):\n if term in self.stopwords:\n return 0\n\n if not term in self.term_num_docs:\n return self.idf_default\n\n return math.log(float(1 + self.get_num_docs()) / \n (1 + self.term_num_docs[term]))","title":""},{"docid":"b7e2d4947a28623fa72af23a6fe53cb3","score":"0.6677582","text":"def idf(self, word, corpus):\r\n\r\n idf = self.doc_freq(word, corpus)\r\n if idf == 0: \r\n return 0\r\n return np.log10(len(corpus)/(idf))","title":""},{"docid":"b9723043fe5e9c564378843a21b06a95","score":"0.66243446","text":"def compute_idf(self, term):\n try:\n # thanks to the inverted index, we have access to all the documents containing the term\n docs = self.inverted_index[term].keys()\n df = len(docs)\n except KeyError:\n return 0\n return log(self.number_of_docs / df)","title":""},{"docid":"9f263d50d42b747d120513716838d8f5","score":"0.6587332","text":"def term_frequency(term: str, document: dict):\n if term not in document:\n return 0\n\n number_of_occurences = document[term]\n total_number_of_occurences = sum(document.values())\n\n return number_of_occurences / total_number_of_occurences","title":""},{"docid":"de89ea5fb8b03ae122b942e3b87a2ce8","score":"0.6554476","text":"def term_freq(self, word, document):\r\n\r\n if word in document.word_freq:\r\n return (1+np.log10(document.word_freq[word]))\r\n else:\r\n return 0","title":""},{"docid":"6f78c0da6db0011ccd8bc003de211461","score":"0.65498453","text":"def get_words_importance(self, doc_word_dict : dict, id : int) -> list:\n word_list = doc_word_dict[id]\n word_importance = {}\n for word in word_list:\n word_importance[word] = log(len(doc_word_dict) / self.get_docs_for_word(word, doc_word_dict))\n return word_importance","title":""},{"docid":"2592e943c06bd2a5be5a849cd218affd","score":"0.6462634","text":"def __term_frequency(term, document, query=False):\n\tif query:\n\t\treturn query_vector[term]\n\tif document not in inverted_index[term].keys():\n\t\treturn 0\n\treturn inverted_index[term][document]","title":""},{"docid":"5624abaeb1c7b984a84d204a831f4bf7","score":"0.6405168","text":"def __document_frequency(term):\n\treturn len(inverted_index[term])","title":""},{"docid":"1af3094b55566ff878786ae2ba3cfef4","score":"0.6375153","text":"def term_frequency(self, term):\n term = re.sub(r'\\W+', '', term).lower()\n if term not in self._word_to_count.keys():\n return 0\n else:\n return self._word_to_count[term] / self._word_count","title":""},{"docid":"586f3fd4626f8420c9d0804104d99fe8","score":"0.6220984","text":"def __get_idf(self, token):\n df = self.dictionary.dfs.get(token, 0)\n if df == 0:\n return 0\n else:\n return math.log(len(self.dictionary.doc_ids)/df, 10)","title":""},{"docid":"9d194912cafdb6ae92cd5cba74d04f45","score":"0.6220814","text":"def idf(self, searcher, fieldname, text):\r\n\r\n parent = searcher.get_parent()\r\n n = parent.doc_frequency(fieldname, text)\r\n dc = parent.doc_count_all()\r\n return log(dc / (n + 1)) + 1","title":""},{"docid":"1b0032c32dcc640f5a00002fa4d914d5","score":"0.62125367","text":"def __log_term_frequency(term, document, query=False):\n\tif __term_frequency(term, document, query) > 0:\n\t\treturn 1 + math.log(__term_frequency(term, document, query))\n\treturn 0","title":""},{"docid":"2a85052c0c58a437b40768cbb5100e80","score":"0.6199197","text":"def idf(self, term):\n return self.get_cache('idf', term,\n lambda: math.log(len(self.DOCVECS)/self.df(term)))","title":""},{"docid":"0c492b24c60f3b8398f35b0d81affcd1","score":"0.61888534","text":"def compute_tf(document, term, type='raw'):\n assert (type in ['raw', 'augmented', 'boolean']), \"The parameter 'type' is not recognized. Please enter 'raw', 'boolean' or 'augmented' as it's value.\"\n tf = 0.0\n if type == 'raw':\n tf = float(document.count(term))\n if type == 'boolean':\n tf = float(term in document)\n if type == 'augmented':\n tf = 0.5 + ((0.5 * float(document.count(term))) / float(max([document.count(x) for x in document])))\n return tf","title":""},{"docid":"b97c9c31f33cf2a704478804d66a14f4","score":"0.6161808","text":"def compute_tf_idf(self, term, id_document):\n tf_idf = self.log_normalization(term, id_document) * self.compute_idf(term)\n return tf_idf","title":""},{"docid":"d4c6248e2039be9f502ed22fd972928f","score":"0.6156177","text":"def term_frequency(word, document):\n return document.count(word) / len(document.split(\" \"))","title":""},{"docid":"c59e803d24c0ef0882023c997952f41c","score":"0.61420256","text":"def word_frequency_of_word_in_document(self, word, document_id):\n if word in self.documents[document_id]:\n return self.documents[document_id][word]\n else:\n return 0","title":""},{"docid":"1a2e701a6e91e0f7f264f8bcdec5f1d3","score":"0.61271435","text":"def inverse_document_frequency(term):\r\n if term in dictionary:\r\n return math.log(N/document_frequency[term],2)\r\n else:\r\n return 0.0","title":""},{"docid":"caad6749524bf8c38cfc72d0be5a5d29","score":"0.6126351","text":"def get_score(self, query_term, doc):","title":""},{"docid":"ee0fd5091e801e91faf085ff3631d573","score":"0.60995793","text":"def tf_idf(self, word, document, corpus):\r\n\r\n return self.term_freq(word, document)*self.idf(word, corpus)","title":""},{"docid":"b30f2746bf96644b686cd8a0c474e32c","score":"0.60398054","text":"def _idf(self, word, counter):\n try:\n return self._log_freqlist_total - math.log(self._freqlist[word])\n except ValueError:\n return 0","title":""},{"docid":"f34b4ae22c6e331f006af3bf546b094f","score":"0.60377926","text":"def log_term_frequency(term: str, document: dict):\n return 1 + log(term_frequency(term, document))","title":""},{"docid":"3b0f3e4494c5f04a6345e54d9f80d450","score":"0.6011292","text":"def tfidfScore(tf, numdocs, numtermincorp):\n return tf * log(numdocs / (1 + numtermincorp))","title":""},{"docid":"fe9e99d67c716bf19c7ea992f94627d4","score":"0.60076827","text":"def _get_term_freq(self, doc):\n tf_dict = {}\n for token in doc:\n if token in tf_dict:\n tf_dict[token] += 1\n else:\n tf_dict[token] = 1\n for token in tf_dict:\n tf_dict[token] = tf_dict[token] / len(doc)\n return tf_dict","title":""},{"docid":"e3ad043b895baa11dfdb2ca1c73d7b55","score":"0.5957657","text":"def getTF(self,word):\r\n return float(self.getCountOf(word))/float(self.getWordCount())","title":""},{"docid":"f2a62be0f3d9539a0a1a0f2b0076ce78","score":"0.59250844","text":"def inverse_document_frequency(self, term):\n\n if term in self.dictionary:\n return math.log(self.N / len(self.index.get_postings(term)), 2)\n return 0.0","title":""},{"docid":"91d88c4128cdaa7dd51d20b795f8deda","score":"0.5862421","text":"def get_tfidf_score(self, input_term, all_terms, unique_terms):\n if unique_terms.size==0: \n log_print(\"No terms found for the input term {}\".format(input_term))\n return None\n\n total = 1855658.0\n tf = Counter(item for sublist in all_terms for item in sublist)\n\n path_to_nyt_idf = os.path.dirname(os.path.realpath(__file__))\n with open(os.path.join(path_to_nyt_idf, 'nyt_idf_nonstem.json'), 'r') as fp:\n idf = json.load(fp)\n score = np.array([tf[term]*np.log(total/idf[term]) for term in unique_terms])\n tf_idf = dict(zip(unique_terms, score/max(score)))\n return tf_idf","title":""},{"docid":"6149e125de392f1ba023640ab7d3d0ef","score":"0.5833293","text":"def __boolean_term_frequency(term, document, query=False):\n\tif __term_frequency(term, document, query) > 0:\n\t\treturn 1\n\treturn 0","title":""},{"docid":"1770af3b106b3a4008e60f156566787d","score":"0.5805489","text":"def idf(word, stats):\n return math.log(stats.N() / stats[word]) if word in stats else 0","title":""},{"docid":"348fade58f793fcb812eda46cec34be5","score":"0.5763374","text":"def term_frequency(word, word_frequency):\n\n return 0 if word_frequency[word] == 0 else 1 + log(word_frequency[word])","title":""},{"docid":"4e09b728ce54fcee100f2eb375d705b2","score":"0.57567257","text":"def document_frequency(term: str, documents: list):\n documents_with_term = [doc for doc in documents if term_frequency(term, doc) > 0];\n\n return len(documents_with_term)","title":""},{"docid":"eaab51e438bd8e4fbbe7b389c6d5f2a2","score":"0.5746729","text":"def get_score(self, query_term, doc):\n return self.__getattribute__(self.retrieval_model)(query_term, doc)","title":""},{"docid":"3669da697e4141eaa0ca4cfc0d1da637","score":"0.5736835","text":"def __inverted_documnent_frequency(term):\n\treturn math.log(movies['num_of_movies'] / __document_frequency(term))","title":""},{"docid":"8488e0b73a112efdc34bb77803e4cd73","score":"0.57291937","text":"def raw_counts(self, query_term, doc):\n return doc.get_dtf() * self.query_terms.count(query_term)","title":""},{"docid":"35dd44506bbd01bdfd5144dcfc628d6f","score":"0.5728637","text":"def tfidf(term: str, document: dict, documents: list):\n tf = term_frequency(term, document)\n idf = inverse_document_frequency(term, documents)\n\n return tf*idf","title":""},{"docid":"bf3ef435509aecb9fd5e9d4ae192029e","score":"0.5718501","text":"def __score(term, document, scoring_scheme, query):\n\tterm_frequency_type = scoring_scheme\n\tif term_frequency_type == \"n\":\n\t\tterm_frequency = __term_frequency(term, document, query)\n\telif term_frequency_type == \"l\":\n\t\tterm_frequency = __log_term_frequency(term, document, query)\n\telif term_frequency_type == \"a\":\n\t\tterm_frequency = __augmented_term_frequency(term, document, query)\n\telif term_frequency_type == \"b\":\n\t\tterm_frequency = __boolean_term_frequency(term, document, query)\n\n\treturn term_frequency * __inverted_documnent_frequency(term)","title":""},{"docid":"a17c89b352252ff33a9369b37f677cbf","score":"0.5707244","text":"def score_one(self, sd):\r\n return (self.param + sd.doc_term_count) / (self.param * sd.doc_unique_terms + sd.doc_size)","title":""},{"docid":"c7592a95c1fb70a21065a5a2edc740ae","score":"0.567741","text":"def compute_idfs(self, word_dict):\r\n\t\tprint('computing IDF scores for words within corpus')\r\n\t\t# obtain document frequencies\r\n\t\tdfreqs = dict(word_dict.dfs)\r\n\t\t# return IDF scores\r\n\t\treturn {word_dict[idx]: np.log(word_dict.num_docs / (1 + float(dfreq))) for idx, dfreq in dfreqs.items()}","title":""},{"docid":"7719a1d51402e4e84c1237245f16469b","score":"0.5644053","text":"def inverse_document_frequency(self, query_word):\n no_qi = self.no_of_documents_containing_a_word(query_word)\n return float(math.log(self.no_of_documents / (no_qi + 1.0)))","title":""},{"docid":"b19b542d025bfce2d3cad706005e27cd","score":"0.5636606","text":"def idfTerm(term, searcher):\n\n return idf(searcher.docFreq(term), searcher.maxDoc())","title":""},{"docid":"f7c433f0945151873995a277b2b1067d","score":"0.5621689","text":"def getFreq(self,text, word_type=''):\n\t\tidList=[];\n\t\t#if araby.isHaraka(text[-1:]): text=text[:-1];\n\t\tidList=self.lookup(text,word_type);\n\t\t# if there are many take the first\n\t\tif idList:\n\t\t\treturn self.getAttribById(idList[0], u'freq')\n\t\telse: \n\t\t\treturn 0;","title":""},{"docid":"8d3029bbba9b9d700bd4a2f62d1ff631","score":"0.56136155","text":"def idf(word, word_list):\n N = len(word_list)\n num_documents_containing_word = len([True for document in word_list if word in document])\n return math.log(N / num_documents_containing_word + 1) # + 1 accounts for if the word doesn't occur in any of the documents","title":""},{"docid":"fc1ea5739249359c1f3a68edeb9bdc16","score":"0.5594896","text":"def importance(self) -> int:\n return self._importance","title":""},{"docid":"45e9e1b76288883f663c61924147090f","score":"0.55904835","text":"def __augmented_term_frequency(term, document, query=False):\n\tmax_term_frequency = -1\n\tfor t in inverted_index.keys():\n\t\tmax_term_frequency = max(max_term_frequency, __term_frequency(t, document, query))\n\treturn 0.5 + 0.5 * ( __term_frequency(term, document, query) / max_term_frequency )","title":""},{"docid":"3999b27040b7591d54a2714c1c96589d","score":"0.55884415","text":"def calc_tfidf_similarity(doc1: Counter, doc2: Counter, idf:\n Dict[Text, float]):\n tf1_max = max(doc1.values())\n tf2_max = max(doc2.values())\n total_sum = 0.0\n for word, tf1 in doc1.items():\n tf2 = doc2[word]\n if tf2 == 0 or word not in idf:\n continue\n tf1_norm = (0.5+0.5*float(tf1)/tf1_max)\n tf2_norm = (0.5+0.5*float(tf2)/tf2_max)\n idf_val = idf[word]\n total_sum += tf1_norm * tf2_norm * (idf_val*idf_val)\n return math.sqrt(total_sum)","title":""},{"docid":"6f5bc01a23ac9affce6c84799cb26171","score":"0.55526114","text":"def get_idf(tf_matrix, term_index):\n\n # Document Frequency (DF)\n df = 0\n for entry in tf_matrix[:, term_index]:\n if entry > 0:\n df += 1\n\n # print \"df = \", df\n # Inverse Document Frequency (IDF)\n if df:\n idf = 1.0 + math.log10(float(TOTAL_DOCS) / df)\n else:\n idf = 0.0\n\n return idf","title":""},{"docid":"59016a1f4e819b2d9a971198ba18fc81","score":"0.554357","text":"def similarity(self, query, id):\n similarity = 0.0\n for term in query.split(' '):\n if term in self.dictionary:\n similarity += self.inverse_document_frequency(term) * self.imp(term, id)\n\n if self.length[id] > 0:\n similarity = similarity / self.length[id]\n return similarity","title":""},{"docid":"95bda274f1cacdd9e0684d4866897bf0","score":"0.5534798","text":"def calculate_document_tf_idf(sentence, paper_bag_of_words):\n # Sanity check\n assert(len(paper_bag_of_words) > 0)\n\n sentence_bag_of_words = defaultdict(float)\n for word in sentence:\n\n if word in STOPWORDS:\n continue\n else:\n sentence_bag_of_words[word] += 1.0\n\n sent_tf_idf = 0\n length = 0\n\n for word in sentence:\n\n if word in STOPWORDS:\n continue\n\n tf = sentence_bag_of_words[word]\n\n # Add 1 to the denominator to prevent division by 0\n idf = np.log(len(paper_bag_of_words) / (paper_bag_of_words[word] + 1))\n\n tf_idf = tf * idf\n\n sent_tf_idf += tf_idf\n\n length += 1\n\n if length == 0:\n return 0\n else:\n return sent_tf_idf / length","title":""},{"docid":"574154d391ef7cea72fcd34ca925cc22","score":"0.5512458","text":"def calculate_tf_idf(sentence, global_count_of_papers_words_occur_in, paper_bag_of_words):\n bag_of_words = paper_bag_of_words\n\n sentence_tf_idf = 0\n\n length = 0\n\n for word in sentence:\n\n if word in STOPWORDS:\n continue\n\n # Get the number of documents containing this word - the idf denominator (1 is added to prevent division by 0)\n docs_containing_word = global_count_of_papers_words_occur_in[word] + 1\n\n # Count of word in this paper - the tf score\n count_word = bag_of_words[word]\n\n idf = np.log(NUMBER_OF_PAPERS / docs_containing_word)\n\n #word_tf_idf = (1 + np.log(count_word)) * idf\n\n word_tf_idf = count_word * idf\n\n sentence_tf_idf += word_tf_idf\n\n length += 1\n\n if length == 0:\n return 0\n else:\n sentence_tf_idf = sentence_tf_idf / length\n return sentence_tf_idf","title":""},{"docid":"3462723797b792010e0af288e4741b46","score":"0.5498431","text":"def dirichlet(self, query_term, doc):\n # Frequency of term in the document (document term frequency - dtf)\n fqiD = doc.get_dtf()\n # Length of the document\n dl = self.inverted_index.get_doc_length(doc.get_doc_id())\n # Frequency of term in the collection (collection term frequency - ctf)\n cqi = self.inverted_index.get_ctf(query_term)\n # Total length of all documents in the collection\n cl = self.inverted_index.get_collection_length()\n \n score = math.log((fqiD + (self.mu * (cqi / cl))) / (dl + self.mu))\n return score * self.query_terms.count(query_term)","title":""},{"docid":"53784acbc9786bc475f618db0be4be48","score":"0.54652566","text":"def _tf(tokenized_doc):\n term_tf = {}\n for term in tokenized_doc:\n if term not in term_tf:\n term_tf[term]=1.0\n else:\n term_tf[term]+=1.0\n\n # pprint(term_tf)\n return term_tf","title":""},{"docid":"3b293b37d790c1975b74936de9cf4842","score":"0.546485","text":"def calculate_similarity(corpus, term_corpus):\n\n N = corpus.shape[0] # total number of reports\n term_counter = Counter()\n\n for index, value in corpus.items():\n total_features = value\n\n for term in term_corpus:\n if term in total_features:\n term_counter[term] += 1\n\n similarity = 0\n # idf = log(num_documents / num_documents_contain_term + 1)\n for term, term_frequency in term_counter.items():\n term_IDF = math.log(float(N) / (term_frequency + 1))\n similarity += term_IDF\n return similarity","title":""},{"docid":"001734219fdd4482655a970acca37de9","score":"0.5433262","text":"def __get_weight_query_term(self, term, term_tf, n):\n\n # calculate tf in query\n # log_tf = 1 + math.log10(term_count)\n\n if term in self.dictionary.keys():\n (freq, postings_line) = self.dictionary[term]\n # calculate idf\n idf = math.log10(float(n)/float(freq))\n return term_tf * idf\n else:\n return 0","title":""},{"docid":"65aac01b64ac0f8b5a171dd749d75a0d","score":"0.5414591","text":"def tf(bag_words, doc_dict):\n tf = {}\n len_doc = len(doc_dict)\n\n for token, count in bag_words.items():\n if count > 0:\n tf[token] = count / float(len_doc)\n else:\n tf[token] = 0\n return tf","title":""},{"docid":"13bf35a9296fb0ecdbb8d9561964c3da","score":"0.5411817","text":"def doc_frequency(self, fieldid, text):\r\n raise NotImplementedError","title":""},{"docid":"e3740a833027b125cf246a422ad7acb1","score":"0.5398581","text":"def compute_tfdf_score(cur, user_id, tf_type):\n score = 0.0\n # Get timeline_document from user\n cur.execute(\"SELECT timeline_document FROM users WHERE user_id = {};\".format(user_id))\n tl_doc = cur.fetchone()\n # tl_doc = cur.fetchone()[0]\n if (tl_doc is None) or (tl_doc[0] is None) or (len(tl_doc[0]) < 1):\n return score\n # Iterate over all topics to compute the final score\n cur.execute(\"SELECT topic, document_frequency FROM topics;\")\n for t in cur:\n # Compute TF\n tf = compute_tf(document=tl_doc[0], term=t[0], type=tf_type)\n # Compute TF-IDF\n score += tf * t[1]\n return score","title":""},{"docid":"a86dc21dd09b9feebb35225e625b55f0","score":"0.53949726","text":"def _get_unigram_count(self, word):\n c = self.db_conn.cursor()\n c.execute(\"SELECT frequency FROM unigram_count WHERE word = ?\",\n (word,))\n result = c.fetchone()\n return float(result[0]) if result else 0","title":""},{"docid":"a6cfcf155e9aaaf81074af691498c62e","score":"0.5393289","text":"def doc_freq(self, word, corpus):\r\n\r\n # finding doc_freq using len(posting list) from inverted index(if present)\r\n if len(self.inv_index)>0:\r\n return len(self.inv_index[word])\r\n\r\n count = 0\r\n for doc in corpus:\r\n if word in doc.word_freq:\r\n count += 1\r\n return count","title":""},{"docid":"0217b748cfb19226bb42bf3b93a85b88","score":"0.5378008","text":"def get_docs_for_word(self, word : str, doc_word_dict : dict) -> float:\n n_docs = len(doc_word_dict)\n n_docs_containing_word = 0\n for doc in doc_word_dict:\n if word in doc_word_dict[doc]:\n n_docs_containing_word = n_docs_containing_word + 1\n if n_docs_containing_word == 0:\n print(\"Safety check. Ideally it shouldn't enter this if condition\")\n return 1\n return n_docs_containing_word","title":""},{"docid":"4c1c7fd7fee301ff306fc66b83ebeba3","score":"0.5369192","text":"def get_score(self, word):\n retval = 0.0\n # calculate score if dictionaries are present\n if self.wdict != None and self.tdict != None:\n w = self.wdict.count(word)\n if w != 0:\n retval = self.tdict.count(word) * 1.0 / w\n return retval","title":""},{"docid":"c6a7c90b47326363418dda94fa0ff68c","score":"0.5367672","text":"def raw_counts(self, query_term, doc):","title":""},{"docid":"c1077a1ca0ed251d0f9937fbbd034a32","score":"0.5360859","text":"def scalar_inc_dec(word, valence, words_and_emoticons):\n previous_word = ' '\n next_word = ' '\n scalar = 0.0\n\n if word in BOOSTER_DICT:\n\n scalar = BOOSTER_DICT[word]\n if valence < 0:\n scalar *= -1\n\n return scalar","title":""},{"docid":"983413b0753de4f66dc6030c1158be4e","score":"0.5358795","text":"def count_bag(self, tweet, use_first_tf_doc):\n\n count = 0.0\n sanitised_tweet_text = tweet['text'] # OSX\n #sanitised_tweet_text = tweet.text # Windows\n hashtag = False\n term_frequency_document = self.termfreq_doc if use_first_tf_doc else self.second_net_termfreq_doc\n count += self.get_author_sentiment(tweet)\n\n\n # The following loop first checks if the word in the tweet\n # is a hastag, setting the hashtag boolean to true if it is.\n # Then, a check is used to see if the term is in the term\n # frequency document. If it is, then add the value of that\n # term (plus 1) to the count, multiplying it by the hash_tag_multiplier \n # variable if the term is a hashtag. Then subtract the number returned\n # by the get_tweet_age_score function for that tweet, and finally\n # return the resulting count. If the count is below zero, return it\n # to zero.\n\n\n for word in sanitised_tweet_text.split():\n if word[0] == \"#\":\n text_word = word.lower().replace(\"#\", \"\")\n hashtag = True\n else:\n text_word = word.lower()\n if term_frequency_document.has_key(text_word):\n #if text_word in term_frequency_document.keys():\n count += 1\n if hashtag == True:\n if self.termfreq_doc.get(text_word) is not None:\n count += (self.termfreq_doc.get(text_word) * self.hash_tag_multiplier)\n hashtag = False\n else:\n if self.termfreq_doc.get(text_word) is not None:\n count += self.termfreq_doc.get(text_word)\n \n count -= self.get_tweet_age_score(tweet)\n if count <= 0.0:\n count = 0.0 \n print(count)\n return count","title":""},{"docid":"ded23487a7ce3d39c1e6f9d0e94b2091","score":"0.53567445","text":"def rarity(self, word):\r\n if not isinstance(word, str):\r\n raise TypeError(\"Word given must be a string\")\r\n\r\n try:\r\n occurrence = self.word_frequency[word]\r\n except KeyError: # misspelling or missing word\r\n return 3\r\n\r\n if self.max/100 <= occurrence: # common\r\n return 0\r\n elif self.max/1000 <= occurrence < self.max/100: # uncommon\r\n return 1\r\n elif 0 < occurrence < self.max/1000: # rare\r\n return 2","title":""},{"docid":"048e6c7db7c4d184c0e8378dbaccd291","score":"0.5353218","text":"def vector_space(self, query_term, doc):\n # Frequency of term in the document (document term frequency - dtf)\n fik = doc.get_dtf()\n # Number of documents in the collection\n N = self.inverted_index.get_total_docs()\n # Number of documents containing the term (document frequency - df)\n nk = self.inverted_index.get_df(query_term)\n \n score = 0\n if fik:\n score = (math.log(fik) + 1) * math.log(N / nk)\n return score","title":""},{"docid":"3e070c1ff4e7e37c6f5ae785447991c2","score":"0.535267","text":"def doc2model_smooth(doc, smooth_term, vocab):\n counts = Counter(doc)\n for term in vocab:\n counts[term] = (counts[term] + smooth_term) / (1. * len(doc) + smooth_term * len(vocab))\n return counts","title":""},{"docid":"69e41f15588c3dceb4502fca53f5500b","score":"0.53482276","text":"def counter_word_in_me(self,word):\n\t\treturn self.words[word].docnum_in_cate if word in self.words else 0","title":""},{"docid":"a371a8dcba9da1b11f25725cff0eb0be","score":"0.5338591","text":"def tfidf_log(term: str, document: dict, documents: list):\n tf = log_term_frequency(term, document)\n idf = inverse_document_frequency(term, documents)\n\n return tf*idf","title":""},{"docid":"2cf82a638cdd1f64e903613e3db423ef","score":"0.5337314","text":"def doc2model(doc):\n counts = Counter(doc)\n for term in counts:\n counts[term] /= 1. * len(doc)\n return counts","title":""},{"docid":"820934a2cf823a1271098eaf9e30e34c","score":"0.53371984","text":"def __calculate_rf(self, idsoal, tf:int, term:str, skor_huruf:str):\n pos = self.__docnum_repository.\\\n get_doc_num_pos_class(idsoal, term, skor_huruf)\n neg = self.__docnum_repository.\\\n get_doc_num_neg_class(idsoal, term, skor_huruf)\n \n rf = log(2 + (pos / max(1, neg)), 10)\n\n return rf","title":""},{"docid":"cac6104b53477adb1a1fcc35ab444886","score":"0.5333681","text":"def idf(corpus):\n n_docs = len(corpus)\n idf_dict = dict.fromkeys(corpus[0].keys(), 0)\n\n for bag_word in corpus:\n for word, count in bag_word.items():\n if count > 0:\n idf_dict[word] += 1\n\n for word, count in idf_dict.items():\n if count > 0:\n idf_dict[word] = math.log(n_docs / float(count))\n else:\n idf_dict[word] = 0\n\n return idf_dict","title":""},{"docid":"d81f03eac0b1b599273080979e0cf423","score":"0.53275126","text":"def score_one(self, sd):\r\n # Q.count(t) * tfn / (tfn + c) * log_2((N+1)/(C.count(t)+0.5) where tfn = D.count(t)*log_2(1 + avgdl/len(D))\r\n # print(\"avg_dl: {}\".format(sd.avg_dl))\r\n # print(\"num_docs: {}\".format(sd.num_docs))\r\n # print(\"total_terms: {}\".format(sd.total_terms))\r\n # print(\"query_length: {}\".format(sd.query_length))\r\n # print(\"t_id: {}\".format(sd.t_id))\r\n # print(\"query_term_weight: {}\".format(sd.query_term_weight))\r\n # print(\"doc_count: {}\".format(sd.doc_count))\r\n # print(\"corpus_term_count: {}\".format(sd.corpus_term_count))\r\n # print(\"d_id: {}\".format(sd.d_id))\r\n # print(\"doc_term_count: {}\".format(sd.doc_term_count))\r\n # print(\"doc_size: {}\".format(sd.doc_size))\r\n # print(\"doc_unique_terms: {}\".format(sd.doc_unique_terms))\r\n # print(\"================================================================================\")\r\n #return (self.param + sd.doc_term_count) / (self.param * sd.doc_unique_terms + sd.doc_size)\r\n\r\n c = self.param\r\n N = sd.num_docs\r\n tfn = sd.doc_term_count*math.log2(1 + sd.avg_dl/sd.doc_size)\r\n return sd.query_term_weight * tfn / (tfn + c) * math.log2((N+1)/(sd.corpus_term_count+0.5))","title":""},{"docid":"d7d59a4ed6f580e24b52ff90a9b44597","score":"0.53198946","text":"def count_tfidf(self):\n\t\tif 'all_docs_num' not in dir(self):\n\t\t\tprint 'just set all_docs_num to class attr firstly'\n\t\t\treturn\n\t\tdocsvector={}\n\t\tsave_idf={}\n\t\tfor doc_id in self.docs:\n\t\t\tdocsvector[doc_id]=[]\n\t\t\tfor word in sorted(self.feature):\n\t\t\t\ttf=0 \n\t\t\t\tif (doc_id in self.words[word].rf) and (self.words_count[doc_id]): \n\t\t\t\t\ttf=self.words[word].rf[doc_id]\n\t\t\t\t\ttf/=self.words_count[doc_id]\n\t\t\t\tdf=self.words[word].docnum_in_cate+self.words[word].docnum_in_others\n\t\t\t\tidf=math.log(self.all_docs_num/df,10.0)\n\t\t\t\tsave_idf[word]=idf\n\t\t\t\ttfidf=tf*idf\n\t\t\t\tdocsvector[doc_id].append(tfidf)\n\t\treturn docsvector,save_idf","title":""},{"docid":"1eed69c4d18982f8247bcdec249b4e8c","score":"0.5296557","text":"def get_term_dist(docs, word2id, lowercase=True):\n term_dist = np.zeros(len(word2id))\n for doc in docs:\n for word in doc:\n if lowercase:\n word = word.lower()\n if word in word2id:\n term_dist[word2id[word]] += 1\n\n # normalize absolute freqs to obtain a relative frequency term distribution\n term_dist /= np.sum(term_dist)\n if np.isnan(np.sum(term_dist)):\n # the sum is nan if docs only contains one document and that document\n # has no words in the vocabulary\n term_dist = np.zeros(len(word2id))\n return term_dist","title":""},{"docid":"b8a569f30568615c5fa8011ae0688fce","score":"0.5287967","text":"def compute_idfs(documents):\n total_docs = len(documents.keys())\n # getting all the unique words in documents\n words = set([word for docs in documents.values() for word in docs])\n # getting idf for words using formula\n idf = {}\n for word in words:\n doc_count = 0\n for docs in documents:\n if word in documents[docs]:\n doc_count += 1\n idf[word] = math.log(total_docs / doc_count)\n return idf","title":""},{"docid":"ebe8071083d9135be0914d01378b3339","score":"0.52826416","text":"def compute_normalized_idf(corpus):\n d = {}\n for document in tqdm(corpus):\n words_document = []\n try:\n for p in sent_tokenize(document):\n words_document.append(tokenize(p, [lower]))\n except TypeError:\n continue\n words_document = list(itertools.chain(*words_document))\n for w in words_document:\n d[w] = d[w]+1 if w in d else 1\n N = len(d.keys())\n return {w: math.log(N/d[w])/math.log(N) for w in d.keys()}","title":""},{"docid":"f3759567f7256a52e33b99527ca8d298","score":"0.52685946","text":"def __calculate_ntf(self, idsoal, tf:int, term:str):\n max_tf = self.__ntfrf_repository.get_max_tf(idsoal, term)\n \n #if max_tf == 0: Tidak Mungkin MAX_TF 0 Jika ada TF\n # max_tf = 1\n\n ntf = tf / max(1, max_tf)\n return ntf","title":""},{"docid":"19b3056c8b9250060a8d80506a6c52ea","score":"0.52613556","text":"def key_func(G):\n n, d = G\n return d[\"computed importance factor\"]","title":""},{"docid":"2daecb6f39e5c4768954801a50777d94","score":"0.52583647","text":"def inverse_document_frequency(term: str, documents: list):\n number_of_documents = len(documents)\n df = document_frequency(term, documents)\n\n return log(number_of_documents) - log(df)","title":""},{"docid":"c373ee7fee612107a1904343b223938b","score":"0.52519584","text":"def compute_idfs(documents):\n words = []\n for filename in documents:\n words = words + documents[filename]\n wordList = set(words)\n\n wordIDF = dict()\n nDoc = len(documents)\n for word in wordList:\n nAppear = 0\n for filename in documents:\n if word in documents[filename]:\n nAppear += 1\n wordIDF[word] = math.log(nDoc/nAppear)\n\n return wordIDF\n\n\n\n\n #raise NotImplementedError","title":""},{"docid":"2773022acfe1beb00e4e81e0a0645d19","score":"0.5249381","text":"def get_tfidf_scores(self, query):\n length = {}\n scores = {}\n for id in self.ids:\n length[id] = 0\n scores[id] = 0\n\n for term in re.findall(r\"[\\w']+|[.,!?;]\", query.strip()):\n term = term.lower()\n if not term in self.document_frequencies:\n continue\n df = self.document_frequencies[term]\n wq = np.log(self.num_documents/df)\n for id in self.ids:\n document_dict = self.term_frequencies[id]\n if not term in document_dict:\n scores[id] += 0\n continue\n tf = document_dict[term]\n length[id] += tf**2\n wd = 1 + np.log(tf)\n scores[id] += wq * wd\n for id in self.ids:\n if length[id] == 0:\n continue\n scores[id] /= np.sqrt(length[id])\n\n return scores","title":""},{"docid":"a94c659133dd8c21e8fcc8548626d3d1","score":"0.5240084","text":"def jelinek_mercer(self, query_term, doc):\n # Frequency of term in the document (document term frequency - dtf)\n fqiD = doc.get_dtf()\n # Length of the document\n dl = self.inverted_index.get_doc_length(doc.get_doc_id())\n # Frequency of term in the collection (collection term frequency - ctf)\n cqi = self.inverted_index.get_ctf(query_term)\n # Total length of all documents in the collection\n cl = self.inverted_index.get_collection_length()\n \n score = math.log(((1 - self.alphaD) * (fqiD / dl)) + (self.alphaD * (cqi / cl)))\n return score * self.query_terms.count(query_term)","title":""},{"docid":"d636d28f74a111a6cb997e74b2e845f6","score":"0.5229651","text":"def no_of_documents_containing_a_word(self, query_word):\n if PROXIMITY.useCache:\n if query_word in BM25.no_of_docs_dict:\n return float(BM25.no_of_docs_dict[query_word])\n else:\n return 0\n else:\n if query_word in self.cache:\n return float(self.cache[query_word])\n else:\n no_of_documents_having_the_word = 0\n for para_id, ranked_word_dict in self.documents.items():\n if query_word in ranked_word_dict:\n no_of_documents_having_the_word += 1\n self.cache[query_word] = no_of_documents_having_the_word\n return float(no_of_documents_having_the_word)","title":""},{"docid":"7168c69387fc787c36783669e23c67e5","score":"0.52270603","text":"def score(self, word, context):\n context = self.check_context(context)\n context_freqdist = self.ngrams[context]\n word_count = context_freqdist[word]\n context_count = context_freqdist.N()\n return (word_count + self.k) / \\\n (context_count + self.k_norm)","title":""},{"docid":"21c5f8d2b68defa13eee488472bae88e","score":"0.52200663","text":"def compute_sentiment_for_tweet(tweet):\n text = polyglot.text.Text(tweet.lower(), hint_language_code='it')\n scores = [word.polarity for word in text.words if word.polarity != 0]\n return np.mean(scores) if scores else 0.0","title":""},{"docid":"9d3401958a69e735567a05ff09171f57","score":"0.5212027","text":"def tf_idf(self, corpus):\n top200list = [(word, count) for count, word in corpus.top200]\n\n \n if corpus.type == \"subject\":\n word_count = self.subject_word_count\n else: \n word_count = self.body_word_count\n \n self.tf_idf_scorelist = []\n # print word_count\n for word, document_frequency in top200list:\n if word not in word_count:\n # If word does not appear in the message, tf-idf == 0\n self.tf_idf_scorelist.append([word, 0])\n else:\n # calculate the tf-idf score for the word, appending the pair (word, score) to the list\n tf_idf_score = word_count[word] * math.log10(corpus.length / float(document_frequency)) + 1.0/200\n self.tf_idf_scorelist.append([word, tf_idf_score])\n \n \n return self.tf_idf_scorelist","title":""},{"docid":"23a54153fbba0f89e126596ded64aa86","score":"0.52037126","text":"def number_doc(self, document: list):\n #doc = [0] * self.item_number()\n for i in range(len(document)):\n if document[i] > 0:\n self.term_indoc[i] += 1\n #print(i, document[i])\n # return doc","title":""},{"docid":"9527f60633735d3c6f56447d6af3074f","score":"0.5198056","text":"def compute_idfs(documents):\n idfs = dict()\n\n for document in documents:\n already_added = set()\n for word in documents[document]:\n if word not in idfs:\n idfs[word] = 1\n already_added.add(word)\n elif word not in already_added:\n idfs[word] += 1\n already_added.add(word)\n\n for word in idfs:\n idfs[word] = np.log( len(documents) / idfs[word] )\n\n return idfs","title":""},{"docid":"a5bc4a76ecf34dc9cbcdb3d03acb7767","score":"0.51957184","text":"def _getCountForUnigram(self,word1):\n count=self.unigrams[(word1)]\n if count==0:\n count=0.001\n return count","title":""},{"docid":"c15339eabb1d35644cd35efdac9d13e4","score":"0.51779836","text":"def findfreq(word):\n\n\tif word in mostcommon:\n\t\treturn mostcommon[word]\n\telse:\n\t\treturn 0","title":""},{"docid":"e69067a5caacec71a03278ae8b987ae2","score":"0.5170481","text":"def idf(inverted_index: List, token: str, collection_size: int) -> float:\n term_frequence = len(inverted_index.get(token, []))\n if term_frequence is 0:\n return 0\n return math.log((collection_size+1) / term_frequence)","title":""},{"docid":"e4aef0991b20ecb512b79c568277d6d9","score":"0.51683074","text":"def calcidf(df):\n docamount = df[1] - 1 # subtract\n docfreq = df[0]\n idf = dict() # create a new dictionary\n for term in docfreq: # for every entry in the df, calculate the idf\n frequency = docfreq.get(term)\n multiplication = docamount / frequency\n answer = mth.log2(multiplication)\n idf[term] = answer # save the idf in the dictionary for the current term\n return idf","title":""},{"docid":"85b13c002cf9b0a943e30e0b203bbe07","score":"0.5163134","text":"def get_emmision(self, word, tag):\n if tag in ['*', 'STOP']:\n return 0.0\n new_word = self.replace_word(word)\n return self.word.get((tag, new_word), 0.0) / self.ngrams[1][tag]","title":""},{"docid":"1f4716e3a6d2b4253747ce5bde849769","score":"0.5157731","text":"def tfidf_search(query, index_set):\n index = get_index(index_set) # [token] -> [(doc_id, token_count)]\n df = get_df(index_set) # {token: doc_freq}\n processed_query = preprocess_query(query, index_set)\n # YOUR CODE HERE\n\n # Normalize index?\n relevant_documents = []\n total_documents = 3204 # Dynamicly?\n \n for word in processed_query:\n for term_frequencies in index[word]:\n doc_id = term_frequencies[1]\n tf = term_frequencies[1]\n idf = math.log(total_documents/df[word]) # IDF = log(total_documents/df)\n tf_idf = tf*idf\n if not any([e[0] == doc_id for e in relevant_documents]) : # Document not encountered before\n relevant_documents.append([doc_id, tf_idf])\n else: # Document encountered. Add tf-idf score to previous score\n for document in relevant_documents:\n if document[0] == doc_id:\n document[1] += tf_idf\n break\n # Sort in descending order according to score\n relevant_documents = sorted(relevant_documents,key=lambda x: (x[1]))\n return relevant_documents","title":""},{"docid":"62ef62e74acd25ee51d17ae5271bb00d","score":"0.5125886","text":"def idf(self, book_num, token):\n return np.log((self.sentence_id + 1) / (self.df(book_num, token) + 1))","title":""},{"docid":"8310f28fea6a5c72c7ee004854250751","score":"0.51238996","text":"def tf_idf_score(tokens):\n for token in tokens.keys():\n df = len(tokens[token])\n idf = math.log(TOTAL_UNIQUE_DOC/df)\n for posting in tokens[token]:\n tf = posting[1]\n tf_idf = (1 + math.log(tf)) * idf\n posting[1] = tf_idf\n \n return tokens","title":""},{"docid":"183d68bf522d93cf0b91a779d2ef0570","score":"0.51199824","text":"def compute_idfs(documents):\n idfs = {} # Initialise a dictionary of idfs\n for doc in documents:\n for word in documents[doc]:\n if word in idfs: # Word already calculated\n continue\n word_occurences = 1\n for doc2 in documents:\n if doc2 == doc: # Skip word iteration we are looking at\n continue\n if word in documents[doc2]:\n word_occurences += 1\n idfs[word] = math.log(len(documents) / word_occurences)\n return idfs","title":""}],"string":"[\n {\n \"docid\": \"1ab6cc16ab1cfd758823ca6ce6adb0c8\",\n \"score\": \"0.73194516\",\n \"text\": \"def get_tfidf_scores(self, term, document):\\n if term in self.tf[document]:\\n return self.tf[document][term] * self.idf[term]\\n else:\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a5322e56d406d8222b4591b5dc78afe3\",\n \"score\": \"0.7267702\",\n \"text\": \"def imp(self, term, id):\\n if id in self.frequency[term]:\\n return self.frequency[term][id] * self.inverse_document_frequency(term)\\n else:\\n return 0.0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4c2be31df7ae39a53804ef7839af5709\",\n \"score\": \"0.7203408\",\n \"text\": \"def compute_term_frequency_in_collection(self, term, id_document):\\n try:\\n tf = self.inverted_index[term][id_document]\\n return tf\\n except KeyError:\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b76922a897681b8201269db22bb15b46\",\n \"score\": \"0.6974998\",\n \"text\": \"def get_idf(self, term):\\n if term in self.stopwords:\\n return 0\\n\\n if not term in self.term_num_docs:\\n return self.idf_default\\n\\n return math.log(float(1 + self.get_num_docs()) / \\n (1 + self.term_num_docs[term]))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b7e2d4947a28623fa72af23a6fe53cb3\",\n \"score\": \"0.6677582\",\n \"text\": \"def idf(self, word, corpus):\\r\\n\\r\\n idf = self.doc_freq(word, corpus)\\r\\n if idf == 0: \\r\\n return 0\\r\\n return np.log10(len(corpus)/(idf))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b9723043fe5e9c564378843a21b06a95\",\n \"score\": \"0.66243446\",\n \"text\": \"def compute_idf(self, term):\\n try:\\n # thanks to the inverted index, we have access to all the documents containing the term\\n docs = self.inverted_index[term].keys()\\n df = len(docs)\\n except KeyError:\\n return 0\\n return log(self.number_of_docs / df)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9f263d50d42b747d120513716838d8f5\",\n \"score\": \"0.6587332\",\n \"text\": \"def term_frequency(term: str, document: dict):\\n if term not in document:\\n return 0\\n\\n number_of_occurences = document[term]\\n total_number_of_occurences = sum(document.values())\\n\\n return number_of_occurences / total_number_of_occurences\",\n \"title\": \"\"\n },\n {\n \"docid\": \"de89ea5fb8b03ae122b942e3b87a2ce8\",\n \"score\": \"0.6554476\",\n \"text\": \"def term_freq(self, word, document):\\r\\n\\r\\n if word in document.word_freq:\\r\\n return (1+np.log10(document.word_freq[word]))\\r\\n else:\\r\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6f78c0da6db0011ccd8bc003de211461\",\n \"score\": \"0.65498453\",\n \"text\": \"def get_words_importance(self, doc_word_dict : dict, id : int) -> list:\\n word_list = doc_word_dict[id]\\n word_importance = {}\\n for word in word_list:\\n word_importance[word] = log(len(doc_word_dict) / self.get_docs_for_word(word, doc_word_dict))\\n return word_importance\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2592e943c06bd2a5be5a849cd218affd\",\n \"score\": \"0.6462634\",\n \"text\": \"def __term_frequency(term, document, query=False):\\n\\tif query:\\n\\t\\treturn query_vector[term]\\n\\tif document not in inverted_index[term].keys():\\n\\t\\treturn 0\\n\\treturn inverted_index[term][document]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5624abaeb1c7b984a84d204a831f4bf7\",\n \"score\": \"0.6405168\",\n \"text\": \"def __document_frequency(term):\\n\\treturn len(inverted_index[term])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1af3094b55566ff878786ae2ba3cfef4\",\n \"score\": \"0.6375153\",\n \"text\": \"def term_frequency(self, term):\\n term = re.sub(r'\\\\W+', '', term).lower()\\n if term not in self._word_to_count.keys():\\n return 0\\n else:\\n return self._word_to_count[term] / self._word_count\",\n \"title\": \"\"\n },\n {\n \"docid\": \"586f3fd4626f8420c9d0804104d99fe8\",\n \"score\": \"0.6220984\",\n \"text\": \"def __get_idf(self, token):\\n df = self.dictionary.dfs.get(token, 0)\\n if df == 0:\\n return 0\\n else:\\n return math.log(len(self.dictionary.doc_ids)/df, 10)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9d194912cafdb6ae92cd5cba74d04f45\",\n \"score\": \"0.6220814\",\n \"text\": \"def idf(self, searcher, fieldname, text):\\r\\n\\r\\n parent = searcher.get_parent()\\r\\n n = parent.doc_frequency(fieldname, text)\\r\\n dc = parent.doc_count_all()\\r\\n return log(dc / (n + 1)) + 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1b0032c32dcc640f5a00002fa4d914d5\",\n \"score\": \"0.62125367\",\n \"text\": \"def __log_term_frequency(term, document, query=False):\\n\\tif __term_frequency(term, document, query) > 0:\\n\\t\\treturn 1 + math.log(__term_frequency(term, document, query))\\n\\treturn 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2a85052c0c58a437b40768cbb5100e80\",\n \"score\": \"0.6199197\",\n \"text\": \"def idf(self, term):\\n return self.get_cache('idf', term,\\n lambda: math.log(len(self.DOCVECS)/self.df(term)))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0c492b24c60f3b8398f35b0d81affcd1\",\n \"score\": \"0.61888534\",\n \"text\": \"def compute_tf(document, term, type='raw'):\\n assert (type in ['raw', 'augmented', 'boolean']), \\\"The parameter 'type' is not recognized. Please enter 'raw', 'boolean' or 'augmented' as it's value.\\\"\\n tf = 0.0\\n if type == 'raw':\\n tf = float(document.count(term))\\n if type == 'boolean':\\n tf = float(term in document)\\n if type == 'augmented':\\n tf = 0.5 + ((0.5 * float(document.count(term))) / float(max([document.count(x) for x in document])))\\n return tf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b97c9c31f33cf2a704478804d66a14f4\",\n \"score\": \"0.6161808\",\n \"text\": \"def compute_tf_idf(self, term, id_document):\\n tf_idf = self.log_normalization(term, id_document) * self.compute_idf(term)\\n return tf_idf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d4c6248e2039be9f502ed22fd972928f\",\n \"score\": \"0.6156177\",\n \"text\": \"def term_frequency(word, document):\\n return document.count(word) / len(document.split(\\\" \\\"))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c59e803d24c0ef0882023c997952f41c\",\n \"score\": \"0.61420256\",\n \"text\": \"def word_frequency_of_word_in_document(self, word, document_id):\\n if word in self.documents[document_id]:\\n return self.documents[document_id][word]\\n else:\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1a2e701a6e91e0f7f264f8bcdec5f1d3\",\n \"score\": \"0.61271435\",\n \"text\": \"def inverse_document_frequency(term):\\r\\n if term in dictionary:\\r\\n return math.log(N/document_frequency[term],2)\\r\\n else:\\r\\n return 0.0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"caad6749524bf8c38cfc72d0be5a5d29\",\n \"score\": \"0.6126351\",\n \"text\": \"def get_score(self, query_term, doc):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ee0fd5091e801e91faf085ff3631d573\",\n \"score\": \"0.60995793\",\n \"text\": \"def tf_idf(self, word, document, corpus):\\r\\n\\r\\n return self.term_freq(word, document)*self.idf(word, corpus)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b30f2746bf96644b686cd8a0c474e32c\",\n \"score\": \"0.60398054\",\n \"text\": \"def _idf(self, word, counter):\\n try:\\n return self._log_freqlist_total - math.log(self._freqlist[word])\\n except ValueError:\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f34b4ae22c6e331f006af3bf546b094f\",\n \"score\": \"0.60377926\",\n \"text\": \"def log_term_frequency(term: str, document: dict):\\n return 1 + log(term_frequency(term, document))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3b0f3e4494c5f04a6345e54d9f80d450\",\n \"score\": \"0.6011292\",\n \"text\": \"def tfidfScore(tf, numdocs, numtermincorp):\\n return tf * log(numdocs / (1 + numtermincorp))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fe9e99d67c716bf19c7ea992f94627d4\",\n \"score\": \"0.60076827\",\n \"text\": \"def _get_term_freq(self, doc):\\n tf_dict = {}\\n for token in doc:\\n if token in tf_dict:\\n tf_dict[token] += 1\\n else:\\n tf_dict[token] = 1\\n for token in tf_dict:\\n tf_dict[token] = tf_dict[token] / len(doc)\\n return tf_dict\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e3ad043b895baa11dfdb2ca1c73d7b55\",\n \"score\": \"0.5957657\",\n \"text\": \"def getTF(self,word):\\r\\n return float(self.getCountOf(word))/float(self.getWordCount())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f2a62be0f3d9539a0a1a0f2b0076ce78\",\n \"score\": \"0.59250844\",\n \"text\": \"def inverse_document_frequency(self, term):\\n\\n if term in self.dictionary:\\n return math.log(self.N / len(self.index.get_postings(term)), 2)\\n return 0.0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"91d88c4128cdaa7dd51d20b795f8deda\",\n \"score\": \"0.5862421\",\n \"text\": \"def get_tfidf_score(self, input_term, all_terms, unique_terms):\\n if unique_terms.size==0: \\n log_print(\\\"No terms found for the input term {}\\\".format(input_term))\\n return None\\n\\n total = 1855658.0\\n tf = Counter(item for sublist in all_terms for item in sublist)\\n\\n path_to_nyt_idf = os.path.dirname(os.path.realpath(__file__))\\n with open(os.path.join(path_to_nyt_idf, 'nyt_idf_nonstem.json'), 'r') as fp:\\n idf = json.load(fp)\\n score = np.array([tf[term]*np.log(total/idf[term]) for term in unique_terms])\\n tf_idf = dict(zip(unique_terms, score/max(score)))\\n return tf_idf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6149e125de392f1ba023640ab7d3d0ef\",\n \"score\": \"0.5833293\",\n \"text\": \"def __boolean_term_frequency(term, document, query=False):\\n\\tif __term_frequency(term, document, query) > 0:\\n\\t\\treturn 1\\n\\treturn 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1770af3b106b3a4008e60f156566787d\",\n \"score\": \"0.5805489\",\n \"text\": \"def idf(word, stats):\\n return math.log(stats.N() / stats[word]) if word in stats else 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"348fade58f793fcb812eda46cec34be5\",\n \"score\": \"0.5763374\",\n \"text\": \"def term_frequency(word, word_frequency):\\n\\n return 0 if word_frequency[word] == 0 else 1 + log(word_frequency[word])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4e09b728ce54fcee100f2eb375d705b2\",\n \"score\": \"0.57567257\",\n \"text\": \"def document_frequency(term: str, documents: list):\\n documents_with_term = [doc for doc in documents if term_frequency(term, doc) > 0];\\n\\n return len(documents_with_term)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"eaab51e438bd8e4fbbe7b389c6d5f2a2\",\n \"score\": \"0.5746729\",\n \"text\": \"def get_score(self, query_term, doc):\\n return self.__getattribute__(self.retrieval_model)(query_term, doc)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3669da697e4141eaa0ca4cfc0d1da637\",\n \"score\": \"0.5736835\",\n \"text\": \"def __inverted_documnent_frequency(term):\\n\\treturn math.log(movies['num_of_movies'] / __document_frequency(term))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8488e0b73a112efdc34bb77803e4cd73\",\n \"score\": \"0.57291937\",\n \"text\": \"def raw_counts(self, query_term, doc):\\n return doc.get_dtf() * self.query_terms.count(query_term)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"35dd44506bbd01bdfd5144dcfc628d6f\",\n \"score\": \"0.5728637\",\n \"text\": \"def tfidf(term: str, document: dict, documents: list):\\n tf = term_frequency(term, document)\\n idf = inverse_document_frequency(term, documents)\\n\\n return tf*idf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bf3ef435509aecb9fd5e9d4ae192029e\",\n \"score\": \"0.5718501\",\n \"text\": \"def __score(term, document, scoring_scheme, query):\\n\\tterm_frequency_type = scoring_scheme\\n\\tif term_frequency_type == \\\"n\\\":\\n\\t\\tterm_frequency = __term_frequency(term, document, query)\\n\\telif term_frequency_type == \\\"l\\\":\\n\\t\\tterm_frequency = __log_term_frequency(term, document, query)\\n\\telif term_frequency_type == \\\"a\\\":\\n\\t\\tterm_frequency = __augmented_term_frequency(term, document, query)\\n\\telif term_frequency_type == \\\"b\\\":\\n\\t\\tterm_frequency = __boolean_term_frequency(term, document, query)\\n\\n\\treturn term_frequency * __inverted_documnent_frequency(term)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a17c89b352252ff33a9369b37f677cbf\",\n \"score\": \"0.5707244\",\n \"text\": \"def score_one(self, sd):\\r\\n return (self.param + sd.doc_term_count) / (self.param * sd.doc_unique_terms + sd.doc_size)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c7592a95c1fb70a21065a5a2edc740ae\",\n \"score\": \"0.567741\",\n \"text\": \"def compute_idfs(self, word_dict):\\r\\n\\t\\tprint('computing IDF scores for words within corpus')\\r\\n\\t\\t# obtain document frequencies\\r\\n\\t\\tdfreqs = dict(word_dict.dfs)\\r\\n\\t\\t# return IDF scores\\r\\n\\t\\treturn {word_dict[idx]: np.log(word_dict.num_docs / (1 + float(dfreq))) for idx, dfreq in dfreqs.items()}\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7719a1d51402e4e84c1237245f16469b\",\n \"score\": \"0.5644053\",\n \"text\": \"def inverse_document_frequency(self, query_word):\\n no_qi = self.no_of_documents_containing_a_word(query_word)\\n return float(math.log(self.no_of_documents / (no_qi + 1.0)))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b19b542d025bfce2d3cad706005e27cd\",\n \"score\": \"0.5636606\",\n \"text\": \"def idfTerm(term, searcher):\\n\\n return idf(searcher.docFreq(term), searcher.maxDoc())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f7c433f0945151873995a277b2b1067d\",\n \"score\": \"0.5621689\",\n \"text\": \"def getFreq(self,text, word_type=''):\\n\\t\\tidList=[];\\n\\t\\t#if araby.isHaraka(text[-1:]): text=text[:-1];\\n\\t\\tidList=self.lookup(text,word_type);\\n\\t\\t# if there are many take the first\\n\\t\\tif idList:\\n\\t\\t\\treturn self.getAttribById(idList[0], u'freq')\\n\\t\\telse: \\n\\t\\t\\treturn 0;\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8d3029bbba9b9d700bd4a2f62d1ff631\",\n \"score\": \"0.56136155\",\n \"text\": \"def idf(word, word_list):\\n N = len(word_list)\\n num_documents_containing_word = len([True for document in word_list if word in document])\\n return math.log(N / num_documents_containing_word + 1) # + 1 accounts for if the word doesn't occur in any of the documents\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fc1ea5739249359c1f3a68edeb9bdc16\",\n \"score\": \"0.5594896\",\n \"text\": \"def importance(self) -> int:\\n return self._importance\",\n \"title\": \"\"\n },\n {\n \"docid\": \"45e9e1b76288883f663c61924147090f\",\n \"score\": \"0.55904835\",\n \"text\": \"def __augmented_term_frequency(term, document, query=False):\\n\\tmax_term_frequency = -1\\n\\tfor t in inverted_index.keys():\\n\\t\\tmax_term_frequency = max(max_term_frequency, __term_frequency(t, document, query))\\n\\treturn 0.5 + 0.5 * ( __term_frequency(term, document, query) / max_term_frequency )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3999b27040b7591d54a2714c1c96589d\",\n \"score\": \"0.55884415\",\n \"text\": \"def calc_tfidf_similarity(doc1: Counter, doc2: Counter, idf:\\n Dict[Text, float]):\\n tf1_max = max(doc1.values())\\n tf2_max = max(doc2.values())\\n total_sum = 0.0\\n for word, tf1 in doc1.items():\\n tf2 = doc2[word]\\n if tf2 == 0 or word not in idf:\\n continue\\n tf1_norm = (0.5+0.5*float(tf1)/tf1_max)\\n tf2_norm = (0.5+0.5*float(tf2)/tf2_max)\\n idf_val = idf[word]\\n total_sum += tf1_norm * tf2_norm * (idf_val*idf_val)\\n return math.sqrt(total_sum)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6f5bc01a23ac9affce6c84799cb26171\",\n \"score\": \"0.55526114\",\n \"text\": \"def get_idf(tf_matrix, term_index):\\n\\n # Document Frequency (DF)\\n df = 0\\n for entry in tf_matrix[:, term_index]:\\n if entry > 0:\\n df += 1\\n\\n # print \\\"df = \\\", df\\n # Inverse Document Frequency (IDF)\\n if df:\\n idf = 1.0 + math.log10(float(TOTAL_DOCS) / df)\\n else:\\n idf = 0.0\\n\\n return idf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"59016a1f4e819b2d9a971198ba18fc81\",\n \"score\": \"0.554357\",\n \"text\": \"def similarity(self, query, id):\\n similarity = 0.0\\n for term in query.split(' '):\\n if term in self.dictionary:\\n similarity += self.inverse_document_frequency(term) * self.imp(term, id)\\n\\n if self.length[id] > 0:\\n similarity = similarity / self.length[id]\\n return similarity\",\n \"title\": \"\"\n },\n {\n \"docid\": \"95bda274f1cacdd9e0684d4866897bf0\",\n \"score\": \"0.5534798\",\n \"text\": \"def calculate_document_tf_idf(sentence, paper_bag_of_words):\\n # Sanity check\\n assert(len(paper_bag_of_words) > 0)\\n\\n sentence_bag_of_words = defaultdict(float)\\n for word in sentence:\\n\\n if word in STOPWORDS:\\n continue\\n else:\\n sentence_bag_of_words[word] += 1.0\\n\\n sent_tf_idf = 0\\n length = 0\\n\\n for word in sentence:\\n\\n if word in STOPWORDS:\\n continue\\n\\n tf = sentence_bag_of_words[word]\\n\\n # Add 1 to the denominator to prevent division by 0\\n idf = np.log(len(paper_bag_of_words) / (paper_bag_of_words[word] + 1))\\n\\n tf_idf = tf * idf\\n\\n sent_tf_idf += tf_idf\\n\\n length += 1\\n\\n if length == 0:\\n return 0\\n else:\\n return sent_tf_idf / length\",\n \"title\": \"\"\n },\n {\n \"docid\": \"574154d391ef7cea72fcd34ca925cc22\",\n \"score\": \"0.5512458\",\n \"text\": \"def calculate_tf_idf(sentence, global_count_of_papers_words_occur_in, paper_bag_of_words):\\n bag_of_words = paper_bag_of_words\\n\\n sentence_tf_idf = 0\\n\\n length = 0\\n\\n for word in sentence:\\n\\n if word in STOPWORDS:\\n continue\\n\\n # Get the number of documents containing this word - the idf denominator (1 is added to prevent division by 0)\\n docs_containing_word = global_count_of_papers_words_occur_in[word] + 1\\n\\n # Count of word in this paper - the tf score\\n count_word = bag_of_words[word]\\n\\n idf = np.log(NUMBER_OF_PAPERS / docs_containing_word)\\n\\n #word_tf_idf = (1 + np.log(count_word)) * idf\\n\\n word_tf_idf = count_word * idf\\n\\n sentence_tf_idf += word_tf_idf\\n\\n length += 1\\n\\n if length == 0:\\n return 0\\n else:\\n sentence_tf_idf = sentence_tf_idf / length\\n return sentence_tf_idf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3462723797b792010e0af288e4741b46\",\n \"score\": \"0.5498431\",\n \"text\": \"def dirichlet(self, query_term, doc):\\n # Frequency of term in the document (document term frequency - dtf)\\n fqiD = doc.get_dtf()\\n # Length of the document\\n dl = self.inverted_index.get_doc_length(doc.get_doc_id())\\n # Frequency of term in the collection (collection term frequency - ctf)\\n cqi = self.inverted_index.get_ctf(query_term)\\n # Total length of all documents in the collection\\n cl = self.inverted_index.get_collection_length()\\n \\n score = math.log((fqiD + (self.mu * (cqi / cl))) / (dl + self.mu))\\n return score * self.query_terms.count(query_term)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"53784acbc9786bc475f618db0be4be48\",\n \"score\": \"0.54652566\",\n \"text\": \"def _tf(tokenized_doc):\\n term_tf = {}\\n for term in tokenized_doc:\\n if term not in term_tf:\\n term_tf[term]=1.0\\n else:\\n term_tf[term]+=1.0\\n\\n # pprint(term_tf)\\n return term_tf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3b293b37d790c1975b74936de9cf4842\",\n \"score\": \"0.546485\",\n \"text\": \"def calculate_similarity(corpus, term_corpus):\\n\\n N = corpus.shape[0] # total number of reports\\n term_counter = Counter()\\n\\n for index, value in corpus.items():\\n total_features = value\\n\\n for term in term_corpus:\\n if term in total_features:\\n term_counter[term] += 1\\n\\n similarity = 0\\n # idf = log(num_documents / num_documents_contain_term + 1)\\n for term, term_frequency in term_counter.items():\\n term_IDF = math.log(float(N) / (term_frequency + 1))\\n similarity += term_IDF\\n return similarity\",\n \"title\": \"\"\n },\n {\n \"docid\": \"001734219fdd4482655a970acca37de9\",\n \"score\": \"0.5433262\",\n \"text\": \"def __get_weight_query_term(self, term, term_tf, n):\\n\\n # calculate tf in query\\n # log_tf = 1 + math.log10(term_count)\\n\\n if term in self.dictionary.keys():\\n (freq, postings_line) = self.dictionary[term]\\n # calculate idf\\n idf = math.log10(float(n)/float(freq))\\n return term_tf * idf\\n else:\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"65aac01b64ac0f8b5a171dd749d75a0d\",\n \"score\": \"0.5414591\",\n \"text\": \"def tf(bag_words, doc_dict):\\n tf = {}\\n len_doc = len(doc_dict)\\n\\n for token, count in bag_words.items():\\n if count > 0:\\n tf[token] = count / float(len_doc)\\n else:\\n tf[token] = 0\\n return tf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"13bf35a9296fb0ecdbb8d9561964c3da\",\n \"score\": \"0.5411817\",\n \"text\": \"def doc_frequency(self, fieldid, text):\\r\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e3740a833027b125cf246a422ad7acb1\",\n \"score\": \"0.5398581\",\n \"text\": \"def compute_tfdf_score(cur, user_id, tf_type):\\n score = 0.0\\n # Get timeline_document from user\\n cur.execute(\\\"SELECT timeline_document FROM users WHERE user_id = {};\\\".format(user_id))\\n tl_doc = cur.fetchone()\\n # tl_doc = cur.fetchone()[0]\\n if (tl_doc is None) or (tl_doc[0] is None) or (len(tl_doc[0]) < 1):\\n return score\\n # Iterate over all topics to compute the final score\\n cur.execute(\\\"SELECT topic, document_frequency FROM topics;\\\")\\n for t in cur:\\n # Compute TF\\n tf = compute_tf(document=tl_doc[0], term=t[0], type=tf_type)\\n # Compute TF-IDF\\n score += tf * t[1]\\n return score\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a86dc21dd09b9feebb35225e625b55f0\",\n \"score\": \"0.53949726\",\n \"text\": \"def _get_unigram_count(self, word):\\n c = self.db_conn.cursor()\\n c.execute(\\\"SELECT frequency FROM unigram_count WHERE word = ?\\\",\\n (word,))\\n result = c.fetchone()\\n return float(result[0]) if result else 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a6cfcf155e9aaaf81074af691498c62e\",\n \"score\": \"0.5393289\",\n \"text\": \"def doc_freq(self, word, corpus):\\r\\n\\r\\n # finding doc_freq using len(posting list) from inverted index(if present)\\r\\n if len(self.inv_index)>0:\\r\\n return len(self.inv_index[word])\\r\\n\\r\\n count = 0\\r\\n for doc in corpus:\\r\\n if word in doc.word_freq:\\r\\n count += 1\\r\\n return count\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0217b748cfb19226bb42bf3b93a85b88\",\n \"score\": \"0.5378008\",\n \"text\": \"def get_docs_for_word(self, word : str, doc_word_dict : dict) -> float:\\n n_docs = len(doc_word_dict)\\n n_docs_containing_word = 0\\n for doc in doc_word_dict:\\n if word in doc_word_dict[doc]:\\n n_docs_containing_word = n_docs_containing_word + 1\\n if n_docs_containing_word == 0:\\n print(\\\"Safety check. Ideally it shouldn't enter this if condition\\\")\\n return 1\\n return n_docs_containing_word\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4c1c7fd7fee301ff306fc66b83ebeba3\",\n \"score\": \"0.5369192\",\n \"text\": \"def get_score(self, word):\\n retval = 0.0\\n # calculate score if dictionaries are present\\n if self.wdict != None and self.tdict != None:\\n w = self.wdict.count(word)\\n if w != 0:\\n retval = self.tdict.count(word) * 1.0 / w\\n return retval\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c6a7c90b47326363418dda94fa0ff68c\",\n \"score\": \"0.5367672\",\n \"text\": \"def raw_counts(self, query_term, doc):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c1077a1ca0ed251d0f9937fbbd034a32\",\n \"score\": \"0.5360859\",\n \"text\": \"def scalar_inc_dec(word, valence, words_and_emoticons):\\n previous_word = ' '\\n next_word = ' '\\n scalar = 0.0\\n\\n if word in BOOSTER_DICT:\\n\\n scalar = BOOSTER_DICT[word]\\n if valence < 0:\\n scalar *= -1\\n\\n return scalar\",\n \"title\": \"\"\n },\n {\n \"docid\": \"983413b0753de4f66dc6030c1158be4e\",\n \"score\": \"0.5358795\",\n \"text\": \"def count_bag(self, tweet, use_first_tf_doc):\\n\\n count = 0.0\\n sanitised_tweet_text = tweet['text'] # OSX\\n #sanitised_tweet_text = tweet.text # Windows\\n hashtag = False\\n term_frequency_document = self.termfreq_doc if use_first_tf_doc else self.second_net_termfreq_doc\\n count += self.get_author_sentiment(tweet)\\n\\n\\n # The following loop first checks if the word in the tweet\\n # is a hastag, setting the hashtag boolean to true if it is.\\n # Then, a check is used to see if the term is in the term\\n # frequency document. If it is, then add the value of that\\n # term (plus 1) to the count, multiplying it by the hash_tag_multiplier \\n # variable if the term is a hashtag. Then subtract the number returned\\n # by the get_tweet_age_score function for that tweet, and finally\\n # return the resulting count. If the count is below zero, return it\\n # to zero.\\n\\n\\n for word in sanitised_tweet_text.split():\\n if word[0] == \\\"#\\\":\\n text_word = word.lower().replace(\\\"#\\\", \\\"\\\")\\n hashtag = True\\n else:\\n text_word = word.lower()\\n if term_frequency_document.has_key(text_word):\\n #if text_word in term_frequency_document.keys():\\n count += 1\\n if hashtag == True:\\n if self.termfreq_doc.get(text_word) is not None:\\n count += (self.termfreq_doc.get(text_word) * self.hash_tag_multiplier)\\n hashtag = False\\n else:\\n if self.termfreq_doc.get(text_word) is not None:\\n count += self.termfreq_doc.get(text_word)\\n \\n count -= self.get_tweet_age_score(tweet)\\n if count <= 0.0:\\n count = 0.0 \\n print(count)\\n return count\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ded23487a7ce3d39c1e6f9d0e94b2091\",\n \"score\": \"0.53567445\",\n \"text\": \"def rarity(self, word):\\r\\n if not isinstance(word, str):\\r\\n raise TypeError(\\\"Word given must be a string\\\")\\r\\n\\r\\n try:\\r\\n occurrence = self.word_frequency[word]\\r\\n except KeyError: # misspelling or missing word\\r\\n return 3\\r\\n\\r\\n if self.max/100 <= occurrence: # common\\r\\n return 0\\r\\n elif self.max/1000 <= occurrence < self.max/100: # uncommon\\r\\n return 1\\r\\n elif 0 < occurrence < self.max/1000: # rare\\r\\n return 2\",\n \"title\": \"\"\n },\n {\n \"docid\": \"048e6c7db7c4d184c0e8378dbaccd291\",\n \"score\": \"0.5353218\",\n \"text\": \"def vector_space(self, query_term, doc):\\n # Frequency of term in the document (document term frequency - dtf)\\n fik = doc.get_dtf()\\n # Number of documents in the collection\\n N = self.inverted_index.get_total_docs()\\n # Number of documents containing the term (document frequency - df)\\n nk = self.inverted_index.get_df(query_term)\\n \\n score = 0\\n if fik:\\n score = (math.log(fik) + 1) * math.log(N / nk)\\n return score\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3e070c1ff4e7e37c6f5ae785447991c2\",\n \"score\": \"0.535267\",\n \"text\": \"def doc2model_smooth(doc, smooth_term, vocab):\\n counts = Counter(doc)\\n for term in vocab:\\n counts[term] = (counts[term] + smooth_term) / (1. * len(doc) + smooth_term * len(vocab))\\n return counts\",\n \"title\": \"\"\n },\n {\n \"docid\": \"69e41f15588c3dceb4502fca53f5500b\",\n \"score\": \"0.53482276\",\n \"text\": \"def counter_word_in_me(self,word):\\n\\t\\treturn self.words[word].docnum_in_cate if word in self.words else 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a371a8dcba9da1b11f25725cff0eb0be\",\n \"score\": \"0.5338591\",\n \"text\": \"def tfidf_log(term: str, document: dict, documents: list):\\n tf = log_term_frequency(term, document)\\n idf = inverse_document_frequency(term, documents)\\n\\n return tf*idf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2cf82a638cdd1f64e903613e3db423ef\",\n \"score\": \"0.5337314\",\n \"text\": \"def doc2model(doc):\\n counts = Counter(doc)\\n for term in counts:\\n counts[term] /= 1. * len(doc)\\n return counts\",\n \"title\": \"\"\n },\n {\n \"docid\": \"820934a2cf823a1271098eaf9e30e34c\",\n \"score\": \"0.53371984\",\n \"text\": \"def __calculate_rf(self, idsoal, tf:int, term:str, skor_huruf:str):\\n pos = self.__docnum_repository.\\\\\\n get_doc_num_pos_class(idsoal, term, skor_huruf)\\n neg = self.__docnum_repository.\\\\\\n get_doc_num_neg_class(idsoal, term, skor_huruf)\\n \\n rf = log(2 + (pos / max(1, neg)), 10)\\n\\n return rf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cac6104b53477adb1a1fcc35ab444886\",\n \"score\": \"0.5333681\",\n \"text\": \"def idf(corpus):\\n n_docs = len(corpus)\\n idf_dict = dict.fromkeys(corpus[0].keys(), 0)\\n\\n for bag_word in corpus:\\n for word, count in bag_word.items():\\n if count > 0:\\n idf_dict[word] += 1\\n\\n for word, count in idf_dict.items():\\n if count > 0:\\n idf_dict[word] = math.log(n_docs / float(count))\\n else:\\n idf_dict[word] = 0\\n\\n return idf_dict\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d81f03eac0b1b599273080979e0cf423\",\n \"score\": \"0.53275126\",\n \"text\": \"def score_one(self, sd):\\r\\n # Q.count(t) * tfn / (tfn + c) * log_2((N+1)/(C.count(t)+0.5) where tfn = D.count(t)*log_2(1 + avgdl/len(D))\\r\\n # print(\\\"avg_dl: {}\\\".format(sd.avg_dl))\\r\\n # print(\\\"num_docs: {}\\\".format(sd.num_docs))\\r\\n # print(\\\"total_terms: {}\\\".format(sd.total_terms))\\r\\n # print(\\\"query_length: {}\\\".format(sd.query_length))\\r\\n # print(\\\"t_id: {}\\\".format(sd.t_id))\\r\\n # print(\\\"query_term_weight: {}\\\".format(sd.query_term_weight))\\r\\n # print(\\\"doc_count: {}\\\".format(sd.doc_count))\\r\\n # print(\\\"corpus_term_count: {}\\\".format(sd.corpus_term_count))\\r\\n # print(\\\"d_id: {}\\\".format(sd.d_id))\\r\\n # print(\\\"doc_term_count: {}\\\".format(sd.doc_term_count))\\r\\n # print(\\\"doc_size: {}\\\".format(sd.doc_size))\\r\\n # print(\\\"doc_unique_terms: {}\\\".format(sd.doc_unique_terms))\\r\\n # print(\\\"================================================================================\\\")\\r\\n #return (self.param + sd.doc_term_count) / (self.param * sd.doc_unique_terms + sd.doc_size)\\r\\n\\r\\n c = self.param\\r\\n N = sd.num_docs\\r\\n tfn = sd.doc_term_count*math.log2(1 + sd.avg_dl/sd.doc_size)\\r\\n return sd.query_term_weight * tfn / (tfn + c) * math.log2((N+1)/(sd.corpus_term_count+0.5))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d7d59a4ed6f580e24b52ff90a9b44597\",\n \"score\": \"0.53198946\",\n \"text\": \"def count_tfidf(self):\\n\\t\\tif 'all_docs_num' not in dir(self):\\n\\t\\t\\tprint 'just set all_docs_num to class attr firstly'\\n\\t\\t\\treturn\\n\\t\\tdocsvector={}\\n\\t\\tsave_idf={}\\n\\t\\tfor doc_id in self.docs:\\n\\t\\t\\tdocsvector[doc_id]=[]\\n\\t\\t\\tfor word in sorted(self.feature):\\n\\t\\t\\t\\ttf=0 \\n\\t\\t\\t\\tif (doc_id in self.words[word].rf) and (self.words_count[doc_id]): \\n\\t\\t\\t\\t\\ttf=self.words[word].rf[doc_id]\\n\\t\\t\\t\\t\\ttf/=self.words_count[doc_id]\\n\\t\\t\\t\\tdf=self.words[word].docnum_in_cate+self.words[word].docnum_in_others\\n\\t\\t\\t\\tidf=math.log(self.all_docs_num/df,10.0)\\n\\t\\t\\t\\tsave_idf[word]=idf\\n\\t\\t\\t\\ttfidf=tf*idf\\n\\t\\t\\t\\tdocsvector[doc_id].append(tfidf)\\n\\t\\treturn docsvector,save_idf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1eed69c4d18982f8247bcdec249b4e8c\",\n \"score\": \"0.5296557\",\n \"text\": \"def get_term_dist(docs, word2id, lowercase=True):\\n term_dist = np.zeros(len(word2id))\\n for doc in docs:\\n for word in doc:\\n if lowercase:\\n word = word.lower()\\n if word in word2id:\\n term_dist[word2id[word]] += 1\\n\\n # normalize absolute freqs to obtain a relative frequency term distribution\\n term_dist /= np.sum(term_dist)\\n if np.isnan(np.sum(term_dist)):\\n # the sum is nan if docs only contains one document and that document\\n # has no words in the vocabulary\\n term_dist = np.zeros(len(word2id))\\n return term_dist\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b8a569f30568615c5fa8011ae0688fce\",\n \"score\": \"0.5287967\",\n \"text\": \"def compute_idfs(documents):\\n total_docs = len(documents.keys())\\n # getting all the unique words in documents\\n words = set([word for docs in documents.values() for word in docs])\\n # getting idf for words using formula\\n idf = {}\\n for word in words:\\n doc_count = 0\\n for docs in documents:\\n if word in documents[docs]:\\n doc_count += 1\\n idf[word] = math.log(total_docs / doc_count)\\n return idf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ebe8071083d9135be0914d01378b3339\",\n \"score\": \"0.52826416\",\n \"text\": \"def compute_normalized_idf(corpus):\\n d = {}\\n for document in tqdm(corpus):\\n words_document = []\\n try:\\n for p in sent_tokenize(document):\\n words_document.append(tokenize(p, [lower]))\\n except TypeError:\\n continue\\n words_document = list(itertools.chain(*words_document))\\n for w in words_document:\\n d[w] = d[w]+1 if w in d else 1\\n N = len(d.keys())\\n return {w: math.log(N/d[w])/math.log(N) for w in d.keys()}\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f3759567f7256a52e33b99527ca8d298\",\n \"score\": \"0.52685946\",\n \"text\": \"def __calculate_ntf(self, idsoal, tf:int, term:str):\\n max_tf = self.__ntfrf_repository.get_max_tf(idsoal, term)\\n \\n #if max_tf == 0: Tidak Mungkin MAX_TF 0 Jika ada TF\\n # max_tf = 1\\n\\n ntf = tf / max(1, max_tf)\\n return ntf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"19b3056c8b9250060a8d80506a6c52ea\",\n \"score\": \"0.52613556\",\n \"text\": \"def key_func(G):\\n n, d = G\\n return d[\\\"computed importance factor\\\"]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2daecb6f39e5c4768954801a50777d94\",\n \"score\": \"0.52583647\",\n \"text\": \"def inverse_document_frequency(term: str, documents: list):\\n number_of_documents = len(documents)\\n df = document_frequency(term, documents)\\n\\n return log(number_of_documents) - log(df)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c373ee7fee612107a1904343b223938b\",\n \"score\": \"0.52519584\",\n \"text\": \"def compute_idfs(documents):\\n words = []\\n for filename in documents:\\n words = words + documents[filename]\\n wordList = set(words)\\n\\n wordIDF = dict()\\n nDoc = len(documents)\\n for word in wordList:\\n nAppear = 0\\n for filename in documents:\\n if word in documents[filename]:\\n nAppear += 1\\n wordIDF[word] = math.log(nDoc/nAppear)\\n\\n return wordIDF\\n\\n\\n\\n\\n #raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2773022acfe1beb00e4e81e0a0645d19\",\n \"score\": \"0.5249381\",\n \"text\": \"def get_tfidf_scores(self, query):\\n length = {}\\n scores = {}\\n for id in self.ids:\\n length[id] = 0\\n scores[id] = 0\\n\\n for term in re.findall(r\\\"[\\\\w']+|[.,!?;]\\\", query.strip()):\\n term = term.lower()\\n if not term in self.document_frequencies:\\n continue\\n df = self.document_frequencies[term]\\n wq = np.log(self.num_documents/df)\\n for id in self.ids:\\n document_dict = self.term_frequencies[id]\\n if not term in document_dict:\\n scores[id] += 0\\n continue\\n tf = document_dict[term]\\n length[id] += tf**2\\n wd = 1 + np.log(tf)\\n scores[id] += wq * wd\\n for id in self.ids:\\n if length[id] == 0:\\n continue\\n scores[id] /= np.sqrt(length[id])\\n\\n return scores\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a94c659133dd8c21e8fcc8548626d3d1\",\n \"score\": \"0.5240084\",\n \"text\": \"def jelinek_mercer(self, query_term, doc):\\n # Frequency of term in the document (document term frequency - dtf)\\n fqiD = doc.get_dtf()\\n # Length of the document\\n dl = self.inverted_index.get_doc_length(doc.get_doc_id())\\n # Frequency of term in the collection (collection term frequency - ctf)\\n cqi = self.inverted_index.get_ctf(query_term)\\n # Total length of all documents in the collection\\n cl = self.inverted_index.get_collection_length()\\n \\n score = math.log(((1 - self.alphaD) * (fqiD / dl)) + (self.alphaD * (cqi / cl)))\\n return score * self.query_terms.count(query_term)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d636d28f74a111a6cb997e74b2e845f6\",\n \"score\": \"0.5229651\",\n \"text\": \"def no_of_documents_containing_a_word(self, query_word):\\n if PROXIMITY.useCache:\\n if query_word in BM25.no_of_docs_dict:\\n return float(BM25.no_of_docs_dict[query_word])\\n else:\\n return 0\\n else:\\n if query_word in self.cache:\\n return float(self.cache[query_word])\\n else:\\n no_of_documents_having_the_word = 0\\n for para_id, ranked_word_dict in self.documents.items():\\n if query_word in ranked_word_dict:\\n no_of_documents_having_the_word += 1\\n self.cache[query_word] = no_of_documents_having_the_word\\n return float(no_of_documents_having_the_word)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7168c69387fc787c36783669e23c67e5\",\n \"score\": \"0.52270603\",\n \"text\": \"def score(self, word, context):\\n context = self.check_context(context)\\n context_freqdist = self.ngrams[context]\\n word_count = context_freqdist[word]\\n context_count = context_freqdist.N()\\n return (word_count + self.k) / \\\\\\n (context_count + self.k_norm)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"21c5f8d2b68defa13eee488472bae88e\",\n \"score\": \"0.52200663\",\n \"text\": \"def compute_sentiment_for_tweet(tweet):\\n text = polyglot.text.Text(tweet.lower(), hint_language_code='it')\\n scores = [word.polarity for word in text.words if word.polarity != 0]\\n return np.mean(scores) if scores else 0.0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9d3401958a69e735567a05ff09171f57\",\n \"score\": \"0.5212027\",\n \"text\": \"def tf_idf(self, corpus):\\n top200list = [(word, count) for count, word in corpus.top200]\\n\\n \\n if corpus.type == \\\"subject\\\":\\n word_count = self.subject_word_count\\n else: \\n word_count = self.body_word_count\\n \\n self.tf_idf_scorelist = []\\n # print word_count\\n for word, document_frequency in top200list:\\n if word not in word_count:\\n # If word does not appear in the message, tf-idf == 0\\n self.tf_idf_scorelist.append([word, 0])\\n else:\\n # calculate the tf-idf score for the word, appending the pair (word, score) to the list\\n tf_idf_score = word_count[word] * math.log10(corpus.length / float(document_frequency)) + 1.0/200\\n self.tf_idf_scorelist.append([word, tf_idf_score])\\n \\n \\n return self.tf_idf_scorelist\",\n \"title\": \"\"\n },\n {\n \"docid\": \"23a54153fbba0f89e126596ded64aa86\",\n \"score\": \"0.52037126\",\n \"text\": \"def number_doc(self, document: list):\\n #doc = [0] * self.item_number()\\n for i in range(len(document)):\\n if document[i] > 0:\\n self.term_indoc[i] += 1\\n #print(i, document[i])\\n # return doc\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9527f60633735d3c6f56447d6af3074f\",\n \"score\": \"0.5198056\",\n \"text\": \"def compute_idfs(documents):\\n idfs = dict()\\n\\n for document in documents:\\n already_added = set()\\n for word in documents[document]:\\n if word not in idfs:\\n idfs[word] = 1\\n already_added.add(word)\\n elif word not in already_added:\\n idfs[word] += 1\\n already_added.add(word)\\n\\n for word in idfs:\\n idfs[word] = np.log( len(documents) / idfs[word] )\\n\\n return idfs\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a5bc4a76ecf34dc9cbcdb3d03acb7767\",\n \"score\": \"0.51957184\",\n \"text\": \"def _getCountForUnigram(self,word1):\\n count=self.unigrams[(word1)]\\n if count==0:\\n count=0.001\\n return count\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c15339eabb1d35644cd35efdac9d13e4\",\n \"score\": \"0.51779836\",\n \"text\": \"def findfreq(word):\\n\\n\\tif word in mostcommon:\\n\\t\\treturn mostcommon[word]\\n\\telse:\\n\\t\\treturn 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e69067a5caacec71a03278ae8b987ae2\",\n \"score\": \"0.5170481\",\n \"text\": \"def idf(inverted_index: List, token: str, collection_size: int) -> float:\\n term_frequence = len(inverted_index.get(token, []))\\n if term_frequence is 0:\\n return 0\\n return math.log((collection_size+1) / term_frequence)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e4aef0991b20ecb512b79c568277d6d9\",\n \"score\": \"0.51683074\",\n \"text\": \"def calcidf(df):\\n docamount = df[1] - 1 # subtract\\n docfreq = df[0]\\n idf = dict() # create a new dictionary\\n for term in docfreq: # for every entry in the df, calculate the idf\\n frequency = docfreq.get(term)\\n multiplication = docamount / frequency\\n answer = mth.log2(multiplication)\\n idf[term] = answer # save the idf in the dictionary for the current term\\n return idf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"85b13c002cf9b0a943e30e0b203bbe07\",\n \"score\": \"0.5163134\",\n \"text\": \"def get_emmision(self, word, tag):\\n if tag in ['*', 'STOP']:\\n return 0.0\\n new_word = self.replace_word(word)\\n return self.word.get((tag, new_word), 0.0) / self.ngrams[1][tag]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1f4716e3a6d2b4253747ce5bde849769\",\n \"score\": \"0.5157731\",\n \"text\": \"def tfidf_search(query, index_set):\\n index = get_index(index_set) # [token] -> [(doc_id, token_count)]\\n df = get_df(index_set) # {token: doc_freq}\\n processed_query = preprocess_query(query, index_set)\\n # YOUR CODE HERE\\n\\n # Normalize index?\\n relevant_documents = []\\n total_documents = 3204 # Dynamicly?\\n \\n for word in processed_query:\\n for term_frequencies in index[word]:\\n doc_id = term_frequencies[1]\\n tf = term_frequencies[1]\\n idf = math.log(total_documents/df[word]) # IDF = log(total_documents/df)\\n tf_idf = tf*idf\\n if not any([e[0] == doc_id for e in relevant_documents]) : # Document not encountered before\\n relevant_documents.append([doc_id, tf_idf])\\n else: # Document encountered. Add tf-idf score to previous score\\n for document in relevant_documents:\\n if document[0] == doc_id:\\n document[1] += tf_idf\\n break\\n # Sort in descending order according to score\\n relevant_documents = sorted(relevant_documents,key=lambda x: (x[1]))\\n return relevant_documents\",\n \"title\": \"\"\n },\n {\n \"docid\": \"62ef62e74acd25ee51d17ae5271bb00d\",\n \"score\": \"0.5125886\",\n \"text\": \"def idf(self, book_num, token):\\n return np.log((self.sentence_id + 1) / (self.df(book_num, token) + 1))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8310f28fea6a5c72c7ee004854250751\",\n \"score\": \"0.51238996\",\n \"text\": \"def tf_idf_score(tokens):\\n for token in tokens.keys():\\n df = len(tokens[token])\\n idf = math.log(TOTAL_UNIQUE_DOC/df)\\n for posting in tokens[token]:\\n tf = posting[1]\\n tf_idf = (1 + math.log(tf)) * idf\\n posting[1] = tf_idf\\n \\n return tokens\",\n \"title\": \"\"\n },\n {\n \"docid\": \"183d68bf522d93cf0b91a779d2ef0570\",\n \"score\": \"0.51199824\",\n \"text\": \"def compute_idfs(documents):\\n idfs = {} # Initialise a dictionary of idfs\\n for doc in documents:\\n for word in documents[doc]:\\n if word in idfs: # Word already calculated\\n continue\\n word_occurences = 1\\n for doc2 in documents:\\n if doc2 == doc: # Skip word iteration we are looking at\\n continue\\n if word in documents[doc2]:\\n word_occurences += 1\\n idfs[word] = math.log(len(documents) / word_occurences)\\n return idfs\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":398,"cells":{"query_id":{"kind":"string","value":"ae240ac6cc2863ef66089a55dc3eb4ed"},"query":{"kind":"string","value":"This method is queue scheduler and executer \\n"},"positive_passages":{"kind":"list like","value":[{"docid":"b9240612058aa55653c74834c388d516","score":"0.0","text":"def lcfs_alg(self, process_waiting):\n cpu_clock = 0\n local_finished_queue = []\n while len(process_waiting) is not 0:\n proc = process_waiting[-1]\n cpu_clock += 1\n\n if proc.exec_start is None:\n proc.exec_start = cpu_clock\n\n proc.remain -= 1\n\n if proc.remain is 0:\n proc.exec_stop = cpu_clock\n local_finished_queue.append(proc)\n del process_waiting[-1]\n self.finished_queue.append(local_finished_queue)","title":""}],"string":"[\n {\n \"docid\": \"b9240612058aa55653c74834c388d516\",\n \"score\": \"0.0\",\n \"text\": \"def lcfs_alg(self, process_waiting):\\n cpu_clock = 0\\n local_finished_queue = []\\n while len(process_waiting) is not 0:\\n proc = process_waiting[-1]\\n cpu_clock += 1\\n\\n if proc.exec_start is None:\\n proc.exec_start = cpu_clock\\n\\n proc.remain -= 1\\n\\n if proc.remain is 0:\\n proc.exec_stop = cpu_clock\\n local_finished_queue.append(proc)\\n del process_waiting[-1]\\n self.finished_queue.append(local_finished_queue)\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"ee659d2f4dda0e351f0bd89aaa2c9951","score":"0.6921316","text":"def processQueue(self):","title":""},{"docid":"09982e5cbe4c7df30fe4ae28f60d7e1f","score":"0.6735559","text":"def scheduler(self):\n j = self.updater.job_queue\n print('getting daily queue')\n for hour in range(24):\n j.run_daily(\n self.reminder, \n days=(0, 1, 2, 3, 4, 5, 6), \n time=datetime.time(hour=hour, minute=0, second=0))","title":""},{"docid":"bf97de4d4a319c49c9bf54fa22625dc4","score":"0.6597712","text":"def submit_task(d, queued_engine):","title":""},{"docid":"23e1185fb8d5270a667d4e2d3257f59e","score":"0.65356296","text":"def schedule(self) -> TaskSchedulerResult:","title":""},{"docid":"39d6c7f5c1bc044182218688a4d86895","score":"0.64829427","text":"async def _scheduler(self) -> None:\n while True:\n results = await self.broker.process_schedule()\n logger.info(\"poll-schedule\", executor=self.executor_id, results=results)\n await anyio.sleep(self.settings.schedule_interval)","title":""},{"docid":"9f1871234406722881c04af1ec3fb7aa","score":"0.64672405","text":"def QueueAction(self):\r\n pass","title":""},{"docid":"248113746a5f9e7b8974a9405b25fadd","score":"0.64446646","text":"def submit_to_queue(self, script_file):","title":""},{"docid":"8614344a5e5d515b7cc39eff0c3a0201","score":"0.63791","text":"def postQueueSetup(self):","title":""},{"docid":"001f189f2d2be78455aa44477059109e","score":"0.63419634","text":"def schedule():","title":""},{"docid":"001f189f2d2be78455aa44477059109e","score":"0.63419634","text":"def schedule():","title":""},{"docid":"fb9ce3e8b6a59bb826188d077a4f8427","score":"0.6271516","text":"def scheduling_step(self):\n self.qNetwork.scheduler.step()","title":""},{"docid":"72fbb8bbe0b7777160730aa42e485ff0","score":"0.6236307","text":"def pre_task(d, queued_engine):","title":""},{"docid":"d177ee87680f989087422d21a082a222","score":"0.6169855","text":"def q_handler(self, queue):\n pass","title":""},{"docid":"5721e445d2d0d490b274d7a059fba8fa","score":"0.61419314","text":"def execute(obj, queue, restaurant):\n mean_a = 1000\n std_a = 200\n queue._queue.append(obj)\n if obj.q_type == 2:\n restaurant.groups.append(obj)\n restaurant.next_appearance_time = restaurant.simulation_time + abs(int(np.random.normal(mean_a, std_a)))\n obj.appearance_time = restaurant.simulation_time","title":""},{"docid":"0155284ce73c99d5d0f469d3b8e58334","score":"0.61335665","text":"def execute(self):\n self.queue_command('execute')","title":""},{"docid":"bbb39cde6a4e2601ecbeebc511beffc6","score":"0.61177796","text":"def q_handler(queue):\n pass","title":""},{"docid":"064201ebbc9fd7b319e41af363cb1595","score":"0.60882354","text":"def runTask(self):","title":""},{"docid":"8cbdbd93f2c1fdddea5994cba197e3d4","score":"0.6071057","text":"def publish_schedule(self):\n while not rospy.is_shutdown():\n # all encompassing try/catch to make sure this loop does not go down\n try:\n\n # copy all relevant entries under lock \n # we're taking a deepcopy as we might mess around with the times a bit\n with self.state_lock:\n expected_completion_time = deepcopy(self.expected_completion_time)\n active_batch = deepcopy(self.active_batch)\n normal_tasks = deepcopy(self.normal_tasks)\n time_critical_tasks = deepcopy(self.time_critical_tasks)\n\n now = rospy.get_rostime()\n # todo: fill this value better\n expected_end_of_batch = rospy.get_rostime() + rospy.Duration(120)\n\n # start from the time_cr\n schedule = ExecutionStatus(currently_executing = len(active_batch) > 0)\n all_tasks = ExecutionStatus(currently_executing = len(active_batch) > 0)\n\n schedule.header.stamp = now\n all_tasks.header.stamp = now\n\n for m in active_batch:\n m.task.execution_time = now\n schedule.execution_queue.append(m.task)\n all_tasks.execution_queue.append(m.task)\n\n\n # schedule.execution_queue += [m.task for m in time_critical_tasks]\n all_tasks.execution_queue += [m.task for m in time_critical_tasks]\n\n all_tasks.execution_queue += [m.task for m in normal_tasks] \n all_tasks.execution_queue = sorted(all_tasks.execution_queue, key=lambda x: x.start_after) \n all_tasks.execution_queue = sorted(all_tasks.execution_queue, key=lambda x: x.priority) \n\n\n self.schedule_publisher.publish(schedule) \n self.all_tasks_schedule_publisher.publish(all_tasks)\n\n self.update_schedule_condition.acquire()\n self.update_schedule_condition.wait()\n self.update_schedule_condition.release()\n except Exception, e:\n rospy.logwarn('Caught exception in publish_schedule loop: %s' % e)\n rospy.sleep(1)","title":""},{"docid":"38fc6dd831a44eb5074059472f95b7c7","score":"0.6069418","text":"def post_task(d, queued_engine):","title":""},{"docid":"875d8cfcb4347b491c2a6203b931d6f8","score":"0.60506755","text":"def boss():\n\n for i in xrange(1,10):\n task_queue.put(i)\n print('Assigned all work in iteration 1')\n\n for i in xrange(10,20):\n task_queue.put(i)\n print('Assigned all work in iteration 2')","title":""},{"docid":"5b34c60faf976bca2db206ef0b3b9e4e","score":"0.603343","text":"def work_queue(q):\n global agent_data\n global listing_data\n global office_data\n if(agent_data):\n q.put(agent_data)\n time.sleep(0.1)\n if(listing_data):\n q.put(listing_data)\n time.sleep(0.1)\n if(office_data):\n q.put(office_data)\n time.sleep(0.1)\n q.join()","title":""},{"docid":"6b118992b9444c8e05303ad1bf98525d","score":"0.6030745","text":"def worker(name, queue, results):\n pass","title":""},{"docid":"0c7fc06973f069f1ba4b0b84046c4e92","score":"0.602613","text":"def __init__(self):\r\n self.queue = []","title":""},{"docid":"e089a5135da4ce04f50dcc5a56ba7f97","score":"0.6015598","text":"def _queueDispatchNormal(self, nextEvent, queue=True, countdown=0, retryOptions=None, queueName=None):\r\n assert nextEvent is not None\r\n assert queueName\r\n \r\n url = self.buildUrl(self.currentState, nextEvent)\r\n params = self.buildParams(self.currentState, nextEvent)\r\n taskName = self.getTaskName(nextEvent)\r\n \r\n task = Task(name=taskName, method=self.method, url=url, params=params, countdown=countdown,\r\n retry_options=retryOptions, headers=self.headers)\r\n if queue:\r\n self.Queue(name=queueName).add(task)\r\n \r\n return task","title":""},{"docid":"e089a5135da4ce04f50dcc5a56ba7f97","score":"0.6015598","text":"def _queueDispatchNormal(self, nextEvent, queue=True, countdown=0, retryOptions=None, queueName=None):\r\n assert nextEvent is not None\r\n assert queueName\r\n \r\n url = self.buildUrl(self.currentState, nextEvent)\r\n params = self.buildParams(self.currentState, nextEvent)\r\n taskName = self.getTaskName(nextEvent)\r\n \r\n task = Task(name=taskName, method=self.method, url=url, params=params, countdown=countdown,\r\n retry_options=retryOptions, headers=self.headers)\r\n if queue:\r\n self.Queue(name=queueName).add(task)\r\n \r\n return task","title":""},{"docid":"9165fb63c6af7adf8ccaa633cfde4dcc","score":"0.60065794","text":"def create_executor():","title":""},{"docid":"931a6cef09618f687c54fd50f221853d","score":"0.6002376","text":"def runMovementExecutor(ctrlQueue):\n ctrlQueue.processMovementAsync()","title":""},{"docid":"fc5981bd695bd8d18f8d894cd71e5336","score":"0.59982544","text":"def __init__(self):\n self.queue = []","title":""},{"docid":"fc5981bd695bd8d18f8d894cd71e5336","score":"0.59982544","text":"def __init__(self):\n self.queue = []","title":""},{"docid":"fc5981bd695bd8d18f8d894cd71e5336","score":"0.59982544","text":"def __init__(self):\n self.queue = []","title":""},{"docid":"dde6721867ea81c6b064153479d33d58","score":"0.59972245","text":"def submit(self, func=_ping, *args):\n self.queue.put((func, args))","title":""},{"docid":"87ec4ff646818ad7d4040082c3d00252","score":"0.5976356","text":"def __init__(self):\n\n self.queue = []","title":""},{"docid":"65a827e4934eb428c0fde4b7914992d7","score":"0.5974972","text":"def start_tasks(automatic_tasks):\n scheduler = AsyncIOScheduler()\n print('Started Chron Monitors')\n # scheduler.add_job(automatic_tasks.block_monitor,CronTrigger(hour='02',second='02'), misfire_grace_time=2,\n # max_instances=20)\n #\n # scheduler.add_job(automatic_tasks.send_dpops_stats,\n # CronTrigger(minute='00'), misfire_grace_time=2, max_instances=20)\n #\n # scheduler.add_job(automatic_tasks.delegate_ranks, CronTrigger(hour='02', second='02'), misfire_grace_time=2,\n # max_instances=20)\n scheduler.add_job(automatic_tasks.delegate_last_block_check,\n CronTrigger(minute='02,04,06,08,10,12,14,16,18,20,22,24,26,'\n '28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58'), misfire_grace_time=2,\n max_instances=20)\n\n\n\n scheduler.start()\n print('Started Chron Monitors : DONE')\n return scheduler","title":""},{"docid":"aa413d93a525947e668840285f42e92d","score":"0.59666026","text":"def run(self):\n while self.frame_number <= self.max_frame_number or not self.run_queue.empty():\n \n # get a frame when frame period arrives\n if self.time % self.frame_period == 0:\n self.frame_arrival(self.frame_number)\n self.frame_number = self.frame_number + 1\n\n # if there are tasks in the run queue\n if not self.run_queue.empty():\n top_task = self.run_queue.queue[0]\n top_task.remain_time = top_task.remain_time - 1\n\n # if the task has finished\n if top_task.remain_time == 0:\n task = self.run_queue.get()\n self.task_finish_count = self.task_finish_count + 1\n task.order = self.task_finish_count\n # add 1 because self.time start from 0\n task.response_time = self.time - task.enqueue_time + 1\n if task.response_time > task.deadline:\n task.missed = 1\n\n self.history.append(task)\n # you can comment out the following line to skip yolo for shorter program runtime\n #self.run_yolo(task)\n \n self.time = self.time + 1\n \n # save scheduling history to file\n self.save_history()\n print(\"Scheduling history saved.\")","title":""},{"docid":"c7efaa6ddd630ba65c6ead98eef8f7ed","score":"0.5962126","text":"def run(self):\n try:\n quit_request_detected = False\n while True:\n aFunction, arguments = self.manager.task_queue.get()\n if aFunction is None:\n break\n if quit_request_detected:\n continue\n try:\n try:\n args, kwargs = arguments\n except ValueError:\n args = arguments\n kwargs = {}\n aFunction(*args, **kwargs) # execute the task\n except Exception:\n self.config.logger.error(\"Error in processing a job\",\n exc_info=True)\n except KeyboardInterrupt:\n self.config.logger.info('quit request detected')\n quit_request_detected = True\n #thread.interrupt_main() # only needed if signal handler\n # not registerd\n except Exception:\n self.config.logger.critical(\"Failure in task_queue\", exc_info=True)","title":""},{"docid":"22d1414bf9d5982b58b1f244b0c65774","score":"0.5945777","text":"def put( self ):\r\n BUY_QUEUE_DB.createQueue( self )","title":""},{"docid":"6c41ee7cfb6588e82aa8a85961bb28b4","score":"0.59050715","text":"def execute(self, evq):\n\n\t\t# can't send if it's busy sending - and doesn't have a unit available for all transmissions\n\t\tbw = int(self.node.available_bandwidth()/self.concurr)\n\t\tif bw < cfg.NODE_BANDWIDTH_UNIT:\n\t\t\treturn None\n\t\t# then pop the last task we got\n\t\tt = self.node.pop_task_to_send(self.k, self.time)\n\t\t# if it's an invalid choice return without sending out the task\n\t\tif t == None:\n\t\t\treturn None\n\t\t# else plan the landing\n\t\tarrival_time = self.time+ task_communication_time(t.packet_size, point_to_point_transmission_rate(self.node._distances[self.destination.index], bw))\n\t\tevq.add_event(Task_arrival(arrival_time, self.destination, self.k, t))\n\t\tevq.add_event(Start_transmitting(self.time, self.node, arrival_time, bw))\n\t\treturn None","title":""},{"docid":"5dc3a7255e77ee0821f078f00fcd92d7","score":"0.5901182","text":"def callback_task_scheduler_creator(queue_task_scheduler, task_supervisor):\n global entity_task_supervisor_info\n global active_task_schedulers\n logger.info(\"SchedulerDealer started\")\n\n while True:\n task_scheduler = None\n # wait for a new materialflow\n materialflow_specification = queue_task_scheduler.get()\n\n # create new task shedular\n task_scheduler = Scheduler(materialflow_specification, task_supervisor)\n\n active_task_schedulers.append(task_scheduler)\n task_scheduler.start()\n\n entity_task_supervisor_info.appendMaterialflow(\n materialflow_specification.id)\n\n task_supervisor.orion_connector.update_entity(\n entity_task_supervisor_info)\n logger.info(\"New TaskScheduler added\")\n\n logger.info(\"SchedulerDealer ended\")","title":""},{"docid":"32245beee93a6556c958388fefddeb79","score":"0.5898572","text":"def worker_thread( self ):\n\n # rand = random.Random()\n \n #while self.running:\n # # To simulate asynchronous I/O, we create a random number at\n # # random intervals. Replace the following 2 lines with the real\n # # thing.\n # time.sleep( rand.random() * 1 )\n # msg = rand.random()\n # self.queue.put(msg)","title":""},{"docid":"cbcfc85165804db4bd663142c9f82f60","score":"0.5887806","text":"def create_queue():\n return True","title":""},{"docid":"c71da4fb04df7990abf1afd84f95e621","score":"0.5882573","text":"def handle_queue(self):\n if not self.queue:\n return\n calculator = self.get_free_calculator()\n if calculator is not None:\n task = self.queue.pop(0) # tuple: (data, client_addr)\n print 'Task from queue'\n self.handle_client_request(*task)","title":""},{"docid":"4a62e16f3cb28ae4221cf1ca49886ef8","score":"0.58702046","text":"def __call__(self, *args, **kwargs):\n self.schedule(*args, **kwargs)","title":""},{"docid":"26860fb43d63571fc92461e544732e1a","score":"0.58692646","text":"def handle_output(self, queue):","title":""},{"docid":"03a30ef670c6ed8fc43d7558bd9bf55b","score":"0.5823347","text":"def run(self):\n\n # Startup\n # ------------------------------------------------------------------\n if(self.first_execution):\n\n # log\n self.logger.debug('Thread first execution')\n\n # setup_timer\n self.setup_timer.emit()\n\n # first_execution\n self.first_execution = False\n\n # Code\n # ------------------------------------------------------------------\n else:\n\n try:\n obj = self.queue.get(block=False)\n except Queue.Empty:\n self.logger.debug('Queue empty')\n return\n\n try:\n obj()\n except Exception, e:\n self.logger.debug('{0}'.format(e))\n finally:\n # notify queue\n self.queue.task_done()","title":""},{"docid":"2b14f6ebce1518b0993d07e19d4c2b25","score":"0.5823279","text":"def process(self):\n self.out.idle=True\n if self.task.finished:\n self.sim.schedule(TaskFinishedEvent(self.sim, self.task, self.time))\n else:\n self.sim.add_task_to_rr_queue(self.task)\n \n \n task=self.sim.get_task_from_rr_queue() \n task.wait_out=task.wait_out+(self.time-task.outtime)\n \n# self.sim.schedule(OutInEvent(self.sim, task, self.time, self.out))\n self.sim.schedule(TaskOutArrivalEvent(self.sim, task, self.time))","title":""},{"docid":"3392e738f705ae414a03887f3d19d98a","score":"0.58100414","text":"def execute(self):\n logging.info(\"Executing Task with ID: \" +str(self.get_id() ) + \" and Name: \"+ self.get_name() )","title":""},{"docid":"b0306046c69aaf5e470b4c9533005e2d","score":"0.5802936","text":"def schedule_run(self, schedule):\n\n if len(schedule.jobs): # no need to start thread if no jobs in queue\n t = threading.Thread(target=self.scheduler_thread)\n # print('Starting scheduler thread')\n t.daemon = True # allows this thread to be auto-killed on program exit\n t.name = 'Scheduler Thread' # naming the thread helps with debugging\n t.start()","title":""},{"docid":"90db4594bf0930bb251744ec1e4107cb","score":"0.5789738","text":"def sort_queue(self, queue, chart):\n ...","title":""},{"docid":"90db4594bf0930bb251744ec1e4107cb","score":"0.5789738","text":"def sort_queue(self, queue, chart):\n ...","title":""},{"docid":"289784cde6c55a3047bfe2c5249ec8fe","score":"0.5789452","text":"def process(self):\n self.out.work(self.task, self.time)","title":""},{"docid":"fc487244608e8a94ba3fd3938c4f272e","score":"0.5786862","text":"def task(self):\n self._command()","title":""},{"docid":"c78660fbebac34809345bc05ab6f3507","score":"0.57828987","text":"def __init__(self):\n\n self.queue = None","title":""},{"docid":"8132b470834cdd118bd19824c5f071e4","score":"0.5778886","text":"def start_worker(self):","title":""},{"docid":"9bc9072fca2436f3a6180285bc49096b","score":"0.57753813","text":"def test_enqueue_scheduled_jobs(self):\n queue = Queue(connection=self.testconn)\n registry = ScheduledJobRegistry(queue=queue)\n job = Job.create('myfunc', connection=self.testconn)\n job.save()\n registry.schedule(job, datetime(2019, 1, 1, tzinfo=timezone.utc))\n scheduler = RQScheduler([queue], connection=self.testconn)\n scheduler.acquire_locks()\n scheduler.enqueue_scheduled_jobs()\n self.assertEqual(len(queue), 1)\n\n # After job is scheduled, registry should be empty\n self.assertEqual(len(registry), 0)\n\n # Jobs scheduled in the far future should not be affected\n registry.schedule(job, datetime(2100, 1, 1, tzinfo=timezone.utc))\n scheduler.enqueue_scheduled_jobs()\n self.assertEqual(len(queue), 1)","title":""},{"docid":"2aa461c2a59099b28f22645538a51645","score":"0.5753001","text":"def wthdMain(self):\r\n while self.running:\r\n time.sleep(1.0)\r\n self.queue.put(\"main\")","title":""},{"docid":"ef597efc0c18387906e9a5714d8a73c7","score":"0.57470465","text":"def queue(self):\n self._queue = True\n return self","title":""},{"docid":"33cdde67ec2238bee286e957570d738d","score":"0.57407373","text":"def put_job(self,name,func):\n self._qlock.acquire()\n self._q.append((name,func))\n self._qlock.release()","title":""},{"docid":"59881637e3876c247e50528a084c1dc4","score":"0.5737807","text":"def schedule(self):\n if not self.schedule_expression:\n return\n self.__create_cw_log_groups()\n self.register_task_definition()\n self.scheduler.schedule()\n click.secho(f\"Scheduled task {self.taskName}\", fg=\"cyan\")","title":""},{"docid":"cf358ce4420190e26bca11676b52cf16","score":"0.5737732","text":"def _apply_queue(self, args, thisTask, cmd_args, payload, setup):\n if not (thisTask.queue is None or thisTask.queue == \"\"):\n cmd_args.append(\"-p\") # partition\n cmd_args.append(thisTask.queue)\n return True","title":""},{"docid":"6f534421e7cf609a3b2e736fd7228fe9","score":"0.57371837","text":"def runTest(self):\n sys_logging(\"start test\")\n switch_init(self.client)\n\n port = port_list[1]\n level = [0,1,2]\n max_childs = [4, 64, 8]\n sched_group_id_group_node = [None]*8\n sched_group_service_id = 1\n service_queueId = [None]*8\n\n\n sched_type1 = SAI_SCHEDULING_TYPE_STRICT\n sched_type2 = SAI_SCHEDULING_TYPE_DWRR\n sched_weight = 10\n cir = 2000000\n cbs = 256000\n pir = 1000000\n pbs = 64000\n queueId_list = []\n\n sched_oid1 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type1, 0, cir, cbs, pir, pbs)\n sys_logging(\"sched_oid_1 0x%x\"%sched_oid1)\n\n sched_oid2 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type2, sched_weight, cir, cbs, pir, pbs)\n sys_logging(\"sched_oid_1 0x%x\"%sched_oid2)\n sched_oid_list = [sched_oid1, sched_oid2]\n\n \n sched_group_id_root = sai_thrift_qos_create_scheduler_group(self.client, port, level[0], max_childs[0], port, 0)\n \n sched_group_id_chan_node = sai_thrift_qos_create_scheduler_group(self.client, port, level[1], max_childs[1], sched_group_id_root, 0)\n \n sched_group_id_group_node[0] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id) \n sched_group_id_group_node[1] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\n sched_group_id_group_node[2] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\n sched_group_id_group_node[3] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\n sched_group_id_group_node[4] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id) \n sched_group_id_group_node[5] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\n sched_group_id_group_node[6] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\n sched_group_id_group_node[7] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\n\n \n queue_type = SAI_QUEUE_TYPE_SERVICE\n queue_index = [0,1,2,3,4,5,6,7]\n service_queueId[0] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[0], parent_id=sched_group_id_group_node[0], service_id=sched_group_service_id, sche_id=sched_oid1) \n service_queueId[1] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[1], parent_id=sched_group_id_group_node[1], service_id=sched_group_service_id, sche_id=sched_oid2)\n service_queueId[2] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[2], parent_id=sched_group_id_group_node[1], service_id=sched_group_service_id, sche_id=sched_oid2)\n service_queueId[3] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[3], parent_id=sched_group_id_group_node[3], service_id=sched_group_service_id, sche_id=sched_oid1)\n service_queueId[4] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[4], parent_id=sched_group_id_group_node[4], service_id=sched_group_service_id)\n service_queueId[5] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[5], parent_id=sched_group_id_group_node[4], service_id=sched_group_service_id)\n service_queueId[6] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[6], parent_id=sched_group_id_group_node[4], service_id=sched_group_service_id)\n service_queueId[7] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[7], parent_id=sched_group_id_group_node[7], service_id=sched_group_service_id)\n #pdb.set_trace()\n\n warmboot(self.client)\n try:\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[0])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid1:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[1])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid2:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[2])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid2:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[3])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid1:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[4])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[5])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[6])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[7])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError()\n\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_oid2)\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(service_queueId[4], attr)\n \n self.client.sai_thrift_set_queue_attribute(service_queueId[5], attr)\n self.client.sai_thrift_set_queue_attribute(service_queueId[6], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_oid1)\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(service_queueId[7], attr)\n \n \n\n\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[0])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid1:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[1])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid2:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[2])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid2:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[3])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid1:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[4])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid2:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[5])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid2:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[6])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid2:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[7])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid1:\n raise NotImplementedError()\n \n\n finally:\n #pdb.set_trace()\n for ii in range(8):\n attr_value = sai_thrift_attribute_value_t(oid=0)\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(service_queueId[ii], attr)\n\n #pdb.set_trace()\n for i in range(8):\n self.client.sai_thrift_remove_queue(service_queueId[i])\n\n for ii in range(8):\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_group_node[ii])\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_chan_node)\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_root)\n\n self.client.sai_thrift_remove_scheduler_profile(sched_oid1)\n self.client.sai_thrift_remove_scheduler_profile(sched_oid2)","title":""},{"docid":"55c8d13354431b48da081edcc48c77c9","score":"0.5726604","text":"def __init__(self):\n self.__queue = Queue.Queue()","title":""},{"docid":"e4340d2e81a85e699eaef96f0da65ac6","score":"0.5724557","text":"def run_dispatcher(sender, instance, created, **kwargs):\n if created or instance.status==\"waiting\": \n #se il dispatcher e' appena stato creato o ri-settato su waiting accodalo\n if not instance.send_date: instance.send_date = datetime.now()\n timestamp = datetimeToUnixSec(instance.send_date)\n spooling_dispatcher.spool(disp=\"%s\" % instance.pk,at=timestamp)","title":""},{"docid":"96666b0b65b7f4194ff1f36151cdf17f","score":"0.5721709","text":"def do_GET(self):\n # f = self.send_head()\n # if f:\n # self.copyfile(f, self.wfile)\n # f.close()\n print self.path \n \n if not self.server.sheduler:\n f.write(\"Sheduler not running\")\n return\n args =self.path\n print \"args\", args\n print 'sheduler', self.server.sheduler\n # Ceci est juste un test que ajoute un job sur le sheduler(\n # un job en duren -a_job_for_test, mais on aurait pu imaginer*\n # un truc plus generic , ou la method en question a executee\n # est passe par la requete Http.\n now = datetime.now() + timedelta(seconds=10)\n\n # comme un 'cron' , voici une facon de scecifier au sheduler\n # un job a effctue tous le trois secondes:) .Note que dans\n # l'exemple la fonction 'a_job_for_test' est juste\n # un exemple , mais nous aurions pu aussi bien imaginer que\n # le nom de la fonction est passe au serveur via Http\n # un truc du genre self.path.split('')\n self.server.sheduler.scheduler.add_interval_job(\n a_job_for_test,\n seconds=3,\n name='a_job_for_test',\n jobstore='MongoDB',\n args=[now])\n\n # comme un 'cron' , voici une facon de scecifier au sheduler\n # un job a effctued dans 10 secondes un seule fois.Note que dans\n # l'exemple la fonction 'a_job_for_test' est juste\n # un exemple , mais nous aurions pu aussi bien imaginer que\n # le nom de la fonction est passe au serveur via Http\n # un truc du genre self.path.split('')\n \n # self.server.sheduler.scheduler.add_date_job(a_job_for_test,\n # now,\n # name='a_job_for_test',\n # jobstore='MongoDB',\n # args=[now])\n thread.start_new_thread(\n self.server.sheduler.scheduler.start, ())","title":""},{"docid":"03e660d8b4b5d1a049987a4269af748a","score":"0.57131505","text":"def start(self):\n self.scheduler.run()","title":""},{"docid":"c44f64483249506b3cf24840449c6458","score":"0.5688256","text":"def _thread_proc(self):","title":""},{"docid":"f4cfd32a0bc0ab24d6d8739d4bfe14ce","score":"0.5688189","text":"def __init__(self):\n self.queue = multiprocessing.Queue()","title":""},{"docid":"30a775ed4183d5e40a776f446586eebd","score":"0.56776375","text":"def process(self): \n self.cpu.idle=True\n if not self.sim.sjf_queue.empty():\n task=self.sim.get_task_from_sjf_queue()\n self.sim.schedule(CpuInEvent(self.sim, task, self.time, self.cpu))\n else:\n pass\n \n self.task.outtime=self.time\n event=TaskOutArrivalEvent(self.sim, self.task, self.time)\n self.sim.schedule(event)","title":""},{"docid":"8f178b55208475f485be62e6c6bffd09","score":"0.5674458","text":"def handle_queue(self):\n cmd, payload = self.queue.get()\n if cmd == 'quit':\n self.running = False\n\n elif cmd == 'insert':\n for file in payload['files']:\n self.send({\n 'do': 'index_add',\n 'filename': file\n })\n\n elif cmd == 'delete':\n for file in payload['files']:\n self.send({\n 'do': 'index_remove',\n 'filename': file\n })\n\n elif cmd == 'search':\n file = payload['file']\n self.send({\n 'do': 'index_search',\n 'filename': file\n })\n\n elif cmd == 'download':\n file = payload['file']\n addr = self.results.get(file)\n if addr is not None:\n print('Using cached address (%s:%s) for %s' % (*addr, file))\n download(self.naxos_path, file, addr)\n else:\n print('You have to search for the file first.') # TODO: Auto-search\n self.input_thread.unblock()\n\n elif cmd == 'discover_overlay':\n self.overlay_edges = set()\n self.send({\n 'do': 'discover_overlay'\n })\n self.periodic_runner.register(watch_edges, {\n 'client': self,\n 'old': set(),\n 'queue': self.queue,\n }, 0.5)\n \n elif cmd == 'print_overlay':\n self.periodic_runner.unregister(watch_edges)\n layout = 'strict graph {\\n\\t'+ '\\n\\t'.join(('%s -- %s' % e for e in self.overlay_edges)) +'\\n}\\n'\n print('Visit the following webpage for a visualization of the overlay:')\n print(tiny_url('https://dreampuf.github.io/GraphvizOnline/#' + urllib.parse.quote(layout)))\n print('Shortened since the link can get really big.')\n self.input_thread.unblock()\n else:\n raise ValueError('Unexpected command %s' % cmd)","title":""},{"docid":"b0e8a2935bdc1060f33beeb24a84a53e","score":"0.56606203","text":"def __init__(self):\n self.queues = [], []","title":""},{"docid":"e14a74e5ad4c335259a0bf3975baa8b0","score":"0.56601393","text":"def execCmd(self , queue , rien):\n while True:\n msg = queue.get()\n if msg == \"Connect\":\n self.tGrbl.connectToGrbl()\n self.tGuillotine.updateBtnState()\n elif msg == \"Disconnect\": \n self.tGrbl.disconnectToGrbl()\n self.tGuillotine.updateBtnState()","title":""},{"docid":"e2a359560e8797247bc3fe9bfbec9b8a","score":"0.5657827","text":"def runTest(self):\n sys_logging(\"start test\")\n switch_init(self.client)\n port = port_list[1]\n sched_type1 = SAI_SCHEDULING_TYPE_STRICT\n sched_type2 = SAI_SCHEDULING_TYPE_DWRR\n sched_weight = 10\n cir = 2000000\n cbs = 256000\n pir = 1000000\n pbs = 64000\n queueId_list = []\n\n sched_oid1 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type1, 0, cir, cbs, pir, pbs)\n sys_logging(\"sched_oid_1 0x%x\"%sched_oid1)\n\n sched_oid2 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type2, sched_weight, cir, cbs, pir, pbs)\n sys_logging(\"sched_oid_1 0x%x\"%sched_oid2)\n sched_oid_list = [sched_oid1, sched_oid2]\n attrs = self.client.sai_thrift_get_port_attribute(port)\n for a in attrs.attr_list: \n if a.id == SAI_PORT_ATTR_QOS_NUMBER_OF_QUEUES:\n sys_logging(\"queue number:%d\"%a.value.u32)\n queue_num = a.value.u32\n if a.id == SAI_PORT_ATTR_QOS_QUEUE_LIST:\n for i in range(a.value.objlist.count):\n queueId_list.append(a.value.objlist.object_id_list[i])\n sys_logging(\"queue_oid[%d]:0x%X\"%(i, a.value.objlist.object_id_list[i]))\n attr_value = sai_thrift_attribute_value_t(oid=sched_oid_list[i%2])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[i], attr)\n #pdb.set_trace()\n warmboot(self.client)\n try:\n for ii in range(queue_num):\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[ii])\n for a in attrs.attr_list: \n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"Get queue[0x%x] scheduler Profile oid: 0x%x\"%(queueId_list[ii], a.value.oid))\n if a.value.oid != sched_oid_list[ii%2]:\n raise NotImplementedError() \n for i in range(8):\n attr_value = sai_thrift_attribute_value_t(oid=sched_oid_list[(i+1)%2])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[i], attr)\n #pdb.set_trace()\n for ii in range(queue_num):\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[ii])\n for a in attrs.attr_list: \n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"Get queue[0x%x] scheduler Profile oid: 0x%x\"%(queueId_list[ii], a.value.oid))\n if a.value.oid != sched_oid_list[(ii+1)%2]:\n raise NotImplementedError() \n finally:\n for i in range(queue_num):\n self.client.sai_thrift_remove_queue(queueId_list[i])\n self.client.sai_thrift_remove_scheduler_profile(sched_oid1)\n self.client.sai_thrift_remove_scheduler_profile(sched_oid2)","title":""},{"docid":"ebf01b91402a0f6f1ca89b4cb8261dcd","score":"0.56389487","text":"def runTest(self):\n sys_logging(\"start test\")\n switch_init(self.client)\n\n port = port_list[1]\n level = [0,1,2]\n max_childs = [4, 64, 8]\n sched_group_id_group_node = [None]*8\n\n\n sched_type1 = SAI_SCHEDULING_TYPE_STRICT\n sched_type2 = SAI_SCHEDULING_TYPE_DWRR\n sched_weight = 10\n cir = 2000000\n cbs = 256000\n pir = 1000000\n pbs = 64000\n queueId_list = []\n\n sched_oid1 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type1, 0, cir, cbs, pir, pbs)\n sys_logging(\"sched_oid_1 0x%x\"%sched_oid1)\n\n sched_oid2 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type2, sched_weight, cir, cbs, pir, pbs)\n sys_logging(\"sched_oid_1 0x%x\"%sched_oid2)\n sched_oid_list = [sched_oid1, sched_oid2]\n\n \n sched_group_id_root = sai_thrift_qos_create_scheduler_group(self.client, port, level[0], max_childs[0], port, 0)\n \n sched_group_id_chan_node = sai_thrift_qos_create_scheduler_group(self.client, port, level[1], max_childs[1], sched_group_id_root, 0)\n \n sched_group_id_group_node[0] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0) \n sched_group_id_group_node[1] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0)\n sched_group_id_group_node[2] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0)\n sched_group_id_group_node[3] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0)\n sched_group_id_group_node[4] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0) \n sched_group_id_group_node[5] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0)\n sched_group_id_group_node[6] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0)\n sched_group_id_group_node[7] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0)\n\n \n attrs = self.client.sai_thrift_get_port_attribute(port)\n for a in attrs.attr_list: \n if a.id == SAI_PORT_ATTR_QOS_NUMBER_OF_QUEUES:\n sys_logging(\"queue number:%d\"%a.value.u32)\n queue_num = a.value.u32\n if a.id == SAI_PORT_ATTR_QOS_QUEUE_LIST:\n for i in range(a.value.objlist.count):\n queueId_list.append(a.value.objlist.object_id_list[i])\n sys_logging(\"queue_oid[%d]:0x%X\"%(i, a.value.objlist.object_id_list[i]))\n\n sys_logging(\"=======set queue parent node profile=======\")\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[0])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[0], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[1])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[1], attr)\n self.client.sai_thrift_set_queue_attribute(queueId_list[2], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[3])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[3], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[4])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[4], attr)\n self.client.sai_thrift_set_queue_attribute(queueId_list[5], attr)\n self.client.sai_thrift_set_queue_attribute(queueId_list[6], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[7])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[7], attr)\n #pdb.set_trace()\n\n warmboot(self.client)\n try:\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[0])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[0]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[1])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[1]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[2])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[1]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[3])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[3]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[4])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[4]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[5])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[4]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[6])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[4]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[7])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[7]:\n raise NotImplementedError()\n\n sys_logging(\"=======set queue scheduler profile=======\")\n attr_value = sai_thrift_attribute_value_t(oid=sched_oid2)\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[1], attr)\n self.client.sai_thrift_set_queue_attribute(queueId_list[2], attr)\n self.client.sai_thrift_set_queue_attribute(queueId_list[4], attr)\n self.client.sai_thrift_set_queue_attribute(queueId_list[5], attr)\n self.client.sai_thrift_set_queue_attribute(queueId_list[6], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_oid1)\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[0], attr)\n self.client.sai_thrift_set_queue_attribute(queueId_list[3], attr)\n self.client.sai_thrift_set_queue_attribute(queueId_list[7], attr)\n\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[0])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid1:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[1])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid2:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[2])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid2:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[3])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid1:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[4])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid2:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[5])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid2:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[6])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid2:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[7])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\n sys_logging(\"get queue scheduler profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_oid1:\n raise NotImplementedError()\n\n\n sys_logging(\"=======remove queue parent node profile=======\")\n #pdb.set_trace()\n for ii in range(8):\n attr_value = sai_thrift_attribute_value_t(oid=0)\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[ii], attr)\n\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[0])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[1])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[2])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[3])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[4])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[5])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[6])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[7])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError()\n\n\n #pdb.set_trace()\n\n sys_logging(\"=======set queue parent node profile again=======\")\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[0])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[0], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[1])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[1], attr)\n self.client.sai_thrift_set_queue_attribute(queueId_list[2], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[3])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[3], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[4])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[4], attr)\n self.client.sai_thrift_set_queue_attribute(queueId_list[5], attr)\n self.client.sai_thrift_set_queue_attribute(queueId_list[6], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[7])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(queueId_list[7], attr)\n\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[0])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[0]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[1])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[1]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[2])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[1]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[3])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[3]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[4])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[4]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[5])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[4]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[6])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[4]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[7])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[7]:\n raise NotImplementedError()\n\n finally:\n\n #pdb.set_trace()\n for i in range(8):\n self.client.sai_thrift_remove_queue(queueId_list[i])\n\n for ii in range(8):\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_group_node[ii])\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_chan_node)\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_root)\n\n self.client.sai_thrift_remove_scheduler_profile(sched_oid1)\n self.client.sai_thrift_remove_scheduler_profile(sched_oid2)","title":""},{"docid":"e19b9979195fbdb29e7088afa802a59b","score":"0.5636245","text":"def send_task(self):\n packed = zlib.compress(cPickle.dumps(self.task_dict))\n encoded = base64.b64encode(packed)\n params_data = {\"task_data\":encoded}\n retry_options = taskqueue.TaskRetryOptions(\n task_retry_limit = self.task_retry_limit)\n the_task = taskqueue.Task(url=\"/task\", params=params_data,\n countdown = self.start_delay, retry_options = retry_options)\n the_task.add() \n #taskqueue.add(url=\"/task\", params=params_data) ","title":""},{"docid":"c9121915943e133cb0ecd8d178b3438e","score":"0.56360734","text":"def next_in_schedule(self):\n if len(self.execution_queue) > 0:\n now = rospy.get_rostime()\n next_task = self.execution_queue[0]\n # get travel time to next task. \n travel_time_to_next_task = self._travel_duration_fn(next_task.start_node_id)\n\n rospy.loginfo('start window: %s' % rostime_to_python(next_task.start_after).time())\n rospy.loginfo(' now: %s' % rostime_to_python(now).time())\n rospy.loginfo(' travel time: %s' % rosduration_to_python(travel_time_to_next_task))\n \n # the task can be executed if we can travel to the task in time for the\n # the start window to open\n if now >= (next_task.start_after - travel_time_to_next_task):\n rospy.loginfo('start window is open')\n self.execute_next_task()\n else: \n # delay is the difference between now and the time to start navigating\n exe_delay = (next_task.start_after - travel_time_to_next_task) - now\n rospy.loginfo('need to delay %s.%s for execution' % (exe_delay.secs, exe_delay.nsecs))\n self.current_task = None\n self.execution_delay_timer = rospy.Timer(exe_delay, self.execution_delay_cb, oneshot=True)\n else:\n self.current_task = None","title":""},{"docid":"85872894ea6da5ec2ca6a8f71360f951","score":"0.56329817","text":"def dequeue(self):\n pass","title":""},{"docid":"738215a11a3ceae0faf5085512e352ce","score":"0.56298023","text":"def commandPeriodic(self):\n self.scheduler.run()","title":""},{"docid":"89d792502ffdd9b809c144ae6a650680","score":"0.56293863","text":"def handle_queue(self):\n cmd, payload = self.queue.get()\n if cmd == 'connect':\n self.network.connect_to_node(payload['addr'], 'paxos_join_request')\n # TODO: add to self.paxos.peer_addresses\n elif cmd == 'first_connection':\n # self.network.connect_to_node(payload['addr'])\n self.network.broadcast({\n 'do': 'ping',\n })\n self.periodic_runner.register(watch_address_pool, {\n 'queue': self.queue,\n 'network': self.network,\n 'old': set(),\n }, 0.5)\n elif cmd == 'connect_to_sampled':\n picked = payload['picked']\n log.debug(\"picked: %s\", picked)\n for addr in picked:\n self.network.connect_to_node(addr)\n self.periodic_runner.unregister(watch_address_pool)\n elif cmd == 'start_paxos':\n if self.paxos is not None:\n self.paxos.start_paxos_round(payload['value'])\n else:\n raise ValueError('Unknown command: %s' % cmd)","title":""},{"docid":"04ac545de20b6de2f9134bf4e231bf5a","score":"0.56275237","text":"def __init__(self):\n\t\tself.queue = []\n\t\tself.poper = []","title":""},{"docid":"1674ebfbc119d61410be73cb43f6f664","score":"0.56234163","text":"def main():\n\n # Build data\n jobs = squeue(user='lmh1', # user id - change to your own\n name=['iprPy_1', 'iprPy_4']) # job names - change to your own\n logs = parse_runner_logs()\n rundirs, runners = check_run_directories()\n\n # Merge data\n logjobs = jobs.merge(logs, how='outer', on='jobid')\n logjobs.loc[(logjobs.status=='active') & (pd.isna(logjobs.user)), 'status'] = 'crashed'\n runlogjobs = logjobs.merge(runners, how='outer', on='pid')\n\n # Loop over all run directories\n keys = ['jobid', 'pid', 'status', 'time', 'calcid', 'tmpdir']\n for i in rundirs.index:\n rundir = rundirs.loc[i]\n\n # List number of prepared calculations and number of runners\n print(rundir.run_directory, rundir.numcalcs, rundir.numrunners)\n dirjobs = runlogjobs[runlogjobs.run_directory == rundir.run_directory]\n\n # Print data for runners\n if len(dirjobs) > 0:\n print(dirjobs[keys])\n print()\n\n # List jobs with no associated bid files (usually finished)\n print('Unknown/finished jobs')\n nodir = runlogjobs[pd.isna(runlogjobs.run_directory)][keys]\n with pd.option_context('display.max_rows', None,):\n print(nodir)\n\n # Delete run logs for successfully finished jobs\n for jobid in nodir[nodir.status=='finished'].jobid.values:\n Path(f'runner_{jobid}.txt').unlink()","title":""},{"docid":"5cd22b40a658528fd6f5e5c0ad09acae","score":"0.56176794","text":"def test_enqueue_at(self):\n queue = Queue(connection=self.testconn)\n registry = ScheduledJobRegistry(queue=queue)\n scheduler = RQScheduler([queue], connection=self.testconn)\n scheduler.acquire_locks()\n # Jobs created using enqueue_at is put in the ScheduledJobRegistry\n job = queue.enqueue_at(datetime(2019, 1, 1, tzinfo=timezone.utc), say_hello)\n self.assertEqual(len(queue), 0)\n self.assertEqual(len(registry), 1)\n\n # enqueue_at set job status to \"scheduled\"\n self.assertTrue(job.get_status() == 'scheduled')\n\n # After enqueue_scheduled_jobs() is called, the registry is empty\n # and job is enqueued\n scheduler.enqueue_scheduled_jobs()\n self.assertEqual(len(queue), 1)\n self.assertEqual(len(registry), 0)","title":""},{"docid":"e4b90ce4ac63d1fc3b70e270b44d071e","score":"0.56115574","text":"def collect(self):\n while True:\n time.sleep(2)\n logging.info(f'Maintain Queue Empty: {self._maintain_queue.empty()}')\n logging.info(f'Queue Empty: {self._queue.empty()}')\n if not self._queue.empty():\n message = self._queue.get()\n logging.info(f\"Popped off message from Queue: {message.entry_info}\")\n self.working_on = \"UPDATE\"\n elif not self._maintain_queue.empty():\n message = self._maintain_queue.get()\n logging.info(f\"Popped off message from Maintain Queue: {message.entry_info}\")\n self.working_on = \"MAINTAIN\"\n else:\n break\n\n if message.type == 'EXIT':\n break\n\n if message.type != 'TASK':\n raise ValueError(f'{message.type} is not a recognized task type')\n\n if message.type == 'TASK':\n try:\n github_url = message.entry_info['task']['given']['github_url']\n repo_id = message.entry_info['repo_id']\n self.query_pr({'github_url': github_url, 'repo_id': repo_id})\n except Exception:\n # logging.error(\"Worker ran into an error for task: {}\\n\".format(message.entry_info['task']))\n # logging.error(\"Error encountered: \" + str(e) + \"\\n\")\n # # traceback.format_exc()\n # logging.info(\"Notifying broker and logging task failure in database...\\n\")\n\n logging.exception(f'Worker ran into an error for task {message.entry_info}')\n self.register_task_failure(message.entry_info['repo_id'],\n message.entry_info['task']['given']['github_url'])\n\n # Add to history table\n task_history = {\n \"repo_id\": message.entry_info['repo_id'],\n \"worker\": self.config['id'],\n \"job_model\": message.entry_info['task']['models'][0],\n \"oauth_id\": self.config['zombie_id'],\n \"timestamp\": datetime.datetime.now(),\n \"status\": \"Error\",\n \"total_results\": self.results_counter\n }\n\n if self.history_id:\n self.helper_db.execute(self.history_table.update().where(self.history_table.c.history_id==self.history_id).values(task_history))\n else:\n r = self.helper_db.execute(self.history_table.insert().values(task_history))\n self.history_id = r.inserted_primary_key[0]\n\n logging.info(f\"Recorded job error for: {message.entry_info['task']}\")\n\n # Update job process table\n updated_job = {\n \"since_id_str\": message.entry_info['repo_id'],\n \"last_count\": self.results_counter,\n \"last_run\": datetime.datetime.now(),\n \"analysis_state\": 0\n }\n self.helper_db.execute(self.job_table.update().where(self.job_table.c.job_model==message.entry_info['task']['models'][0]).values(updated_job))\n logging.info(\"Updated job process for model: \" + message.entry_info['task']['models'][0] + \"\\n\")\n\n # Reset results counter for next task\n self.results_counter = 0\n pass","title":""},{"docid":"94336d720287cddcd9005360a1490fd6","score":"0.5610968","text":"def run_queue(self):\n\n #FIXME: need a finally here to cleanup exceptions states\n lqueue = self.chunk_queue(self.command_queue)\n self.run_command_queue(lqueue)\n\n del self.command_queue[:]\n self.memo_map.clear()","title":""},{"docid":"c51fe701898c1a3e0c07a6917fd0341a","score":"0.56016207","text":"def monitor_task_queue(self):\n\n self.handle_new_tasks()","title":""},{"docid":"d546bf86e6a677575961e6b11e020bf9","score":"0.559495","text":"def agentbehavior1(queue):\n pass","title":""},{"docid":"66edc80b7c52d3f24c17d2c5c9e12602","score":"0.5594344","text":"def run(self, *args, **kwargs):\n self.config_json = args[1]\n self.task_id = self.request.id\n self.temp_iviu = {\n \"database\":self.config_json['mysql']['db'],\n \"table\":\"p00390\",\n \"type\":\"insert\",\n \"ts\":1527621106,\n \"xid\":1784748,\n \"commit\":True,\n \"data\": \"\"\n }\n self.redis_conn = None\n self.redis_connections = {}\n self.net = CheckNet()\n self.retry_count = 0\n self.err_flag = False\n self.email_flag =True\n self.start()\n # print(\"tt in run method\",args[2])\n if len(args) == 3:\n self.thread_each_table(args[0],args[2])\n else:\n self.thread_each_table(args[0], \"\")","title":""},{"docid":"e6d17fda6177fe2ce267ae69d19db552","score":"0.5593024","text":"def test_start_requeue(self):\n pass","title":""},{"docid":"c17feb99867e2b14d923b20e64b9c1c0","score":"0.55925614","text":"def __init__( self ):\n\n # Create the queue\n self.queue = Queue.Queue()\n\n # Set up the GUI part\n self.gui_manager = tbh_gui_manager( self.queue, self.endApplication )\n self.gui_manager.show()\n \n self.data_viz_queue = Queue.Queue()\n \n self.pomdp_data_viz = tbh_pomdp_data_viz.tbh_pomdp_data_viz_t( \\\n self.queue, self.endApplication )\n self.pomdp_data_viz.show()\n #self.gui.console.show()\n\n # A timer to periodically call periodicCall :-)\n self.queue_timer = PyQt4.QtCore.QTimer()\n\n # Start the timer -- this replaces the initial call \n # to periodicCall\n self.queue_timer.start(100)\n PyQt4.QtCore.QObject.connect(self.queue_timer, PyQt4.QtCore.SIGNAL(\"timeout()\"), \\\n self.periodicCall)\n\n\n\n # Set up the thread to do asynchronous I/O\n # More can be made if necessary\n self.running = 1\n \n \tself.thread = threading.Thread( target=self.worker_thread )\n self.thread.start()\n\n # Start the periodic call in the GUI to check if the queue contains\n # anything\n self.periodicCall()","title":""},{"docid":"d2c4295c672872fd4813356a760b166d","score":"0.5592507","text":"def add_job(self, func, *args):\n self.queue.append((func, args))","title":""},{"docid":"32ac073776ac841780639545fd8c3812","score":"0.5590981","text":"def runTest(self):\n sys_logging(\"start test\")\n switch_init(self.client)\n\n port = port_list[1]\n level = [0,1,2]\n max_childs = [4, 64, 8]\n sched_group_id_group_node = [None]*8\n sched_group_service_id = 1\n service_queueId = [None]*8\n\n\n sched_type1 = SAI_SCHEDULING_TYPE_STRICT\n sched_type2 = SAI_SCHEDULING_TYPE_DWRR\n sched_weight = 10\n cir = 2000000\n cbs = 256000\n pir = 1000000\n pbs = 64000\n\n sched_oid1 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type1, 0, cir, cbs, pir, pbs)\n sys_logging(\"sched_oid_1 0x%x\"%sched_oid1)\n\n sched_oid2 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type2, sched_weight, cir, cbs, pir, pbs)\n sys_logging(\"sched_oid_1 0x%x\"%sched_oid2)\n sched_oid_list = [sched_oid1, sched_oid2]\n\n \n sched_group_id_root = sai_thrift_qos_create_scheduler_group(self.client, port, level[0], max_childs[0], port, 0)\n \n sched_group_id_chan_node = sai_thrift_qos_create_scheduler_group(self.client, port, level[1], max_childs[1], sched_group_id_root, 0)\n \n sched_group_id_group_node[0] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id) \n sched_group_id_group_node[1] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\n sched_group_id_group_node[2] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\n sched_group_id_group_node[3] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\n sched_group_id_group_node[4] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id) \n sched_group_id_group_node[5] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\n sched_group_id_group_node[6] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\n sched_group_id_group_node[7] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\n\n \n queue_type = SAI_QUEUE_TYPE_SERVICE\n queue_index = [0,1,2,3,4,5,6,7]\n service_queueId[0] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[0], parent_id=sched_group_id_group_node[0], service_id=sched_group_service_id, sche_id=sched_oid1) \n service_queueId[1] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[1], parent_id=sched_group_id_group_node[1], service_id=sched_group_service_id, sche_id=sched_oid2)\n service_queueId[2] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[2], parent_id=sched_group_id_group_node[1], service_id=sched_group_service_id, sche_id=sched_oid2)\n service_queueId[3] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[3], parent_id=sched_group_id_group_node[3], service_id=sched_group_service_id, sche_id=sched_oid1)\n service_queueId[4] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[4], service_id=sched_group_service_id, sche_id=sched_oid2)\n service_queueId[5] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[5], service_id=sched_group_service_id, sche_id=sched_oid2)\n service_queueId[6] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[6], service_id=sched_group_service_id, sche_id=sched_oid2)\n service_queueId[7] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[7], service_id=sched_group_service_id, sche_id=sched_oid1)\n #pdb.set_trace()\n\n warmboot(self.client)\n try:\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[0])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[0]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[1])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[1]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[2])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[1]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[3])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[3]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[4])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[5])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[6])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[7])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != SAI_NULL_OBJECT_ID:\n raise NotImplementedError()\n\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[4])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(service_queueId[4], attr)\n self.client.sai_thrift_set_queue_attribute(service_queueId[5], attr)\n self.client.sai_thrift_set_queue_attribute(service_queueId[6], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[7])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(service_queueId[7], attr)\n \n \n\n\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[0])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[0]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[1])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[1]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[2])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[1]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[3])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[3]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[4])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[4]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[5])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[4]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[6])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[4]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[7])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[7]:\n raise NotImplementedError()\n\n\n for ii in range(8):\n attr_value = sai_thrift_attribute_value_t(oid=0)\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(service_queueId[ii], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[0])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(service_queueId[0], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[1])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(service_queueId[1], attr)\n self.client.sai_thrift_set_queue_attribute(service_queueId[2], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[3])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(service_queueId[3], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[4])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(service_queueId[4], attr)\n self.client.sai_thrift_set_queue_attribute(service_queueId[5], attr)\n self.client.sai_thrift_set_queue_attribute(service_queueId[6], attr)\n\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[7])\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(service_queueId[7], attr)\n\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[0])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[0]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[1])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[1]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[2])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[1]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[3])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[3]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[4])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[4]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[5])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[4]:\n raise NotImplementedError()\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[6])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[4]:\n raise NotImplementedError() \n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[7])\n assert(SAI_STATUS_SUCCESS == attrs.status)\n for a in attrs.attr_list:\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\n sys_logging(\"get queue parent node profile:0x%x\"%a.value.oid)\n if a.value.oid != sched_group_id_group_node[7]:\n raise NotImplementedError()\n\n finally:\n #pdb.set_trace()\n for ii in range(8):\n attr_value = sai_thrift_attribute_value_t(oid=0)\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\n self.client.sai_thrift_set_queue_attribute(service_queueId[ii], attr)\n\n #pdb.set_trace()\n for i in range(8):\n self.client.sai_thrift_remove_queue(service_queueId[i])\n\n for ii in range(8):\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_group_node[ii])\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_chan_node)\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_root)\n\n self.client.sai_thrift_remove_scheduler_profile(sched_oid1)\n self.client.sai_thrift_remove_scheduler_profile(sched_oid2)","title":""},{"docid":"3909cc076c9fbb71777323f5ac029dce","score":"0.5588554","text":"def requeue(self):\n log.info('Requeueing the task')\n taskmanager.crawlNow(connector_instance_ids =[self.task.connector_instance_id],\n workspace_id=self.task.workspace_id)","title":""},{"docid":"1c7fc3cadc529fbb0aa73b5413c2ba10","score":"0.55814713","text":"def dequeue_actions(self):\n dequeued = []\n for task in self.get_todo():\n cmd = self.format_cmd(task[\"action\"], task[\"path\"], task[\"rids\"])\n log_cmd = self.format_log_cmd(task[\"action\"], task[\"path\"], task[\"rids\"])\n self.log.info(\"run '%s' queued %s ago\", \" \".join(log_cmd), print_duration(self.now - task[\"queued\"]))\n self.exec_action(task[\"sigs\"], cmd)\n dequeued += task[\"sigs\"]\n self.delete_queued(dequeued)","title":""},{"docid":"407a566ef3fdc17b0ba8b79245e5d803","score":"0.5576157","text":"def setupCmdQueue(self):\n raise NotImplementedError","title":""},{"docid":"bf53116b6fda45c5c50f7183253490f6","score":"0.55741537","text":"def _execute(self):\n\t\traise NotImplementedError(\"Task handlers must override _execute\")","title":""},{"docid":"c50f24e8dab399fdce369b39ee4823d0","score":"0.556992","text":"def refresh(self):\n self.queue.sort(key=lambda x: x.exe_time)\n self.catch_up()","title":""},{"docid":"9d645f21808d504b03f92a5372717b6d","score":"0.556369","text":"def processQueueAsync(self):\n print(\"Plotter process started\")\n self.mcq = MotorCtrlQueue(self.config)\n self.mcq.start()\n\n i = 0\n item = self.workerQueue.get()\n start = time.time()\n while(item is not None):\n\n self.executeCmd(item)\n\n i += 1\n if i % 1000 == 0:\n print(\"Processed %d commands. %f ms per cmd. \" %\n (i, (time.time() - start)*1000/i))\n\n item = self.workerQueue.get()\n\n # Wait for stepper queue\n self.mcq.join()\n print(\"Plotter process stopped\")\n exit(0)","title":""},{"docid":"13d9f8d58e85192394c4cd085a2cb146","score":"0.5563209","text":"def pre_schedule(worker, job):\n data = pickle.loads(job.data)\n #print data\n s = requests.Session()\n \n task_r = s.get(\"http://localhost:8001\"+data[\"task\"])\n print \"doing:\", data[\"task\"]\n task_js = json.loads(task_r.text)\n \n function = task_js[\"async_function\"]\n \n input_dataset = json.loads(s.get(\"http://localhost:8001\"+data[\"input_dataset\"]).text)\n output_dataset = json.loads(s.get(\"http://localhost:8001\"+data[\"output_dataset\"]).text)\n \n input_dataset_id = input_dataset[\"id\"]\n output_dataset_id = output_dataset[\"id\"]\n \n \n #print input_columns\n #print output_column\n #print function\n #print input_dataset\n #print output_dataset\n \n \n #schedule\n count = input_dataset[\"datapoint_count\"]\n \n #TODO bucket list is \"hardcoded\" here. find some other way to do that\n bucket_list = \",\".join([\"'\"+str(input_dataset_id)+\"-\"+str(c)+\"'\" for c in xrange(1+int(count/10000))])\n \n \n table = \"tsstore\"\n \n lowest_time = input_dataset[\"lowest_ts\"]\n highest_time = input_dataset[\"highest_ts\"]\n \n #partition time buckets\n date_format = \"%Y-%m-%d %H:%M:%S.%f\"\n lt = datetime.datetime.strptime(lowest_time, date_format)-datetime.timedelta(microseconds=1)\n ht = datetime.datetime.strptime(highest_time, date_format)\n diff = ht-lt\n \n #TODO change to some other value during production\n batch_size = 10\n \n try:\n interval = task_js[\"interval_in_seconds\"]\n #is aggregation\n print \"is aggregation\"\n IS_CALCULATION = False\n num_tasks = int(diff.total_seconds()/interval)\n \n cols = []\n dims_with_cols = []\n for dim in input_dataset[\"dimensions\"]:\n col_r = s.get(\"http://localhost:8001\"+dim)\n jreq = json.loads(col_r.text)[\"ts_column\"]\n cols.append(jreq)\n dims_with_cols.append(DimWithCol(dim, jreq))\n \n output_column = cols[0]\n input_columns = cols[1:]\n \n \n except KeyError:\n #is calculation\n print \"is calculation\"\n IS_CALCULATION = True\n cluster = Cluster(data[\"cassandra_nodes\"])\n session = cluster.connect('ws')\n stmt = \"select count(*) from tsstore where bucket in (%s) and dataset=%s;\" % (bucket_list, input_dataset_id)\n row = session.execute(stmt)\n count = row[0]._asdict()[\"count\"]\n \n session.shutdown()\n \n output_dimension = s.get(\"http://localhost:8001\"+task_js[\"output_dimension\"])\n output_column = json.loads(output_dimension.text)[\"ts_column\"]\n \n input_dimensions = task_js[\"input_dimensions\"]\n input_columns = []\n for ic in input_dimensions:\n ic_r = s.get(\"http://localhost:8001\"+ic)\n input_columns.append(json.loads(ic_r.text)[\"ts_column\"])\n interval = (diff.total_seconds()*batch_size)/count\n num_tasks = int(count/batch_size)\n \n #print interval\n #print count/batch_size\n \n #update task_count\n task_update_callback(data[\"task_id\"], int(num_tasks))\n \n temp_ht = lt+datetime.timedelta(seconds=interval)+datetime.timedelta(microseconds=1)\n lt -= datetime.timedelta(microseconds=1)\n lowest_time = datetime.datetime.strftime(lt, date_format)\n highest_time = datetime.datetime.strftime(temp_ht, date_format)\n \n #while True:\n for XX in xrange(num_tasks+2):\n stmt = \"select %s,dataset,bucket from %s where bucket in (%s) and time >= '%s' AND time <= '%s' and dataset=%s order by dataset, time;\" % (\",\".join(input_columns+[output_column]+([\"time\"] if IS_CALCULATION else [])), table, bucket_list, lowest_time, highest_time, input_dataset_id)\n print stmt\n print num_tasks+1, XX\n #create job with previous stmt\n dat = {}\n dat[\"stmt\"] = stmt\n dat[\"function\"] = function\n dat[\"output_column\"] = output_column\n dat[\"output_dataset\"] = data[\"output_dataset\"]\n dat[\"task_id\"] = data[\"task_id\"]\n dat[\"cassandra_nodes\"] = data[\"cassandra_nodes\"]\n client = GearmanClient(JOBSERVER_LIST)\n try:\n interval = task_js[\"interval_in_seconds\"]\n #is aggregation\n #dat[\"input_columns\"] = input_columns+[output_column]\n dat[\"input_dimensions\"] = dims_with_cols\n \n client.submit_job(\"row_aggregator\", pickle.dumps(dat),background=True)\n except KeyError:\n #is calculation\n dat[\"output_dimension\"] = task_js[\"output_dimension\"]\n client.submit_job(\"row_calculator\", pickle.dumps(dat),background=True)\n \n #st = statsd.StatsClient(\"192.168.149.161\",8125)\n #st.incr(\"task_created\")\n\n #update timestamps\n lt += datetime.timedelta(seconds=interval)+datetime.timedelta(microseconds=1)\n temp_ht += datetime.timedelta(seconds=interval)+datetime.timedelta(microseconds=1)\n \n lowest_time = datetime.datetime.strftime(lt, date_format)\n highest_time = datetime.datetime.strftime(temp_ht, date_format)\n print lowest_time\n print highest_time\n \n #if lt > ht:\n # break\n \n return \"a\"","title":""},{"docid":"72fe02423100850a617257dca48ea999","score":"0.5562906","text":"def test_queue_and_jobs_6(self):\n output = \"\"\"\n [0] queue (sftp://someone:@localhost) -- 252 B/s\n sftp://someone:@localhost/home/someone\n Now executing: [1] mirror -c /tmp/test_controllerbsn4wlu2/remote/ra /tmp/test_controllerbsn4wlu2/local/ -- 249/8.2k (3%) 100 B/s\n -[2] mirror -c /tmp/test_controllerbsn4wlu2/remote/rb /tmp/test_controllerbsn4wlu2/local/ -- 374/9.3k (4%) 153 B/s\n Commands queued:\n 1. pget -c \"/tmp/test_controllerbsn4wlu2/remote/rc\" -o \"/tmp/test_controllerbsn4wlu2/local/\" \n [1] mirror -c /tmp/test_controllerbsn4wlu2/remote/ra /tmp/test_controllerbsn4wlu2/local/ -- 249/8.2k (3%) 100 B/s\n \\\\transfer `raa' \n `raa' at 238 (23%) 100b/s eta:8s [Receiving data]\n \\mirror `rab' -- 0/7.2k (0%)\n \\\\transfer `rab/raba' \n `raba' at 0 (0%) [Connecting...]\n \\\\transfer `rab/rabb' \n `rabb' at 0 (0%) [Waiting for response...]\n [2] mirror -c /tmp/test_controllerbsn4wlu2/remote/rb /tmp/test_controllerbsn4wlu2/local/ -- 374/9.3k (4%) 153 B/s\n \\\\transfer `rba' \n `rba' at 159 (3%) 77b/s eta:51s [Receiving data]\n \\\\transfer `rbb' \n `rbb' at 153 (2%) 76b/s eta:66s [Receiving data]\n \"\"\"\n parser = LftpJobStatusParser()\n statuses = parser.parse(output)\n golden_queue = [\n LftpJobStatus(job_id=1,\n job_type=LftpJobStatus.Type.PGET,\n state=LftpJobStatus.State.QUEUED,\n name=\"rc\",\n flags=\"-c\"),\n ]\n golden_job1 = LftpJobStatus(job_id=1,\n job_type=LftpJobStatus.Type.MIRROR,\n state=LftpJobStatus.State.RUNNING,\n name=\"ra\",\n flags=\"-c\")\n golden_job1.total_transfer_state = LftpJobStatus.TransferState(249, 8396, 3, 100, None)\n golden_job1.add_active_file_transfer_state(\"raa\", LftpJobStatus.TransferState(None, None, None, 100, 8))\n golden_job1.add_active_file_transfer_state(\"rab/raba\", LftpJobStatus.TransferState(None, None, None, None, None))\n golden_job1.add_active_file_transfer_state(\"rab/rabb\", LftpJobStatus.TransferState(None, None, None, None, None))\n golden_job2 = LftpJobStatus(job_id=2,\n job_type=LftpJobStatus.Type.MIRROR,\n state=LftpJobStatus.State.RUNNING,\n name=\"rb\",\n flags=\"-c\")\n golden_job2.total_transfer_state = LftpJobStatus.TransferState(374, 9523, 4, 153, None)\n golden_job2.add_active_file_transfer_state(\"rba\", LftpJobStatus.TransferState(None, None, None, 77, 51))\n golden_job2.add_active_file_transfer_state(\"rbb\", LftpJobStatus.TransferState(None, None, None, 76, 66))\n golden_jobs = [golden_job1, golden_job2]\n self.assertEqual(len(golden_queue)+len(golden_jobs), len(statuses))\n statuses_queue = [j for j in statuses if j.state == LftpJobStatus.State.QUEUED]\n self.assertEqual(golden_queue, statuses_queue)\n statuses_jobs = [j for j in statuses if j.state == LftpJobStatus.State.RUNNING]\n self.assertEqual(golden_jobs, statuses_jobs)","title":""},{"docid":"46d7b2de353ab41d78a49c531dc0261c","score":"0.55613804","text":"def queue_events(self, timeout):","title":""},{"docid":"2e7a152416156e0115c320ac03961d63","score":"0.5554936","text":"def _init_queue(self):\n self.queue.put((do_page_parse, self.root_url))","title":""},{"docid":"d81c7b030e4380ac69de85200441b370","score":"0.5553766","text":"def submit(self):\n \n if len(self.queue) == 0:\n raise Exception(\"There are no script to be submitted to the queue\\n did you run create_scripts?\")\n\n for queueFileName in self.queue:\n os.system(\"qsub \" + queueFileName)","title":""},{"docid":"a1e0ae997b610f20c6917c185ee971c9","score":"0.5550807","text":"def main_task():\n\n interval = 5\n apis = Scheduler.get_apis()\n for api in apis:\n class_name = api.api_class.split('.')[2]\n sched.add_job(Scheduler.fetch_data, 'interval',\n name='{}'.format(api.name),\n seconds=api.refresh_time,\n start_date=datetime.now()+timedelta(\n minutes=interval),\n end_date=datetime.now()+timedelta(hours=23),\n args=[api.api_class, api.name],\n replace_existing=True, id='{}'.format(class_name),\n jobstore='sqlalchemy', misfire_grace_time=300)\n interval += interval","title":""}],"string":"[\n {\n \"docid\": \"ee659d2f4dda0e351f0bd89aaa2c9951\",\n \"score\": \"0.6921316\",\n \"text\": \"def processQueue(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"09982e5cbe4c7df30fe4ae28f60d7e1f\",\n \"score\": \"0.6735559\",\n \"text\": \"def scheduler(self):\\n j = self.updater.job_queue\\n print('getting daily queue')\\n for hour in range(24):\\n j.run_daily(\\n self.reminder, \\n days=(0, 1, 2, 3, 4, 5, 6), \\n time=datetime.time(hour=hour, minute=0, second=0))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bf97de4d4a319c49c9bf54fa22625dc4\",\n \"score\": \"0.6597712\",\n \"text\": \"def submit_task(d, queued_engine):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"23e1185fb8d5270a667d4e2d3257f59e\",\n \"score\": \"0.65356296\",\n \"text\": \"def schedule(self) -> TaskSchedulerResult:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"39d6c7f5c1bc044182218688a4d86895\",\n \"score\": \"0.64829427\",\n \"text\": \"async def _scheduler(self) -> None:\\n while True:\\n results = await self.broker.process_schedule()\\n logger.info(\\\"poll-schedule\\\", executor=self.executor_id, results=results)\\n await anyio.sleep(self.settings.schedule_interval)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9f1871234406722881c04af1ec3fb7aa\",\n \"score\": \"0.64672405\",\n \"text\": \"def QueueAction(self):\\r\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"248113746a5f9e7b8974a9405b25fadd\",\n \"score\": \"0.64446646\",\n \"text\": \"def submit_to_queue(self, script_file):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8614344a5e5d515b7cc39eff0c3a0201\",\n \"score\": \"0.63791\",\n \"text\": \"def postQueueSetup(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"001f189f2d2be78455aa44477059109e\",\n \"score\": \"0.63419634\",\n \"text\": \"def schedule():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"001f189f2d2be78455aa44477059109e\",\n \"score\": \"0.63419634\",\n \"text\": \"def schedule():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fb9ce3e8b6a59bb826188d077a4f8427\",\n \"score\": \"0.6271516\",\n \"text\": \"def scheduling_step(self):\\n self.qNetwork.scheduler.step()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"72fbb8bbe0b7777160730aa42e485ff0\",\n \"score\": \"0.6236307\",\n \"text\": \"def pre_task(d, queued_engine):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d177ee87680f989087422d21a082a222\",\n \"score\": \"0.6169855\",\n \"text\": \"def q_handler(self, queue):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5721e445d2d0d490b274d7a059fba8fa\",\n \"score\": \"0.61419314\",\n \"text\": \"def execute(obj, queue, restaurant):\\n mean_a = 1000\\n std_a = 200\\n queue._queue.append(obj)\\n if obj.q_type == 2:\\n restaurant.groups.append(obj)\\n restaurant.next_appearance_time = restaurant.simulation_time + abs(int(np.random.normal(mean_a, std_a)))\\n obj.appearance_time = restaurant.simulation_time\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0155284ce73c99d5d0f469d3b8e58334\",\n \"score\": \"0.61335665\",\n \"text\": \"def execute(self):\\n self.queue_command('execute')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bbb39cde6a4e2601ecbeebc511beffc6\",\n \"score\": \"0.61177796\",\n \"text\": \"def q_handler(queue):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"064201ebbc9fd7b319e41af363cb1595\",\n \"score\": \"0.60882354\",\n \"text\": \"def runTask(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8cbdbd93f2c1fdddea5994cba197e3d4\",\n \"score\": \"0.6071057\",\n \"text\": \"def publish_schedule(self):\\n while not rospy.is_shutdown():\\n # all encompassing try/catch to make sure this loop does not go down\\n try:\\n\\n # copy all relevant entries under lock \\n # we're taking a deepcopy as we might mess around with the times a bit\\n with self.state_lock:\\n expected_completion_time = deepcopy(self.expected_completion_time)\\n active_batch = deepcopy(self.active_batch)\\n normal_tasks = deepcopy(self.normal_tasks)\\n time_critical_tasks = deepcopy(self.time_critical_tasks)\\n\\n now = rospy.get_rostime()\\n # todo: fill this value better\\n expected_end_of_batch = rospy.get_rostime() + rospy.Duration(120)\\n\\n # start from the time_cr\\n schedule = ExecutionStatus(currently_executing = len(active_batch) > 0)\\n all_tasks = ExecutionStatus(currently_executing = len(active_batch) > 0)\\n\\n schedule.header.stamp = now\\n all_tasks.header.stamp = now\\n\\n for m in active_batch:\\n m.task.execution_time = now\\n schedule.execution_queue.append(m.task)\\n all_tasks.execution_queue.append(m.task)\\n\\n\\n # schedule.execution_queue += [m.task for m in time_critical_tasks]\\n all_tasks.execution_queue += [m.task for m in time_critical_tasks]\\n\\n all_tasks.execution_queue += [m.task for m in normal_tasks] \\n all_tasks.execution_queue = sorted(all_tasks.execution_queue, key=lambda x: x.start_after) \\n all_tasks.execution_queue = sorted(all_tasks.execution_queue, key=lambda x: x.priority) \\n\\n\\n self.schedule_publisher.publish(schedule) \\n self.all_tasks_schedule_publisher.publish(all_tasks)\\n\\n self.update_schedule_condition.acquire()\\n self.update_schedule_condition.wait()\\n self.update_schedule_condition.release()\\n except Exception, e:\\n rospy.logwarn('Caught exception in publish_schedule loop: %s' % e)\\n rospy.sleep(1)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"38fc6dd831a44eb5074059472f95b7c7\",\n \"score\": \"0.6069418\",\n \"text\": \"def post_task(d, queued_engine):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"875d8cfcb4347b491c2a6203b931d6f8\",\n \"score\": \"0.60506755\",\n \"text\": \"def boss():\\n\\n for i in xrange(1,10):\\n task_queue.put(i)\\n print('Assigned all work in iteration 1')\\n\\n for i in xrange(10,20):\\n task_queue.put(i)\\n print('Assigned all work in iteration 2')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5b34c60faf976bca2db206ef0b3b9e4e\",\n \"score\": \"0.603343\",\n \"text\": \"def work_queue(q):\\n global agent_data\\n global listing_data\\n global office_data\\n if(agent_data):\\n q.put(agent_data)\\n time.sleep(0.1)\\n if(listing_data):\\n q.put(listing_data)\\n time.sleep(0.1)\\n if(office_data):\\n q.put(office_data)\\n time.sleep(0.1)\\n q.join()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6b118992b9444c8e05303ad1bf98525d\",\n \"score\": \"0.6030745\",\n \"text\": \"def worker(name, queue, results):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0c7fc06973f069f1ba4b0b84046c4e92\",\n \"score\": \"0.602613\",\n \"text\": \"def __init__(self):\\r\\n self.queue = []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e089a5135da4ce04f50dcc5a56ba7f97\",\n \"score\": \"0.6015598\",\n \"text\": \"def _queueDispatchNormal(self, nextEvent, queue=True, countdown=0, retryOptions=None, queueName=None):\\r\\n assert nextEvent is not None\\r\\n assert queueName\\r\\n \\r\\n url = self.buildUrl(self.currentState, nextEvent)\\r\\n params = self.buildParams(self.currentState, nextEvent)\\r\\n taskName = self.getTaskName(nextEvent)\\r\\n \\r\\n task = Task(name=taskName, method=self.method, url=url, params=params, countdown=countdown,\\r\\n retry_options=retryOptions, headers=self.headers)\\r\\n if queue:\\r\\n self.Queue(name=queueName).add(task)\\r\\n \\r\\n return task\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e089a5135da4ce04f50dcc5a56ba7f97\",\n \"score\": \"0.6015598\",\n \"text\": \"def _queueDispatchNormal(self, nextEvent, queue=True, countdown=0, retryOptions=None, queueName=None):\\r\\n assert nextEvent is not None\\r\\n assert queueName\\r\\n \\r\\n url = self.buildUrl(self.currentState, nextEvent)\\r\\n params = self.buildParams(self.currentState, nextEvent)\\r\\n taskName = self.getTaskName(nextEvent)\\r\\n \\r\\n task = Task(name=taskName, method=self.method, url=url, params=params, countdown=countdown,\\r\\n retry_options=retryOptions, headers=self.headers)\\r\\n if queue:\\r\\n self.Queue(name=queueName).add(task)\\r\\n \\r\\n return task\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9165fb63c6af7adf8ccaa633cfde4dcc\",\n \"score\": \"0.60065794\",\n \"text\": \"def create_executor():\",\n \"title\": \"\"\n },\n {\n \"docid\": \"931a6cef09618f687c54fd50f221853d\",\n \"score\": \"0.6002376\",\n \"text\": \"def runMovementExecutor(ctrlQueue):\\n ctrlQueue.processMovementAsync()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fc5981bd695bd8d18f8d894cd71e5336\",\n \"score\": \"0.59982544\",\n \"text\": \"def __init__(self):\\n self.queue = []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fc5981bd695bd8d18f8d894cd71e5336\",\n \"score\": \"0.59982544\",\n \"text\": \"def __init__(self):\\n self.queue = []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fc5981bd695bd8d18f8d894cd71e5336\",\n \"score\": \"0.59982544\",\n \"text\": \"def __init__(self):\\n self.queue = []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dde6721867ea81c6b064153479d33d58\",\n \"score\": \"0.59972245\",\n \"text\": \"def submit(self, func=_ping, *args):\\n self.queue.put((func, args))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"87ec4ff646818ad7d4040082c3d00252\",\n \"score\": \"0.5976356\",\n \"text\": \"def __init__(self):\\n\\n self.queue = []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"65a827e4934eb428c0fde4b7914992d7\",\n \"score\": \"0.5974972\",\n \"text\": \"def start_tasks(automatic_tasks):\\n scheduler = AsyncIOScheduler()\\n print('Started Chron Monitors')\\n # scheduler.add_job(automatic_tasks.block_monitor,CronTrigger(hour='02',second='02'), misfire_grace_time=2,\\n # max_instances=20)\\n #\\n # scheduler.add_job(automatic_tasks.send_dpops_stats,\\n # CronTrigger(minute='00'), misfire_grace_time=2, max_instances=20)\\n #\\n # scheduler.add_job(automatic_tasks.delegate_ranks, CronTrigger(hour='02', second='02'), misfire_grace_time=2,\\n # max_instances=20)\\n scheduler.add_job(automatic_tasks.delegate_last_block_check,\\n CronTrigger(minute='02,04,06,08,10,12,14,16,18,20,22,24,26,'\\n '28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58'), misfire_grace_time=2,\\n max_instances=20)\\n\\n\\n\\n scheduler.start()\\n print('Started Chron Monitors : DONE')\\n return scheduler\",\n \"title\": \"\"\n },\n {\n \"docid\": \"aa413d93a525947e668840285f42e92d\",\n \"score\": \"0.59666026\",\n \"text\": \"def run(self):\\n while self.frame_number <= self.max_frame_number or not self.run_queue.empty():\\n \\n # get a frame when frame period arrives\\n if self.time % self.frame_period == 0:\\n self.frame_arrival(self.frame_number)\\n self.frame_number = self.frame_number + 1\\n\\n # if there are tasks in the run queue\\n if not self.run_queue.empty():\\n top_task = self.run_queue.queue[0]\\n top_task.remain_time = top_task.remain_time - 1\\n\\n # if the task has finished\\n if top_task.remain_time == 0:\\n task = self.run_queue.get()\\n self.task_finish_count = self.task_finish_count + 1\\n task.order = self.task_finish_count\\n # add 1 because self.time start from 0\\n task.response_time = self.time - task.enqueue_time + 1\\n if task.response_time > task.deadline:\\n task.missed = 1\\n\\n self.history.append(task)\\n # you can comment out the following line to skip yolo for shorter program runtime\\n #self.run_yolo(task)\\n \\n self.time = self.time + 1\\n \\n # save scheduling history to file\\n self.save_history()\\n print(\\\"Scheduling history saved.\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c7efaa6ddd630ba65c6ead98eef8f7ed\",\n \"score\": \"0.5962126\",\n \"text\": \"def run(self):\\n try:\\n quit_request_detected = False\\n while True:\\n aFunction, arguments = self.manager.task_queue.get()\\n if aFunction is None:\\n break\\n if quit_request_detected:\\n continue\\n try:\\n try:\\n args, kwargs = arguments\\n except ValueError:\\n args = arguments\\n kwargs = {}\\n aFunction(*args, **kwargs) # execute the task\\n except Exception:\\n self.config.logger.error(\\\"Error in processing a job\\\",\\n exc_info=True)\\n except KeyboardInterrupt:\\n self.config.logger.info('quit request detected')\\n quit_request_detected = True\\n #thread.interrupt_main() # only needed if signal handler\\n # not registerd\\n except Exception:\\n self.config.logger.critical(\\\"Failure in task_queue\\\", exc_info=True)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"22d1414bf9d5982b58b1f244b0c65774\",\n \"score\": \"0.5945777\",\n \"text\": \"def put( self ):\\r\\n BUY_QUEUE_DB.createQueue( self )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6c41ee7cfb6588e82aa8a85961bb28b4\",\n \"score\": \"0.59050715\",\n \"text\": \"def execute(self, evq):\\n\\n\\t\\t# can't send if it's busy sending - and doesn't have a unit available for all transmissions\\n\\t\\tbw = int(self.node.available_bandwidth()/self.concurr)\\n\\t\\tif bw < cfg.NODE_BANDWIDTH_UNIT:\\n\\t\\t\\treturn None\\n\\t\\t# then pop the last task we got\\n\\t\\tt = self.node.pop_task_to_send(self.k, self.time)\\n\\t\\t# if it's an invalid choice return without sending out the task\\n\\t\\tif t == None:\\n\\t\\t\\treturn None\\n\\t\\t# else plan the landing\\n\\t\\tarrival_time = self.time+ task_communication_time(t.packet_size, point_to_point_transmission_rate(self.node._distances[self.destination.index], bw))\\n\\t\\tevq.add_event(Task_arrival(arrival_time, self.destination, self.k, t))\\n\\t\\tevq.add_event(Start_transmitting(self.time, self.node, arrival_time, bw))\\n\\t\\treturn None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5dc3a7255e77ee0821f078f00fcd92d7\",\n \"score\": \"0.5901182\",\n \"text\": \"def callback_task_scheduler_creator(queue_task_scheduler, task_supervisor):\\n global entity_task_supervisor_info\\n global active_task_schedulers\\n logger.info(\\\"SchedulerDealer started\\\")\\n\\n while True:\\n task_scheduler = None\\n # wait for a new materialflow\\n materialflow_specification = queue_task_scheduler.get()\\n\\n # create new task shedular\\n task_scheduler = Scheduler(materialflow_specification, task_supervisor)\\n\\n active_task_schedulers.append(task_scheduler)\\n task_scheduler.start()\\n\\n entity_task_supervisor_info.appendMaterialflow(\\n materialflow_specification.id)\\n\\n task_supervisor.orion_connector.update_entity(\\n entity_task_supervisor_info)\\n logger.info(\\\"New TaskScheduler added\\\")\\n\\n logger.info(\\\"SchedulerDealer ended\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"32245beee93a6556c958388fefddeb79\",\n \"score\": \"0.5898572\",\n \"text\": \"def worker_thread( self ):\\n\\n # rand = random.Random()\\n \\n #while self.running:\\n # # To simulate asynchronous I/O, we create a random number at\\n # # random intervals. Replace the following 2 lines with the real\\n # # thing.\\n # time.sleep( rand.random() * 1 )\\n # msg = rand.random()\\n # self.queue.put(msg)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cbcfc85165804db4bd663142c9f82f60\",\n \"score\": \"0.5887806\",\n \"text\": \"def create_queue():\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c71da4fb04df7990abf1afd84f95e621\",\n \"score\": \"0.5882573\",\n \"text\": \"def handle_queue(self):\\n if not self.queue:\\n return\\n calculator = self.get_free_calculator()\\n if calculator is not None:\\n task = self.queue.pop(0) # tuple: (data, client_addr)\\n print 'Task from queue'\\n self.handle_client_request(*task)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4a62e16f3cb28ae4221cf1ca49886ef8\",\n \"score\": \"0.58702046\",\n \"text\": \"def __call__(self, *args, **kwargs):\\n self.schedule(*args, **kwargs)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"26860fb43d63571fc92461e544732e1a\",\n \"score\": \"0.58692646\",\n \"text\": \"def handle_output(self, queue):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"03a30ef670c6ed8fc43d7558bd9bf55b\",\n \"score\": \"0.5823347\",\n \"text\": \"def run(self):\\n\\n # Startup\\n # ------------------------------------------------------------------\\n if(self.first_execution):\\n\\n # log\\n self.logger.debug('Thread first execution')\\n\\n # setup_timer\\n self.setup_timer.emit()\\n\\n # first_execution\\n self.first_execution = False\\n\\n # Code\\n # ------------------------------------------------------------------\\n else:\\n\\n try:\\n obj = self.queue.get(block=False)\\n except Queue.Empty:\\n self.logger.debug('Queue empty')\\n return\\n\\n try:\\n obj()\\n except Exception, e:\\n self.logger.debug('{0}'.format(e))\\n finally:\\n # notify queue\\n self.queue.task_done()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2b14f6ebce1518b0993d07e19d4c2b25\",\n \"score\": \"0.5823279\",\n \"text\": \"def process(self):\\n self.out.idle=True\\n if self.task.finished:\\n self.sim.schedule(TaskFinishedEvent(self.sim, self.task, self.time))\\n else:\\n self.sim.add_task_to_rr_queue(self.task)\\n \\n \\n task=self.sim.get_task_from_rr_queue() \\n task.wait_out=task.wait_out+(self.time-task.outtime)\\n \\n# self.sim.schedule(OutInEvent(self.sim, task, self.time, self.out))\\n self.sim.schedule(TaskOutArrivalEvent(self.sim, task, self.time))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3392e738f705ae414a03887f3d19d98a\",\n \"score\": \"0.58100414\",\n \"text\": \"def execute(self):\\n logging.info(\\\"Executing Task with ID: \\\" +str(self.get_id() ) + \\\" and Name: \\\"+ self.get_name() )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b0306046c69aaf5e470b4c9533005e2d\",\n \"score\": \"0.5802936\",\n \"text\": \"def schedule_run(self, schedule):\\n\\n if len(schedule.jobs): # no need to start thread if no jobs in queue\\n t = threading.Thread(target=self.scheduler_thread)\\n # print('Starting scheduler thread')\\n t.daemon = True # allows this thread to be auto-killed on program exit\\n t.name = 'Scheduler Thread' # naming the thread helps with debugging\\n t.start()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"90db4594bf0930bb251744ec1e4107cb\",\n \"score\": \"0.5789738\",\n \"text\": \"def sort_queue(self, queue, chart):\\n ...\",\n \"title\": \"\"\n },\n {\n \"docid\": \"90db4594bf0930bb251744ec1e4107cb\",\n \"score\": \"0.5789738\",\n \"text\": \"def sort_queue(self, queue, chart):\\n ...\",\n \"title\": \"\"\n },\n {\n \"docid\": \"289784cde6c55a3047bfe2c5249ec8fe\",\n \"score\": \"0.5789452\",\n \"text\": \"def process(self):\\n self.out.work(self.task, self.time)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"fc487244608e8a94ba3fd3938c4f272e\",\n \"score\": \"0.5786862\",\n \"text\": \"def task(self):\\n self._command()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c78660fbebac34809345bc05ab6f3507\",\n \"score\": \"0.57828987\",\n \"text\": \"def __init__(self):\\n\\n self.queue = None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8132b470834cdd118bd19824c5f071e4\",\n \"score\": \"0.5778886\",\n \"text\": \"def start_worker(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9bc9072fca2436f3a6180285bc49096b\",\n \"score\": \"0.57753813\",\n \"text\": \"def test_enqueue_scheduled_jobs(self):\\n queue = Queue(connection=self.testconn)\\n registry = ScheduledJobRegistry(queue=queue)\\n job = Job.create('myfunc', connection=self.testconn)\\n job.save()\\n registry.schedule(job, datetime(2019, 1, 1, tzinfo=timezone.utc))\\n scheduler = RQScheduler([queue], connection=self.testconn)\\n scheduler.acquire_locks()\\n scheduler.enqueue_scheduled_jobs()\\n self.assertEqual(len(queue), 1)\\n\\n # After job is scheduled, registry should be empty\\n self.assertEqual(len(registry), 0)\\n\\n # Jobs scheduled in the far future should not be affected\\n registry.schedule(job, datetime(2100, 1, 1, tzinfo=timezone.utc))\\n scheduler.enqueue_scheduled_jobs()\\n self.assertEqual(len(queue), 1)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2aa461c2a59099b28f22645538a51645\",\n \"score\": \"0.5753001\",\n \"text\": \"def wthdMain(self):\\r\\n while self.running:\\r\\n time.sleep(1.0)\\r\\n self.queue.put(\\\"main\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ef597efc0c18387906e9a5714d8a73c7\",\n \"score\": \"0.57470465\",\n \"text\": \"def queue(self):\\n self._queue = True\\n return self\",\n \"title\": \"\"\n },\n {\n \"docid\": \"33cdde67ec2238bee286e957570d738d\",\n \"score\": \"0.57407373\",\n \"text\": \"def put_job(self,name,func):\\n self._qlock.acquire()\\n self._q.append((name,func))\\n self._qlock.release()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"59881637e3876c247e50528a084c1dc4\",\n \"score\": \"0.5737807\",\n \"text\": \"def schedule(self):\\n if not self.schedule_expression:\\n return\\n self.__create_cw_log_groups()\\n self.register_task_definition()\\n self.scheduler.schedule()\\n click.secho(f\\\"Scheduled task {self.taskName}\\\", fg=\\\"cyan\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"cf358ce4420190e26bca11676b52cf16\",\n \"score\": \"0.5737732\",\n \"text\": \"def _apply_queue(self, args, thisTask, cmd_args, payload, setup):\\n if not (thisTask.queue is None or thisTask.queue == \\\"\\\"):\\n cmd_args.append(\\\"-p\\\") # partition\\n cmd_args.append(thisTask.queue)\\n return True\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6f534421e7cf609a3b2e736fd7228fe9\",\n \"score\": \"0.57371837\",\n \"text\": \"def runTest(self):\\n sys_logging(\\\"start test\\\")\\n switch_init(self.client)\\n\\n port = port_list[1]\\n level = [0,1,2]\\n max_childs = [4, 64, 8]\\n sched_group_id_group_node = [None]*8\\n sched_group_service_id = 1\\n service_queueId = [None]*8\\n\\n\\n sched_type1 = SAI_SCHEDULING_TYPE_STRICT\\n sched_type2 = SAI_SCHEDULING_TYPE_DWRR\\n sched_weight = 10\\n cir = 2000000\\n cbs = 256000\\n pir = 1000000\\n pbs = 64000\\n queueId_list = []\\n\\n sched_oid1 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type1, 0, cir, cbs, pir, pbs)\\n sys_logging(\\\"sched_oid_1 0x%x\\\"%sched_oid1)\\n\\n sched_oid2 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type2, sched_weight, cir, cbs, pir, pbs)\\n sys_logging(\\\"sched_oid_1 0x%x\\\"%sched_oid2)\\n sched_oid_list = [sched_oid1, sched_oid2]\\n\\n \\n sched_group_id_root = sai_thrift_qos_create_scheduler_group(self.client, port, level[0], max_childs[0], port, 0)\\n \\n sched_group_id_chan_node = sai_thrift_qos_create_scheduler_group(self.client, port, level[1], max_childs[1], sched_group_id_root, 0)\\n \\n sched_group_id_group_node[0] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id) \\n sched_group_id_group_node[1] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\\n sched_group_id_group_node[2] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\\n sched_group_id_group_node[3] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\\n sched_group_id_group_node[4] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id) \\n sched_group_id_group_node[5] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\\n sched_group_id_group_node[6] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\\n sched_group_id_group_node[7] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\\n\\n \\n queue_type = SAI_QUEUE_TYPE_SERVICE\\n queue_index = [0,1,2,3,4,5,6,7]\\n service_queueId[0] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[0], parent_id=sched_group_id_group_node[0], service_id=sched_group_service_id, sche_id=sched_oid1) \\n service_queueId[1] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[1], parent_id=sched_group_id_group_node[1], service_id=sched_group_service_id, sche_id=sched_oid2)\\n service_queueId[2] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[2], parent_id=sched_group_id_group_node[1], service_id=sched_group_service_id, sche_id=sched_oid2)\\n service_queueId[3] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[3], parent_id=sched_group_id_group_node[3], service_id=sched_group_service_id, sche_id=sched_oid1)\\n service_queueId[4] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[4], parent_id=sched_group_id_group_node[4], service_id=sched_group_service_id)\\n service_queueId[5] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[5], parent_id=sched_group_id_group_node[4], service_id=sched_group_service_id)\\n service_queueId[6] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[6], parent_id=sched_group_id_group_node[4], service_id=sched_group_service_id)\\n service_queueId[7] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[7], parent_id=sched_group_id_group_node[7], service_id=sched_group_service_id)\\n #pdb.set_trace()\\n\\n warmboot(self.client)\\n try:\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[0])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid1:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[1])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid2:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[2])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid2:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[3])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid1:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[4])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[5])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[6])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[7])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError()\\n\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_oid2)\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[4], attr)\\n \\n self.client.sai_thrift_set_queue_attribute(service_queueId[5], attr)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[6], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_oid1)\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[7], attr)\\n \\n \\n\\n\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[0])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid1:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[1])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid2:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[2])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid2:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[3])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid1:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[4])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid2:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[5])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid2:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[6])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid2:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[7])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid1:\\n raise NotImplementedError()\\n \\n\\n finally:\\n #pdb.set_trace()\\n for ii in range(8):\\n attr_value = sai_thrift_attribute_value_t(oid=0)\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[ii], attr)\\n\\n #pdb.set_trace()\\n for i in range(8):\\n self.client.sai_thrift_remove_queue(service_queueId[i])\\n\\n for ii in range(8):\\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_group_node[ii])\\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_chan_node)\\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_root)\\n\\n self.client.sai_thrift_remove_scheduler_profile(sched_oid1)\\n self.client.sai_thrift_remove_scheduler_profile(sched_oid2)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"55c8d13354431b48da081edcc48c77c9\",\n \"score\": \"0.5726604\",\n \"text\": \"def __init__(self):\\n self.__queue = Queue.Queue()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e4340d2e81a85e699eaef96f0da65ac6\",\n \"score\": \"0.5724557\",\n \"text\": \"def run_dispatcher(sender, instance, created, **kwargs):\\n if created or instance.status==\\\"waiting\\\": \\n #se il dispatcher e' appena stato creato o ri-settato su waiting accodalo\\n if not instance.send_date: instance.send_date = datetime.now()\\n timestamp = datetimeToUnixSec(instance.send_date)\\n spooling_dispatcher.spool(disp=\\\"%s\\\" % instance.pk,at=timestamp)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"96666b0b65b7f4194ff1f36151cdf17f\",\n \"score\": \"0.5721709\",\n \"text\": \"def do_GET(self):\\n # f = self.send_head()\\n # if f:\\n # self.copyfile(f, self.wfile)\\n # f.close()\\n print self.path \\n \\n if not self.server.sheduler:\\n f.write(\\\"Sheduler not running\\\")\\n return\\n args =self.path\\n print \\\"args\\\", args\\n print 'sheduler', self.server.sheduler\\n # Ceci est juste un test que ajoute un job sur le sheduler(\\n # un job en duren -a_job_for_test, mais on aurait pu imaginer*\\n # un truc plus generic , ou la method en question a executee\\n # est passe par la requete Http.\\n now = datetime.now() + timedelta(seconds=10)\\n\\n # comme un 'cron' , voici une facon de scecifier au sheduler\\n # un job a effctue tous le trois secondes:) .Note que dans\\n # l'exemple la fonction 'a_job_for_test' est juste\\n # un exemple , mais nous aurions pu aussi bien imaginer que\\n # le nom de la fonction est passe au serveur via Http\\n # un truc du genre self.path.split('')\\n self.server.sheduler.scheduler.add_interval_job(\\n a_job_for_test,\\n seconds=3,\\n name='a_job_for_test',\\n jobstore='MongoDB',\\n args=[now])\\n\\n # comme un 'cron' , voici une facon de scecifier au sheduler\\n # un job a effctued dans 10 secondes un seule fois.Note que dans\\n # l'exemple la fonction 'a_job_for_test' est juste\\n # un exemple , mais nous aurions pu aussi bien imaginer que\\n # le nom de la fonction est passe au serveur via Http\\n # un truc du genre self.path.split('')\\n \\n # self.server.sheduler.scheduler.add_date_job(a_job_for_test,\\n # now,\\n # name='a_job_for_test',\\n # jobstore='MongoDB',\\n # args=[now])\\n thread.start_new_thread(\\n self.server.sheduler.scheduler.start, ())\",\n \"title\": \"\"\n },\n {\n \"docid\": \"03e660d8b4b5d1a049987a4269af748a\",\n \"score\": \"0.57131505\",\n \"text\": \"def start(self):\\n self.scheduler.run()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c44f64483249506b3cf24840449c6458\",\n \"score\": \"0.5688256\",\n \"text\": \"def _thread_proc(self):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f4cfd32a0bc0ab24d6d8739d4bfe14ce\",\n \"score\": \"0.5688189\",\n \"text\": \"def __init__(self):\\n self.queue = multiprocessing.Queue()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"30a775ed4183d5e40a776f446586eebd\",\n \"score\": \"0.56776375\",\n \"text\": \"def process(self): \\n self.cpu.idle=True\\n if not self.sim.sjf_queue.empty():\\n task=self.sim.get_task_from_sjf_queue()\\n self.sim.schedule(CpuInEvent(self.sim, task, self.time, self.cpu))\\n else:\\n pass\\n \\n self.task.outtime=self.time\\n event=TaskOutArrivalEvent(self.sim, self.task, self.time)\\n self.sim.schedule(event)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8f178b55208475f485be62e6c6bffd09\",\n \"score\": \"0.5674458\",\n \"text\": \"def handle_queue(self):\\n cmd, payload = self.queue.get()\\n if cmd == 'quit':\\n self.running = False\\n\\n elif cmd == 'insert':\\n for file in payload['files']:\\n self.send({\\n 'do': 'index_add',\\n 'filename': file\\n })\\n\\n elif cmd == 'delete':\\n for file in payload['files']:\\n self.send({\\n 'do': 'index_remove',\\n 'filename': file\\n })\\n\\n elif cmd == 'search':\\n file = payload['file']\\n self.send({\\n 'do': 'index_search',\\n 'filename': file\\n })\\n\\n elif cmd == 'download':\\n file = payload['file']\\n addr = self.results.get(file)\\n if addr is not None:\\n print('Using cached address (%s:%s) for %s' % (*addr, file))\\n download(self.naxos_path, file, addr)\\n else:\\n print('You have to search for the file first.') # TODO: Auto-search\\n self.input_thread.unblock()\\n\\n elif cmd == 'discover_overlay':\\n self.overlay_edges = set()\\n self.send({\\n 'do': 'discover_overlay'\\n })\\n self.periodic_runner.register(watch_edges, {\\n 'client': self,\\n 'old': set(),\\n 'queue': self.queue,\\n }, 0.5)\\n \\n elif cmd == 'print_overlay':\\n self.periodic_runner.unregister(watch_edges)\\n layout = 'strict graph {\\\\n\\\\t'+ '\\\\n\\\\t'.join(('%s -- %s' % e for e in self.overlay_edges)) +'\\\\n}\\\\n'\\n print('Visit the following webpage for a visualization of the overlay:')\\n print(tiny_url('https://dreampuf.github.io/GraphvizOnline/#' + urllib.parse.quote(layout)))\\n print('Shortened since the link can get really big.')\\n self.input_thread.unblock()\\n else:\\n raise ValueError('Unexpected command %s' % cmd)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b0e8a2935bdc1060f33beeb24a84a53e\",\n \"score\": \"0.56606203\",\n \"text\": \"def __init__(self):\\n self.queues = [], []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e14a74e5ad4c335259a0bf3975baa8b0\",\n \"score\": \"0.56601393\",\n \"text\": \"def execCmd(self , queue , rien):\\n while True:\\n msg = queue.get()\\n if msg == \\\"Connect\\\":\\n self.tGrbl.connectToGrbl()\\n self.tGuillotine.updateBtnState()\\n elif msg == \\\"Disconnect\\\": \\n self.tGrbl.disconnectToGrbl()\\n self.tGuillotine.updateBtnState()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e2a359560e8797247bc3fe9bfbec9b8a\",\n \"score\": \"0.5657827\",\n \"text\": \"def runTest(self):\\n sys_logging(\\\"start test\\\")\\n switch_init(self.client)\\n port = port_list[1]\\n sched_type1 = SAI_SCHEDULING_TYPE_STRICT\\n sched_type2 = SAI_SCHEDULING_TYPE_DWRR\\n sched_weight = 10\\n cir = 2000000\\n cbs = 256000\\n pir = 1000000\\n pbs = 64000\\n queueId_list = []\\n\\n sched_oid1 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type1, 0, cir, cbs, pir, pbs)\\n sys_logging(\\\"sched_oid_1 0x%x\\\"%sched_oid1)\\n\\n sched_oid2 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type2, sched_weight, cir, cbs, pir, pbs)\\n sys_logging(\\\"sched_oid_1 0x%x\\\"%sched_oid2)\\n sched_oid_list = [sched_oid1, sched_oid2]\\n attrs = self.client.sai_thrift_get_port_attribute(port)\\n for a in attrs.attr_list: \\n if a.id == SAI_PORT_ATTR_QOS_NUMBER_OF_QUEUES:\\n sys_logging(\\\"queue number:%d\\\"%a.value.u32)\\n queue_num = a.value.u32\\n if a.id == SAI_PORT_ATTR_QOS_QUEUE_LIST:\\n for i in range(a.value.objlist.count):\\n queueId_list.append(a.value.objlist.object_id_list[i])\\n sys_logging(\\\"queue_oid[%d]:0x%X\\\"%(i, a.value.objlist.object_id_list[i]))\\n attr_value = sai_thrift_attribute_value_t(oid=sched_oid_list[i%2])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[i], attr)\\n #pdb.set_trace()\\n warmboot(self.client)\\n try:\\n for ii in range(queue_num):\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[ii])\\n for a in attrs.attr_list: \\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"Get queue[0x%x] scheduler Profile oid: 0x%x\\\"%(queueId_list[ii], a.value.oid))\\n if a.value.oid != sched_oid_list[ii%2]:\\n raise NotImplementedError() \\n for i in range(8):\\n attr_value = sai_thrift_attribute_value_t(oid=sched_oid_list[(i+1)%2])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[i], attr)\\n #pdb.set_trace()\\n for ii in range(queue_num):\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[ii])\\n for a in attrs.attr_list: \\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"Get queue[0x%x] scheduler Profile oid: 0x%x\\\"%(queueId_list[ii], a.value.oid))\\n if a.value.oid != sched_oid_list[(ii+1)%2]:\\n raise NotImplementedError() \\n finally:\\n for i in range(queue_num):\\n self.client.sai_thrift_remove_queue(queueId_list[i])\\n self.client.sai_thrift_remove_scheduler_profile(sched_oid1)\\n self.client.sai_thrift_remove_scheduler_profile(sched_oid2)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ebf01b91402a0f6f1ca89b4cb8261dcd\",\n \"score\": \"0.56389487\",\n \"text\": \"def runTest(self):\\n sys_logging(\\\"start test\\\")\\n switch_init(self.client)\\n\\n port = port_list[1]\\n level = [0,1,2]\\n max_childs = [4, 64, 8]\\n sched_group_id_group_node = [None]*8\\n\\n\\n sched_type1 = SAI_SCHEDULING_TYPE_STRICT\\n sched_type2 = SAI_SCHEDULING_TYPE_DWRR\\n sched_weight = 10\\n cir = 2000000\\n cbs = 256000\\n pir = 1000000\\n pbs = 64000\\n queueId_list = []\\n\\n sched_oid1 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type1, 0, cir, cbs, pir, pbs)\\n sys_logging(\\\"sched_oid_1 0x%x\\\"%sched_oid1)\\n\\n sched_oid2 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type2, sched_weight, cir, cbs, pir, pbs)\\n sys_logging(\\\"sched_oid_1 0x%x\\\"%sched_oid2)\\n sched_oid_list = [sched_oid1, sched_oid2]\\n\\n \\n sched_group_id_root = sai_thrift_qos_create_scheduler_group(self.client, port, level[0], max_childs[0], port, 0)\\n \\n sched_group_id_chan_node = sai_thrift_qos_create_scheduler_group(self.client, port, level[1], max_childs[1], sched_group_id_root, 0)\\n \\n sched_group_id_group_node[0] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0) \\n sched_group_id_group_node[1] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0)\\n sched_group_id_group_node[2] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0)\\n sched_group_id_group_node[3] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0)\\n sched_group_id_group_node[4] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0) \\n sched_group_id_group_node[5] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0)\\n sched_group_id_group_node[6] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0)\\n sched_group_id_group_node[7] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0)\\n\\n \\n attrs = self.client.sai_thrift_get_port_attribute(port)\\n for a in attrs.attr_list: \\n if a.id == SAI_PORT_ATTR_QOS_NUMBER_OF_QUEUES:\\n sys_logging(\\\"queue number:%d\\\"%a.value.u32)\\n queue_num = a.value.u32\\n if a.id == SAI_PORT_ATTR_QOS_QUEUE_LIST:\\n for i in range(a.value.objlist.count):\\n queueId_list.append(a.value.objlist.object_id_list[i])\\n sys_logging(\\\"queue_oid[%d]:0x%X\\\"%(i, a.value.objlist.object_id_list[i]))\\n\\n sys_logging(\\\"=======set queue parent node profile=======\\\")\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[0])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[0], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[1])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[1], attr)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[2], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[3])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[3], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[4])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[4], attr)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[5], attr)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[6], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[7])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[7], attr)\\n #pdb.set_trace()\\n\\n warmboot(self.client)\\n try:\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[0])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[0]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[1])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[1]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[2])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[1]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[3])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[3]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[4])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[4]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[5])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[4]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[6])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[4]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[7])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[7]:\\n raise NotImplementedError()\\n\\n sys_logging(\\\"=======set queue scheduler profile=======\\\")\\n attr_value = sai_thrift_attribute_value_t(oid=sched_oid2)\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[1], attr)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[2], attr)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[4], attr)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[5], attr)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[6], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_oid1)\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[0], attr)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[3], attr)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[7], attr)\\n\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[0])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid1:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[1])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid2:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[2])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid2:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[3])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid1:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[4])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid2:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[5])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid2:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[6])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid2:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[7])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_SCHEDULER_PROFILE_ID:\\n sys_logging(\\\"get queue scheduler profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_oid1:\\n raise NotImplementedError()\\n\\n\\n sys_logging(\\\"=======remove queue parent node profile=======\\\")\\n #pdb.set_trace()\\n for ii in range(8):\\n attr_value = sai_thrift_attribute_value_t(oid=0)\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[ii], attr)\\n\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[0])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[1])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[2])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[3])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[4])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[5])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[6])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[7])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError()\\n\\n\\n #pdb.set_trace()\\n\\n sys_logging(\\\"=======set queue parent node profile again=======\\\")\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[0])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[0], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[1])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[1], attr)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[2], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[3])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[3], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[4])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[4], attr)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[5], attr)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[6], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[7])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(queueId_list[7], attr)\\n\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[0])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[0]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[1])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[1]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[2])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[1]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[3])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[3]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[4])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[4]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[5])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[4]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[6])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[4]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(queueId_list[7])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[7]:\\n raise NotImplementedError()\\n\\n finally:\\n\\n #pdb.set_trace()\\n for i in range(8):\\n self.client.sai_thrift_remove_queue(queueId_list[i])\\n\\n for ii in range(8):\\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_group_node[ii])\\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_chan_node)\\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_root)\\n\\n self.client.sai_thrift_remove_scheduler_profile(sched_oid1)\\n self.client.sai_thrift_remove_scheduler_profile(sched_oid2)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e19b9979195fbdb29e7088afa802a59b\",\n \"score\": \"0.5636245\",\n \"text\": \"def send_task(self):\\n packed = zlib.compress(cPickle.dumps(self.task_dict))\\n encoded = base64.b64encode(packed)\\n params_data = {\\\"task_data\\\":encoded}\\n retry_options = taskqueue.TaskRetryOptions(\\n task_retry_limit = self.task_retry_limit)\\n the_task = taskqueue.Task(url=\\\"/task\\\", params=params_data,\\n countdown = self.start_delay, retry_options = retry_options)\\n the_task.add() \\n #taskqueue.add(url=\\\"/task\\\", params=params_data) \",\n \"title\": \"\"\n },\n {\n \"docid\": \"c9121915943e133cb0ecd8d178b3438e\",\n \"score\": \"0.56360734\",\n \"text\": \"def next_in_schedule(self):\\n if len(self.execution_queue) > 0:\\n now = rospy.get_rostime()\\n next_task = self.execution_queue[0]\\n # get travel time to next task. \\n travel_time_to_next_task = self._travel_duration_fn(next_task.start_node_id)\\n\\n rospy.loginfo('start window: %s' % rostime_to_python(next_task.start_after).time())\\n rospy.loginfo(' now: %s' % rostime_to_python(now).time())\\n rospy.loginfo(' travel time: %s' % rosduration_to_python(travel_time_to_next_task))\\n \\n # the task can be executed if we can travel to the task in time for the\\n # the start window to open\\n if now >= (next_task.start_after - travel_time_to_next_task):\\n rospy.loginfo('start window is open')\\n self.execute_next_task()\\n else: \\n # delay is the difference between now and the time to start navigating\\n exe_delay = (next_task.start_after - travel_time_to_next_task) - now\\n rospy.loginfo('need to delay %s.%s for execution' % (exe_delay.secs, exe_delay.nsecs))\\n self.current_task = None\\n self.execution_delay_timer = rospy.Timer(exe_delay, self.execution_delay_cb, oneshot=True)\\n else:\\n self.current_task = None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"85872894ea6da5ec2ca6a8f71360f951\",\n \"score\": \"0.56329817\",\n \"text\": \"def dequeue(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"738215a11a3ceae0faf5085512e352ce\",\n \"score\": \"0.56298023\",\n \"text\": \"def commandPeriodic(self):\\n self.scheduler.run()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"89d792502ffdd9b809c144ae6a650680\",\n \"score\": \"0.56293863\",\n \"text\": \"def handle_queue(self):\\n cmd, payload = self.queue.get()\\n if cmd == 'connect':\\n self.network.connect_to_node(payload['addr'], 'paxos_join_request')\\n # TODO: add to self.paxos.peer_addresses\\n elif cmd == 'first_connection':\\n # self.network.connect_to_node(payload['addr'])\\n self.network.broadcast({\\n 'do': 'ping',\\n })\\n self.periodic_runner.register(watch_address_pool, {\\n 'queue': self.queue,\\n 'network': self.network,\\n 'old': set(),\\n }, 0.5)\\n elif cmd == 'connect_to_sampled':\\n picked = payload['picked']\\n log.debug(\\\"picked: %s\\\", picked)\\n for addr in picked:\\n self.network.connect_to_node(addr)\\n self.periodic_runner.unregister(watch_address_pool)\\n elif cmd == 'start_paxos':\\n if self.paxos is not None:\\n self.paxos.start_paxos_round(payload['value'])\\n else:\\n raise ValueError('Unknown command: %s' % cmd)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"04ac545de20b6de2f9134bf4e231bf5a\",\n \"score\": \"0.56275237\",\n \"text\": \"def __init__(self):\\n\\t\\tself.queue = []\\n\\t\\tself.poper = []\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1674ebfbc119d61410be73cb43f6f664\",\n \"score\": \"0.56234163\",\n \"text\": \"def main():\\n\\n # Build data\\n jobs = squeue(user='lmh1', # user id - change to your own\\n name=['iprPy_1', 'iprPy_4']) # job names - change to your own\\n logs = parse_runner_logs()\\n rundirs, runners = check_run_directories()\\n\\n # Merge data\\n logjobs = jobs.merge(logs, how='outer', on='jobid')\\n logjobs.loc[(logjobs.status=='active') & (pd.isna(logjobs.user)), 'status'] = 'crashed'\\n runlogjobs = logjobs.merge(runners, how='outer', on='pid')\\n\\n # Loop over all run directories\\n keys = ['jobid', 'pid', 'status', 'time', 'calcid', 'tmpdir']\\n for i in rundirs.index:\\n rundir = rundirs.loc[i]\\n\\n # List number of prepared calculations and number of runners\\n print(rundir.run_directory, rundir.numcalcs, rundir.numrunners)\\n dirjobs = runlogjobs[runlogjobs.run_directory == rundir.run_directory]\\n\\n # Print data for runners\\n if len(dirjobs) > 0:\\n print(dirjobs[keys])\\n print()\\n\\n # List jobs with no associated bid files (usually finished)\\n print('Unknown/finished jobs')\\n nodir = runlogjobs[pd.isna(runlogjobs.run_directory)][keys]\\n with pd.option_context('display.max_rows', None,):\\n print(nodir)\\n\\n # Delete run logs for successfully finished jobs\\n for jobid in nodir[nodir.status=='finished'].jobid.values:\\n Path(f'runner_{jobid}.txt').unlink()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5cd22b40a658528fd6f5e5c0ad09acae\",\n \"score\": \"0.56176794\",\n \"text\": \"def test_enqueue_at(self):\\n queue = Queue(connection=self.testconn)\\n registry = ScheduledJobRegistry(queue=queue)\\n scheduler = RQScheduler([queue], connection=self.testconn)\\n scheduler.acquire_locks()\\n # Jobs created using enqueue_at is put in the ScheduledJobRegistry\\n job = queue.enqueue_at(datetime(2019, 1, 1, tzinfo=timezone.utc), say_hello)\\n self.assertEqual(len(queue), 0)\\n self.assertEqual(len(registry), 1)\\n\\n # enqueue_at set job status to \\\"scheduled\\\"\\n self.assertTrue(job.get_status() == 'scheduled')\\n\\n # After enqueue_scheduled_jobs() is called, the registry is empty\\n # and job is enqueued\\n scheduler.enqueue_scheduled_jobs()\\n self.assertEqual(len(queue), 1)\\n self.assertEqual(len(registry), 0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e4b90ce4ac63d1fc3b70e270b44d071e\",\n \"score\": \"0.56115574\",\n \"text\": \"def collect(self):\\n while True:\\n time.sleep(2)\\n logging.info(f'Maintain Queue Empty: {self._maintain_queue.empty()}')\\n logging.info(f'Queue Empty: {self._queue.empty()}')\\n if not self._queue.empty():\\n message = self._queue.get()\\n logging.info(f\\\"Popped off message from Queue: {message.entry_info}\\\")\\n self.working_on = \\\"UPDATE\\\"\\n elif not self._maintain_queue.empty():\\n message = self._maintain_queue.get()\\n logging.info(f\\\"Popped off message from Maintain Queue: {message.entry_info}\\\")\\n self.working_on = \\\"MAINTAIN\\\"\\n else:\\n break\\n\\n if message.type == 'EXIT':\\n break\\n\\n if message.type != 'TASK':\\n raise ValueError(f'{message.type} is not a recognized task type')\\n\\n if message.type == 'TASK':\\n try:\\n github_url = message.entry_info['task']['given']['github_url']\\n repo_id = message.entry_info['repo_id']\\n self.query_pr({'github_url': github_url, 'repo_id': repo_id})\\n except Exception:\\n # logging.error(\\\"Worker ran into an error for task: {}\\\\n\\\".format(message.entry_info['task']))\\n # logging.error(\\\"Error encountered: \\\" + str(e) + \\\"\\\\n\\\")\\n # # traceback.format_exc()\\n # logging.info(\\\"Notifying broker and logging task failure in database...\\\\n\\\")\\n\\n logging.exception(f'Worker ran into an error for task {message.entry_info}')\\n self.register_task_failure(message.entry_info['repo_id'],\\n message.entry_info['task']['given']['github_url'])\\n\\n # Add to history table\\n task_history = {\\n \\\"repo_id\\\": message.entry_info['repo_id'],\\n \\\"worker\\\": self.config['id'],\\n \\\"job_model\\\": message.entry_info['task']['models'][0],\\n \\\"oauth_id\\\": self.config['zombie_id'],\\n \\\"timestamp\\\": datetime.datetime.now(),\\n \\\"status\\\": \\\"Error\\\",\\n \\\"total_results\\\": self.results_counter\\n }\\n\\n if self.history_id:\\n self.helper_db.execute(self.history_table.update().where(self.history_table.c.history_id==self.history_id).values(task_history))\\n else:\\n r = self.helper_db.execute(self.history_table.insert().values(task_history))\\n self.history_id = r.inserted_primary_key[0]\\n\\n logging.info(f\\\"Recorded job error for: {message.entry_info['task']}\\\")\\n\\n # Update job process table\\n updated_job = {\\n \\\"since_id_str\\\": message.entry_info['repo_id'],\\n \\\"last_count\\\": self.results_counter,\\n \\\"last_run\\\": datetime.datetime.now(),\\n \\\"analysis_state\\\": 0\\n }\\n self.helper_db.execute(self.job_table.update().where(self.job_table.c.job_model==message.entry_info['task']['models'][0]).values(updated_job))\\n logging.info(\\\"Updated job process for model: \\\" + message.entry_info['task']['models'][0] + \\\"\\\\n\\\")\\n\\n # Reset results counter for next task\\n self.results_counter = 0\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"94336d720287cddcd9005360a1490fd6\",\n \"score\": \"0.5610968\",\n \"text\": \"def run_queue(self):\\n\\n #FIXME: need a finally here to cleanup exceptions states\\n lqueue = self.chunk_queue(self.command_queue)\\n self.run_command_queue(lqueue)\\n\\n del self.command_queue[:]\\n self.memo_map.clear()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c51fe701898c1a3e0c07a6917fd0341a\",\n \"score\": \"0.56016207\",\n \"text\": \"def monitor_task_queue(self):\\n\\n self.handle_new_tasks()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d546bf86e6a677575961e6b11e020bf9\",\n \"score\": \"0.559495\",\n \"text\": \"def agentbehavior1(queue):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"66edc80b7c52d3f24c17d2c5c9e12602\",\n \"score\": \"0.5594344\",\n \"text\": \"def run(self, *args, **kwargs):\\n self.config_json = args[1]\\n self.task_id = self.request.id\\n self.temp_iviu = {\\n \\\"database\\\":self.config_json['mysql']['db'],\\n \\\"table\\\":\\\"p00390\\\",\\n \\\"type\\\":\\\"insert\\\",\\n \\\"ts\\\":1527621106,\\n \\\"xid\\\":1784748,\\n \\\"commit\\\":True,\\n \\\"data\\\": \\\"\\\"\\n }\\n self.redis_conn = None\\n self.redis_connections = {}\\n self.net = CheckNet()\\n self.retry_count = 0\\n self.err_flag = False\\n self.email_flag =True\\n self.start()\\n # print(\\\"tt in run method\\\",args[2])\\n if len(args) == 3:\\n self.thread_each_table(args[0],args[2])\\n else:\\n self.thread_each_table(args[0], \\\"\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e6d17fda6177fe2ce267ae69d19db552\",\n \"score\": \"0.5593024\",\n \"text\": \"def test_start_requeue(self):\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c17feb99867e2b14d923b20e64b9c1c0\",\n \"score\": \"0.55925614\",\n \"text\": \"def __init__( self ):\\n\\n # Create the queue\\n self.queue = Queue.Queue()\\n\\n # Set up the GUI part\\n self.gui_manager = tbh_gui_manager( self.queue, self.endApplication )\\n self.gui_manager.show()\\n \\n self.data_viz_queue = Queue.Queue()\\n \\n self.pomdp_data_viz = tbh_pomdp_data_viz.tbh_pomdp_data_viz_t( \\\\\\n self.queue, self.endApplication )\\n self.pomdp_data_viz.show()\\n #self.gui.console.show()\\n\\n # A timer to periodically call periodicCall :-)\\n self.queue_timer = PyQt4.QtCore.QTimer()\\n\\n # Start the timer -- this replaces the initial call \\n # to periodicCall\\n self.queue_timer.start(100)\\n PyQt4.QtCore.QObject.connect(self.queue_timer, PyQt4.QtCore.SIGNAL(\\\"timeout()\\\"), \\\\\\n self.periodicCall)\\n\\n\\n\\n # Set up the thread to do asynchronous I/O\\n # More can be made if necessary\\n self.running = 1\\n \\n \\tself.thread = threading.Thread( target=self.worker_thread )\\n self.thread.start()\\n\\n # Start the periodic call in the GUI to check if the queue contains\\n # anything\\n self.periodicCall()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d2c4295c672872fd4813356a760b166d\",\n \"score\": \"0.5592507\",\n \"text\": \"def add_job(self, func, *args):\\n self.queue.append((func, args))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"32ac073776ac841780639545fd8c3812\",\n \"score\": \"0.5590981\",\n \"text\": \"def runTest(self):\\n sys_logging(\\\"start test\\\")\\n switch_init(self.client)\\n\\n port = port_list[1]\\n level = [0,1,2]\\n max_childs = [4, 64, 8]\\n sched_group_id_group_node = [None]*8\\n sched_group_service_id = 1\\n service_queueId = [None]*8\\n\\n\\n sched_type1 = SAI_SCHEDULING_TYPE_STRICT\\n sched_type2 = SAI_SCHEDULING_TYPE_DWRR\\n sched_weight = 10\\n cir = 2000000\\n cbs = 256000\\n pir = 1000000\\n pbs = 64000\\n\\n sched_oid1 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type1, 0, cir, cbs, pir, pbs)\\n sys_logging(\\\"sched_oid_1 0x%x\\\"%sched_oid1)\\n\\n sched_oid2 = sai_thrift_qos_create_scheduler_profile(self.client, sched_type2, sched_weight, cir, cbs, pir, pbs)\\n sys_logging(\\\"sched_oid_1 0x%x\\\"%sched_oid2)\\n sched_oid_list = [sched_oid1, sched_oid2]\\n\\n \\n sched_group_id_root = sai_thrift_qos_create_scheduler_group(self.client, port, level[0], max_childs[0], port, 0)\\n \\n sched_group_id_chan_node = sai_thrift_qos_create_scheduler_group(self.client, port, level[1], max_childs[1], sched_group_id_root, 0)\\n \\n sched_group_id_group_node[0] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id) \\n sched_group_id_group_node[1] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\\n sched_group_id_group_node[2] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\\n sched_group_id_group_node[3] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\\n sched_group_id_group_node[4] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id) \\n sched_group_id_group_node[5] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\\n sched_group_id_group_node[6] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\\n sched_group_id_group_node[7] = sai_thrift_qos_create_scheduler_group(self.client, port, level[2], max_childs[2], sched_group_id_chan_node, 0, service_id=sched_group_service_id)\\n\\n \\n queue_type = SAI_QUEUE_TYPE_SERVICE\\n queue_index = [0,1,2,3,4,5,6,7]\\n service_queueId[0] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[0], parent_id=sched_group_id_group_node[0], service_id=sched_group_service_id, sche_id=sched_oid1) \\n service_queueId[1] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[1], parent_id=sched_group_id_group_node[1], service_id=sched_group_service_id, sche_id=sched_oid2)\\n service_queueId[2] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[2], parent_id=sched_group_id_group_node[1], service_id=sched_group_service_id, sche_id=sched_oid2)\\n service_queueId[3] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[3], parent_id=sched_group_id_group_node[3], service_id=sched_group_service_id, sche_id=sched_oid1)\\n service_queueId[4] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[4], service_id=sched_group_service_id, sche_id=sched_oid2)\\n service_queueId[5] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[5], service_id=sched_group_service_id, sche_id=sched_oid2)\\n service_queueId[6] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[6], service_id=sched_group_service_id, sche_id=sched_oid2)\\n service_queueId[7] = sai_thrift_create_queue_id(self.client, queue_type, port, queue_index[7], service_id=sched_group_service_id, sche_id=sched_oid1)\\n #pdb.set_trace()\\n\\n warmboot(self.client)\\n try:\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[0])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[0]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[1])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[1]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[2])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[1]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[3])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[3]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[4])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[5])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[6])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[7])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != SAI_NULL_OBJECT_ID:\\n raise NotImplementedError()\\n\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[4])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[4], attr)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[5], attr)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[6], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[7])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[7], attr)\\n \\n \\n\\n\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[0])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[0]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[1])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[1]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[2])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[1]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[3])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[3]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[4])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[4]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[5])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[4]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[6])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[4]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[7])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[7]:\\n raise NotImplementedError()\\n\\n\\n for ii in range(8):\\n attr_value = sai_thrift_attribute_value_t(oid=0)\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[ii], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[0])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[0], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[1])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[1], attr)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[2], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[3])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[3], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[4])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[4], attr)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[5], attr)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[6], attr)\\n\\n attr_value = sai_thrift_attribute_value_t(oid=sched_group_id_group_node[7])\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[7], attr)\\n\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[0])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[0]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[1])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[1]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[2])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[1]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[3])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[3]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[4])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[4]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[5])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[4]:\\n raise NotImplementedError()\\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[6])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[4]:\\n raise NotImplementedError() \\n attrs = self.client.sai_thrift_get_queue_attribute(service_queueId[7])\\n assert(SAI_STATUS_SUCCESS == attrs.status)\\n for a in attrs.attr_list:\\n if a.id == SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE:\\n sys_logging(\\\"get queue parent node profile:0x%x\\\"%a.value.oid)\\n if a.value.oid != sched_group_id_group_node[7]:\\n raise NotImplementedError()\\n\\n finally:\\n #pdb.set_trace()\\n for ii in range(8):\\n attr_value = sai_thrift_attribute_value_t(oid=0)\\n attr = sai_thrift_attribute_t(id=SAI_QUEUE_ATTR_PARENT_SCHEDULER_NODE, value=attr_value)\\n self.client.sai_thrift_set_queue_attribute(service_queueId[ii], attr)\\n\\n #pdb.set_trace()\\n for i in range(8):\\n self.client.sai_thrift_remove_queue(service_queueId[i])\\n\\n for ii in range(8):\\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_group_node[ii])\\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_chan_node)\\n self.client.sai_thrift_remove_scheduler_group(sched_group_id_root)\\n\\n self.client.sai_thrift_remove_scheduler_profile(sched_oid1)\\n self.client.sai_thrift_remove_scheduler_profile(sched_oid2)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3909cc076c9fbb71777323f5ac029dce\",\n \"score\": \"0.5588554\",\n \"text\": \"def requeue(self):\\n log.info('Requeueing the task')\\n taskmanager.crawlNow(connector_instance_ids =[self.task.connector_instance_id],\\n workspace_id=self.task.workspace_id)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1c7fc3cadc529fbb0aa73b5413c2ba10\",\n \"score\": \"0.55814713\",\n \"text\": \"def dequeue_actions(self):\\n dequeued = []\\n for task in self.get_todo():\\n cmd = self.format_cmd(task[\\\"action\\\"], task[\\\"path\\\"], task[\\\"rids\\\"])\\n log_cmd = self.format_log_cmd(task[\\\"action\\\"], task[\\\"path\\\"], task[\\\"rids\\\"])\\n self.log.info(\\\"run '%s' queued %s ago\\\", \\\" \\\".join(log_cmd), print_duration(self.now - task[\\\"queued\\\"]))\\n self.exec_action(task[\\\"sigs\\\"], cmd)\\n dequeued += task[\\\"sigs\\\"]\\n self.delete_queued(dequeued)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"407a566ef3fdc17b0ba8b79245e5d803\",\n \"score\": \"0.5576157\",\n \"text\": \"def setupCmdQueue(self):\\n raise NotImplementedError\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bf53116b6fda45c5c50f7183253490f6\",\n \"score\": \"0.55741537\",\n \"text\": \"def _execute(self):\\n\\t\\traise NotImplementedError(\\\"Task handlers must override _execute\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c50f24e8dab399fdce369b39ee4823d0\",\n \"score\": \"0.556992\",\n \"text\": \"def refresh(self):\\n self.queue.sort(key=lambda x: x.exe_time)\\n self.catch_up()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9d645f21808d504b03f92a5372717b6d\",\n \"score\": \"0.556369\",\n \"text\": \"def processQueueAsync(self):\\n print(\\\"Plotter process started\\\")\\n self.mcq = MotorCtrlQueue(self.config)\\n self.mcq.start()\\n\\n i = 0\\n item = self.workerQueue.get()\\n start = time.time()\\n while(item is not None):\\n\\n self.executeCmd(item)\\n\\n i += 1\\n if i % 1000 == 0:\\n print(\\\"Processed %d commands. %f ms per cmd. \\\" %\\n (i, (time.time() - start)*1000/i))\\n\\n item = self.workerQueue.get()\\n\\n # Wait for stepper queue\\n self.mcq.join()\\n print(\\\"Plotter process stopped\\\")\\n exit(0)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"13d9f8d58e85192394c4cd085a2cb146\",\n \"score\": \"0.5563209\",\n \"text\": \"def pre_schedule(worker, job):\\n data = pickle.loads(job.data)\\n #print data\\n s = requests.Session()\\n \\n task_r = s.get(\\\"http://localhost:8001\\\"+data[\\\"task\\\"])\\n print \\\"doing:\\\", data[\\\"task\\\"]\\n task_js = json.loads(task_r.text)\\n \\n function = task_js[\\\"async_function\\\"]\\n \\n input_dataset = json.loads(s.get(\\\"http://localhost:8001\\\"+data[\\\"input_dataset\\\"]).text)\\n output_dataset = json.loads(s.get(\\\"http://localhost:8001\\\"+data[\\\"output_dataset\\\"]).text)\\n \\n input_dataset_id = input_dataset[\\\"id\\\"]\\n output_dataset_id = output_dataset[\\\"id\\\"]\\n \\n \\n #print input_columns\\n #print output_column\\n #print function\\n #print input_dataset\\n #print output_dataset\\n \\n \\n #schedule\\n count = input_dataset[\\\"datapoint_count\\\"]\\n \\n #TODO bucket list is \\\"hardcoded\\\" here. find some other way to do that\\n bucket_list = \\\",\\\".join([\\\"'\\\"+str(input_dataset_id)+\\\"-\\\"+str(c)+\\\"'\\\" for c in xrange(1+int(count/10000))])\\n \\n \\n table = \\\"tsstore\\\"\\n \\n lowest_time = input_dataset[\\\"lowest_ts\\\"]\\n highest_time = input_dataset[\\\"highest_ts\\\"]\\n \\n #partition time buckets\\n date_format = \\\"%Y-%m-%d %H:%M:%S.%f\\\"\\n lt = datetime.datetime.strptime(lowest_time, date_format)-datetime.timedelta(microseconds=1)\\n ht = datetime.datetime.strptime(highest_time, date_format)\\n diff = ht-lt\\n \\n #TODO change to some other value during production\\n batch_size = 10\\n \\n try:\\n interval = task_js[\\\"interval_in_seconds\\\"]\\n #is aggregation\\n print \\\"is aggregation\\\"\\n IS_CALCULATION = False\\n num_tasks = int(diff.total_seconds()/interval)\\n \\n cols = []\\n dims_with_cols = []\\n for dim in input_dataset[\\\"dimensions\\\"]:\\n col_r = s.get(\\\"http://localhost:8001\\\"+dim)\\n jreq = json.loads(col_r.text)[\\\"ts_column\\\"]\\n cols.append(jreq)\\n dims_with_cols.append(DimWithCol(dim, jreq))\\n \\n output_column = cols[0]\\n input_columns = cols[1:]\\n \\n \\n except KeyError:\\n #is calculation\\n print \\\"is calculation\\\"\\n IS_CALCULATION = True\\n cluster = Cluster(data[\\\"cassandra_nodes\\\"])\\n session = cluster.connect('ws')\\n stmt = \\\"select count(*) from tsstore where bucket in (%s) and dataset=%s;\\\" % (bucket_list, input_dataset_id)\\n row = session.execute(stmt)\\n count = row[0]._asdict()[\\\"count\\\"]\\n \\n session.shutdown()\\n \\n output_dimension = s.get(\\\"http://localhost:8001\\\"+task_js[\\\"output_dimension\\\"])\\n output_column = json.loads(output_dimension.text)[\\\"ts_column\\\"]\\n \\n input_dimensions = task_js[\\\"input_dimensions\\\"]\\n input_columns = []\\n for ic in input_dimensions:\\n ic_r = s.get(\\\"http://localhost:8001\\\"+ic)\\n input_columns.append(json.loads(ic_r.text)[\\\"ts_column\\\"])\\n interval = (diff.total_seconds()*batch_size)/count\\n num_tasks = int(count/batch_size)\\n \\n #print interval\\n #print count/batch_size\\n \\n #update task_count\\n task_update_callback(data[\\\"task_id\\\"], int(num_tasks))\\n \\n temp_ht = lt+datetime.timedelta(seconds=interval)+datetime.timedelta(microseconds=1)\\n lt -= datetime.timedelta(microseconds=1)\\n lowest_time = datetime.datetime.strftime(lt, date_format)\\n highest_time = datetime.datetime.strftime(temp_ht, date_format)\\n \\n #while True:\\n for XX in xrange(num_tasks+2):\\n stmt = \\\"select %s,dataset,bucket from %s where bucket in (%s) and time >= '%s' AND time <= '%s' and dataset=%s order by dataset, time;\\\" % (\\\",\\\".join(input_columns+[output_column]+([\\\"time\\\"] if IS_CALCULATION else [])), table, bucket_list, lowest_time, highest_time, input_dataset_id)\\n print stmt\\n print num_tasks+1, XX\\n #create job with previous stmt\\n dat = {}\\n dat[\\\"stmt\\\"] = stmt\\n dat[\\\"function\\\"] = function\\n dat[\\\"output_column\\\"] = output_column\\n dat[\\\"output_dataset\\\"] = data[\\\"output_dataset\\\"]\\n dat[\\\"task_id\\\"] = data[\\\"task_id\\\"]\\n dat[\\\"cassandra_nodes\\\"] = data[\\\"cassandra_nodes\\\"]\\n client = GearmanClient(JOBSERVER_LIST)\\n try:\\n interval = task_js[\\\"interval_in_seconds\\\"]\\n #is aggregation\\n #dat[\\\"input_columns\\\"] = input_columns+[output_column]\\n dat[\\\"input_dimensions\\\"] = dims_with_cols\\n \\n client.submit_job(\\\"row_aggregator\\\", pickle.dumps(dat),background=True)\\n except KeyError:\\n #is calculation\\n dat[\\\"output_dimension\\\"] = task_js[\\\"output_dimension\\\"]\\n client.submit_job(\\\"row_calculator\\\", pickle.dumps(dat),background=True)\\n \\n #st = statsd.StatsClient(\\\"192.168.149.161\\\",8125)\\n #st.incr(\\\"task_created\\\")\\n\\n #update timestamps\\n lt += datetime.timedelta(seconds=interval)+datetime.timedelta(microseconds=1)\\n temp_ht += datetime.timedelta(seconds=interval)+datetime.timedelta(microseconds=1)\\n \\n lowest_time = datetime.datetime.strftime(lt, date_format)\\n highest_time = datetime.datetime.strftime(temp_ht, date_format)\\n print lowest_time\\n print highest_time\\n \\n #if lt > ht:\\n # break\\n \\n return \\\"a\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"72fe02423100850a617257dca48ea999\",\n \"score\": \"0.5562906\",\n \"text\": \"def test_queue_and_jobs_6(self):\\n output = \\\"\\\"\\\"\\n [0] queue (sftp://someone:@localhost) -- 252 B/s\\n sftp://someone:@localhost/home/someone\\n Now executing: [1] mirror -c /tmp/test_controllerbsn4wlu2/remote/ra /tmp/test_controllerbsn4wlu2/local/ -- 249/8.2k (3%) 100 B/s\\n -[2] mirror -c /tmp/test_controllerbsn4wlu2/remote/rb /tmp/test_controllerbsn4wlu2/local/ -- 374/9.3k (4%) 153 B/s\\n Commands queued:\\n 1. pget -c \\\"/tmp/test_controllerbsn4wlu2/remote/rc\\\" -o \\\"/tmp/test_controllerbsn4wlu2/local/\\\" \\n [1] mirror -c /tmp/test_controllerbsn4wlu2/remote/ra /tmp/test_controllerbsn4wlu2/local/ -- 249/8.2k (3%) 100 B/s\\n \\\\\\\\transfer `raa' \\n `raa' at 238 (23%) 100b/s eta:8s [Receiving data]\\n \\\\mirror `rab' -- 0/7.2k (0%)\\n \\\\\\\\transfer `rab/raba' \\n `raba' at 0 (0%) [Connecting...]\\n \\\\\\\\transfer `rab/rabb' \\n `rabb' at 0 (0%) [Waiting for response...]\\n [2] mirror -c /tmp/test_controllerbsn4wlu2/remote/rb /tmp/test_controllerbsn4wlu2/local/ -- 374/9.3k (4%) 153 B/s\\n \\\\\\\\transfer `rba' \\n `rba' at 159 (3%) 77b/s eta:51s [Receiving data]\\n \\\\\\\\transfer `rbb' \\n `rbb' at 153 (2%) 76b/s eta:66s [Receiving data]\\n \\\"\\\"\\\"\\n parser = LftpJobStatusParser()\\n statuses = parser.parse(output)\\n golden_queue = [\\n LftpJobStatus(job_id=1,\\n job_type=LftpJobStatus.Type.PGET,\\n state=LftpJobStatus.State.QUEUED,\\n name=\\\"rc\\\",\\n flags=\\\"-c\\\"),\\n ]\\n golden_job1 = LftpJobStatus(job_id=1,\\n job_type=LftpJobStatus.Type.MIRROR,\\n state=LftpJobStatus.State.RUNNING,\\n name=\\\"ra\\\",\\n flags=\\\"-c\\\")\\n golden_job1.total_transfer_state = LftpJobStatus.TransferState(249, 8396, 3, 100, None)\\n golden_job1.add_active_file_transfer_state(\\\"raa\\\", LftpJobStatus.TransferState(None, None, None, 100, 8))\\n golden_job1.add_active_file_transfer_state(\\\"rab/raba\\\", LftpJobStatus.TransferState(None, None, None, None, None))\\n golden_job1.add_active_file_transfer_state(\\\"rab/rabb\\\", LftpJobStatus.TransferState(None, None, None, None, None))\\n golden_job2 = LftpJobStatus(job_id=2,\\n job_type=LftpJobStatus.Type.MIRROR,\\n state=LftpJobStatus.State.RUNNING,\\n name=\\\"rb\\\",\\n flags=\\\"-c\\\")\\n golden_job2.total_transfer_state = LftpJobStatus.TransferState(374, 9523, 4, 153, None)\\n golden_job2.add_active_file_transfer_state(\\\"rba\\\", LftpJobStatus.TransferState(None, None, None, 77, 51))\\n golden_job2.add_active_file_transfer_state(\\\"rbb\\\", LftpJobStatus.TransferState(None, None, None, 76, 66))\\n golden_jobs = [golden_job1, golden_job2]\\n self.assertEqual(len(golden_queue)+len(golden_jobs), len(statuses))\\n statuses_queue = [j for j in statuses if j.state == LftpJobStatus.State.QUEUED]\\n self.assertEqual(golden_queue, statuses_queue)\\n statuses_jobs = [j for j in statuses if j.state == LftpJobStatus.State.RUNNING]\\n self.assertEqual(golden_jobs, statuses_jobs)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"46d7b2de353ab41d78a49c531dc0261c\",\n \"score\": \"0.55613804\",\n \"text\": \"def queue_events(self, timeout):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2e7a152416156e0115c320ac03961d63\",\n \"score\": \"0.5554936\",\n \"text\": \"def _init_queue(self):\\n self.queue.put((do_page_parse, self.root_url))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d81c7b030e4380ac69de85200441b370\",\n \"score\": \"0.5553766\",\n \"text\": \"def submit(self):\\n \\n if len(self.queue) == 0:\\n raise Exception(\\\"There are no script to be submitted to the queue\\\\n did you run create_scripts?\\\")\\n\\n for queueFileName in self.queue:\\n os.system(\\\"qsub \\\" + queueFileName)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a1e0ae997b610f20c6917c185ee971c9\",\n \"score\": \"0.5550807\",\n \"text\": \"def main_task():\\n\\n interval = 5\\n apis = Scheduler.get_apis()\\n for api in apis:\\n class_name = api.api_class.split('.')[2]\\n sched.add_job(Scheduler.fetch_data, 'interval',\\n name='{}'.format(api.name),\\n seconds=api.refresh_time,\\n start_date=datetime.now()+timedelta(\\n minutes=interval),\\n end_date=datetime.now()+timedelta(hours=23),\\n args=[api.api_class, api.name],\\n replace_existing=True, id='{}'.format(class_name),\\n jobstore='sqlalchemy', misfire_grace_time=300)\\n interval += interval\",\n \"title\": \"\"\n }\n]","isConversational":false}}},{"rowIdx":399,"cells":{"query_id":{"kind":"string","value":"7cf6d7a7b128f652585284b8eb15cfc0"},"query":{"kind":"string","value":"Emits a 'cld' instruction."},"positive_passages":{"kind":"list like","value":[{"docid":"e034cd2a187354cc37d2628c032dc82a","score":"0.5156586","text":"def cld(self) -> None:\n self.buf[self.pos] = 252\n self.pos += 1","title":""}],"string":"[\n {\n \"docid\": \"e034cd2a187354cc37d2628c032dc82a\",\n \"score\": \"0.5156586\",\n \"text\": \"def cld(self) -> None:\\n self.buf[self.pos] = 252\\n self.pos += 1\",\n \"title\": \"\"\n }\n]","isConversational":false},"negative_passages":{"kind":"list like","value":[{"docid":"10f6e1d757e33098a497f06762b836a0","score":"0.6387597","text":"def cl(self, c):\n self.force_menu('oper')\n self.send('cl ' + str(c))\n return output(self.proc.before)","title":""},{"docid":"93fe9d0119da5f74106fdbe79ae1cdc7","score":"0.5471392","text":"def do_ccmd(self, args):\n print 'args:', args.split()","title":""},{"docid":"753df6ce3ce639b27fc94b20be4374d9","score":"0.5453434","text":"def gen_c_instruction(self, dest, comp, jump):\n return '111' + self.comp(comp) + self.dest(dest) + self.jump(jump)","title":""},{"docid":"91b8cb9b58d6fbcde90e6b276a962fce","score":"0.53294784","text":"def cmd_makecldf(self, args):","title":""},{"docid":"a004240355f4033a155a694cf0dca221","score":"0.5321995","text":"def d017100cc ( state ) :\n byte = state[\"byte\"]\n stream = state[\"stream\"]\n\n cc = cctable[byte&0xFF-0o100]\n\n state[\"size\"] = \"r32\"\n\n rmfield = parse_rm(state)\n regfield = parse_reg(state)\n\n return f'CMOV{cc} {regfield}, {rmfield}'","title":""},{"docid":"a4f57c2d0dd37eb167ac00eb2e22cfff","score":"0.53189015","text":"def d160cc ( state ) :\n byte = state[\"byte\"]\n stream = state[\"stream\"]\n\n cc = cctable[byte-0o160]\n\n disp8 = int.from_bytes(stream.read(1), byteorder='little', signed=True)\n state[\"pos\"] += 1\n state[\"hex\"].append(f'{disp8&0xFF:08X}')\n\n return f'J{cc} {disp8} to {state[\"pos\"]+disp8:08X}'","title":""},{"docid":"515af1abe08cbabc3057958996665783","score":"0.51874214","text":"def cldf(self) -> pycldf.Dataset:\n if self._cldf is None:\n raise AttributeError('Writer.cldf is only set when Writer is used in with statement!')\n return self._cldf","title":""},{"docid":"b9c6cc1a6e17af463fc83c0f895e6af6","score":"0.5133083","text":"def write_cdl(cdl):\n\n values = list(cdl.slope)\n values.extend(cdl.offset)\n values.extend(cdl.power)\n values.append(cdl.sat)\n values = [str(i) for i in values]\n\n ss_cdl = ' '.join(values)\n\n with open(cdl.file_out, 'wb') as cdl_f:\n cdl_f.write(enc(ss_cdl))","title":""},{"docid":"ae55651318111e9c526738cc94a4439b","score":"0.5131566","text":"def ccds():\n allowed_str_args = ['hgnc_symbol', 'ccdsid']\n\n allowed_int_args = ['limit', 'hgnc_identifier']\n\n args = get_args(\n request_args=request.args,\n allowed_int_args=allowed_int_args,\n allowed_str_args=allowed_str_args\n )\n\n return jsonify(query.ccds(**args))","title":""},{"docid":"3a79cc8f7e312979d06c7a7d06d2f4e8","score":"0.5094653","text":"def cldf_dir(self) -> DataDir:\n return self.dir / 'cldf'","title":""},{"docid":"5a261b26f5a0f85c1b280a15c8f373a7","score":"0.50675637","text":"def _parse_c_instruction(self):\n line = '111'\n line += self.code.comp(self.parser.comp)\n line += self.code.dest(self.parser.dest)\n line += self.code.jump(self.parser.jump)\n self._write_line(line)","title":""},{"docid":"b485e57165e7f1e004356df1547a1064","score":"0.5047674","text":"def cmd_makecldf(self, args: argparse.Namespace):\n args.log.warning('cmd_{0} not implemented for dataset {1}'.format('makecldf', self.id))\n return NOOP","title":""},{"docid":"5015fb32fe82f726f9ad048426a158e3","score":"0.5033455","text":"def request_cdr(self):\n self.model.request_computed_value_output(\"cdr\")","title":""},{"docid":"249e103a985c24429e822934d79ff480","score":"0.49677145","text":"def set_dc(self):\n self.instr.write(self.channel + ':COUPLING DC')\n return None","title":""},{"docid":"01c26aa345440ac251f5bdbab47fd57e","score":"0.49471664","text":"def ldc(concentration, discharge,\n conversion_factor,\n target_concentration=None,\n y_label='Load',\n yscale='log',\n ylim=None,\n ax=None,\n label_conditions=False):\n rank = rankdata(discharge)\n # calculate probability of each rank\n prob = (1-(rank/(len(rank)+1)))*100\n load = concentration * discharge * conversion_factor\n\n if ax is None:\n fig, ax = plt.subplots(1)\n\n # plot target curve\n if target_concentration is None:\n target_concentration = load_mean_concentration(concentration, discharge)\n\n hb_extent = None\n if ylim is not None:\n plot_ylim = ylim\n hb_extent=(1,100, ylim[0], ylim[1])\n\n if yscale is 'log':\n plot_ylim = (10**ylim[0], 10**ylim[1])\n\n\n\n # plot data via matplotlib\n hb = ax.hexbin(prob, load, gridsize=50,\n yscale=yscale,\n cmap='pink_r',\n mincnt=1,\n extent=hb_extent,\n linewidths=0.2)\n\n target_ldc(target_concentration, discharge, conversion_factor, ax=ax)\n\n cb = plt.colorbar(hb, ax=ax, orientation='horizontal')\n cb.set_label('Count')\n #ax.set_yscale('log')\n ax.set_ylabel(y_label)\n ax.set_xlabel('Flow Duration Interval (%)')\n ax.grid(alpha=0.2, which='both', linestyle='--', linewidth=0.5)\n #ax.grid(alpha=0.2, which='major', linestyle='--', linewidth=0.5)\n ax.set_xlim(0,100)\n\n if ylim is not None:\n ax.set_ylim(plot_ylim)\n\n if label_conditions==True:\n label_dc_flow_conditions(ax)","title":""},{"docid":"46e7009cc6e33ee12cffd3b98259dc60","score":"0.49342784","text":"def do_c(self, line):\n return self.do_connect(line)","title":""},{"docid":"51bf1c0e1eda52758309b4cc82022db0","score":"0.48940757","text":"def d2cd(d, e):\n cd = e.css('cd', 0)\n # Test for division by 0\n if cd + e.gd:\n return (d + e.gd) / (cd + e.gd)\n # Undefined, no info about column depth and gutter or zero division.\n return 0","title":""},{"docid":"e928e0c6aba962fd3537c711206634b8","score":"0.4871802","text":"def write_dcd (self, filename='tfd', dirname='.') :\n Conformers.write_dcd(self,filename,dirname)","title":""},{"docid":"4efe20ed0dc8e705c5cea87f96f14e98","score":"0.48573828","text":"def d017200cc ( state ) :\n byte = state[\"byte\"]\n stream = state[\"stream\"]\n\n cc = cctable[byte&0xFF-0o200]\n\n disp32 = int.from_bytes(stream.read(4), byteorder='little', signed=True)\n state[\"pos\"] += 4\n state[\"hex\"].append(f'{disp32&0xFFFFFFFF:08X}')\n\n return f'J{cc} {disp32} to {state[\"pos\"]+disp32:08X}'","title":""},{"docid":"2c6138323f516b24cbff4600d2fb59f2","score":"0.4829934","text":"def toggle_dcn(self, dcn_id: str):\n if self.dcn:\n self.dcn = None\n self.setText(12, '')\n self.cooling.setDisabled(False)\n else:\n self.dcn = dcn_id\n self.setText(12, dcn_id)\n self.cooling.setDisabled(True)","title":""},{"docid":"b54c4b7d2d179e178c94032bf72acea6","score":"0.48284918","text":"def cpd():\n return pkp.cpd.CPD(ultimate_analysis=ua, proximate_analysis=pa,\n pressure=101325, name='CPD coal')","title":""},{"docid":"a1d9ba9d6d04360d7bfe3d0a90554e9b","score":"0.4827443","text":"def cdf(self, d):\n y = norm.ppf(d, 0, 1)\n\n return multivariate_normal.cdf(y, mean=None, cov=self.corrMatrix)","title":""},{"docid":"0bcae870cb45e81d55601e0b9b170f6f","score":"0.481945","text":"def d2y_dtdC(self, y, dydC):\n\n C = self._cdata['C']\n nC = len(C)\n i1, i2, i3, i4 = self._cdata['i'].T\n\n yext = np.concatenate([y, [1]])\n dydCext = dydC.reshape(-1, self._N)\n if dydCext.shape[0] != nC:\n raise ValueError('Invalid size gradient passed to d2y_dtdC')\n dydCext = np.concatenate(\n [dydCext, np.zeros((nC, 1))], axis=1)\n d2ydtdC = dydCext*0.\n\n dcy1 = yext[i1]*yext[i2]\n\n np.add.at(d2ydtdC, (range(nC), i3), -dcy1)\n np.add.at(d2ydtdC, (range(nC), i4), dcy1)\n\n iC = np.repeat(np.arange(nC), nC)\n i1t = np.tile(i1, nC)\n i2t = np.tile(i2, nC)\n i3t = np.tile(i3, nC)\n i4t = np.tile(i4, nC)\n\n dcy2 = np.tile(C, nC)*(dydCext[iC, i1t]*yext[i2t] +\n dydCext[iC, i2t]*yext[i1t])\n\n np.add.at(d2ydtdC, (iC, i3t), -dcy2)\n np.add.at(d2ydtdC, (iC, i4t), dcy2)\n\n d2ydtdC = d2ydtdC[:, :-1].reshape(-1)\n\n return d2ydtdC","title":""},{"docid":"658024c6332736f7e1456cc4e97587bc","score":"0.48092347","text":"def evalc(d, expression, arg = 0, include = '', address = 0x1fffda0, show_disassembly = False):\n compile(d, address, expression, include, show_disassembly)\n return d.blx(address + 1, arg)[0]","title":""},{"docid":"d11e89e8931eb85199ed3c025b0aae6e","score":"0.48031557","text":"def D_C(self, z):\n def integrand(z, om, ol):\n return 1. / sqrt(om * (1. + z)**3\n + (1. - om - ol) * (1. + z)**2 + ol)\n om, ol, h = self.om, self.ol, self.h\n res = integrate.quad(lambda x: integrand(x, om, ol), 0., z)\n return self.D_H * res[0]","title":""},{"docid":"36fba0d5ee7e3f52c3fa1c6088f1df36","score":"0.4795712","text":"def do_dxcl(self, params):\n try:\n args = self.dxcl_parser.parse_args(params.split())\n calls_args = argparse.Namespace()\n\n if args.class_name:\n if args.direction == 'to':\n calls_args.to_class = args.class_name\n elif args.direction == 'from':\n calls_args.from_class = args.class_name\n\n if args.method_name:\n if args.direction == 'to':\n calls_args.to_method = args.method_name\n elif args.direction == 'from':\n calls_args.from_method = args.method_name\n\n log.info(calls_args)\n # Get calls\n results = self.get_calls(calls_args)\n\n # Get cross-references\n xresults = self.analysis.xref_call(results, args.direction, args.xref_depth)\n\n # Create new graph\n calls_graph = CallGraph()\n\n for r in xresults:\n calls_graph.add_call(r)\n\n # Finalize graph\n calls_graph.finalize()\n\n # Write output\n if args.output:\n calls_graph.write(args.output_format, args.output, args.output_prog, args.output_args)\n log.info(\"Wrote results to %s\" % args.output)\n\n except SystemExit:\n pass","title":""},{"docid":"0c8629f97093fa64b4369cfcd602e20a","score":"0.47871363","text":"def calcdCdT(thermconsts):\n if thermconsts['LKFluid'] == 'ref':\n c1 = thermconsts['LKc1ref']\n c2 = thermconsts['LKc2ref']\n c3 = thermconsts['LKc3ref'] \n elif thermconsts['LKFluid'] == 'simple':\n c1 = thermconsts['LKc1simple']\n c2 = thermconsts['LKc2simple']\n c3 = thermconsts['LKc3simple']\n else:\n print ('LK error in calcLKC')\n\n T = thermconsts['Temperature']\n Tc = thermconsts['TCrit']\n t2 = T*T;\n t4 = t2*t2;\n tc3 = Tc*Tc*Tc;\n \n return (c2*Tc/t2) - (c3*tc3/t4)","title":""},{"docid":"68905102798ce5f854b823357fd40c25","score":"0.47779915","text":"def ccd(self):\n return CCDData.read(self.path)","title":""},{"docid":"53413c91c782d92eba920d33df543215","score":"0.4772914","text":"def det_coor(Gt, costth, wavelength, distance, y_size, z_size, \n dety_center, detz_center, R_tilt, tx, ty, tz):\n\n # Unit directional vector for reflection\n v = n.array([costth, \n wavelength/(2*n.pi)*Gt[1],\n wavelength/(2*n.pi)*Gt[2]])\n t = (R_tilt[0, 0]*distance - \\\n n.sum(R_tilt[:, 0]*n.array([tx, ty, tz])))/n.sum(R_tilt[:, 0]*v)\n Ltv = n.array([tx-distance, ty, tz])+ t*v\n dety = n.sum(R_tilt[:, 1]*Ltv)/y_size + dety_center\n detz = n.sum(R_tilt[:, 2]*Ltv)/z_size + detz_center\n return [dety, detz]","title":""},{"docid":"93f7c6fc3ba99233cf668906c5b1f49f","score":"0.4756373","text":"def get_CD(self, CL, delta_e):\n return self.get_quantity('CDtot', CL, delta_e)","title":""},{"docid":"bede35b9ab467b2a19ac860a6f13592f","score":"0.47293612","text":"def cdf(self, dist, v):","title":""},{"docid":"30572bc32c737cfc9bbfc86223fa124c","score":"0.4718782","text":"def do_dcl(self, params):\n try:\n args = self.dcl_parser.parse_args(params.split())\n results = self.get_calls(args)\n\n # Create new graph\n calls_graph = CallGraph()\n for r in results:\n calls_graph.add_call(r)\n\n # Finalize graph\n calls_graph.finalize()\n\n # Write output\n if args.output:\n if results:\n calls_graph.write(\n args.output_format, args.output,\n args.output_prog, args.output_args)\n log.info(\"Wrote results to %s\" % args.output)\n else:\n log.info(\"No results :(\")\n\n except SystemExit:\n pass","title":""},{"docid":"736cc0f7b23a7ffbf2d83d62dfa4084a","score":"0.4680829","text":"def set_Ccv_from_voltage_distance(\n self,\n voltage_node_idx: int,\n dV: float,\n charge_node_idx: int,\n ) -> None:\n capa_val = -elem_charge * dV\n self.set_capacitance(\n \"cv\",\n [charge_node_idx, voltage_node_idx],\n capa_val,\n )","title":""},{"docid":"b293554ea3cf66f9e58642ec2c6834ce","score":"0.46645945","text":"def MatlabDC(self,event):\n\t\tself.dyncore=1","title":""},{"docid":"67a26634c9cc9b498111881bdd404990","score":"0.4623921","text":"def CD_0(self):\r\n return self.CD_min + self.K_apo2 * self.CL_min ** 2","title":""},{"docid":"6e90fe87f5d1a2237e8519442c4c3613","score":"0.46181998","text":"def genDCD(residues,name,prot,path,run_type,n_chains):\n top = md.Topology()\n for _ in range(n_chains):\n chain = top.add_chain()\n for resname in prot.fasta:\n residue = top.add_residue(residues.loc[resname,'three'], chain)\n top.add_atom(residues.loc[resname,'three'], element=md.element.carbon, residue=residue)\n traj = md.load_dcd(path+\"/{:s}.dcd\".format(run_type), top)\n traj.center_coordinates()\n traj.xyz *= 10\n traj.unitcell_lengths *= 10\n traj.xyz += traj.unitcell_lengths[0,0]/2\n traj[:].save_dcd(path+\"/{:s}.dcd\".format(name))\n traj[0].save_pdb(path+\"/{:s}.pdb\".format(name))","title":""},{"docid":"b532cd39894710ea81daaeb6e066aa87","score":"0.45979238","text":"def ccmd(*targets, **kwargs):\n import subprocess\n\n def run_ccmd_checks(\n target, ret, checks, interval, source, timestamp, group, command, description, alert, **kwargs\n ):\n command = command.format(target=target)\n check_result = {\n \"success\": 0,\n \"checks\": checks,\n \"comment\": \"\",\n \"target\": target,\n \"check_type\": \"CCMD\",\n \"rtt\": 0.0,\n \"source\": source,\n \"@timestamp\": timestamp,\n \"group\": group,\n \"description\": description,\n \"command\": command,\n }\n command = [i.strip() for i in command.split(\" \") if i.strip()]\n # do CCMD checks\n for i in range(checks):\n try:\n result = subprocess.check_output(command, stderr=subprocess.STDOUT)\n result = result.decode(encoding=\"utf-8\")\n if (\n \"Destination net unreachable\" in result\n or \"TTL expired in transit\" in result\n or \"Destination host unreachable\" in result\n ):\n continue\n else:\n check_result[\"success\"] += 1\n except:\n check_result[\n \"comment\"\n ] += \"CCMD Check {}, ERROR in subprocess, command '{}' failed or returned non zero status code\\n\".format(\n i, str(command)\n )\n time.sleep(interval)\n # calculate success and loss percentages\n check_result[\"success\"] = (check_result[\"success\"] / checks) * 100\n check_result[\"loss\"] = 100 - check_result[\"success\"]\n # sent alert if requested to do so\n if check_result[\"success\"] == 0 and alert is True:\n _send_alert(check_type=\"CCMD\", target=target, data=check_result)\n # save thread run results\n ret[\"out\"].append(check_result)\n\n # initialize variables\n check_kwargs = _get_kwargs(**kwargs)\n # create threads objects\n job_threads = []\n for target_dict in targets:\n if not target_dict.get(\"command\") or not target_dict.get(\"target\"):\n log.error(\n \"dnuts.ccmd: no 'command' or 'target' argument found for target - {}\".format(target)\n )\n continue\n job_threads.append(\n Thread(\n target=run_ccmd_checks,\n kwargs=dict(\n target=target_dict[\"target\"].strip(),\n command=target_dict[\"command\"].strip(),\n description=target_dict.get(\"description\", \"\").strip(),\n **check_kwargs\n ),\n )\n )\n # run threads\n log.info(\n \"Running {len} CCMD connection checks in {threads} threads, {checks} check(s) per target, with {interval}s interval and {timeout}s timeout\".format(\n len=len(job_threads), **check_kwargs\n )\n )\n _run_threads(\n job_threads,\n max=check_kwargs[\"threads\"],\n timeout=check_kwargs[\"timeout\"] * 2 * check_kwargs[\"checks\"],\n )\n log.info(\"CCMD Checks completed\")\n\n return check_kwargs[\"ret\"]","title":""},{"docid":"9478451c3fa2b27a8ed7e0dbd44d7b08","score":"0.45846218","text":"def crc(self):\n return self.comp_command('DSCRC').lstrip('DSCRC ').rstrip()","title":""},{"docid":"ab2ea1f4c5e0d2418f73ac9044a6ec74","score":"0.45644945","text":"def _genCCCDiff(self,\n regName,\n name,\n title,\n caption,\n outputDir):\n\n import LATCRootData\n regInfo = LATCRootData.PRECINCT_INFO[self._precinctName][regName]\n \n regData = self._cfgPrecinctData.getRegisterData(regName)\n baselineData = self._baselinePrecinctData.getRegisterData(regName)\n diffData = [new - old for (new,old) in zip(regData,baselineData)]\n # extract GCCC index from global GCFE indeces\n import calConstant\n cccData = [calConstant.getCFEId(idx)[1] for idx in range(calConstant.GLOBAL_N_GCFE)]\n \n import ROOTPlotUtils\n return ROOTPlotUtils.make2DHist(cccData,\n diffData,\n name,\n title,\n caption,\n \"GCCC\",\n \"%s diff (cfg - baseline)\"%regName,\n outputDir,\n calConstant.NUM_GCCC,\n 2*(regInfo.maxVal+1),\n calConstant.NUM_GCCC,\n regInfo.maxVal+1,\n 0,\n -1*(regInfo.maxVal+1))","title":""},{"docid":"f5f00f4dca7539272090535912b5a235","score":"0.45629635","text":"def pgcdl(l):\n p=l[0]\n for i in range(1,len(l)):\n p=pgcd(p,l[i])\n return p","title":""},{"docid":"ffd453111561dafc3987bc185ecb1004","score":"0.45616314","text":"def write_cc(cdl):\n with open(cdl.file_out, 'wb') as cdl_f:\n cdl_f.write(cdl.xml_root)","title":""},{"docid":"5a1be46bc78fd58aa761924da4c55802","score":"0.455433","text":"def _ccmd(self, args, rv=0):\n assert type(args) == str\n # Ensure 'coverage' is turned off-- it won't work.\n self.cmdline_run(\"{0}\".format(args), exit=rv, coverage=False)","title":""},{"docid":"f55ee40d4f7dd059decd1e6cf99229f2","score":"0.4548994","text":"def Dc(self, z):\n if z==0:\n return 0\n else:\n f = lambda z: 1.0/self.__E(z)\n I = integrate.quad(f, 0, z)\n return self.Dh * I[0]","title":""},{"docid":"5ec8891e11763bbf07bc9da6ed97a767","score":"0.4543415","text":"def get_cl(field, bp, hd, mask, map, coupled_cell, tmp_path=None):\n\n # Initialize Cls\n n_bins = map.shape[1]\n n_ells = len(bp)\n cl = np.zeros((2, 2, n_ells, n_bins, n_bins))\n\n # Dimensions\n Nx = hd['NAXIS1']\n Ny = hd['NAXIS2']\n Lx = Nx*abs(hd['CDELT1'])*np.pi/180 # Mask dimension in radians\n Ly = Ny*abs(hd['CDELT2'])*np.pi/180 # Mask dimension in radians\n\n # Fields definition\n fd = np.array([nmt.NmtFieldFlat(\n Lx, Ly, mask[x], [map[0, x], -map[1, x]]) for x in range(n_bins)])\n # Bins for flat sky fields\n b = nmt.NmtBinFlat(bp[:, 0], bp[:, 1])\n # Effective ells\n ell = b.get_effective_ells()\n\n # Iterate over redshift bins to compute Cl's\n mcm_paths = []\n for nb1 in range(n_bins):\n for nb2 in range(nb1, n_bins):\n # Temporary path for mode coupling matrix\n if tmp_path is None:\n mcm_p = os.path.expanduser('~')\n else:\n mcm_p = tmp_path\n mcm_p = mcm_p+'/mcm_{}_Z{}{}.dat'.format(field, nb1+1, nb2+1)\n mcm_paths.append(mcm_p)\n # Define workspace for mode coupling matrix\n wf = nmt.NmtWorkspaceFlat()\n try:\n wf.read_from(mcm_p)\n except RuntimeError:\n wf.compute_coupling_matrix(fd[nb1], fd[nb2], b)\n wf.write_to(mcm_p)\n print('Calculated mode coupling matrix for bins {}{}'\n ''.format(nb1+1, nb2+1))\n sys.stdout.flush()\n # Calculate Cl's\n cl_c = nmt.compute_coupled_cell_flat(fd[nb1], fd[nb2], b)\n if coupled_cell is True:\n cl_d = cl_c\n else:\n cl_d = wf.decouple_cell(cl_c)\n cl_d = np.reshape(cl_d, (2, 2, n_ells))\n cl[:, :, :, nb1, nb2] = cl_d\n cl[:, :, :, nb2, nb1] = cl_d\n\n return ell, cl, mcm_paths","title":""},{"docid":"f03076ba667b5b3f85826b1dcf5ce982","score":"0.45395768","text":"def _ldc(self):\n value = self.pop(CONTROL)\n self._push_val(value) # adds value to memory and pushes it's address to STACK","title":""},{"docid":"6e71f803d765eb328a43f8019e074f76","score":"0.45364988","text":"def draw_clonal_marker(self):\n\n # add background noise\n self.fill(1, self.bg_level, self.bg_noise)\n\n # draw nuclei\n means = self.data['clonal_marker'].values\n stds = self.data['clonal_marker_std'].values\n self.draw_nuclei(channel=1, means=means, stds=stds)","title":""},{"docid":"2d5a35afa18a02a7c7a85b213b55688a","score":"0.45291862","text":"def _test_model_cld():\r\n print(\"Loading\")\r\n import coffeehouse_languagedetection\r\n print(\"Ready\\n\")\r\n\r\n while True:\r\n input_text = input(\"> \")\r\n results = coffeehouse_languagedetection.predict(input_text, dltc=False, cld=True, ld=False)\r\n print(results['cld'])\r\n print(results['cld'][0])","title":""},{"docid":"c57a1b04c7b961a41ad089ccb912ee14","score":"0.45217818","text":"def execute_gen_dc(self):\n # write the shading header\n self.write_static_shading()\n\n command1 = 'gen_dc \"{hea_path}\" -dir'.format(hea_path=self.hea_path)\n command2 = 'gen_dc \"{hea_path}\" -dif'.format(hea_path=self.hea_path)\n command3 = 'gen_dc \"{hea_path}\" -paste'.format(hea_path=self.hea_path)\n\n CEADaySim.run_cmd(command1)\n CEADaySim.run_cmd(command2)\n CEADaySim.run_cmd(command3)","title":""},{"docid":"055ed6c173c938da2fb017d7e9cee309","score":"0.4516811","text":"def calcdIdV(self):\n I = self.getI()\n self.dIdV = np.gradient(I,self.V_range)","title":""},{"docid":"42362d5e5b19638a5bc85fd009ddc25e","score":"0.44972062","text":"def clifford_conductor(self):\n D = self.disc()\n return prod([x[0] for x in factor(2 * self.level()) if self.clifford_invariant(x[0]) == -1])","title":""},{"docid":"b1ee72efbba9eae06c1783ac6f2ebfe8","score":"0.4482374","text":"def fetch_cdum() -> None:","title":""},{"docid":"eaa3872a87b6051eddb7b65625102710","score":"0.44770986","text":"def to_cshl_short(self) -> str:\n if self.variant_type & core.Allele.Type.substitution:\n return f\"sub({self.ref}->{self.alt})\"\n if self.variant_type & core.Allele.Type.small_insertion:\n return f\"ins({self.alt})\"\n if self.variant_type & core.Allele.Type.small_deletion:\n return f\"del({self.length})\"\n if self.variant_type & core.Allele.Type.complex:\n return f\"comp({self.ref}->{self.alt})\"\n if self.variant_type & core.Allele.Type.large_duplication:\n return \"CNV+\"\n if self.variant_type & core.Allele.Type.large_deletion:\n return \"CNV-\"\n raise ValueError(f\"unexpected variant type: {self.variant_type}\")","title":""},{"docid":"f32924eb57923c0873366b053a01239c","score":"0.44690257","text":"def cce_diag(config_map=None):\n # for pylint, otherwise \"Dangerous default value {} as argument\"\n if config_map is None:\n config_map = {}\n\n def _build(sch, tensor_list, kernel_name='cce_diag_op'):\n target = 'llvm'\n mod = tvm.build(sch, tensor_list, target, name=kernel_name)\n return mod\n\n def _lower(sch, tensor_list):\n print(tvm.lower(sch, tensor_list, simple_mode=True))\n\n def _check(mod, input_tensors, output_tensors, ref_input_func, ref_output_func, rtol):\n ctx = tvm.context('llvm', 0)\n if not ctx.exist:\n raise RuntimeError('Only support diagnose on CPU now')\n np_inputs = []\n tvm_inputs = []\n tvm_outputs = []\n if ref_input_func is None:\n for tensor in input_tensors:\n np_inputs.append(\n np.random.uniform(size=get_const_tuple(tensor.shape)).astype(tensor.dtype))\n else:\n np_inputs = ref_input_func(*input_tensors)\n for np_input in np_inputs:\n tvm_inputs.append(tvm.nd.array(np_input, ctx))\n\n for tensor in output_tensors:\n tvm_outputs.append(\n tvm.nd.array(np.zeros(get_const_tuple(tensor.shape), dtype=tensor.dtype), ctx))\n\n mod(*(tvm_inputs + tvm_outputs))\n if ref_output_func is None:\n print([output.asnumpy() for output in tvm_outputs])\n else:\n np_output = ref_output_func(*np_inputs)\n if rtol is None:\n np.testing.assert_allclose(tvm_outputs[0].asnumpy(), np_output, rtol=1e-3)\n else:\n np.testing.assert_allclose(tvm_outputs[0].asnumpy(), np_output, rtol=rtol)\n print('CHECK PASS')\n\n input_tensors = config_map[\"input_tensors\"]\n output_tensors = config_map[\"output_tensors\"]\n ref_input_func = config_map[\"ref_input_func\"]\n ref_output_func = config_map[\"ref_output_func\"]\n rtol = config_map[\"rtol\"]\n\n sch = tvm.create_schedule([x.op for x in output_tensors])\n if config_map[\"print_ir\"]:\n _lower(sch, input_tensors + output_tensors)\n\n mod = _build(sch, input_tensors + output_tensors, config_map[\"name\"])\n\n _check(mod, input_tensors, output_tensors, ref_input_func, ref_output_func, rtol)","title":""},{"docid":"3aa04ec97657f1aced10bc834b7accea","score":"0.44670403","text":"def calcdDdT(thermconsts):\n if thermconsts['LKFluid'] == 'ref':\n d2 = thermconsts['LKd2ref']\n elif thermconsts['LKFluid'] == 'simple':\n d2 = thermconsts['LKd2simple']\n else:\n print ('LK error in calcLKD')\n\n T = thermconsts['Temperature']\n Tc = thermconsts['TCrit']\n t2 = T*T\n return -(d2*Tc/t2)","title":""},{"docid":"8bd4484e6a5ab3f898361db36c5b89e3","score":"0.44381437","text":"def get_gate_invocation_c(self):\r\n # No function block is generated if one of the inputs is a wire with constant value.\r\n # I.e. either the constant or the second input wire is propagated to the output for the corresponding logic gate's logic function.\r\n if self.disable_generation:\r\n return \"\"\r\n else:\r\n return f\" {self.out.name} = {self.gate_type}({self.a.get_wire_value_c_hier()}, {self.b.get_wire_value_c_hier()});\\n\"","title":""},{"docid":"dd1cfb74c94fc94a13784b612b4589fd","score":"0.44379905","text":"def lll_cost(d):\n return d ** 3","title":""},{"docid":"9e94357064c0f2afb388440179f93aee","score":"0.44379246","text":"def cdy(f):\n n = f.shape[1]\n south = [0] + list(range(n-1))\n north = list(range(1,n)) + [n-1]\n return 0.5*(f[:,north] - f[:,south])","title":""},{"docid":"5da04385d387b99ae27b9060104b393d","score":"0.4416052","text":"def make_dbc(build: BuildData, labs_dir: str, dbc_path: str) -> NoReturn:\n try:\n gendbc(\n source_dir=labs_dir,\n encoding=\"utf-8\",\n dbc_path=dbc_path,\n dbc_folder=build.top_dbc_folder_name,\n flatten=False,\n verbose=verbosity_is_enabled(),\n debugging=False,\n )\n finally:\n pass","title":""},{"docid":"32c2ad273204b9006c5e7d36e8597b56","score":"0.44115666","text":"def toCylindrical(self,dir=[0,1,2]):\n f = zeros_like(self)\n x,y,z = [ self[...,i] for i in dir ]\n f[...,0] = sqrt(x*x+y*y)\n f[...,1] = arctan2(y,x) / rad\n f[...,2] = z\n return f","title":""},{"docid":"3b6503cb6681437f9d4c9f71e1596946","score":"0.44020143","text":"def C(source):\n return _embed_or_inline_c(source, True)","title":""},{"docid":"ce624478a3a2f1f5ba48ddb7dbbb3cfe","score":"0.43961677","text":"def hvs_crd(c1, c2, rev=False):\n if rev:\n endcord = (c2['elat'], c2['elon'])\n else:\n endcord = (c2['slat'], c2['slon'])\n return haversine((c1['elat'], c1['elon']), endcord)","title":""},{"docid":"b192a8f581539dfd9f40ebb5f7382744","score":"0.43924603","text":"def cdx(f):\n m = f.shape[0]\n west = [0] + list(range(m-1))\n east = list(range(1,m)) + [m-1]\n return 0.5*(f[east,:] - f[west,:])","title":""},{"docid":"ee6e872be2491df2b4169a8d904a057f","score":"0.4390537","text":"def LC2CL(tensor):\n # type: (Tensor) -> Tensor\n return tensor.transpose(0, 1).contiguous()","title":""},{"docid":"e3b288a3db20dce938a1c63f026cf47d","score":"0.4383879","text":"def genomic_to_cdna_coord(transcript, genomic_coord):\n exons = [exon.get_as_interval()\n for exon in get_exons(transcript)]\n\n if len(exons) == 0:\n return None\n\n strand = transcript.strand\n\n if strand == \"+\":\n exons.sort(key=lambda exon: exon.chrom_start)\n else:\n exons.sort(key=lambda exon: -exon.chrom_end)\n\n distances = [exon.distance(genomic_coord)\n for exon in exons]\n min_distance_to_exon = min(map(abs, distances))\n\n coding_offset = 0\n for exon in exons:\n exon_length = exon.chrom_end - exon.chrom_start\n distance = exon.distance(genomic_coord)\n if abs(distance) == min_distance_to_exon:\n if strand == \"+\":\n exon_start_cds_offset = coding_offset + 1\n exon_end_cds_offset = coding_offset + exon_length\n else:\n exon_start_cds_offset = coding_offset + exon_length\n exon_end_cds_offset = coding_offset + 1\n # This is the exon we want to annotate against.\n if distance == 0:\n # Inside the exon.\n if strand == \"+\":\n coord = (exon_start_cds_offset +\n (genomic_coord -\n (exon.chrom_start + 1)))\n else:\n coord = (exon_end_cds_offset +\n (exon.chrom_end -\n genomic_coord))\n cdna_coord = CDNACoord(coord, 0)\n else:\n # Outside the exon.\n if distance > 0:\n nearest_exonic = exon_start_cds_offset\n else:\n nearest_exonic = exon_end_cds_offset\n if strand == \"+\":\n distance *= -1\n\n # If outside transcript, don't use offset.\n if (genomic_coord < transcript.tx_position.chrom_start + 1 or\n genomic_coord > transcript.tx_position.chrom_stop):\n nearest_exonic += distance\n distance = 0\n cdna_coord = CDNACoord(nearest_exonic, distance)\n break\n coding_offset += exon_length\n\n # Adjust coordinates for coding transcript.\n if transcript.is_coding:\n # Detect if position before start codon.\n utr5p = get_utr5p_size(transcript) if transcript.is_coding else 0\n cdna_coord.coord -= utr5p\n if cdna_coord.coord <= 0:\n cdna_coord.coord -= 1\n else:\n # Detect if position is after stop_codon.\n exons = get_exons(transcript)\n stop_codon = find_stop_codon(exons, transcript.cds_position)\n stop_codon -= utr5p\n if (cdna_coord.coord > stop_codon or\n cdna_coord.coord == stop_codon and cdna_coord.offset > 0):\n cdna_coord.coord -= stop_codon\n cdna_coord.landmark = CDNA_STOP_CODON\n\n return cdna_coord","title":""},{"docid":"ca8eef915055a80110e94a478c94d646","score":"0.43692192","text":"def write_cl(filename, cl, dtype=np.float64):\n # check the dtype and convert it\n fitsformat = getformat(dtype)\n column_names = ['TEMPERATURE','GRADIENT','CURL','G-T','C-T','C-G']\n if isinstance(cl, list):\n cols = [pf.Column(name=column_name,\n format='%s'%fitsformat,\n array=column_cl) for column_name, column_cl in zip(column_names[:len(cl)], cl)]\n else: # we write only one TT\n cols = [pf.Column(name='TEMPERATURE',\n format='%s'%fitsformat,\n array=cl)]\n\n tbhdu = pf.BinTableHDU.from_columns(cols)\n # add needed keywords\n tbhdu.header['CREATOR'] = 'healpy'\n writeto(tbhdu, filename)","title":""},{"docid":"43329a638c037c76595e84ebf59a64ed","score":"0.43676528","text":"def __ccmd(self, args, rv=0):\n assert type(args) == str\n # Ensure 'coverage' is turned off-- it won't work.\n self.cmdline_run(\"{0}\".format(args), exit=rv, coverage=False)","title":""},{"docid":"2037383eadb3c2f16ee9bdab685fca19","score":"0.4366915","text":"def cllr(Hp_LRs, Hd_LRs):\n Np = len(Hp_LRs)\n Nd = len(Hd_LRs)\n return 1.0 / 2.0 * (\n (1.0 / Np * sum([np.log2(1 + 1.0 / LR) for LR in Hp_LRs])) + 1.0 / Nd * sum([np.log2(1 + LR) for LR in Hd_LRs]))","title":""},{"docid":"7e3fdc4477bebddc08bd7f6b17a25465","score":"0.43542147","text":"def clc(self) -> None:\n self.buf[self.pos] = 248\n self.pos += 1","title":""},{"docid":"3b97b58db7291c8d471c63b486ba8cc0","score":"0.4349628","text":"def test_cdm(baseline_file='cl_baseline_cdm.pkl',atol=1e-20,rtol=1e-3):\n print('\\nTesting Cls for cdm...\\n')\n check_cl_match(baseline_file,'cdm',atol=atol,rtol=rtol)","title":""},{"docid":"1f76fcc9b2f0b4e8ba968c3814ea5de4","score":"0.4337672","text":"def cci(self, n, array=False):\n result = talib.CCI(self.high, self.low, self.close, n)\n if array:\n return result\n return result[-1]","title":""},{"docid":"6a7181e257ef6314c2bc974c0dac6c3c","score":"0.43283027","text":"def genDCD(residues,name,prot):\n top = md.Topology()\n chain = top.add_chain()\n for resname in prot.fasta:\n residue = top.add_residue(residues.loc[resname,'three'], chain)\n top.add_atom(residues.loc[resname,'three'], element=md.element.carbon, residue=residue)\n for i in range(len(prot.fasta)-1):\n top.add_bond(top.atom(i),top.atom(i+1))\n traj = md.load(prot.path+\"/{:s}_0.gsd\".format(name), top)[1000:]\n traj.top = top\n for replica in range(1,replicas(prot)):\n t = md.load(prot.path+\"/{:s}_{:d}.gsd\".format(name,replica), top)[1000:]\n t.top = top\n traj = md.join([traj,t])\n del t\n traj = traj.image_molecules(inplace=False, anchor_molecules=[set(traj.top.chain(0).atoms)], make_whole=True)\n traj.center_coordinates()\n traj.xyz += traj.unitcell_lengths[0,0]/2\n traj.save_dcd(prot.path+\"/{:s}.dcd\".format(name))\n traj[0].save_pdb(prot.path+\"/{:s}.pdb\".format(name))\n for replica in range(replicas(prot)):\n os.remove(prot.path+\"/{:s}_{:d}.gsd\".format(name,replica))","title":""},{"docid":"59f759cb79ef49dde6095ceb73a4ce42","score":"0.43271166","text":"def do_cd(self, line):\n args = self.line_to_args(line)\n if len(args) == 0:\n dirname = '~'\n else:\n if args[0] == '-':\n dirname = self.prev_dir\n else:\n dirname = args[0]\n dirname = resolve_path(self.cur_dir, dirname)\n\n mode = auto(self.devs, get_mode, dirname)\n if mode_isdir(mode):\n self.prev_dir = self.cur_dir\n self.cur_dir = dirname\n auto(self.devs, chdir, dirname)\n else:\n eprint(\"Directory '%s' does not exist\" % dirname)","title":""},{"docid":"f5ac87133ba0723857a4b114a5633826","score":"0.4322817","text":"def dot_c(self):\n return ' '*self.indent_level+self._sep.join(self._defs)","title":""},{"docid":"35a0bec5c5fa65e1c7bb723643d74062","score":"0.4320173","text":"def cdhit(\n input_fasta: str,\n percent_identity: float,\n length_difference_cutoff: float = None,\n min_alignment_coverage: float = None,\n percent_identity_suffix: bool = False,\n output_dir: str = None\n) -> None:\n\n if not os.path.exists(input_fasta):\n raise FileNotFoundError(f'Fasta file {input_fasta} was not found.')\n\n if output_dir is not None:\n if not os.path.isdir(output_dir):\n raise NotADirectoryError(f'{output_dir} is not a directory.')\n output_prefix = os.path.join(output_dir, os.path.splitext(os.path.basename(input_fasta))[0])\n else:\n output_prefix = os.path.splitext(input_fasta)[0]\n\n if percent_identity_suffix:\n output_prefix = output_prefix + str(percent_identity)\n # from pdb import set_trace; set_trace()\n params = [\n 'cd-hit',\n '-i', input_fasta,\n '-o', output_prefix,\n '-c', str(percent_identity),\n '-n', str(_cdhit_word_size(percent_identity)),\n '-d', '0',\n '-sc', '1',\n ]\n\n if length_difference_cutoff is not None:\n params.extend(['-s', str(length_difference_cutoff)])\n\n if min_alignment_coverage is not None:\n params.extend([\n '-aL', str(min_alignment_coverage),\n '-aS', str(min_alignment_coverage),\n ])\n\n subprocess.check_call(params)","title":""},{"docid":"c2c6958c103993dd1bc1eb0e137796e9","score":"0.43184483","text":"def DC(self,V=0, ch=1):\n\t\t\n\t\tself.session.write(\":SOUR%d:APPL:DC DEF,DEF, %.4f\" % (ch,V))","title":""},{"docid":"c249095397e69fd63a33dac96f568537","score":"0.4313726","text":"def calcd(self, t):\n\n if t < self.x[0]:\n return None\n elif t > self.x[-1]:\n return None\n\n i = self.__search_index(t)\n dx = t - self.x[i]\n result = self.b[i] + 2.0 * self.c[i] * dx + 3.0 * self.d[i] * dx ** 2.0\n return result","title":""},{"docid":"9e65b76d841a1487f31b9746fbdea7b4","score":"0.43133104","text":"def dwwc(\n graph,\n metapath,\n damping=0.5,\n dense_threshold=0,\n dtype=numpy.float64,\n dwwc_method=None,\n):\n return dwwc_method(\n graph=graph,\n metapath=metapath,\n damping=damping,\n dense_threshold=dense_threshold,\n dtype=dtype,\n )","title":""},{"docid":"a597b14013e443be5f5c3a8501155223","score":"0.43100724","text":"def cxtd_comp_from_undirected(self):\n self.cxtd_comp = list(nx.connected_component_subgraphs(self.disgraph))\n print(\"Num of cxtd comps in disgarph: %d\"%(len(self.cxtd_comp)))","title":""},{"docid":"9d4c47402d034aba208f8f79d1e80079","score":"0.43012372","text":"def compute_C_matrix(self):\n self.C = np.repeat(np.diag(self.Lp)[:, np.newaxis],\n self.Lp.shape[0], axis=1)\n self.C += np.repeat(np.diag(self.Lp)[np.newaxis, :],\n self.Lp.shape[0], axis=0)\n self.C -= 2*self.Lp\n # the following is much slower\n # self.C = np.zeros(self.Lp.shape)\n # for i in range(self.Lp.shape[0]):\n # for j in range(self.Lp.shape[1]):\n # self.C[i, j] = self.Lp[i, i] + self.Lp[j, j] - 2*self.Lp[i, j]\n volG = np.sum(self.z)\n self.C *= volG\n sett.mt(0, 'computed commute distance matrix')\n self.Dchosen = self.C","title":""},{"docid":"c53598f524c632a699ad3aefd3bf12b1","score":"0.42999962","text":"def convert_coulomb(self, data):\r\n\r\n return \"{} C\".format(data)","title":""},{"docid":"2a8c151c0c157aa1896976808d02d0d0","score":"0.42947423","text":"def cy(self, ctl, tgt):\n return self.append(CyGate(), [ctl, tgt], [])","title":""},{"docid":"6261b6e63f0b61d17cb423fef8c4f465","score":"0.42942545","text":"def cdist(self, x, y):\n\n differences = x.unsqueeze(1) - y.unsqueeze(0)\n distances = torch.sum(differences**2, -1).sqrt()\n return distances","title":""},{"docid":"7803f994ac5b2fa4f389ef4c430673c0","score":"0.42906135","text":"def gen_cord(dot_number):\n global lt\n if len(lt[dot_number]) > 0: # if we already have coord-s for current dot in cache\n yield from lt[dot_number]\n return # we don't need to recalculate them again -> return\n i = (matrix[0][dot_number])\n s = set()\n for j in range(i + 1):\n s.update(((j, i - j), (j, -(i - j)), (-j, -(i - j)), (-j, i - j)))\n if len(s) > i * 2: # to speed up the calculation we compute partially\n yield from s # The same as \"for p in s: yield p\"\n lt[dot_number] = lt[dot_number].union(s)\n s.clear()\n if len(s) > 0: # remains\n yield from s\n lt[dot_number] = lt[dot_number].union(s)","title":""},{"docid":"a281fa05065db4cb810bf44ba46ebe5e","score":"0.42890027","text":"def closeness_centrality(self, distance=None, write=False,\n write_property=None):\n if distance is not None:\n warnings.warn(\n \"Weighted closeness centrality for Neo4j graphs \"\n \"is not implemented: computing the unweighted version\",\n MetricProcessor.MetricProcessingWarning)\n result = self._run_gdc_query(\n \"gds.alpha.closeness\", \"closeness\", weight=None,\n write=write, write_property=write_property,\n score_name=\"centrality\")\n return result","title":""},{"docid":"8ee95a5141df0890d43382cb3f4d5f7a","score":"0.42743996","text":"def _get_c_l(self) -> float:\n return self._c_l","title":""},{"docid":"59174e599277637b60a3ed5f32c9d5b7","score":"0.42741856","text":"def convert_candela(self, data):\r\n\r\n return \"{} cd\".format(data)","title":""},{"docid":"f045ac790efc806ebead1f0008344665","score":"0.42726877","text":"def C(self, q , dq ): \n \n [c1,s1,c2,s2,c12,s12] = self.trig( q )\n \n h = self.m2 * self.l1 * self.lc2 * s2\n \n C = np.zeros((2,2))\n \n C[0,0] = - h * dq[1]\n C[1,0] = h * dq[0]\n C[0,1] = - h * ( dq[0] + dq[1] )\n C[1,1] = 0\n\n \n return C","title":""},{"docid":"d481ee0f690587c040b20bddd6a643cf","score":"0.42699832","text":"def run_command(command):\n p = subprocess.Popen(['cl'], shell=True, stdout=subprocess.PIPE,\n stderr=subprocess.STDOUT)\n text = p.stdout.read()\n return 0, text","title":""},{"docid":"8665c12e99bbc4bba290ba67e6d85fee","score":"0.42662162","text":"def compute_ctc_loss(logits, labels, logit_length, label_length):\r\n return tf.nn.ctc_loss(\r\n labels=labels,\r\n logits=logits,\r\n label_length=label_length,\r\n logit_length=logit_length,\r\n logits_time_major=False,\r\n unique=None,\r\n blank_index=-1,\r\n name=None\r\n )","title":""},{"docid":"9aa4d909b59fb3940f2682374f734545","score":"0.4264086","text":"def to_cshl_full(self) -> str:\n if self.variant_type & core.Allele.Type.tandem_repeat:\n return f\"TR({self.tr_ref}x{self.tr_unit}->{self.tr_alt})\"\n if self.variant_type & core.Allele.Type.substitution:\n return f\"sub({self.ref}->{self.alt})\"\n if self.variant_type & core.Allele.Type.small_insertion:\n return f\"ins({self.alt})\"\n if self.variant_type & core.Allele.Type.small_deletion:\n return f\"del({self.length})\"\n if self.variant_type & core.Allele.Type.complex:\n return f\"comp({self.ref}->{self.alt})\"\n if self.variant_type & core.Allele.Type.large_duplication:\n return \"CNV+\"\n if self.variant_type & core.Allele.Type.large_deletion:\n return \"CNV-\"\n raise ValueError(f\"unexpected variant type: {self.variant_type}\")","title":""},{"docid":"5bf4a544d11dd84b0c2de9b26ad5c04a","score":"0.42640367","text":"def Calcd(self,t):\n \n j=int(math.floor(t))\n if(j<0):\n j=0\n elif(j>=len(self.a)):\n j=len(self.a)-1\n\n dt=t-j\n result=self.b[j]+2.0*self.c[j]*dt+3.0*self.d[j]*dt*dt\n return result","title":""},{"docid":"e04d1e18bddbd4df1af371a80c05a324","score":"0.42573228","text":"def gcdex(self, a, b):\n return python_gcdex(a, b)","title":""},{"docid":"c50fa3111f6bc964518c482970d84a7f","score":"0.4257226","text":"def _get_C_cc_diagonals(self) -> npt.NDArray[np.float64]:\n C_cv_sums = np.sum(np.absolute(np.array(self._C_cv)), axis=1)\n # from other dots:\n off_diag = self._C_cc - np.diag(np.diag(self._C_cc))\n off_diag_sums = np.sum(np.absolute(off_diag), axis=1)\n\n diag = C_cv_sums + off_diag_sums\n diag += np.absolute(self._c_r) + np.absolute(self._c_r)\n\n return np.diag(diag)","title":""},{"docid":"da64da90405b8d849840b52f6f8c5767","score":"0.42549163","text":"def get_gate_invocation_c(self):\r\n # No function block is generated if one of the inputs is a wire with constant value.\r\n # I.e. either the constant or the second input wire is propagated to the output for the corresponding logic gate's logic function.\r\n if self.disable_generation:\r\n return \"\"\r\n else:\r\n return f\" {self.out.name} = {self.gate_type}({self.a.get_wire_value_c_hier()});\\n\"","title":""},{"docid":"8a8b86338f1062b57dbed0901cc42815","score":"0.42515898","text":"def getNodeCD(self):\n return self.__nodeCD","title":""},{"docid":"0131b73008109e2eef8aa3843d067f7e","score":"0.4247958","text":"def dV_C(self, z):\n om, ol, h = self.om, self.ol, self.h\n ok = 1. - om - ol\n _D_H = self.D_H\n _D_A = self.D_A(z)\n return _D_H * (1. + z)**2 * _D_A**2 / E(z, om, ol)","title":""},{"docid":"5eb5af85f794eeb1dbc71afbf197cbab","score":"0.42442828","text":"def cosh(x1):\n\n if (use_origin_backend(x1)):\n return numpy.cosh(x1)\n\n if not isinstance(x1, dparray):\n raise TypeError(f\"DPNP cosh(): Unsupported x1={type(x1)}\")\n\n return dpnp_cosh(x1)","title":""},{"docid":"6d710b10f3c798bbc43a98c10bc118bb","score":"0.42385876","text":"def CylindricalGrid2D(dr=None, dz=None, \n nr=None, nz=None, \n Lr=None, Lz=None,\n dx=1., dy=1., \n nx=None, ny=None,\n Lx=None, Ly=None,\n origin=((0,),(0,)),\n overlap=2,\n communicator=parallelComm):\n\n\n\n\n if dr is not None:\n dx = dr\n\n if dz is not None:\n dy = dz\n\n\n nx = nr or nx\n ny = nz or ny\n\n Lx = Lr or Lx\n Ly = Lz or Ly\n \n if numerix.getShape(dx) == () and numerix.getShape(dy) == ():\n\n dx, nx = _dnl(dx, nx, Lx)\n dy, ny = _dnl(dy, ny, Ly)\n from fipy.meshes.cylindricalUniformGrid2D import CylindricalUniformGrid2D\n return CylindricalUniformGrid2D(dx=dx, dy=dy, nx=nx or 1, ny=ny or 1, origin=origin, overlap=overlap, communicator=communicator)\n else:\n from fipy.meshes.cylindricalNonUniformGrid2D import CylindricalNonUniformGrid2D\n return CylindricalNonUniformGrid2D(dx=dx, dy=dy, nx=nx, ny=ny, origin=origin, overlap=overlap, communicator=communicator)","title":""},{"docid":"9efaa01bf65441af1794a17447f4fa75","score":"0.42385522","text":"def cmidd(x, y, z, base=2):\n assert len(x) == len(y) == len(z), \"Arrays should have same length\"\n xz = np.c_[x, z]\n yz = np.c_[y, z]\n xyz = np.c_[x, y, z]\n return entropyd(xz, base) + entropyd(yz, base) - entropyd(xyz, base) - entropyd(z, base)","title":""},{"docid":"24003c9b109a4f8fac267e7305ea8665","score":"0.42337123","text":"def addDCC(self, lda_address, lda_channel):\n print \"force DCC\"\n theDcc = Dcc()\n theDcc.setString(\"LDA_ADDRESS\", lda_address)\n theDcc.setInt(\"LDA_CHANNEL\", lda_channel)\n self.dccConf.add(theDcc)\n self.dccs.append(theDcc)\n print \"\\t DCC added\", theDcc.getString(\"LDA_ADDRESS\"), theDcc.getInt(\"LDA_CHANNEL\")","title":""}],"string":"[\n {\n \"docid\": \"10f6e1d757e33098a497f06762b836a0\",\n \"score\": \"0.6387597\",\n \"text\": \"def cl(self, c):\\n self.force_menu('oper')\\n self.send('cl ' + str(c))\\n return output(self.proc.before)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"93fe9d0119da5f74106fdbe79ae1cdc7\",\n \"score\": \"0.5471392\",\n \"text\": \"def do_ccmd(self, args):\\n print 'args:', args.split()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"753df6ce3ce639b27fc94b20be4374d9\",\n \"score\": \"0.5453434\",\n \"text\": \"def gen_c_instruction(self, dest, comp, jump):\\n return '111' + self.comp(comp) + self.dest(dest) + self.jump(jump)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"91b8cb9b58d6fbcde90e6b276a962fce\",\n \"score\": \"0.53294784\",\n \"text\": \"def cmd_makecldf(self, args):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a004240355f4033a155a694cf0dca221\",\n \"score\": \"0.5321995\",\n \"text\": \"def d017100cc ( state ) :\\n byte = state[\\\"byte\\\"]\\n stream = state[\\\"stream\\\"]\\n\\n cc = cctable[byte&0xFF-0o100]\\n\\n state[\\\"size\\\"] = \\\"r32\\\"\\n\\n rmfield = parse_rm(state)\\n regfield = parse_reg(state)\\n\\n return f'CMOV{cc} {regfield}, {rmfield}'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a4f57c2d0dd37eb167ac00eb2e22cfff\",\n \"score\": \"0.53189015\",\n \"text\": \"def d160cc ( state ) :\\n byte = state[\\\"byte\\\"]\\n stream = state[\\\"stream\\\"]\\n\\n cc = cctable[byte-0o160]\\n\\n disp8 = int.from_bytes(stream.read(1), byteorder='little', signed=True)\\n state[\\\"pos\\\"] += 1\\n state[\\\"hex\\\"].append(f'{disp8&0xFF:08X}')\\n\\n return f'J{cc} {disp8} to {state[\\\"pos\\\"]+disp8:08X}'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"515af1abe08cbabc3057958996665783\",\n \"score\": \"0.51874214\",\n \"text\": \"def cldf(self) -> pycldf.Dataset:\\n if self._cldf is None:\\n raise AttributeError('Writer.cldf is only set when Writer is used in with statement!')\\n return self._cldf\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b9c6cc1a6e17af463fc83c0f895e6af6\",\n \"score\": \"0.5133083\",\n \"text\": \"def write_cdl(cdl):\\n\\n values = list(cdl.slope)\\n values.extend(cdl.offset)\\n values.extend(cdl.power)\\n values.append(cdl.sat)\\n values = [str(i) for i in values]\\n\\n ss_cdl = ' '.join(values)\\n\\n with open(cdl.file_out, 'wb') as cdl_f:\\n cdl_f.write(enc(ss_cdl))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ae55651318111e9c526738cc94a4439b\",\n \"score\": \"0.5131566\",\n \"text\": \"def ccds():\\n allowed_str_args = ['hgnc_symbol', 'ccdsid']\\n\\n allowed_int_args = ['limit', 'hgnc_identifier']\\n\\n args = get_args(\\n request_args=request.args,\\n allowed_int_args=allowed_int_args,\\n allowed_str_args=allowed_str_args\\n )\\n\\n return jsonify(query.ccds(**args))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3a79cc8f7e312979d06c7a7d06d2f4e8\",\n \"score\": \"0.5094653\",\n \"text\": \"def cldf_dir(self) -> DataDir:\\n return self.dir / 'cldf'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5a261b26f5a0f85c1b280a15c8f373a7\",\n \"score\": \"0.50675637\",\n \"text\": \"def _parse_c_instruction(self):\\n line = '111'\\n line += self.code.comp(self.parser.comp)\\n line += self.code.dest(self.parser.dest)\\n line += self.code.jump(self.parser.jump)\\n self._write_line(line)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b485e57165e7f1e004356df1547a1064\",\n \"score\": \"0.5047674\",\n \"text\": \"def cmd_makecldf(self, args: argparse.Namespace):\\n args.log.warning('cmd_{0} not implemented for dataset {1}'.format('makecldf', self.id))\\n return NOOP\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5015fb32fe82f726f9ad048426a158e3\",\n \"score\": \"0.5033455\",\n \"text\": \"def request_cdr(self):\\n self.model.request_computed_value_output(\\\"cdr\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"249e103a985c24429e822934d79ff480\",\n \"score\": \"0.49677145\",\n \"text\": \"def set_dc(self):\\n self.instr.write(self.channel + ':COUPLING DC')\\n return None\",\n \"title\": \"\"\n },\n {\n \"docid\": \"01c26aa345440ac251f5bdbab47fd57e\",\n \"score\": \"0.49471664\",\n \"text\": \"def ldc(concentration, discharge,\\n conversion_factor,\\n target_concentration=None,\\n y_label='Load',\\n yscale='log',\\n ylim=None,\\n ax=None,\\n label_conditions=False):\\n rank = rankdata(discharge)\\n # calculate probability of each rank\\n prob = (1-(rank/(len(rank)+1)))*100\\n load = concentration * discharge * conversion_factor\\n\\n if ax is None:\\n fig, ax = plt.subplots(1)\\n\\n # plot target curve\\n if target_concentration is None:\\n target_concentration = load_mean_concentration(concentration, discharge)\\n\\n hb_extent = None\\n if ylim is not None:\\n plot_ylim = ylim\\n hb_extent=(1,100, ylim[0], ylim[1])\\n\\n if yscale is 'log':\\n plot_ylim = (10**ylim[0], 10**ylim[1])\\n\\n\\n\\n # plot data via matplotlib\\n hb = ax.hexbin(prob, load, gridsize=50,\\n yscale=yscale,\\n cmap='pink_r',\\n mincnt=1,\\n extent=hb_extent,\\n linewidths=0.2)\\n\\n target_ldc(target_concentration, discharge, conversion_factor, ax=ax)\\n\\n cb = plt.colorbar(hb, ax=ax, orientation='horizontal')\\n cb.set_label('Count')\\n #ax.set_yscale('log')\\n ax.set_ylabel(y_label)\\n ax.set_xlabel('Flow Duration Interval (%)')\\n ax.grid(alpha=0.2, which='both', linestyle='--', linewidth=0.5)\\n #ax.grid(alpha=0.2, which='major', linestyle='--', linewidth=0.5)\\n ax.set_xlim(0,100)\\n\\n if ylim is not None:\\n ax.set_ylim(plot_ylim)\\n\\n if label_conditions==True:\\n label_dc_flow_conditions(ax)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"46e7009cc6e33ee12cffd3b98259dc60\",\n \"score\": \"0.49342784\",\n \"text\": \"def do_c(self, line):\\n return self.do_connect(line)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"51bf1c0e1eda52758309b4cc82022db0\",\n \"score\": \"0.48940757\",\n \"text\": \"def d2cd(d, e):\\n cd = e.css('cd', 0)\\n # Test for division by 0\\n if cd + e.gd:\\n return (d + e.gd) / (cd + e.gd)\\n # Undefined, no info about column depth and gutter or zero division.\\n return 0\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e928e0c6aba962fd3537c711206634b8\",\n \"score\": \"0.4871802\",\n \"text\": \"def write_dcd (self, filename='tfd', dirname='.') :\\n Conformers.write_dcd(self,filename,dirname)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"4efe20ed0dc8e705c5cea87f96f14e98\",\n \"score\": \"0.48573828\",\n \"text\": \"def d017200cc ( state ) :\\n byte = state[\\\"byte\\\"]\\n stream = state[\\\"stream\\\"]\\n\\n cc = cctable[byte&0xFF-0o200]\\n\\n disp32 = int.from_bytes(stream.read(4), byteorder='little', signed=True)\\n state[\\\"pos\\\"] += 4\\n state[\\\"hex\\\"].append(f'{disp32&0xFFFFFFFF:08X}')\\n\\n return f'J{cc} {disp32} to {state[\\\"pos\\\"]+disp32:08X}'\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2c6138323f516b24cbff4600d2fb59f2\",\n \"score\": \"0.4829934\",\n \"text\": \"def toggle_dcn(self, dcn_id: str):\\n if self.dcn:\\n self.dcn = None\\n self.setText(12, '')\\n self.cooling.setDisabled(False)\\n else:\\n self.dcn = dcn_id\\n self.setText(12, dcn_id)\\n self.cooling.setDisabled(True)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b54c4b7d2d179e178c94032bf72acea6\",\n \"score\": \"0.48284918\",\n \"text\": \"def cpd():\\n return pkp.cpd.CPD(ultimate_analysis=ua, proximate_analysis=pa,\\n pressure=101325, name='CPD coal')\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a1d9ba9d6d04360d7bfe3d0a90554e9b\",\n \"score\": \"0.4827443\",\n \"text\": \"def cdf(self, d):\\n y = norm.ppf(d, 0, 1)\\n\\n return multivariate_normal.cdf(y, mean=None, cov=self.corrMatrix)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0bcae870cb45e81d55601e0b9b170f6f\",\n \"score\": \"0.481945\",\n \"text\": \"def d2y_dtdC(self, y, dydC):\\n\\n C = self._cdata['C']\\n nC = len(C)\\n i1, i2, i3, i4 = self._cdata['i'].T\\n\\n yext = np.concatenate([y, [1]])\\n dydCext = dydC.reshape(-1, self._N)\\n if dydCext.shape[0] != nC:\\n raise ValueError('Invalid size gradient passed to d2y_dtdC')\\n dydCext = np.concatenate(\\n [dydCext, np.zeros((nC, 1))], axis=1)\\n d2ydtdC = dydCext*0.\\n\\n dcy1 = yext[i1]*yext[i2]\\n\\n np.add.at(d2ydtdC, (range(nC), i3), -dcy1)\\n np.add.at(d2ydtdC, (range(nC), i4), dcy1)\\n\\n iC = np.repeat(np.arange(nC), nC)\\n i1t = np.tile(i1, nC)\\n i2t = np.tile(i2, nC)\\n i3t = np.tile(i3, nC)\\n i4t = np.tile(i4, nC)\\n\\n dcy2 = np.tile(C, nC)*(dydCext[iC, i1t]*yext[i2t] +\\n dydCext[iC, i2t]*yext[i1t])\\n\\n np.add.at(d2ydtdC, (iC, i3t), -dcy2)\\n np.add.at(d2ydtdC, (iC, i4t), dcy2)\\n\\n d2ydtdC = d2ydtdC[:, :-1].reshape(-1)\\n\\n return d2ydtdC\",\n \"title\": \"\"\n },\n {\n \"docid\": \"658024c6332736f7e1456cc4e97587bc\",\n \"score\": \"0.48092347\",\n \"text\": \"def evalc(d, expression, arg = 0, include = '', address = 0x1fffda0, show_disassembly = False):\\n compile(d, address, expression, include, show_disassembly)\\n return d.blx(address + 1, arg)[0]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d11e89e8931eb85199ed3c025b0aae6e\",\n \"score\": \"0.48031557\",\n \"text\": \"def D_C(self, z):\\n def integrand(z, om, ol):\\n return 1. / sqrt(om * (1. + z)**3\\n + (1. - om - ol) * (1. + z)**2 + ol)\\n om, ol, h = self.om, self.ol, self.h\\n res = integrate.quad(lambda x: integrand(x, om, ol), 0., z)\\n return self.D_H * res[0]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"36fba0d5ee7e3f52c3fa1c6088f1df36\",\n \"score\": \"0.4795712\",\n \"text\": \"def do_dxcl(self, params):\\n try:\\n args = self.dxcl_parser.parse_args(params.split())\\n calls_args = argparse.Namespace()\\n\\n if args.class_name:\\n if args.direction == 'to':\\n calls_args.to_class = args.class_name\\n elif args.direction == 'from':\\n calls_args.from_class = args.class_name\\n\\n if args.method_name:\\n if args.direction == 'to':\\n calls_args.to_method = args.method_name\\n elif args.direction == 'from':\\n calls_args.from_method = args.method_name\\n\\n log.info(calls_args)\\n # Get calls\\n results = self.get_calls(calls_args)\\n\\n # Get cross-references\\n xresults = self.analysis.xref_call(results, args.direction, args.xref_depth)\\n\\n # Create new graph\\n calls_graph = CallGraph()\\n\\n for r in xresults:\\n calls_graph.add_call(r)\\n\\n # Finalize graph\\n calls_graph.finalize()\\n\\n # Write output\\n if args.output:\\n calls_graph.write(args.output_format, args.output, args.output_prog, args.output_args)\\n log.info(\\\"Wrote results to %s\\\" % args.output)\\n\\n except SystemExit:\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0c8629f97093fa64b4369cfcd602e20a\",\n \"score\": \"0.47871363\",\n \"text\": \"def calcdCdT(thermconsts):\\n if thermconsts['LKFluid'] == 'ref':\\n c1 = thermconsts['LKc1ref']\\n c2 = thermconsts['LKc2ref']\\n c3 = thermconsts['LKc3ref'] \\n elif thermconsts['LKFluid'] == 'simple':\\n c1 = thermconsts['LKc1simple']\\n c2 = thermconsts['LKc2simple']\\n c3 = thermconsts['LKc3simple']\\n else:\\n print ('LK error in calcLKC')\\n\\n T = thermconsts['Temperature']\\n Tc = thermconsts['TCrit']\\n t2 = T*T;\\n t4 = t2*t2;\\n tc3 = Tc*Tc*Tc;\\n \\n return (c2*Tc/t2) - (c3*tc3/t4)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"68905102798ce5f854b823357fd40c25\",\n \"score\": \"0.47779915\",\n \"text\": \"def ccd(self):\\n return CCDData.read(self.path)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"53413c91c782d92eba920d33df543215\",\n \"score\": \"0.4772914\",\n \"text\": \"def det_coor(Gt, costth, wavelength, distance, y_size, z_size, \\n dety_center, detz_center, R_tilt, tx, ty, tz):\\n\\n # Unit directional vector for reflection\\n v = n.array([costth, \\n wavelength/(2*n.pi)*Gt[1],\\n wavelength/(2*n.pi)*Gt[2]])\\n t = (R_tilt[0, 0]*distance - \\\\\\n n.sum(R_tilt[:, 0]*n.array([tx, ty, tz])))/n.sum(R_tilt[:, 0]*v)\\n Ltv = n.array([tx-distance, ty, tz])+ t*v\\n dety = n.sum(R_tilt[:, 1]*Ltv)/y_size + dety_center\\n detz = n.sum(R_tilt[:, 2]*Ltv)/z_size + detz_center\\n return [dety, detz]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"93f7c6fc3ba99233cf668906c5b1f49f\",\n \"score\": \"0.4756373\",\n \"text\": \"def get_CD(self, CL, delta_e):\\n return self.get_quantity('CDtot', CL, delta_e)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"bede35b9ab467b2a19ac860a6f13592f\",\n \"score\": \"0.47293612\",\n \"text\": \"def cdf(self, dist, v):\",\n \"title\": \"\"\n },\n {\n \"docid\": \"30572bc32c737cfc9bbfc86223fa124c\",\n \"score\": \"0.4718782\",\n \"text\": \"def do_dcl(self, params):\\n try:\\n args = self.dcl_parser.parse_args(params.split())\\n results = self.get_calls(args)\\n\\n # Create new graph\\n calls_graph = CallGraph()\\n for r in results:\\n calls_graph.add_call(r)\\n\\n # Finalize graph\\n calls_graph.finalize()\\n\\n # Write output\\n if args.output:\\n if results:\\n calls_graph.write(\\n args.output_format, args.output,\\n args.output_prog, args.output_args)\\n log.info(\\\"Wrote results to %s\\\" % args.output)\\n else:\\n log.info(\\\"No results :(\\\")\\n\\n except SystemExit:\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"736cc0f7b23a7ffbf2d83d62dfa4084a\",\n \"score\": \"0.4680829\",\n \"text\": \"def set_Ccv_from_voltage_distance(\\n self,\\n voltage_node_idx: int,\\n dV: float,\\n charge_node_idx: int,\\n ) -> None:\\n capa_val = -elem_charge * dV\\n self.set_capacitance(\\n \\\"cv\\\",\\n [charge_node_idx, voltage_node_idx],\\n capa_val,\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b293554ea3cf66f9e58642ec2c6834ce\",\n \"score\": \"0.46645945\",\n \"text\": \"def MatlabDC(self,event):\\n\\t\\tself.dyncore=1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"67a26634c9cc9b498111881bdd404990\",\n \"score\": \"0.4623921\",\n \"text\": \"def CD_0(self):\\r\\n return self.CD_min + self.K_apo2 * self.CL_min ** 2\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6e90fe87f5d1a2237e8519442c4c3613\",\n \"score\": \"0.46181998\",\n \"text\": \"def genDCD(residues,name,prot,path,run_type,n_chains):\\n top = md.Topology()\\n for _ in range(n_chains):\\n chain = top.add_chain()\\n for resname in prot.fasta:\\n residue = top.add_residue(residues.loc[resname,'three'], chain)\\n top.add_atom(residues.loc[resname,'three'], element=md.element.carbon, residue=residue)\\n traj = md.load_dcd(path+\\\"/{:s}.dcd\\\".format(run_type), top)\\n traj.center_coordinates()\\n traj.xyz *= 10\\n traj.unitcell_lengths *= 10\\n traj.xyz += traj.unitcell_lengths[0,0]/2\\n traj[:].save_dcd(path+\\\"/{:s}.dcd\\\".format(name))\\n traj[0].save_pdb(path+\\\"/{:s}.pdb\\\".format(name))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b532cd39894710ea81daaeb6e066aa87\",\n \"score\": \"0.45979238\",\n \"text\": \"def ccmd(*targets, **kwargs):\\n import subprocess\\n\\n def run_ccmd_checks(\\n target, ret, checks, interval, source, timestamp, group, command, description, alert, **kwargs\\n ):\\n command = command.format(target=target)\\n check_result = {\\n \\\"success\\\": 0,\\n \\\"checks\\\": checks,\\n \\\"comment\\\": \\\"\\\",\\n \\\"target\\\": target,\\n \\\"check_type\\\": \\\"CCMD\\\",\\n \\\"rtt\\\": 0.0,\\n \\\"source\\\": source,\\n \\\"@timestamp\\\": timestamp,\\n \\\"group\\\": group,\\n \\\"description\\\": description,\\n \\\"command\\\": command,\\n }\\n command = [i.strip() for i in command.split(\\\" \\\") if i.strip()]\\n # do CCMD checks\\n for i in range(checks):\\n try:\\n result = subprocess.check_output(command, stderr=subprocess.STDOUT)\\n result = result.decode(encoding=\\\"utf-8\\\")\\n if (\\n \\\"Destination net unreachable\\\" in result\\n or \\\"TTL expired in transit\\\" in result\\n or \\\"Destination host unreachable\\\" in result\\n ):\\n continue\\n else:\\n check_result[\\\"success\\\"] += 1\\n except:\\n check_result[\\n \\\"comment\\\"\\n ] += \\\"CCMD Check {}, ERROR in subprocess, command '{}' failed or returned non zero status code\\\\n\\\".format(\\n i, str(command)\\n )\\n time.sleep(interval)\\n # calculate success and loss percentages\\n check_result[\\\"success\\\"] = (check_result[\\\"success\\\"] / checks) * 100\\n check_result[\\\"loss\\\"] = 100 - check_result[\\\"success\\\"]\\n # sent alert if requested to do so\\n if check_result[\\\"success\\\"] == 0 and alert is True:\\n _send_alert(check_type=\\\"CCMD\\\", target=target, data=check_result)\\n # save thread run results\\n ret[\\\"out\\\"].append(check_result)\\n\\n # initialize variables\\n check_kwargs = _get_kwargs(**kwargs)\\n # create threads objects\\n job_threads = []\\n for target_dict in targets:\\n if not target_dict.get(\\\"command\\\") or not target_dict.get(\\\"target\\\"):\\n log.error(\\n \\\"dnuts.ccmd: no 'command' or 'target' argument found for target - {}\\\".format(target)\\n )\\n continue\\n job_threads.append(\\n Thread(\\n target=run_ccmd_checks,\\n kwargs=dict(\\n target=target_dict[\\\"target\\\"].strip(),\\n command=target_dict[\\\"command\\\"].strip(),\\n description=target_dict.get(\\\"description\\\", \\\"\\\").strip(),\\n **check_kwargs\\n ),\\n )\\n )\\n # run threads\\n log.info(\\n \\\"Running {len} CCMD connection checks in {threads} threads, {checks} check(s) per target, with {interval}s interval and {timeout}s timeout\\\".format(\\n len=len(job_threads), **check_kwargs\\n )\\n )\\n _run_threads(\\n job_threads,\\n max=check_kwargs[\\\"threads\\\"],\\n timeout=check_kwargs[\\\"timeout\\\"] * 2 * check_kwargs[\\\"checks\\\"],\\n )\\n log.info(\\\"CCMD Checks completed\\\")\\n\\n return check_kwargs[\\\"ret\\\"]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9478451c3fa2b27a8ed7e0dbd44d7b08\",\n \"score\": \"0.45846218\",\n \"text\": \"def crc(self):\\n return self.comp_command('DSCRC').lstrip('DSCRC ').rstrip()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ab2ea1f4c5e0d2418f73ac9044a6ec74\",\n \"score\": \"0.45644945\",\n \"text\": \"def _genCCCDiff(self,\\n regName,\\n name,\\n title,\\n caption,\\n outputDir):\\n\\n import LATCRootData\\n regInfo = LATCRootData.PRECINCT_INFO[self._precinctName][regName]\\n \\n regData = self._cfgPrecinctData.getRegisterData(regName)\\n baselineData = self._baselinePrecinctData.getRegisterData(regName)\\n diffData = [new - old for (new,old) in zip(regData,baselineData)]\\n # extract GCCC index from global GCFE indeces\\n import calConstant\\n cccData = [calConstant.getCFEId(idx)[1] for idx in range(calConstant.GLOBAL_N_GCFE)]\\n \\n import ROOTPlotUtils\\n return ROOTPlotUtils.make2DHist(cccData,\\n diffData,\\n name,\\n title,\\n caption,\\n \\\"GCCC\\\",\\n \\\"%s diff (cfg - baseline)\\\"%regName,\\n outputDir,\\n calConstant.NUM_GCCC,\\n 2*(regInfo.maxVal+1),\\n calConstant.NUM_GCCC,\\n regInfo.maxVal+1,\\n 0,\\n -1*(regInfo.maxVal+1))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f5f00f4dca7539272090535912b5a235\",\n \"score\": \"0.45629635\",\n \"text\": \"def pgcdl(l):\\n p=l[0]\\n for i in range(1,len(l)):\\n p=pgcd(p,l[i])\\n return p\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ffd453111561dafc3987bc185ecb1004\",\n \"score\": \"0.45616314\",\n \"text\": \"def write_cc(cdl):\\n with open(cdl.file_out, 'wb') as cdl_f:\\n cdl_f.write(cdl.xml_root)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5a1be46bc78fd58aa761924da4c55802\",\n \"score\": \"0.455433\",\n \"text\": \"def _ccmd(self, args, rv=0):\\n assert type(args) == str\\n # Ensure 'coverage' is turned off-- it won't work.\\n self.cmdline_run(\\\"{0}\\\".format(args), exit=rv, coverage=False)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f55ee40d4f7dd059decd1e6cf99229f2\",\n \"score\": \"0.4548994\",\n \"text\": \"def Dc(self, z):\\n if z==0:\\n return 0\\n else:\\n f = lambda z: 1.0/self.__E(z)\\n I = integrate.quad(f, 0, z)\\n return self.Dh * I[0]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5ec8891e11763bbf07bc9da6ed97a767\",\n \"score\": \"0.4543415\",\n \"text\": \"def get_cl(field, bp, hd, mask, map, coupled_cell, tmp_path=None):\\n\\n # Initialize Cls\\n n_bins = map.shape[1]\\n n_ells = len(bp)\\n cl = np.zeros((2, 2, n_ells, n_bins, n_bins))\\n\\n # Dimensions\\n Nx = hd['NAXIS1']\\n Ny = hd['NAXIS2']\\n Lx = Nx*abs(hd['CDELT1'])*np.pi/180 # Mask dimension in radians\\n Ly = Ny*abs(hd['CDELT2'])*np.pi/180 # Mask dimension in radians\\n\\n # Fields definition\\n fd = np.array([nmt.NmtFieldFlat(\\n Lx, Ly, mask[x], [map[0, x], -map[1, x]]) for x in range(n_bins)])\\n # Bins for flat sky fields\\n b = nmt.NmtBinFlat(bp[:, 0], bp[:, 1])\\n # Effective ells\\n ell = b.get_effective_ells()\\n\\n # Iterate over redshift bins to compute Cl's\\n mcm_paths = []\\n for nb1 in range(n_bins):\\n for nb2 in range(nb1, n_bins):\\n # Temporary path for mode coupling matrix\\n if tmp_path is None:\\n mcm_p = os.path.expanduser('~')\\n else:\\n mcm_p = tmp_path\\n mcm_p = mcm_p+'/mcm_{}_Z{}{}.dat'.format(field, nb1+1, nb2+1)\\n mcm_paths.append(mcm_p)\\n # Define workspace for mode coupling matrix\\n wf = nmt.NmtWorkspaceFlat()\\n try:\\n wf.read_from(mcm_p)\\n except RuntimeError:\\n wf.compute_coupling_matrix(fd[nb1], fd[nb2], b)\\n wf.write_to(mcm_p)\\n print('Calculated mode coupling matrix for bins {}{}'\\n ''.format(nb1+1, nb2+1))\\n sys.stdout.flush()\\n # Calculate Cl's\\n cl_c = nmt.compute_coupled_cell_flat(fd[nb1], fd[nb2], b)\\n if coupled_cell is True:\\n cl_d = cl_c\\n else:\\n cl_d = wf.decouple_cell(cl_c)\\n cl_d = np.reshape(cl_d, (2, 2, n_ells))\\n cl[:, :, :, nb1, nb2] = cl_d\\n cl[:, :, :, nb2, nb1] = cl_d\\n\\n return ell, cl, mcm_paths\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f03076ba667b5b3f85826b1dcf5ce982\",\n \"score\": \"0.45395768\",\n \"text\": \"def _ldc(self):\\n value = self.pop(CONTROL)\\n self._push_val(value) # adds value to memory and pushes it's address to STACK\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6e71f803d765eb328a43f8019e074f76\",\n \"score\": \"0.45364988\",\n \"text\": \"def draw_clonal_marker(self):\\n\\n # add background noise\\n self.fill(1, self.bg_level, self.bg_noise)\\n\\n # draw nuclei\\n means = self.data['clonal_marker'].values\\n stds = self.data['clonal_marker_std'].values\\n self.draw_nuclei(channel=1, means=means, stds=stds)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2d5a35afa18a02a7c7a85b213b55688a\",\n \"score\": \"0.45291862\",\n \"text\": \"def _test_model_cld():\\r\\n print(\\\"Loading\\\")\\r\\n import coffeehouse_languagedetection\\r\\n print(\\\"Ready\\\\n\\\")\\r\\n\\r\\n while True:\\r\\n input_text = input(\\\"> \\\")\\r\\n results = coffeehouse_languagedetection.predict(input_text, dltc=False, cld=True, ld=False)\\r\\n print(results['cld'])\\r\\n print(results['cld'][0])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c57a1b04c7b961a41ad089ccb912ee14\",\n \"score\": \"0.45217818\",\n \"text\": \"def execute_gen_dc(self):\\n # write the shading header\\n self.write_static_shading()\\n\\n command1 = 'gen_dc \\\"{hea_path}\\\" -dir'.format(hea_path=self.hea_path)\\n command2 = 'gen_dc \\\"{hea_path}\\\" -dif'.format(hea_path=self.hea_path)\\n command3 = 'gen_dc \\\"{hea_path}\\\" -paste'.format(hea_path=self.hea_path)\\n\\n CEADaySim.run_cmd(command1)\\n CEADaySim.run_cmd(command2)\\n CEADaySim.run_cmd(command3)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"055ed6c173c938da2fb017d7e9cee309\",\n \"score\": \"0.4516811\",\n \"text\": \"def calcdIdV(self):\\n I = self.getI()\\n self.dIdV = np.gradient(I,self.V_range)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"42362d5e5b19638a5bc85fd009ddc25e\",\n \"score\": \"0.44972062\",\n \"text\": \"def clifford_conductor(self):\\n D = self.disc()\\n return prod([x[0] for x in factor(2 * self.level()) if self.clifford_invariant(x[0]) == -1])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b1ee72efbba9eae06c1783ac6f2ebfe8\",\n \"score\": \"0.4482374\",\n \"text\": \"def fetch_cdum() -> None:\",\n \"title\": \"\"\n },\n {\n \"docid\": \"eaa3872a87b6051eddb7b65625102710\",\n \"score\": \"0.44770986\",\n \"text\": \"def to_cshl_short(self) -> str:\\n if self.variant_type & core.Allele.Type.substitution:\\n return f\\\"sub({self.ref}->{self.alt})\\\"\\n if self.variant_type & core.Allele.Type.small_insertion:\\n return f\\\"ins({self.alt})\\\"\\n if self.variant_type & core.Allele.Type.small_deletion:\\n return f\\\"del({self.length})\\\"\\n if self.variant_type & core.Allele.Type.complex:\\n return f\\\"comp({self.ref}->{self.alt})\\\"\\n if self.variant_type & core.Allele.Type.large_duplication:\\n return \\\"CNV+\\\"\\n if self.variant_type & core.Allele.Type.large_deletion:\\n return \\\"CNV-\\\"\\n raise ValueError(f\\\"unexpected variant type: {self.variant_type}\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f32924eb57923c0873366b053a01239c\",\n \"score\": \"0.44690257\",\n \"text\": \"def cce_diag(config_map=None):\\n # for pylint, otherwise \\\"Dangerous default value {} as argument\\\"\\n if config_map is None:\\n config_map = {}\\n\\n def _build(sch, tensor_list, kernel_name='cce_diag_op'):\\n target = 'llvm'\\n mod = tvm.build(sch, tensor_list, target, name=kernel_name)\\n return mod\\n\\n def _lower(sch, tensor_list):\\n print(tvm.lower(sch, tensor_list, simple_mode=True))\\n\\n def _check(mod, input_tensors, output_tensors, ref_input_func, ref_output_func, rtol):\\n ctx = tvm.context('llvm', 0)\\n if not ctx.exist:\\n raise RuntimeError('Only support diagnose on CPU now')\\n np_inputs = []\\n tvm_inputs = []\\n tvm_outputs = []\\n if ref_input_func is None:\\n for tensor in input_tensors:\\n np_inputs.append(\\n np.random.uniform(size=get_const_tuple(tensor.shape)).astype(tensor.dtype))\\n else:\\n np_inputs = ref_input_func(*input_tensors)\\n for np_input in np_inputs:\\n tvm_inputs.append(tvm.nd.array(np_input, ctx))\\n\\n for tensor in output_tensors:\\n tvm_outputs.append(\\n tvm.nd.array(np.zeros(get_const_tuple(tensor.shape), dtype=tensor.dtype), ctx))\\n\\n mod(*(tvm_inputs + tvm_outputs))\\n if ref_output_func is None:\\n print([output.asnumpy() for output in tvm_outputs])\\n else:\\n np_output = ref_output_func(*np_inputs)\\n if rtol is None:\\n np.testing.assert_allclose(tvm_outputs[0].asnumpy(), np_output, rtol=1e-3)\\n else:\\n np.testing.assert_allclose(tvm_outputs[0].asnumpy(), np_output, rtol=rtol)\\n print('CHECK PASS')\\n\\n input_tensors = config_map[\\\"input_tensors\\\"]\\n output_tensors = config_map[\\\"output_tensors\\\"]\\n ref_input_func = config_map[\\\"ref_input_func\\\"]\\n ref_output_func = config_map[\\\"ref_output_func\\\"]\\n rtol = config_map[\\\"rtol\\\"]\\n\\n sch = tvm.create_schedule([x.op for x in output_tensors])\\n if config_map[\\\"print_ir\\\"]:\\n _lower(sch, input_tensors + output_tensors)\\n\\n mod = _build(sch, input_tensors + output_tensors, config_map[\\\"name\\\"])\\n\\n _check(mod, input_tensors, output_tensors, ref_input_func, ref_output_func, rtol)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3aa04ec97657f1aced10bc834b7accea\",\n \"score\": \"0.44670403\",\n \"text\": \"def calcdDdT(thermconsts):\\n if thermconsts['LKFluid'] == 'ref':\\n d2 = thermconsts['LKd2ref']\\n elif thermconsts['LKFluid'] == 'simple':\\n d2 = thermconsts['LKd2simple']\\n else:\\n print ('LK error in calcLKD')\\n\\n T = thermconsts['Temperature']\\n Tc = thermconsts['TCrit']\\n t2 = T*T\\n return -(d2*Tc/t2)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8bd4484e6a5ab3f898361db36c5b89e3\",\n \"score\": \"0.44381437\",\n \"text\": \"def get_gate_invocation_c(self):\\r\\n # No function block is generated if one of the inputs is a wire with constant value.\\r\\n # I.e. either the constant or the second input wire is propagated to the output for the corresponding logic gate's logic function.\\r\\n if self.disable_generation:\\r\\n return \\\"\\\"\\r\\n else:\\r\\n return f\\\" {self.out.name} = {self.gate_type}({self.a.get_wire_value_c_hier()}, {self.b.get_wire_value_c_hier()});\\\\n\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"dd1cfb74c94fc94a13784b612b4589fd\",\n \"score\": \"0.44379905\",\n \"text\": \"def lll_cost(d):\\n return d ** 3\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9e94357064c0f2afb388440179f93aee\",\n \"score\": \"0.44379246\",\n \"text\": \"def cdy(f):\\n n = f.shape[1]\\n south = [0] + list(range(n-1))\\n north = list(range(1,n)) + [n-1]\\n return 0.5*(f[:,north] - f[:,south])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5da04385d387b99ae27b9060104b393d\",\n \"score\": \"0.4416052\",\n \"text\": \"def make_dbc(build: BuildData, labs_dir: str, dbc_path: str) -> NoReturn:\\n try:\\n gendbc(\\n source_dir=labs_dir,\\n encoding=\\\"utf-8\\\",\\n dbc_path=dbc_path,\\n dbc_folder=build.top_dbc_folder_name,\\n flatten=False,\\n verbose=verbosity_is_enabled(),\\n debugging=False,\\n )\\n finally:\\n pass\",\n \"title\": \"\"\n },\n {\n \"docid\": \"32c2ad273204b9006c5e7d36e8597b56\",\n \"score\": \"0.44115666\",\n \"text\": \"def toCylindrical(self,dir=[0,1,2]):\\n f = zeros_like(self)\\n x,y,z = [ self[...,i] for i in dir ]\\n f[...,0] = sqrt(x*x+y*y)\\n f[...,1] = arctan2(y,x) / rad\\n f[...,2] = z\\n return f\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3b6503cb6681437f9d4c9f71e1596946\",\n \"score\": \"0.44020143\",\n \"text\": \"def C(source):\\n return _embed_or_inline_c(source, True)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ce624478a3a2f1f5ba48ddb7dbbb3cfe\",\n \"score\": \"0.43961677\",\n \"text\": \"def hvs_crd(c1, c2, rev=False):\\n if rev:\\n endcord = (c2['elat'], c2['elon'])\\n else:\\n endcord = (c2['slat'], c2['slon'])\\n return haversine((c1['elat'], c1['elon']), endcord)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"b192a8f581539dfd9f40ebb5f7382744\",\n \"score\": \"0.43924603\",\n \"text\": \"def cdx(f):\\n m = f.shape[0]\\n west = [0] + list(range(m-1))\\n east = list(range(1,m)) + [m-1]\\n return 0.5*(f[east,:] - f[west,:])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ee6e872be2491df2b4169a8d904a057f\",\n \"score\": \"0.4390537\",\n \"text\": \"def LC2CL(tensor):\\n # type: (Tensor) -> Tensor\\n return tensor.transpose(0, 1).contiguous()\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e3b288a3db20dce938a1c63f026cf47d\",\n \"score\": \"0.4383879\",\n \"text\": \"def genomic_to_cdna_coord(transcript, genomic_coord):\\n exons = [exon.get_as_interval()\\n for exon in get_exons(transcript)]\\n\\n if len(exons) == 0:\\n return None\\n\\n strand = transcript.strand\\n\\n if strand == \\\"+\\\":\\n exons.sort(key=lambda exon: exon.chrom_start)\\n else:\\n exons.sort(key=lambda exon: -exon.chrom_end)\\n\\n distances = [exon.distance(genomic_coord)\\n for exon in exons]\\n min_distance_to_exon = min(map(abs, distances))\\n\\n coding_offset = 0\\n for exon in exons:\\n exon_length = exon.chrom_end - exon.chrom_start\\n distance = exon.distance(genomic_coord)\\n if abs(distance) == min_distance_to_exon:\\n if strand == \\\"+\\\":\\n exon_start_cds_offset = coding_offset + 1\\n exon_end_cds_offset = coding_offset + exon_length\\n else:\\n exon_start_cds_offset = coding_offset + exon_length\\n exon_end_cds_offset = coding_offset + 1\\n # This is the exon we want to annotate against.\\n if distance == 0:\\n # Inside the exon.\\n if strand == \\\"+\\\":\\n coord = (exon_start_cds_offset +\\n (genomic_coord -\\n (exon.chrom_start + 1)))\\n else:\\n coord = (exon_end_cds_offset +\\n (exon.chrom_end -\\n genomic_coord))\\n cdna_coord = CDNACoord(coord, 0)\\n else:\\n # Outside the exon.\\n if distance > 0:\\n nearest_exonic = exon_start_cds_offset\\n else:\\n nearest_exonic = exon_end_cds_offset\\n if strand == \\\"+\\\":\\n distance *= -1\\n\\n # If outside transcript, don't use offset.\\n if (genomic_coord < transcript.tx_position.chrom_start + 1 or\\n genomic_coord > transcript.tx_position.chrom_stop):\\n nearest_exonic += distance\\n distance = 0\\n cdna_coord = CDNACoord(nearest_exonic, distance)\\n break\\n coding_offset += exon_length\\n\\n # Adjust coordinates for coding transcript.\\n if transcript.is_coding:\\n # Detect if position before start codon.\\n utr5p = get_utr5p_size(transcript) if transcript.is_coding else 0\\n cdna_coord.coord -= utr5p\\n if cdna_coord.coord <= 0:\\n cdna_coord.coord -= 1\\n else:\\n # Detect if position is after stop_codon.\\n exons = get_exons(transcript)\\n stop_codon = find_stop_codon(exons, transcript.cds_position)\\n stop_codon -= utr5p\\n if (cdna_coord.coord > stop_codon or\\n cdna_coord.coord == stop_codon and cdna_coord.offset > 0):\\n cdna_coord.coord -= stop_codon\\n cdna_coord.landmark = CDNA_STOP_CODON\\n\\n return cdna_coord\",\n \"title\": \"\"\n },\n {\n \"docid\": \"ca8eef915055a80110e94a478c94d646\",\n \"score\": \"0.43692192\",\n \"text\": \"def write_cl(filename, cl, dtype=np.float64):\\n # check the dtype and convert it\\n fitsformat = getformat(dtype)\\n column_names = ['TEMPERATURE','GRADIENT','CURL','G-T','C-T','C-G']\\n if isinstance(cl, list):\\n cols = [pf.Column(name=column_name,\\n format='%s'%fitsformat,\\n array=column_cl) for column_name, column_cl in zip(column_names[:len(cl)], cl)]\\n else: # we write only one TT\\n cols = [pf.Column(name='TEMPERATURE',\\n format='%s'%fitsformat,\\n array=cl)]\\n\\n tbhdu = pf.BinTableHDU.from_columns(cols)\\n # add needed keywords\\n tbhdu.header['CREATOR'] = 'healpy'\\n writeto(tbhdu, filename)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"43329a638c037c76595e84ebf59a64ed\",\n \"score\": \"0.43676528\",\n \"text\": \"def __ccmd(self, args, rv=0):\\n assert type(args) == str\\n # Ensure 'coverage' is turned off-- it won't work.\\n self.cmdline_run(\\\"{0}\\\".format(args), exit=rv, coverage=False)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2037383eadb3c2f16ee9bdab685fca19\",\n \"score\": \"0.4366915\",\n \"text\": \"def cllr(Hp_LRs, Hd_LRs):\\n Np = len(Hp_LRs)\\n Nd = len(Hd_LRs)\\n return 1.0 / 2.0 * (\\n (1.0 / Np * sum([np.log2(1 + 1.0 / LR) for LR in Hp_LRs])) + 1.0 / Nd * sum([np.log2(1 + LR) for LR in Hd_LRs]))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7e3fdc4477bebddc08bd7f6b17a25465\",\n \"score\": \"0.43542147\",\n \"text\": \"def clc(self) -> None:\\n self.buf[self.pos] = 248\\n self.pos += 1\",\n \"title\": \"\"\n },\n {\n \"docid\": \"3b97b58db7291c8d471c63b486ba8cc0\",\n \"score\": \"0.4349628\",\n \"text\": \"def test_cdm(baseline_file='cl_baseline_cdm.pkl',atol=1e-20,rtol=1e-3):\\n print('\\\\nTesting Cls for cdm...\\\\n')\\n check_cl_match(baseline_file,'cdm',atol=atol,rtol=rtol)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"1f76fcc9b2f0b4e8ba968c3814ea5de4\",\n \"score\": \"0.4337672\",\n \"text\": \"def cci(self, n, array=False):\\n result = talib.CCI(self.high, self.low, self.close, n)\\n if array:\\n return result\\n return result[-1]\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6a7181e257ef6314c2bc974c0dac6c3c\",\n \"score\": \"0.43283027\",\n \"text\": \"def genDCD(residues,name,prot):\\n top = md.Topology()\\n chain = top.add_chain()\\n for resname in prot.fasta:\\n residue = top.add_residue(residues.loc[resname,'three'], chain)\\n top.add_atom(residues.loc[resname,'three'], element=md.element.carbon, residue=residue)\\n for i in range(len(prot.fasta)-1):\\n top.add_bond(top.atom(i),top.atom(i+1))\\n traj = md.load(prot.path+\\\"/{:s}_0.gsd\\\".format(name), top)[1000:]\\n traj.top = top\\n for replica in range(1,replicas(prot)):\\n t = md.load(prot.path+\\\"/{:s}_{:d}.gsd\\\".format(name,replica), top)[1000:]\\n t.top = top\\n traj = md.join([traj,t])\\n del t\\n traj = traj.image_molecules(inplace=False, anchor_molecules=[set(traj.top.chain(0).atoms)], make_whole=True)\\n traj.center_coordinates()\\n traj.xyz += traj.unitcell_lengths[0,0]/2\\n traj.save_dcd(prot.path+\\\"/{:s}.dcd\\\".format(name))\\n traj[0].save_pdb(prot.path+\\\"/{:s}.pdb\\\".format(name))\\n for replica in range(replicas(prot)):\\n os.remove(prot.path+\\\"/{:s}_{:d}.gsd\\\".format(name,replica))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"59f759cb79ef49dde6095ceb73a4ce42\",\n \"score\": \"0.43271166\",\n \"text\": \"def do_cd(self, line):\\n args = self.line_to_args(line)\\n if len(args) == 0:\\n dirname = '~'\\n else:\\n if args[0] == '-':\\n dirname = self.prev_dir\\n else:\\n dirname = args[0]\\n dirname = resolve_path(self.cur_dir, dirname)\\n\\n mode = auto(self.devs, get_mode, dirname)\\n if mode_isdir(mode):\\n self.prev_dir = self.cur_dir\\n self.cur_dir = dirname\\n auto(self.devs, chdir, dirname)\\n else:\\n eprint(\\\"Directory '%s' does not exist\\\" % dirname)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f5ac87133ba0723857a4b114a5633826\",\n \"score\": \"0.4322817\",\n \"text\": \"def dot_c(self):\\n return ' '*self.indent_level+self._sep.join(self._defs)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"35a0bec5c5fa65e1c7bb723643d74062\",\n \"score\": \"0.4320173\",\n \"text\": \"def cdhit(\\n input_fasta: str,\\n percent_identity: float,\\n length_difference_cutoff: float = None,\\n min_alignment_coverage: float = None,\\n percent_identity_suffix: bool = False,\\n output_dir: str = None\\n) -> None:\\n\\n if not os.path.exists(input_fasta):\\n raise FileNotFoundError(f'Fasta file {input_fasta} was not found.')\\n\\n if output_dir is not None:\\n if not os.path.isdir(output_dir):\\n raise NotADirectoryError(f'{output_dir} is not a directory.')\\n output_prefix = os.path.join(output_dir, os.path.splitext(os.path.basename(input_fasta))[0])\\n else:\\n output_prefix = os.path.splitext(input_fasta)[0]\\n\\n if percent_identity_suffix:\\n output_prefix = output_prefix + str(percent_identity)\\n # from pdb import set_trace; set_trace()\\n params = [\\n 'cd-hit',\\n '-i', input_fasta,\\n '-o', output_prefix,\\n '-c', str(percent_identity),\\n '-n', str(_cdhit_word_size(percent_identity)),\\n '-d', '0',\\n '-sc', '1',\\n ]\\n\\n if length_difference_cutoff is not None:\\n params.extend(['-s', str(length_difference_cutoff)])\\n\\n if min_alignment_coverage is not None:\\n params.extend([\\n '-aL', str(min_alignment_coverage),\\n '-aS', str(min_alignment_coverage),\\n ])\\n\\n subprocess.check_call(params)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c2c6958c103993dd1bc1eb0e137796e9\",\n \"score\": \"0.43184483\",\n \"text\": \"def DC(self,V=0, ch=1):\\n\\t\\t\\n\\t\\tself.session.write(\\\":SOUR%d:APPL:DC DEF,DEF, %.4f\\\" % (ch,V))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c249095397e69fd63a33dac96f568537\",\n \"score\": \"0.4313726\",\n \"text\": \"def calcd(self, t):\\n\\n if t < self.x[0]:\\n return None\\n elif t > self.x[-1]:\\n return None\\n\\n i = self.__search_index(t)\\n dx = t - self.x[i]\\n result = self.b[i] + 2.0 * self.c[i] * dx + 3.0 * self.d[i] * dx ** 2.0\\n return result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9e65b76d841a1487f31b9746fbdea7b4\",\n \"score\": \"0.43133104\",\n \"text\": \"def dwwc(\\n graph,\\n metapath,\\n damping=0.5,\\n dense_threshold=0,\\n dtype=numpy.float64,\\n dwwc_method=None,\\n):\\n return dwwc_method(\\n graph=graph,\\n metapath=metapath,\\n damping=damping,\\n dense_threshold=dense_threshold,\\n dtype=dtype,\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a597b14013e443be5f5c3a8501155223\",\n \"score\": \"0.43100724\",\n \"text\": \"def cxtd_comp_from_undirected(self):\\n self.cxtd_comp = list(nx.connected_component_subgraphs(self.disgraph))\\n print(\\\"Num of cxtd comps in disgarph: %d\\\"%(len(self.cxtd_comp)))\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9d4c47402d034aba208f8f79d1e80079\",\n \"score\": \"0.43012372\",\n \"text\": \"def compute_C_matrix(self):\\n self.C = np.repeat(np.diag(self.Lp)[:, np.newaxis],\\n self.Lp.shape[0], axis=1)\\n self.C += np.repeat(np.diag(self.Lp)[np.newaxis, :],\\n self.Lp.shape[0], axis=0)\\n self.C -= 2*self.Lp\\n # the following is much slower\\n # self.C = np.zeros(self.Lp.shape)\\n # for i in range(self.Lp.shape[0]):\\n # for j in range(self.Lp.shape[1]):\\n # self.C[i, j] = self.Lp[i, i] + self.Lp[j, j] - 2*self.Lp[i, j]\\n volG = np.sum(self.z)\\n self.C *= volG\\n sett.mt(0, 'computed commute distance matrix')\\n self.Dchosen = self.C\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c53598f524c632a699ad3aefd3bf12b1\",\n \"score\": \"0.42999962\",\n \"text\": \"def convert_coulomb(self, data):\\r\\n\\r\\n return \\\"{} C\\\".format(data)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"2a8c151c0c157aa1896976808d02d0d0\",\n \"score\": \"0.42947423\",\n \"text\": \"def cy(self, ctl, tgt):\\n return self.append(CyGate(), [ctl, tgt], [])\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6261b6e63f0b61d17cb423fef8c4f465\",\n \"score\": \"0.42942545\",\n \"text\": \"def cdist(self, x, y):\\n\\n differences = x.unsqueeze(1) - y.unsqueeze(0)\\n distances = torch.sum(differences**2, -1).sqrt()\\n return distances\",\n \"title\": \"\"\n },\n {\n \"docid\": \"7803f994ac5b2fa4f389ef4c430673c0\",\n \"score\": \"0.42906135\",\n \"text\": \"def gen_cord(dot_number):\\n global lt\\n if len(lt[dot_number]) > 0: # if we already have coord-s for current dot in cache\\n yield from lt[dot_number]\\n return # we don't need to recalculate them again -> return\\n i = (matrix[0][dot_number])\\n s = set()\\n for j in range(i + 1):\\n s.update(((j, i - j), (j, -(i - j)), (-j, -(i - j)), (-j, i - j)))\\n if len(s) > i * 2: # to speed up the calculation we compute partially\\n yield from s # The same as \\\"for p in s: yield p\\\"\\n lt[dot_number] = lt[dot_number].union(s)\\n s.clear()\\n if len(s) > 0: # remains\\n yield from s\\n lt[dot_number] = lt[dot_number].union(s)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"a281fa05065db4cb810bf44ba46ebe5e\",\n \"score\": \"0.42890027\",\n \"text\": \"def closeness_centrality(self, distance=None, write=False,\\n write_property=None):\\n if distance is not None:\\n warnings.warn(\\n \\\"Weighted closeness centrality for Neo4j graphs \\\"\\n \\\"is not implemented: computing the unweighted version\\\",\\n MetricProcessor.MetricProcessingWarning)\\n result = self._run_gdc_query(\\n \\\"gds.alpha.closeness\\\", \\\"closeness\\\", weight=None,\\n write=write, write_property=write_property,\\n score_name=\\\"centrality\\\")\\n return result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8ee95a5141df0890d43382cb3f4d5f7a\",\n \"score\": \"0.42743996\",\n \"text\": \"def _get_c_l(self) -> float:\\n return self._c_l\",\n \"title\": \"\"\n },\n {\n \"docid\": \"59174e599277637b60a3ed5f32c9d5b7\",\n \"score\": \"0.42741856\",\n \"text\": \"def convert_candela(self, data):\\r\\n\\r\\n return \\\"{} cd\\\".format(data)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"f045ac790efc806ebead1f0008344665\",\n \"score\": \"0.42726877\",\n \"text\": \"def C(self, q , dq ): \\n \\n [c1,s1,c2,s2,c12,s12] = self.trig( q )\\n \\n h = self.m2 * self.l1 * self.lc2 * s2\\n \\n C = np.zeros((2,2))\\n \\n C[0,0] = - h * dq[1]\\n C[1,0] = h * dq[0]\\n C[0,1] = - h * ( dq[0] + dq[1] )\\n C[1,1] = 0\\n\\n \\n return C\",\n \"title\": \"\"\n },\n {\n \"docid\": \"d481ee0f690587c040b20bddd6a643cf\",\n \"score\": \"0.42699832\",\n \"text\": \"def run_command(command):\\n p = subprocess.Popen(['cl'], shell=True, stdout=subprocess.PIPE,\\n stderr=subprocess.STDOUT)\\n text = p.stdout.read()\\n return 0, text\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8665c12e99bbc4bba290ba67e6d85fee\",\n \"score\": \"0.42662162\",\n \"text\": \"def compute_ctc_loss(logits, labels, logit_length, label_length):\\r\\n return tf.nn.ctc_loss(\\r\\n labels=labels,\\r\\n logits=logits,\\r\\n label_length=label_length,\\r\\n logit_length=logit_length,\\r\\n logits_time_major=False,\\r\\n unique=None,\\r\\n blank_index=-1,\\r\\n name=None\\r\\n )\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9aa4d909b59fb3940f2682374f734545\",\n \"score\": \"0.4264086\",\n \"text\": \"def to_cshl_full(self) -> str:\\n if self.variant_type & core.Allele.Type.tandem_repeat:\\n return f\\\"TR({self.tr_ref}x{self.tr_unit}->{self.tr_alt})\\\"\\n if self.variant_type & core.Allele.Type.substitution:\\n return f\\\"sub({self.ref}->{self.alt})\\\"\\n if self.variant_type & core.Allele.Type.small_insertion:\\n return f\\\"ins({self.alt})\\\"\\n if self.variant_type & core.Allele.Type.small_deletion:\\n return f\\\"del({self.length})\\\"\\n if self.variant_type & core.Allele.Type.complex:\\n return f\\\"comp({self.ref}->{self.alt})\\\"\\n if self.variant_type & core.Allele.Type.large_duplication:\\n return \\\"CNV+\\\"\\n if self.variant_type & core.Allele.Type.large_deletion:\\n return \\\"CNV-\\\"\\n raise ValueError(f\\\"unexpected variant type: {self.variant_type}\\\")\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5bf4a544d11dd84b0c2de9b26ad5c04a\",\n \"score\": \"0.42640367\",\n \"text\": \"def Calcd(self,t):\\n \\n j=int(math.floor(t))\\n if(j<0):\\n j=0\\n elif(j>=len(self.a)):\\n j=len(self.a)-1\\n\\n dt=t-j\\n result=self.b[j]+2.0*self.c[j]*dt+3.0*self.d[j]*dt*dt\\n return result\",\n \"title\": \"\"\n },\n {\n \"docid\": \"e04d1e18bddbd4df1af371a80c05a324\",\n \"score\": \"0.42573228\",\n \"text\": \"def gcdex(self, a, b):\\n return python_gcdex(a, b)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"c50fa3111f6bc964518c482970d84a7f\",\n \"score\": \"0.4257226\",\n \"text\": \"def _get_C_cc_diagonals(self) -> npt.NDArray[np.float64]:\\n C_cv_sums = np.sum(np.absolute(np.array(self._C_cv)), axis=1)\\n # from other dots:\\n off_diag = self._C_cc - np.diag(np.diag(self._C_cc))\\n off_diag_sums = np.sum(np.absolute(off_diag), axis=1)\\n\\n diag = C_cv_sums + off_diag_sums\\n diag += np.absolute(self._c_r) + np.absolute(self._c_r)\\n\\n return np.diag(diag)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"da64da90405b8d849840b52f6f8c5767\",\n \"score\": \"0.42549163\",\n \"text\": \"def get_gate_invocation_c(self):\\r\\n # No function block is generated if one of the inputs is a wire with constant value.\\r\\n # I.e. either the constant or the second input wire is propagated to the output for the corresponding logic gate's logic function.\\r\\n if self.disable_generation:\\r\\n return \\\"\\\"\\r\\n else:\\r\\n return f\\\" {self.out.name} = {self.gate_type}({self.a.get_wire_value_c_hier()});\\\\n\\\"\",\n \"title\": \"\"\n },\n {\n \"docid\": \"8a8b86338f1062b57dbed0901cc42815\",\n \"score\": \"0.42515898\",\n \"text\": \"def getNodeCD(self):\\n return self.__nodeCD\",\n \"title\": \"\"\n },\n {\n \"docid\": \"0131b73008109e2eef8aa3843d067f7e\",\n \"score\": \"0.4247958\",\n \"text\": \"def dV_C(self, z):\\n om, ol, h = self.om, self.ol, self.h\\n ok = 1. - om - ol\\n _D_H = self.D_H\\n _D_A = self.D_A(z)\\n return _D_H * (1. + z)**2 * _D_A**2 / E(z, om, ol)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"5eb5af85f794eeb1dbc71afbf197cbab\",\n \"score\": \"0.42442828\",\n \"text\": \"def cosh(x1):\\n\\n if (use_origin_backend(x1)):\\n return numpy.cosh(x1)\\n\\n if not isinstance(x1, dparray):\\n raise TypeError(f\\\"DPNP cosh(): Unsupported x1={type(x1)}\\\")\\n\\n return dpnp_cosh(x1)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"6d710b10f3c798bbc43a98c10bc118bb\",\n \"score\": \"0.42385876\",\n \"text\": \"def CylindricalGrid2D(dr=None, dz=None, \\n nr=None, nz=None, \\n Lr=None, Lz=None,\\n dx=1., dy=1., \\n nx=None, ny=None,\\n Lx=None, Ly=None,\\n origin=((0,),(0,)),\\n overlap=2,\\n communicator=parallelComm):\\n\\n\\n\\n\\n if dr is not None:\\n dx = dr\\n\\n if dz is not None:\\n dy = dz\\n\\n\\n nx = nr or nx\\n ny = nz or ny\\n\\n Lx = Lr or Lx\\n Ly = Lz or Ly\\n \\n if numerix.getShape(dx) == () and numerix.getShape(dy) == ():\\n\\n dx, nx = _dnl(dx, nx, Lx)\\n dy, ny = _dnl(dy, ny, Ly)\\n from fipy.meshes.cylindricalUniformGrid2D import CylindricalUniformGrid2D\\n return CylindricalUniformGrid2D(dx=dx, dy=dy, nx=nx or 1, ny=ny or 1, origin=origin, overlap=overlap, communicator=communicator)\\n else:\\n from fipy.meshes.cylindricalNonUniformGrid2D import CylindricalNonUniformGrid2D\\n return CylindricalNonUniformGrid2D(dx=dx, dy=dy, nx=nx, ny=ny, origin=origin, overlap=overlap, communicator=communicator)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"9efaa01bf65441af1794a17447f4fa75\",\n \"score\": \"0.42385522\",\n \"text\": \"def cmidd(x, y, z, base=2):\\n assert len(x) == len(y) == len(z), \\\"Arrays should have same length\\\"\\n xz = np.c_[x, z]\\n yz = np.c_[y, z]\\n xyz = np.c_[x, y, z]\\n return entropyd(xz, base) + entropyd(yz, base) - entropyd(xyz, base) - entropyd(z, base)\",\n \"title\": \"\"\n },\n {\n \"docid\": \"24003c9b109a4f8fac267e7305ea8665\",\n \"score\": \"0.42337123\",\n \"text\": \"def addDCC(self, lda_address, lda_channel):\\n print \\\"force DCC\\\"\\n theDcc = Dcc()\\n theDcc.setString(\\\"LDA_ADDRESS\\\", lda_address)\\n theDcc.setInt(\\\"LDA_CHANNEL\\\", lda_channel)\\n self.dccConf.add(theDcc)\\n self.dccs.append(theDcc)\\n print \\\"\\\\t DCC added\\\", theDcc.getString(\\\"LDA_ADDRESS\\\"), theDcc.getInt(\\\"LDA_CHANNEL\\\")\",\n \"title\": \"\"\n }\n]","isConversational":false}}}],"truncated":false,"partial":false},"paginationData":{"pageIndex":3,"numItemsPerPage":100,"numTotalItems":994482,"offset":300,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6IjVHZDBvd0g5MTM2eDZjc1FvbE1zcktNWUZoRVFoUm5PVVVybEpjOUhaUEEifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc5MDUyNDMyNiwianRpIjoiMGQyM2M3NjktMGYwNi00YjJhLTgzOGEtNWJiYTgxZTI1YWFjIiwic3ViIjoiL2RhdGFzZXRzL250aGFrdXIvY29ybnN0YWNrLXB5dGhvbi12MS10ZXZhdHJvbi0xTSIsImV4cCI6MTc5MDUyNzkyNiwiaXNzIjoiaHR0cHM6Ly9odWdnaW5nZmFjZS5jbyJ9.xVHr3ejuitVXVXP8IfpA4MDMNasgzeQIj2_QoUt3FRVVp2VhwfPGGVnR8utg5X7MFqLkuLRLT6qhysL02VGbCw","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":994482,"numBytesParquet":23972089656}]},"discussionsStats":{"closed":0,"open":1,"total":1},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query_id stringlengths 32 32 | query stringlengths 9 4.01k | positive_passages listlengths 1 1 | negative_passages listlengths 88 101 |
|---|---|---|---|
5ee7897f9c3469042c9481cb0aaa95db | Create a Convolutional Layer | [
{
"docid": "538739d29b1eff228e06813a471a4179",
"score": "0.0",
"text": "def conv2d(inputs, filters, kernel_size = 1, strides = 1, pad = 'VALID', name = None):\r\n\twith tf.name_scope(name):\r\n\t\tkernel = tf.Variable(tf.contrib.layers.xavier_initializer(uniform=False)([kernel_size,kernel_size, inputs.g... | [
{
"docid": "b070c84c9fc1b5e2fad7e952f9059ce4",
"score": "0.70827186",
"text": "def new_convolutional_layer(input, num_input_channels, size_filter, num_filter, pooling=True, name=\"Conv_layer\"):\n with tf.name_scope(name):\n shape = [size_filter, size_filter, num_input_channels, num_filter] #... |
718f6daa719d8feb086d37b9a2ee67ff | with this hook you can do something very generic to a response after all processing. | [
{
"docid": "0bd3658fd421c84cde654d2b2673beeb",
"score": "0.72350335",
"text": "def finalize_response(self, response):\n return response",
"title": ""
}
] | [
{
"docid": "5096446644aa74e0296f4e3833d8e85c",
"score": "0.7852177",
"text": "def process_response(self, request, response):\n pass",
"title": ""
},
{
"docid": "4f1dd571ef4f5cfee7912e94b204d348",
"score": "0.76349527",
"text": "def _post_process(self, response: requests.Respon... |
97acf9a4daf2ff4a1fa2ca4a7cafbccb | Function to receive json | [
{
"docid": "5c6438353ee5cedec71e2dcd9d6ef8a1",
"score": "0.5765529",
"text": "def receiveJson(sock):\n buffer = sock.recv(4)\n if buffer:\n print('Data received')\n json_length = struct.unpack(\"!i\", buffer)[0]\n # Reference: https://stackoverflow.com/a/15964489/9798310\n ... | [
{
"docid": "dfb868339faad755f062796bbcfa141b",
"score": "0.78848916",
"text": "def read_json():",
"title": ""
},
{
"docid": "30707fc438c9e879ada201232f998f06",
"score": "0.70540917",
"text": "def json(self):",
"title": ""
},
{
"docid": "a2b5a2de1b87e4397e2128a5226af038",
... |
f928e10b71127be588db7080aadddf59 | new request with added url prefix | [
{
"docid": "500302353444e52592c399ad0c5b42b1",
"score": "0.7734129",
"text": "def add_prefix(self, prefix: str) -> 'Request':\n return replace(self, url=prefix + self.url)",
"title": ""
}
] | [
{
"docid": "5a983c427ab4ff4da4b887f4601c21f8",
"score": "0.6477151",
"text": "def process_request(self, request):\n self.request = request\n site = get_current_site(request)\n if site.id > 1:\n prefix = \"_{0}\".format(site.id)\n self.request.urlconf = settings... |
6e6569e4b674b3abb5a1fb9d542546fa | Recovers all the containers of an instance including metasploit msfrpcd. | [
{
"docid": "2a532e88e44d753f7eda991a95711b40",
"score": "0.6858903",
"text": "def recover_containers(containers):\n port = None\n\n for container in containers: # start all the containers\n container.start()\n container.reload()\n\n for ports in container.ports.values():\n ... | [
{
"docid": "4e5206faee73d635ed0330cac7c2af7c",
"score": "0.6030402",
"text": "def restart_vpp_in_all_containers(self):\n for container in self.containers:\n self.engine.container = self.containers[container]\n self.engine.restart_vpp()",
"title": ""
},
{
"docid":... |
c41d47381d7582440c496fa8c8c5fcdb | applies the given netmask to the networks, True if the results are the same | [
{
"docid": "d17a9c442dee1d7a39c64f9b1bc71315",
"score": "0.6128977",
"text": "def in_subnet(network1, network2, netmask):\n subnet1 = apply_netmask(network1, netmask)\n subnet2 = apply_netmask(network2, netmask)\n return subnet1 == subnet2",
"title": ""
}
] | [
{
"docid": "61e94f906aa1799ab53499bafb573297",
"score": "0.61975306",
"text": "def net_contains(net, cand):\n\treturn cand.network_address in net and cand.broadcast_address in net",
"title": ""
},
{
"docid": "403ee80e33bce6a7f6c613285760624c",
"score": "0.6157785",
"text": "def apply... |
3b7c40e01f7562f1c2c98b475a8995a0 | Differentiate signals to get velocity and accelerations | [
{
"docid": "d9604181fdba608edd1fd29a759bdbfe",
"score": "0.5557643",
"text": "def get_accel(self, isnumeric=False):\n self.isnumeric = isnumeric\n y = self.y\n ndof = self.ndof\n fs = self.fs\n\n yd = np.empty(y.shape)\n ydd = np.empty(y.shape)\n for i in... | [
{
"docid": "8c76ae0beb9a41d26d305633e98782ae",
"score": "0.6204682",
"text": "def base_velocity(self):\n raise NotImplementedError('Not yet implemented!')",
"title": ""
},
{
"docid": "621cf629c68f1d2bb317f5ec88170f2c",
"score": "0.61361825",
"text": "def velocity(self) -> np.ndarr... |
49fd8840ef9368227d2b7e660821b272 | + Truncate/drop all tables and recreate them + Delete all packages in package_files | [
{
"docid": "0533af5678f26a8b1eb78b03d099c715",
"score": "0.0",
"text": "def clear(server_path, force=False):\n # Confirm:\n ans = input(\"Are you sure you want to delete all packages? [yN]\")\n if ans.lower() in ('y', 'yes'):\n pass\n elif ans.lower() in('n', 'no'):\n logger.de... | [
{
"docid": "7a68d64a77b898c481a9e4d0c0265a0d",
"score": "0.7258292",
"text": "def _clear_all_tables(self):\n self.session.close()\n self.meta_data.drop_all()\n self.meta_data.create_all()\n clear_mappers()",
"title": ""
},
{
"docid": "53f3ca5be2e84c984f9ff654fafc1... |
35fa76dfe12a7bcfcb841a04b983c9cf | Parse wifi values from terminal | [
{
"docid": "45e8150210b1713afc39966fbe5879ba",
"score": "0.6029007",
"text": "def wifi_stats(stats_count=3):\n link_sum,level_sum, noise_sum = 0, 0, 0\n for i in range(stats_count):\n args = [\"grep\", \"-i\", \"wlp2s0\",\"/proc/net/wireless\"]\n try:\n link, level, noise ... | [
{
"docid": "9fb87dbbad13db7c5198dc9f65e4ca76",
"score": "0.6035363",
"text": "def get_wifi_settings():\n sets = {'ssid': 'SSID', 'passwd': 'PASS'}\n\n if settings.PB_HOSTAPD_FILE is None:\n return sets\n\n with open(settings.PB_HOSTAPD_FILE, 'r') as f:\n for line in f:\n ... |
c9ca1502783cde9e7254c22151a34af7 | This method is the workhorse of the browser. It handles screen drawing and the keyboard. | [
{
"docid": "adee66d3b690a632aad4bc601d68f8b2",
"score": "0.0",
"text": "def _dodisplay(self, scr):\n self.scr = scr\n curses.halfdelay(1)\n footery = 2\n\n keys = []\n for cmd in (\"quit\", \"help\"):\n key = self.keymap.findkey(cmd, None)\n if ke... | [
{
"docid": "0d8778a822da0bea2b74406879196b37",
"score": "0.73315173",
"text": "def draw(self, screen):\n pass",
"title": ""
},
{
"docid": "6984ab10ce449f006f1e8504d628c9cc",
"score": "0.6826859",
"text": "def draw(self):\n self.canvas_draw()\n self.screen.blit(se... |
a712f0cb9d8eddbf41248121075a19fa | Attach a lot of summaries to a Tensor (for TensorBoard visualization). | [
{
"docid": "f55821b85f4b9014bb03f97a13767b5a",
"score": "0.5550347",
"text": "def variable_summaries(var):\n with tf.name_scope('summaries'):\n mean = tf.reduce_mean(var)\n tf.summary.scalar('mean', mean)\n with tf.name_scope('stddev'):\n stddev = tf.sqrt(tf.reduce_mean(tf.square(var - me... | [
{
"docid": "384e9aded997888d340ff722a51377a8",
"score": "0.77373797",
"text": "def add_summaries(self):\n # defines a namespace for the summaries\n with tf.name_scope('summaries'):\n # adds a plot for the loss\n tf.summary.scalar('loss', self.loss)\n #tf.summary.scalar('accuracy', s... |
e12b204058941f7972fcc012f64c5c74 | calibrate load z calibration data from file and return lookup table | [
{
"docid": "b05059abdc9e9a381f41838516343bd6",
"score": "0.5337697",
"text": "def z_calibration(self, SaveAs=False):\n z = np.genfromtxt(calibration_data, names=True, skiprows=1)\n\n #fit = exp2d.Exp2D()\n p, best, err = fit().fit(np.array(z['mm']), np.array(z['value']), y0=0)\n fdata = fit(... | [
{
"docid": "7374324898ccb78687f58e814c21b167",
"score": "0.6299177",
"text": "def load_calib_data(self, filename):\n\n if os.path.exists(filename):\n data = pickle_load(filename)\n\n for camera in stereo.cameras:\n camera.cam_mat = data['cameras'][camera.id]['... |
69d4dc11c310fbf809daa1fe6ad75e3e | Compares two nested models by likelihood ratio test | [
{
"docid": "f177e33e18cf8c07f6bdfec041c53fc1",
"score": "0.6138221",
"text": "def LikelihoodRatioTest(null_model, alt_model):\n\n chisq = -2.0 * null_model.loglikelihood() + 2.0 * alt_model.loglikelihood()\n df = null_model.df - alt_model.df # Null model has more DFs\n res = LikelihoodRatioTest... | [
{
"docid": "bf8e7021a8b42eba46d0f452fe785a88",
"score": "0.6811791",
"text": "def mismatch(model1, model2):\n\n return 1.0 - np.abs(np.vdot(model1, model2) / np.vdot(model1, model1))",
"title": ""
},
{
"docid": "783d78e07638ddc84b9c6d56582419be",
"score": "0.6533749",
"text": "def... |
c80064b9608786be6f6d43da0b4d693c | Branching is not random. A branch should occur inside the method or to the beginning of another method. This method analyzes the branching address of a branch instruction and then provides a probability of the address being correct | [
{
"docid": "1cd624279e6db30d049094eafcc8f170",
"score": "0.7213883",
"text": "def _compute_branch_address(self, inst, current_fn, lowest_addr, highest_addr):\n if inst.ignore or not inst.is_branch:\n return\n jmp_addr = inst.jumping_address\n\n if jmp_addr is None:\n ... | [
{
"docid": "1307af128f0a5c78af4461deb19951e6",
"score": "0.6226275",
"text": "def perform_always_branch(self, data, addr):\n\t\treturn None",
"title": ""
},
{
"docid": "8a73668c32d2ea65e4e433a87fa449c8",
"score": "0.5962285",
"text": "def determine_next_step(self, branch: int, x: dic... |
b01a5967c443eb60787ab383abd1670a | Loads the given schema file | [
{
"docid": "f636b948ad3143cd695eff59d138a523",
"score": "0.72388625",
"text": "def _load_json_schema(filename):\n\n relative_path = join('.', filename)\n absolute_path = join(dirname(__file__), relative_path)\n\n with open(absolute_path) as schema_file:\n return json.loads(schema_file.re... | [
{
"docid": "6e4995ac5e247b12c5dfe531342cb979",
"score": "0.77058876",
"text": "def _load_schema_from_local_file(file_name):\n print \"Loading schema from file '{}'\".format(file_name)\n try:\n with open(file_name) as schema_file:\n schema = pickle.load(schema_file)\n r... |
f3ac5f2be00b23cd61aace8c8e723530 | linepair is the sequence of two lines; the first runs the function and assigns the output, and the second generates an array of indices where the output error exceeds a tolerance. | [
{
"docid": "2cee509d40c4a062da1f7d729e373d6b",
"score": "0.54965043",
"text": "def __init__(self, linepair):\n\n self.linepair = linepair\n self.runline = linepair[0]\n self.testline = linepair[1]\n\n # parse the line that runs the function\n head, tail = self.runline.... | [
{
"docid": "8ce386777d1ed111f3cb2783d0814d00",
"score": "0.61191684",
"text": "def get_parallel_line_pairs(slope_bucket : Dict[int, List[List[tuple]]]) -> List[List[tuple]]:\n parallel_line_pairs = []\n for slope, lines in slope_bucket.items():\n print(f'Looping for slope : {slope}:\\n')\n ... |
53995d40d676c5765cc0c649e11ab981 | Returns the current values of all weights in the network in a dictionary with the same keys as self.weight_keys. | [
{
"docid": "92a8aac52d5eb688bc26546c1edf7d65",
"score": "0.7493311",
"text": "def get_weights(self, sess):\n keys = sorted(self.weight_keys)\n weight_dict = {}\n for i, k in enumerate(keys):\n weight_dict[k] = sess.run(self.parameters[i])\n\n return weight_dict",
... | [
{
"docid": "eca0e62d23f2146e66f80ec97663dc41",
"score": "0.8380025",
"text": "def get_weights(self):\n weights = {}\n for key in self.weights:\n weights[key] = self.weights[key].get_value()\n return weights",
"title": ""
},
{
"docid": "0c397626a40b260f6ee205b7... |
d767493699a07ddcd42621c67fd2e118 | Given a positive integer n, generate the primes < n. | [
{
"docid": "47565328f245af61b47771408283e044",
"score": "0.0",
"text": "def basicSieveSum(n):\n s = [1]*n\n for p in xrange(2, 1+int(math.sqrt(n-1))):\n if s[p]:\n a = p*p \n s[a::p] = [0] * -((a-n)//p)\n sm = 0\n for p in xrange(2, n): \n if s[p]:\n sm += p\n return sm",
"... | [
{
"docid": "bb38992d97c5b1bdca1c86ad4f61d2a4",
"score": "0.8815054",
"text": "def generate_primes(n):\n primes = []\n for i in range(2, n + 1):\n if is_prime(i):\n primes.append(i)\n return primes",
"title": ""
},
{
"docid": "343d3818ff2bab1820a2586b19dd5c27",
... |
4ac309522543ac6843994eb767a69abb | check Checkpoint a mailbox on the server. | [
{
"docid": "54457b720b105c250612e134d92c4731",
"score": "0.5425262",
"text": "def check(self, argv):\n self._print_msg(self._client.check())",
"title": ""
}
] | [
{
"docid": "805dfc8005657b800fd5e4eba32ddf6e",
"score": "0.64372647",
"text": "def _check_boxes(connection):\r\n response, mailboxes = connection.list()\r\n if response == 'OK':\r\n print \"Mailboxes:\"\r\n print mailboxes",
"title": ""
},
{
"docid": "911a56fcf17678afb8a2ed... |
03654944cbdd631faf9f136c19a7b4dd | Frequency of closed GOPs. | [
{
"docid": "6d377044c365689374db148beed5adbe",
"score": "0.0",
"text": "def gop_closed_cadence(self) -> Optional[int]:\n return pulumi.get(self, \"gop_closed_cadence\")",
"title": ""
}
] | [
{
"docid": "b3aecd515721ed0ded243ccad03b82f0",
"score": "0.6738275",
"text": "def freq() -> int:",
"title": ""
},
{
"docid": "6a3de2c7938da78ca22fa42a0e9a0726",
"score": "0.64109796",
"text": "def freq():\n ...",
"title": ""
},
{
"docid": "7a3ce4a44641c3eb046228992d0f6... |
e71a262dc65258038ea4ad2436938f07 | There may be only one possible choice for a particular unit | [
{
"docid": "25b3f3d41f0543a51f51798fbfed6c97",
"score": "0.63899994",
"text": "def only_choice(grid):\n for unit in all_units:\n for d in '123456789':\n choices = [n for n in unit if d in grid[n]]\n if len(choices) == 1:\n grid = assign_value(grid, choices[... | [
{
"docid": "1982c5e15c66bae15bf1b7fa7414a2dc",
"score": "0.6371527",
"text": "def only_choice(values):\n # unitlist = self.rowUnits() + self.colUnits() + self.squareUnits()\n\n fillUpUnits(rowUnits(), values)\n fillUpUnits(colUnits(), values)\n fillUpUnits(squareUnits(), values)\n return ... |
6955cbd8ff7a599105390c16094f3506 | Sets the reference of this Body25. | [
{
"docid": "fbac8f63485bd82c00ccf9b0610ddedc",
"score": "0.66401124",
"text": "def reference(self, reference: str):\n\n self._reference = reference",
"title": ""
}
] | [
{
"docid": "94e7ab98a43027ed7c456278e641c382",
"score": "0.73035944",
"text": "def setreference(self, ref):\n self._reference = ref",
"title": ""
},
{
"docid": "cbdf1e730b08f4160e8b55c02f955762",
"score": "0.6978299",
"text": "def set_reference(self, reference):\n\n sel... |
062e53385be12da3262258379b8d138a | Helper method to keep our tests DRY | [
{
"docid": "c1fefd5f8cbadcc4e37eec35121f22ba",
"score": "0.0",
"text": "def given_a_series_of_prices(self, prices):\n timestamps = [datetime(2015, 5, 28), datetime(2015, 5, 29),\n datetime(2015, 5, 30)]\n for timestamp, price in zip(timestamps, prices):\n se... | [
{
"docid": "f9c82fcce3672cf836716181212cb178",
"score": "0.7571753",
"text": "def _test(self):",
"title": ""
},
{
"docid": "f9c82fcce3672cf836716181212cb178",
"score": "0.7571753",
"text": "def _test(self):",
"title": ""
},
{
"docid": "f9c82fcce3672cf836716181212cb178",
... |
b677ca61c75260738aaf0ddec5ce2b65 | Normalizes string, converts to lowercase, removes nonalpha characters, | [
{
"docid": "9f8e7ce7916a2afefdd81b4bb23bb675",
"score": "0.0",
"text": "def sanitize(value):\n import re\n re.sub('[^\\w\\-_\\. ]', '_', value)\n value = value.replace(\" \", \"_\")\n logger.debug(f'Saving file with sanitized name: {value}')\n return value",
"title": ""
}
] | [
{
"docid": "21d05d24e2e0b083869daab4c2577f97",
"score": "0.79351604",
"text": "def normalizeText(s):\n s = s.lower()\n s = REMSPACE.sub(' ', s)\n s = ALPHAONLY.sub('', s)\n s = s.strip()\n return s",
"title": ""
},
{
"docid": "8163d4336b7bb30bc7f5f8acab4d5c46",
"score": "0... |
06c6dd3d6b60a452da31149b7cd48f4c | Determine if version number needs to be updated | [
{
"docid": "4fd3c5010c81efb4c2891cf13d5dbb7c",
"score": "0.0",
"text": "def main():\n local_version = get_version(\"../../vertical_multi_columns/__init__.py\")\n print(f\"{local_version=}\")\n\n resp = requests.get(sys.argv[1])\n pypi_version = resp.json()[\"info\"][\"version\"]\n print(f... | [
{
"docid": "edd9ba140dee6b58f1594ab78eb66623",
"score": "0.747243",
"text": "def latestVersionValid():",
"title": ""
},
{
"docid": "edd9ba140dee6b58f1594ab78eb66623",
"score": "0.747243",
"text": "def latestVersionValid():",
"title": ""
},
{
"docid": "e08f90db58eb696c5e4e... |
c09532df2a7eb5de34c61599cbdfff3a | The ARN of the bucket. | [
{
"docid": "0833f505a89d3e8f24c57e43b09f9b4b",
"score": "0.85899574",
"text": "def bucket_arn(self) -> str:\n return jsii.get(self, \"bucketArn\")",
"title": ""
}
] | [
{
"docid": "cd16b59e48c62bc36c6a993f3486202c",
"score": "0.8556041",
"text": "def bucket_arn(self) -> str:\n ...",
"title": ""
},
{
"docid": "1f02024d39e89f53e5c0393567499f43",
"score": "0.8067578",
"text": "def bucket_arn(self) -> pulumi.Input[str]:\n return pulumi.get... |
4382f219b527dab17a0eac5e599326ef | get the url link | [
{
"docid": "921636792c7324ff28a8f31af78eba2f",
"score": "0.0",
"text": "async def message_url(self, message_id: str) -> UrlLinkPayload:",
"title": ""
}
] | [
{
"docid": "411716a5d825a4ca3911c7c270c84f0c",
"score": "0.8282871",
"text": "def get_link (self):\n if self.relative_url != '':\n return self.relative_url\n else:\n return self.url",
"title": ""
},
{
"docid": "97b221b6714784f61d6886850fdb85dc",
"score... |
fbe39aef838317b089316438cad11925 | The only meaning of this function is to trigger HighlimePauseCommandListener | [
{
"docid": "019a4a108508ad49cf7201fe72c86c88",
"score": "0.72343063",
"text": "def run():\n print('Highlime paused')",
"title": ""
}
] | [
{
"docid": "898f0e506e7f8c034b4be4605b68abcc",
"score": "0.6303478",
"text": "def pause(self):\r\n self._command_queue.put('PAUSE')",
"title": ""
},
{
"docid": "a2fbfa52839871c05016db68f6602804",
"score": "0.6262444",
"text": "def pause():\r\n command(\"M0\")",
"title":... |
c626eae38259a07289a7b7708d2c1ce7 | Returns or sets the text of header. | [
{
"docid": "b1592dbb51367a2b79d2e7c8a17593a7",
"score": "0.0",
"text": "def header_right(self):\n return self.impl.header_right",
"title": ""
}
] | [
{
"docid": "ab438d89b8054bc9433af182d69b5617",
"score": "0.77726483",
"text": "def header_text(self):\n return object_attr_string_repr(self.header)",
"title": ""
},
{
"docid": "85fdadd7ccdfdf866f181fae0ac29e0c",
"score": "0.7516228",
"text": "def setHeader(self, text):\n ... |
cf24a9a72fbf65c07687a84538833017 | Return a string representing the node in g2o format | [
{
"docid": "223b7b608650d8a8dbb39bab7f4324fd",
"score": "0.0",
"text": "def to_g2o(self):\n line = \"VERTEX_SE3:QUAT {} \".format(self.id_)\n line += \" \".join([str(x) for x in self.t]) + \" \"\n line += \" \".join([str(x) for x in self.q])\n return line",
"title": ""
... | [
{
"docid": "10ff3df0af534ac4a0f9ac4acdbf8192",
"score": "0.7376439",
"text": "def __str__(self):\n string = '@nodes\\nlabel deg\\n'\n for i in self.V:\n string += '%3d %3d\\n'%(i,self.deg(i))\n\n string += '@edges\\n label\\n'\n ... |
f2d1d503acd930c5ec07c4f30e77a603 | Function to calculate the overall sentiment using NLTK's vader library. | [
{
"docid": "798a0136783d5ddca3272bbee7431a00",
"score": "0.67116237",
"text": "def overall_sentiment(text):\r\n sid = SentimentIntensityAnalyzer()\r\n ss = sid.polarity_scores(text)\r\n for _ in sorted(ss):\r\n if ss[\"compound\"] >= 0.15:\r\n return \"positive\"\r\n el... | [
{
"docid": "e3c5c0e86bce2b5b341ec4e089f8f077",
"score": "0.72598004",
"text": "def sentiment(text):\n words = pattern_split.split(text.lower())\n sentiments = map(lambda word: afinn.get(word, 0), words)\n if sentiments:\n # How should you weight the individual word sentiments? \n ... |
d2ad09c8cbe6b76dcdcf2bf822e90025 | !Calls self.communicate(), and returns the stdout from the pipeline (self.outbytes). The return value will be Null if the pipeline was redirected to a file or if the constructor's capture option was not True. | [
{
"docid": "d8e40611db405a37b900f39eea4e4026",
"score": "0.5637281",
"text": "def to_string(self):\n self.communicate()\n o=self.out\n if not isinstance(o,str):\n o=str(o)\n return o",
"title": ""
}
] | [
{
"docid": "79d9e8c61854efd57d11968a3ffd058b",
"score": "0.6113572",
"text": "def capture(*cmd):\n a = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n return a.communicate()",
"title": ""
},
{
"docid": "aa2bd5a65384749897ba3080cd28c526",
"score": "0.6037035"... |
02034d9965d781f30c6f7918368b3e67 | Creates tokens from raw text | [
{
"docid": "47d8828dde4173cdc244ec460e9816af",
"score": "0.59687525",
"text": "def tokenize_text(self,text):\n tokenizer = RegexpTokenizer(r'\\w+')\n \n tokens = tokenizer.tokenize(text)\n extra_stops = [str(i) for i in range(2100)]\n extra_stops +=['zero','one','two',... | [
{
"docid": "542013bc74bde82830f0473726cfb956",
"score": "0.7338718",
"text": "def tokenize(raw_text):\n\n return raw_text.split()",
"title": ""
},
{
"docid": "2f9ff835a968bb12af51b8b89ca14dab",
"score": "0.71471465",
"text": "def tokenize(self, text):\n ...",
"title": "... |
329232d02e29ea3ed29d2ff519324fd5 | Gets the locale used if `TurnContext.activity.locale` is not specified. | [
{
"docid": "2521393f2c80cbbdbe0fddd527a97efd",
"score": "0.0",
"text": "def default_locale(self, value: str) -> None:\n self._default_locale = value",
"title": ""
}
] | [
{
"docid": "0183bb62745d02306c278fdc5d75d2a0",
"score": "0.7553464",
"text": "def getCurrentLocale(self):\n\n permutation = self.getCurrentPermutation()\n if permutation:\n locale = permutation.get(\"locale\")\n if locale:\n return locale\n\n ret... |
3acc3d2008079b219ac7f83ecb7e3210 | Create the command line to be passed to RTC server. This function does not add the min_port and max_port param to the RTC command line | [
{
"docid": "ac80715cd3570bd89c02d5a142a1b8f6",
"score": "0.6836483",
"text": "def get_rtc_cmdline_params(self, as_config_file, vs_config_file):\n as_lb, as_port, vs_lb, vs_port = self._get_audio_video_lb_address(\n as_config_file, vs_config_file)\n # Create the command line for ... | [
{
"docid": "4849001e343d48655bbecfa022eafbab",
"score": "0.7281892",
"text": "def get_rtc_cmdline_params_port_range(self, as_config_file, vs_config_file):\n as_lb, as_port, vs_lb, vs_port = self._get_audio_video_lb_address(\n as_config_file, vs_config_file)\n # Create the comman... |
92d841dcafd34df3242b964e23640f53 | Log and email warning about any acquisition stars with observed positions outside the expected search box (plus a pad). For acquisition stars with tracked positions in the wrong search box, note the box (classic acquisition anomaly). | [
{
"docid": "300ea322480477cd031f996f103b2e96",
"score": "0.6799472",
"text": "def warn_on_acq_anom(acqs, emails):\n # Find tracked objects in the acq stats table outside the intended search box plus padding\n\n # Note that dy/dz are observed yag/zag (t_guide) - predicted yag/zag (t_guide) using AO... | [
{
"docid": "ce3f1e64473ba2120407263f5189104a",
"score": "0.5493461",
"text": "def test_pos_err_on_guide():\n stars = StarsTable.empty()\n stars.add_fake_star(id=100, yang=100, zang=-200, POS_ERR=2010, mag=8.0)\n stars.add_fake_star(id=101, yang=0, zang=500, mag=8.0, POS_ERR=1260) # Just over w... |
e63245e828429092ba71c86e1d1ee3ad | Get histogram counts per each processed CCD frame as a 2D array. Use setHistBins to configure histogram bins. Bin edges and centers are available in self.hedges and self.hcenters. Return a 2D array of histogram counts per each frame. | [
{
"docid": "4f01216566be8d30ec6cbf2945acbf80",
"score": "0.6916845",
"text": "def ahistogram(self):\n import functools\n from py15sacla.utils import eqbinhistogram\n self._ensureHistBinsExist()\n lo, hi, bins = self.chistbins\n fnc = functools.partial(eqbinhistogram, b... | [
{
"docid": "4bcc28038117f26ba6811756bf804fdb",
"score": "0.66184413",
"text": "def ToHistogram(self):\n return np.array([bin[3] for bin in self.bins])",
"title": ""
},
{
"docid": "9e7fd3f24c8b8f0b511422fe75da5fec",
"score": "0.65742964",
"text": "def histogram(self):\n ... |
5ff642964c526823046501a5c2bba226 | Should be implemented by the base class (if using renderable, ensure it comes last in resolution order) | [
{
"docid": "41c2be246653e727bdbe448de1a403c8",
"score": "0.0",
"text": "def position_intersects(self, position: Position) -> bool:\n raise NotImplementedError",
"title": ""
}
] | [
{
"docid": "0c7c45818ff2bc1931fe2e11d314069b",
"score": "0.76715225",
"text": "def __init__(self):\n super(RenderBase, self).__init__()\n return",
"title": ""
},
{
"docid": "21569fd1241d3b25a8ac06aaa8d53153",
"score": "0.7640047",
"text": "def render(self):\n rai... |
5db90035f9cdea3e72db69035db905b8 | Updates the marker according to the given event. All submarkers will be updated before the compound marker itself is updated. | [
{
"docid": "dc13326b3e9e55f908c4e8b1abd051bc",
"score": "0.63127154",
"text": "def track(self, event: Event) -> None:\n for marker in self.sub_markers:\n marker.track(event)\n super().track(event)",
"title": ""
}
] | [
{
"docid": "308e72dad6a59f68311c1f154078fc03",
"score": "0.6227557",
"text": "def update(self, event, annotation):\n # Get artist-specific information about the pick event\n info = self.event_info(event)\n\n if self.props_override is not None:\n info = self.props_override... |
c7872bd282a051e526f485e11f6379c8 | Help to encode message. Called before message encoding. | [
{
"docid": "9bf32b62df0636367e7201fcc181c3af",
"score": "0.0",
"text": "def before_encode(cls, func):\n\n @functools.wraps(func)\n def wrap(*args, **kwargs):\n return func(*args, **kwargs)\n\n return wrap",
"title": ""
}
] | [
{
"docid": "c6241b38b2421d64e9fd4f34efabf7eb",
"score": "0.6964077",
"text": "def encode(self, *args, **kwargs):\r\n pass",
"title": ""
},
{
"docid": "2e45b8167aacfe58cba85502f8a700ab",
"score": "0.6803782",
"text": "def encode(message):\n # Please print out which line of t... |
7fe51914cbe9fe09b58be396ee2f3f9f | Check if a fault was detected. | [
{
"docid": "e54a3686327db8d5b5e9171e62c207f5",
"score": "0.694356",
"text": "def DetectedFault(self):\n\n if self.FaultOnEarlyExit and (self.thread is None or not self.thread.is_alive()) and \\\n (self.handledFault is None or not self.handledFault.is_set()):\n ... | [
{
"docid": "6e0f214cdbd2d2f656dcdcb35150cef2",
"score": "0.72903425",
"text": "def check_failure(self, fault_name):\n srch_str = '\\s{}'.format(fault_name)\n if re.findall(srch_str, self.fd_data):\n return False\n else:\n return True",
"title": ""
},
{
... |
14ac21724398d659a2adc4e56824b6a6 | Return a list of string containing all the current hostnames | [
{
"docid": "25c7f310d6616a91bc15cbb5a1776bb5",
"score": "0.80563426",
"text": "def getListHostnames(self):\n\t\tlist = self.getSession().query(Node.name).all()\n\t\treturn [item for item, in list]",
"title": ""
}
] | [
{
"docid": "fda32db0718449990a2b6180d66bc9bd",
"score": "0.7972852",
"text": "def hostnames(self) -> pulumi.Output[Sequence[str]]:\n return pulumi.get(self, \"hostnames\")",
"title": ""
},
{
"docid": "b041d5586a7c69cbc0634e494a0d123f",
"score": "0.78123796",
"text": "def getHo... |
35c623f30178746f5f5e8f39c70f007d | Return the DataContainer from a table row instance. | [
{
"docid": "2a9b0521fe06029a4ddea1f3ce11bf0d",
"score": "0.5291903",
"text": "def _retrieve(self, row):\n uid = uuid.UUID(hex=row['uid'], version=4)\n return Particle(\n uid=uid, coordinates=row['coordinates'], data=self._data[uid])",
"title": ""
}
] | [
{
"docid": "01a807f81ace83f5eeb9eb05cdcb0fa3",
"score": "0.62217975",
"text": "def get_row(self, row):\n return self._db.get_row(self._name, row, column_map=self._colmap)",
"title": ""
},
{
"docid": "afeecb2a704c4bdaeb7392b3d002009b",
"score": "0.6117592",
"text": "def row(sel... |
13ba29af0c10bb044a0db3512e28328d | Convert string to int | [
{
"docid": "28dd1eb62954e144c7b6c8cb573b83a1",
"score": "0.76648444",
"text": "def string_to_int(string):\n\n string = string.replace('.', '')\n string = string.split('(')[0].strip()\n return int(string)",
"title": ""
}
] | [
{
"docid": "4b040796ab3ac4bb90c477eb99082b3b",
"score": "0.835715",
"text": "def _to_int(string):\r\n if isinstance(string, str):\r\n return ord(string[0])\r\n else:\r\n return string",
"title": ""
},
{
"docid": "053ae9ba7134f6482eed54ec1895a44c",
"sco... |
0efdbe0ce685754dada5ce85c74f8460 | Measure the agreement and KL divergence between the predictions produced by model trained on exact augmentation objectives vs models trained on approximate objectives. | [
{
"docid": "470839c6e196ef515bb7b98ff504f674",
"score": "0.67365485",
"text": "def agreement_kl_difference(augmentations):\n model_variants = {'kernel': lambda model: [model, exact_to_og_model(model), exact_to_1st_order_model(model),\n exact_to_2nd_order_no_1s... | [
{
"docid": "c322dbaec2b331c7a9ddb961765bb690",
"score": "0.64305675",
"text": "def compute_accuray(predictions, y):\n\treturn np.mean(np.equal(predictions.detach().numpy(), y.numpy()))",
"title": ""
},
{
"docid": "ba7d945e9ae06d3e616a6c0fd6cc9414",
"score": "0.63229054",
"text": "def... |
5bcc2d1e5631452b6d04a2d77bd3b135 | This tests the functionality of raising TerminateSimulation exception in handle_result. | [
{
"docid": "c5e35f86415dfcf81cf24b4452ab42fc",
"score": "0.6437277",
"text": "def test_terminate_simulation(self):\r\n class Extended_Problem(Implicit_Problem):\r\n def __init__(self):\r\n pass\r\n def handle_event(self,solver, event_info):\r\n ... | [
{
"docid": "a5e7d92dcfa627fb50dc50d429c88849",
"score": "0.70890814",
"text": "def test_handle_stop_and_exit(self) -> None:\n self.aea._skills_exception_policy = ExceptionPolicyEnum.stop_and_exit\n self.handler.handle = self.raise_exception # type: ignore # cause error: Cannot assign to a... |
33d5f69c80edac04532e759092ff0904 | Get all axes offset voltages `offsets` is a list of offset voltags, whose length is equal to the number of active (connected) axes. | [
{
"docid": "a9105f97237b4bd2c4c935723e01c677",
"score": "0.6659708",
"text": "def set_all_offsets(self, offsets):\n self._set_all_axes_data(self.set_offset,offsets)\n return self.get_all_offsets()",
"title": ""
}
] | [
{
"docid": "1adc973b87fe44a565cce97d6ac19eb5",
"score": "0.66350055",
"text": "def get_all_offsets(self):\n return self._get_all_axes_data(self.get_offset)",
"title": ""
},
{
"docid": "1adc973b87fe44a565cce97d6ac19eb5",
"score": "0.66350055",
"text": "def get_all_offsets(self)... |
9567fd29f63203e11751913ca00a388a | Get work history for the last years | [
{
"docid": "f7cf9bac763b508fcc011afe972f3c3d",
"score": "0.7542441",
"text": "def getHistoryYear(num = 0):\n\tresult=[]\n\tcurrentTime=datetime.datetime.now()\n\tlimit=datetime.datetime(currentTime.year-num, currentTime.month, currentTime.day)\n\tfor job in resume[\"work\"]:\n\t\tif \"endDate\" not in j... | [
{
"docid": "6a57c759e75570e494a30824b6c5c3f0",
"score": "0.6485748",
"text": "def getHistory(num = None):\n\thistory=[]\n\tif num != None:\n\t\thistory=resume[\"work\"][:int(num)]\n\telse:\n\t\thistory=resume[\"work\"]\n\treturn jsonify(history)",
"title": ""
},
{
"docid": "0be23c49742351038... |
680bbb3f8eef67b3cf95a7ab8b726022 | method returns data on a particular row from the database | [
{
"docid": "6a7b364b630db5ea4e7a786272d9323e",
"score": "0.0",
"text": "def retrieve_one(cls, query_string):\n cls.cur.execute(query_string)\n return cls.cur.fetchone()",
"title": ""
}
] | [
{
"docid": "a67f11b8cab53f3c4a2e0c3f3678feb8",
"score": "0.73097724",
"text": "def GetItem(self, row):",
"title": ""
},
{
"docid": "a67f11b8cab53f3c4a2e0c3f3678feb8",
"score": "0.73097724",
"text": "def GetItem(self, row):",
"title": ""
},
{
"docid": "f21e043b20c4889fc58c... |
ca76e70edbf7c76a72017aa3721eb59e | Verify email reset token. Loads the user id and the requested email and simultaneously checks token age. If not too old, get user with id and set email. | [
{
"docid": "5e6d7a14706f367fa7bd5d591c364ec5",
"score": "0.67778265",
"text": "def verify_token(token):\n ts = URLSafeTimedSerializer(flask.current_app.config[\"SECRET_KEY\"])\n\n try:\n user_id, email = ts.loads(token, salt='verify-email', max_age=900)\n except SignatureExpired:\n ... | [
{
"docid": "1426832ab2106935047455b4d985ed59",
"score": "0.7034363",
"text": "def verify_reset_token(token):\r\n s = Serializer(app.config['SECRET_KEY'])\r\n try:\r\n user_id = s.loads(token)['user_id']\r\n except:\r\n return None\r\n return User.query.g... |
63786851c7e7ae73d467536316bbf110 | Renders the current game state to the screen. | [
{
"docid": "b2fb00ada0d03815848d460f37515c6e",
"score": "0.6745435",
"text": "def draw_game_state(self, win):\n state = self.get_game_state()\n output = ''\n if state == 'UNFINISHED':\n turn = self.get_turn()\n if turn == 'b':\n player = 'Blue'\n... | [
{
"docid": "22595c50b0cb7ee71aca591ea16d2c4d",
"score": "0.77084374",
"text": "def render(self):\n self.screen.fill(WHITE) # Fill background before drawing scene\n #-- Add rendering code here --#\n\n #-----------------------------#\n pg.display.flip() # Draw the screen onto... |
904764c2259b3ba951b292527cd2236d | Returns an sdf object with center in the world frame of reference | [
{
"docid": "a3e19fbe645b06d7e0165558833d8e2f",
"score": "0.0",
"text": "def transform_to_world(self):\n return self.transform(self.pose_, scale=self.scale_)",
"title": ""
}
] | [
{
"docid": "4eca910060e666cb12d863fec6f2d3cc",
"score": "0.6257024",
"text": "def center_world(self):\n return self.transform_pt_grid_to_obj(self.center_)",
"title": ""
},
{
"docid": "d705a42fbaf32da90b68f8f2ddea5cc9",
"score": "0.5883293",
"text": "def getReferencePoint(self)... |
bdc24c088c12848d5b231d245b1f0744 | finds all strings in files in folder needing translations | [
{
"docid": "13a6c79eac27cc87bbd719f558c434b7",
"score": "0.0",
"text": "def find_matches(folder, name=\"T\", extensions=[\"py\", \"js\", \"html\"]):\n matches_found = set()\n re_string_t = (\n r\"(?<=[^\\w]%s\\()(?P<name>\"\n r\"[uU]?[rR]?(?:'''(?:[^']|'{1,2}(?!'))*''... | [
{
"docid": "b74b547fe120d671ecae5ebbd8d893da",
"score": "0.7044006",
"text": "def read_languages_from_filenames(dir_to_search):\n pattern = re.compile(\"([a-z]{2}-[A-Z]{2}).txt\")\n for file in os.listdir(dir_to_search):\n find = pattern.findall(file)\n if len(find) == 1 and find[0] ... |
88343d661da9053d368c91949b04f973 | Encode the resolved_object_ids and post_publics fields from updates. ...and cap them at MAX_RESOLVED_OBJECT_IDS and MAX_POST_PUBLICS. Tries to keep the latest ones by assuming that ids are roughly monotonically increasing. | [
{
"docid": "234fd8edec74def44765105566c158e5",
"score": "0.55814445",
"text": "def _pre_put_hook(self):\n self._save_cache('resolved_object_ids')\n self._save_cache('post_publics')",
"title": ""
}
] | [
{
"docid": "4bf963b0be4c4c0c53a7b45bd19c7bd6",
"score": "0.5439419",
"text": "def fix_ids(self, objs, many, **kwargs):\n\n def _replace_id(obj):\n obj.unfreeze()\n obj.id = obj.id.replace(\"//plans/\", \"/\")\n obj.freeze()\n\n if many:\n for obj... |
990a3fbb10a1f962868fc5cf396a5296 | Translate Resource Format from gcloud values to configconnector values. | [
{
"docid": "0dbf48ed7e0eef5fb333f99a5106a04f",
"score": "0.5140977",
"text": "def _NormalizeResourceFormat(resource_format):\n if resource_format == 'terraform':\n return 'hcl'\n return resource_format",
"title": ""
}
] | [
{
"docid": "a5f9c7d808fa23ca55c7477f25ad0d10",
"score": "0.5538266",
"text": "def cr_to_config(cluster_resource: Dict[str, Any]) -> Dict[str, Any]:\n config = translate(cluster_resource[\"spec\"], dictionary=CONFIG_FIELDS)\n config[\"available_node_types\"] = get_node_types(cluster_resource)\n ... |
aa2ee5f1f74bfde6f685a36a0bd012c2 | This is a function that prints colored text to the terminal from bash evaluate statements. Usefull for debugging. This should monkeypatch the logging module. | [
{
"docid": "6bd01b8d59927d5dbaae1f4bea3109f4",
"score": "0.59094536",
"text": "def tprint(self, msg, color, indent=0):\n\n if isinstance(color, TCOLOR):\n color = color.value\n else:\n if isinstance(color, str):\n color_map = {k.name: k.value for k in T... | [
{
"docid": "225953f55941efe14144cfd23f423c83",
"score": "0.7001603",
"text": "def pp(text, value):\n print(text, color.highlight(str(value)), end='')",
"title": ""
},
{
"docid": "66c955a449659697e657d941a867d827",
"score": "0.6782162",
"text": "def pl_red(cls, text):\n cls.... |
30aa2d13687dba10443f4215686391e6 | Returns the next valid NMEA string which contains the pattern | [
{
"docid": "48c59ba11064ea30a83fab334ec66bb8",
"score": "0.6115745",
"text": "def get_nmea_pkt(self, pattern):\n pattern_bytes = bytes(pattern, 'utf-8')\n while True:\n line = self.device_tx_rx.readline()\n # logging.debug(\"L80GPS:readline returned - \"+str(line))\n ... | [
{
"docid": "f94f8c7a2891abe1746fe91e9b7ab2a9",
"score": "0.577851",
"text": "def AcceptPattern(self) -> str:",
"title": ""
},
{
"docid": "c4cefcff5d25eb9a5bcb6e0328c023ca",
"score": "0.57108873",
"text": "def onePattern(pattern):",
"title": ""
},
{
"docid": "005a64d102171... |
79bf5f0140d5fc9c5aab83a7346697ae | Creates new task and adds it to self.tasks list. | [
{
"docid": "58f29043119db2d1a970602d9f076cad",
"score": "0.7127945",
"text": "def add_task(self, name, deadline, description):\n self.tasks.append(Task(name, deadline, description))",
"title": ""
}
] | [
{
"docid": "fff715377043acf3b789f9b33833fa82",
"score": "0.78593135",
"text": "def add_task(self, task):\n self.tasks.append(task)",
"title": ""
},
{
"docid": "8cab1af511cd0fbcd1134dec97afbf29",
"score": "0.78399205",
"text": "def create_task(self, task):\n data = dict(... |
8f480a818118d060dfba28738950ec74 | Softens an image using one of several filters. | [
{
"docid": "5d3cfea736e76f8320ee6dfb7e5d4a77",
"score": "0.0",
"text": "def __blur(src, type, radius):\n if(type is BlurType.Box_Blur):\n ksize = int(2 * round(radius) + 1)\n print(src)\n print(ksize)\n return cv2.blur(src, (ksize, ksize))\n elif... | [
{
"docid": "87599eb62b460574ed33b965f0c6fdc1",
"score": "0.6943461",
"text": "def custom_filter(image):\n image = image.filter(ImageFilter.Kernel(\n size=(3, 3), kernel=(1, 0, 1, 0, 0, 0, 1, 0, 1)))\n return image",
"title": ""
},
{
"docid": "da7ead8256ef484dbcd90737a1f125bd",
... |
657f9833689eadd32ede8cb67f11aec8 | Get the timestamp for user's site enrollment (utc aware) | [
{
"docid": "7a30fdc32da68e4891f7ca477d3a5bdf",
"score": "0.7706258",
"text": "def get_user_site_enrollment_timestamp(user_uuid, site_uuid):\n user_site_metadata_response = baseline_service.get_user_site_metadata_by_user_sites(user_uuid, [site_uuid])\n if user_site_metadata_response['upsideCode'] !... | [
{
"docid": "efdc97fdc119fbe9011a06d2c4f6c7bf",
"score": "0.66244805",
"text": "def get_timestamp():\n from datetime import datetime\n from time import mktime\n\n return str(mktime(datetime.utcnow().timetuple()))[:-2]",
"title": ""
},
{
"docid": "78f0512e3b85471fedeac4dd7a1a02ad",
... |
2668d5281c958faa32046850e7d7c55c | Creates a new association between place and amenity | [
{
"docid": "8705a0904d83101d81d23cdca73d3e8e",
"score": "0.71571684",
"text": "def create_place_amenity(place_id, amenity_id):\n place = storage.get('Place', place_id)\n if place:\n amenity = storage.get('Amenity', amenity_id)\n if amenity:\n if amenity in place.amenities:... | [
{
"docid": "6c177291a926dea00d249873ca4bcba6",
"score": "0.73436147",
"text": "def create_link_place_amenity(place_id, amenity_id):\n place = models.storage.get(Place, place_id)\n if not place:\n abort(404)\n amenity = models.storage.get(Amenity, amenity_id)\n if not amenity:\n ... |
b045baebd3fdeb67f323f4540274d7b2 | Call with lfile = Path of file with list of image file names bsz = Batch size you want this to generate csz = Output images will be size csz x csz niter = Resume at niterations isval = Running on train or val (random crops and shuffling for train) | [
{
"docid": "aece2bf01fb86cd50abdd7e024ad11db",
"score": "0.5739073",
"text": "def __init__(self,lfile,bsz,csz,niter=0,isval=False):\n\n self.bsz = bsz\n self.csz = csz\n self.isrand = not isval\n\n # Setup fetch graph\n self.graph()\n\n # Load file list\n ... | [
{
"docid": "c42d77f1f24bb0462c6d7dc01a486be2",
"score": "0.67475164",
"text": "def generateBatchesForOneEpoch(self):\n\n #printMessageVerb(self.FLAGverbose, '-->> generating batches ...')\n\n\n # Load the files if needed\n if (self.currentEpoch == 0) or ((self.currentEpoch > 0) and ... |
3e91058010205107203c86ac299054e1 | Remove small Poly series coefficients. | [
{
"docid": "b3b43851ecc1c56368879bc4395bc2ab",
"score": "0.0",
"text": "def trimseq(seq):\n if len(seq) == 0 or seq[-1] != 0:\n return seq\n else:\n for i in range(len(seq) - 1, -1, -1):\n if seq[i] != 0:\n break\n return seq[:i+1]",
"title": ""
... | [
{
"docid": "8b9ee84b793ab334e701ba720865622b",
"score": "0.6996968",
"text": "def removepiston(self):\n\t\tZ = self.__coefficients__\n\t\tZ[0] = 0\n\t\treturn Z",
"title": ""
},
{
"docid": "9e68ca731d7a246e64c0cc1333dab693",
"score": "0.6676961",
"text": "def removecoma(self):\n\t\tc... |
efbb09e08a98276527ed32ce2c4be1f9 | Set wifi Infrastrucure Parameters. Have to use models for loss, latency, bw.. | [
{
"docid": "bc2380ef1fb03f6cf8cb6a6d1049ad99",
"score": "0.688999",
"text": "def setInfraParameters(self, sta, ap, distance, wlan):\n if wlan != '':\n self.parameters(sta, ap, distance, wlan)\n else:\n for wlan in range(0, sta.nWlans):\n self.parameters... | [
{
"docid": "382c49d23c62cfc09cc339a28e81a2f8",
"score": "0.7367894",
"text": "def set_wifi_parameters(self, *args, **kwargs):\n self._enable_warn()\n return",
"title": ""
},
{
"docid": "603d08cbe987a95961a828e529e32973",
"score": "0.65696967",
"text": "def apply_wireles... |
8580523f96004df044b4a84e4ff477c8 | Should be called at the beginning of each training epoch to prepare the compression method to continue training the model in the `next_epoch`. | [
{
"docid": "36ca0df77856774e73fc2d607a13f7e5",
"score": "0.0",
"text": "def epoch_step(self, next_epoch: Optional[int] = None) -> None:",
"title": ""
}
] | [
{
"docid": "db01a079c55e78fc097df6ee0d63770f",
"score": "0.68628335",
"text": "def __call__(self, epoch):\n\n if not self.weights:\n self.initialize_weights()\n \n self.train(epoch)",
"title": ""
},
{
"docid": "218f3fba5d19c7cb821fed89201ba63e",
"score": "... |
fff3bec00f214119f70bab2f9b98afd1 | Contrast stretching by break point (number provided by Rick Kohrs) | [
{
"docid": "936971accc3d801e92a7f02eea46286e",
"score": "0.0",
"text": "def breakpoint_stretch(C, breakpoint):\n lower = normalize(C, 0, 10) # Low end\n upper = normalize(C, 10, 255) # High end\n\n # Combine the two datasets\n # This works because if upper=1 and lower==.7, ... | [
{
"docid": "ca537003831770effb6236db0cfa5019",
"score": "0.63466364",
"text": "def adj_contrast(src):\n clahe = cv2.createCLAHE(clipLimit=10.0, tileGridSize=(2, 2))\n return clahe.apply(src)",
"title": ""
},
{
"docid": "b7df05c15d94e7d7f048f8f1c1ef6835",
"score": "0.6288289",
"... |
80bb542c4b50552131d7e18b214540f7 | Returns ``True`` if there were any warnings. | [
{
"docid": "c1c4bffdf737a4995d54951d0a165374",
"score": "0.8521827",
"text": "def has_warnings(self):\n return len(self._warnings) > 0",
"title": ""
}
] | [
{
"docid": "c28235583242444733b88c1d6dd7ca90",
"score": "0.8699406",
"text": "def has_warnings(self):\r\n if self.get_warnings():\r\n return True\r\n else:\r\n return False",
"title": ""
},
{
"docid": "9b6d3ab68cfedf5e1c8745e5c6147a81",
"score": "0.860... |
5955f2344749e17e519010ce65509e09 | Computes the closest distances for all the atoms | [
{
"docid": "48e9f35731dbbe50f315b81df81e0041",
"score": "0.6647483",
"text": "def close_distances(self):\n if self._pairs is None or self._distances is None:\n\n if self.structure.is_periodic:\n pcm_log.debug('Computing distances from scratch...')\n pairs_... | [
{
"docid": "34a6f16d64add96004fd651c569f8446",
"score": "0.6619735",
"text": "def get_dist(self,atom):\n d = self.r-self.r[:,atom].reshape(3,1) # subtract the location col from the matrix for each atom\n dist = np.sqrt((d*d).sum(axis=0))\n dist_copy = dist.copy()\n dist_copy[dist_co... |
4638e155b95bdf2494f442218efe45ac | Gets the parameters for the grid search testing with bagging. | [
{
"docid": "ccf7f78b93c8282a23d02b26fe7fdd86",
"score": "0.78553545",
"text": "def get_bagging_grid_parameters():\n return dict(\n n_estimators=[5, 25, 100],\n bootstrap_features=[False, True],\n bootstrap=[False, True])",
"title": ""
}
] | [
{
"docid": "b89661190b87e1ffca562123b1d18608",
"score": "0.71491104",
"text": "def get_boosting_grid_parameters():\n return dict(\n n_estimators=[5, 25, 100],\n learning_rate=[0.5, 1, 2])",
"title": ""
},
{
"docid": "3f8730fa6fbd992972292a7c161543f3",
"score": "0.6752372... |
a2a3b4e78852fea42966da891506ed81 | Parses the ranking CSVs and writes them to the database. | [
{
"docid": "f86987d541533bda041b2f677783d392",
"score": "0.0",
"text": "def fillrankingdb(path=os.path.join(SCRAPED_DATA_DIR, \"rankings\", \"bgg\")):\n django.core.management.call_command(\"fillrankingdb\", path)",
"title": ""
}
] | [
{
"docid": "b0c5db9da7df4319b33a769deacddba5",
"score": "0.63729155",
"text": "def save_ranks(self):\n ranks_out = os.path.join(self.out_dir, \"ranks.tsv\")\n self.ranks.to_csv(ranks_out, sep=\"\\t\")",
"title": ""
},
{
"docid": "bf5de976bf2b4566427a0d2912a11649",
"score": ... |
46c36c1019f8fb27aefa21a649fc8f63 | Performs a scatter of data to the different available parallelizer processes. | [
{
"docid": "3a86da7d6c1bf390c35945bfb4e57717",
"score": "0.63945365",
"text": "def scatter(self, data, **kwargs):\n\n if self.contract is not None:\n self.contract.handle_call(self, \"scatter\")\n if self.on_main:\n locs = list(self.comm.locations) # gotta be safe\n ... | [
{
"docid": "6c8c17da0c38df782cee0143cc7a70a4",
"score": "0.7503602",
"text": "def scatter(self, data, **kwargs):\n raise NotImplementedError(\"Parallelizer is an abstract base class\")",
"title": ""
},
{
"docid": "1dfb67fb390b7da012f3d07ed338dee0",
"score": "0.6475183",
"text"... |
b863464a6d76e353b40be6333e3a7837 | Returns a string of text in a filename format | [
{
"docid": "0cfbf84790b3da0475cef545c5bfff4b",
"score": "0.7140004",
"text": "def FileNameFormatter(strText):\n import string\n\n # Strip text of punctuation\n for c in string.punctuation:\n strText = strText.replace(c, \"\")\n # Strip WhiteSpaces from FileName\n if \" \" in strTex... | [
{
"docid": "9654ec3c00778fe5a356bffd25ba6a86",
"score": "0.7665484",
"text": "def get_file(self, text):\n\n\t\treturn text.strip().replace('_', '/')",
"title": ""
},
{
"docid": "b3c3595ed9340ebfde71fc54b3d4e7f2",
"score": "0.7471361",
"text": "def filename():\n return ''",
"ti... |
7a67b4d613ccae500306736feb8cf311 | Performs a batch normalization using a standard set of parameters. | [
{
"docid": "d222ee00d2451852c5d10f9346db41f4",
"score": "0.7165613",
"text": "def batch_norm(inputs, training, data_format):\n # We set fused=True for a significant performance boost. See\n # https://www.tensorflow.org/performance/performance_guide#common_fused_ops\n return tf.layers.batch_normalizat... | [
{
"docid": "583df9d602bfa25f63378da156b52475",
"score": "0.7308336",
"text": "def normalize_batch(x: torch.Tensor) -> torch.Tensor:\n f = Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n\n for b in range(x.shape[0]):\n f(x[b])\n\n return x",
"title": ""
},
{
... |
184ed9fcd6e5ef4e35599ae0f89801a1 | Split a list into a list containing multiple lists of size | [
{
"docid": "0c68170fe1f6aa41880bd752a7ad06b8",
"score": "0.0",
"text": "def thread_group(total_items, size):\n per_thread = round(len(total_items) / int(size))\n groups = []\n group = []\n\n for item in total_items:\n group.append(item)\n if len(group) >= per_thread:\n ... | [
{
"docid": "3ba0007ac8998de32b42301187625b06",
"score": "0.7920258",
"text": "def get_chunks(input_list, num_chunks):\n\n chunked = np.array_split(input_list, num_chunks)\n return [x.tolist() for x in chunked]",
"title": ""
},
{
"docid": "88c3da6b0e968a4c0f0d53cd0f8dedf7",
"score":... |
acb254396889db07f767e23ddd7235d3 | Get LED strip brightness | [
{
"docid": "db77cea0e3afdc2fa5b26d136885a699",
"score": "0.68747914",
"text": "def getBrightness(self) -> int:\n return self._brightness",
"title": ""
}
] | [
{
"docid": "6d2a1e1f20aa611fb3ae4a3d6f103186",
"score": "0.7632183",
"text": "def brightness(self) -> int:\n pass",
"title": ""
},
{
"docid": "944a8dc948b504cffde835cb0abc5795",
"score": "0.7624959",
"text": "def brightness(self):\n return libratbag.ratbag_led_get_brigh... |
47e732ddee436c9c5b80be0e25da1794 | Parse the next inline element in subject, advancing subject position and adding the result to 'inlines'. | [
{
"docid": "719ebba8497de2ee4cbbf01758c86eaa",
"score": "0.69148296",
"text": "def parse_inline(self, inlines):\n c = self.peek()\n# print 'C', repr(c)\n# print 'POS', self.pos\n# print 'SUB', repr(self.subject)\n# pprint([i.dump() for i in inlines])\n r = N... | [
{
"docid": "3abf27bb73f04c924719f7f6a70c8946",
"score": "0.57719964",
"text": "def inlines(self):\n for inline in range(self.startInline, self.endInline+1, self.stepInline):\n yield inline",
"title": ""
},
{
"docid": "6621a5f0a1ef41c160ed721707835a08",
"score": "0.54631... |
7d2ae14e0f07f38686ce1cc6442e1b10 | Helper function to build Sprint name for JIRA. | [
{
"docid": "592bbad6008c85f9b56ba95d57f94b38",
"score": "0.72261506",
"text": "def build_sprint(operational_year, operational_quarter, sprint_length, sprint_index):\n return 'Y%s-Q%s-L%s-S%s' % (\n operational_year, operational_quarter, sprint_length, sprint_index\n )",
"title": ""
}
... | [
{
"docid": "9c995330fc18315b488d0d98da722891",
"score": "0.6251241",
"text": "def get_trial_name_capture1(user, trial,capture):\n return 'Suturing_%s%03d%s' % (user, trial,capture)",
"title": ""
},
{
"docid": "b5560e31e7d53022dc1693d599b9e19c",
"score": "0.6211164",
"text": "def m... |
4357cc9622aa6e03a139d2d3ea2b28be | Create a string to be written to a Colvars file. | [
{
"docid": "2034dd75dedcb8a203a547e72c16281c",
"score": "0.0",
"text": "def _create(star, dna, lower, upper, k, steps, start, stop):\n group1_end = star\n group2_start = star+1\n group2_end = star+dna\n colvar = \"colvar {{\\n name dist\\n distance {{\\n group1 {{atomNumbersRange 1-{}}}... | [
{
"docid": "84153e24371b21890b7573ad151587da",
"score": "0.6302888",
"text": "def make_namd_colvar_string(self):\n serial_group1 = [str(index+1) for index in self.group1]\n serial_group2 = [str(index+1) for index in self.group2]\n serial_group1_str = \" \".join(serial_group1)\n ... |
0d28e8ef4d44c78a166c75c014e756ac | Exports a batch of telemetry data. | [
{
"docid": "083b6055270d44fb835e141133c0d353",
"score": "0.5884133",
"text": "def export(\n self, metric_records: Sequence[MetricRecord]\n ) -> \"MetricsExportResult\":",
"title": ""
}
] | [
{
"docid": "a94acecd27598216250fe5ba9c86dc4b",
"score": "0.62449056",
"text": "def export():\n for agent in Performance.agentList:\n agent.performance.__exportAgentPerformance__()",
"title": ""
},
{
"docid": "fbac169c2b86f9fe4415042d706e091a",
"score": "0.6139936",
... |
dcd5cfeec1176c6ac0717df07bad0e9a | Sends the help message | [
{
"docid": "6a6dad1f3b2ffea5792f1b3258f003ef",
"score": "0.0",
"text": "async def help(self, ctx):\n\n await ctx.send('Type `>run` and python script to run python')",
"title": ""
}
] | [
{
"docid": "dc0ada3b234879429e494800a76a63e9",
"score": "0.8490778",
"text": "def do_help(self, *args):\n self.stdout.write(HELP_MESSAGE)",
"title": ""
},
{
"docid": "d47fb2e6b3684f66a3ede28374e5bee6",
"score": "0.81821424",
"text": "def do_help(self):\n self.send_bot_m... |
835c11f46f8cfb87636628b33f3e0e4b | Create leaderboard view for Round2 | [
{
"docid": "2fe3cc33225358d9525373963b157990",
"score": "0.56610113",
"text": "def rd2leaderboard(request):\n\n #Add views\n playing_players = Rd2SlotModel.objects.filter(player_name__isnull=False)\n\n #Add context\n context = {\n 'playing_players': playing_players,\n }\n\n ... | [
{
"docid": "437d7c5565d4948aa3c19c5e239cc8fe",
"score": "0.7503058",
"text": "def leaderboard(self):\n click.echo(\"\\n----Leaderboard----\")\n players = OrderedDict(\n sorted(self.players.items(), key=lambda x: getitem(x[1], \"round\"))\n )\n columns = [\"Rank\", ... |
ce428872890f3297fc66b259f0a143e2 | Gets the bullets sprite group. | [
{
"docid": "02462abbbe3a9e237407eea959f7c752",
"score": "0.6066278",
"text": "def get_bullets (self):\n\n return self.bullets",
"title": ""
}
] | [
{
"docid": "15d234b9db0d0fc7dd1acbff40c75c5b",
"score": "0.6432783",
"text": "def sprites(self):\n return self._group.sprites()",
"title": ""
},
{
"docid": "de6a149d4ec31f0f540233fe9e875647",
"score": "0.6042333",
"text": "def loadBullet(self):\n bullet = Projectile(sel... |
9b1add6e10b15c71fe389d9b7764923e | Whether node to node encryption is enabled. | [
{
"docid": "8b7f9b5071a1577ec845863ad1fdb178",
"score": "0.57095563",
"text": "def enabled(self) -> bool:\n return pulumi.get(self, \"enabled\")",
"title": ""
}
] | [
{
"docid": "3fbe407ec13d3ca2f66c52dec688511e",
"score": "0.72343796",
"text": "def encryption_at_host_enabled(self) -> pulumi.Output[Optional[bool]]:\n return pulumi.get(self, \"encryption_at_host_enabled\")",
"title": ""
},
{
"docid": "87e151fc000a0308a51f52aafeee4a4e",
"score": ... |
b2e408f4c573f516b292aaff446c06b2 | r""" Return a Steiner Quadruple System on `n` points. | [
{
"docid": "d1bc147bc816209e50c649bbb8517d26",
"score": "0.7664719",
"text": "def steiner_quadruple_system(n, check = False):\n n = int(n)\n if not ((n%6) in [2, 4]):\n raise ValueError(\"n mod 6 must be equal to 2 or 4\")\n elif n == 4:\n sqs = IncidenceStructure(4, [[0,1,2,3]], ... | [
{
"docid": "cf3f839797ef63cebb2f18a384cec215",
"score": "0.60831946",
"text": "def chebpts(n):\r\n\r\n # Special case (no points)\r\n if n == 0:\r\n x = []\r\n w = [] \r\n v = []\r\n t = []\r\n # Special case (single point)\r\n elif n == 1:\r\n x = 0 \r\n ... |
3a3a2e849b00f11158ef1aeb7e55f162 | See the real Accessor for a description. | [
{
"docid": "db55e38a64c281fd6e8ab26938b883f2",
"score": "0.0",
"text": "def fetch_points(self, metric_name, time_start, time_end, step,\n aggregator_func=None, _fake_query_results=None):\n if not _fake_query_results:\n points = self._metric_to_points[metric_name]\n ... | [
{
"docid": "9b1f057f9b6b248713bf759651dc2c80",
"score": "0.7138444",
"text": "def get(self, ):\n\t\tpass",
"title": ""
},
{
"docid": "4560c322427918f793eb8b1980ad174e",
"score": "0.71203256",
"text": "def _get(self):\n raise NotImplementedError",
"title": ""
},
{
"... |
633bb61656b4648540046f3aadfbf43e | main function for lcoal usage | [
{
"docid": "a8ec5a21efbccc76636cc0ff1be8f8cc",
"score": "0.58221775",
"text": "def main():\r\n test()",
"title": ""
}
] | [
{
"docid": "08aa0c5cc07c5efe590ba89320b45dbc",
"score": "0.69941837",
"text": "def main():",
"title": ""
},
{
"docid": "08aa0c5cc07c5efe590ba89320b45dbc",
"score": "0.69941837",
"text": "def main():",
"title": ""
},
{
"docid": "08aa0c5cc07c5efe590ba89320b45dbc",
"scor... |
f12dbbd813dce1dfccea81d087209d5a | Create a simple user that we link all the answers to. | [
{
"docid": "f841e3174f163c6984457f84a2649161",
"score": "0.0",
"text": "def begin(request):\n request.session.flush() # \"Logout\" from any previous session\n\n if request.method == \"POST\":\n new_name = request.POST[\"name\"]\n new_motto = request.POST[\"motto\"]\n # Try th... | [
{
"docid": "c40661dc617572feba289b687098d62c",
"score": "0.7658639",
"text": "def create_user(self, user_id: str, user_name: str) -> None:",
"title": ""
},
{
"docid": "32f5b47e07cd7cd2b99bba64fa162310",
"score": "0.7454858",
"text": "def createUser():\n user_data = fb.get_initial_... |
96e071f315bfe84fab392617e3d43f4e | Sets the signup_url of this GoogleEnterprise. | [
{
"docid": "c6aaf918a064923c95e551ecbc6b8ad3",
"score": "0.782311",
"text": "def signup_url(self, signup_url):\n if signup_url is not None and len(signup_url) < 1:\n raise ValueError(\"Invalid value for `signup_url`, length must be greater than or equal to `1`\")\n\n self._signu... | [
{
"docid": "78bdf485adf3c2eb3ffcc3a06ee8dbac",
"score": "0.6903089",
"text": "def signup_url(self):\n return self._signup_url",
"title": ""
},
{
"docid": "c927cb649a708861b0d0105a9309bbd9",
"score": "0.57198805",
"text": "def ___set_url(self, url):\n self.__set_url(url)... |
850b14adc74914000ecee267cb5a171e | Replaces 'pattern' in 'string' with 'sub' if 'pattern' starts 'string'. | [
{
"docid": "ebf3a6bfd34aa2c3d8d9c5914ab345ea",
"score": "0.77272403",
"text": "def lreplace(pattern, sub, string):\n return re.sub('^%s' % pattern, sub, string)",
"title": ""
}
] | [
{
"docid": "e224a45e914a1459828b24848b832fbe",
"score": "0.65532935",
"text": "def sub(self, pattern: str, repl: Union[str, callable], string: str, strict: bool = True, case_sensitive: bool = False) -> str:\n if case_sensitive:\n result = re.sub(pattern, repl, string)\n else:\n ... |
6b82f7758ded5229235eb1ea75beaed1 | Show specific post comment | [
{
"docid": "e37729c20a16f0bc02a8c8d3290c90c5",
"score": "0.59195065",
"text": "def comment(post_id, comment_id):\n check_comment(post_id, comment_id, False)\n\n db = get_db()\n comment_sql = get_comment_of_post(db, post_id, comment_id)\n\n comment = dict(comment_sql)\n return jsonify(comm... | [
{
"docid": "90b5fce23163cc1947185be27a583845",
"score": "0.7372231",
"text": "def post_detail(request, id):\n post = Post.objects.get(id=id)\n return render(request, 'comment/post_detail.html', {'post': post})",
"title": ""
},
{
"docid": "c7bd1ff09b7932f489e77bb54fe2afb7",
"score":... |
d892852aa3e7a6ea40c368be4d467adc | Convert value to boolean. | [
{
"docid": "62d72b52a5d57f1f68f69a09dd84d2d0",
"score": "0.80972165",
"text": "def toBool(self, val: Any) -> bool:\n if type(val) == bool:\n return val\n elif type(val) == int:\n return val != 0\n elif type(val) == str:\n v = val.lower()\n ... | [
{
"docid": "5d4bd8517d78334032a46f042455bfcc",
"score": "0.863882",
"text": "def to_boolean(value: Any) -> bool:\n return BooleanConverter.to_boolean_with_default(value, False)",
"title": ""
},
{
"docid": "fee659ff6685b59b558ebd84f3dfcd34",
"score": "0.85566324",
"text": "def ... |
5f2376e139bf9216035dd5e8721f8c77 | Get a 2d numpy array of obstacles in the form [[x, y], [x, y], ...] | [
{
"docid": "74d1869550c2ceeb24977a200a7bdbae",
"score": "0.7013155",
"text": "def get_obstacles(self):\n return np.argwhere(self.obstacles == True) * self.config.grid_reso",
"title": ""
}
] | [
{
"docid": "3e0ccacd4db9e4bc1fcb1726c1a0fa96",
"score": "0.7382825",
"text": "def obstacles(self):\n return list(self._obstacles)",
"title": ""
},
{
"docid": "6586c95dc5ce60c31e82d33802373a2e",
"score": "0.7301217",
"text": "def get_obstacles_positions(obstacles: []) -> List[P... |
d9b703dfa0713d148772683e9d85d349 | Reduce the items in this list to identifiers that can be used to recreate them from scratch. This adds each item to the cache too. | [
{
"docid": "b0417d0cd78b920baa1079318656fc4c",
"score": "0.69286984",
"text": "def _pack_items(self):\n identifiers = tuple(self.identify_items(self))\n cache_keys = self.make_cache_keys(identifiers)\n cache_items = dict(izip(cache_keys, self))\n self.cache.set_many(cache_ite... | [
{
"docid": "04f3496398ff04367f08c593ebc8f7c4",
"score": "0.71066976",
"text": "def _unpack_items(self):\n\n # Prevent the unpack operation from occurring more than once.\n if hasattr(self, '_unpack'):\n delattr(self, '_unpack')\n else:\n return\n\n # The... |
95246c749a7299f7107f201320e37e0a | Updates the World Object Grid | [
{
"docid": "e215fbe7a36102b1ca32dcd123523225",
"score": "0.7229946",
"text": "def update_world_object(self, Object, x, y):\n self.WOG[x][y] = Object",
"title": ""
}
] | [
{
"docid": "ccb16c16812bbd50b00fe75b0f0a58a2",
"score": "0.6663007",
"text": "def update(self, player, obj_list):\n for obj in obj_list:\n obj.update(obj_list)\n player.update(self.map.tile_boxes)",
"title": ""
},
{
"docid": "4251b18b88419fdcb5c977011fe47ba1",
"s... |
fe15a1a597b13a43456fd8bdf2a252fd | rejects a nonnumeric input of "foo" | [
{
"docid": "1232bc5326ddca1da44076edffbc92a9",
"score": "0.0",
"text": "def test_reject_foo():\n check50.run(\"python3 cash.py\").stdin(\"foo\").reject()",
"title": ""
}
] | [
{
"docid": "eb8de4b095347f3422d0d8ab42c05c67",
"score": "0.6866605",
"text": "def check(param):\n try:\n param = float(param)\n\n except ValueError:\n print(\"Incorrect input \\\"%s\\\". Must be number.\" % param)",
"title": ""
},
{
"docid": "a6ba2276e2f4248e8994b8cae14a2... |
684d4bb24cc2591d34e2cb4b07a3c8d5 | where should we go next tick? | [
{
"docid": "50f191c660eb379fbac6e791db39402f",
"score": "0.0",
"text": "def nextStep(self):\n options = self.surroundingValues()\n\n a = [self.expandTile(tile, tile.explored) for tile in options]\n\n m = min(a)\n maxIndexes = [i for i, j in enumerate(a) if j == m]\n\n\tprint ... | [
{
"docid": "47e4d0cbcb6e027f154a33d964fd0780",
"score": "0.76231015",
"text": "def tick(self):",
"title": ""
},
{
"docid": "47e4d0cbcb6e027f154a33d964fd0780",
"score": "0.76231015",
"text": "def tick(self):",
"title": ""
},
{
"docid": "c6895c04d064960b1ae0bf4a4da83d20",
... |
ba9bf18738bbfb8d5804a416357f11d0 | Read in a schema definition for our part of the config and hook it | [
{
"docid": "4a9c2e5bea03e0bb0804ad72647ec2bf",
"score": "0.0",
"text": "def extend_schema(self, parent_schema):\n schema_path = os.path.join(self.dogen.pwd, \"schema\", \"cct_schema.yaml\")\n schema = {}\n with open(schema_path, 'r') as fh:\n schema = yaml.safe_load(fh)\n... | [
{
"docid": "20a2e7a8484156b260fdb229de1e1660",
"score": "0.7257588",
"text": "def load_schema(self):\n raise NotImplementedError",
"title": ""
},
{
"docid": "a12bfee9e3094a2afc066b5de193e7d9",
"score": "0.72208834",
"text": "def input_config_schema(self) -> IDefinitionConfigSc... |
ba2f90b28966006b3764a6a8cadb2c84 | Returns the importance of term in document id. If the term isn't in the document, then return 0. | [
{
"docid": "40550b3d44025bcbb8fdf4c3d7ea859c",
"score": "0.718705",
"text": "def imp(term,id):\r\n if id in postings[term]:\r\n return postings[term][id]*inverse_document_frequency(term)\r\n else:\r\n return 0.0",
"title": ""
}
] | [
{
"docid": "1ab6cc16ab1cfd758823ca6ce6adb0c8",
"score": "0.73194516",
"text": "def get_tfidf_scores(self, term, document):\n if term in self.tf[document]:\n return self.tf[document][term] * self.idf[term]\n else:\n return 0",
"title": ""
},
{
"docid": "a53... |
ae240ac6cc2863ef66089a55dc3eb4ed | This method is queue scheduler and executer \n | [
{
"docid": "b9240612058aa55653c74834c388d516",
"score": "0.0",
"text": "def lcfs_alg(self, process_waiting):\n cpu_clock = 0\n local_finished_queue = []\n while len(process_waiting) is not 0:\n proc = process_waiting[-1]\n cpu_clock += 1\n\n if proc.... | [
{
"docid": "ee659d2f4dda0e351f0bd89aaa2c9951",
"score": "0.6921316",
"text": "def processQueue(self):",
"title": ""
},
{
"docid": "09982e5cbe4c7df30fe4ae28f60d7e1f",
"score": "0.6735559",
"text": "def scheduler(self):\n j = self.updater.job_queue\n print('getting daily ... |
7cf6d7a7b128f652585284b8eb15cfc0 | Emits a 'cld' instruction. | [
{
"docid": "e034cd2a187354cc37d2628c032dc82a",
"score": "0.5156586",
"text": "def cld(self) -> None:\n self.buf[self.pos] = 252\n self.pos += 1",
"title": ""
}
] | [
{
"docid": "10f6e1d757e33098a497f06762b836a0",
"score": "0.6387597",
"text": "def cl(self, c):\n self.force_menu('oper')\n self.send('cl ' + str(c))\n return output(self.proc.before)",
"title": ""
},
{
"docid": "93fe9d0119da5f74106fdbe79ae1cdc7",
"score": "0.5471392"... |